core: remove old ndarray code and NDArray proxy

Nothing depends on the old ndarray implementation now.

.pre-commit-config.yaml

@@ -1,7 +1,7 @@
 # See https://pre-commit.com for more information
 # See https://pre-commit.com/hooks.html for more hooks
 
-default_stages: [pre-commit]
+default_stages: [commit]
 
 repos:
   - repo: local

Cargo.lock

@@ -26,9 +26,9 @@ dependencies = [
 
 [[package]]
 name = "anstream"
-version = "0.6.18"
+version = "0.6.15"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8acc5369981196006228e28809f761875c0327210a891e941f4c683b3a99529b"
+checksum = "64e15c1ab1f89faffbf04a634d5e1962e9074f2741eef6d97f3c4e322426d526"
 dependencies = [
  "anstyle",
  "anstyle-parse",
@@ -41,36 +41,36 @@ dependencies = [
 
 [[package]]
 name = "anstyle"
-version = "1.0.10"
+version = "1.0.8"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "55cc3b69f167a1ef2e161439aa98aed94e6028e5f9a59be9a6ffb47aef1651f9"
+checksum = "1bec1de6f59aedf83baf9ff929c98f2ad654b97c9510f4e70cf6f661d49fd5b1"
 
 [[package]]
 name = "anstyle-parse"
-version = "0.2.6"
+version = "0.2.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3b2d16507662817a6a20a9ea92df6652ee4f94f914589377d69f3b21bc5798a9"
+checksum = "eb47de1e80c2b463c735db5b217a0ddc39d612e7ac9e2e96a5aed1f57616c1cb"
 dependencies = [
  "utf8parse",
 ]
 
 [[package]]
 name = "anstyle-query"
-version = "1.1.2"
+version = "1.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "79947af37f4177cfead1110013d678905c37501914fba0efea834c3fe9a8d60c"
+checksum = "6d36fc52c7f6c869915e99412912f22093507da8d9e942ceaf66fe4b7c14422a"
 dependencies = [
- "windows-sys 0.59.0",
+ "windows-sys 0.52.0",
 ]
 
 [[package]]
 name = "anstyle-wincon"
-version = "3.0.6"
+version = "3.0.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2109dbce0e72be3ec00bed26e6a7479ca384ad226efdd66db8fa2e3a38c83125"
+checksum = "5bf74e1b6e971609db8ca7a9ce79fd5768ab6ae46441c572e46cf596f59e57f8"
 dependencies = [
  "anstyle",
- "windows-sys 0.59.0",
+ "windows-sys 0.52.0",
 ]
 
 [[package]]
@@ -126,9 +126,9 @@ checksum = "1fd0f2584146f6f2ef48085050886acf353beff7305ebd1ae69500e27c67f64b"
 
 [[package]]
 name = "cc"
-version = "1.2.7"
+version = "1.1.30"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a012a0df96dd6d06ba9a1b29d6402d1a5d77c6befd2566afdc26e10603dc93d7"
+checksum = "b16803a61b81d9eabb7eae2588776c4c1e584b738ede45fdbb4c972cec1e9945"
 dependencies = [
  "shlex",
 ]
@@ -141,9 +141,9 @@ checksum = "baf1de4339761588bc0619e3cbc0120ee582ebb74b53b4efbf79117bd2da40fd"
 
 [[package]]
 name = "clap"
-version = "4.5.23"
+version = "4.5.20"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3135e7ec2ef7b10c6ed8950f0f792ed96ee093fa088608f1c76e569722700c84"
+checksum = "b97f376d85a664d5837dbae44bf546e6477a679ff6610010f17276f686d867e8"
 dependencies = [
  "clap_builder",
  "clap_derive",
@@ -151,9 +151,9 @@ dependencies = [
 
 [[package]]
 name = "clap_builder"
-version = "4.5.23"
+version = "4.5.20"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "30582fc632330df2bd26877bde0c1f4470d57c582bbc070376afcd04d8cb4838"
+checksum = "19bc80abd44e4bed93ca373a0704ccbd1b710dc5749406201bb018272808dc54"
 dependencies = [
  "anstream",
  "anstyle",
@@ -170,38 +170,38 @@ dependencies = [
  "heck 0.5.0",
  "proc-macro2",
  "quote",
- "syn 2.0.94",
+ "syn 2.0.79",
 ]
 
 [[package]]
 name = "clap_lex"
-version = "0.7.4"
+version = "0.7.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f46ad14479a25103f283c0f10005961cf086d8dc42205bb44c46ac563475dca6"
+checksum = "1462739cb27611015575c0c11df5df7601141071f07518d56fcc1be504cbec97"
 
 [[package]]
 name = "colorchoice"
-version = "1.0.3"
+version = "1.0.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5b63caa9aa9397e2d9480a9b13673856c78d8ac123288526c37d7839f2a86990"
+checksum = "d3fd119d74b830634cea2a0f58bbd0d54540518a14397557951e79340abc28c0"
 
 [[package]]
 name = "console"
-version = "0.15.10"
+version = "0.15.8"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ea3c6ecd8059b57859df5c69830340ed3c41d30e3da0c1cbed90a96ac853041b"
+checksum = "0e1f83fc076bd6dd27517eacdf25fef6c4dfe5f1d7448bafaaf3a26f13b5e4eb"
 dependencies = [
  "encode_unicode",
+ "lazy_static",
  "libc",
- "once_cell",
+ "windows-sys 0.52.0",
- "windows-sys 0.59.0",
 ]
 
 [[package]]
 name = "cpufeatures"
-version = "0.2.16"
+version = "0.2.14"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "16b80225097f2e5ae4e7179dd2266824648f3e2f49d9134d584b76389d31c4c3"
+checksum = "608697df725056feaccfa42cffdaeeec3fccc4ffc38358ecd19b243e716a78e0"
 dependencies = [
  "libc",
 ]
@@ -221,18 +221,18 @@ dependencies = [
 
 [[package]]
 name = "crossbeam-channel"
-version = "0.5.14"
+version = "0.5.13"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "06ba6d68e24814cb8de6bb986db8222d3a027d15872cabc0d18817bc3c0e4471"
+checksum = "33480d6946193aa8033910124896ca395333cae7e2d1113d1fef6c3272217df2"
 dependencies = [
  "crossbeam-utils",
 ]
 
 [[package]]
 name = "crossbeam-deque"
-version = "0.8.6"
+version = "0.8.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9dd111b7b7f7d55b72c0a6ae361660ee5853c9af73f70c3c2ef6858b950e2e51"
+checksum = "613f8cc01fe9cf1a3eb3d7f488fd2fa8388403e97039e2f73692932e291a770d"
 dependencies = [
  "crossbeam-epoch",
  "crossbeam-utils",
@@ -249,18 +249,18 @@ dependencies = [
 
 [[package]]
 name = "crossbeam-queue"
-version = "0.3.12"
+version = "0.3.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0f58bbc28f91df819d0aa2a2c00cd19754769c2fad90579b3592b1c9ba7a3115"
+checksum = "df0346b5d5e76ac2fe4e327c5fd1118d6be7c51dfb18f9b7922923f287471e35"
 dependencies = [
  "crossbeam-utils",
 ]
 
 [[package]]
 name = "crossbeam-utils"
-version = "0.8.21"
+version = "0.8.20"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d0a5c400df2834b80a4c3327b3aad3a4c4cd4de0629063962b03235697506a28"
+checksum = "22ec99545bb0ed0ea7bb9b8e1e9122ea386ff8a48c0922e43f36d45ab09e0e80"
 
 [[package]]
 name = "crypto-common"
@@ -282,12 +282,6 @@ dependencies = [
  "crypto-common",
 ]
 
-[[package]]
-name = "dissimilar"
-version = "1.0.9"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "59f8e79d1fbf76bdfbde321e902714bf6c49df88a7dda6fc682fc2979226962d"
-
 [[package]]
 name = "either"
 version = "1.13.0"
@@ -305,9 +299,9 @@ dependencies = [
 
 [[package]]
 name = "encode_unicode"
-version = "1.0.0"
+version = "0.3.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "34aa73646ffb006b8f5147f3dc182bd4bcb190227ce861fc4a4844bf8e3cb2c0"
+checksum = "a357d28ed41a50f9c765dbfe56cbc04a64e53e5fc58ba79fbc34c10ef3df831f"
 
 [[package]]
 name = "equivalent"
@@ -317,19 +311,19 @@ checksum = "5443807d6dff69373d433ab9ef5378ad8df50ca6298caf15de6e52e24aaf54d5"
 
 [[package]]
 name = "errno"
-version = "0.3.10"
+version = "0.3.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "33d852cb9b869c2a9b3df2f71a3074817f01e1844f839a144f5fcef059a4eb5d"
+checksum = "534c5cf6194dfab3db3242765c03bbe257cf92f22b38f6bc0c58d59108a820ba"
 dependencies = [
  "libc",
- "windows-sys 0.59.0",
+ "windows-sys 0.52.0",
 ]
 
 [[package]]
 name = "fastrand"
-version = "2.3.0"
+version = "2.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "37909eebbb50d72f9059c3b6d82c0463f2ff062c9e95845c43a6c9c0355411be"
+checksum = "e8c02a5121d4ea3eb16a80748c74f5549a5665e4c21333c6098f283870fbdea6"
 
 [[package]]
 name = "fixedbitset"
@@ -376,12 +370,6 @@ dependencies = [
  "wasi",
 ]
 
-[[package]]
-name = "glob"
-version = "0.3.2"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a8d1add55171497b4705a648c6b583acafb01d58050a51727785f0b2c8e0a2b2"
-
 [[package]]
 name = "hashbrown"
 version = "0.12.3"
@@ -399,9 +387,9 @@ dependencies = [
 
 [[package]]
 name = "hashbrown"
-version = "0.15.2"
+version = "0.15.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "bf151400ff0baff5465007dd2f3e717f3fe502074ca563069ce3a6629d07b289"
+checksum = "1e087f84d4f86bf4b218b927129862374b72199ae7d8657835f1e89000eea4fb"
 
 [[package]]
 name = "heck"
@@ -417,11 +405,11 @@ checksum = "2304e00983f87ffb38b55b444b5e3b60a884b5d30c0fca7d82fe33449bbe55ea"
 
 [[package]]
 name = "home"
-version = "0.5.11"
+version = "0.5.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "589533453244b0995c858700322199b2becb13b627df2851f64a2775d024abcf"
+checksum = "e3d1354bf6b7235cb4a0576c2619fd4ed18183f689b12b006a0ee7329eeff9a5"
 dependencies = [
- "windows-sys 0.59.0",
+ "windows-sys 0.52.0",
 ]
 
 [[package]]
@@ -436,12 +424,12 @@ dependencies = [
 
 [[package]]
 name = "indexmap"
-version = "2.7.0"
+version = "2.6.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "62f822373a4fe84d4bb149bf54e584a7f4abec90e072ed49cda0edea5b95471f"
+checksum = "707907fe3c25f5424cce2cb7e1cbcafee6bdbe735ca90ef77c29e84591e5b9da"
 dependencies = [
  "equivalent",
- "hashbrown 0.15.2",
+ "hashbrown 0.15.0",
 ]
 
 [[package]]
@@ -472,7 +460,7 @@ checksum = "9dd28cfd4cfba665d47d31c08a6ba637eed16770abca2eccbbc3ca831fef1e44"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.94",
+ "syn 2.0.79",
 ]
 
 [[package]]
@@ -506,9 +494,9 @@ dependencies = [
 
 [[package]]
 name = "itoa"
-version = "1.0.14"
+version = "1.0.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d75a2a4b1b190afb6f5425f10f6a8f959d2ea0b9c2b1d79553551850539e4674"
+checksum = "49f1f14873335454500d59611f1cf4a4b0f786f9ac11f4312a78e4cf2566695b"
 
 [[package]]
 name = "keccak"
@@ -559,15 +547,15 @@ checksum = "bbd2bcb4c963f2ddae06a2efc7e9f3591312473c50c6685e1f298068316e66fe"
 
 [[package]]
 name = "libc"
-version = "0.2.169"
+version = "0.2.161"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b5aba8db14291edd000dfcc4d620c7ebfb122c613afb886ca8803fa4e128a20a"
+checksum = "8e9489c2807c139ffd9c1794f4af0ebe86a828db53ecdc7fea2111d0fed085d1"
 
 [[package]]
 name = "libloading"
-version = "0.8.6"
+version = "0.8.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "fc2f4eb4bc735547cfed7c0a4922cbd04a4655978c09b54f1f7b228750664c34"
+checksum = "4979f22fdb869068da03c9f7528f8297c6fd2606bc3a4affe42e6a823fdb8da4"
 dependencies = [
  "cfg-if",
  "windows-targets",
@@ -646,6 +634,7 @@ name = "nac3ast"
 version = "0.1.0"
 dependencies = [
  "fxhash",
+ "lazy_static",
  "parking_lot",
  "string-interner",
 ]
@@ -655,12 +644,11 @@ name = "nac3core"
 version = "0.1.0"
 dependencies = [
  "crossbeam",
- "indexmap 2.7.0",
+ "indexmap 2.6.0",
  "indoc",
  "inkwell",
  "insta",
  "itertools",
- "nac3core_derive",
  "nac3parser",
  "parking_lot",
  "rayon",
@@ -670,18 +658,6 @@ dependencies = [
  "test-case",
 ]
 
-[[package]]
-name = "nac3core_derive"
-version = "0.1.0"
-dependencies = [
- "nac3core",
- "proc-macro-error",
- "proc-macro2",
- "quote",
- "syn 2.0.94",
- "trybuild",
-]
-
 [[package]]
 name = "nac3ld"
 version = "0.1.0"
@@ -756,7 +732,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b4c5cc86750666a3ed20bdaf5ca2a0344f9c67674cae0515bec2da16fbaa47db"
 dependencies = [
  "fixedbitset",
- "indexmap 2.7.0",
+ "indexmap 2.6.0",
 ]
 
 [[package]]
@@ -799,7 +775,7 @@ dependencies = [
  "phf_shared 0.11.2",
  "proc-macro2",
  "quote",
- "syn 2.0.94",
+ "syn 2.0.79",
 ]
 
 [[package]]
@@ -828,9 +804,9 @@ checksum = "5be167a7af36ee22fe3115051bc51f6e6c7054c9348e28deb4f49bd6f705a315"
 
 [[package]]
 name = "portable-atomic"
-version = "1.10.0"
+version = "1.9.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "280dc24453071f1b63954171985a0b0d30058d287960968b9b2aca264c8d4ee6"
+checksum = "cc9c68a3f6da06753e9335d63e27f6b9754dd1920d941135b7ea8224f141adb2"
 
 [[package]]
 name = "ppv-lite86"
@@ -847,35 +823,11 @@ version = "0.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "925383efa346730478fb4838dbe9137d2a47675ad789c546d150a6e1dd4ab31c"
 
-[[package]]
-name = "proc-macro-error"
-version = "1.0.4"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "da25490ff9892aab3fcf7c36f08cfb902dd3e71ca0f9f9517bea02a73a5ce38c"
-dependencies = [
- "proc-macro-error-attr",
- "proc-macro2",
- "quote",
- "syn 1.0.109",
- "version_check",
-]
-
-[[package]]
-name = "proc-macro-error-attr"
-version = "1.0.4"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a1be40180e52ecc98ad80b184934baf3d0d29f979574e439af5a55274b35f869"
-dependencies = [
- "proc-macro2",
- "quote",
- "version_check",
-]
-
 [[package]]
 name = "proc-macro2"
-version = "1.0.92"
+version = "1.0.88"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "37d3544b3f2748c54e147655edb5025752e2303145b5aefb3c3ea2c78b973bb0"
+checksum = "7c3a7fc5db1e57d5a779a352c8cdb57b29aa4c40cc69c3a68a7fedc815fbf2f9"
 dependencies = [
  "unicode-ident",
 ]
@@ -927,7 +879,7 @@ dependencies = [
  "proc-macro2",
  "pyo3-macros-backend",
  "quote",
- "syn 2.0.94",
+ "syn 2.0.79",
 ]
 
 [[package]]
@@ -940,14 +892,14 @@ dependencies = [
  "proc-macro2",
  "pyo3-build-config",
  "quote",
- "syn 2.0.94",
+ "syn 2.0.79",
 ]
 
 [[package]]
 name = "quote"
-version = "1.0.38"
+version = "1.0.37"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0e4dccaaaf89514f546c693ddc140f729f958c247918a13380cccc6078391acc"
+checksum = "b5b9d34b8991d19d98081b46eacdd8eb58c6f2b201139f7c5f643cc155a633af"
 dependencies = [
  "proc-macro2",
 ]
@@ -1004,18 +956,18 @@ dependencies = [
 
 [[package]]
 name = "redox_syscall"
-version = "0.5.8"
+version = "0.5.7"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "03a862b389f93e68874fbf580b9de08dd02facb9a788ebadaf4a3fd33cf58834"
+checksum = "9b6dfecf2c74bce2466cabf93f6664d6998a69eb21e39f4207930065b27b771f"
 dependencies = [
  "bitflags",
 ]
 
 [[package]]
 name = "regex"
-version = "1.11.1"
+version = "1.11.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b544ef1b4eac5dc2db33ea63606ae9ffcfac26c1416a2806ae0bf5f56b201191"
+checksum = "38200e5ee88914975b69f657f0801b6f6dccafd44fd9326302a4aaeecfacb1d8"
 dependencies = [
  "aho-corasick",
  "memchr",
@@ -1025,9 +977,9 @@ dependencies = [
 
 [[package]]
 name = "regex-automata"
-version = "0.4.9"
+version = "0.4.8"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "809e8dc61f6de73b46c85f4c96486310fe304c434cfa43669d7b40f711150908"
+checksum = "368758f23274712b504848e9d5a6f010445cc8b87a7cdb4d7cbee666c1288da3"
 dependencies = [
  "aho-corasick",
  "memchr",
@@ -1049,22 +1001,22 @@ dependencies = [
 
 [[package]]
 name = "rustix"
-version = "0.38.42"
+version = "0.38.37"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f93dc38ecbab2eb790ff964bb77fa94faf256fd3e73285fd7ba0903b76bedb85"
+checksum = "8acb788b847c24f28525660c4d7758620a7210875711f79e7f663cc152726811"
 dependencies = [
  "bitflags",
  "errno",
  "libc",
  "linux-raw-sys",
- "windows-sys 0.59.0",
+ "windows-sys 0.52.0",
 ]
 
 [[package]]
 name = "rustversion"
-version = "1.0.19"
+version = "1.0.18"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f7c45b9784283f1b2e7fb61b42047c2fd678ef0960d4f6f1eba131594cc369d4"
+checksum = "0e819f2bc632f285be6d7cd36e25940d45b2391dd6d9b939e79de557f7014248"
 
 [[package]]
 name = "ryu"
@@ -1089,35 +1041,35 @@ checksum = "94143f37725109f92c262ed2cf5e59bce7498c01bcc1502d7b9afe439a4e9f49"
 
 [[package]]
 name = "semver"
-version = "1.0.24"
+version = "1.0.23"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3cb6eb87a131f756572d7fb904f6e7b68633f09cca868c5df1c4b8d1a694bbba"
+checksum = "61697e0a1c7e512e84a621326239844a24d8207b4669b41bc18b32ea5cbf988b"
 
 [[package]]
 name = "serde"
-version = "1.0.217"
+version = "1.0.210"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "02fc4265df13d6fa1d00ecff087228cc0a2b5f3c0e87e258d8b94a156e984c70"
+checksum = "c8e3592472072e6e22e0a54d5904d9febf8508f65fb8552499a1abc7d1078c3a"
 dependencies = [
  "serde_derive",
 ]
 
 [[package]]
 name = "serde_derive"
-version = "1.0.217"
+version = "1.0.210"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5a9bf7cf98d04a2b28aead066b7496853d4779c9cc183c440dbac457641e19a0"
+checksum = "243902eda00fad750862fc144cea25caca5e20d615af0a81bee94ca738f1df1f"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.94",
+ "syn 2.0.79",
 ]
 
 [[package]]
 name = "serde_json"
-version = "1.0.134"
+version = "1.0.129"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d00f4175c42ee48b15416f6193a959ba3a0d67fc699a0db9ad12df9f83991c7d"
+checksum = "6dbcf9b78a125ee667ae19388837dd12294b858d101fdd393cb9d5501ef09eb2"
 dependencies = [
  "itoa",
  "memchr",
@@ -1125,15 +1077,6 @@ dependencies = [
  "serde",
 ]
 
-[[package]]
-name = "serde_spanned"
-version = "0.6.8"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "87607cb1398ed59d48732e575a4c28a7a8ebf2454b964fe3f224f2afc07909e1"
-dependencies = [
- "serde",
-]
-
 [[package]]
 name = "serde_yaml"
 version = "0.8.26"
@@ -1226,7 +1169,7 @@ dependencies = [
  "proc-macro2",
  "quote",
  "rustversion",
- "syn 2.0.94",
+ "syn 2.0.79",
 ]
 
 [[package]]
@@ -1242,9 +1185,9 @@ dependencies = [
 
 [[package]]
 name = "syn"
-version = "2.0.94"
+version = "2.0.79"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "987bc0be1cdea8b10216bd06e2ca407d40b9543468fafd3ddfb02f36e77f71f3"
+checksum = "89132cd0bf050864e1d38dc3bbc07a0eb8e7530af26344d3d2bbbef83499f590"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -1257,21 +1200,14 @@ version = "0.12.16"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "61c41af27dd6d1e27b1b16b489db798443478cef1f06a660c96db617ba5de3b1"
 
-[[package]]
-name = "target-triple"
-version = "0.1.3"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "42a4d50cdb458045afc8131fd91b64904da29548bcb63c7236e0844936c13078"
-
 [[package]]
 name = "tempfile"
-version = "3.15.0"
+version = "3.13.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9a8a559c81686f576e8cd0290cd2a24a2a9ad80c98b3478856500fcbd7acd704"
+checksum = "f0f2c9fc62d0beef6951ccffd757e241266a2c833136efbe35af6cd2567dca5b"
 dependencies = [
  "cfg-if",
  "fastrand",
- "getrandom",
  "once_cell",
  "rustix",
  "windows-sys 0.59.0",
@@ -1279,23 +1215,14 @@ dependencies = [
 
 [[package]]
 name = "term"
-version = "1.0.1"
+version = "1.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a3bb6001afcea98122260987f8b7b5da969ecad46dbf0b5453702f776b491a41"
+checksum = "4df4175de05129f31b80458c6df371a15e7fc3fd367272e6bf938e5c351c7ea0"
 dependencies = [
  "home",
  "windows-sys 0.52.0",
 ]
 
-[[package]]
-name = "termcolor"
-version = "1.4.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "06794f8f6c5c898b3275aebefa6b8a1cb24cd2c6c79397ab15774837a0bc5755"
-dependencies = [
- "winapi-util",
-]
-
 [[package]]
 name = "test-case"
 version = "1.2.3"
@@ -1311,72 +1238,22 @@ dependencies = [
 
 [[package]]
 name = "thiserror"
-version = "1.0.69"
+version = "1.0.64"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b6aaf5339b578ea85b50e080feb250a3e8ae8cfcdff9a461c9ec2904bc923f52"
+checksum = "d50af8abc119fb8bb6dbabcfa89656f46f84aa0ac7688088608076ad2b459a84"
 dependencies = [
  "thiserror-impl",
 ]
 
 [[package]]
 name = "thiserror-impl"
-version = "1.0.69"
+version = "1.0.64"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4fee6c4efc90059e10f81e6d42c60a18f76588c3d74cb83a0b242a2b6c7504c1"
+checksum = "08904e7672f5eb876eaaf87e0ce17857500934f4981c4a0ab2b4aa98baac7fc3"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.94",
+ "syn 2.0.79",
-]
-
-[[package]]
-name = "toml"
-version = "0.8.19"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a1ed1f98e3fdc28d6d910e6737ae6ab1a93bf1985935a1193e68f93eeb68d24e"
-dependencies = [
- "serde",
- "serde_spanned",
- "toml_datetime",
- "toml_edit",
-]
-
-[[package]]
-name = "toml_datetime"
-version = "0.6.8"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0dd7358ecb8fc2f8d014bf86f6f638ce72ba252a2c3a2572f2a795f1d23efb41"
-dependencies = [
- "serde",
-]
-
-[[package]]
-name = "toml_edit"
-version = "0.22.22"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4ae48d6208a266e853d946088ed816055e556cc6028c5e8e2b84d9fa5dd7c7f5"
-dependencies = [
- "indexmap 2.7.0",
- "serde",
- "serde_spanned",
- "toml_datetime",
- "winnow",
-]
-
-[[package]]
-name = "trybuild"
-version = "1.0.101"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8dcd332a5496c026f1e14b7f3d2b7bd98e509660c04239c58b0ba38a12daded4"
-dependencies = [
- "dissimilar",
- "glob",
- "serde",
- "serde_derive",
- "serde_json",
- "target-triple",
- "termcolor",
- "toml",
 ]
 
 [[package]]
@@ -1439,9 +1316,9 @@ dependencies = [
 
 [[package]]
 name = "unicode-ident"
-version = "1.0.14"
+version = "1.0.13"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "adb9e6ca4f869e1180728b7950e35922a7fc6397f7b641499e8f3ef06e50dc83"
+checksum = "e91b56cd4cadaeb79bbf1a5645f6b4f8dc5bde8834ad5894a8db35fda9efa1fe"
 
 [[package]]
 name = "unicode-width"
@@ -1602,15 +1479,6 @@ version = "0.52.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "589f6da84c646204747d1270a2a5661ea66ed1cced2631d546fdfb155959f9ec"
 
-[[package]]
-name = "winnow"
-version = "0.6.22"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "39281189af81c07ec09db316b302a3e67bf9bd7cbf6c820b50e35fee9c2fa980"
-dependencies = [
- "memchr",
-]
-
 [[package]]
 name = "yaml-rust"
 version = "0.4.5"
@@ -1638,5 +1506,5 @@ checksum = "fa4f8080344d4671fb4e831a13ad1e68092748387dfc4f55e356242fae12ce3e"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.94",
+ "syn 2.0.79",
 ]

Cargo.toml

@@ -4,7 +4,6 @@ members = [
   "nac3ast",
   "nac3parser",
   "nac3core",
-  "nac3core/nac3core_derive",
   "nac3standalone",
   "nac3artiq",
   "runkernel",

flake.lock

@@ -2,11 +2,11 @@
   "nodes": {
     "nixpkgs": {
       "locked": {
-        "lastModified": 1735834308,
+        "lastModified": 1727348695,
-        "narHash": "sha256-dklw3AXr3OGO4/XT1Tu3Xz9n/we8GctZZ75ZWVqAVhk=",
+        "narHash": "sha256-J+PeFKSDV+pHL7ukkfpVzCOO7mBSrrpJ3svwBFABbhI=",
         "owner": "NixOS",
         "repo": "nixpkgs",
-        "rev": "6df24922a1400241dae323af55f30e4318a6ca65",
+        "rev": "1925c603f17fc89f4c8f6bf6f631a802ad85d784",
         "type": "github"
       },
       "original": {

flake.nix

@@ -107,18 +107,18 @@
             (pkgs.fetchFromGitHub {
               owner = "m-labs";
               repo = "sipyco";
-              rev = "094a6cd63ffa980ef63698920170e50dc9ba77fd";
+              rev = "939f84f9b5eef7efbf7423c735d1834783b6140e";
-              sha256 = "sha256-PPnAyDedUQ7Og/Cby9x5OT9wMkNGTP8GS53V6N/dk4w=";
+              sha256 = "sha256-15Nun4EY35j+6SPZkjzZtyH/ncxLS60KuGJjFh5kSTc=";
             })
             (pkgs.fetchFromGitHub {
               owner = "m-labs";
               repo = "artiq";
-              rev = "28c9de3e251daa89a8c9fd79d5ab64a3ec03bac6";
+              rev = "923ca3377d42c815f979983134ec549dc39d3ca0";
-              sha256 = "sha256-vAvpbHc5B+1wtG8zqN7j9dQE1ON+i22v+uqA+tw6Gak=";
+              sha256 = "sha256-oJoEeNEeNFSUyh6jXG8Tzp6qHVikeHS0CzfE+mODPgw=";
             })
           ];
           buildInputs = [
-            (python3-mimalloc.withPackages(ps: [ ps.numpy ps.scipy ps.jsonschema ps.lmdb ps.platformdirs nac3artiq-instrumented ]))
+            (python3-mimalloc.withPackages(ps: [ ps.numpy ps.scipy ps.jsonschema ps.lmdb nac3artiq-instrumented ]))
             pkgs.llvmPackages_14.llvm.out
           ];
           phases = [ "buildPhase" "installPhase" ];

nac3artiq/demo/embedding_map.py

@@ -7,6 +7,33 @@ class EmbeddingMap:
         self.function_map = {}
         self.attributes_writeback = []
 
+        # preallocate exception names
+        self.preallocate_runtime_exception_names(["RuntimeError",
+                                          "RTIOUnderflow",
+                                          "RTIOOverflow",
+                                          "RTIODestinationUnreachable",
+                                          "DMAError",
+                                          "I2CError",
+                                          "CacheError",
+                                          "SPIError",
+                                          "0:ZeroDivisionError",
+                                          "0:IndexError",
+                                          "0:ValueError",
+                                          "0:RuntimeError",
+                                          "0:AssertionError",
+                                          "0:KeyError",
+                                          "0:NotImplementedError",
+                                          "0:OverflowError",
+                                          "0:IOError",
+                                          "0:UnwrapNoneError"])
+
+    def preallocate_runtime_exception_names(self, names):
+        for i, name in enumerate(names):
+            if ":" not in name:
+                name = "0:artiq.coredevice.exceptions." + name
+            exn_id = self.store_str(name)
+            assert exn_id == i
+
     def store_function(self, key, fun):
         self.function_map[key] = fun
         return key

nac3artiq/demo/min_artiq.py

@@ -206,7 +206,7 @@ class Core:
         embedding = EmbeddingMap()
 
         if allow_registration:
-            compiler.analyze(registered_functions, registered_classes, set())
+            compiler.analyze(registered_functions, registered_classes)
             allow_registration = False
 
         if hasattr(method, "__self__"):

nac3artiq/src/codegen.rs

@@ -12,25 +12,21 @@ use pyo3::{
     PyObject, PyResult, Python,
 };
 
-use super::{symbol_resolver::InnerResolver, timeline::TimeFns};
 use nac3core::{
     codegen::{
+        classes::{ListValue, RangeValue, UntypedArrayLikeAccessor},
         expr::{destructure_range, gen_call},
-        llvm_intrinsics::{call_int_smax, call_memcpy, call_stackrestore, call_stacksave},
+        llvm_intrinsics::{call_int_smax, call_stackrestore, call_stacksave},
+        model::*,
+        object::{any::AnyObject, ndarray::NDArrayObject},
         stmt::{gen_block, gen_for_callback_incrementing, gen_if_callback, gen_with},
-        type_aligned_alloca,
-        types::ndarray::NDArrayType,
-        values::{
-            ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, ProxyValue, RangeValue,
-            UntypedArrayLikeAccessor,
-        },
         CodeGenContext, CodeGenerator,
     },
     inkwell::{
         context::Context,
         module::Linkage,
-        types::{BasicType, IntType},
+        types::IntType,
-        values::{BasicValueEnum, IntValue, PointerValue, StructValue},
+        values::{BasicValue, BasicValueEnum, IntValue, PointerValue, StructValue},
         AddressSpace, IntPredicate, OptimizationLevel,
     },
     nac3parser::ast::{Expr, ExprKind, Located, Stmt, StmtKind, StrRef},
@@ -43,6 +39,8 @@ use nac3core::{
     typecheck::typedef::{iter_type_vars, FunSignature, FuncArg, Type, TypeEnum, VarMap},
 };
 
+use super::{symbol_resolver::InnerResolver, timeline::TimeFns};
+
 /// The parallelism mode within a block.
 #[derive(Copy, Clone, Eq, PartialEq)]
 enum ParallelMode {
@@ -458,52 +456,42 @@ fn format_rpc_arg<'ctx>(
             // NAC3: NDArray = { usize, usize*, T* }
             // libproto_artiq: NDArray = [data[..], dim_sz[..]]
 
-            let llvm_i1 = ctx.ctx.bool_type();
+            let ndarray = AnyObject { ty: arg_ty, value: arg };
-            let llvm_usize = generator.get_size_type(ctx.ctx);
+            let ndarray = NDArrayObject::from_object(generator, ctx, ndarray);
 
-            let (elem_ty, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, arg_ty);
+            let dtype = ctx.get_llvm_type(generator, ndarray.dtype);
-            let ndims = extract_ndims(&ctx.unifier, ndims);
+            let ndims = ndarray.ndims_llvm(generator, ctx.ctx);
-            let dtype = ctx.get_llvm_type(generator, elem_ty);
-            let ndarray = NDArrayType::new(generator, ctx.ctx, dtype, ndims)
-                .map_value(arg.into_pointer_value(), None);
-
-            let ndims = llvm_usize.const_int(ndims, false);
 
             // `ndarray.data` is possibly not contiguous, and we need it to be contiguous for
             // the reader.
             // Turning it into a ContiguousNDArray to get a `data` that is contiguous.
-            let carray = ndarray.make_contiguous_ndarray(generator, ctx);
+            let carray = ndarray.make_contiguous_ndarray(generator, ctx, Any(dtype));
 
-            let sizeof_usize = llvm_usize.size_of();
+            let sizeof_sizet = Int(SizeT).size_of(generator, ctx.ctx);
-            let sizeof_usize =
+            let sizeof_sizet = Int(SizeT).truncate_or_bit_cast(generator, ctx, sizeof_sizet);
-                ctx.builder.build_int_z_extend_or_bit_cast(sizeof_usize, llvm_usize, "").unwrap();
 
-            let sizeof_pdata = dtype.ptr_type(AddressSpace::default()).size_of();
+            let sizeof_pdata = Ptr(Any(dtype)).size_of(generator, ctx.ctx);
-            let sizeof_pdata =
+            let sizeof_pdata = Int(SizeT).truncate_or_bit_cast(generator, ctx, sizeof_pdata);
-                ctx.builder.build_int_z_extend_or_bit_cast(sizeof_pdata, llvm_usize, "").unwrap();
 
-            let sizeof_buf_shape = ctx.builder.build_int_mul(sizeof_usize, ndims, "").unwrap();
+            let sizeof_buf_shape = sizeof_sizet.mul(ctx, ndims);
-            let sizeof_buf = ctx.builder.build_int_add(sizeof_buf_shape, sizeof_pdata, "").unwrap();
+            let sizeof_buf = sizeof_buf_shape.add(ctx, sizeof_pdata);
 
             // buf = { data: void*, shape: [size_t; ndims]; }
-            let buf = ctx.builder.build_array_alloca(llvm_i8, sizeof_buf, "rpc.arg").unwrap();
+            let buf = Int(Byte).array_alloca(generator, ctx, sizeof_buf.value);
-            let buf = ArraySliceValue::from_ptr_val(buf, sizeof_buf, Some("rpc.arg"));
+            let buf_data = buf;
-            let buf_data = buf.base_ptr(ctx, generator);
+            let buf_shape = buf_data.offset(ctx, sizeof_pdata.value);
-            let buf_shape =
-                unsafe { buf.ptr_offset_unchecked(ctx, generator, &sizeof_pdata, None) };
 
             // Write to `buf->data`
-            let carray_data = carray.load_data(ctx);
+            let carray_data = carray.get(generator, ctx, |f| f.data); // has type Ptr<Any>
-            let carray_data = ctx.builder.build_pointer_cast(carray_data, llvm_pi8, "").unwrap();
+            let carray_data = carray_data.pointer_cast(generator, ctx, Int(Byte));
-            call_memcpy(ctx, buf_data, carray_data, sizeof_pdata, llvm_i1.const_zero());
+            buf_data.copy_from(generator, ctx, carray_data, sizeof_pdata.value);
 
             // Write to `buf->shape`
-            let carray_shape = ndarray.shape().base_ptr(ctx, generator);
+            let carray_shape = ndarray.instance.get(generator, ctx, |f| f.shape);
-            let carray_shape_i8 =
+            let carray_shape_i8 = carray_shape.pointer_cast(generator, ctx, Int(Byte));
-                ctx.builder.build_pointer_cast(carray_shape, llvm_pi8, "").unwrap();
+            buf_shape.copy_from(generator, ctx, carray_shape_i8, sizeof_buf_shape.value);
-            call_memcpy(ctx, buf_shape, carray_shape_i8, sizeof_buf_shape, llvm_i1.const_zero());
 
-            buf.base_ptr(ctx, generator)
+            buf.value
         }
 
         _ => {
@@ -544,8 +532,6 @@ fn format_rpc_ret<'ctx>(
     let llvm_i32 = ctx.ctx.i32_type();
     let llvm_i8_8 = ctx.ctx.struct_type(&[llvm_i8.array_type(8).into()], false);
     let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
 
     let rpc_recv = ctx.module.get_function("rpc_recv").unwrap_or_else(|| {
         ctx.module.add_function("rpc_recv", llvm_i32.fn_type(&[llvm_pi8.into()], false), None)
@@ -566,7 +552,10 @@ fn format_rpc_ret<'ctx>(
 
     let result = match &*ctx.unifier.get_ty_immutable(ret_ty) {
         TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-            let num_0 = llvm_usize.const_zero();
+            // FIXME: It is possible to rewrite everything more neatly with `Model<'ctx>`, but this is not too important.
+
+            let num_0 = Int(SizeT).const_0(generator, ctx.ctx);
+            let num_8 = Int(SizeT).const_int(generator, ctx.ctx, 8, false);
 
             // Round `val` up to its modulo `power_of_two`
             let round_up = |ctx: &mut CodeGenContext<'ctx, '_>,
@@ -595,10 +584,8 @@ fn format_rpc_ret<'ctx>(
             // Allocate the resulting ndarray
             // A condition after format_rpc_ret ensures this will not be popped this off.
             let (dtype, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, ret_ty);
-            let dtype_llvm = ctx.get_llvm_type(generator, dtype);
             let ndims = extract_ndims(&ctx.unifier, ndims);
-            let ndarray = NDArrayType::new(generator, ctx.ctx, dtype_llvm, ndims)
+            let ndarray = NDArrayObject::alloca(generator, ctx, dtype, ndims);
-                .construct_uninitialized(generator, ctx, None);
 
             // NOTE: Current content of `ndarray`:
             //   - * `data` - **NOT YET** allocated.
@@ -607,34 +594,40 @@ fn format_rpc_ret<'ctx>(
             //   - * `shape` - allocated; has uninitialized values.
             //   - * `strides` - allocated; has uninitialized values.
 
-            let itemsize = ndarray.load_itemsize(ctx); // Same as doing a `ctx.get_llvm_type` on `dtype` and get its `size_of()`.
+            let itemsize = ndarray.instance.get(generator, ctx, |f| f.itemsize); // Same as doing a `ctx.get_llvm_type` on `dtype` and get its `size_of()`.
+            let dtype_llvm = ctx.get_llvm_type(generator, dtype);
 
             // Allocates a buffer for the initial RPC'ed object, which is guaranteed to be
             // (4 + 4 * ndims) bytes with 8-byte alignment
-            let sizeof_usize = llvm_usize.size_of();
+            let sizeof_size_t = Int(SizeT).size_of(generator, ctx.ctx);
-            let sizeof_usize =
+            let sizeof_size_t = Int(SizeT).z_extend_or_truncate(generator, ctx, sizeof_size_t); // sizeof(size_t)
-                ctx.builder.build_int_truncate_or_bit_cast(sizeof_usize, llvm_usize, "").unwrap();
 
-            let sizeof_ptr = llvm_i8.ptr_type(AddressSpace::default()).size_of();
+            let sizeof_ptr = Ptr(Int(Byte)).size_of(generator, ctx.ctx);
-            let sizeof_ptr =
+            let sizeof_ptr = Int(SizeT).z_extend_or_truncate(generator, ctx, sizeof_ptr); // sizeof(uint8_t*)
-                ctx.builder.build_int_z_extend_or_bit_cast(sizeof_ptr, llvm_usize, "").unwrap();
 
-            let sizeof_shape =
+            let sizeof_shape = ndarray.ndims_llvm(generator, ctx.ctx).mul(ctx, sizeof_size_t); // sizeof([size_t; ndims]); same as the # of bytes of `ndarray.shape`.
-                ctx.builder.build_int_mul(ndarray.load_ndims(ctx), sizeof_usize, "").unwrap();
 
             // Size of the buffer for the initial `rpc_recv()`.
-            let unaligned_buffer_size =
+            let unaligned_buffer_size = sizeof_ptr.add(ctx, sizeof_shape); // sizeof(uint8_t*) + sizeof([size_t; ndims]).
-                ctx.builder.build_int_add(sizeof_ptr, sizeof_shape, "").unwrap();
+            let buffer_size = round_up(ctx, unaligned_buffer_size.value, num_8.value);
+            let buffer_size = unsafe { Int(SizeT).believe_value(buffer_size) };
 
             let stackptr = call_stacksave(ctx, None);
-            let buffer = type_aligned_alloca(
+            // Just to be absolutely sure, alloca in [i8 x 8] slices to force 8-byte alignment
-                generator,
+            let buffer = ctx
-                ctx,
+                .builder
-                llvm_i8_8,
+                .build_array_alloca(
-                unaligned_buffer_size,
+                    llvm_i8_8,
-                Some("rpc.buffer"),
+                    ctx.builder.build_int_unsigned_div(buffer_size.value, num_8.value, "").unwrap(),
-            );
+                    "rpc.buffer",
-            let buffer = ArraySliceValue::from_ptr_val(buffer, unaligned_buffer_size, None);
+                )
+                .unwrap();
+            let buffer = ctx
+                .builder
+                .build_bit_cast(buffer, llvm_pi8, "")
+                .map(BasicValueEnum::into_pointer_value)
+                .unwrap();
+            let buffer = unsafe { Ptr(Int(Byte)).believe_value(buffer) };
 
             // The first call to `rpc_recv` reads the top-level ndarray object: [pdata, shape]
             //
@@ -642,22 +635,20 @@ fn format_rpc_ret<'ctx>(
             let ndarray_nbytes = ctx
                 .build_call_or_invoke(
                     rpc_recv,
-                    &[buffer.base_ptr(ctx, generator).into()], // Reads [usize; ndims]
+                    &[buffer.value.into()], // Reads [usize; ndims]
                     "rpc.size.next",
                 )
                 .map(BasicValueEnum::into_int_value)
                 .unwrap();
+            let ndarray_nbytes = unsafe { Int(SizeT).believe_value(ndarray_nbytes) };
 
             // debug_assert(ndarray_nbytes > 0)
             if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
-                let cmp = ctx
+                let cmp = ndarray_nbytes.compare(ctx, IntPredicate::UGT, num_0);
-                    .builder
-                    .build_int_compare(IntPredicate::UGT, ndarray_nbytes, num_0, "")
-                    .unwrap();
 
                 ctx.make_assert(
                     generator,
-                    cmp,
+                    cmp.value,
                     "0:AssertionError",
                     "Unexpected RPC termination for ndarray - Expected data buffer next",
                     [None, None, None],
@@ -667,10 +658,8 @@ fn format_rpc_ret<'ctx>(
 
             // Copy shape from the buffer to `ndarray.shape`.
             // We need to skip the first `sizeof(uint8_t*)` bytes to skip the `pdata` in `[pdata, shape]`.
-            let pbuffer_shape =
+            let pbuffer_shape = buffer.offset(ctx, sizeof_ptr.value);
-                unsafe { buffer.ptr_offset_unchecked(ctx, generator, &sizeof_ptr, None) };
+            let pbuffer_shape = pbuffer_shape.pointer_cast(generator, ctx, Int(SizeT));
-            let pbuffer_shape =
-                ctx.builder.build_pointer_cast(pbuffer_shape, llvm_pusize, "").unwrap();
 
             // Copy shape from buffer to `ndarray.shape`
             ndarray.copy_shape_from_array(generator, ctx, pbuffer_shape);
@@ -681,35 +670,26 @@ fn format_rpc_ret<'ctx>(
             // Allocate `ndarray.data`.
             // `ndarray.shape` must be initialized beforehand in this implementation
             //   (for ndarray.create_data() to know how many elements to allocate)
-            unsafe { ndarray.create_data(generator, ctx) }; // NOTE: the strides of `ndarray` has also been set to contiguous in `create_data`.
+            ndarray.create_data(generator, ctx); // NOTE: the strides of `ndarray` has also been set to contiguous in `::create_data()`.
 
             // debug_assert(nelems * sizeof(T) >= ndarray_nbytes)
             if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
                 let num_elements = ndarray.size(generator, ctx);
 
-                let expected_ndarray_nbytes =
+                let expected_ndarray_nbytes = num_elements.mul(ctx, itemsize);
-                    ctx.builder.build_int_mul(num_elements, itemsize, "").unwrap();
+                let cmp = expected_ndarray_nbytes.compare(ctx, IntPredicate::UGE, ndarray_nbytes);
-                let cmp = ctx
-                    .builder
-                    .build_int_compare(
-                        IntPredicate::UGE,
-                        expected_ndarray_nbytes,
-                        ndarray_nbytes,
-                        "",
-                    )
-                    .unwrap();
 
                 ctx.make_assert(
                     generator,
-                    cmp,
+                    cmp.value,
                     "0:AssertionError",
                     "Unexpected allocation size request for ndarray data - Expected up to {0} bytes, got {1} bytes",
-                    [Some(expected_ndarray_nbytes), Some(ndarray_nbytes), None],
+                    [Some(expected_ndarray_nbytes.value), Some(ndarray_nbytes.value), None],
                     ctx.current_loc,
                 );
             }
 
-            let ndarray_data = ndarray.data().base_ptr(ctx, generator);
+            let ndarray_data = ndarray.instance.get(generator, ctx, |f| f.data);
 
             // NOTE: Currently on `prehead_bb`
             ctx.builder.build_unconditional_branch(head_bb).unwrap();
@@ -718,7 +698,7 @@ fn format_rpc_ret<'ctx>(
             ctx.builder.position_at_end(head_bb);
 
             let phi = ctx.builder.build_phi(llvm_pi8, "rpc.ptr").unwrap();
-            phi.add_incoming(&[(&ndarray_data, prehead_bb)]);
+            phi.add_incoming(&[(&ndarray_data.value, prehead_bb)]);
 
             let alloc_size = ctx
                 .build_call_or_invoke(rpc_recv, &[phi.as_basic_value()], "rpc.size.next")
@@ -733,13 +713,12 @@ fn format_rpc_ret<'ctx>(
 
             ctx.builder.position_at_end(alloc_bb);
             // Align the allocation to sizeof(T)
-            let alloc_size = round_up(ctx, alloc_size, itemsize);
+            let alloc_size = round_up(ctx, alloc_size, itemsize.value);
-            // TODO(Derppening): Candidate for refactor into type_aligned_alloca
             let alloc_ptr = ctx
                 .builder
                 .build_array_alloca(
                     dtype_llvm,
-                    ctx.builder.build_int_unsigned_div(alloc_size, itemsize, "").unwrap(),
+                    ctx.builder.build_int_unsigned_div(alloc_size, itemsize.value, "").unwrap(),
                     "rpc.alloc",
                 )
                 .unwrap();
@@ -749,7 +728,7 @@ fn format_rpc_ret<'ctx>(
             ctx.builder.build_unconditional_branch(head_bb).unwrap();
 
             ctx.builder.position_at_end(tail_bb);
-            ndarray.as_base_value().into()
+            ndarray.instance.value.as_basic_value_enum()
         }
 
         _ => {
@@ -962,12 +941,11 @@ fn rpc_codegen_callback_fn<'ctx>(
     }
 }
 
-pub fn attributes_writeback<'ctx>(
+pub fn attributes_writeback(
-    ctx: &mut CodeGenContext<'ctx, '_>,
+    ctx: &mut CodeGenContext<'_, '_>,
     generator: &mut dyn CodeGenerator,
     inner_resolver: &InnerResolver,
     host_attributes: &PyObject,
-    return_obj: Option<(Type, ValueEnum<'ctx>)>,
 ) -> Result<(), String> {
     Python::with_gil(|py| -> PyResult<Result<(), String>> {
         let host_attributes: &PyList = host_attributes.downcast(py)?;
@@ -977,11 +955,6 @@ pub fn attributes_writeback<'ctx>(
         let zero = int32.const_zero();
         let mut values = Vec::new();
         let mut scratch_buffer = Vec::new();
-
-        if let Some((ty, obj)) = return_obj {
-            values.push((ty, obj.to_basic_value_enum(ctx, generator, ty).unwrap()));
-        }
-
         for val in (*globals).values() {
             let val = val.as_ref(py);
             let ty = inner_resolver.get_obj_type(
@@ -1060,7 +1033,7 @@ pub fn attributes_writeback<'ctx>(
         let args: Vec<_> =
             values.into_iter().map(|(_, val)| (None, ValueEnum::Dynamic(val))).collect();
         if let Err(e) =
-            rpc_codegen_callback_fn(ctx, None, (&fun, PrimDef::Int32.id()), args, generator, true)
+            rpc_codegen_callback_fn(ctx, None, (&fun, PrimDef::Int32.id()), args, generator, false)
         {
             return Ok(Err(e));
         }
@@ -1286,8 +1259,7 @@ fn polymorphic_print<'ctx>(
                 fmt.push('[');
                 flush(ctx, generator, &mut fmt, &mut args);
 
-                let val =
+                let val = ListValue::from_ptr_val(value.into_pointer_value(), llvm_usize, None);
-                    ListValue::from_pointer_value(value.into_pointer_value(), llvm_usize, None);
                 let len = val.load_size(ctx, None);
                 let last =
                     ctx.builder.build_int_sub(len, llvm_usize.const_int(1, false), "").unwrap();
@@ -1341,27 +1313,23 @@ fn polymorphic_print<'ctx>(
                 fmt.push_str("array([");
                 flush(ctx, generator, &mut fmt, &mut args);
 
-                let (dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
+                let ndarray = AnyObject { ty, value };
-                let ndarray = NDArrayType::from_unifier_type(generator, ctx, ty)
+                let ndarray = NDArrayObject::from_object(generator, ctx, ndarray);
-                    .map_value(value.into_pointer_value(), None);
 
-                let num_0 = llvm_usize.const_zero();
+                let num_0 = Int(SizeT).const_0(generator, ctx.ctx);
 
                 // Print `ndarray` as a flat list delimited by interspersed with ", \0"
                 ndarray.foreach(generator, ctx, |generator, ctx, _, hdl| {
-                    let i = hdl.get_index(ctx);
+                    let i = hdl.get_index(generator, ctx);
-                    let scalar = hdl.get_scalar(ctx);
+                    let scalar = hdl.get_scalar(generator, ctx);
 
-                    // if (i != 0) puts(", ");
+                    // if (i != 0) { puts(", "); }
                     gen_if_callback(
                         generator,
                         ctx,
                         |_, ctx| {
-                            let not_first = ctx
+                            let not_first = i.compare(ctx, IntPredicate::NE, num_0);
-                                .builder
+                            Ok(not_first.value)
-                                .build_int_compare(IntPredicate::NE, i, num_0, "")
-                                .unwrap();
-                            Ok(not_first)
                         },
                         |generator, ctx| {
                             printf(ctx, generator, ", \0".into(), Vec::default());
@@ -1374,7 +1342,7 @@ fn polymorphic_print<'ctx>(
                     polymorphic_print(
                         ctx,
                         generator,
-                        &[(dtype, scalar.into())],
+                        &[(scalar.ty, scalar.value.into())],
                         "",
                         None,
                         true,
@@ -1391,7 +1359,7 @@ fn polymorphic_print<'ctx>(
                 fmt.push_str("range(");
                 flush(ctx, generator, &mut fmt, &mut args);
 
-                let val = RangeValue::from_pointer_value(value.into_pointer_value(), None);
+                let val = RangeValue::from_ptr_val(value.into_pointer_value(), None);
 
                 let (start, stop, step) = destructure_range(ctx, val);
 

nac3artiq/src/lib.rs

@@ -1,4 +1,10 @@
-#![deny(future_incompatible, let_underscore, nonstandard_style, clippy::all)]
+#![deny(
+    future_incompatible,
+    let_underscore,
+    nonstandard_style,
+    rust_2024_compatibility,
+    clippy::all
+)]
 #![warn(clippy::pedantic)]
 #![allow(
     unsafe_op_in_unsafe_fn,
@@ -24,19 +30,19 @@ use parking_lot::{Mutex, RwLock};
 use pyo3::{
     create_exception, exceptions,
     prelude::*,
-    types::{PyBytes, PyDict, PyNone, PySet},
+    types::{PyBytes, PyDict, PySet},
 };
 use tempfile::{self, TempDir};
 
 use nac3core::{
     codegen::{
         concrete_type::ConcreteTypeStore, gen_func_impl, irrt::load_irrt, CodeGenLLVMOptions,
-        CodeGenTargetMachineOptions, CodeGenTask, CodeGenerator, WithCall, WorkerRegistry,
+        CodeGenTargetMachineOptions, CodeGenTask, WithCall, WorkerRegistry,
     },
     inkwell::{
         context::Context,
         memory_buffer::MemoryBuffer,
-        module::{FlagBehavior, Linkage, Module},
+        module::{Linkage, Module},
         passes::PassBuilderOptions,
         support::is_multithreaded,
         targets::*,
@@ -142,32 +148,14 @@ impl Nac3 {
         module: &PyObject,
         registered_class_ids: &HashSet<u64>,
     ) -> PyResult<()> {
-        let (module_name, source_file, source) =
+        let (module_name, source_file) = Python::with_gil(|py| -> PyResult<(String, String)> {
-            Python::with_gil(|py| -> PyResult<(String, String, String)> {
+            let module: &PyAny = module.extract(py)?;
-                let module: &PyAny = module.extract(py)?;
+            Ok((module.getattr("__name__")?.extract()?, module.getattr("__file__")?.extract()?))
-                let source_file = module.getattr("__file__");
+        })?;
-                let (source_file, source) = if let Ok(source_file) = source_file {
-                    let source_file = source_file.extract()?;
-                    (
-                        source_file,
-                        fs::read_to_string(source_file).map_err(|e| {
-                            exceptions::PyIOError::new_err(format!(
-                                "failed to read input file: {e}"
-                            ))
-                        })?,
-                    )
-                } else {
-                    // kernels submitted by content have no file
-                    // but still can provide source by StringLoader
-                    let get_src_fn = module
-                        .getattr("__loader__")?
-                        .extract::<PyObject>()?
-                        .getattr(py, "get_source")?;
-                    ("<expcontent>", get_src_fn.call1(py, (PyNone::get(py),))?.extract(py)?)
-                };
-                Ok((module.getattr("__name__")?.extract()?, source_file.to_string(), source))
-            })?;
 
+        let source = fs::read_to_string(&source_file).map_err(|e| {
+            exceptions::PyIOError::new_err(format!("failed to read input file: {e}"))
+        })?;
         let parser_result = parse_program(&source, source_file.into())
             .map_err(|e| exceptions::PySyntaxError::new_err(format!("parse error: {e}")))?;
 
@@ -577,7 +565,7 @@ impl Nac3 {
             field_to_val: RwLock::default(),
             name_to_pyid,
             module: module.to_object(py),
-            helper: helper.clone(),
+            helper,
             string_store: self.string_store.clone(),
             exception_ids: self.exception_ids.clone(),
             deferred_eval_store: self.deferred_eval_store.clone(),
@@ -685,12 +673,33 @@ impl Nac3 {
         let task = CodeGenTask {
             subst: Vec::default(),
             symbol_name: "__modinit__".to_string(),
+            body: instance.body,
+            signature,
+            resolver: resolver.clone(),
+            store,
+            unifier_index: instance.unifier_id,
+            calls: instance.calls,
+            id: 0,
+        };
+
+        let mut store = ConcreteTypeStore::new();
+        let mut cache = HashMap::new();
+        let signature = store.from_signature(
+            &mut composer.unifier,
+            &self.primitive,
+            &fun_signature,
+            &mut cache,
+        );
+        let signature = store.add_cty(signature);
+        let attributes_writeback_task = CodeGenTask {
+            subst: Vec::default(),
+            symbol_name: "attributes_writeback".to_string(),
             body: Arc::new(Vec::default()),
             signature,
             resolver,
             store,
             unifier_index: instance.unifier_id,
-            calls: instance.calls,
+            calls: Arc::new(HashMap::default()),
             id: 0,
         };
 
@@ -714,27 +723,19 @@ impl Nac3 {
             .collect();
 
         let membuffer = membuffers.clone();
-        let mut has_return = false;
         py.allow_threads(|| {
             let (registry, handles) =
                 WorkerRegistry::create_workers(threads, top_level.clone(), &self.llvm_options, &f);
+            registry.add_task(task);
+            registry.wait_tasks_complete(handles);
 
-            let mut generator = ArtiqCodeGenerator::new("main".to_string(), size_t, self.time_fns);
+            let mut generator =
+                ArtiqCodeGenerator::new("attributes_writeback".to_string(), size_t, self.time_fns);
             let context = Context::create();
-            let module = context.create_module("main");
+            let module = context.create_module("attributes_writeback");
             let target_machine = self.llvm_options.create_target_machine().unwrap();
             module.set_data_layout(&target_machine.get_target_data().get_data_layout());
             module.set_triple(&target_machine.get_triple());
-            module.add_basic_value_flag(
-                "Debug Info Version",
-                FlagBehavior::Warning,
-                context.i32_type().const_int(3, false),
-            );
-            module.add_basic_value_flag(
-                "Dwarf Version",
-                FlagBehavior::Warning,
-                context.i32_type().const_int(4, false),
-            );
             let builder = context.create_builder();
             let (_, module, _) = gen_func_impl(
                 &context,
@@ -742,27 +743,9 @@ impl Nac3 {
                 &registry,
                 builder,
                 module,
-                task,
+                attributes_writeback_task,
                 |generator, ctx| {
-                    assert_eq!(instance.body.len(), 1, "toplevel module should have 1 statement");
+                    attributes_writeback(ctx, generator, inner_resolver.as_ref(), &host_attributes)
-                    let StmtKind::Expr { value: ref expr, .. } = instance.body[0].node else {
-                        unreachable!("toplevel statement must be an expression")
-                    };
-                    let ExprKind::Call { .. } = expr.node else {
-                        unreachable!("toplevel expression must be a function call")
-                    };
-
-                    let return_obj =
-                        generator.gen_expr(ctx, expr)?.map(|value| (expr.custom.unwrap(), value));
-                    has_return = return_obj.is_some();
-                    registry.wait_tasks_complete(handles);
-                    attributes_writeback(
-                        ctx,
-                        generator,
-                        inner_resolver.as_ref(),
-                        &host_attributes,
-                        return_obj,
-                    )
                 },
             )
             .unwrap();
@@ -771,23 +754,35 @@ impl Nac3 {
             membuffer.lock().push(buffer);
         });
 
-        embedding_map.setattr("expects_return", has_return).unwrap();
-
         // Link all modules into `main`.
         let buffers = membuffers.lock();
         let main = context
-            .create_module_from_ir(MemoryBuffer::create_from_memory_range(
+            .create_module_from_ir(MemoryBuffer::create_from_memory_range(&buffers[0], "main"))
-                buffers.last().unwrap(),
-                "main",
-            ))
             .unwrap();
-        for buffer in buffers.iter().rev().skip(1) {
+        for buffer in buffers.iter().skip(1) {
             let other = context
                 .create_module_from_ir(MemoryBuffer::create_from_memory_range(buffer, "main"))
                 .unwrap();
 
             main.link_in_module(other).map_err(|err| CompileError::new_err(err.to_string()))?;
         }
+        let builder = context.create_builder();
+        let modinit_return = main
+            .get_function("__modinit__")
+            .unwrap()
+            .get_last_basic_block()
+            .unwrap()
+            .get_terminator()
+            .unwrap();
+        builder.position_before(&modinit_return);
+        builder
+            .build_call(
+                main.get_function("attributes_writeback").unwrap(),
+                &[],
+                "attributes_writeback",
+            )
+            .unwrap();
+
         main.link_in_module(irrt).map_err(|err| CompileError::new_err(err.to_string()))?;
 
         let mut function_iter = main.get_first_function();
@@ -822,20 +817,6 @@ impl Nac3 {
             panic!("Failed to run optimization for module `main`: {}", err.to_string());
         }
 
-        Python::with_gil(|py| {
-            let string_store = self.string_store.read();
-            let mut string_store_vec = string_store.iter().collect::<Vec<_>>();
-            string_store_vec.sort_by(|(_s1, key1), (_s2, key2)| key1.cmp(key2));
-            for (s, key) in string_store_vec {
-                let embed_key: i32 = helper.store_str.call1(py, (s,)).unwrap().extract(py).unwrap();
-                assert_eq!(
-                    embed_key, *key,
-                    "string {s} is out of sync between embedding map (key={embed_key}) and \
-                    the internal string store (key={key})"
-                );
-            }
-        });
-
         link_fn(&main)
     }
 
@@ -1085,48 +1066,6 @@ impl Nac3 {
         let working_directory = tempfile::Builder::new().prefix("nac3-").tempdir().unwrap();
         fs::write(working_directory.path().join("kernel.ld"), include_bytes!("kernel.ld")).unwrap();
 
-        let mut string_store: HashMap<String, i32> = HashMap::default();
-
-        // Keep this list of exceptions in sync with `EXCEPTION_ID_LOOKUP` in `artiq::firmware::ksupport::eh_artiq`
-        // The exceptions declared here must be defined in `artiq.coredevice.exceptions`
-        // Verify synchronization by running the test cases in `artiq.test.coredevice.test_exceptions`
-        let runtime_exception_names = [
-            "RTIOUnderflow",
-            "RTIOOverflow",
-            "RTIODestinationUnreachable",
-            "DMAError",
-            "I2CError",
-            "CacheError",
-            "SPIError",
-            "SubkernelError",
-            "0:AssertionError",
-            "0:AttributeError",
-            "0:IndexError",
-            "0:IOError",
-            "0:KeyError",
-            "0:NotImplementedError",
-            "0:OverflowError",
-            "0:RuntimeError",
-            "0:TimeoutError",
-            "0:TypeError",
-            "0:ValueError",
-            "0:ZeroDivisionError",
-            "0:LinAlgError",
-            "UnwrapNoneError",
-        ];
-
-        // Preallocate runtime exception names
-        for (i, name) in runtime_exception_names.iter().enumerate() {
-            let exn_name = if name.find(':').is_none() {
-                format!("0:artiq.coredevice.exceptions.{name}")
-            } else {
-                (*name).to_string()
-            };
-
-            let id = i32::try_from(i).unwrap();
-            string_store.insert(exn_name, id);
-        }
-
         Ok(Nac3 {
             isa,
             time_fns,
@@ -1136,7 +1075,7 @@ impl Nac3 {
             top_levels: Vec::default(),
             pyid_to_def: Arc::default(),
             working_directory,
-            string_store: Arc::new(string_store.into()),
+            string_store: Arc::default(),
             exception_ids: Arc::default(),
             deferred_eval_store: DeferredEvaluationStore::new(),
             llvm_options: CodeGenLLVMOptions {
@@ -1146,12 +1085,7 @@ impl Nac3 {
         })
     }
 
-    fn analyze(
+    fn analyze(&mut self, functions: &PySet, classes: &PySet) -> PyResult<()> {
-        &mut self,
-        functions: &PySet,
-        classes: &PySet,
-        content_modules: &PySet,
-    ) -> PyResult<()> {
         let (modules, class_ids) =
             Python::with_gil(|py| -> PyResult<(HashMap<u64, PyObject>, HashSet<u64>)> {
                 let mut modules: HashMap<u64, PyObject> = HashMap::new();
@@ -1161,21 +1095,13 @@ impl Nac3 {
                 let getmodule_fn = PyModule::import(py, "inspect")?.getattr("getmodule")?;
 
                 for function in functions {
-                    let module: PyObject = getmodule_fn.call1((function,))?.extract()?;
+                    let module = getmodule_fn.call1((function,))?.extract()?;
-                    if !module.is_none(py) {
+                    modules.insert(id_fn.call1((&module,))?.extract()?, module);
-                        modules.insert(id_fn.call1((&module,))?.extract()?, module);
-                    }
                 }
                 for class in classes {
-                    let module: PyObject = getmodule_fn.call1((class,))?.extract()?;
+                    let module = getmodule_fn.call1((class,))?.extract()?;
-                    if !module.is_none(py) {
-                        modules.insert(id_fn.call1((&module,))?.extract()?, module);
-                    }
-                    class_ids.insert(id_fn.call1((class,))?.extract()?);
-                }
-                for module in content_modules {
-                    let module: PyObject = module.extract()?;
                     modules.insert(id_fn.call1((&module,))?.extract()?, module);
+                    class_ids.insert(id_fn.call1((class,))?.extract()?);
                 }
                 Ok((modules, class_ids))
             })?;

nac3artiq/src/symbol_resolver.rs

@@ -13,17 +13,16 @@ use pyo3::{
     PyAny, PyErr, PyObject, PyResult, Python,
 };
 
-use super::PrimitivePythonId;
 use nac3core::{
     codegen::{
-        types::{ndarray::NDArrayType, ProxyType},
+        model::*,
-        values::ndarray::make_contiguous_strides,
+        object::ndarray::{make_contiguous_strides, NDArray},
         CodeGenContext, CodeGenerator,
     },
     inkwell::{
         module::Linkage,
-        types::{BasicType, BasicTypeEnum},
+        types::BasicType,
-        values::BasicValueEnum,
+        values::{BasicValue, BasicValueEnum},
         AddressSpace,
     },
     nac3parser::ast::{self, StrRef},
@@ -39,6 +38,8 @@ use nac3core::{
     },
 };
 
+use super::PrimitivePythonId;
+
 pub enum PrimitiveValue {
     I32(i32),
     I64(i64),
@@ -1085,19 +1086,15 @@ impl InnerResolver {
             } else {
                 unreachable!("must be ndarray")
             };
-            let (ndarray_dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ndarray_ty);
+            let (ndarray_dtype, ndarray_ndims) =
-
+                unpack_ndarray_var_tys(&mut ctx.unifier, ndarray_ty);
-            let llvm_i8 = ctx.ctx.i8_type();
-            let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
-            let llvm_usize = generator.get_size_type(ctx.ctx);
-            let llvm_ndarray = NDArrayType::from_unifier_type(generator, ctx, ndarray_ty);
-            let dtype = llvm_ndarray.element_type();
 
+            let dtype = Any(ctx.get_llvm_type(generator, ndarray_dtype));
             {
                 if self.global_value_ids.read().contains_key(&id) {
                     let global = ctx.module.get_global(&id_str).unwrap_or_else(|| {
                         ctx.module.add_global(
-                            llvm_ndarray.as_base_type().get_element_type().into_struct_type(),
+                            Struct(NDArray).llvm_type(generator, ctx.ctx),
                             Some(AddressSpace::default()),
                             &id_str,
                         )
@@ -1107,14 +1104,26 @@ impl InnerResolver {
                 self.global_value_ids.write().insert(id, obj.into());
             }
 
-            let ndims = llvm_ndarray.ndims();
+            let TypeEnum::TLiteral { values, .. } = &*ctx.unifier.get_ty_immutable(ndarray_ndims)
+            else {
+                unreachable!("Expected Literal for ndarray_ndims")
+            };
+
+            let ndarray_ndims = if values.len() == 1 {
+                values[0].clone()
+            } else {
+                todo!("Unpacking literal of more than one element unimplemented")
+            };
+            let Ok(ndims) = u64::try_from(ndarray_ndims) else {
+                unreachable!("Expected u64 value for ndarray_ndims")
+            };
 
             // Obtain the shape of the ndarray
             let shape_tuple: &PyTuple = obj.getattr("shape")?.downcast()?;
             assert_eq!(shape_tuple.len(), ndims as usize);
 
             // The Rust type inferencer cannot figure this out
-            let shape_values = shape_tuple
+            let shape_values: Result<Vec<Instance<'ctx, Int<SizeT>>>, PyErr> = shape_tuple
                 .iter()
                 .enumerate()
                 .map(|(i, elem)| {
@@ -1124,32 +1133,33 @@ impl InnerResolver {
                             super::CompileError::new_err(format!("Error getting element {i}: {e}"))
                         })?
                         .unwrap();
-                    let value = value.into_int_value();
+                    let value = Int(SizeT).check_value(generator, ctx.ctx, value).unwrap();
                     Ok(value)
                 })
-                .collect::<Result<Vec<_>, PyErr>>()?;
+                .collect();
+            let shape_values = shape_values?;
 
             // Also use this opportunity to get the constant values of `shape_values` for calculating strides.
             let shape_u64s = shape_values
                 .iter()
                 .map(|dim| {
-                    assert!(dim.is_const());
+                    assert!(dim.value.is_const());
-                    dim.get_zero_extended_constant().unwrap()
+                    dim.value.get_zero_extended_constant().unwrap()
                 })
                 .collect_vec();
-            let shape_values = llvm_usize.const_array(&shape_values);
+            let shape_values = Int(SizeT).const_array(generator, ctx.ctx, &shape_values);
 
             // create a global for ndarray.shape and initialize it using the shape
             let shape_global = ctx.module.add_global(
-                llvm_usize.array_type(ndims as u32),
+                Array { len: AnyLen(ndims as u32), item: Int(SizeT) }.llvm_type(generator, ctx.ctx),
                 Some(AddressSpace::default()),
                 &(id_str.clone() + ".shape"),
             );
-            shape_global.set_initializer(&shape_values);
+            shape_global.set_initializer(&shape_values.value);
 
             // Obtain the (flattened) elements of the ndarray
             let sz: usize = obj.getattr("size")?.extract()?;
-            let data: Vec<_> = (0..sz)
+            let data_values: Vec<Instance<'ctx, Any>> = (0..sz)
                 .map(|i| {
                     obj.getattr("flat")?.get_item(i).and_then(|elem| {
                         let value = self
@@ -1161,97 +1171,79 @@ impl InnerResolver {
                             })?
                             .unwrap();
 
-                        assert_eq!(value.get_type(), dtype);
+                        let value = dtype.check_value(generator, ctx.ctx, value).unwrap();
                         Ok(value)
                     })
                 })
                 .try_collect()?;
-            let data = data.into_iter();
+            let data = dtype.const_array(generator, ctx.ctx, &data_values);
-            let data = match dtype {
-                BasicTypeEnum::ArrayType(ty) => {
-                    ty.const_array(&data.map(BasicValueEnum::into_array_value).collect_vec())
-                }
-
-                BasicTypeEnum::FloatType(ty) => {
-                    ty.const_array(&data.map(BasicValueEnum::into_float_value).collect_vec())
-                }
-
-                BasicTypeEnum::IntType(ty) => {
-                    ty.const_array(&data.map(BasicValueEnum::into_int_value).collect_vec())
-                }
-
-                BasicTypeEnum::PointerType(ty) => {
-                    ty.const_array(&data.map(BasicValueEnum::into_pointer_value).collect_vec())
-                }
-
-                BasicTypeEnum::StructType(ty) => {
-                    ty.const_array(&data.map(BasicValueEnum::into_struct_value).collect_vec())
-                }
-
-                BasicTypeEnum::VectorType(_) => unreachable!(),
-            };
 
             // create a global for ndarray.data and initialize it using the elements
             //
             // NOTE: NDArray's `data` is `u8*`. Here, `data_global` is an array of `dtype`.
             // We will have to cast it to an `u8*` later.
             let data_global = ctx.module.add_global(
-                dtype.array_type(sz as u32),
+                Array { len: AnyLen(sz as u32), item: dtype }.llvm_type(generator, ctx.ctx),
                 Some(AddressSpace::default()),
                 &(id_str.clone() + ".data"),
             );
-            data_global.set_initializer(&data);
+            data_global.set_initializer(&data.value);
 
             // Get the constant itemsize.
-            let itemsize = dtype.size_of().unwrap();
+            let itemsize = dtype.llvm_type(generator, ctx.ctx).size_of().unwrap();
             let itemsize = itemsize.get_zero_extended_constant().unwrap();
 
             // Create the strides needed for ndarray.strides
             let strides = make_contiguous_strides(itemsize, ndims, &shape_u64s);
-            let strides =
+            let strides = strides
-                strides.into_iter().map(|stride| llvm_usize.const_int(stride, false)).collect_vec();
+                .into_iter()
-            let strides = llvm_usize.const_array(&strides);
+                .map(|stride| Int(SizeT).const_int(generator, ctx.ctx, stride, false))
+                .collect_vec();
+            let strides = Int(SizeT).const_array(generator, ctx.ctx, &strides);
 
             // create a global for ndarray.strides and initialize it
             let strides_global = ctx.module.add_global(
-                llvm_i8.array_type(ndims as u32),
+                Array { len: AnyLen(ndims as u32), item: Int(Byte) }.llvm_type(generator, ctx.ctx),
                 Some(AddressSpace::default()),
-                &format!("${id_str}.strides"),
+                &(id_str.clone() + ".strides"),
             );
-            strides_global.set_initializer(&strides);
+            strides_global.set_initializer(&strides.value);
 
             // create a global for the ndarray object and initialize it
+            // We are also doing [`Model::check_value`] instead of [`Model::believe_value`] to catch bugs.
 
             // NOTE: data_global is an array of dtype, we want a `u8*`.
-            let ndarray_data = data_global.as_pointer_value();
+            let ndarray_data = Ptr(dtype).check_value(generator, ctx.ctx, data_global).unwrap();
-            let ndarray_data = ctx.builder.build_pointer_cast(ndarray_data, llvm_pi8, "").unwrap();
+            let ndarray_data = Ptr(Int(Byte)).pointer_cast(generator, ctx, ndarray_data.value);
 
-            let ndarray_itemsize = llvm_usize.const_int(itemsize, false);
+            let ndarray_itemsize = Int(SizeT).const_int(generator, ctx.ctx, itemsize, false);
 
-            let ndarray_ndims = llvm_usize.const_int(ndims, false);
+            let ndarray_ndims = Int(SizeT).const_int(generator, ctx.ctx, ndims, false);
 
-            let ndarray_shape = shape_global.as_pointer_value();
+            let ndarray_shape =
+                Ptr(Int(SizeT)).check_value(generator, ctx.ctx, shape_global).unwrap();
 
-            let ndarray_strides = strides_global.as_pointer_value();
+            let ndarray_strides =
+                Ptr(Int(SizeT)).check_value(generator, ctx.ctx, strides_global).unwrap();
 
-            let ndarray = llvm_ndarray
+            let ndarray = Struct(NDArray).const_struct(
-                .as_base_type()
+                generator,
-                .get_element_type()
+                ctx.ctx,
-                .into_struct_type()
+                &[
-                .const_named_struct(&[
+                    ndarray_data.value.as_basic_value_enum(),
-                    ndarray_itemsize.into(),
+                    ndarray_itemsize.value.as_basic_value_enum(),
-                    ndarray_ndims.into(),
+                    ndarray_ndims.value.as_basic_value_enum(),
-                    ndarray_shape.into(),
+                    ndarray_shape.value.as_basic_value_enum(),
-                    ndarray_strides.into(),
+                    ndarray_strides.value.as_basic_value_enum(),
-                    ndarray_data.into(),
+                ],
-                ]);
+            );
 
             let ndarray_global = ctx.module.add_global(
-                llvm_ndarray.as_base_type().get_element_type().into_struct_type(),
+                Struct(NDArray).llvm_type(generator, ctx.ctx),
                 Some(AddressSpace::default()),
                 &id_str,
             );
-            ndarray_global.set_initializer(&ndarray);
+            ndarray_global.set_initializer(&ndarray.value);
 
             Ok(Some(ndarray_global.as_pointer_value().into()))
         } else if ty_id == self.primitive_ids.tuple {
@@ -1576,7 +1568,10 @@ impl SymbolResolver for Resolver {
         if let Some(id) = string_store.get(s) {
             *id
         } else {
-            let id = i32::try_from(string_store.len()).unwrap();
+            let id = Python::with_gil(|py| -> PyResult<i32> {
+                self.0.helper.store_str.call1(py, (s,))?.extract(py)
+            })
+            .unwrap();
             string_store.insert(s.into(), id);
             id
         }

nac3ast/Cargo.toml

@@ -10,6 +10,7 @@ constant-optimization = ["fold"]
 fold = []
 
 [dependencies]
+lazy_static = "1.5"
 parking_lot = "0.12"
 string-interner = "0.17"
 fxhash = "0.2"

nac3ast/src/ast_gen.rs

@@ -5,12 +5,14 @@ pub use crate::location::Location;
 
 use fxhash::FxBuildHasher;
 use parking_lot::{Mutex, MutexGuard};
-use std::{cell::RefCell, collections::HashMap, fmt, sync::LazyLock};
+use std::{cell::RefCell, collections::HashMap, fmt};
 use string_interner::{symbol::SymbolU32, DefaultBackend, StringInterner};
 
 pub type Interner = StringInterner<DefaultBackend, FxBuildHasher>;
-static INTERNER: LazyLock<Mutex<Interner>> =
+lazy_static! {
-    LazyLock::new(|| Mutex::new(StringInterner::with_hasher(FxBuildHasher::default())));
+    static ref INTERNER: Mutex<Interner> =
+        Mutex::new(StringInterner::with_hasher(FxBuildHasher::default()));
+}
 
 thread_local! {
     static LOCAL_INTERNER: RefCell<HashMap<String, StrRef>> = RefCell::default();

nac3ast/src/lib.rs

@@ -1,4 +1,10 @@
-#![deny(future_incompatible, let_underscore, nonstandard_style, clippy::all)]
+#![deny(
+    future_incompatible,
+    let_underscore,
+    nonstandard_style,
+    rust_2024_compatibility,
+    clippy::all
+)]
 #![warn(clippy::pedantic)]
 #![allow(
     clippy::missing_errors_doc,
@@ -8,6 +14,9 @@
     clippy::wildcard_imports
 )]
 
+#[macro_use]
+extern crate lazy_static;
+
 mod ast_gen;
 mod constant;
 #[cfg(feature = "fold")]

nac3core/Cargo.toml

@@ -5,8 +5,6 @@ authors = ["M-Labs"]
 edition = "2021"
 
 [features]
-default = ["derive"]
-derive = ["dep:nac3core_derive"]
 no-escape-analysis = []
 
 [dependencies]
@@ -15,7 +13,6 @@ crossbeam = "0.8"
 indexmap = "2.6"
 parking_lot = "0.12"
 rayon = "1.10"
-nac3core_derive = { path = "nac3core_derive", optional = true }
 nac3parser = { path = "../nac3parser" }
 strum = "0.26"
 strum_macros = "0.26"

nac3core/build.rs

@@ -56,8 +56,9 @@ fn main() {
     let output = Command::new("clang-irrt")
         .args(flags)
         .output()
-        .inspect(|o| {
+        .map(|o| {
             assert!(o.status.success(), "{}", std::str::from_utf8(&o.stderr).unwrap());
+            o
         })
         .unwrap();
 

nac3core/irrt/irrt.cpp

@@ -1,9 +1,9 @@
 #include "irrt/exception.hpp"
+#include "irrt/int_types.hpp"
 #include "irrt/list.hpp"
 #include "irrt/math.hpp"
 #include "irrt/range.hpp"
 #include "irrt/slice.hpp"
-#include "irrt/string.hpp"
 #include "irrt/ndarray/basic.hpp"
 #include "irrt/ndarray/def.hpp"
 #include "irrt/ndarray/iter.hpp"

nac3core/irrt/irrt/cslice.hpp

@@ -4,6 +4,6 @@
 
 template<typename SizeT>
 struct CSlice {
-    void* base;
+    uint8_t* base;
     SizeT len;
 };

nac3core/irrt/irrt/exception.hpp

@@ -6,7 +6,7 @@
 /**
  * @brief The int type of ARTIQ exception IDs.
  */
-using ExceptionId = int32_t;
+typedef int32_t ExceptionId;
 
 /*
  * Set of exceptions C++ IRRT can use.
@@ -55,14 +55,14 @@ void _raise_exception_helper(ExceptionId id,
                              int64_t param2) {
     Exception<SizeT> e = {
         .id = id,
-        .filename = {.base = reinterpret_cast<void*>(const_cast<char*>(filename)),
+        .filename = {.base = reinterpret_cast<uint8_t*>(const_cast<char*>(filename)),
-                     .len = static_cast<SizeT>(__builtin_strlen(filename))},
+                     .len = static_cast<int32_t>(__builtin_strlen(filename))},
         .line = line,
         .column = 0,
-        .function = {.base = reinterpret_cast<void*>(const_cast<char*>(function)),
+        .function = {.base = reinterpret_cast<uint8_t*>(const_cast<char*>(function)),
-                     .len = static_cast<SizeT>(__builtin_strlen(function))},
+                     .len = static_cast<int32_t>(__builtin_strlen(function))},
-        .msg = {.base = reinterpret_cast<void*>(const_cast<char*>(msg)),
+        .msg = {.base = reinterpret_cast<uint8_t*>(const_cast<char*>(msg)),
-                .len = static_cast<SizeT>(__builtin_strlen(msg))},
+                .len = static_cast<int32_t>(__builtin_strlen(msg))},
     };
     e.params[0] = param0;
     e.params[1] = param1;
@@ -70,7 +70,6 @@ void _raise_exception_helper(ExceptionId id,
     __nac3_raise(reinterpret_cast<void*>(&e));
     __builtin_unreachable();
 }
-}  // namespace
 
 /**
  * @brief Raise an exception with location details (location in the IRRT source files).
@@ -83,3 +82,4 @@ void _raise_exception_helper(ExceptionId id,
  */
 #define raise_exception(SizeT, id, msg, param0, param1, param2) \
     _raise_exception_helper<SizeT>(id, __FILE__, __LINE__, __FUNCTION__, msg, param0, param1, param2)
+}  // namespace

nac3core/irrt/irrt/int_types.hpp

@@ -8,18 +8,15 @@ using uint32_t = unsigned _BitInt(32);
 using int64_t = _BitInt(64);
 using uint64_t = unsigned _BitInt(64);
 #else
-
-#pragma clang diagnostic push
-#pragma clang diagnostic ignored "-Wdeprecated-type"
 using int8_t = _ExtInt(8);
 using uint8_t = unsigned _ExtInt(8);
 using int32_t = _ExtInt(32);
 using uint32_t = unsigned _ExtInt(32);
 using int64_t = _ExtInt(64);
 using uint64_t = unsigned _ExtInt(64);
-#pragma clang diagnostic pop
-
 #endif
 
+// NDArray indices are always `uint32_t`.
+using NDIndexInt = uint32_t;
 // The type of an index or a value describing the length of a range/slice is always `int32_t`.
 using SliceIndex = int32_t;

nac3core/irrt/irrt/list.hpp

@@ -28,12 +28,12 @@ extern "C" {
 SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
                                              SliceIndex dest_end,
                                              SliceIndex dest_step,
-                                             void* dest_arr,
+                                             uint8_t* dest_arr,
                                              SliceIndex dest_arr_len,
                                              SliceIndex src_start,
                                              SliceIndex src_end,
                                              SliceIndex src_step,
-                                             void* src_arr,
+                                             uint8_t* src_arr,
                                              SliceIndex src_arr_len,
                                              const SliceIndex size) {
     /* if dest_arr_len == 0, do nothing since we do not support extending list */
@@ -44,13 +44,11 @@ SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
         const SliceIndex src_len = (src_end >= src_start) ? (src_end - src_start + 1) : 0;
         const SliceIndex dest_len = (dest_end >= dest_start) ? (dest_end - dest_start + 1) : 0;
         if (src_len > 0) {
-            __builtin_memmove(static_cast<uint8_t*>(dest_arr) + dest_start * size,
+            __builtin_memmove(dest_arr + dest_start * size, src_arr + src_start * size, src_len * size);
-                              static_cast<uint8_t*>(src_arr) + src_start * size, src_len * size);
         }
         if (dest_len > 0) {
             /* dropping */
-            __builtin_memmove(static_cast<uint8_t*>(dest_arr) + (dest_start + src_len) * size,
+            __builtin_memmove(dest_arr + (dest_start + src_len) * size, dest_arr + (dest_end + 1) * size,
-                              static_cast<uint8_t*>(dest_arr) + (dest_end + 1) * size,
                               (dest_arr_len - dest_end - 1) * size);
         }
         /* shrink size */
@@ -61,7 +59,7 @@ SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
                           && !(max(dest_start, dest_end) < min(src_start, src_end)
                                || max(src_start, src_end) < min(dest_start, dest_end));
     if (need_alloca) {
-        void* tmp = __builtin_alloca(src_arr_len * size);
+        uint8_t* tmp = reinterpret_cast<uint8_t*>(__builtin_alloca(src_arr_len * size));
         __builtin_memcpy(tmp, src_arr, src_arr_len * size);
         src_arr = tmp;
     }
@@ -70,24 +68,20 @@ SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
     for (; (src_step > 0) ? (src_ind <= src_end) : (src_ind >= src_end); src_ind += src_step, dest_ind += dest_step) {
         /* for constant optimization */
         if (size == 1) {
-            __builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind, static_cast<uint8_t*>(src_arr) + src_ind, 1);
+            __builtin_memcpy(dest_arr + dest_ind, src_arr + src_ind, 1);
         } else if (size == 4) {
-            __builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind * 4,
+            __builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
-                             static_cast<uint8_t*>(src_arr) + src_ind * 4, 4);
         } else if (size == 8) {
-            __builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind * 8,
+            __builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
-                             static_cast<uint8_t*>(src_arr) + src_ind * 8, 8);
         } else {
             /* memcpy for var size, cannot overlap after previous alloca */
-            __builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind * size,
+            __builtin_memcpy(dest_arr + dest_ind * size, src_arr + src_ind * size, size);
-                             static_cast<uint8_t*>(src_arr) + src_ind * size, size);
         }
     }
     /* only dest_step == 1 can we shrink the dest list. */
     /* size should be ensured prior to calling this function */
     if (dest_step == 1 && dest_end >= dest_start) {
-        __builtin_memmove(static_cast<uint8_t*>(dest_arr) + dest_ind * size,
+        __builtin_memmove(dest_arr + dest_ind * size, dest_arr + (dest_end + 1) * size,
-                          static_cast<uint8_t*>(dest_arr) + (dest_end + 1) * size,
                           (dest_arr_len - dest_end - 1) * size);
         return dest_arr_len - (dest_end - dest_ind) - 1;
     }

nac3core/irrt/irrt/math.hpp

@@ -1,7 +1,5 @@
 #pragma once
 
-#include "irrt/int_types.hpp"
-
 namespace {
 // adapted from GNU Scientific Library: https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
 // need to make sure `exp >= 0` before calling this function
@@ -92,4 +90,4 @@ double __nac3_j0(double x) {
 
     return j0(x);
 }
-}  // namespace
+}

nac3core/irrt/irrt/ndarray/array.hpp

@@ -8,7 +8,8 @@
 #include "irrt/ndarray/def.hpp"
 
 namespace {
-namespace ndarray::array {
+namespace ndarray {
+namespace array {
 /**
  * @brief In the context of `np.array(<list>)`, deduce the ndarray's shape produced by `<list>` and raise
  * an exception if there is anything wrong with `<shape>` (e.g., inconsistent dimensions `np.array([[1.0, 2.0],
@@ -87,7 +88,7 @@ void write_list_to_array_helper(SizeT axis, SizeT* index, List<SizeT>* list, NDA
     if (axis + 1 == ndarray->ndims) {
         // `list` has type `list[scalar]`
         // `ndarray` is contiguous, so we can do this, and this is fast.
-        uint8_t* dst = static_cast<uint8_t*>(ndarray->data) + (ndarray->itemsize * (*index));
+        uint8_t* dst = ndarray->data + (ndarray->itemsize * (*index));
         __builtin_memcpy(dst, list->items, ndarray->itemsize * list->len);
         *index += list->len;
     } else {
@@ -108,7 +109,8 @@ void write_list_to_array(List<SizeT>* list, NDArray<SizeT>* ndarray) {
     SizeT index = 0;
     write_list_to_array_helper<SizeT>((SizeT)0, &index, list, ndarray);
 }
-}  // namespace ndarray::array
+}  // namespace array
+}  // namespace ndarray
 }  // namespace
 
 extern "C" {

nac3core/irrt/irrt/ndarray/basic.hpp

@@ -6,7 +6,8 @@
 #include "irrt/ndarray/def.hpp"
 
 namespace {
-namespace ndarray::basic {
+namespace ndarray {
+namespace basic {
 /**
  * @brief Assert that `shape` does not contain negative dimensions.
  *
@@ -112,13 +113,12 @@ SizeT nbytes(const NDArray<SizeT>* ndarray) {
  */
 template<typename SizeT>
 SizeT len(const NDArray<SizeT>* ndarray) {
-    if (ndarray->ndims != 0) {
+    // numpy prohibits `__len__` on unsized objects
+    if (ndarray->ndims == 0) {
+        raise_exception(SizeT, EXN_TYPE_ERROR, "len() of unsized object", NO_PARAM, NO_PARAM, NO_PARAM);
+    } else {
         return ndarray->shape[0];
     }
-
-    // numpy prohibits `__len__` on unsized objects
-    raise_exception(SizeT, EXN_TYPE_ERROR, "len() of unsized object", NO_PARAM, NO_PARAM, NO_PARAM);
-    __builtin_unreachable();
 }
 
 /**
@@ -178,10 +178,10 @@ bool is_c_contiguous(const NDArray<SizeT>* ndarray) {
  * This function does no bound check.
  */
 template<typename SizeT>
-void* get_pelement_by_indices(const NDArray<SizeT>* ndarray, const SizeT* indices) {
+uint8_t* get_pelement_by_indices(const NDArray<SizeT>* ndarray, const SizeT* indices) {
-    void* element = ndarray->data;
+    uint8_t* element = ndarray->data;
     for (SizeT dim_i = 0; dim_i < ndarray->ndims; dim_i++)
-        element = static_cast<uint8_t*>(element) + indices[dim_i] * ndarray->strides[dim_i];
+        element += indices[dim_i] * ndarray->strides[dim_i];
     return element;
 }
 
@@ -191,12 +191,12 @@ void* get_pelement_by_indices(const NDArray<SizeT>* ndarray, const SizeT* indice
  * This function does no bound check.
  */
 template<typename SizeT>
-void* get_nth_pelement(const NDArray<SizeT>* ndarray, SizeT nth) {
+uint8_t* get_nth_pelement(const NDArray<SizeT>* ndarray, SizeT nth) {
-    void* element = ndarray->data;
+    uint8_t* element = ndarray->data;
     for (SizeT i = 0; i < ndarray->ndims; i++) {
         SizeT axis = ndarray->ndims - i - 1;
         SizeT dim = ndarray->shape[axis];
-        element = static_cast<uint8_t*>(element) + ndarray->strides[axis] * (nth % dim);
+        element += ndarray->strides[axis] * (nth % dim);
         nth /= dim;
     }
     return element;
@@ -224,7 +224,7 @@ void set_strides_by_shape(NDArray<SizeT>* ndarray) {
  * @param pvalue Pointer to the value `pelement` will be set to.
  */
 template<typename SizeT>
-void set_pelement_value(NDArray<SizeT>* ndarray, void* pelement, const void* pvalue) {
+void set_pelement_value(NDArray<SizeT>* ndarray, uint8_t* pelement, const uint8_t* pvalue) {
     __builtin_memcpy(pelement, pvalue, ndarray->itemsize);
 }
 
@@ -246,7 +246,8 @@ void copy_data(const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
         ndarray::basic::set_pelement_value(dst_ndarray, dst_element, src_element);
     }
 }
-}  // namespace ndarray::basic
+}  // namespace basic
+}  // namespace ndarray
 }  // namespace
 
 extern "C" {
@@ -306,19 +307,19 @@ bool __nac3_ndarray_is_c_contiguous64(NDArray<int64_t>* ndarray) {
     return is_c_contiguous(ndarray);
 }
 
-void* __nac3_ndarray_get_nth_pelement(const NDArray<int32_t>* ndarray, int32_t nth) {
+uint8_t* __nac3_ndarray_get_nth_pelement(const NDArray<int32_t>* ndarray, int32_t nth) {
     return get_nth_pelement(ndarray, nth);
 }
 
-void* __nac3_ndarray_get_nth_pelement64(const NDArray<int64_t>* ndarray, int64_t nth) {
+uint8_t* __nac3_ndarray_get_nth_pelement64(const NDArray<int64_t>* ndarray, int64_t nth) {
     return get_nth_pelement(ndarray, nth);
 }
 
-void* __nac3_ndarray_get_pelement_by_indices(const NDArray<int32_t>* ndarray, int32_t* indices) {
+uint8_t* __nac3_ndarray_get_pelement_by_indices(const NDArray<int32_t>* ndarray, int32_t* indices) {
     return get_pelement_by_indices(ndarray, indices);
 }
 
-void* __nac3_ndarray_get_pelement_by_indices64(const NDArray<int64_t>* ndarray, int64_t* indices) {
+uint8_t* __nac3_ndarray_get_pelement_by_indices64(const NDArray<int64_t>* ndarray, int64_t* indices) {
     return get_pelement_by_indices(ndarray, indices);
 }
 

nac3core/irrt/irrt/ndarray/broadcast.hpp

@@ -13,7 +13,8 @@ struct ShapeEntry {
 }  // namespace
 
 namespace {
-namespace ndarray::broadcast {
+namespace ndarray {
+namespace broadcast {
 /**
  * @brief Return true if `src_shape` can broadcast to `dst_shape`.
  *
@@ -86,10 +87,8 @@ void broadcast_shapes(SizeT num_shapes, const ShapeEntry<SizeT>* shapes, SizeT d
         }
     }
 
-#ifdef IRRT_DEBUG_ASSERT
     // Check pre-condition: `dst_ndims` must be `max([shape.ndims for shape in shapes])`
     debug_assert_eq(SizeT, max_ndims_found, dst_ndims);
-#endif
 }
 
 /**
@@ -135,7 +134,8 @@ void broadcast_to(const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray
         }
     }
 }
-}  // namespace ndarray::broadcast
+}  // namespace broadcast
+}  // namespace ndarray
 }  // namespace
 
 extern "C" {

nac3core/irrt/irrt/ndarray/def.hpp

@@ -7,16 +7,15 @@ namespace {
  * @brief The NDArray object
  *
  * Official numpy implementation:
- * https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst#pyarrayinterface
+ * https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst
- *
- * Note that this implementation is based on `PyArrayInterface` rather of `PyArrayObject`. The
- * difference between `PyArrayInterface` and `PyArrayObject` (relevant to our implementation) is
- * that `PyArrayInterface` *has* `itemsize` and uses `void*` for its `data`, whereas `PyArrayObject`
- * does not require `itemsize` (probably using `strides[-1]` instead) and uses `char*` for its
- * `data`. There are also minor differences in the struct layout.
  */
 template<typename SizeT>
 struct NDArray {
+    /**
+     * @brief The underlying data this `ndarray` is pointing to.
+     */
+    uint8_t* data;
+
     /**
      * @brief The number of bytes of a single element in `data`.
      */
@@ -42,10 +41,5 @@ struct NDArray {
      * Note that `strides` can have negative values or contain 0.
      */
     SizeT* strides;
-
-    /**
-     * @brief The underlying data this `ndarray` is pointing to.
-     */
-    void* data;
 };
 }  // namespace

nac3core/irrt/irrt/ndarray/indexing.hpp

@@ -65,7 +65,8 @@ struct NDIndex {
 }  // namespace
 
 namespace {
-namespace ndarray::indexing {
+namespace ndarray {
+namespace indexing {
 /**
  * @brief Perform ndarray "basic indexing" (https://numpy.org/doc/stable/user/basics.indexing.html#basic-indexing)
  *
@@ -153,7 +154,7 @@ void index(SizeT num_indices, const NDIndex* indices, const NDArray<SizeT>* src_
                                 input, src_axis, src_ndarray->shape[src_axis]);
             }
 
-            dst_ndarray->data = static_cast<uint8_t*>(dst_ndarray->data) + k * src_ndarray->strides[src_axis];
+            dst_ndarray->data += k * src_ndarray->strides[src_axis];
 
             src_axis++;
         } else if (index->type == ND_INDEX_TYPE_SLICE) {
@@ -161,8 +162,7 @@ void index(SizeT num_indices, const NDIndex* indices, const NDArray<SizeT>* src_
 
             Range<int32_t> range = slice->indices_checked<SizeT>(src_ndarray->shape[src_axis]);
 
-            dst_ndarray->data =
+            dst_ndarray->data += (SizeT)range.start * src_ndarray->strides[src_axis];
-                static_cast<uint8_t*>(dst_ndarray->data) + (SizeT)range.start * src_ndarray->strides[src_axis];
             dst_ndarray->strides[dst_axis] = ((SizeT)range.step) * src_ndarray->strides[src_axis];
             dst_ndarray->shape[dst_axis] = (SizeT)range.len<SizeT>();
 
@@ -197,7 +197,8 @@ void index(SizeT num_indices, const NDIndex* indices, const NDArray<SizeT>* src_
     debug_assert_eq(SizeT, src_ndarray->ndims, src_axis);
     debug_assert_eq(SizeT, dst_ndarray->ndims, dst_axis);
 }
-}  // namespace ndarray::indexing
+}  // namespace indexing
+}  // namespace ndarray
 }  // namespace
 
 extern "C" {

nac3core/irrt/irrt/ndarray/iter.hpp

@@ -58,7 +58,7 @@ struct NDIter {
      *
      * Initially this points to first element of the ndarray.
      */
-    void* element;
+    uint8_t* element;
 
     /**
      * @brief Cache for the product of shape.
@@ -67,7 +67,7 @@ struct NDIter {
      */
     SizeT size;
 
-    void initialize(SizeT ndims, SizeT* shape, SizeT* strides, void* element, SizeT* indices) {
+    void initialize(SizeT ndims, SizeT* shape, SizeT* strides, uint8_t* element, SizeT* indices) {
         this->ndims = ndims;
         this->shape = shape;
         this->strides = strides;
@@ -108,9 +108,9 @@ struct NDIter {
                 // TODO: There is something called backstrides to speedup iteration.
                 // See https://ajcr.net/stride-guide-part-1/, and
                 // https://docs.scipy.org/doc/numpy-1.13.0/reference/c-api.types-and-structures.html#c.PyArrayIterObject.PyArrayIterObject.backstrides.
-                element = static_cast<void*>(reinterpret_cast<uint8_t*>(element) - strides[axis] * (shape[axis] - 1));
+                element -= strides[axis] * (shape[axis] - 1);
             } else {
-                element = static_cast<void*>(reinterpret_cast<uint8_t*>(element) + strides[axis]);
+                element += strides[axis];
                 break;
             }
         }

nac3core/irrt/irrt/ndarray/matmul.hpp

@@ -10,7 +10,8 @@
 // NOTE: Everything would be much easier and elegant if einsum is implemented.
 
 namespace {
-namespace ndarray::matmul {
+namespace ndarray {
+namespace matmul {
 
 /**
  * @brief Perform the broadcast in `np.einsum("...ij,...jk->...ik", a, b)`.
@@ -68,7 +69,8 @@ void calculate_shapes(SizeT a_ndims,
     dst_shape[final_ndims - 2] = a_shape[a_ndims - 2];
     dst_shape[final_ndims - 1] = b_shape[b_ndims - 1];
 }
-}  // namespace ndarray::matmul
+}  // namespace matmul
+}  // namespace ndarray
 }  // namespace
 
 extern "C" {

nac3core/irrt/irrt/ndarray/reshape.hpp

@@ -5,7 +5,8 @@
 #include "irrt/ndarray/def.hpp"
 
 namespace {
-namespace ndarray::reshape {
+namespace ndarray {
+namespace reshape {
 /**
  * @brief Perform assertions on and resolve unknown dimensions in `new_shape` in `np.reshape(<ndarray>, new_shape)`
  *
@@ -83,7 +84,8 @@ void resolve_and_check_new_shape(SizeT size, SizeT new_ndims, SizeT* new_shape)
                         NO_PARAM);
     }
 }
-}  // namespace ndarray::reshape
+}  // namespace reshape
+}  // namespace ndarray
 }  // namespace
 
 extern "C" {

nac3core/irrt/irrt/ndarray/transpose.hpp

@@ -16,7 +16,8 @@
  */
 
 namespace {
-namespace ndarray::transpose {
+namespace ndarray {
+namespace transpose {
 /**
  * @brief Do assertions on `<axes>` in `np.transpose(<array>, <axes>)`.
  *
@@ -122,7 +123,8 @@ void transpose(const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray, S
         }
     }
 }
-}  // namespace ndarray::transpose
+}  // namespace transpose
+}  // namespace ndarray
 }  // namespace
 
 extern "C" {

nac3core/irrt/irrt/string.hpp

@@ -1,23 +0,0 @@
-#pragma once
-
-#include "irrt/int_types.hpp"
-
-namespace {
-template<typename SizeT>
-bool __nac3_str_eq_impl(const char* str1, SizeT len1, const char* str2, SizeT len2) {
-    if (len1 != len2) {
-        return 0;
-    }
-    return __builtin_memcmp(str1, str2, static_cast<SizeT>(len1)) == 0;
-}
-}  // namespace
-
-extern "C" {
-bool nac3_str_eq(const char* str1, uint32_t len1, const char* str2, uint32_t len2) {
-    return __nac3_str_eq_impl<uint32_t>(str1, len1, str2, len2);
-}
-
-bool nac3_str_eq64(const char* str1, uint64_t len1, const char* str2, uint64_t len2) {
-    return __nac3_str_eq_impl<uint64_t>(str1, len1, str2, len2);
-}
-}

nac3core/nac3core_derive/Cargo.toml

@@ -1,21 +0,0 @@
-[package]
-name = "nac3core_derive"
-version = "0.1.0"
-edition = "2021"
-
-[lib]
-proc-macro = true
-
-[[test]]
-name = "structfields_tests"
-path = "tests/structfields_test.rs"
-
-[dev-dependencies]
-nac3core = { path = ".." }
-trybuild = { version = "1.0", features = ["diff"] }
-
-[dependencies]
-proc-macro2 = "1.0"
-proc-macro-error = "1.0"
-syn = "2.0"
-quote = "1.0"

nac3core/nac3core_derive/src/lib.rs

@@ -1,320 +0,0 @@
-use proc_macro::TokenStream;
-use proc_macro_error::{abort, proc_macro_error};
-use quote::quote;
-use syn::{
-    parse_macro_input, spanned::Spanned, Data, DataStruct, Expr, ExprField, ExprMethodCall,
-    ExprPath, GenericArgument, Ident, LitStr, Path, PathArguments, Type, TypePath,
-};
-
-/// Extracts all generic arguments of a [`Type`] into a [`Vec`].
-///
-/// Returns [`Some`] of a possibly-empty [`Vec`] if the path of `ty` matches with
-/// `expected_ty_name`, otherwise returns [`None`].
-fn extract_generic_args(expected_ty_name: &'static str, ty: &Type) -> Option<Vec<GenericArgument>> {
-    let Type::Path(TypePath { qself: None, path, .. }) = ty else {
-        return None;
-    };
-
-    let segments = &path.segments;
-    if segments.len() != 1 {
-        return None;
-    };
-
-    let segment = segments.iter().next().unwrap();
-    if segment.ident != expected_ty_name {
-        return None;
-    }
-
-    let PathArguments::AngleBracketed(path_args) = &segment.arguments else {
-        return Some(Vec::new());
-    };
-    let args = &path_args.args;
-
-    Some(args.iter().cloned().collect::<Vec<_>>())
-}
-
-/// Maps a `path` matching one of the `target_idents` into the `replacement` [`Ident`].
-fn map_path_to_ident(path: &Path, target_idents: &[&str], replacement: &str) -> Option<Ident> {
-    path.require_ident()
-        .ok()
-        .filter(|ident| target_idents.iter().any(|target| ident == target))
-        .map(|ident| Ident::new(replacement, ident.span()))
-}
-
-/// Extracts the left-hand side of a dot-expression.
-fn extract_dot_operand(expr: &Expr) -> Option<&Expr> {
-    match expr {
-        Expr::MethodCall(ExprMethodCall { receiver: operand, .. })
-        | Expr::Field(ExprField { base: operand, .. }) => Some(operand),
-        _ => None,
-    }
-}
-
-/// Replaces the top-level receiver of a dot-expression with an [`Ident`], returning `Some(&mut expr)` if the
-/// replacement is performed.
-///
-/// The top-level receiver is the left-most receiver expression, e.g. the top-level receiver of `a.b.c.foo()` is `a`.
-fn replace_top_level_receiver(expr: &mut Expr, ident: Ident) -> Option<&mut Expr> {
-    if let Expr::MethodCall(ExprMethodCall { receiver: operand, .. })
-    | Expr::Field(ExprField { base: operand, .. }) = expr
-    {
-        return if extract_dot_operand(operand).is_some() {
-            if replace_top_level_receiver(operand, ident).is_some() {
-                Some(expr)
-            } else {
-                None
-            }
-        } else {
-            *operand = Box::new(Expr::Path(ExprPath {
-                attrs: Vec::default(),
-                qself: None,
-                path: ident.into(),
-            }));
-
-            Some(expr)
-        };
-    }
-
-    None
-}
-
-/// Iterates all operands to the left-hand side of the `.` of an [expression][`Expr`], i.e. the container operand of all
-/// [`Expr::Field`] and the receiver operand of all [`Expr::MethodCall`].
-///
-/// The iterator will return the operand expressions in reverse order of appearance. For example, `a.b.c.func()` will
-/// return `vec![c, b, a]`.
-fn iter_dot_operands(expr: &Expr) -> impl Iterator<Item = &Expr> {
-    let mut o = extract_dot_operand(expr);
-
-    std::iter::from_fn(move || {
-        let this = o;
-        o = o.as_ref().and_then(|o| extract_dot_operand(o));
-
-        this
-    })
-}
-
-/// Normalizes a value expression for use when creating an instance of this structure, returning a
-/// [`proc_macro2::TokenStream`] of tokens representing the normalized expression.
-fn normalize_value_expr(expr: &Expr) -> proc_macro2::TokenStream {
-    match &expr {
-        Expr::Path(ExprPath { qself: None, path, .. }) => {
-            if let Some(ident) = map_path_to_ident(path, &["usize", "size_t"], "llvm_usize") {
-                quote! { #ident }
-            } else {
-                abort!(
-                    path,
-                    format!(
-                        "Expected one of `size_t`, `usize`, or an implicit call expression in #[value_type(...)], found {}", 
-                        quote!(#expr).to_string(),
-                    )
-                )
-            }
-        }
-
-        Expr::Call(_) => {
-            quote! { ctx.#expr }
-        }
-
-        Expr::MethodCall(_) => {
-            let base_receiver = iter_dot_operands(expr).last();
-
-            match base_receiver {
-                // `usize.{...}`, `size_t.{...}` -> Rewrite the identifiers to `llvm_usize`
-                Some(Expr::Path(ExprPath { qself: None, path, .. }))
-                    if map_path_to_ident(path, &["usize", "size_t"], "llvm_usize").is_some() =>
-                {
-                    let ident =
-                        map_path_to_ident(path, &["usize", "size_t"], "llvm_usize").unwrap();
-
-                    let mut expr = expr.clone();
-                    let expr = replace_top_level_receiver(&mut expr, ident).unwrap();
-
-                    quote!(#expr)
-                }
-
-                // `ctx.{...}`, `context.{...}` -> Rewrite the identifiers to `ctx`
-                Some(Expr::Path(ExprPath { qself: None, path, .. }))
-                    if map_path_to_ident(path, &["ctx", "context"], "ctx").is_some() =>
-                {
-                    let ident = map_path_to_ident(path, &["ctx", "context"], "ctx").unwrap();
-
-                    let mut expr = expr.clone();
-                    let expr = replace_top_level_receiver(&mut expr, ident).unwrap();
-
-                    quote!(#expr)
-                }
-
-                // No reserved identifier prefix -> Prepend `ctx.` to the entire expression
-                _ => quote! { ctx.#expr },
-            }
-        }
-
-        _ => {
-            abort!(
-                expr,
-                format!(
-                    "Expected one of `size_t`, `usize`, or an implicit call expression in #[value_type(...)], found {}", 
-                    quote!(#expr).to_string(),
-                )
-            )
-        }
-    }
-}
-
-/// Derives an implementation of `codegen::types::structure::StructFields`.
-///
-/// The benefit of using `#[derive(StructFields)]` is that all index- or order-dependent logic required by
-/// `impl StructFields` is automatically generated by this implementation, including the field index as required by
-/// `StructField::new` and the fields as returned by `StructFields::to_vec`.
-///
-/// # Prerequisites
-///
-/// In order to derive from [`StructFields`], you must implement (or derive) [`Eq`] and [`Copy`] as required by
-/// `StructFields`.
-///
-/// Moreover, `#[derive(StructFields)]` can only be used for `struct`s with named fields, and may only contain fields
-/// with either `StructField` or [`PhantomData`] types.
-///
-/// # Attributes for [`StructFields`]
-///
-/// Each `StructField` field must be declared with the `#[value_type(...)]` attribute. The argument of `value_type`
-/// accepts one of the following:
-///
-/// - An expression returning an instance of `inkwell::types::BasicType` (with or without the receiver `ctx`/`context`).
-/// For example, `context.i8_type()`, `ctx.i8_type()`, and `i8_type()` all refer to `i8`.
-/// - The reserved identifiers `usize` and `size_t` referring to an `inkwell::types::IntType` of the platform-dependent
-/// integer size. `usize` and `size_t` can also be used as the receiver to other method calls, e.g.
-/// `usize.array_type(3)`.
-///
-/// # Example
-///
-/// The following is an example of an LLVM slice implemented using `#[derive(StructFields)]`.
-///
-/// ```rust,ignore
-/// use nac3core::{
-///     codegen::types::structure::StructField,
-///     inkwell::{
-///         values::{IntValue, PointerValue},
-///         AddressSpace,
-///     },
-/// };
-/// use nac3core_derive::StructFields;
-///
-/// // All classes that implement StructFields must also implement Eq and Copy
-/// #[derive(PartialEq, Eq, Clone, Copy, StructFields)]
-/// pub struct SliceValue<'ctx> {
-///     // Declares ptr have a value type of i8*
-///     //
-///     // Can also be written as `ctx.i8_type().ptr_type(...)` or `context.i8_type().ptr_type(...)`
-///     #[value_type(i8_type().ptr_type(AddressSpace::default()))]
-///     ptr: StructField<'ctx, PointerValue<'ctx>>,
-///
-///     // Declares len have a value type of usize, depending on the target compilation platform
-///     #[value_type(usize)]
-///     len: StructField<'ctx, IntValue<'ctx>>,
-/// }
-/// ```
-#[proc_macro_derive(StructFields, attributes(value_type))]
-#[proc_macro_error]
-pub fn derive(input: TokenStream) -> TokenStream {
-    let input = parse_macro_input!(input as syn::DeriveInput);
-    let ident = &input.ident;
-
-    let Data::Struct(DataStruct { fields, .. }) = &input.data else {
-        abort!(input, "Only structs with named fields are supported");
-    };
-    if let Err(err_span) =
-        fields
-            .iter()
-            .try_for_each(|field| if field.ident.is_some() { Ok(()) } else { Err(field.span()) })
-    {
-        abort!(err_span, "Only structs with named fields are supported");
-    };
-
-    // Check if struct<'ctx>
-    if input.generics.params.len() != 1 {
-        abort!(input.generics, "Expected exactly 1 generic parameter")
-    }
-
-    let phantom_info = fields
-        .iter()
-        .filter(|field| extract_generic_args("PhantomData", &field.ty).is_some())
-        .map(|field| field.ident.as_ref().unwrap())
-        .cloned()
-        .collect::<Vec<_>>();
-
-    let field_info = fields
-        .iter()
-        .filter(|field| extract_generic_args("PhantomData", &field.ty).is_none())
-        .map(|field| {
-            let ident = field.ident.as_ref().unwrap();
-            let ty = &field.ty;
-
-            let Some(_) = extract_generic_args("StructField", ty) else {
-                abort!(field, "Only StructField and PhantomData are allowed")
-            };
-
-            let attrs = &field.attrs;
-            let Some(value_type_attr) =
-                attrs.iter().find(|attr| attr.path().is_ident("value_type"))
-            else {
-                abort!(field, "Expected #[value_type(...)] attribute for field");
-            };
-
-            let Ok(value_type_expr) = value_type_attr.parse_args::<Expr>() else {
-                abort!(value_type_attr, "Expected expression in #[value_type(...)]");
-            };
-
-            let value_expr_toks = normalize_value_expr(&value_type_expr);
-
-            (ident.clone(), value_expr_toks)
-        })
-        .collect::<Vec<_>>();
-
-    // `<*>::new` impl of `StructField` and `PhantomData` for `StructFields::new`
-    let phantoms_create = phantom_info
-        .iter()
-        .map(|id| quote! { #id: ::std::marker::PhantomData })
-        .collect::<Vec<_>>();
-    let fields_create = field_info
-        .iter()
-        .map(|(id, ty)| {
-            let id_lit = LitStr::new(&id.to_string(), id.span());
-            quote! {
-                #id: ::nac3core::codegen::types::structure::StructField::create(
-                    &mut counter,
-                    #id_lit,
-                    #ty,
-                )
-            }
-        })
-        .collect::<Vec<_>>();
-
-    // `.into()` impl of `StructField` for `StructFields::to_vec`
-    let fields_into =
-        field_info.iter().map(|(id, _)| quote! { self.#id.into() }).collect::<Vec<_>>();
-
-    let impl_block = quote! {
-        impl<'ctx> ::nac3core::codegen::types::structure::StructFields<'ctx> for #ident<'ctx> {
-            fn new(ctx: impl ::nac3core::inkwell::context::AsContextRef<'ctx>, llvm_usize: ::nac3core::inkwell::types::IntType<'ctx>) -> Self {
-                let ctx = unsafe { ::nac3core::inkwell::context::ContextRef::new(ctx.as_ctx_ref()) };
-
-                let mut counter = ::nac3core::codegen::types::structure::FieldIndexCounter::default();
-
-                #ident {
-                    #(#fields_create),*
-                    #(#phantoms_create),*
-                }
-            }
-
-            fn to_vec(&self) -> ::std::vec::Vec<(&'static str, ::nac3core::inkwell::types::BasicTypeEnum<'ctx>)> {
-                vec![
-                    #(#fields_into),*
-                ]
-            }
-        }
-    };
-
-    impl_block.into()
-}

nac3core/nac3core_derive/tests/structfields_empty.rs

@@ -1,9 +0,0 @@
-use nac3core_derive::StructFields;
-use std::marker::PhantomData;
-
-#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
-pub struct EmptyValue<'ctx> {
-    _phantom: PhantomData<&'ctx ()>,
-}
-
-fn main() {}

nac3core/nac3core_derive/tests/structfields_ndarray.rs

@@ -1,20 +0,0 @@
-use nac3core::{
-    codegen::types::structure::StructField,
-    inkwell::{
-        values::{IntValue, PointerValue},
-        AddressSpace,
-    },
-};
-use nac3core_derive::StructFields;
-
-#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
-pub struct NDArrayValue<'ctx> {
-    #[value_type(usize)]
-    ndims: StructField<'ctx, IntValue<'ctx>>,
-    #[value_type(usize.ptr_type(AddressSpace::default()))]
-    shape: StructField<'ctx, PointerValue<'ctx>>,
-    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
-    data: StructField<'ctx, PointerValue<'ctx>>,
-}
-
-fn main() {}

nac3core/nac3core_derive/tests/structfields_slice.rs

@@ -1,18 +0,0 @@
-use nac3core::{
-    codegen::types::structure::StructField,
-    inkwell::{
-        values::{IntValue, PointerValue},
-        AddressSpace,
-    },
-};
-use nac3core_derive::StructFields;
-
-#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
-pub struct SliceValue<'ctx> {
-    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
-    ptr: StructField<'ctx, PointerValue<'ctx>>,
-    #[value_type(usize)]
-    len: StructField<'ctx, IntValue<'ctx>>,
-}
-
-fn main() {}

nac3core/nac3core_derive/tests/structfields_slice_context.rs

@@ -1,18 +0,0 @@
-use nac3core::{
-    codegen::types::structure::StructField,
-    inkwell::{
-        values::{IntValue, PointerValue},
-        AddressSpace,
-    },
-};
-use nac3core_derive::StructFields;
-
-#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
-pub struct SliceValue<'ctx> {
-    #[value_type(context.i8_type().ptr_type(AddressSpace::default()))]
-    ptr: StructField<'ctx, PointerValue<'ctx>>,
-    #[value_type(usize)]
-    len: StructField<'ctx, IntValue<'ctx>>,
-}
-
-fn main() {}

nac3core/nac3core_derive/tests/structfields_slice_ctx.rs

@@ -1,18 +0,0 @@
-use nac3core::{
-    codegen::types::structure::StructField,
-    inkwell::{
-        values::{IntValue, PointerValue},
-        AddressSpace,
-    },
-};
-use nac3core_derive::StructFields;
-
-#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
-pub struct SliceValue<'ctx> {
-    #[value_type(ctx.i8_type().ptr_type(AddressSpace::default()))]
-    ptr: StructField<'ctx, PointerValue<'ctx>>,
-    #[value_type(usize)]
-    len: StructField<'ctx, IntValue<'ctx>>,
-}
-
-fn main() {}

nac3core/nac3core_derive/tests/structfields_slice_sizet.rs

@@ -1,18 +0,0 @@
-use nac3core::{
-    codegen::types::structure::StructField,
-    inkwell::{
-        values::{IntValue, PointerValue},
-        AddressSpace,
-    },
-};
-use nac3core_derive::StructFields;
-
-#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
-pub struct SliceValue<'ctx> {
-    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
-    ptr: StructField<'ctx, PointerValue<'ctx>>,
-    #[value_type(size_t)]
-    len: StructField<'ctx, IntValue<'ctx>>,
-}
-
-fn main() {}

nac3core/nac3core_derive/tests/structfields_test.rs

@@ -1,10 +0,0 @@
-#[test]
-fn test_parse_empty() {
-    let t = trybuild::TestCases::new();
-    t.pass("tests/structfields_empty.rs");
-    t.pass("tests/structfields_slice.rs");
-    t.pass("tests/structfields_slice_ctx.rs");
-    t.pass("tests/structfields_slice_context.rs");
-    t.pass("tests/structfields_slice_sizet.rs");
-    t.pass("tests/structfields_ndarray.rs");
-}

nac3core/src/codegen/expr.rs

@@ -8,10 +8,13 @@ use std::{
 use inkwell::{
     attributes::{Attribute, AttributeLoc},
     types::{AnyType, BasicType, BasicTypeEnum},
-    values::{BasicValueEnum, CallSiteValue, FunctionValue, IntValue, PointerValue, StructValue},
+    values::{
+        BasicValue, BasicValueEnum, CallSiteValue, FunctionValue, IntValue, PointerValue,
+        StructValue,
+    },
     AddressSpace, IntPredicate, OptimizationLevel,
 };
-use itertools::{izip, Either, Itertools};
+use itertools::{chain, izip, Either, Itertools};
 
 use nac3parser::ast::{
     self, Boolop, Cmpop, Comprehension, Constant, Expr, ExprKind, Location, Operator, StrRef,
@@ -19,34 +22,35 @@ use nac3parser::ast::{
 };
 
 use super::{
+    classes::{
+        ArrayLikeIndexer, ArrayLikeValue, ListType, ListValue, ProxyType, ProxyValue, RangeValue,
+        UntypedArrayLikeAccessor,
+    },
     concrete_type::{ConcreteFuncArg, ConcreteTypeEnum, ConcreteTypeStore},
     gen_in_range_check, get_llvm_abi_type, get_llvm_type, get_va_count_arg_name,
     irrt::*,
     llvm_intrinsics::{
         call_expect, call_float_floor, call_float_pow, call_float_powi, call_int_smax,
-        call_memcpy_generic,
+        call_int_umin, call_memcpy_generic,
     },
     macros::codegen_unreachable,
     need_sret,
+    object::{
+        any::AnyObject,
+        ndarray::{
+            indexing::util::gen_ndarray_subscript_ndindices, NDArrayObject, NDArrayOut,
+            ScalarOrNDArray,
+        },
+    },
     stmt::{
         gen_for_callback_incrementing, gen_if_callback, gen_if_else_expr_callback, gen_raise,
         gen_var,
     },
-    types::{ndarray::NDArrayType, ListType},
-    values::{
-        ndarray::{NDArrayOut, RustNDIndex, ScalarOrNDArray},
-        ArrayLikeIndexer, ArrayLikeValue, ListValue, ProxyValue, RangeValue,
-        UntypedArrayLikeAccessor,
-    },
     CodeGenContext, CodeGenTask, CodeGenerator,
 };
 use crate::{
     symbol_resolver::{SymbolValue, ValueEnum},
-    toplevel::{
+    toplevel::{helper::PrimDef, DefinitionId, TopLevelDef},
-        helper::{arraylike_flatten_element_type, PrimDef},
-        numpy::unpack_ndarray_var_tys,
-        DefinitionId, TopLevelDef,
-    },
     typecheck::{
         magic_methods::{Binop, BinopVariant, HasOpInfo},
         typedef::{FunSignature, FuncArg, Type, TypeEnum, TypeVarId, Unifier, VarMap},
@@ -1095,6 +1099,33 @@ pub fn destructure_range<'ctx>(
     (start, end, step)
 }
 
+/// Allocates a List structure with the given [type][ty] and [length]. The name of the resulting
+/// LLVM value is `{name}.addr`, or `list.addr` if [name] is not specified.
+///
+/// Setting `ty` to [`None`] implies that the list is empty **and** does not have a known element
+/// type, and will therefore set the `list.data` type as `size_t*`. It is undefined behavior to
+/// generate a sized list with an unknown element type.
+pub fn allocate_list<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ty: Option<BasicTypeEnum<'ctx>>,
+    length: IntValue<'ctx>,
+    name: Option<&'ctx str>,
+) -> ListValue<'ctx> {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_elem_ty = ty.unwrap_or(llvm_usize.into());
+
+    // List structure; type { ty*, size_t }
+    let arr_ty = ListType::new(generator, ctx.ctx, llvm_elem_ty);
+    let list = arr_ty.new_value(generator, ctx, name);
+
+    let length = ctx.builder.build_int_z_extend(length, llvm_usize, "").unwrap();
+    list.store_size(ctx, generator, length);
+    list.create_data(ctx, llvm_elem_ty, None);
+
+    list
+}
+
 /// Generates LLVM IR for a [list comprehension expression][expr].
 pub fn gen_comprehension<'ctx, G: CodeGenerator>(
     generator: &mut G,
@@ -1142,8 +1173,7 @@ pub fn gen_comprehension<'ctx, G: CodeGenerator>(
         TypeEnum::TObj { obj_id, .. }
             if *obj_id == ctx.primitives.range.obj_id(&ctx.unifier).unwrap() =>
         {
-            let iter_val =
+            let iter_val = RangeValue::from_ptr_val(iter_val.into_pointer_value(), Some("range"));
-                RangeValue::from_pointer_value(iter_val.into_pointer_value(), Some("range"));
             let (start, stop, step) = destructure_range(ctx, iter_val);
             let diff = ctx.builder.build_int_sub(stop, start, "diff").unwrap();
             // add 1 to the length as the value is rounded to zero
@@ -1167,11 +1197,12 @@ pub fn gen_comprehension<'ctx, G: CodeGenerator>(
                     "listcomp.alloc_size",
                 )
                 .unwrap();
-            list = ListType::new(generator, ctx.ctx, elem_ty).construct(
+            list = allocate_list(
                 generator,
                 ctx,
+                Some(elem_ty),
                 list_alloc_size.into_int_value(),
-                Some("listcomp"),
+                Some("listcomp.addr"),
             );
 
             let i = generator.gen_store_target(ctx, target, Some("i.addr"))?.unwrap();
@@ -1218,12 +1249,7 @@ pub fn gen_comprehension<'ctx, G: CodeGenerator>(
                     Some("length"),
                 )
                 .into_int_value();
-            list = ListType::new(generator, ctx.ctx, elem_ty).construct(
+            list = allocate_list(generator, ctx, Some(elem_ty), length, Some("listcomp"));
-                generator,
-                ctx,
-                length,
-                Some("listcomp"),
-            );
 
             let counter = generator.gen_var_alloc(ctx, size_t.into(), Some("counter.addr"))?;
             // counter = -1
@@ -1378,18 +1404,15 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
                 let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty1);
                 let sizeof_elem = llvm_elem_ty.size_of().unwrap();
 
-                let lhs =
+                let lhs = ListValue::from_ptr_val(left_val.into_pointer_value(), llvm_usize, None);
-                    ListValue::from_pointer_value(left_val.into_pointer_value(), llvm_usize, None);
+                let rhs = ListValue::from_ptr_val(right_val.into_pointer_value(), llvm_usize, None);
-                let rhs =
-                    ListValue::from_pointer_value(right_val.into_pointer_value(), llvm_usize, None);
 
                 let size = ctx
                     .builder
                     .build_int_add(lhs.load_size(ctx, None), rhs.load_size(ctx, None), "")
                     .unwrap();
 
-                let new_list = ListType::new(generator, ctx.ctx, llvm_elem_ty)
+                let new_list = allocate_list(generator, ctx, Some(llvm_elem_ty), size, None);
-                    .construct(generator, ctx, size, None);
 
                 let lhs_size = ctx
                     .builder
@@ -1465,7 +1488,7 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
                         codegen_unreachable!(ctx)
                     };
                 let list_val =
-                    ListValue::from_pointer_value(list_val.into_pointer_value(), llvm_usize, None);
+                    ListValue::from_ptr_val(list_val.into_pointer_value(), llvm_usize, None);
                 let int_val = ctx
                     .builder
                     .build_int_s_extend(int_val.into_int_value(), llvm_usize, "")
@@ -1476,9 +1499,10 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
                 let elem_llvm_ty = ctx.get_llvm_type(generator, elem_ty);
                 let sizeof_elem = elem_llvm_ty.size_of().unwrap();
 
-                let new_list = ListType::new(generator, ctx.ctx, elem_llvm_ty).construct(
+                let new_list = allocate_list(
                     generator,
                     ctx,
+                    Some(elem_llvm_ty),
                     ctx.builder.build_int_mul(list_val.load_size(ctx, None), int_val, "").unwrap(),
                     None,
                 );
@@ -1531,23 +1555,21 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
     } else if ty1.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id())
         || ty2.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id())
     {
-        let left = ScalarOrNDArray::from_value(generator, ctx, (ty1, left_val));
+        let left =
-        let right = ScalarOrNDArray::from_value(generator, ctx, (ty2, right_val));
+            ScalarOrNDArray::split_object(generator, ctx, AnyObject { ty: ty1, value: left_val });
-
+        let right =
-        let ty1_dtype = arraylike_flatten_element_type(&mut ctx.unifier, ty1);
+            ScalarOrNDArray::split_object(generator, ctx, AnyObject { ty: ty2, value: right_val });
-        let ty2_dtype = arraylike_flatten_element_type(&mut ctx.unifier, ty2);
 
         // Inhomogeneous binary operations are not supported.
-        assert!(ctx.unifier.unioned(ty1_dtype, ty2_dtype));
+        assert!(ctx.unifier.unioned(left.get_dtype(), right.get_dtype()));
 
-        let common_dtype = ty1_dtype;
+        let common_dtype = left.get_dtype();
-        let llvm_common_dtype = left.get_dtype();
 
         let out = match op.variant {
-            BinopVariant::Normal => NDArrayOut::NewNDArray { dtype: llvm_common_dtype },
+            BinopVariant::Normal => NDArrayOut::NewNDArray { dtype: common_dtype },
             BinopVariant::AugAssign => {
-                // Augmented assignment - `left` has to be an ndarray. If it were a scalar then NAC3
+                // If this is an augmented assignment.
-                // simply doesn't support it.
+                // `left` has to be an ndarray. If it were a scalar then NAC3 simply doesn't support it.
                 if let ScalarOrNDArray::NDArray(out_ndarray) = left {
                     NDArrayOut::WriteToNDArray { ndarray: out_ndarray }
                 } else {
@@ -1557,12 +1579,12 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
         };
 
         if op.base == Operator::MatMult {
+            // Handle matrix multiplication.
             let left = left.to_ndarray(generator, ctx);
             let right = right.to_ndarray(generator, ctx);
-            let result = left
+            let result = NDArrayObject::matmul(generator, ctx, left, right, out)
-                .matmul(generator, ctx, ty1, (ty2, right), (common_dtype, out))
                 .split_unsized(generator, ctx);
-            Ok(Some(result.to_basic_value_enum().into()))
+            Ok(Some(ValueEnum::Dynamic(result.to_basic_value_enum())))
         } else {
             // For other operations, they are all elementwise operations.
 
@@ -1577,31 +1599,31 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
             let left = left.to_ndarray(generator, ctx);
             let right = right.to_ndarray(generator, ctx);
 
-            let result = NDArrayType::new_broadcast(
+            let result = NDArrayObject::broadcast_starmap(
                 generator,
-                ctx.ctx,
+                ctx,
-                llvm_common_dtype,
+                &[left, right],
-                &[left.get_type(), right.get_type()],
+                out,
+                |generator, ctx, scalars| {
+                    let left_value = scalars[0];
+                    let right_value = scalars[1];
+
+                    let result = gen_binop_expr_with_values(
+                        generator,
+                        ctx,
+                        (&Some(left.dtype), left_value),
+                        op,
+                        (&Some(right.dtype), right_value),
+                        ctx.current_loc,
+                    )?
+                    .unwrap()
+                    .to_basic_value_enum(ctx, generator, common_dtype)?;
+
+                    Ok(result)
+                },
             )
-            .broadcast_starmap(generator, ctx, &[left, right], out, |generator, ctx, scalars| {
-                let left_value = scalars[0];
-                let right_value = scalars[1];
-
-                let result = gen_binop_expr_with_values(
-                    generator,
-                    ctx,
-                    (&Some(ty1_dtype), left_value),
-                    op,
-                    (&Some(ty2_dtype), right_value),
-                    ctx.current_loc,
-                )?
-                .unwrap()
-                .to_basic_value_enum(ctx, generator, common_dtype)?;
-
-                Ok(result)
-            })
             .unwrap();
-            Ok(Some(result.as_base_value().into()))
+            Ok(Some(ValueEnum::Dynamic(result.instance.value.as_basic_value_enum())))
         }
     } else {
         let left_ty_enum = ctx.unifier.get_ty_immutable(left_ty.unwrap());
@@ -1737,12 +1759,7 @@ pub fn gen_unaryop_expr_with_values<'ctx, G: CodeGenerator>(
             ast::Unaryop::Invert => ctx.builder.build_not(val, "not").map(Into::into).unwrap(),
             ast::Unaryop::Not => ctx
                 .builder
-                .build_int_compare(
+                .build_xor(val, val.get_type().const_all_ones(), "not")
-                    inkwell::IntPredicate::EQ,
-                    val,
-                    val.get_type().const_zero(),
-                    "not",
-                )
                 .map(Into::into)
                 .unwrap(),
             ast::Unaryop::UAdd => val.into(),
@@ -1764,14 +1781,12 @@ pub fn gen_unaryop_expr_with_values<'ctx, G: CodeGenerator>(
             _ => val.into(),
         }
     } else if ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) {
-        let (ndarray_dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
+        let ndarray = AnyObject { value: val, ty };
-
+        let ndarray = NDArrayObject::from_object(generator, ctx, ndarray);
-        let ndarray = NDArrayType::from_unifier_type(generator, ctx, ty)
-            .map_value(val.into_pointer_value(), None);
 
         // ndarray uses `~` rather than `not` to perform elementwise inversion, convert it before
         // passing it to the elementwise codegen function
-        let op = if ndarray_dtype.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::Bool.id()) {
+        let op = if ndarray.dtype.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::Bool.id()) {
             if op == ast::Unaryop::Invert {
                 ast::Unaryop::Not
             } else {
@@ -1788,15 +1803,15 @@ pub fn gen_unaryop_expr_with_values<'ctx, G: CodeGenerator>(
         let mapped_ndarray = ndarray.map(
             generator,
             ctx,
-            NDArrayOut::NewNDArray { dtype: ndarray.get_type().element_type() },
+            NDArrayOut::NewNDArray { dtype: ndarray.dtype },
             |generator, ctx, scalar| {
-                gen_unaryop_expr_with_values(generator, ctx, op, (&Some(ndarray_dtype), scalar))?
+                gen_unaryop_expr_with_values(generator, ctx, op, (&Some(ndarray.dtype), scalar))?
-                    .map(|val| val.to_basic_value_enum(ctx, generator, ndarray_dtype))
                     .unwrap()
+                    .to_basic_value_enum(ctx, generator, ndarray.dtype)
             },
         )?;
 
-        mapped_ndarray.as_base_value().into()
+        ValueEnum::Dynamic(mapped_ndarray.instance.value.as_basic_value_enum())
     } else {
         unimplemented!()
     }))
@@ -1843,25 +1858,19 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
             let (Some(right_ty), right) = comparators[0] else { codegen_unreachable!(ctx) };
             let op = ops[0];
 
-            let left_ty_dtype = arraylike_flatten_element_type(&mut ctx.unifier, left_ty);
+            let left = AnyObject { value: left, ty: left_ty };
-            let right_ty_dtype = arraylike_flatten_element_type(&mut ctx.unifier, right_ty);
+            let left =
+                ScalarOrNDArray::split_object(generator, ctx, left).to_ndarray(generator, ctx);
 
-            let left = ScalarOrNDArray::from_value(generator, ctx, (left_ty, left))
+            let right = AnyObject { value: right, ty: right_ty };
-                .to_ndarray(generator, ctx);
+            let right =
-            let right = ScalarOrNDArray::from_value(generator, ctx, (right_ty, right))
+                ScalarOrNDArray::split_object(generator, ctx, right).to_ndarray(generator, ctx);
-                .to_ndarray(generator, ctx);
 
-            let result_ndarray = NDArrayType::new_broadcast(
+            let result_ndarray = NDArrayObject::broadcast_starmap(
-                generator,
-                ctx.ctx,
-                ctx.ctx.i8_type().into(),
-                &[left.get_type(), right.get_type()],
-            )
-            .broadcast_starmap(
                 generator,
                 ctx,
                 &[left, right],
-                NDArrayOut::NewNDArray { dtype: ctx.ctx.i8_type().into() },
+                NDArrayOut::NewNDArray { dtype: ctx.primitives.bool },
                 |generator, ctx, scalars| {
                     let left_scalar = scalars[0];
                     let right_scalar = scalars[1];
@@ -1869,9 +1878,9 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
                     let val = gen_cmpop_expr_with_values(
                         generator,
                         ctx,
-                        (Some(left_ty_dtype), left_scalar),
+                        (Some(left.dtype), left_scalar),
                         &[op],
-                        &[(Some(right_ty_dtype), right_scalar)],
+                        &[(Some(right.dtype), right_scalar)],
                     )?
                     .unwrap()
                     .to_basic_value_enum(
@@ -1884,11 +1893,11 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
                 },
             )?;
 
-            return Ok(Some(result_ndarray.as_base_value().into()));
+            return Ok(Some(result_ndarray.instance.value.into()));
         }
     }
 
-    let cmp_val = izip!(once(&left).chain(comparators.iter()), comparators.iter(), ops.iter(),)
+    let cmp_val = izip!(chain(once(&left), comparators.iter()), comparators.iter(), ops.iter(),)
         .fold(Ok(None), |prev: Result<Option<_>, String>, (lhs, rhs, op)| {
             let (left_ty, lhs) = lhs;
             let (right_ty, rhs) = rhs;
@@ -1968,43 +1977,111 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
             } else if left_ty == ctx.primitives.str {
                 assert!(ctx.unifier.unioned(left_ty, right_ty));
 
-                let lhs = lhs.into_struct_value();
+                let llvm_i1 = ctx.ctx.bool_type();
-                let rhs = rhs.into_struct_value();
-
                 let llvm_i32 = ctx.ctx.i32_type();
                 let llvm_usize = generator.get_size_type(ctx.ctx);
 
+                let lhs = lhs.into_struct_value();
+                let rhs = rhs.into_struct_value();
+
                 let plhs = generator.gen_var_alloc(ctx, lhs.get_type().into(), None).unwrap();
                 ctx.builder.build_store(plhs, lhs).unwrap();
                 let prhs = generator.gen_var_alloc(ctx, lhs.get_type().into(), None).unwrap();
                 ctx.builder.build_store(prhs, rhs).unwrap();
 
-                let lhs_ptr = ctx.build_in_bounds_gep_and_load(
-                    plhs,
-                    &[llvm_usize.const_zero(), llvm_i32.const_zero()],
-                    None,
-                ).into_pointer_value();
                 let lhs_len = ctx.build_in_bounds_gep_and_load(
                     plhs,
-                    &[llvm_usize.const_zero(), llvm_i32.const_int(1, false)],
+                    &[llvm_i32.const_zero(), llvm_i32.const_int(1, false)],
+                    None,
+                ).into_int_value();
+                let rhs_len = ctx.build_in_bounds_gep_and_load(
+                    prhs,
+                    &[llvm_i32.const_zero(), llvm_i32.const_int(1, false)],
                     None,
                 ).into_int_value();
 
-                let rhs_ptr = ctx.build_in_bounds_gep_and_load(
+                let len = call_int_umin(ctx, lhs_len, rhs_len, None);
-                    prhs,
+
-                    &[llvm_usize.const_zero(), llvm_i32.const_zero()],
+                let current_bb = ctx.builder.get_insert_block().unwrap();
+                let post_foreach_cmp = ctx.ctx.insert_basic_block_after(current_bb, "foreach.cmp.end");
+
+                ctx.builder.position_at_end(post_foreach_cmp);
+                let cmp_phi = ctx.builder.build_phi(llvm_i1, "").unwrap();
+                ctx.builder.position_at_end(current_bb);
+
+                gen_for_callback_incrementing(
+                    generator,
+                    ctx,
                     None,
-                ).into_pointer_value();
+                    llvm_usize.const_zero(),
-                let rhs_len = ctx.build_in_bounds_gep_and_load(
+                    (len, false),
-                    prhs,
+                    |generator, ctx, _, i| {
-                    &[llvm_usize.const_zero(), llvm_i32.const_int(1, false)],
+                        let lhs_char = {
-                    None,
+                            let plhs_data = ctx.build_in_bounds_gep_and_load(
-                ).into_int_value();
+                                plhs,
-                let result = call_string_eq(generator, ctx, lhs_ptr, lhs_len, rhs_ptr, rhs_len);
+                                &[llvm_i32.const_zero(), llvm_i32.const_zero()],
+                                None,
+                            ).into_pointer_value();
+
+                            ctx.build_in_bounds_gep_and_load(
+                                plhs_data,
+                                &[i],
+                                None
+                            ).into_int_value()
+                        };
+                        let rhs_char = {
+                            let prhs_data = ctx.build_in_bounds_gep_and_load(
+                                prhs,
+                                &[llvm_i32.const_zero(), llvm_i32.const_zero()],
+                                None,
+                            ).into_pointer_value();
+
+                            ctx.build_in_bounds_gep_and_load(
+                                prhs_data,
+                                &[i],
+                                None
+                            ).into_int_value()
+                        };
+
+                        gen_if_callback(
+                            generator,
+                            ctx,
+                            |_, ctx| {
+                                Ok(ctx.builder.build_int_compare(IntPredicate::NE, lhs_char, rhs_char, "").unwrap())
+                            },
+                            |_, ctx| {
+                                let bb = ctx.builder.get_insert_block().unwrap();
+                                cmp_phi.add_incoming(&[(&llvm_i1.const_zero(), bb)]);
+                                ctx.builder.build_unconditional_branch(post_foreach_cmp).unwrap();
+
+                                Ok(())
+                            },
+                            |_, _| Ok(()),
+                        )?;
+
+                        Ok(())
+                    },
+                    llvm_usize.const_int(1, false),
+                )?;
+
+                let bb = ctx.builder.get_insert_block().unwrap();
+                let is_len_eq = ctx.builder.build_int_compare(
+                    IntPredicate::EQ,
+                    lhs_len,
+                    rhs_len,
+                    "",
+                ).unwrap();
+                cmp_phi.add_incoming(&[(&is_len_eq, bb)]);
+                ctx.builder.build_unconditional_branch(post_foreach_cmp).unwrap();
+
+                ctx.builder.position_at_end(post_foreach_cmp);
+                let cmp_phi = cmp_phi.as_basic_value().into_int_value();
+
+                // Invert the final value if __ne__
                 if *op == Cmpop::NotEq {
-                    ctx.builder.build_not(result, "").unwrap() 
+                    ctx.builder.build_not(cmp_phi, "").unwrap()
                 } else {
-                    result
+                    cmp_phi
                 }
             } else if [left_ty, right_ty]
                 .iter()
@@ -2058,9 +2135,9 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
                     }
 
                     let left_val =
-                        ListValue::from_pointer_value(lhs.into_pointer_value(), llvm_usize, None);
+                        ListValue::from_ptr_val(lhs.into_pointer_value(), llvm_usize, None);
                     let right_val =
-                        ListValue::from_pointer_value(rhs.into_pointer_value(), llvm_usize, None);
+                        ListValue::from_ptr_val(rhs.into_pointer_value(), llvm_usize, None);
 
                     Ok(gen_if_else_expr_callback(
                         generator,
@@ -2481,20 +2558,7 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
                 Some(elements[0].get_type())
             };
             let length = generator.get_size_type(ctx.ctx).const_int(elements.len() as u64, false);
-            let arr_str_ptr = if let Some(ty) = ty {
+            let arr_str_ptr = allocate_list(generator, ctx, ty, length, Some("list"));
-                ListType::new(generator, ctx.ctx, ty).construct(
-                    generator,
-                    ctx,
-                    length,
-                    Some("list"),
-                )
-            } else {
-                ListType::new_untyped(generator, ctx.ctx).construct_empty(
-                    generator,
-                    ctx,
-                    Some("list"),
-                )
-            };
             let arr_ptr = arr_str_ptr.data();
             for (i, v) in elements.iter().enumerate() {
                 let elem_ptr = arr_ptr.ptr_offset(
@@ -2646,53 +2710,48 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
             };
             let left = generator.bool_to_i1(ctx, left);
             let current = ctx.builder.get_insert_block().unwrap().get_parent().unwrap();
-            let a_begin_bb = ctx.ctx.append_basic_block(current, "a_begin");
+            let a_bb = ctx.ctx.append_basic_block(current, "a");
-            let a_end_bb = ctx.ctx.append_basic_block(current, "a_end");
+            let b_bb = ctx.ctx.append_basic_block(current, "b");
-            let b_begin_bb = ctx.ctx.append_basic_block(current, "b_begin");
-            let b_end_bb = ctx.ctx.append_basic_block(current, "b_end");
             let cont_bb = ctx.ctx.append_basic_block(current, "cont");
-            ctx.builder.build_conditional_branch(left, a_begin_bb, b_begin_bb).unwrap();
+            ctx.builder.build_conditional_branch(left, a_bb, b_bb).unwrap();
-
-            ctx.builder.position_at_end(a_end_bb);
-            ctx.builder.build_unconditional_branch(cont_bb).unwrap();
-            ctx.builder.position_at_end(b_end_bb);
-            ctx.builder.build_unconditional_branch(cont_bb).unwrap();
             let (a, b) = match op {
                 Boolop::Or => {
-                    ctx.builder.position_at_end(a_begin_bb);
+                    ctx.builder.position_at_end(a_bb);
                     let a = ctx.ctx.i8_type().const_int(1, false);
-                    ctx.builder.build_unconditional_branch(a_end_bb).unwrap();
+                    ctx.builder.build_unconditional_branch(cont_bb).unwrap();
 
-                    ctx.builder.position_at_end(b_begin_bb);
+                    ctx.builder.position_at_end(b_bb);
                     let b = if let Some(v) = generator.gen_expr(ctx, &values[1])? {
                         let b = v
                             .to_basic_value_enum(ctx, generator, values[1].custom.unwrap())?
                             .into_int_value();
                         let b = generator.bool_to_i8(ctx, b);
+                        ctx.builder.build_unconditional_branch(cont_bb).unwrap();
+
                         Some(b)
                     } else {
                         None
                     };
-                    ctx.builder.build_unconditional_branch(b_end_bb).unwrap();
 
                     (Some(a), b)
                 }
                 Boolop::And => {
-                    ctx.builder.position_at_end(a_begin_bb);
+                    ctx.builder.position_at_end(a_bb);
                     let a = if let Some(v) = generator.gen_expr(ctx, &values[1])? {
                         let a = v
                             .to_basic_value_enum(ctx, generator, values[1].custom.unwrap())?
                             .into_int_value();
                         let a = generator.bool_to_i8(ctx, a);
+                        ctx.builder.build_unconditional_branch(cont_bb).unwrap();
+
                         Some(a)
                     } else {
                         None
                     };
-                    ctx.builder.build_unconditional_branch(a_end_bb).unwrap();
 
-                    ctx.builder.position_at_end(b_begin_bb);
+                    ctx.builder.position_at_end(b_bb);
                     let b = ctx.ctx.i8_type().const_zero();
-                    ctx.builder.build_unconditional_branch(b_end_bb).unwrap();
+                    ctx.builder.build_unconditional_branch(cont_bb).unwrap();
 
                     (a, Some(b))
                 }
@@ -2702,7 +2761,7 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
             match (a, b) {
                 (Some(a), Some(b)) => {
                     let phi = ctx.builder.build_phi(ctx.ctx.i8_type(), "").unwrap();
-                    phi.add_incoming(&[(&a, a_end_bb), (&b, b_end_bb)]);
+                    phi.add_incoming(&[(&a, a_bb), (&b, b_bb)]);
                     phi.as_basic_value().into()
                 }
                 (Some(a), None) => a.into(),
@@ -2940,7 +2999,7 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
                     } else {
                         return Ok(None);
                     };
-                    let v = ListValue::from_pointer_value(v, usize, Some("arr"));
+                    let v = ListValue::from_ptr_val(v, usize, Some("arr"));
                     let ty = ctx.get_llvm_type(generator, *ty);
                     if let ExprKind::Slice { lower, upper, step } = &slice.node {
                         let one = int32.const_int(1, false);
@@ -2972,12 +3031,8 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
                                 .unwrap(),
                             step,
                         );
-                        let res_array_ret = ListType::new(generator, ctx.ctx, ty).construct(
+                        let res_array_ret =
-                            generator,
+                            allocate_list(generator, ctx, Some(ty), length, Some("ret"));
-                            ctx,
-                            length,
-                            Some("ret"),
-                        );
                         let Some(res_ind) = handle_slice_indices(
                             &None,
                             &None,
@@ -3052,10 +3107,14 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
 
                     let ndarray_ty = value.custom.unwrap();
                     let ndarray = ndarray.to_basic_value_enum(ctx, generator, ndarray_ty)?;
-                    let ndarray = NDArrayType::from_unifier_type(generator, ctx, ndarray_ty)
-                        .map_value(ndarray.into_pointer_value(), None);
 
-                    let indices = RustNDIndex::from_subscript_expr(generator, ctx, slice)?;
+                    let ndarray = NDArrayObject::from_object(
+                        generator,
+                        ctx,
+                        AnyObject { ty: ndarray_ty, value: ndarray },
+                    );
+
+                    let indices = gen_ndarray_subscript_ndindices(generator, ctx, slice)?;
                     let result = ndarray
                         .index(generator, ctx, &indices)
                         .split_unsized(generator, ctx)
@@ -3109,97 +3168,3 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
         _ => unimplemented!(),
     }))
 }
-
-/// Creates a function in the current module and inserts a `call` instruction into the LLVM IR.
-#[allow(clippy::too_many_arguments)]
-pub fn create_fn_and_call<'ctx>(
-    ctx: &CodeGenContext<'ctx, '_>,
-    fn_name: &str,
-    ret_type: Option<BasicTypeEnum<'ctx>>,
-    params: &[BasicTypeEnum<'ctx>],
-    args: &[BasicValueEnum<'ctx>],
-    is_var_args: bool,
-    call_value_name: Option<&str>,
-    configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
-) -> Option<BasicValueEnum<'ctx>> {
-    let intrinsic_fn = ctx.module.get_function(fn_name).unwrap_or_else(|| {
-        let params = params.iter().copied().map(BasicTypeEnum::into).collect_vec();
-        let fn_type = if let Some(ret_type) = ret_type {
-            ret_type.fn_type(params.as_slice(), is_var_args)
-        } else {
-            ctx.ctx.void_type().fn_type(params.as_slice(), is_var_args)
-        };
-
-        ctx.module.add_function(fn_name, fn_type, None)
-    });
-
-    if let Some(configure) = configure {
-        configure(&intrinsic_fn);
-    }
-
-    let args = args.iter().copied().map(BasicValueEnum::into).collect_vec();
-    ctx.builder
-        .build_call(intrinsic_fn, args.as_slice(), call_value_name.unwrap_or_default())
-        .map(CallSiteValue::try_as_basic_value)
-        .map(Either::left)
-        .unwrap()
-}
-
-/// Creates a function in the current module and inserts a `call` instruction into the LLVM IR.
-///
-/// This is a wrapper around [`create_fn_and_call`] for non-vararg function. This function allows
-/// parameters and arguments to be specified as tuples to better indicate the expected type and
-/// actual value of each parameter-argument pair of the call.
-pub fn create_and_call_function<'ctx>(
-    ctx: &CodeGenContext<'ctx, '_>,
-    fn_name: &str,
-    ret_type: Option<BasicTypeEnum<'ctx>>,
-    params: &[(BasicTypeEnum<'ctx>, BasicValueEnum<'ctx>)],
-    value_name: Option<&str>,
-    configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
-) -> Option<BasicValueEnum<'ctx>> {
-    let param_tys = params.iter().map(|(ty, _)| ty).copied().map(BasicTypeEnum::into).collect_vec();
-    let arg_values =
-        params.iter().map(|(_, value)| value).copied().map(BasicValueEnum::into).collect_vec();
-
-    create_fn_and_call(
-        ctx,
-        fn_name,
-        ret_type,
-        param_tys.as_slice(),
-        arg_values.as_slice(),
-        false,
-        value_name,
-        configure,
-    )
-}
-
-/// Creates a function in the current module and inserts a `call` instruction into the LLVM IR.
-///
-/// This is a wrapper around [`create_fn_and_call`] for non-vararg function. This function allows
-/// only arguments to be specified and performs inference for the parameter types of the function
-/// using [`BasicValueEnum::get_type`] on the arguments.
-///
-/// This function is recommended if it is known that all function arguments match the parameter
-/// types of the invoked function.
-pub fn infer_and_call_function<'ctx>(
-    ctx: &CodeGenContext<'ctx, '_>,
-    fn_name: &str,
-    ret_type: Option<BasicTypeEnum<'ctx>>,
-    args: &[BasicValueEnum<'ctx>],
-    value_name: Option<&str>,
-    configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
-) -> Option<BasicValueEnum<'ctx>> {
-    let param_tys = args.iter().map(BasicValueEnum::get_type).collect_vec();
-
-    create_fn_and_call(
-        ctx,
-        fn_name,
-        ret_type,
-        param_tys.as_slice(),
-        args,
-        false,
-        value_name,
-        configure,
-    )
-}

nac3core/src/codegen/generator.rs

@@ -6,7 +6,7 @@ use inkwell::{
 
 use nac3parser::ast::{Expr, Stmt, StrRef};
 
-use super::{bool_to_i1, bool_to_i8, expr::*, stmt::*, values::ArraySliceValue, CodeGenContext};
+use super::{bool_to_i1, bool_to_i8, classes::ArraySliceValue, expr::*, stmt::*, CodeGenContext};
 use crate::{
     symbol_resolver::ValueEnum,
     toplevel::{DefinitionId, TopLevelDef},
@@ -17,7 +17,6 @@ pub trait CodeGenerator {
     /// Return the module name for the code generator.
     fn get_name(&self) -> &str;
 
-    /// Return an instance of [`IntType`] corresponding to the type of `size_t` for this instance.
     fn get_size_type<'ctx>(&self, ctx: &'ctx Context) -> IntType<'ctx>;
 
     /// Generate function call and returns the function return value.

nac3core/src/codegen/irrt/list.rs

@@ -1,174 +0,0 @@
-use inkwell::{
-    types::BasicTypeEnum,
-    values::{BasicValueEnum, CallSiteValue, IntValue},
-    AddressSpace, IntPredicate,
-};
-use itertools::Either;
-
-use super::calculate_len_for_slice_range;
-use crate::codegen::{
-    macros::codegen_unreachable,
-    values::{ArrayLikeValue, ListValue},
-    CodeGenContext, CodeGenerator,
-};
-
-/// This function handles 'end' **inclusively**.
-/// Order of tuples `assign_idx` and `value_idx` is ('start', 'end', 'step').
-/// Negative index should be handled before entering this function
-pub fn list_slice_assignment<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    ty: BasicTypeEnum<'ctx>,
-    dest_arr: ListValue<'ctx>,
-    dest_idx: (IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>),
-    src_arr: ListValue<'ctx>,
-    src_idx: (IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>),
-) {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let llvm_pi8 = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
-    let llvm_i32 = ctx.ctx.i32_type();
-
-    assert_eq!(dest_idx.0.get_type(), llvm_i32);
-    assert_eq!(dest_idx.1.get_type(), llvm_i32);
-    assert_eq!(dest_idx.2.get_type(), llvm_i32);
-    assert_eq!(src_idx.0.get_type(), llvm_i32);
-    assert_eq!(src_idx.1.get_type(), llvm_i32);
-    assert_eq!(src_idx.2.get_type(), llvm_i32);
-
-    let (fun_symbol, elem_ptr_type) = ("__nac3_list_slice_assign_var_size", llvm_pi8);
-    let slice_assign_fun = {
-        let ty_vec = vec![
-            llvm_i32.into(),      // dest start idx
-            llvm_i32.into(),      // dest end idx
-            llvm_i32.into(),      // dest step
-            elem_ptr_type.into(), // dest arr ptr
-            llvm_i32.into(),      // dest arr len
-            llvm_i32.into(),      // src start idx
-            llvm_i32.into(),      // src end idx
-            llvm_i32.into(),      // src step
-            elem_ptr_type.into(), // src arr ptr
-            llvm_i32.into(),      // src arr len
-            llvm_i32.into(),      // size
-        ];
-        ctx.module.get_function(fun_symbol).unwrap_or_else(|| {
-            let fn_t = llvm_i32.fn_type(ty_vec.as_slice(), false);
-            ctx.module.add_function(fun_symbol, fn_t, None)
-        })
-    };
-
-    let zero = llvm_i32.const_zero();
-    let one = llvm_i32.const_int(1, false);
-    let dest_arr_ptr = dest_arr.data().base_ptr(ctx, generator);
-    let dest_arr_ptr =
-        ctx.builder.build_pointer_cast(dest_arr_ptr, elem_ptr_type, "dest_arr_ptr_cast").unwrap();
-    let dest_len = dest_arr.load_size(ctx, Some("dest.len"));
-    let dest_len =
-        ctx.builder.build_int_truncate_or_bit_cast(dest_len, llvm_i32, "srclen32").unwrap();
-    let src_arr_ptr = src_arr.data().base_ptr(ctx, generator);
-    let src_arr_ptr =
-        ctx.builder.build_pointer_cast(src_arr_ptr, elem_ptr_type, "src_arr_ptr_cast").unwrap();
-    let src_len = src_arr.load_size(ctx, Some("src.len"));
-    let src_len =
-        ctx.builder.build_int_truncate_or_bit_cast(src_len, llvm_i32, "srclen32").unwrap();
-
-    // index in bound and positive should be done
-    // assert if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest), and
-    // throw exception if not satisfied
-    let src_end = ctx
-        .builder
-        .build_select(
-            ctx.builder.build_int_compare(IntPredicate::SLT, src_idx.2, zero, "is_neg").unwrap(),
-            ctx.builder.build_int_sub(src_idx.1, one, "e_min_one").unwrap(),
-            ctx.builder.build_int_add(src_idx.1, one, "e_add_one").unwrap(),
-            "final_e",
-        )
-        .map(BasicValueEnum::into_int_value)
-        .unwrap();
-    let dest_end = ctx
-        .builder
-        .build_select(
-            ctx.builder.build_int_compare(IntPredicate::SLT, dest_idx.2, zero, "is_neg").unwrap(),
-            ctx.builder.build_int_sub(dest_idx.1, one, "e_min_one").unwrap(),
-            ctx.builder.build_int_add(dest_idx.1, one, "e_add_one").unwrap(),
-            "final_e",
-        )
-        .map(BasicValueEnum::into_int_value)
-        .unwrap();
-    let src_slice_len =
-        calculate_len_for_slice_range(generator, ctx, src_idx.0, src_end, src_idx.2);
-    let dest_slice_len =
-        calculate_len_for_slice_range(generator, ctx, dest_idx.0, dest_end, dest_idx.2);
-    let src_eq_dest = ctx
-        .builder
-        .build_int_compare(IntPredicate::EQ, src_slice_len, dest_slice_len, "slice_src_eq_dest")
-        .unwrap();
-    let src_slt_dest = ctx
-        .builder
-        .build_int_compare(IntPredicate::SLT, src_slice_len, dest_slice_len, "slice_src_slt_dest")
-        .unwrap();
-    let dest_step_eq_one = ctx
-        .builder
-        .build_int_compare(
-            IntPredicate::EQ,
-            dest_idx.2,
-            dest_idx.2.get_type().const_int(1, false),
-            "slice_dest_step_eq_one",
-        )
-        .unwrap();
-    let cond_1 = ctx.builder.build_and(dest_step_eq_one, src_slt_dest, "slice_cond_1").unwrap();
-    let cond = ctx.builder.build_or(src_eq_dest, cond_1, "slice_cond").unwrap();
-    ctx.make_assert(
-        generator,
-        cond,
-        "0:ValueError",
-        "attempt to assign sequence of size {0} to slice of size {1} with step size {2}",
-        [Some(src_slice_len), Some(dest_slice_len), Some(dest_idx.2)],
-        ctx.current_loc,
-    );
-
-    let new_len = {
-        let args = vec![
-            dest_idx.0.into(),   // dest start idx
-            dest_idx.1.into(),   // dest end idx
-            dest_idx.2.into(),   // dest step
-            dest_arr_ptr.into(), // dest arr ptr
-            dest_len.into(),     // dest arr len
-            src_idx.0.into(),    // src start idx
-            src_idx.1.into(),    // src end idx
-            src_idx.2.into(),    // src step
-            src_arr_ptr.into(),  // src arr ptr
-            src_len.into(),      // src arr len
-            {
-                let s = match ty {
-                    BasicTypeEnum::FloatType(t) => t.size_of(),
-                    BasicTypeEnum::IntType(t) => t.size_of(),
-                    BasicTypeEnum::PointerType(t) => t.size_of(),
-                    BasicTypeEnum::StructType(t) => t.size_of().unwrap(),
-                    _ => codegen_unreachable!(ctx),
-                };
-                ctx.builder.build_int_truncate_or_bit_cast(s, llvm_i32, "size").unwrap()
-            }
-            .into(),
-        ];
-        ctx.builder
-            .build_call(slice_assign_fun, args.as_slice(), "slice_assign")
-            .map(CallSiteValue::try_as_basic_value)
-            .map(|v| v.map_left(BasicValueEnum::into_int_value))
-            .map(Either::unwrap_left)
-            .unwrap()
-    };
-
-    // update length
-    let need_update =
-        ctx.builder.build_int_compare(IntPredicate::NE, new_len, dest_len, "need_update").unwrap();
-    let current = ctx.builder.get_insert_block().unwrap().get_parent().unwrap();
-    let update_bb = ctx.ctx.append_basic_block(current, "update");
-    let cont_bb = ctx.ctx.append_basic_block(current, "cont");
-    ctx.builder.build_conditional_branch(need_update, update_bb, cont_bb).unwrap();
-    ctx.builder.position_at_end(update_bb);
-    let new_len =
-        ctx.builder.build_int_z_extend_or_bit_cast(new_len, llvm_usize, "new_len").unwrap();
-    dest_arr.store_size(ctx, generator, new_len);
-    ctx.builder.build_unconditional_branch(cont_bb).unwrap();
-    ctx.builder.position_at_end(cont_bb);
-}

nac3core/src/codegen/irrt/math.rs

@@ -1,168 +0,0 @@
-use inkwell::{
-    values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue},
-    IntPredicate,
-};
-use itertools::Either;
-
-use crate::codegen::{
-    macros::codegen_unreachable,
-    {CodeGenContext, CodeGenerator},
-};
-
-// repeated squaring method adapted from GNU Scientific Library:
-// https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
-pub fn integer_power<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    base: IntValue<'ctx>,
-    exp: IntValue<'ctx>,
-    signed: bool,
-) -> IntValue<'ctx> {
-    let symbol = match (base.get_type().get_bit_width(), exp.get_type().get_bit_width(), signed) {
-        (32, 32, true) => "__nac3_int_exp_int32_t",
-        (64, 64, true) => "__nac3_int_exp_int64_t",
-        (32, 32, false) => "__nac3_int_exp_uint32_t",
-        (64, 64, false) => "__nac3_int_exp_uint64_t",
-        _ => codegen_unreachable!(ctx),
-    };
-    let base_type = base.get_type();
-    let pow_fun = ctx.module.get_function(symbol).unwrap_or_else(|| {
-        let fn_type = base_type.fn_type(&[base_type.into(), base_type.into()], false);
-        ctx.module.add_function(symbol, fn_type, None)
-    });
-    // throw exception when exp < 0
-    let ge_zero = ctx
-        .builder
-        .build_int_compare(
-            IntPredicate::SGE,
-            exp,
-            exp.get_type().const_zero(),
-            "assert_int_pow_ge_0",
-        )
-        .unwrap();
-    ctx.make_assert(
-        generator,
-        ge_zero,
-        "0:ValueError",
-        "integer power must be positive or zero",
-        [None, None, None],
-        ctx.current_loc,
-    );
-    ctx.builder
-        .build_call(pow_fun, &[base.into(), exp.into()], "call_int_pow")
-        .map(CallSiteValue::try_as_basic_value)
-        .map(|v| v.map_left(BasicValueEnum::into_int_value))
-        .map(Either::unwrap_left)
-        .unwrap()
-}
-
-/// Generates a call to `isinf` in IR. Returns an `i1` representing the result.
-pub fn call_isinf<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    v: FloatValue<'ctx>,
-) -> IntValue<'ctx> {
-    let llvm_i32 = ctx.ctx.i32_type();
-    let llvm_f64 = ctx.ctx.f64_type();
-
-    assert_eq!(v.get_type(), llvm_f64);
-
-    let intrinsic_fn = ctx.module.get_function("__nac3_isinf").unwrap_or_else(|| {
-        let fn_type = llvm_i32.fn_type(&[llvm_f64.into()], false);
-        ctx.module.add_function("__nac3_isinf", fn_type, None)
-    });
-
-    let ret = ctx
-        .builder
-        .build_call(intrinsic_fn, &[v.into()], "isinf")
-        .map(CallSiteValue::try_as_basic_value)
-        .map(|v| v.map_left(BasicValueEnum::into_int_value))
-        .map(Either::unwrap_left)
-        .unwrap();
-
-    generator.bool_to_i1(ctx, ret)
-}
-
-/// Generates a call to `isnan` in IR. Returns an `i1` representing the result.
-pub fn call_isnan<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    v: FloatValue<'ctx>,
-) -> IntValue<'ctx> {
-    let llvm_i32 = ctx.ctx.i32_type();
-    let llvm_f64 = ctx.ctx.f64_type();
-
-    assert_eq!(v.get_type(), llvm_f64);
-
-    let intrinsic_fn = ctx.module.get_function("__nac3_isnan").unwrap_or_else(|| {
-        let fn_type = llvm_i32.fn_type(&[llvm_f64.into()], false);
-        ctx.module.add_function("__nac3_isnan", fn_type, None)
-    });
-
-    let ret = ctx
-        .builder
-        .build_call(intrinsic_fn, &[v.into()], "isnan")
-        .map(CallSiteValue::try_as_basic_value)
-        .map(|v| v.map_left(BasicValueEnum::into_int_value))
-        .map(Either::unwrap_left)
-        .unwrap();
-
-    generator.bool_to_i1(ctx, ret)
-}
-
-/// Generates a call to `gamma` in IR. Returns an `f64` representing the result.
-pub fn call_gamma<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
-    let llvm_f64 = ctx.ctx.f64_type();
-
-    assert_eq!(v.get_type(), llvm_f64);
-
-    let intrinsic_fn = ctx.module.get_function("__nac3_gamma").unwrap_or_else(|| {
-        let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
-        ctx.module.add_function("__nac3_gamma", fn_type, None)
-    });
-
-    ctx.builder
-        .build_call(intrinsic_fn, &[v.into()], "gamma")
-        .map(CallSiteValue::try_as_basic_value)
-        .map(|v| v.map_left(BasicValueEnum::into_float_value))
-        .map(Either::unwrap_left)
-        .unwrap()
-}
-
-/// Generates a call to `gammaln` in IR. Returns an `f64` representing the result.
-pub fn call_gammaln<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
-    let llvm_f64 = ctx.ctx.f64_type();
-
-    assert_eq!(v.get_type(), llvm_f64);
-
-    let intrinsic_fn = ctx.module.get_function("__nac3_gammaln").unwrap_or_else(|| {
-        let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
-        ctx.module.add_function("__nac3_gammaln", fn_type, None)
-    });
-
-    ctx.builder
-        .build_call(intrinsic_fn, &[v.into()], "gammaln")
-        .map(CallSiteValue::try_as_basic_value)
-        .map(|v| v.map_left(BasicValueEnum::into_float_value))
-        .map(Either::unwrap_left)
-        .unwrap()
-}
-
-/// Generates a call to `j0` in IR. Returns an `f64` representing the result.
-pub fn call_j0<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
-    let llvm_f64 = ctx.ctx.f64_type();
-
-    assert_eq!(v.get_type(), llvm_f64);
-
-    let intrinsic_fn = ctx.module.get_function("__nac3_j0").unwrap_or_else(|| {
-        let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
-        ctx.module.add_function("__nac3_j0", fn_type, None)
-    });
-
-    ctx.builder
-        .build_call(intrinsic_fn, &[v.into()], "j0")
-        .map(CallSiteValue::try_as_basic_value)
-        .map(|v| v.map_left(BasicValueEnum::into_float_value))
-        .map(Either::unwrap_left)
-        .unwrap()
-}

nac3core/src/codegen/irrt/mod.rs

@@ -3,26 +3,25 @@ use inkwell::{
     context::Context,
     memory_buffer::MemoryBuffer,
     module::Module,
-    values::{BasicValue, BasicValueEnum, IntValue},
+    types::BasicTypeEnum,
-    IntPredicate,
+    values::{BasicValue, BasicValueEnum, CallSiteValue, FloatValue, IntValue},
+    AddressSpace, IntPredicate,
 };
+use itertools::Either;
 
 use nac3parser::ast::Expr;
 
-use super::{CodeGenContext, CodeGenerator};
+use super::{
+    classes::{ArrayLikeValue, ListValue},
+    macros::codegen_unreachable,
+    model::{function::FnCall, *},
+    object::{
+        list::List,
+        ndarray::{broadcast::ShapeEntry, indexing::NDIndex, nditer::NDIter, NDArray},
+    },
+    CodeGenContext, CodeGenerator,
+};
 use crate::{symbol_resolver::SymbolResolver, typecheck::typedef::Type};
-pub use list::*;
-pub use math::*;
-pub use range::*;
-pub use slice::*;
-pub use string::*;
-
-mod list;
-mod math;
-pub mod ndarray;
-mod range;
-mod slice;
-mod string;
 
 #[must_use]
 pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver) -> Module<'ctx> {
@@ -63,25 +62,86 @@ pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver)
     irrt_mod
 }
 
-/// Returns the name of a function which contains variants for 32-bit and 64-bit `size_t`.
+// repeated squaring method adapted from GNU Scientific Library:
-///
+// https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
-/// - When [`TypeContext::size_type`] is 32-bits, the function name is `fn_name}`.
+pub fn integer_power<'ctx, G: CodeGenerator + ?Sized>(
-/// - When [`TypeContext::size_type`] is 64-bits, the function name is `{fn_name}64`.
+    generator: &mut G,
-#[must_use]
+    ctx: &mut CodeGenContext<'ctx, '_>,
-pub fn get_usize_dependent_function_name<G: CodeGenerator + ?Sized>(
+    base: IntValue<'ctx>,
-    generator: &G,
+    exp: IntValue<'ctx>,
-    ctx: &CodeGenContext<'_, '_>,
+    signed: bool,
-    name: &str,
+) -> IntValue<'ctx> {
-) -> String {
+    let symbol = match (base.get_type().get_bit_width(), exp.get_type().get_bit_width(), signed) {
-    let mut name = name.to_owned();
+        (32, 32, true) => "__nac3_int_exp_int32_t",
-    match generator.get_size_type(ctx.ctx).get_bit_width() {
+        (64, 64, true) => "__nac3_int_exp_int64_t",
-        32 => {}
+        (32, 32, false) => "__nac3_int_exp_uint32_t",
-        64 => name.push_str("64"),
+        (64, 64, false) => "__nac3_int_exp_uint64_t",
-        bit_width => {
+        _ => codegen_unreachable!(ctx),
-            panic!("Unsupported int type bit width {bit_width}, must be either 32-bits or 64-bits")
+    };
-        }
+    let base_type = base.get_type();
-    }
+    let pow_fun = ctx.module.get_function(symbol).unwrap_or_else(|| {
-    name
+        let fn_type = base_type.fn_type(&[base_type.into(), base_type.into()], false);
+        ctx.module.add_function(symbol, fn_type, None)
+    });
+    // throw exception when exp < 0
+    let ge_zero = ctx
+        .builder
+        .build_int_compare(
+            IntPredicate::SGE,
+            exp,
+            exp.get_type().const_zero(),
+            "assert_int_pow_ge_0",
+        )
+        .unwrap();
+    ctx.make_assert(
+        generator,
+        ge_zero,
+        "0:ValueError",
+        "integer power must be positive or zero",
+        [None, None, None],
+        ctx.current_loc,
+    );
+    ctx.builder
+        .build_call(pow_fun, &[base.into(), exp.into()], "call_int_pow")
+        .map(CallSiteValue::try_as_basic_value)
+        .map(|v| v.map_left(BasicValueEnum::into_int_value))
+        .map(Either::unwrap_left)
+        .unwrap()
+}
+
+pub fn calculate_len_for_slice_range<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    start: IntValue<'ctx>,
+    end: IntValue<'ctx>,
+    step: IntValue<'ctx>,
+) -> IntValue<'ctx> {
+    const SYMBOL: &str = "__nac3_range_slice_len";
+    let len_func = ctx.module.get_function(SYMBOL).unwrap_or_else(|| {
+        let i32_t = ctx.ctx.i32_type();
+        let fn_t = i32_t.fn_type(&[i32_t.into(), i32_t.into(), i32_t.into()], false);
+        ctx.module.add_function(SYMBOL, fn_t, None)
+    });
+
+    // assert step != 0, throw exception if not
+    let not_zero = ctx
+        .builder
+        .build_int_compare(IntPredicate::NE, step, step.get_type().const_zero(), "range_step_ne")
+        .unwrap();
+    ctx.make_assert(
+        generator,
+        not_zero,
+        "0:ValueError",
+        "step must not be zero",
+        [None, None, None],
+        ctx.current_loc,
+    );
+    ctx.builder
+        .build_call(len_func, &[start.into(), end.into(), step.into()], "calc_len")
+        .map(CallSiteValue::try_as_basic_value)
+        .map(|v| v.map_left(BasicValueEnum::into_int_value))
+        .map(Either::unwrap_left)
+        .unwrap()
 }
 
 /// NOTE: the output value of the end index of this function should be compared ***inclusively***,
@@ -132,11 +192,10 @@ pub fn handle_slice_indices<'ctx, G: CodeGenerator>(
     generator: &mut G,
     length: IntValue<'ctx>,
 ) -> Result<Option<(IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>)>, String> {
-    let llvm_i32 = ctx.ctx.i32_type();
+    let int32 = ctx.ctx.i32_type();
-
+    let zero = int32.const_zero();
-    let zero = llvm_i32.const_zero();
+    let one = int32.const_int(1, false);
-    let one = llvm_i32.const_int(1, false);
+    let length = ctx.builder.build_int_truncate_or_bit_cast(length, int32, "leni32").unwrap();
-    let length = ctx.builder.build_int_truncate_or_bit_cast(length, llvm_i32, "leni32").unwrap();
     Ok(Some(match (start, end, step) {
         (s, e, None) => (
             if let Some(s) = s.as_ref() {
@@ -145,7 +204,7 @@ pub fn handle_slice_indices<'ctx, G: CodeGenerator>(
                     None => return Ok(None),
                 }
             } else {
-                llvm_i32.const_zero()
+                int32.const_zero()
             },
             {
                 let e = if let Some(s) = e.as_ref() {
@@ -250,3 +309,569 @@ pub fn handle_slice_indices<'ctx, G: CodeGenerator>(
         }
     }))
 }
+
+/// this function allows index out of range, since python
+/// allows index out of range in slice (`a = [1,2,3]; a[1:10] == [2,3]`).
+pub fn handle_slice_index_bound<'ctx, G: CodeGenerator>(
+    i: &Expr<Option<Type>>,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    generator: &mut G,
+    length: IntValue<'ctx>,
+) -> Result<Option<IntValue<'ctx>>, String> {
+    const SYMBOL: &str = "__nac3_slice_index_bound";
+    let func = ctx.module.get_function(SYMBOL).unwrap_or_else(|| {
+        let i32_t = ctx.ctx.i32_type();
+        let fn_t = i32_t.fn_type(&[i32_t.into(), i32_t.into()], false);
+        ctx.module.add_function(SYMBOL, fn_t, None)
+    });
+
+    let i = if let Some(v) = generator.gen_expr(ctx, i)? {
+        v.to_basic_value_enum(ctx, generator, i.custom.unwrap())?
+    } else {
+        return Ok(None);
+    };
+    Ok(Some(
+        ctx.builder
+            .build_call(func, &[i.into(), length.into()], "bounded_ind")
+            .map(CallSiteValue::try_as_basic_value)
+            .map(|v| v.map_left(BasicValueEnum::into_int_value))
+            .map(Either::unwrap_left)
+            .unwrap(),
+    ))
+}
+
+/// This function handles 'end' **inclusively**.
+/// Order of tuples `assign_idx` and `value_idx` is ('start', 'end', 'step').
+/// Negative index should be handled before entering this function
+pub fn list_slice_assignment<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ty: BasicTypeEnum<'ctx>,
+    dest_arr: ListValue<'ctx>,
+    dest_idx: (IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>),
+    src_arr: ListValue<'ctx>,
+    src_idx: (IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>),
+) {
+    let size_ty = generator.get_size_type(ctx.ctx);
+    let int8_ptr = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
+    let int32 = ctx.ctx.i32_type();
+    let (fun_symbol, elem_ptr_type) = ("__nac3_list_slice_assign_var_size", int8_ptr);
+    let slice_assign_fun = {
+        let ty_vec = vec![
+            int32.into(),         // dest start idx
+            int32.into(),         // dest end idx
+            int32.into(),         // dest step
+            elem_ptr_type.into(), // dest arr ptr
+            int32.into(),         // dest arr len
+            int32.into(),         // src start idx
+            int32.into(),         // src end idx
+            int32.into(),         // src step
+            elem_ptr_type.into(), // src arr ptr
+            int32.into(),         // src arr len
+            int32.into(),         // size
+        ];
+        ctx.module.get_function(fun_symbol).unwrap_or_else(|| {
+            let fn_t = int32.fn_type(ty_vec.as_slice(), false);
+            ctx.module.add_function(fun_symbol, fn_t, None)
+        })
+    };
+
+    let zero = int32.const_zero();
+    let one = int32.const_int(1, false);
+    let dest_arr_ptr = dest_arr.data().base_ptr(ctx, generator);
+    let dest_arr_ptr =
+        ctx.builder.build_pointer_cast(dest_arr_ptr, elem_ptr_type, "dest_arr_ptr_cast").unwrap();
+    let dest_len = dest_arr.load_size(ctx, Some("dest.len"));
+    let dest_len = ctx.builder.build_int_truncate_or_bit_cast(dest_len, int32, "srclen32").unwrap();
+    let src_arr_ptr = src_arr.data().base_ptr(ctx, generator);
+    let src_arr_ptr =
+        ctx.builder.build_pointer_cast(src_arr_ptr, elem_ptr_type, "src_arr_ptr_cast").unwrap();
+    let src_len = src_arr.load_size(ctx, Some("src.len"));
+    let src_len = ctx.builder.build_int_truncate_or_bit_cast(src_len, int32, "srclen32").unwrap();
+
+    // index in bound and positive should be done
+    // assert if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest), and
+    // throw exception if not satisfied
+    let src_end = ctx
+        .builder
+        .build_select(
+            ctx.builder.build_int_compare(IntPredicate::SLT, src_idx.2, zero, "is_neg").unwrap(),
+            ctx.builder.build_int_sub(src_idx.1, one, "e_min_one").unwrap(),
+            ctx.builder.build_int_add(src_idx.1, one, "e_add_one").unwrap(),
+            "final_e",
+        )
+        .map(BasicValueEnum::into_int_value)
+        .unwrap();
+    let dest_end = ctx
+        .builder
+        .build_select(
+            ctx.builder.build_int_compare(IntPredicate::SLT, dest_idx.2, zero, "is_neg").unwrap(),
+            ctx.builder.build_int_sub(dest_idx.1, one, "e_min_one").unwrap(),
+            ctx.builder.build_int_add(dest_idx.1, one, "e_add_one").unwrap(),
+            "final_e",
+        )
+        .map(BasicValueEnum::into_int_value)
+        .unwrap();
+    let src_slice_len =
+        calculate_len_for_slice_range(generator, ctx, src_idx.0, src_end, src_idx.2);
+    let dest_slice_len =
+        calculate_len_for_slice_range(generator, ctx, dest_idx.0, dest_end, dest_idx.2);
+    let src_eq_dest = ctx
+        .builder
+        .build_int_compare(IntPredicate::EQ, src_slice_len, dest_slice_len, "slice_src_eq_dest")
+        .unwrap();
+    let src_slt_dest = ctx
+        .builder
+        .build_int_compare(IntPredicate::SLT, src_slice_len, dest_slice_len, "slice_src_slt_dest")
+        .unwrap();
+    let dest_step_eq_one = ctx
+        .builder
+        .build_int_compare(
+            IntPredicate::EQ,
+            dest_idx.2,
+            dest_idx.2.get_type().const_int(1, false),
+            "slice_dest_step_eq_one",
+        )
+        .unwrap();
+    let cond_1 = ctx.builder.build_and(dest_step_eq_one, src_slt_dest, "slice_cond_1").unwrap();
+    let cond = ctx.builder.build_or(src_eq_dest, cond_1, "slice_cond").unwrap();
+    ctx.make_assert(
+        generator,
+        cond,
+        "0:ValueError",
+        "attempt to assign sequence of size {0} to slice of size {1} with step size {2}",
+        [Some(src_slice_len), Some(dest_slice_len), Some(dest_idx.2)],
+        ctx.current_loc,
+    );
+
+    let new_len = {
+        let args = vec![
+            dest_idx.0.into(),   // dest start idx
+            dest_idx.1.into(),   // dest end idx
+            dest_idx.2.into(),   // dest step
+            dest_arr_ptr.into(), // dest arr ptr
+            dest_len.into(),     // dest arr len
+            src_idx.0.into(),    // src start idx
+            src_idx.1.into(),    // src end idx
+            src_idx.2.into(),    // src step
+            src_arr_ptr.into(),  // src arr ptr
+            src_len.into(),      // src arr len
+            {
+                let s = match ty {
+                    BasicTypeEnum::FloatType(t) => t.size_of(),
+                    BasicTypeEnum::IntType(t) => t.size_of(),
+                    BasicTypeEnum::PointerType(t) => t.size_of(),
+                    BasicTypeEnum::StructType(t) => t.size_of().unwrap(),
+                    _ => codegen_unreachable!(ctx),
+                };
+                ctx.builder.build_int_truncate_or_bit_cast(s, int32, "size").unwrap()
+            }
+            .into(),
+        ];
+        ctx.builder
+            .build_call(slice_assign_fun, args.as_slice(), "slice_assign")
+            .map(CallSiteValue::try_as_basic_value)
+            .map(|v| v.map_left(BasicValueEnum::into_int_value))
+            .map(Either::unwrap_left)
+            .unwrap()
+    };
+    // update length
+    let need_update =
+        ctx.builder.build_int_compare(IntPredicate::NE, new_len, dest_len, "need_update").unwrap();
+    let current = ctx.builder.get_insert_block().unwrap().get_parent().unwrap();
+    let update_bb = ctx.ctx.append_basic_block(current, "update");
+    let cont_bb = ctx.ctx.append_basic_block(current, "cont");
+    ctx.builder.build_conditional_branch(need_update, update_bb, cont_bb).unwrap();
+    ctx.builder.position_at_end(update_bb);
+    let new_len = ctx.builder.build_int_z_extend_or_bit_cast(new_len, size_ty, "new_len").unwrap();
+    dest_arr.store_size(ctx, generator, new_len);
+    ctx.builder.build_unconditional_branch(cont_bb).unwrap();
+    ctx.builder.position_at_end(cont_bb);
+}
+
+/// Generates a call to `isinf` in IR. Returns an `i1` representing the result.
+pub fn call_isinf<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    v: FloatValue<'ctx>,
+) -> IntValue<'ctx> {
+    let intrinsic_fn = ctx.module.get_function("__nac3_isinf").unwrap_or_else(|| {
+        let fn_type = ctx.ctx.i32_type().fn_type(&[ctx.ctx.f64_type().into()], false);
+        ctx.module.add_function("__nac3_isinf", fn_type, None)
+    });
+
+    let ret = ctx
+        .builder
+        .build_call(intrinsic_fn, &[v.into()], "isinf")
+        .map(CallSiteValue::try_as_basic_value)
+        .map(|v| v.map_left(BasicValueEnum::into_int_value))
+        .map(Either::unwrap_left)
+        .unwrap();
+
+    generator.bool_to_i1(ctx, ret)
+}
+
+/// Generates a call to `isnan` in IR. Returns an `i1` representing the result.
+pub fn call_isnan<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    v: FloatValue<'ctx>,
+) -> IntValue<'ctx> {
+    let intrinsic_fn = ctx.module.get_function("__nac3_isnan").unwrap_or_else(|| {
+        let fn_type = ctx.ctx.i32_type().fn_type(&[ctx.ctx.f64_type().into()], false);
+        ctx.module.add_function("__nac3_isnan", fn_type, None)
+    });
+
+    let ret = ctx
+        .builder
+        .build_call(intrinsic_fn, &[v.into()], "isnan")
+        .map(CallSiteValue::try_as_basic_value)
+        .map(|v| v.map_left(BasicValueEnum::into_int_value))
+        .map(Either::unwrap_left)
+        .unwrap();
+
+    generator.bool_to_i1(ctx, ret)
+}
+
+/// Generates a call to `gamma` in IR. Returns an `f64` representing the result.
+pub fn call_gamma<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
+    let llvm_f64 = ctx.ctx.f64_type();
+
+    let intrinsic_fn = ctx.module.get_function("__nac3_gamma").unwrap_or_else(|| {
+        let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
+        ctx.module.add_function("__nac3_gamma", fn_type, None)
+    });
+
+    ctx.builder
+        .build_call(intrinsic_fn, &[v.into()], "gamma")
+        .map(CallSiteValue::try_as_basic_value)
+        .map(|v| v.map_left(BasicValueEnum::into_float_value))
+        .map(Either::unwrap_left)
+        .unwrap()
+}
+
+/// Generates a call to `gammaln` in IR. Returns an `f64` representing the result.
+pub fn call_gammaln<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
+    let llvm_f64 = ctx.ctx.f64_type();
+
+    let intrinsic_fn = ctx.module.get_function("__nac3_gammaln").unwrap_or_else(|| {
+        let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
+        ctx.module.add_function("__nac3_gammaln", fn_type, None)
+    });
+
+    ctx.builder
+        .build_call(intrinsic_fn, &[v.into()], "gammaln")
+        .map(CallSiteValue::try_as_basic_value)
+        .map(|v| v.map_left(BasicValueEnum::into_float_value))
+        .map(Either::unwrap_left)
+        .unwrap()
+}
+
+/// Generates a call to `j0` in IR. Returns an `f64` representing the result.
+pub fn call_j0<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
+    let llvm_f64 = ctx.ctx.f64_type();
+
+    let intrinsic_fn = ctx.module.get_function("__nac3_j0").unwrap_or_else(|| {
+        let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
+        ctx.module.add_function("__nac3_j0", fn_type, None)
+    });
+
+    ctx.builder
+        .build_call(intrinsic_fn, &[v.into()], "j0")
+        .map(CallSiteValue::try_as_basic_value)
+        .map(|v| v.map_left(BasicValueEnum::into_float_value))
+        .map(Either::unwrap_left)
+        .unwrap()
+}
+
+// When [`TypeContext::size_type`] is 32-bits, the function name is "{fn_name}".
+// When [`TypeContext::size_type`] is 64-bits, the function name is "{fn_name}64".
+#[must_use]
+pub fn get_sizet_dependent_function_name<G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &CodeGenContext<'_, '_>,
+    name: &str,
+) -> String {
+    let mut name = name.to_owned();
+    match generator.get_size_type(ctx.ctx).get_bit_width() {
+        32 => {}
+        64 => name.push_str("64"),
+        bit_width => {
+            panic!("Unsupported int type bit width {bit_width}, must be either 32-bits or 64-bits")
+        }
+    }
+    name
+}
+
+pub fn call_nac3_ndarray_util_assert_shape_no_negative<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndims: Instance<'ctx, Int<SizeT>>,
+    shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name = get_sizet_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_util_assert_shape_no_negative",
+    );
+    FnCall::builder(generator, ctx, &name).arg(ndims).arg(shape).returning_void();
+}
+
+pub fn call_nac3_ndarray_util_assert_output_shape_same<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray_ndims: Instance<'ctx, Int<SizeT>>,
+    ndarray_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    output_ndims: Instance<'ctx, Int<SizeT>>,
+    output_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name = get_sizet_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_util_assert_output_shape_same",
+    );
+    FnCall::builder(generator, ctx, &name)
+        .arg(ndarray_ndims)
+        .arg(ndarray_shape)
+        .arg(output_ndims)
+        .arg(output_shape)
+        .returning_void();
+}
+
+pub fn call_nac3_ndarray_size<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) -> Instance<'ctx, Int<SizeT>> {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_size");
+    FnCall::builder(generator, ctx, &name).arg(ndarray).returning_auto("size")
+}
+
+pub fn call_nac3_ndarray_nbytes<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) -> Instance<'ctx, Int<SizeT>> {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_nbytes");
+    FnCall::builder(generator, ctx, &name).arg(ndarray).returning_auto("nbytes")
+}
+
+pub fn call_nac3_ndarray_len<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) -> Instance<'ctx, Int<SizeT>> {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_len");
+    FnCall::builder(generator, ctx, &name).arg(ndarray).returning_auto("len")
+}
+
+pub fn call_nac3_ndarray_is_c_contiguous<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) -> Instance<'ctx, Int<Bool>> {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_is_c_contiguous");
+    FnCall::builder(generator, ctx, &name).arg(ndarray).returning_auto("is_c_contiguous")
+}
+
+pub fn call_nac3_ndarray_get_nth_pelement<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    index: Instance<'ctx, Int<SizeT>>,
+) -> Instance<'ctx, Ptr<Int<Byte>>> {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_get_nth_pelement");
+    FnCall::builder(generator, ctx, &name).arg(ndarray).arg(index).returning_auto("pelement")
+}
+
+pub fn call_nac3_ndarray_get_pelement_by_indices<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    indices: Instance<'ctx, Ptr<Int<SizeT>>>,
+) -> Instance<'ctx, Ptr<Int<Byte>>> {
+    let name =
+        get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_get_pelement_by_indices");
+    FnCall::builder(generator, ctx, &name).arg(ndarray).arg(indices).returning_auto("pelement")
+}
+
+pub fn call_nac3_ndarray_set_strides_by_shape<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) {
+    let name =
+        get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_set_strides_by_shape");
+    FnCall::builder(generator, ctx, &name).arg(ndarray).returning_void();
+}
+
+pub fn call_nac3_ndarray_copy_data<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    src_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    dst_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_copy_data");
+    FnCall::builder(generator, ctx, &name).arg(src_ndarray).arg(dst_ndarray).returning_void();
+}
+
+pub fn call_nac3_nditer_initialize<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    iter: Instance<'ctx, Ptr<Struct<NDIter>>>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    indices: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_nditer_initialize");
+    FnCall::builder(generator, ctx, &name).arg(iter).arg(ndarray).arg(indices).returning_void();
+}
+
+pub fn call_nac3_nditer_has_element<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    iter: Instance<'ctx, Ptr<Struct<NDIter>>>,
+) -> Instance<'ctx, Int<Bool>> {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_nditer_has_element");
+    FnCall::builder(generator, ctx, &name).arg(iter).returning_auto("has_element")
+}
+
+pub fn call_nac3_nditer_next<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    iter: Instance<'ctx, Ptr<Struct<NDIter>>>,
+) {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_nditer_next");
+    FnCall::builder(generator, ctx, &name).arg(iter).returning_void();
+}
+
+pub fn call_nac3_ndarray_index<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    num_indices: Instance<'ctx, Int<SizeT>>,
+    indices: Instance<'ctx, Ptr<Struct<NDIndex>>>,
+    src_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    dst_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_index");
+    FnCall::builder(generator, ctx, &name)
+        .arg(num_indices)
+        .arg(indices)
+        .arg(src_ndarray)
+        .arg(dst_ndarray)
+        .returning_void();
+}
+
+pub fn call_nac3_ndarray_array_set_and_validate_list_shape<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    list: Instance<'ctx, Ptr<Struct<List<Int<Byte>>>>>,
+    ndims: Instance<'ctx, Int<SizeT>>,
+    shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name = get_sizet_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_array_set_and_validate_list_shape",
+    );
+    FnCall::builder(generator, ctx, &name).arg(list).arg(ndims).arg(shape).returning_void();
+}
+
+pub fn call_nac3_ndarray_array_write_list_to_array<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    list: Instance<'ctx, Ptr<Struct<List<Int<Byte>>>>>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) {
+    let name = get_sizet_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_array_write_list_to_array",
+    );
+    FnCall::builder(generator, ctx, &name).arg(list).arg(ndarray).returning_void();
+}
+
+pub fn call_nac3_ndarray_reshape_resolve_and_check_new_shape<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    size: Instance<'ctx, Int<SizeT>>,
+    new_ndims: Instance<'ctx, Int<SizeT>>,
+    new_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name = get_sizet_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_reshape_resolve_and_check_new_shape",
+    );
+    FnCall::builder(generator, ctx, &name).arg(size).arg(new_ndims).arg(new_shape).returning_void();
+}
+
+pub fn call_nac3_ndarray_broadcast_to<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    src_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    dst_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_broadcast_to");
+    FnCall::builder(generator, ctx, &name).arg(src_ndarray).arg(dst_ndarray).returning_void();
+}
+
+pub fn call_nac3_ndarray_broadcast_shapes<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    num_shape_entries: Instance<'ctx, Int<SizeT>>,
+    shape_entries: Instance<'ctx, Ptr<Struct<ShapeEntry>>>,
+    dst_ndims: Instance<'ctx, Int<SizeT>>,
+    dst_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_broadcast_shapes");
+    FnCall::builder(generator, ctx, &name)
+        .arg(num_shape_entries)
+        .arg(shape_entries)
+        .arg(dst_ndims)
+        .arg(dst_shape)
+        .returning_void();
+}
+
+pub fn call_nac3_ndarray_transpose<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    src_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    dst_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    num_axes: Instance<'ctx, Int<SizeT>>,
+    axes: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_transpose");
+    FnCall::builder(generator, ctx, &name)
+        .arg(src_ndarray)
+        .arg(dst_ndarray)
+        .arg(num_axes)
+        .arg(axes)
+        .returning_void();
+}
+
+#[allow(clippy::too_many_arguments)]
+pub fn call_nac3_ndarray_matmul_calculate_shapes<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    a_ndims: Instance<'ctx, Int<SizeT>>,
+    a_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    b_ndims: Instance<'ctx, Int<SizeT>>,
+    b_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    final_ndims: Instance<'ctx, Int<SizeT>>,
+    new_a_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    new_b_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    dst_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name =
+        get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_matmul_calculate_shapes");
+    FnCall::builder(generator, ctx, &name)
+        .arg(a_ndims)
+        .arg(a_shape)
+        .arg(b_ndims)
+        .arg(b_shape)
+        .arg(final_ndims)
+        .arg(new_a_shape)
+        .arg(new_b_shape)
+        .arg(dst_shape)
+        .returning_void();
+}

nac3core/src/codegen/irrt/ndarray/array.rs

@@ -1,80 +0,0 @@
-use inkwell::{types::BasicTypeEnum, values::IntValue};
-
-use crate::codegen::{
-    expr::infer_and_call_function,
-    irrt::get_usize_dependent_function_name,
-    values::{ndarray::NDArrayValue, ListValue, ProxyValue, TypedArrayLikeAccessor},
-    CodeGenContext, CodeGenerator,
-};
-
-/// Generates a call to `__nac3_ndarray_array_set_and_validate_list_shape`.
-///
-/// Deduces the target shape of the `ndarray` from the provided `list`, raising an exception if
-/// there is any issue with the resultant `shape`.
-///
-/// `shape` must be pre-allocated by the caller of this function to `[usize; ndims]`, and must be
-/// initialized to all `-1`s.
-pub fn call_nac3_ndarray_array_set_and_validate_list_shape<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    list: ListValue<'ctx>,
-    ndims: IntValue<'ctx>,
-    shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-) {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    assert_eq!(list.get_type().element_type().unwrap(), ctx.ctx.i8_type().into());
-    assert_eq!(ndims.get_type(), llvm_usize);
-    assert_eq!(
-        BasicTypeEnum::try_from(shape.element_type(ctx, generator)).unwrap(),
-        llvm_usize.into()
-    );
-
-    let name = get_usize_dependent_function_name(
-        generator,
-        ctx,
-        "__nac3_ndarray_array_set_and_validate_list_shape",
-    );
-
-    infer_and_call_function(
-        ctx,
-        &name,
-        None,
-        &[list.as_base_value().into(), ndims.into(), shape.base_ptr(ctx, generator).into()],
-        None,
-        None,
-    );
-}
-
-/// Generates a call to `__nac3_ndarray_array_write_list_to_array`.
-///
-/// Copies the contents stored in `list` into `ndarray`.
-///
-/// The `ndarray` must fulfill the following preconditions:
-///
-/// - `ndarray.itemsize`: Must be initialized.
-/// - `ndarray.ndims`: Must be initialized.
-/// - `ndarray.shape`: Must be initialized.
-/// - `ndarray.data`: Must be allocated and contiguous.
-pub fn call_nac3_ndarray_array_write_list_to_array<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    list: ListValue<'ctx>,
-    ndarray: NDArrayValue<'ctx>,
-) {
-    assert_eq!(list.get_type().element_type().unwrap(), ctx.ctx.i8_type().into());
-
-    let name = get_usize_dependent_function_name(
-        generator,
-        ctx,
-        "__nac3_ndarray_array_write_list_to_array",
-    );
-
-    infer_and_call_function(
-        ctx,
-        &name,
-        None,
-        &[list.as_base_value().into(), ndarray.as_base_value().into()],
-        None,
-        None,
-    );
-}

nac3core/src/codegen/irrt/ndarray/basic.rs

@@ -1,310 +0,0 @@
-use inkwell::{
-    types::BasicTypeEnum,
-    values::{BasicValueEnum, IntValue, PointerValue},
-    AddressSpace,
-};
-
-use crate::codegen::{
-    expr::{create_and_call_function, infer_and_call_function},
-    irrt::get_usize_dependent_function_name,
-    types::ProxyType,
-    values::{ndarray::NDArrayValue, ProxyValue, TypedArrayLikeAccessor},
-    CodeGenContext, CodeGenerator,
-};
-
-/// Generates a call to `__nac3_ndarray_util_assert_shape_no_negative`.
-///
-/// Assets that `shape` does not contain negative dimensions.
-pub fn call_nac3_ndarray_util_assert_shape_no_negative<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-) {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
-
-    assert_eq!(
-        BasicTypeEnum::try_from(shape.element_type(ctx, generator)).unwrap(),
-        llvm_usize.into()
-    );
-
-    let name = get_usize_dependent_function_name(
-        generator,
-        ctx,
-        "__nac3_ndarray_util_assert_shape_no_negative",
-    );
-
-    create_and_call_function(
-        ctx,
-        &name,
-        Some(llvm_usize.into()),
-        &[
-            (llvm_usize.into(), shape.size(ctx, generator).into()),
-            (llvm_pusize.into(), shape.base_ptr(ctx, generator).into()),
-        ],
-        None,
-        None,
-    );
-}
-
-/// Generates a call to `__nac3_ndarray_util_assert_shape_output_shape_same`.
-///
-/// Asserts that `ndarray_shape` and `output_shape` are the same in the context of writing output to
-/// an `ndarray`.
-pub fn call_nac3_ndarray_util_assert_output_shape_same<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    ndarray_shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-    output_shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-) {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
-
-    assert_eq!(
-        BasicTypeEnum::try_from(ndarray_shape.element_type(ctx, generator)).unwrap(),
-        llvm_usize.into()
-    );
-    assert_eq!(
-        BasicTypeEnum::try_from(output_shape.element_type(ctx, generator)).unwrap(),
-        llvm_usize.into()
-    );
-
-    let name = get_usize_dependent_function_name(
-        generator,
-        ctx,
-        "__nac3_ndarray_util_assert_output_shape_same",
-    );
-
-    create_and_call_function(
-        ctx,
-        &name,
-        Some(llvm_usize.into()),
-        &[
-            (llvm_usize.into(), ndarray_shape.size(ctx, generator).into()),
-            (llvm_pusize.into(), ndarray_shape.base_ptr(ctx, generator).into()),
-            (llvm_usize.into(), output_shape.size(ctx, generator).into()),
-            (llvm_pusize.into(), output_shape.base_ptr(ctx, generator).into()),
-        ],
-        None,
-        None,
-    );
-}
-
-/// Generates a call to `__nac3_ndarray_size`.
-///
-/// Returns a [`usize`][CodeGenerator::get_size_type] value of the number of elements of an
-/// `ndarray`, corresponding to the value of `ndarray.size`.
-pub fn call_nac3_ndarray_size<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    ndarray: NDArrayValue<'ctx>,
-) -> IntValue<'ctx> {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let llvm_ndarray = ndarray.get_type().as_base_type();
-
-    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_size");
-
-    create_and_call_function(
-        ctx,
-        &name,
-        Some(llvm_usize.into()),
-        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
-        Some("size"),
-        None,
-    )
-    .map(BasicValueEnum::into_int_value)
-    .unwrap()
-}
-
-/// Generates a call to `__nac3_ndarray_nbytes`.
-///
-/// Returns a [`usize`][CodeGenerator::get_size_type] value of the number of bytes consumed by the
-/// data of the `ndarray`, corresponding to the value of `ndarray.nbytes`.
-pub fn call_nac3_ndarray_nbytes<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    ndarray: NDArrayValue<'ctx>,
-) -> IntValue<'ctx> {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let llvm_ndarray = ndarray.get_type().as_base_type();
-
-    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_nbytes");
-
-    create_and_call_function(
-        ctx,
-        &name,
-        Some(llvm_usize.into()),
-        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
-        Some("nbytes"),
-        None,
-    )
-    .map(BasicValueEnum::into_int_value)
-    .unwrap()
-}
-
-/// Generates a call to `__nac3_ndarray_len`.
-///
-/// Returns a [`usize`][CodeGenerator::get_size_type] value of the size of the topmost dimension of
-/// the `ndarray`, corresponding to the value of `ndarray.__len__`.
-pub fn call_nac3_ndarray_len<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    ndarray: NDArrayValue<'ctx>,
-) -> IntValue<'ctx> {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let llvm_ndarray = ndarray.get_type().as_base_type();
-
-    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_len");
-
-    create_and_call_function(
-        ctx,
-        &name,
-        Some(llvm_usize.into()),
-        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
-        Some("len"),
-        None,
-    )
-    .map(BasicValueEnum::into_int_value)
-    .unwrap()
-}
-
-/// Generates a call to `__nac3_ndarray_is_c_contiguous`.
-///
-/// Returns an `i1` value indicating whether the `ndarray` is C-contiguous.
-pub fn call_nac3_ndarray_is_c_contiguous<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    ndarray: NDArrayValue<'ctx>,
-) -> IntValue<'ctx> {
-    let llvm_i1 = ctx.ctx.bool_type();
-    let llvm_ndarray = ndarray.get_type().as_base_type();
-
-    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_is_c_contiguous");
-
-    create_and_call_function(
-        ctx,
-        &name,
-        Some(llvm_i1.into()),
-        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
-        Some("is_c_contiguous"),
-        None,
-    )
-    .map(BasicValueEnum::into_int_value)
-    .unwrap()
-}
-
-/// Generates a call to `__nac3_ndarray_get_nth_pelement`.
-///
-/// Returns a [`PointerValue`] to the `index`-th flattened element of the `ndarray`.
-pub fn call_nac3_ndarray_get_nth_pelement<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    ndarray: NDArrayValue<'ctx>,
-    index: IntValue<'ctx>,
-) -> PointerValue<'ctx> {
-    let llvm_i8 = ctx.ctx.i8_type();
-    let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let llvm_ndarray = ndarray.get_type().as_base_type();
-
-    assert_eq!(index.get_type(), llvm_usize);
-
-    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_get_nth_pelement");
-
-    create_and_call_function(
-        ctx,
-        &name,
-        Some(llvm_pi8.into()),
-        &[(llvm_ndarray.into(), ndarray.as_base_value().into()), (llvm_usize.into(), index.into())],
-        Some("pelement"),
-        None,
-    )
-    .map(BasicValueEnum::into_pointer_value)
-    .unwrap()
-}
-
-/// Generates a call to `__nac3_ndarray_get_pelement_by_indices`.
-///
-/// `indices` must have the same number of elements as the number of dimensions in `ndarray`.
-///
-/// Returns a [`PointerValue`] to the element indexed by `indices`.
-pub fn call_nac3_ndarray_get_pelement_by_indices<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    ndarray: NDArrayValue<'ctx>,
-    indices: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-) -> PointerValue<'ctx> {
-    let llvm_i8 = ctx.ctx.i8_type();
-    let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
-    let llvm_ndarray = ndarray.get_type().as_base_type();
-
-    assert_eq!(
-        BasicTypeEnum::try_from(indices.element_type(ctx, generator)).unwrap(),
-        llvm_usize.into()
-    );
-
-    let name =
-        get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_get_pelement_by_indices");
-
-    create_and_call_function(
-        ctx,
-        &name,
-        Some(llvm_pi8.into()),
-        &[
-            (llvm_ndarray.into(), ndarray.as_base_value().into()),
-            (llvm_pusize.into(), indices.base_ptr(ctx, generator).into()),
-        ],
-        Some("pelement"),
-        None,
-    )
-    .map(BasicValueEnum::into_pointer_value)
-    .unwrap()
-}
-
-/// Generates a call to `__nac3_ndarray_set_strides_by_shape`.
-///
-/// Sets `ndarray.strides` assuming that `ndarray.shape` is C-contiguous.
-pub fn call_nac3_ndarray_set_strides_by_shape<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    ndarray: NDArrayValue<'ctx>,
-) {
-    let llvm_ndarray = ndarray.get_type().as_base_type();
-
-    let name =
-        get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_set_strides_by_shape");
-
-    create_and_call_function(
-        ctx,
-        &name,
-        None,
-        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
-        None,
-        None,
-    );
-}
-
-/// Generates a call to `__nac3_ndarray_copy_data`.
-///
-/// Copies all elements from `src_ndarray` to `dst_ndarray` using their flattened views. The number
-/// of elements in `src_ndarray` must be greater than or equal to the number of elements in
-/// `dst_ndarray`.
-pub fn call_nac3_ndarray_copy_data<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    src_ndarray: NDArrayValue<'ctx>,
-    dst_ndarray: NDArrayValue<'ctx>,
-) {
-    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_copy_data");
-
-    infer_and_call_function(
-        ctx,
-        &name,
-        None,
-        &[src_ndarray.as_base_value().into(), dst_ndarray.as_base_value().into()],
-        None,
-        None,
-    );
-}

nac3core/src/codegen/irrt/ndarray/broadcast.rs

@@ -1,82 +0,0 @@
-use inkwell::values::IntValue;
-
-use crate::codegen::{
-    expr::infer_and_call_function,
-    irrt::get_usize_dependent_function_name,
-    types::{ndarray::ShapeEntryType, ProxyType},
-    values::{
-        ndarray::NDArrayValue, ArrayLikeValue, ArraySliceValue, ProxyValue, TypedArrayLikeAccessor,
-        TypedArrayLikeMutator,
-    },
-    CodeGenContext, CodeGenerator,
-};
-
-/// Generates a call to `__nac3_ndarray_broadcast_to`.
-///
-/// Attempts to broadcast `src_ndarray` to the new shape defined by `dst_ndarray`.
-///
-/// `dst_ndarray` must meet the following preconditions:
-///
-/// - `dst_ndarray.ndims` must be initialized and matching the length of `dst_ndarray.shape`.
-/// - `dst_ndarray.shape` must be initialized and contains the target broadcast shape.
-/// - `dst_ndarray.strides` must be allocated and may contain uninitialized values.
-pub fn call_nac3_ndarray_broadcast_to<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    src_ndarray: NDArrayValue<'ctx>,
-    dst_ndarray: NDArrayValue<'ctx>,
-) {
-    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_broadcast_to");
-    infer_and_call_function(
-        ctx,
-        &name,
-        None,
-        &[src_ndarray.as_base_value().into(), dst_ndarray.as_base_value().into()],
-        None,
-        None,
-    );
-}
-
-/// Generates a call to `__nac3_ndarray_broadcast_shapes`.
-///
-/// Attempts to calculate the resultant shape from broadcasting all shapes in `shape_entries`,
-/// writing the result to `dst_shape`.
-pub fn call_nac3_ndarray_broadcast_shapes<'ctx, G, Shape>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    num_shape_entries: IntValue<'ctx>,
-    shape_entries: ArraySliceValue<'ctx>,
-    dst_ndims: IntValue<'ctx>,
-    dst_shape: &Shape,
-) where
-    G: CodeGenerator + ?Sized,
-    Shape: TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>
-        + TypedArrayLikeMutator<'ctx, G, IntValue<'ctx>>,
-{
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    assert_eq!(num_shape_entries.get_type(), llvm_usize);
-    assert!(ShapeEntryType::is_type(
-        generator,
-        ctx.ctx,
-        shape_entries.base_ptr(ctx, generator).get_type()
-    )
-    .is_ok());
-    assert_eq!(dst_ndims.get_type(), llvm_usize);
-    assert_eq!(dst_shape.element_type(ctx, generator), llvm_usize.into());
-
-    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_broadcast_shapes");
-    infer_and_call_function(
-        ctx,
-        &name,
-        None,
-        &[
-            num_shape_entries.into(),
-            shape_entries.base_ptr(ctx, generator).into(),
-            dst_ndims.into(),
-            dst_shape.base_ptr(ctx, generator).into(),
-        ],
-        None,
-        None,
-    );
-}

nac3core/src/codegen/irrt/ndarray/indexing.rs

@@ -1,34 +0,0 @@
-use crate::codegen::{
-    expr::infer_and_call_function,
-    irrt::get_usize_dependent_function_name,
-    values::{ndarray::NDArrayValue, ArrayLikeValue, ArraySliceValue, ProxyValue},
-    CodeGenContext, CodeGenerator,
-};
-
-/// Generates a call to `__nac3_ndarray_index`.
-///
-/// Performs [basic indexing](https://numpy.org/doc/stable/user/basics.indexing.html#basic-indexing)
-/// on `src_ndarray` using `indices`, writing the result to `dst_ndarray`, corresponding to the
-/// operation `dst_ndarray = src_ndarray[indices]`.
-pub fn call_nac3_ndarray_index<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    indices: ArraySliceValue<'ctx>,
-    src_ndarray: NDArrayValue<'ctx>,
-    dst_ndarray: NDArrayValue<'ctx>,
-) {
-    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_index");
-    infer_and_call_function(
-        ctx,
-        &name,
-        None,
-        &[
-            indices.size(ctx, generator).into(),
-            indices.base_ptr(ctx, generator).into(),
-            src_ndarray.as_base_value().into(),
-            dst_ndarray.as_base_value().into(),
-        ],
-        None,
-        None,
-    );
-}

nac3core/src/codegen/irrt/ndarray/iter.rs

@@ -1,86 +0,0 @@
-use inkwell::{
-    types::BasicTypeEnum,
-    values::{BasicValueEnum, IntValue},
-    AddressSpace,
-};
-
-use crate::codegen::{
-    expr::{create_and_call_function, infer_and_call_function},
-    irrt::get_usize_dependent_function_name,
-    types::ProxyType,
-    values::{
-        ndarray::{NDArrayValue, NDIterValue},
-        ProxyValue, TypedArrayLikeAccessor,
-    },
-    CodeGenContext, CodeGenerator,
-};
-
-/// Generates a call to `__nac3_nditer_initialize`.
-///
-/// Initializes the `iter` object.
-pub fn call_nac3_nditer_initialize<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    iter: NDIterValue<'ctx>,
-    ndarray: NDArrayValue<'ctx>,
-    indices: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-) {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
-
-    assert_eq!(
-        BasicTypeEnum::try_from(indices.element_type(ctx, generator)).unwrap(),
-        llvm_usize.into()
-    );
-
-    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_nditer_initialize");
-
-    create_and_call_function(
-        ctx,
-        &name,
-        None,
-        &[
-            (iter.get_type().as_base_type().into(), iter.as_base_value().into()),
-            (ndarray.get_type().as_base_type().into(), ndarray.as_base_value().into()),
-            (llvm_pusize.into(), indices.base_ptr(ctx, generator).into()),
-        ],
-        None,
-        None,
-    );
-}
-
-/// Generates a call to `__nac3_nditer_initialize_has_element`.
-///
-/// Returns an `i1` value indicating whether there are elements left to traverse for the `iter`
-/// object.
-pub fn call_nac3_nditer_has_element<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    iter: NDIterValue<'ctx>,
-) -> IntValue<'ctx> {
-    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_nditer_has_element");
-
-    infer_and_call_function(
-        ctx,
-        &name,
-        Some(ctx.ctx.bool_type().into()),
-        &[iter.as_base_value().into()],
-        None,
-        None,
-    )
-    .map(BasicValueEnum::into_int_value)
-    .unwrap()
-}
-
-/// Generates a call to `__nac3_nditer_next`.
-///
-/// Moves `iter` to point to the next element.
-pub fn call_nac3_nditer_next<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    iter: NDIterValue<'ctx>,
-) {
-    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_nditer_next");
-
-    infer_and_call_function(ctx, &name, None, &[iter.as_base_value().into()], None, None);
-}

nac3core/src/codegen/irrt/ndarray/matmul.rs

@@ -1,66 +0,0 @@
-use inkwell::{types::BasicTypeEnum, values::IntValue};
-
-use crate::codegen::{
-    expr::infer_and_call_function, irrt::get_usize_dependent_function_name,
-    values::TypedArrayLikeAccessor, CodeGenContext, CodeGenerator,
-};
-
-/// Generates a call to `__nac3_ndarray_matmul_calculate_shapes`.
-///
-/// Calculates the broadcasted shapes for `a`, `b`, and the `ndarray` holding the final values of
-/// `a @ b`.
-#[allow(clippy::too_many_arguments)]
-pub fn call_nac3_ndarray_matmul_calculate_shapes<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    a_shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-    b_shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-    final_ndims: IntValue<'ctx>,
-    new_a_shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-    new_b_shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-    dst_shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-) {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    assert_eq!(
-        BasicTypeEnum::try_from(a_shape.element_type(ctx, generator)).unwrap(),
-        llvm_usize.into()
-    );
-    assert_eq!(
-        BasicTypeEnum::try_from(b_shape.element_type(ctx, generator)).unwrap(),
-        llvm_usize.into()
-    );
-    assert_eq!(
-        BasicTypeEnum::try_from(new_a_shape.element_type(ctx, generator)).unwrap(),
-        llvm_usize.into()
-    );
-    assert_eq!(
-        BasicTypeEnum::try_from(new_b_shape.element_type(ctx, generator)).unwrap(),
-        llvm_usize.into()
-    );
-    assert_eq!(
-        BasicTypeEnum::try_from(dst_shape.element_type(ctx, generator)).unwrap(),
-        llvm_usize.into()
-    );
-
-    let name =
-        get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_matmul_calculate_shapes");
-
-    infer_and_call_function(
-        ctx,
-        &name,
-        None,
-        &[
-            a_shape.size(ctx, generator).into(),
-            a_shape.base_ptr(ctx, generator).into(),
-            b_shape.size(ctx, generator).into(),
-            b_shape.base_ptr(ctx, generator).into(),
-            final_ndims.into(),
-            new_a_shape.base_ptr(ctx, generator).into(),
-            new_b_shape.base_ptr(ctx, generator).into(),
-            dst_shape.base_ptr(ctx, generator).into(),
-        ],
-        None,
-        None,
-    );
-}

nac3core/src/codegen/irrt/ndarray/mod.rs

@@ -1,17 +0,0 @@
-pub use array::*;
-pub use basic::*;
-pub use broadcast::*;
-pub use indexing::*;
-pub use iter::*;
-pub use matmul::*;
-pub use reshape::*;
-pub use transpose::*;
-
-mod array;
-mod basic;
-mod broadcast;
-mod indexing;
-mod iter;
-mod matmul;
-mod reshape;
-mod transpose;

nac3core/src/codegen/irrt/ndarray/reshape.rs

@@ -1,40 +0,0 @@
-use inkwell::values::IntValue;
-
-use crate::codegen::{
-    expr::infer_and_call_function,
-    irrt::get_usize_dependent_function_name,
-    values::{ArrayLikeValue, ArraySliceValue},
-    CodeGenContext, CodeGenerator,
-};
-
-/// Generates a call to `__nac3_ndarray_reshape_resolve_and_check_new_shape`.
-///
-/// Resolves unknown dimensions in `new_shape` for `numpy.reshape(<ndarray>, new_shape)`, raising an
-/// assertion if multiple dimensions are unknown (`-1`).
-pub fn call_nac3_ndarray_reshape_resolve_and_check_new_shape<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    size: IntValue<'ctx>,
-    new_ndims: IntValue<'ctx>,
-    new_shape: ArraySliceValue<'ctx>,
-) {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    assert_eq!(size.get_type(), llvm_usize);
-    assert_eq!(new_ndims.get_type(), llvm_usize);
-    assert_eq!(new_shape.element_type(ctx, generator), llvm_usize.into());
-
-    let name = get_usize_dependent_function_name(
-        generator,
-        ctx,
-        "__nac3_ndarray_reshape_resolve_and_check_new_shape",
-    );
-    infer_and_call_function(
-        ctx,
-        &name,
-        None,
-        &[size.into(), new_ndims.into(), new_shape.base_ptr(ctx, generator).into()],
-        None,
-        None,
-    );
-}

nac3core/src/codegen/irrt/ndarray/transpose.rs

@@ -1,48 +0,0 @@
-use inkwell::{values::IntValue, AddressSpace};
-
-use crate::codegen::{
-    expr::infer_and_call_function,
-    irrt::get_usize_dependent_function_name,
-    values::{ndarray::NDArrayValue, ProxyValue, TypedArrayLikeAccessor},
-    CodeGenContext, CodeGenerator,
-};
-
-/// Generates a call to `__nac3_ndarray_transpose`.
-///
-/// Creates a transpose view of `src_ndarray` and writes the result to `dst_ndarray`.
-///
-/// `dst_ndarray` must fulfill the following preconditions:
-///
-/// - `dst_ndarray.ndims` must be initialized and must be equal to `src_ndarray.ndims`.
-/// - `dst_ndarray.shape` must be allocated and may contain uninitialized values.
-/// - `dst_ndarray.strides` must be allocated and may contain uninitialized values.
-pub fn call_nac3_ndarray_transpose<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    src_ndarray: NDArrayValue<'ctx>,
-    dst_ndarray: NDArrayValue<'ctx>,
-    axes: Option<&impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>>,
-) {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    assert!(axes.is_none_or(|axes| axes.size(ctx, generator).get_type() == llvm_usize));
-    assert!(axes.is_none_or(|axes| axes.element_type(ctx, generator) == llvm_usize.into()));
-
-    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_transpose");
-    infer_and_call_function(
-        ctx,
-        &name,
-        None,
-        &[
-            src_ndarray.as_base_value().into(),
-            dst_ndarray.as_base_value().into(),
-            axes.map_or(llvm_usize.const_zero(), |axes| axes.size(ctx, generator)).into(),
-            axes.map_or(llvm_usize.ptr_type(AddressSpace::default()).const_null(), |axes| {
-                axes.base_ptr(ctx, generator)
-            })
-            .into(),
-        ],
-        None,
-        None,
-    );
-}

nac3core/src/codegen/irrt/range.rs

@@ -1,56 +0,0 @@
-use inkwell::{
-    values::{BasicValueEnum, CallSiteValue, IntValue},
-    IntPredicate,
-};
-use itertools::Either;
-
-use crate::codegen::{CodeGenContext, CodeGenerator};
-
-/// Invokes the `__nac3_range_slice_len` in IRRT.
-///
-/// - `start`: The `i32` start value for the slice.
-/// - `end`: The `i32` end value for the slice.
-/// - `step`: The `i32` step value for the slice.
-///
-/// Returns an `i32` value of the length of the slice.
-pub fn calculate_len_for_slice_range<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    start: IntValue<'ctx>,
-    end: IntValue<'ctx>,
-    step: IntValue<'ctx>,
-) -> IntValue<'ctx> {
-    const SYMBOL: &str = "__nac3_range_slice_len";
-
-    let llvm_i32 = ctx.ctx.i32_type();
-
-    assert_eq!(start.get_type(), llvm_i32);
-    assert_eq!(end.get_type(), llvm_i32);
-    assert_eq!(step.get_type(), llvm_i32);
-
-    let len_func = ctx.module.get_function(SYMBOL).unwrap_or_else(|| {
-        let fn_t = llvm_i32.fn_type(&[llvm_i32.into(), llvm_i32.into(), llvm_i32.into()], false);
-        ctx.module.add_function(SYMBOL, fn_t, None)
-    });
-
-    // assert step != 0, throw exception if not
-    let not_zero = ctx
-        .builder
-        .build_int_compare(IntPredicate::NE, step, step.get_type().const_zero(), "range_step_ne")
-        .unwrap();
-    ctx.make_assert(
-        generator,
-        not_zero,
-        "0:ValueError",
-        "step must not be zero",
-        [None, None, None],
-        ctx.current_loc,
-    );
-
-    ctx.builder
-        .build_call(len_func, &[start.into(), end.into(), step.into()], "calc_len")
-        .map(CallSiteValue::try_as_basic_value)
-        .map(|v| v.map_left(BasicValueEnum::into_int_value))
-        .map(Either::unwrap_left)
-        .unwrap()
-}

nac3core/src/codegen/irrt/slice.rs

@@ -1,39 +0,0 @@
-use inkwell::values::{BasicValueEnum, CallSiteValue, IntValue};
-use itertools::Either;
-
-use nac3parser::ast::Expr;
-
-use crate::{
-    codegen::{CodeGenContext, CodeGenerator},
-    typecheck::typedef::Type,
-};
-
-/// this function allows index out of range, since python
-/// allows index out of range in slice (`a = [1,2,3]; a[1:10] == [2,3]`).
-pub fn handle_slice_index_bound<'ctx, G: CodeGenerator>(
-    i: &Expr<Option<Type>>,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    generator: &mut G,
-    length: IntValue<'ctx>,
-) -> Result<Option<IntValue<'ctx>>, String> {
-    const SYMBOL: &str = "__nac3_slice_index_bound";
-    let func = ctx.module.get_function(SYMBOL).unwrap_or_else(|| {
-        let i32_t = ctx.ctx.i32_type();
-        let fn_t = i32_t.fn_type(&[i32_t.into(), i32_t.into()], false);
-        ctx.module.add_function(SYMBOL, fn_t, None)
-    });
-
-    let i = if let Some(v) = generator.gen_expr(ctx, i)? {
-        v.to_basic_value_enum(ctx, generator, i.custom.unwrap())?
-    } else {
-        return Ok(None);
-    };
-    Ok(Some(
-        ctx.builder
-            .build_call(func, &[i.into(), length.into()], "bounded_ind")
-            .map(CallSiteValue::try_as_basic_value)
-            .map(|v| v.map_left(BasicValueEnum::into_int_value))
-            .map(Either::unwrap_left)
-            .unwrap(),
-    ))
-}

nac3core/src/codegen/irrt/string.rs

@@ -1,46 +0,0 @@
-use inkwell::values::{BasicValueEnum, CallSiteValue, IntValue, PointerValue};
-use itertools::Either;
-
-use super::get_usize_dependent_function_name;
-use crate::codegen::{CodeGenContext, CodeGenerator};
-
-/// Generates a call to string equality comparison. Returns an `i1` representing whether the strings are equal.
-pub fn call_string_eq<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    str1_ptr: PointerValue<'ctx>,
-    str1_len: IntValue<'ctx>,
-    str2_ptr: PointerValue<'ctx>,
-    str2_len: IntValue<'ctx>,
-) -> IntValue<'ctx> {
-    let llvm_i1 = ctx.ctx.bool_type();
-
-    let func_name = get_usize_dependent_function_name(generator, ctx, "nac3_str_eq");
-
-    let func = ctx.module.get_function(&func_name).unwrap_or_else(|| {
-        ctx.module.add_function(
-            &func_name,
-            llvm_i1.fn_type(
-                &[
-                    str1_ptr.get_type().into(),
-                    str1_len.get_type().into(),
-                    str2_ptr.get_type().into(),
-                    str2_len.get_type().into(),
-                ],
-                false,
-            ),
-            None,
-        )
-    });
-
-    ctx.builder
-        .build_call(
-            func,
-            &[str1_ptr.into(), str1_len.into(), str2_ptr.into(), str2_len.into()],
-            "str_eq_call",
-        )
-        .map(CallSiteValue::try_as_basic_value)
-        .map(|v| v.map_left(BasicValueEnum::into_int_value))
-        .map(Either::unwrap_left)
-        .unwrap()
-}

nac3core/src/codegen/llvm_intrinsics.rs

@@ -1,6 +1,7 @@
 use inkwell::{
+    context::Context,
     intrinsics::Intrinsic,
-    types::AnyTypeEnum::IntType,
+    types::{AnyTypeEnum::IntType, FloatType},
     values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue, PointerValue},
     AddressSpace,
 };
@@ -8,6 +9,34 @@ use itertools::Either;
 
 use super::CodeGenContext;
 
+/// Returns the string representation for the floating-point type `ft` when used in intrinsic
+/// functions.
+fn get_float_intrinsic_repr(ctx: &Context, ft: FloatType) -> &'static str {
+    // Standard LLVM floating-point types
+    if ft == ctx.f16_type() {
+        return "f16";
+    }
+    if ft == ctx.f32_type() {
+        return "f32";
+    }
+    if ft == ctx.f64_type() {
+        return "f64";
+    }
+    if ft == ctx.f128_type() {
+        return "f128";
+    }
+
+    // Non-standard floating-point types
+    if ft == ctx.x86_f80_type() {
+        return "f80";
+    }
+    if ft == ctx.ppc_f128_type() {
+        return "ppcf128";
+    }
+
+    unreachable!()
+}
+
 /// Invokes the [`llvm.va_start`](https://llvm.org/docs/LangRef.html#llvm-va-start-intrinsic)
 /// intrinsic.
 pub fn call_va_start<'ctx>(ctx: &CodeGenContext<'ctx, '_>, arglist: PointerValue<'ctx>) {
@@ -25,7 +54,7 @@ pub fn call_va_start<'ctx>(ctx: &CodeGenContext<'ctx, '_>, arglist: PointerValue
     ctx.builder.build_call(intrinsic_fn, &[arglist.into()], "").unwrap();
 }
 
-/// Invokes the [`llvm.va_end`](https://llvm.org/docs/LangRef.html#llvm-va-end-intrinsic)
+/// Invokes the [`llvm.va_start`](https://llvm.org/docs/LangRef.html#llvm-va-start-intrinsic)
 /// intrinsic.
 pub fn call_va_end<'ctx>(ctx: &CodeGenContext<'ctx, '_>, arglist: PointerValue<'ctx>) {
     const FN_NAME: &str = "llvm.va_end";
@@ -172,49 +201,6 @@ pub fn call_memcpy_generic<'ctx>(
     call_memcpy(ctx, dest, src, len, is_volatile);
 }
 
-/// Invokes the `llvm.memcpy` intrinsic.
-///
-/// Unlike [`call_memcpy`], this function accepts any type of pointer value. If `dest` or `src` is
-/// not a pointer to an integer, the pointer(s) will be cast to `i8*` before invoking `memcpy`.
-/// Moreover, `len` now refers to the number of elements to copy (rather than number of bytes to
-/// copy).
-pub fn call_memcpy_generic_array<'ctx>(
-    ctx: &CodeGenContext<'ctx, '_>,
-    dest: PointerValue<'ctx>,
-    src: PointerValue<'ctx>,
-    len: IntValue<'ctx>,
-    is_volatile: IntValue<'ctx>,
-) {
-    let llvm_i8 = ctx.ctx.i8_type();
-    let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
-    let llvm_sizeof_expr_t = llvm_i8.size_of().get_type();
-
-    let dest_elem_t = dest.get_type().get_element_type();
-    let src_elem_t = src.get_type().get_element_type();
-
-    let dest = if matches!(dest_elem_t, IntType(t) if t.get_bit_width() == 8) {
-        dest
-    } else {
-        ctx.builder
-            .build_bit_cast(dest, llvm_p0i8, "")
-            .map(BasicValueEnum::into_pointer_value)
-            .unwrap()
-    };
-    let src = if matches!(src_elem_t, IntType(t) if t.get_bit_width() == 8) {
-        src
-    } else {
-        ctx.builder
-            .build_bit_cast(src, llvm_p0i8, "")
-            .map(BasicValueEnum::into_pointer_value)
-            .unwrap()
-    };
-
-    let len = ctx.builder.build_int_z_extend_or_bit_cast(len, llvm_sizeof_expr_t, "").unwrap();
-    let len = ctx.builder.build_int_mul(len, src_elem_t.size_of().unwrap(), "").unwrap();
-
-    call_memcpy(ctx, dest, src, len, is_volatile);
-}
-
 /// Macro to find and generate build call for llvm intrinsic (body of llvm intrinsic function)
 ///
 /// Arguments:
@@ -357,25 +343,3 @@ pub fn call_float_powi<'ctx>(
         .map(Either::unwrap_left)
         .unwrap()
 }
-
-/// Invokes the [`llvm.ctpop`](https://llvm.org/docs/LangRef.html#llvm-ctpop-intrinsic) intrinsic.
-pub fn call_int_ctpop<'ctx>(
-    ctx: &CodeGenContext<'ctx, '_>,
-    src: IntValue<'ctx>,
-    name: Option<&str>,
-) -> IntValue<'ctx> {
-    const FN_NAME: &str = "llvm.ctpop";
-
-    let llvm_src_t = src.get_type();
-
-    let intrinsic_fn = Intrinsic::find(FN_NAME)
-        .and_then(|intrinsic| intrinsic.get_declaration(&ctx.module, &[llvm_src_t.into()]))
-        .unwrap();
-
-    ctx.builder
-        .build_call(intrinsic_fn, &[src.into()], name.unwrap_or_default())
-        .map(CallSiteValue::try_as_basic_value)
-        .map(|v| v.map_left(BasicValueEnum::into_int_value))
-        .map(Either::unwrap_left)
-        .unwrap()
-}

nac3core/src/codegen/mod.rs

@@ -30,31 +30,30 @@ use nac3parser::ast::{Location, Stmt, StrRef};
 
 use crate::{
     symbol_resolver::{StaticValue, SymbolResolver},
-    toplevel::{
+    toplevel::{helper::PrimDef, TopLevelContext, TopLevelDef},
-        helper::{extract_ndims, PrimDef},
-        numpy::unpack_ndarray_var_tys,
-        TopLevelContext, TopLevelDef,
-    },
     typecheck::{
         type_inferencer::{CodeLocation, PrimitiveStore},
         typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
     },
 };
+use classes::{ListType, ProxyType, RangeType};
 use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
 pub use generator::{CodeGenerator, DefaultCodeGenerator};
-use types::{ndarray::NDArrayType, ListType, ProxyType, RangeType, TupleType};
+use model::*;
+use object::ndarray::NDArray;
 
 pub mod builtin_fns;
+pub mod classes;
 pub mod concrete_type;
 pub mod expr;
 pub mod extern_fns;
 mod generator;
 pub mod irrt;
 pub mod llvm_intrinsics;
+pub mod model;
 pub mod numpy;
+pub mod object;
 pub mod stmt;
-pub mod types;
-pub mod values;
 
 #[cfg(test)]
 mod test;
@@ -514,13 +513,7 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
                         }
 
                         TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-                            let (dtype, ndims) = unpack_ndarray_var_tys(unifier, ty);
+                            Ptr(Struct(NDArray)).llvm_type(generator, ctx).as_basic_type_enum()
-                            let ndims = extract_ndims(unifier, ndims);
-                            let element_type = get_llvm_type(
-                                ctx, module, generator, unifier, top_level, type_cache, dtype,
-                            );
-
-                            NDArrayType::new(generator, ctx, element_type, ndims).as_base_type().into()
                         }
 
                         _ => unreachable!(
@@ -574,7 +567,7 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
                         get_llvm_type(ctx, module, generator, unifier, top_level, type_cache, *ty)
                     })
                     .collect_vec();
-                TupleType::new(generator, ctx, &fields).as_base_type().into()
+                ctx.struct_type(&fields, false).into()
             }
             TVirtual { .. } => unimplemented!(),
             _ => unreachable!("{}", ty_enum.get_type_name()),
@@ -1124,106 +1117,3 @@ fn gen_in_range_check<'ctx>(
 fn get_va_count_arg_name(arg_name: StrRef) -> StrRef {
     format!("__{}_va_count", &arg_name).into()
 }
-
-/// Returns the alignment of the type.
-///
-/// This is necessary as `get_alignment` is not implemented as part of [`BasicType`].
-pub fn get_type_alignment<'ctx>(ty: impl Into<BasicTypeEnum<'ctx>>) -> IntValue<'ctx> {
-    match ty.into() {
-        BasicTypeEnum::ArrayType(ty) => ty.get_alignment(),
-        BasicTypeEnum::FloatType(ty) => ty.get_alignment(),
-        BasicTypeEnum::IntType(ty) => ty.get_alignment(),
-        BasicTypeEnum::PointerType(ty) => ty.get_alignment(),
-        BasicTypeEnum::StructType(ty) => ty.get_alignment(),
-        BasicTypeEnum::VectorType(ty) => ty.get_alignment(),
-    }
-}
-
-/// Inserts an `alloca` instruction with allocation `size` given in bytes and the alignment of the
-/// given type.
-///
-/// The returned [`PointerValue`] will have a type of `i8*`, a size of at least `size`, and will be
-/// aligned with the alignment of `align_ty`.
-pub fn type_aligned_alloca<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    align_ty: impl Into<BasicTypeEnum<'ctx>>,
-    size: IntValue<'ctx>,
-    name: Option<&str>,
-) -> PointerValue<'ctx> {
-    /// Round `val` up to its modulo `power_of_two`.
-    fn round_up<'ctx>(
-        ctx: &CodeGenContext<'ctx, '_>,
-        val: IntValue<'ctx>,
-        power_of_two: IntValue<'ctx>,
-    ) -> IntValue<'ctx> {
-        debug_assert_eq!(
-            val.get_type().get_bit_width(),
-            power_of_two.get_type().get_bit_width(),
-            "`val` ({}) and `power_of_two` ({}) must be the same type",
-            val.get_type(),
-            power_of_two.get_type(),
-        );
-
-        let llvm_val_t = val.get_type();
-
-        let max_rem =
-            ctx.builder.build_int_sub(power_of_two, llvm_val_t.const_int(1, false), "").unwrap();
-        ctx.builder
-            .build_and(
-                ctx.builder.build_int_add(val, max_rem, "").unwrap(),
-                ctx.builder.build_not(max_rem, "").unwrap(),
-                "",
-            )
-            .unwrap()
-    }
-
-    let llvm_i8 = ctx.ctx.i8_type();
-    let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let align_ty = align_ty.into();
-
-    let size = ctx.builder.build_int_truncate_or_bit_cast(size, llvm_usize, "").unwrap();
-
-    debug_assert_eq!(
-        size.get_type().get_bit_width(),
-        llvm_usize.get_bit_width(),
-        "Expected size_t ({}) for parameter `size` of `aligned_alloca`, got {}",
-        llvm_usize,
-        size.get_type(),
-    );
-
-    let alignment = get_type_alignment(align_ty);
-    let alignment = ctx.builder.build_int_truncate_or_bit_cast(alignment, llvm_usize, "").unwrap();
-
-    if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
-        let alignment_bitcount = llvm_intrinsics::call_int_ctpop(ctx, alignment, None);
-
-        ctx.make_assert(
-            generator,
-            ctx.builder
-                .build_int_compare(
-                    IntPredicate::EQ,
-                    alignment_bitcount,
-                    alignment_bitcount.get_type().const_int(1, false),
-                    "",
-                )
-                .unwrap(),
-            "0:AssertionError",
-            "Expected power-of-two alignment for aligned_alloca, got {0}",
-            [Some(alignment), None, None],
-            ctx.current_loc,
-        );
-    }
-
-    let buffer_size = round_up(ctx, size, alignment);
-    let aligned_slices = ctx.builder.build_int_unsigned_div(buffer_size, alignment, "").unwrap();
-
-    // Just to be absolutely sure, alloca in [i8 x alignment] slices
-    let buffer = ctx.builder.build_array_alloca(align_ty, aligned_slices, "").unwrap();
-
-    ctx.builder
-        .build_bit_cast(buffer, llvm_pi8, name.unwrap_or_default())
-        .map(BasicValueEnum::into_pointer_value)
-        .unwrap()
-}

nac3core/src/codegen/model/any.rs

@@ -0,0 +1,41 @@
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum},
+    values::BasicValueEnum,
+};
+
+use super::*;
+use crate::codegen::CodeGenerator;
+
+/// A [`Model`] of any [`BasicTypeEnum`].
+///
+/// Use this when it is infeasible to use model abstractions.
+#[derive(Debug, Clone, Copy)]
+pub struct Any<'ctx>(pub BasicTypeEnum<'ctx>);
+
+impl<'ctx> Model<'ctx> for Any<'ctx> {
+    type Value = BasicValueEnum<'ctx>;
+    type Type = BasicTypeEnum<'ctx>;
+
+    fn llvm_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        _ctx: &'ctx Context,
+    ) -> Self::Type {
+        self.0
+    }
+
+    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &mut G,
+        _ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError> {
+        let ty = ty.as_basic_type_enum();
+        if ty == self.0 {
+            Ok(())
+        } else {
+            Err(ModelError(format!("Expecting {}, but got {}", self.0, ty)))
+        }
+    }
+}

nac3core/src/codegen/model/array.rs

@@ -0,0 +1,146 @@
+use std::fmt;
+
+use inkwell::{
+    context::Context,
+    types::{ArrayType, BasicType, BasicTypeEnum},
+    values::{ArrayValue, IntValue},
+};
+
+use super::*;
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+/// Trait for Rust structs identifying length values for [`Array`].
+pub trait ArrayLen: fmt::Debug + Clone + Copy {
+    fn length(&self) -> u32;
+}
+
+/// A statically known length.
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Len<const N: u32>;
+
+/// A dynamically known length.
+#[derive(Debug, Clone, Copy)]
+pub struct AnyLen(pub u32);
+
+impl<const N: u32> ArrayLen for Len<N> {
+    fn length(&self) -> u32 {
+        N
+    }
+}
+
+impl ArrayLen for AnyLen {
+    fn length(&self) -> u32 {
+        self.0
+    }
+}
+
+/// A Model for an [`ArrayType`].
+///
+/// `Len` should be of a [`LenKind`] and `Item` should be a of [`Model`].
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Array<Len, Item> {
+    /// Length of this array.
+    pub len: Len,
+    /// [`Model`] of the array items.
+    pub item: Item,
+}
+
+impl<'ctx, Len: ArrayLen, Item: Model<'ctx>> Model<'ctx> for Array<Len, Item> {
+    type Value = ArrayValue<'ctx>;
+    type Type = ArrayType<'ctx>;
+
+    fn llvm_type<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &'ctx Context,
+    ) -> Self::Type {
+        self.item.llvm_type(generator, ctx).array_type(self.len.length())
+    }
+
+    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError> {
+        let ty = ty.as_basic_type_enum();
+        let BasicTypeEnum::ArrayType(ty) = ty else {
+            return Err(ModelError(format!("Expecting ArrayType, but got {ty:?}")));
+        };
+
+        if ty.len() != self.len.length() {
+            return Err(ModelError(format!(
+                "Expecting ArrayType with size {}, but got an ArrayType with size {}",
+                ty.len(),
+                self.len.length()
+            )));
+        }
+
+        self.item
+            .check_type(generator, ctx, ty.get_element_type())
+            .map_err(|err| err.under_context("an ArrayType"))?;
+
+        Ok(())
+    }
+}
+
+impl<'ctx, Len: ArrayLen, Item: Model<'ctx>> Instance<'ctx, Ptr<Array<Len, Item>>> {
+    /// Get the pointer to the `i`-th (0-based) array element.
+    pub fn gep(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        i: IntValue<'ctx>,
+    ) -> Instance<'ctx, Ptr<Item>> {
+        let zero = ctx.ctx.i32_type().const_zero();
+        let ptr = unsafe { ctx.builder.build_in_bounds_gep(self.value, &[zero, i], "").unwrap() };
+
+        unsafe { Ptr(self.model.0.item).believe_value(ptr) }
+    }
+
+    /// Like `gep` but `i` is a constant.
+    pub fn gep_const(&self, ctx: &CodeGenContext<'ctx, '_>, i: u64) -> Instance<'ctx, Ptr<Item>> {
+        assert!(
+            i < u64::from(self.model.0.len.length()),
+            "Index {i} is out of bounds. Array length = {}",
+            self.model.0.len.length()
+        );
+
+        let i = ctx.ctx.i32_type().const_int(i, false);
+        self.gep(ctx, i)
+    }
+
+    /// Convenience function equivalent to `.gep(...).load(...)`.
+    pub fn get<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        i: IntValue<'ctx>,
+    ) -> Instance<'ctx, Item> {
+        self.gep(ctx, i).load(generator, ctx)
+    }
+
+    /// Like `get` but `i` is a constant.
+    pub fn get_const<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        i: u64,
+    ) -> Instance<'ctx, Item> {
+        self.gep_const(ctx, i).load(generator, ctx)
+    }
+
+    /// Convenience function equivalent to `.gep(...).store(...)`.
+    pub fn set(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        i: IntValue<'ctx>,
+        value: Instance<'ctx, Item>,
+    ) {
+        self.gep(ctx, i).store(ctx, value);
+    }
+
+    /// Like `set` but `i` is a constant.
+    pub fn set_const(&self, ctx: &CodeGenContext<'ctx, '_>, i: u64, value: Instance<'ctx, Item>) {
+        self.gep_const(ctx, i).store(ctx, value);
+    }
+}

nac3core/src/codegen/model/core.rs

@@ -0,0 +1,207 @@
+use std::fmt;
+
+use inkwell::{context::Context, types::*, values::*};
+use itertools::Itertools;
+
+use super::*;
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+/// A error type for reporting any [`Model`]-related error (e.g., a [`BasicType`] mismatch).
+#[derive(Debug, Clone)]
+pub struct ModelError(pub String);
+
+impl ModelError {
+    /// Append a context message to the error.
+    pub(super) fn under_context(mut self, context: &str) -> Self {
+        self.0.push_str(" ... in ");
+        self.0.push_str(context);
+        self
+    }
+}
+
+/// Trait for Rust structs identifying [`BasicType`]s in the context of a known [`CodeGenerator`] and [`CodeGenContext`].
+///
+/// For instance,
+/// - [`Int<Int32>`] identifies an [`IntType`] with 32-bits.
+/// - [`Int<SizeT>`] identifies an [`IntType`] with bit-width [`CodeGenerator::get_size_type`].
+/// - [`Ptr<Int<SizeT>>`] identifies a [`PointerType`] that points to an [`IntType`] with bit-width [`CodeGenerator::get_size_type`].
+/// - [`Int<AnyInt>`] identifies an [`IntType`] with bit-width of whatever is set in the [`AnyInt`] object.
+/// - [`Any`] identifies a [`BasicType`] set in the [`Any`] object itself.
+///
+/// You can get the [`BasicType`] out of a model with [`Model::get_type`].
+///
+/// Furthermore, [`Instance<'ctx, M>`] is a simple structure that carries a [`BasicValue`] with [`BasicType`] identified by model `M`.
+///
+/// The main purpose of this abstraction is to have a more Rust type-safe way to use Inkwell and give type-hints for programmers.
+///
+/// ### Notes on `Default` trait
+///
+/// For some models like [`Int<Int32>`] or [`Int<SizeT>`], they have a [`Default`] trait since just by looking at their types, it is possible
+/// to tell the [`BasicType`]s they are identifying.
+///
+/// This can be used to create strongly-typed interfaces accepting only values of a specific [`BasicType`] without having to worry about
+/// writing debug assertions to check, for example, if the programmer has passed in an [`IntValue`] with the wrong bit-width.
+/// ```ignore
+/// fn give_me_i32_and_get_a_size_t_back<'ctx>(i32: Instance<'ctx, Int<Int32>>) -> Instance<'ctx, Int<SizeT>> {
+///     // code...
+/// }
+/// ```
+///
+/// ### Notes on converting between Inkwell and model/ge.
+///
+/// Suppose you have an [`IntValue`], and you want to pass it into a function that takes a [`Instance<'ctx, Int<Int32>>`]. You can do use
+/// [`Model::check_value`] or [`Model::believe_value`].
+/// ```ignore
+/// let my_value: IntValue<'ctx>;
+///
+/// let my_value = Int(Int32).check_value(my_value).unwrap(); // Panics if `my_value` is not 32-bit with a descriptive error message.
+///
+/// // or, if you are absolutely certain that `my_value` is 32-bit and doing extra checks is a waste of time:
+/// let my_value = Int(Int32).believe_value(my_value);
+/// ```
+pub trait Model<'ctx>: fmt::Debug + Clone + Copy {
+    /// The [`BasicType`] *variant* this model is identifying.
+    type Type: BasicType<'ctx>;
+
+    /// The [`BasicValue`] type of the [`BasicType`] of this model.
+    type Value: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>>;
+
+    /// Return the [`BasicType`] of this model.
+    #[must_use]
+    fn llvm_type<G: CodeGenerator + ?Sized>(&self, generator: &G, ctx: &'ctx Context)
+        -> Self::Type;
+
+    /// Get the number of bytes of the [`BasicType`] of this model.
+    fn size_of<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> IntValue<'ctx> {
+        self.llvm_type(generator, ctx).size_of().unwrap()
+    }
+
+    /// Check if a [`BasicType`] matches the [`BasicType`] of this model.
+    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError>;
+
+    /// Create an instance from a value.
+    ///
+    /// # Safety
+    ///
+    /// Caller must make sure the type of `value` and the type of this `model` are equivalent.
+    #[must_use]
+    unsafe fn believe_value(&self, value: Self::Value) -> Instance<'ctx, Self> {
+        Instance { model: *self, value }
+    }
+
+    /// Check if a [`BasicValue`]'s type is equivalent to the type of this model.
+    /// Wrap the [`BasicValue`] into an [`Instance`] if it is.
+    fn check_value<V: BasicValue<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        value: V,
+    ) -> Result<Instance<'ctx, Self>, ModelError> {
+        let value = value.as_basic_value_enum();
+        self.check_type(generator, ctx, value.get_type())
+            .map_err(|err| err.under_context(format!("the value {value:?}").as_str()))?;
+
+        let Ok(value) = Self::Value::try_from(value) else {
+            unreachable!("check_type() has bad implementation")
+        };
+        unsafe { Ok(self.believe_value(value)) }
+    }
+
+    // Allocate a value on the stack and return its pointer.
+    fn alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Ptr<Self>> {
+        let p = ctx.builder.build_alloca(self.llvm_type(generator, ctx.ctx), "").unwrap();
+        unsafe { Ptr(*self).believe_value(p) }
+    }
+
+    // Allocate an array on the stack and return its pointer.
+    fn array_alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        len: IntValue<'ctx>,
+    ) -> Instance<'ctx, Ptr<Self>> {
+        let p =
+            ctx.builder.build_array_alloca(self.llvm_type(generator, ctx.ctx), len, "").unwrap();
+        unsafe { Ptr(*self).believe_value(p) }
+    }
+
+    fn var_alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&str>,
+    ) -> Result<Instance<'ctx, Ptr<Self>>, String> {
+        let ty = self.llvm_type(generator, ctx.ctx).as_basic_type_enum();
+        let p = generator.gen_var_alloc(ctx, ty, name)?;
+        unsafe { Ok(Ptr(*self).believe_value(p)) }
+    }
+
+    fn array_var_alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        len: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> Result<Instance<'ctx, Ptr<Self>>, String> {
+        // TODO: Remove ArraySliceValue
+        let ty = self.llvm_type(generator, ctx.ctx).as_basic_type_enum();
+        let p = generator.gen_array_var_alloc(ctx, ty, len, name)?;
+        unsafe { Ok(Ptr(*self).believe_value(PointerValue::from(p))) }
+    }
+
+    /// Allocate a constant array.
+    fn const_array<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        values: &[Instance<'ctx, Self>],
+    ) -> Instance<'ctx, Array<AnyLen, Self>> {
+        macro_rules! make {
+            ($t:expr, $into_value:expr) => {
+                $t.const_array(
+                    &values
+                        .iter()
+                        .map(|x| $into_value(x.value.as_basic_value_enum()))
+                        .collect_vec(),
+                )
+            };
+        }
+
+        let value = match self.llvm_type(generator, ctx).as_basic_type_enum() {
+            BasicTypeEnum::ArrayType(t) => make!(t, BasicValueEnum::into_array_value),
+            BasicTypeEnum::IntType(t) => make!(t, BasicValueEnum::into_int_value),
+            BasicTypeEnum::FloatType(t) => make!(t, BasicValueEnum::into_float_value),
+            BasicTypeEnum::PointerType(t) => make!(t, BasicValueEnum::into_pointer_value),
+            BasicTypeEnum::StructType(t) => make!(t, BasicValueEnum::into_struct_value),
+            BasicTypeEnum::VectorType(t) => make!(t, BasicValueEnum::into_vector_value),
+        };
+
+        Array { len: AnyLen(values.len() as u32), item: *self }
+            .check_value(generator, ctx, value)
+            .unwrap()
+    }
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct Instance<'ctx, M: Model<'ctx>> {
+    /// The model of this instance.
+    pub model: M,
+
+    /// The value of this instance.
+    ///
+    /// It is guaranteed the [`BasicType`] of `value` is consistent with that of `model`.
+    pub value: M::Value,
+}

nac3core/src/codegen/model/float.rs

@@ -0,0 +1,93 @@
+use std::fmt;
+
+use inkwell::{
+    context::Context,
+    types::{BasicType, FloatType},
+    values::FloatValue,
+};
+
+use super::*;
+use crate::codegen::CodeGenerator;
+
+pub trait FloatKind<'ctx>: fmt::Debug + Clone + Copy {
+    fn get_float_type<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &'ctx Context,
+    ) -> FloatType<'ctx>;
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Float32;
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Float64;
+
+impl<'ctx> FloatKind<'ctx> for Float32 {
+    fn get_float_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        ctx: &'ctx Context,
+    ) -> FloatType<'ctx> {
+        ctx.f32_type()
+    }
+}
+
+impl<'ctx> FloatKind<'ctx> for Float64 {
+    fn get_float_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        ctx: &'ctx Context,
+    ) -> FloatType<'ctx> {
+        ctx.f64_type()
+    }
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct AnyFloat<'ctx>(FloatType<'ctx>);
+
+impl<'ctx> FloatKind<'ctx> for AnyFloat<'ctx> {
+    fn get_float_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        _ctx: &'ctx Context,
+    ) -> FloatType<'ctx> {
+        self.0
+    }
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Float<N>(pub N);
+
+impl<'ctx, N: FloatKind<'ctx>> Model<'ctx> for Float<N> {
+    type Value = FloatValue<'ctx>;
+    type Type = FloatType<'ctx>;
+
+    fn llvm_type<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &'ctx Context,
+    ) -> Self::Type {
+        self.0.get_float_type(generator, ctx)
+    }
+
+    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError> {
+        let ty = ty.as_basic_type_enum();
+        let Ok(ty) = FloatType::try_from(ty) else {
+            return Err(ModelError(format!("Expecting FloatType, but got {ty:?}")));
+        };
+
+        let exp_ty = self.0.get_float_type(generator, ctx);
+
+        // TODO: Inkwell does not have get_bit_width for FloatType?
+        if ty != exp_ty {
+            return Err(ModelError(format!("Expecting {exp_ty:?}, but got {ty:?}")));
+        }
+
+        Ok(())
+    }
+}

nac3core/src/codegen/model/function.rs

@@ -0,0 +1,121 @@
+use inkwell::{
+    attributes::{Attribute, AttributeLoc},
+    types::{BasicMetadataTypeEnum, BasicType, FunctionType},
+    values::{AnyValue, BasicMetadataValueEnum, BasicValue, BasicValueEnum, CallSiteValue},
+};
+use itertools::Itertools;
+
+use super::*;
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+#[derive(Debug, Clone, Copy)]
+struct Arg<'ctx> {
+    ty: BasicMetadataTypeEnum<'ctx>,
+    val: BasicMetadataValueEnum<'ctx>,
+}
+
+/// A convenience structure to construct & call an LLVM function.
+///
+/// ### Usage
+///
+/// The syntax is like this:
+/// ```ignore
+/// let result = CallFunction::begin("my_function_name")
+///   .attrs(...)
+///   .arg(arg1)
+///   .arg(arg2)
+///   .arg(arg3)
+///   .returning("my_function_result", Int32);
+/// ```
+///
+/// The function `my_function_name` is called when `.returning()` (or its variants) is called, returning
+/// the result as an `Instance<'ctx, Int<Int32>>`.
+///
+/// If `my_function_name` has not been declared in `ctx.module`, once `.returning()` is called, a function
+/// declaration of `my_function_name` is added to `ctx.module`, where the [`FunctionType`] is deduced from
+/// the argument types and returning type.
+pub struct FnCall<'ctx, 'a, 'b, 'c, 'd, G: CodeGenerator + ?Sized> {
+    generator: &'d mut G,
+    ctx: &'b CodeGenContext<'ctx, 'a>,
+    /// Function name
+    name: &'c str,
+    /// Call arguments
+    args: Vec<Arg<'ctx>>,
+    /// LLVM function Attributes
+    attrs: Vec<&'static str>,
+}
+
+impl<'ctx, 'a, 'b, 'c, 'd, G: CodeGenerator + ?Sized> FnCall<'ctx, 'a, 'b, 'c, 'd, G> {
+    pub fn builder(generator: &'d mut G, ctx: &'b CodeGenContext<'ctx, 'a>, name: &'c str) -> Self {
+        FnCall { generator, ctx, name, args: Vec::new(), attrs: Vec::new() }
+    }
+
+    /// Push a list of LLVM function attributes to the function declaration.
+    #[must_use]
+    pub fn attrs(mut self, attrs: Vec<&'static str>) -> Self {
+        self.attrs = attrs;
+        self
+    }
+
+    /// Push a call argument to the function call.
+    #[allow(clippy::needless_pass_by_value)]
+    #[must_use]
+    pub fn arg<M: Model<'ctx>>(mut self, arg: Instance<'ctx, M>) -> Self {
+        let arg = Arg {
+            ty: arg.model.llvm_type(self.generator, self.ctx.ctx).as_basic_type_enum().into(),
+            val: arg.value.as_basic_value_enum().into(),
+        };
+        self.args.push(arg);
+        self
+    }
+
+    /// Call the function and expect the function to return a value of type of `return_model`.
+    #[must_use]
+    pub fn returning<M: Model<'ctx>>(self, name: &str, return_model: M) -> Instance<'ctx, M> {
+        let ret_ty = return_model.llvm_type(self.generator, self.ctx.ctx);
+
+        let ret = self.call(|tys| ret_ty.fn_type(tys, false), name);
+        let ret = BasicValueEnum::try_from(ret.as_any_value_enum()).unwrap(); // Must work
+        let ret = return_model.check_value(self.generator, self.ctx.ctx, ret).unwrap(); // Must work
+        ret
+    }
+
+    /// Like [`CallFunction::returning_`] but `return_model` is automatically inferred.
+    #[must_use]
+    pub fn returning_auto<M: Model<'ctx> + Default>(self, name: &str) -> Instance<'ctx, M> {
+        self.returning(name, M::default())
+    }
+
+    /// Call the function and expect the function to return a void-type.
+    pub fn returning_void(self) {
+        let ret_ty = self.ctx.ctx.void_type();
+
+        let _ = self.call(|tys| ret_ty.fn_type(tys, false), "");
+    }
+
+    fn call<F>(&self, make_fn_type: F, return_value_name: &str) -> CallSiteValue<'ctx>
+    where
+        F: FnOnce(&[BasicMetadataTypeEnum<'ctx>]) -> FunctionType<'ctx>,
+    {
+        // Get the LLVM function.
+        let func = self.ctx.module.get_function(self.name).unwrap_or_else(|| {
+            // Declare the function if it doesn't exist.
+            let tys = self.args.iter().map(|arg| arg.ty).collect_vec();
+
+            let func_type = make_fn_type(&tys);
+            let func = self.ctx.module.add_function(self.name, func_type, None);
+
+            for attr in &self.attrs {
+                func.add_attribute(
+                    AttributeLoc::Function,
+                    self.ctx.ctx.create_enum_attribute(Attribute::get_named_enum_kind_id(attr), 0),
+                );
+            }
+
+            func
+        });
+
+        let vals = self.args.iter().map(|arg| arg.val).collect_vec();
+        self.ctx.builder.build_call(func, &vals, return_value_name).unwrap()
+    }
+}

nac3core/src/codegen/model/int.rs

@@ -0,0 +1,421 @@
+use std::{cmp::Ordering, fmt};
+
+use inkwell::{
+    context::Context,
+    types::{BasicType, IntType},
+    values::IntValue,
+    IntPredicate,
+};
+
+use super::*;
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+pub trait IntKind<'ctx>: fmt::Debug + Clone + Copy {
+    fn get_int_type<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &'ctx Context,
+    ) -> IntType<'ctx>;
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Bool;
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Byte;
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Int32;
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Int64;
+#[derive(Debug, Clone, Copy, Default)]
+pub struct SizeT;
+
+impl<'ctx> IntKind<'ctx> for Bool {
+    fn get_int_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        ctx: &'ctx Context,
+    ) -> IntType<'ctx> {
+        ctx.bool_type()
+    }
+}
+
+impl<'ctx> IntKind<'ctx> for Byte {
+    fn get_int_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        ctx: &'ctx Context,
+    ) -> IntType<'ctx> {
+        ctx.i8_type()
+    }
+}
+
+impl<'ctx> IntKind<'ctx> for Int32 {
+    fn get_int_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        ctx: &'ctx Context,
+    ) -> IntType<'ctx> {
+        ctx.i32_type()
+    }
+}
+
+impl<'ctx> IntKind<'ctx> for Int64 {
+    fn get_int_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        ctx: &'ctx Context,
+    ) -> IntType<'ctx> {
+        ctx.i64_type()
+    }
+}
+
+impl<'ctx> IntKind<'ctx> for SizeT {
+    fn get_int_type<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &'ctx Context,
+    ) -> IntType<'ctx> {
+        generator.get_size_type(ctx)
+    }
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct AnyInt<'ctx>(pub IntType<'ctx>);
+
+impl<'ctx> IntKind<'ctx> for AnyInt<'ctx> {
+    fn get_int_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        _ctx: &'ctx Context,
+    ) -> IntType<'ctx> {
+        self.0
+    }
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Int<N>(pub N);
+
+impl<'ctx, N: IntKind<'ctx>> Model<'ctx> for Int<N> {
+    type Value = IntValue<'ctx>;
+    type Type = IntType<'ctx>;
+
+    fn llvm_type<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &'ctx Context,
+    ) -> Self::Type {
+        self.0.get_int_type(generator, ctx)
+    }
+
+    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError> {
+        let ty = ty.as_basic_type_enum();
+        let Ok(ty) = IntType::try_from(ty) else {
+            return Err(ModelError(format!("Expecting IntType, but got {ty:?}")));
+        };
+
+        let exp_ty = self.0.get_int_type(generator, ctx);
+        if ty.get_bit_width() != exp_ty.get_bit_width() {
+            return Err(ModelError(format!(
+                "Expecting IntType to have {} bit(s), but got {} bit(s)",
+                exp_ty.get_bit_width(),
+                ty.get_bit_width()
+            )));
+        }
+
+        Ok(())
+    }
+}
+
+impl<'ctx, N: IntKind<'ctx>> Int<N> {
+    pub fn const_int<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        value: u64,
+        sign_extend: bool,
+    ) -> Instance<'ctx, Self> {
+        let value = self.llvm_type(generator, ctx).const_int(value, sign_extend);
+        unsafe { self.believe_value(value) }
+    }
+
+    pub fn const_0<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> Instance<'ctx, Self> {
+        let value = self.llvm_type(generator, ctx).const_zero();
+        unsafe { self.believe_value(value) }
+    }
+
+    pub fn const_1<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> Instance<'ctx, Self> {
+        self.const_int(generator, ctx, 1, false)
+    }
+
+    pub fn const_all_ones<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> Instance<'ctx, Self> {
+        let value = self.llvm_type(generator, ctx).const_all_ones();
+        unsafe { self.believe_value(value) }
+    }
+
+    pub fn s_extend_or_bit_cast<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> Instance<'ctx, Self> {
+        assert!(
+            value.get_type().get_bit_width()
+                <= self.0.get_int_type(generator, ctx.ctx).get_bit_width()
+        );
+        let value = ctx
+            .builder
+            .build_int_s_extend_or_bit_cast(value, self.llvm_type(generator, ctx.ctx), "")
+            .unwrap();
+        unsafe { self.believe_value(value) }
+    }
+
+    pub fn s_extend<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> Instance<'ctx, Self> {
+        assert!(
+            value.get_type().get_bit_width()
+                < self.0.get_int_type(generator, ctx.ctx).get_bit_width()
+        );
+        let value =
+            ctx.builder.build_int_s_extend(value, self.llvm_type(generator, ctx.ctx), "").unwrap();
+        unsafe { self.believe_value(value) }
+    }
+
+    pub fn z_extend_or_bit_cast<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> Instance<'ctx, Self> {
+        assert!(
+            value.get_type().get_bit_width()
+                <= self.0.get_int_type(generator, ctx.ctx).get_bit_width()
+        );
+        let value = ctx
+            .builder
+            .build_int_z_extend_or_bit_cast(value, self.llvm_type(generator, ctx.ctx), "")
+            .unwrap();
+        unsafe { self.believe_value(value) }
+    }
+
+    pub fn z_extend<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> Instance<'ctx, Self> {
+        assert!(
+            value.get_type().get_bit_width()
+                < self.0.get_int_type(generator, ctx.ctx).get_bit_width()
+        );
+        let value =
+            ctx.builder.build_int_z_extend(value, self.llvm_type(generator, ctx.ctx), "").unwrap();
+        unsafe { self.believe_value(value) }
+    }
+
+    pub fn truncate_or_bit_cast<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> Instance<'ctx, Self> {
+        assert!(
+            value.get_type().get_bit_width()
+                >= self.0.get_int_type(generator, ctx.ctx).get_bit_width()
+        );
+        let value = ctx
+            .builder
+            .build_int_truncate_or_bit_cast(value, self.llvm_type(generator, ctx.ctx), "")
+            .unwrap();
+        unsafe { self.believe_value(value) }
+    }
+
+    pub fn truncate<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> Instance<'ctx, Self> {
+        assert!(
+            value.get_type().get_bit_width()
+                > self.0.get_int_type(generator, ctx.ctx).get_bit_width()
+        );
+        let value =
+            ctx.builder.build_int_truncate(value, self.llvm_type(generator, ctx.ctx), "").unwrap();
+        unsafe { self.believe_value(value) }
+    }
+
+    /// `sext` or `trunc` an int to this model's int type. Does nothing if equal bit-widths.
+    pub fn s_extend_or_truncate<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> Instance<'ctx, Self> {
+        let their_width = value.get_type().get_bit_width();
+        let our_width = self.0.get_int_type(generator, ctx.ctx).get_bit_width();
+        match their_width.cmp(&our_width) {
+            Ordering::Less => self.s_extend(generator, ctx, value),
+            Ordering::Equal => unsafe { self.believe_value(value) },
+            Ordering::Greater => self.truncate(generator, ctx, value),
+        }
+    }
+
+    /// `zext` or `trunc` an int to this model's int type. Does nothing if equal bit-widths.
+    pub fn z_extend_or_truncate<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> Instance<'ctx, Self> {
+        let their_width = value.get_type().get_bit_width();
+        let our_width = self.0.get_int_type(generator, ctx.ctx).get_bit_width();
+        match their_width.cmp(&our_width) {
+            Ordering::Less => self.z_extend(generator, ctx, value),
+            Ordering::Equal => unsafe { self.believe_value(value) },
+            Ordering::Greater => self.truncate(generator, ctx, value),
+        }
+    }
+}
+
+impl Int<Bool> {
+    #[must_use]
+    pub fn const_false<'ctx, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> Instance<'ctx, Self> {
+        self.const_int(generator, ctx, 0, false)
+    }
+
+    #[must_use]
+    pub fn const_true<'ctx, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> Instance<'ctx, Self> {
+        self.const_int(generator, ctx, 1, false)
+    }
+}
+
+impl<'ctx, N: IntKind<'ctx>> Instance<'ctx, Int<N>> {
+    pub fn s_extend_or_bit_cast<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+    ) -> Instance<'ctx, Int<NewN>> {
+        Int(to_int_kind).s_extend_or_bit_cast(generator, ctx, self.value)
+    }
+
+    pub fn s_extend<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+    ) -> Instance<'ctx, Int<NewN>> {
+        Int(to_int_kind).s_extend(generator, ctx, self.value)
+    }
+
+    pub fn z_extend_or_bit_cast<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+    ) -> Instance<'ctx, Int<NewN>> {
+        Int(to_int_kind).z_extend_or_bit_cast(generator, ctx, self.value)
+    }
+
+    pub fn z_extend<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+    ) -> Instance<'ctx, Int<NewN>> {
+        Int(to_int_kind).z_extend(generator, ctx, self.value)
+    }
+
+    pub fn truncate_or_bit_cast<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+    ) -> Instance<'ctx, Int<NewN>> {
+        Int(to_int_kind).truncate_or_bit_cast(generator, ctx, self.value)
+    }
+
+    pub fn truncate<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+    ) -> Instance<'ctx, Int<NewN>> {
+        Int(to_int_kind).truncate(generator, ctx, self.value)
+    }
+
+    pub fn s_extend_or_truncate<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+    ) -> Instance<'ctx, Int<NewN>> {
+        Int(to_int_kind).s_extend_or_truncate(generator, ctx, self.value)
+    }
+
+    pub fn z_extend_or_truncate<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+    ) -> Instance<'ctx, Int<NewN>> {
+        Int(to_int_kind).z_extend_or_truncate(generator, ctx, self.value)
+    }
+
+    #[must_use]
+    pub fn add(&self, ctx: &CodeGenContext<'ctx, '_>, other: Self) -> Self {
+        let value = ctx.builder.build_int_add(self.value, other.value, "").unwrap();
+        unsafe { self.model.believe_value(value) }
+    }
+
+    #[must_use]
+    pub fn sub(&self, ctx: &CodeGenContext<'ctx, '_>, other: Self) -> Self {
+        let value = ctx.builder.build_int_sub(self.value, other.value, "").unwrap();
+        unsafe { self.model.believe_value(value) }
+    }
+
+    #[must_use]
+    pub fn mul(&self, ctx: &CodeGenContext<'ctx, '_>, other: Self) -> Self {
+        let value = ctx.builder.build_int_mul(self.value, other.value, "").unwrap();
+        unsafe { self.model.believe_value(value) }
+    }
+
+    pub fn compare(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        op: IntPredicate,
+        other: Self,
+    ) -> Instance<'ctx, Int<Bool>> {
+        let value = ctx.builder.build_int_compare(op, self.value, other.value, "").unwrap();
+        unsafe { Int(Bool).believe_value(value) }
+    }
+}

nac3core/src/codegen/model/mod.rs

@@ -0,0 +1,17 @@
+mod any;
+mod array;
+mod core;
+mod float;
+pub mod function;
+mod int;
+mod ptr;
+mod structure;
+pub mod util;
+
+pub use any::*;
+pub use array::*;
+pub use core::*;
+pub use float::*;
+pub use int::*;
+pub use ptr::*;
+pub use structure::*;

nac3core/src/codegen/model/ptr.rs

@@ -0,0 +1,222 @@
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum, PointerType},
+    values::{IntValue, PointerValue},
+    AddressSpace,
+};
+
+use super::*;
+use crate::codegen::{llvm_intrinsics::call_memcpy_generic, CodeGenContext, CodeGenerator};
+
+/// A model for [`PointerType`].
+///
+/// `Item` is the element type this pointer is pointing to, and should be of a [`Model`].
+///
+// TODO: LLVM 15: `Item` is a Rust type-hint for the LLVM type of value the `.store()/.load()` family
+// of functions return. If a truly opaque pointer is needed, tell the programmer to use `OpaquePtr`.
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Ptr<Item>(pub Item);
+
+/// An opaque pointer. Like [`Ptr`] but without any Rust type-hints about its element type.
+///
+/// `.load()/.store()` is not available for [`Instance`]s of opaque pointers.
+pub type OpaquePtr = Ptr<()>;
+
+// TODO: LLVM 15: `Item: Model<'ctx>` don't even need to be a model anymore. It will only be
+// a type-hint for the `.load()/.store()` functions for the `pointee_ty`.
+//
+// See https://thedan64.github.io/inkwell/inkwell/builder/struct.Builder.html#method.build_load.
+impl<'ctx, Item: Model<'ctx>> Model<'ctx> for Ptr<Item> {
+    type Value = PointerValue<'ctx>;
+    type Type = PointerType<'ctx>;
+
+    fn llvm_type<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &'ctx Context,
+    ) -> Self::Type {
+        // TODO: LLVM 15: ctx.ptr_type(AddressSpace::default())
+        self.0.llvm_type(generator, ctx).ptr_type(AddressSpace::default())
+    }
+
+    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError> {
+        let ty = ty.as_basic_type_enum();
+        let Ok(ty) = PointerType::try_from(ty) else {
+            return Err(ModelError(format!("Expecting PointerType, but got {ty:?}")));
+        };
+
+        let elem_ty = ty.get_element_type();
+        let Ok(elem_ty) = BasicTypeEnum::try_from(elem_ty) else {
+            return Err(ModelError(format!(
+                "Expecting pointer element type to be a BasicTypeEnum, but got {elem_ty:?}"
+            )));
+        };
+
+        // TODO: inkwell `get_element_type()` will be deprecated.
+        // Remove the check for `get_element_type()` when the time comes.
+        self.0
+            .check_type(generator, ctx, elem_ty)
+            .map_err(|err| err.under_context("a PointerType"))?;
+
+        Ok(())
+    }
+}
+
+impl<'ctx, Item: Model<'ctx>> Ptr<Item> {
+    /// Return a ***constant*** nullptr.
+    pub fn nullptr<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> Instance<'ctx, Ptr<Item>> {
+        let ptr = self.llvm_type(generator, ctx).const_null();
+        unsafe { self.believe_value(ptr) }
+    }
+
+    /// Cast a pointer into this model with [`inkwell::builder::Builder::build_pointer_cast`]
+    pub fn pointer_cast<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        ptr: PointerValue<'ctx>,
+    ) -> Instance<'ctx, Ptr<Item>> {
+        // TODO: LLVM 15: Write in an impl where `Item` does not have to be `Model<'ctx>`.
+        // TODO: LLVM 15: This function will only have to be:
+        // ```
+        // return self.believe_value(ptr);
+        // ```
+        let t = self.llvm_type(generator, ctx.ctx);
+        let ptr = ctx.builder.build_pointer_cast(ptr, t, "").unwrap();
+        unsafe { self.believe_value(ptr) }
+    }
+}
+
+impl<'ctx, Item: Model<'ctx>> Instance<'ctx, Ptr<Item>> {
+    /// Offset the pointer by [`inkwell::builder::Builder::build_in_bounds_gep`].
+    #[must_use]
+    pub fn offset(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        offset: IntValue<'ctx>,
+    ) -> Instance<'ctx, Ptr<Item>> {
+        let p = unsafe { ctx.builder.build_in_bounds_gep(self.value, &[offset], "").unwrap() };
+        unsafe { self.model.believe_value(p) }
+    }
+
+    /// Offset the pointer by [`inkwell::builder::Builder::build_in_bounds_gep`] by a constant offset.
+    #[must_use]
+    pub fn offset_const(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        offset: i64,
+    ) -> Instance<'ctx, Ptr<Item>> {
+        let offset = ctx.ctx.i32_type().const_int(offset as u64, true);
+        self.offset(ctx, offset)
+    }
+
+    pub fn set_index(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        index: IntValue<'ctx>,
+        value: Instance<'ctx, Item>,
+    ) {
+        self.offset(ctx, index).store(ctx, value);
+    }
+
+    pub fn set_index_const(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        index: i64,
+        value: Instance<'ctx, Item>,
+    ) {
+        self.offset_const(ctx, index).store(ctx, value);
+    }
+
+    pub fn get_index<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        index: IntValue<'ctx>,
+    ) -> Instance<'ctx, Item> {
+        self.offset(ctx, index).load(generator, ctx)
+    }
+
+    pub fn get_index_const<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        index: i64,
+    ) -> Instance<'ctx, Item> {
+        self.offset_const(ctx, index).load(generator, ctx)
+    }
+
+    /// Load the value with [`inkwell::builder::Builder::build_load`].
+    pub fn load<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Item> {
+        let value = ctx.builder.build_load(self.value, "").unwrap();
+        self.model.0.check_value(generator, ctx.ctx, value).unwrap() // If unwrap() panics, there is a logic error.
+    }
+
+    /// Store a value with [`inkwell::builder::Builder::build_store`].
+    pub fn store(&self, ctx: &CodeGenContext<'ctx, '_>, value: Instance<'ctx, Item>) {
+        ctx.builder.build_store(self.value, value.value).unwrap();
+    }
+
+    /// Return a casted pointer of element type `NewElement` with [`inkwell::builder::Builder::build_pointer_cast`].
+    pub fn pointer_cast<NewItem: Model<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        new_item: NewItem,
+    ) -> Instance<'ctx, Ptr<NewItem>> {
+        // TODO: LLVM 15: Write in an impl where `Item` does not have to be `Model<'ctx>`.
+        Ptr(new_item).pointer_cast(generator, ctx, self.value)
+    }
+
+    /// Cast this pointer to `uint8_t*`
+    pub fn cast_to_pi8<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Ptr<Int<Byte>>> {
+        Ptr(Int(Byte)).pointer_cast(generator, ctx, self.value)
+    }
+
+    /// Check if the pointer is null with [`inkwell::builder::Builder::build_is_null`].
+    pub fn is_null(&self, ctx: &CodeGenContext<'ctx, '_>) -> Instance<'ctx, Int<Bool>> {
+        let value = ctx.builder.build_is_null(self.value, "").unwrap();
+        unsafe { Int(Bool).believe_value(value) }
+    }
+
+    /// Check if the pointer is not null with [`inkwell::builder::Builder::build_is_not_null`].
+    pub fn is_not_null(&self, ctx: &CodeGenContext<'ctx, '_>) -> Instance<'ctx, Int<Bool>> {
+        let value = ctx.builder.build_is_not_null(self.value, "").unwrap();
+        unsafe { Int(Bool).believe_value(value) }
+    }
+
+    /// `memcpy` from another pointer.
+    pub fn copy_from<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        source: Self,
+        num_items: IntValue<'ctx>,
+    ) {
+        // Force extend `num_items` and `itemsize` to `i64` so their types would match.
+        let itemsize = self.model.size_of(generator, ctx.ctx);
+        let itemsize = Int(SizeT).z_extend_or_truncate(generator, ctx, itemsize);
+        let num_items = Int(SizeT).z_extend_or_truncate(generator, ctx, num_items);
+        let totalsize = itemsize.mul(ctx, num_items);
+
+        let is_volatile = ctx.ctx.bool_type().const_zero(); // is_volatile = false
+        call_memcpy_generic(ctx, self.value, source.value, totalsize.value, is_volatile);
+    }
+}

nac3core/src/codegen/model/structure.rs

@@ -0,0 +1,363 @@
+use std::fmt;
+
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum, StructType},
+    values::{BasicValueEnum, StructValue},
+};
+
+use super::*;
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+/// A traveral that traverses a Rust `struct` that is used to declare an LLVM's struct's field types.
+pub trait FieldTraversal<'ctx> {
+    /// Output type of [`FieldTraversal::add`].
+    type Output<M>;
+
+    /// Traverse through the type of a declared field and do something with it.
+    ///
+    /// * `name` - The cosmetic name of the LLVM field. Used for debugging.
+    /// * `model` - The [`Model`] representing the LLVM type of this field.
+    fn add<M: Model<'ctx>>(&mut self, name: &'static str, model: M) -> Self::Output<M>;
+
+    /// Like [`FieldTraversal::add`] but [`Model`] is automatically inferred from its [`Default`] trait.
+    fn add_auto<M: Model<'ctx> + Default>(&mut self, name: &'static str) -> Self::Output<M> {
+        self.add(name, M::default())
+    }
+}
+
+/// Descriptor of an LLVM struct field.
+#[derive(Debug, Clone, Copy)]
+pub struct GepField<M> {
+    /// The GEP index of this field. This is the index to use with `build_gep`.
+    pub gep_index: u32,
+    /// The cosmetic name of this field.
+    pub name: &'static str,
+    /// The [`Model`] of this field's type.
+    pub model: M,
+}
+
+/// A traversal to calculate the GEP index of fields.
+pub struct GepFieldTraversal {
+    /// The current GEP index.
+    gep_index_counter: u32,
+}
+
+impl<'ctx> FieldTraversal<'ctx> for GepFieldTraversal {
+    type Output<M> = GepField<M>;
+
+    fn add<M: Model<'ctx>>(&mut self, name: &'static str, model: M) -> Self::Output<M> {
+        let gep_index = self.gep_index_counter;
+        self.gep_index_counter += 1;
+        Self::Output { gep_index, name, model }
+    }
+}
+
+/// A traversal to collect the field types of a struct.
+///
+/// This is used to collect field types and construct the LLVM struct type with [`Context::struct_type`].
+struct TypeFieldTraversal<'ctx, 'a, G: CodeGenerator + ?Sized> {
+    generator: &'a G,
+    ctx: &'ctx Context,
+    /// The collected field types so far in exact order.
+    field_types: Vec<BasicTypeEnum<'ctx>>,
+}
+
+impl<'ctx, 'a, G: CodeGenerator + ?Sized> FieldTraversal<'ctx> for TypeFieldTraversal<'ctx, 'a, G> {
+    type Output<M> = (); // Checking types return nothing.
+
+    fn add<M: Model<'ctx>>(&mut self, _name: &'static str, model: M) -> Self::Output<M> {
+        let t = model.llvm_type(self.generator, self.ctx).as_basic_type_enum();
+        self.field_types.push(t);
+    }
+}
+
+/// A traversal to check the types of fields.
+struct CheckTypeFieldTraversal<'ctx, 'a, G: CodeGenerator + ?Sized> {
+    generator: &'a mut G,
+    ctx: &'ctx Context,
+    /// The current GEP index, so we can tell the index of the field we are checking
+    /// and report the GEP index.
+    gep_index_counter: u32,
+    /// The [`StructType`] to check.
+    scrutinee: StructType<'ctx>,
+    /// The list of collected errors so far.
+    errors: Vec<ModelError>,
+}
+
+impl<'ctx, 'a, G: CodeGenerator + ?Sized> FieldTraversal<'ctx>
+    for CheckTypeFieldTraversal<'ctx, 'a, G>
+{
+    type Output<M> = (); // Checking types return nothing.
+
+    fn add<M: Model<'ctx>>(&mut self, name: &'static str, model: M) -> Self::Output<M> {
+        let gep_index = self.gep_index_counter;
+        self.gep_index_counter += 1;
+
+        if let Some(t) = self.scrutinee.get_field_type_at_index(gep_index) {
+            if let Err(err) = model.check_type(self.generator, self.ctx, t) {
+                self.errors
+                    .push(err.under_context(format!("field #{gep_index} '{name}'").as_str()));
+            }
+        }
+        // Otherwise, it will be caught by Struct's `check_type`.
+    }
+}
+
+/// A trait for Rust structs identifying LLVM structures.
+///
+/// ### Example
+///
+/// Suppose you want to define this structure:
+/// ```c
+/// template <typename T>
+/// struct ContiguousNDArray {
+///     size_t ndims;
+///     size_t* shape;
+///     T* data;
+/// }
+/// ```
+///
+/// This is how it should be done:
+/// ```ignore
+/// pub struct ContiguousNDArrayFields<'ctx, F: FieldTraversal<'ctx>, Item: Model<'ctx>> {
+///     pub ndims: F::Out<Int<SizeT>>,
+///     pub shape: F::Out<Ptr<Int<SizeT>>>,
+///     pub data: F::Out<Ptr<Item>>,
+/// }
+///
+/// /// An ndarray without strides and non-opaque `data` field in NAC3.
+/// #[derive(Debug, Clone, Copy)]
+/// pub struct ContiguousNDArray<M> {
+///     /// [`Model`] of the items.
+///     pub item: M,
+/// }
+///
+/// impl<'ctx, Item: Model<'ctx>> StructKind<'ctx> for ContiguousNDArray<Item> {
+///     type Fields<F: FieldTraversal<'ctx>> = ContiguousNDArrayFields<'ctx, F, Item>;
+///
+///     fn traverse_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+///         // The order of `traversal.add*` is important
+///         Self::Fields {
+///             ndims: traversal.add_auto("ndims"),
+///             shape: traversal.add_auto("shape"),
+///             data: traversal.add("data", Ptr(self.item)),
+///         }
+///     }
+/// }
+/// ```
+///
+/// The [`FieldTraversal`] here is a mechanism to allow the fields of `ContiguousNDArrayFields` to be
+/// traversed to do useful work such as:
+///
+/// - To create the [`StructType`] of `ContiguousNDArray` by collecting [`BasicType`]s of the fields.
+/// - To enable the `.gep(ctx, |f| f.ndims).store(ctx, ...)` syntax.
+///
+/// Suppose now that you have defined `ContiguousNDArray` and you want to allocate a `ContiguousNDArray`
+/// with dtype `float64` in LLVM, this is how you do it:
+/// ```ignore
+/// type F64NDArray = Struct<ContiguousNDArray<Float<Float64>>>; // Type alias for leaner documentation
+/// let model: F64NDArray = Struct(ContigousNDArray { item: Float(Float64) });
+/// let ndarray: Instance<'ctx, Ptr<F64NDArray>> = model.alloca(generator, ctx);
+/// ```
+///
+/// ...and here is how you may manipulate/access `ndarray`:
+///
+/// (NOTE: some arguments have been omitted)
+///
+/// ```ignore
+/// // Get `&ndarray->data`
+/// ndarray.gep(|f| f.data); // type: Instance<'ctx, Ptr<Float<Float64>>>
+///
+/// // Get `ndarray->ndims`
+/// ndarray.get(|f| f.ndims); // type: Instance<'ctx, Int<SizeT>>
+///
+/// // Get `&ndarray->ndims`
+/// ndarray.gep(|f| f.ndims); // type: Instance<'ctx, Ptr<Int<SizeT>>>
+///
+/// // Get `ndarray->shape[0]`
+/// ndarray.get(|f| f.shape).get_index_const(0); // Instance<'ctx, Int<SizeT>>
+///
+/// // Get `&ndarray->shape[2]`
+/// ndarray.get(|f| f.shape).offset_const(2); // Instance<'ctx, Ptr<Int<SizeT>>>
+///
+/// // Do `ndarray->ndims = 3;`
+/// let num_3 = Int(SizeT).const_int(3);
+/// ndarray.set(|f| f.ndims, num_3);
+/// ```
+pub trait StructKind<'ctx>: fmt::Debug + Clone + Copy {
+    /// The associated fields of this struct.
+    type Fields<F: FieldTraversal<'ctx>>;
+
+    /// Traverse through all fields of this [`StructKind`].
+    ///
+    /// Only used internally in this module for implementing other components.
+    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F>;
+
+    /// Get a convenience structure to get a struct field's GEP index through its corresponding Rust field.
+    ///
+    /// Only used internally in this module for implementing other components.
+    fn fields(&self) -> Self::Fields<GepFieldTraversal> {
+        self.iter_fields(&mut GepFieldTraversal { gep_index_counter: 0 })
+    }
+
+    /// Get the LLVM [`StructType`] of this [`StructKind`].
+    fn get_struct_type<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &'ctx Context,
+    ) -> StructType<'ctx> {
+        let mut traversal = TypeFieldTraversal { generator, ctx, field_types: Vec::new() };
+        self.iter_fields(&mut traversal);
+
+        ctx.struct_type(&traversal.field_types, false)
+    }
+}
+
+/// A model for LLVM struct.
+///
+/// `S` should be of a [`StructKind`].
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Struct<S>(pub S);
+
+impl<'ctx, S: StructKind<'ctx>> Struct<S> {
+    /// Create a constant struct value from its fields.
+    ///
+    /// This function also validates `fields` and panic when there is something wrong.
+    pub fn const_struct<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        fields: &[BasicValueEnum<'ctx>],
+    ) -> Instance<'ctx, Self> {
+        // NOTE: There *could* have been a functor `F<M> = Instance<'ctx, M>` for `S::Fields<F>`
+        // to create a more user-friendly interface, but Rust's type system is not sophisticated enough
+        // and if you try doing that Rust would force you put lifetimes everywhere.
+        let val = ctx.const_struct(fields, false);
+        self.check_value(generator, ctx, val).unwrap()
+    }
+}
+
+impl<'ctx, S: StructKind<'ctx>> Model<'ctx> for Struct<S> {
+    type Value = StructValue<'ctx>;
+    type Type = StructType<'ctx>;
+
+    fn llvm_type<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &'ctx Context,
+    ) -> Self::Type {
+        self.0.get_struct_type(generator, ctx)
+    }
+
+    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError> {
+        let ty = ty.as_basic_type_enum();
+        let Ok(ty) = StructType::try_from(ty) else {
+            return Err(ModelError(format!("Expecting StructType, but got {ty:?}")));
+        };
+
+        // Check each field individually.
+        let mut traversal = CheckTypeFieldTraversal {
+            generator,
+            ctx,
+            gep_index_counter: 0,
+            errors: Vec::new(),
+            scrutinee: ty,
+        };
+        self.0.iter_fields(&mut traversal);
+
+        // Check the number of fields.
+        let exp_num_fields = traversal.gep_index_counter;
+        let got_num_fields = u32::try_from(ty.get_field_types().len()).unwrap();
+        if exp_num_fields != got_num_fields {
+            return Err(ModelError(format!(
+                "Expecting StructType with {exp_num_fields} field(s), but got {got_num_fields}"
+            )));
+        }
+
+        if !traversal.errors.is_empty() {
+            // Currently, only the first error is reported.
+            return Err(traversal.errors[0].clone());
+        }
+
+        Ok(())
+    }
+}
+
+impl<'ctx, S: StructKind<'ctx>> Instance<'ctx, Struct<S>> {
+    /// Get a field with [`StructValue::get_field_at_index`].
+    pub fn get_field<G: CodeGenerator + ?Sized, M, GetField>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        get_field: GetField,
+    ) -> Instance<'ctx, M>
+    where
+        M: Model<'ctx>,
+        GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
+    {
+        let field = get_field(self.model.0.fields());
+        let val = self.value.get_field_at_index(field.gep_index).unwrap();
+        field.model.check_value(generator, ctx, val).unwrap()
+    }
+}
+
+impl<'ctx, S: StructKind<'ctx>> Instance<'ctx, Ptr<Struct<S>>> {
+    /// Get a pointer to a field with [`Builder::build_in_bounds_gep`].
+    pub fn gep<M, GetField>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        get_field: GetField,
+    ) -> Instance<'ctx, Ptr<M>>
+    where
+        M: Model<'ctx>,
+        GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
+    {
+        let field = get_field(self.model.0 .0.fields());
+        let llvm_i32 = ctx.ctx.i32_type();
+
+        let ptr = unsafe {
+            ctx.builder
+                .build_in_bounds_gep(
+                    self.value,
+                    &[llvm_i32.const_zero(), llvm_i32.const_int(u64::from(field.gep_index), false)],
+                    field.name,
+                )
+                .unwrap()
+        };
+
+        unsafe { Ptr(field.model).believe_value(ptr) }
+    }
+
+    /// Convenience function equivalent to `.gep(...).load(...)`.
+    pub fn get<M, GetField, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        get_field: GetField,
+    ) -> Instance<'ctx, M>
+    where
+        M: Model<'ctx>,
+        GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
+    {
+        self.gep(ctx, get_field).load(generator, ctx)
+    }
+
+    /// Convenience function equivalent to `.gep(...).store(...)`.
+    pub fn set<M, GetField>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        get_field: GetField,
+        value: Instance<'ctx, M>,
+    ) where
+        M: Model<'ctx>,
+        GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
+    {
+        self.gep(ctx, get_field).store(ctx, value);
+    }
+}

nac3core/src/codegen/model/util.rs

@@ -0,0 +1,41 @@
+use super::*;
+use crate::codegen::{
+    stmt::{gen_for_callback_incrementing, BreakContinueHooks},
+    CodeGenContext, CodeGenerator,
+};
+
+/// Like [`gen_for_callback_incrementing`] with [`Model`] abstractions.
+///
+/// The value for `stop` is exclusive.
+pub fn gen_for_model<'ctx, 'a, G, F, N>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, 'a>,
+    start: Instance<'ctx, Int<N>>,
+    stop: Instance<'ctx, Int<N>>,
+    step: Instance<'ctx, Int<N>>,
+    body: F,
+) -> Result<(), String>
+where
+    G: CodeGenerator + ?Sized,
+    F: FnOnce(
+        &mut G,
+        &mut CodeGenContext<'ctx, 'a>,
+        BreakContinueHooks<'ctx>,
+        Instance<'ctx, Int<N>>,
+    ) -> Result<(), String>,
+    N: IntKind<'ctx> + Default,
+{
+    let int_model = Int(N::default());
+    gen_for_callback_incrementing(
+        generator,
+        ctx,
+        None,
+        start.value,
+        (stop.value, false),
+        |g, ctx, hooks, i| {
+            let i = unsafe { int_model.believe_value(i) };
+            body(g, ctx, hooks, i)
+        },
+        step.value,
+    )
+}

nac3core/src/codegen/numpy.rs

@@ -7,18 +7,17 @@ use nac3parser::ast::StrRef;
 
 use super::{
     macros::codegen_unreachable,
+    model::*,
+    object::{
+        any::AnyObject,
+        ndarray::{nditer::NDIterHandle, shape_util::parse_numpy_int_sequence, NDArrayObject},
+    },
     stmt::gen_for_callback,
-    types::ndarray::{NDArrayType, NDIterType},
-    values::{ndarray::shape::parse_numpy_int_sequence, ProxyValue},
     CodeGenContext, CodeGenerator,
 };
 use crate::{
     symbol_resolver::ValueEnum,
-    toplevel::{
+    toplevel::{helper::extract_ndims, numpy::unpack_ndarray_var_tys, DefinitionId},
-        helper::{arraylike_flatten_element_type, extract_ndims},
-        numpy::unpack_ndarray_var_tys,
-        DefinitionId,
-    },
     typecheck::typedef::{FunSignature, Type},
 };
 
@@ -37,14 +36,12 @@ pub fn gen_ndarray_empty<'ctx>(
     let shape_arg = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
 
     let (dtype, ndims) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
-    let llvm_dtype = context.get_llvm_type(generator, dtype);
     let ndims = extract_ndims(&context.unifier, ndims);
 
-    let shape = parse_numpy_int_sequence(generator, context, (shape_ty, shape_arg));
+    let shape = AnyObject { value: shape_arg, ty: shape_ty };
-
+    let (_, shape) = parse_numpy_int_sequence(generator, context, shape);
-    let ndarray = NDArrayType::new(generator, context.ctx, llvm_dtype, ndims)
+    let ndarray = NDArrayObject::make_np_empty(generator, context, dtype, ndims, shape);
-        .construct_numpy_empty(generator, context, &shape, None);
+    Ok(ndarray.instance.value)
-    Ok(ndarray.as_base_value())
 }
 
 /// Generates LLVM IR for `ndarray.zeros`.
@@ -62,14 +59,12 @@ pub fn gen_ndarray_zeros<'ctx>(
     let shape_arg = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
 
     let (dtype, ndims) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
-    let llvm_dtype = context.get_llvm_type(generator, dtype);
     let ndims = extract_ndims(&context.unifier, ndims);
 
-    let shape = parse_numpy_int_sequence(generator, context, (shape_ty, shape_arg));
+    let shape = AnyObject { value: shape_arg, ty: shape_ty };
-
+    let (_, shape) = parse_numpy_int_sequence(generator, context, shape);
-    let ndarray = NDArrayType::new(generator, context.ctx, llvm_dtype, ndims)
+    let ndarray = NDArrayObject::make_np_zeros(generator, context, dtype, ndims, shape);
-        .construct_numpy_zeros(generator, context, dtype, &shape, None);
+    Ok(ndarray.instance.value)
-    Ok(ndarray.as_base_value())
 }
 
 /// Generates LLVM IR for `ndarray.ones`.
@@ -87,14 +82,12 @@ pub fn gen_ndarray_ones<'ctx>(
     let shape_arg = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
 
     let (dtype, ndims) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
-    let llvm_dtype = context.get_llvm_type(generator, dtype);
     let ndims = extract_ndims(&context.unifier, ndims);
 
-    let shape = parse_numpy_int_sequence(generator, context, (shape_ty, shape_arg));
+    let shape = AnyObject { value: shape_arg, ty: shape_ty };
-
+    let (_, shape) = parse_numpy_int_sequence(generator, context, shape);
-    let ndarray = NDArrayType::new(generator, context.ctx, llvm_dtype, ndims)
+    let ndarray = NDArrayObject::make_np_ones(generator, context, dtype, ndims, shape);
-        .construct_numpy_ones(generator, context, dtype, &shape, None);
+    Ok(ndarray.instance.value)
-    Ok(ndarray.as_base_value())
 }
 
 /// Generates LLVM IR for `ndarray.full`.
@@ -115,19 +108,13 @@ pub fn gen_ndarray_full<'ctx>(
         args[1].1.clone().to_basic_value_enum(context, generator, fill_value_ty)?;
 
     let (dtype, ndims) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
-    let llvm_dtype = context.get_llvm_type(generator, dtype);
     let ndims = extract_ndims(&context.unifier, ndims);
 
-    let shape = parse_numpy_int_sequence(generator, context, (shape_ty, shape_arg));
+    let shape = AnyObject { value: shape_arg, ty: shape_ty };
-
+    let (_, shape) = parse_numpy_int_sequence(generator, context, shape);
-    let ndarray = NDArrayType::new(generator, context.ctx, llvm_dtype, ndims).construct_numpy_full(
+    let ndarray =
-        generator,
+        NDArrayObject::make_np_full(generator, context, dtype, ndims, shape, fill_value_arg);
-        context,
+    Ok(ndarray.instance.value)
-        &shape,
-        fill_value_arg,
-        None,
-    );
-    Ok(ndarray.as_base_value())
 }
 
 pub fn gen_ndarray_array<'ctx>(
@@ -161,12 +148,13 @@ pub fn gen_ndarray_array<'ctx>(
     let (_, ndims) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
     let ndims = extract_ndims(&context.unifier, ndims);
 
-    let copy = generator.bool_to_i1(context, copy_arg.into_int_value());
+    let object = AnyObject { value: obj_arg, ty: obj_ty };
-    let ndarray = NDArrayType::from_unifier_type(generator, context, fun.0.ret)
+    // NAC3 booleans are i8.
-        .construct_numpy_array(generator, context, (obj_ty, obj_arg), copy, None)
+    let copy = Int(Bool).truncate(generator, context, copy_arg.into_int_value());
+    let ndarray = NDArrayObject::make_np_array(generator, context, object, copy)
         .atleast_nd(generator, context, ndims);
 
-    Ok(ndarray.as_base_value())
+    Ok(ndarray.instance.value)
 }
 
 /// Generates LLVM IR for `ndarray.eye`.
@@ -207,25 +195,21 @@ pub fn gen_ndarray_eye<'ctx>(
 
     let (dtype, _) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
 
-    let llvm_usize = generator.get_size_type(context.ctx);
+    let nrows = Int(Int32)
-    let llvm_dtype = context.get_llvm_type(generator, dtype);
+        .check_value(generator, context.ctx, nrows_arg)
+        .unwrap()
+        .s_extend_or_bit_cast(generator, context, SizeT);
+    let ncols = Int(Int32)
+        .check_value(generator, context.ctx, ncols_arg)
+        .unwrap()
+        .s_extend_or_bit_cast(generator, context, SizeT);
+    let offset = Int(Int32)
+        .check_value(generator, context.ctx, offset_arg)
+        .unwrap()
+        .s_extend_or_bit_cast(generator, context, SizeT);
 
-    let nrows = context
+    let ndarray = NDArrayObject::make_np_eye(generator, context, dtype, nrows, ncols, offset);
-        .builder
+    Ok(ndarray.instance.value)
-        .build_int_s_extend_or_bit_cast(nrows_arg.into_int_value(), llvm_usize, "")
-        .unwrap();
-    let ncols = context
-        .builder
-        .build_int_s_extend_or_bit_cast(ncols_arg.into_int_value(), llvm_usize, "")
-        .unwrap();
-    let offset = context
-        .builder
-        .build_int_s_extend_or_bit_cast(offset_arg.into_int_value(), llvm_usize, "")
-        .unwrap();
-
-    let ndarray = NDArrayType::new(generator, context.ctx, llvm_dtype, 2)
-        .construct_numpy_eye(generator, context, dtype, nrows, ncols, offset, None);
-    Ok(ndarray.as_base_value())
 }
 
 /// Generates LLVM IR for `ndarray.identity`.
@@ -239,21 +223,15 @@ pub fn gen_ndarray_identity<'ctx>(
     assert!(obj.is_none());
     assert_eq!(args.len(), 1);
 
+    let (dtype, _) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
+
     let n_ty = fun.0.args[0].ty;
     let n_arg = args[0].1.clone().to_basic_value_enum(context, generator, n_ty)?;
 
-    let (dtype, _) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
+    let n = Int(Int32).check_value(generator, context.ctx, n_arg).unwrap();
-
+    let n = n.s_extend_or_bit_cast(generator, context, SizeT);
-    let llvm_usize = generator.get_size_type(context.ctx);
+    let ndarray = NDArrayObject::make_np_identity(generator, context, dtype, n);
-    let llvm_dtype = context.get_llvm_type(generator, dtype);
+    Ok(ndarray.instance.value)
-
-    let n = context
-        .builder
-        .build_int_s_extend_or_bit_cast(n_arg.into_int_value(), llvm_usize, "")
-        .unwrap();
-    let ndarray = NDArrayType::new(generator, context.ctx, llvm_dtype, 2)
-        .construct_numpy_identity(generator, context, dtype, n, None);
-    Ok(ndarray.as_base_value())
 }
 
 /// Generates LLVM IR for `ndarray.copy`.
@@ -271,10 +249,10 @@ pub fn gen_ndarray_copy<'ctx>(
     let this_arg =
         obj.as_ref().unwrap().1.clone().to_basic_value_enum(context, generator, this_ty)?;
 
-    let this = NDArrayType::from_unifier_type(generator, context, this_ty)
+    let this = AnyObject { value: this_arg, ty: this_ty };
-        .map_value(this_arg.into_pointer_value(), None);
+    let this = NDArrayObject::from_object(generator, context, this);
     let ndarray = this.make_copy(generator, context);
-    Ok(ndarray.as_base_value())
+    Ok(ndarray.instance.value)
 }
 
 /// Generates LLVM IR for `ndarray.fill`.
@@ -294,8 +272,8 @@ pub fn gen_ndarray_fill<'ctx>(
     let value_ty = fun.0.args[0].ty;
     let value_arg = args[0].1.clone().to_basic_value_enum(context, generator, value_ty)?;
 
-    let this = NDArrayType::from_unifier_type(generator, context, this_ty)
+    let this = AnyObject { value: this_arg, ty: this_ty };
-        .map_value(this_arg.into_pointer_value(), None);
+    let this = NDArrayObject::from_object(generator, context, this);
     this.fill(generator, context, value_arg);
     Ok(())
 }
@@ -309,32 +287,36 @@ pub fn gen_ndarray_fill<'ctx>(
 pub fn ndarray_dot<'ctx, G: CodeGenerator + ?Sized>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
-    (x1_ty, x1): (Type, BasicValueEnum<'ctx>),
+    x1: (Type, BasicValueEnum<'ctx>),
-    (x2_ty, x2): (Type, BasicValueEnum<'ctx>),
+    x2: (Type, BasicValueEnum<'ctx>),
 ) -> Result<BasicValueEnum<'ctx>, String> {
     const FN_NAME: &str = "ndarray_dot";
+    let (x1_ty, x1) = x1;
+    let (x2_ty, x2) = x2;
 
     match (x1, x2) {
-        (BasicValueEnum::PointerValue(n1), BasicValueEnum::PointerValue(n2)) => {
+        (BasicValueEnum::PointerValue(_), BasicValueEnum::PointerValue(_)) => {
-            let a = NDArrayType::from_unifier_type(generator, ctx, x1_ty).map_value(n1, None);
+            let a = AnyObject { ty: x1_ty, value: x1 };
-            let b = NDArrayType::from_unifier_type(generator, ctx, x2_ty).map_value(n2, None);
+            let b = AnyObject { ty: x2_ty, value: x2 };
+
+            let a = NDArrayObject::from_object(generator, ctx, a);
+            let b = NDArrayObject::from_object(generator, ctx, b);
 
             // TODO: General `np.dot()` https://numpy.org/doc/stable/reference/generated/numpy.dot.html.
-            assert_eq!(a.get_type().ndims(), 1);
+            assert_eq!(a.ndims, 1);
-            assert_eq!(b.get_type().ndims(), 1);
+            assert_eq!(b.ndims, 1);
-            let common_dtype = arraylike_flatten_element_type(&mut ctx.unifier, x1_ty);
+            let common_dtype = a.dtype;
 
             // Check shapes.
             let a_size = a.size(generator, ctx);
             let b_size = b.size(generator, ctx);
-            let same_shape =
+            let same_shape = a_size.compare(ctx, IntPredicate::EQ, b_size);
-                ctx.builder.build_int_compare(IntPredicate::EQ, a_size, b_size, "").unwrap();
             ctx.make_assert(
                 generator,
-                same_shape,
+                same_shape.value,
                 "0:ValueError",
                 "shapes ({0},) and ({1},) not aligned: {0} (dim 0) != {1} (dim 1)",
-                [Some(a_size), Some(b_size), None],
+                [Some(a_size.value), Some(b_size.value), None],
                 ctx.current_loc,
             );
 
@@ -349,17 +331,17 @@ pub fn ndarray_dot<'ctx, G: CodeGenerator + ?Sized>(
                 ctx,
                 Some("np_dot"),
                 |generator, ctx| {
-                    let a_iter = NDIterType::new(generator, ctx.ctx).construct(generator, ctx, a);
+                    let a_iter = NDIterHandle::new(generator, ctx, a);
-                    let b_iter = NDIterType::new(generator, ctx.ctx).construct(generator, ctx, b);
+                    let b_iter = NDIterHandle::new(generator, ctx, b);
                     Ok((a_iter, b_iter))
                 },
                 |generator, ctx, (a_iter, _b_iter)| {
                     // Only a_iter drives the condition, b_iter should have the same status.
-                    Ok(a_iter.has_element(generator, ctx))
+                    Ok(a_iter.has_element(generator, ctx).value)
                 },
-                |_, ctx, _hooks, (a_iter, b_iter)| {
+                |generator, ctx, _hooks, (a_iter, b_iter)| {
-                    let a_scalar = a_iter.get_scalar(ctx);
+                    let a_scalar = a_iter.get_scalar(generator, ctx).value;
-                    let b_scalar = b_iter.get_scalar(ctx);
+                    let b_scalar = b_iter.get_scalar(generator, ctx).value;
 
                     let old_result = ctx.builder.build_load(result, "").unwrap();
                     let new_result: BasicValueEnum<'ctx> = match old_result {
@@ -369,14 +351,12 @@ pub fn ndarray_dot<'ctx, G: CodeGenerator + ?Sized>(
                             let x = ctx.builder.build_int_mul(a_scalar, b_scalar, "").unwrap();
                             ctx.builder.build_int_add(old_result, x, "").unwrap().into()
                         }
-
                         BasicValueEnum::FloatValue(old_result) => {
                             let a_scalar = a_scalar.into_float_value();
                             let b_scalar = b_scalar.into_float_value();
                             let x = ctx.builder.build_float_mul(a_scalar, b_scalar, "").unwrap();
                             ctx.builder.build_float_add(old_result, x, "").unwrap().into()
                         }
-
                         _ => {
                             panic!("Unrecognized dtype: {}", ctx.unifier.stringify(common_dtype));
                         }
@@ -395,15 +375,12 @@ pub fn ndarray_dot<'ctx, G: CodeGenerator + ?Sized>(
 
             Ok(ctx.builder.build_load(result, "").unwrap())
         }
-
         (BasicValueEnum::IntValue(e1), BasicValueEnum::IntValue(e2)) => {
             Ok(ctx.builder.build_int_mul(e1, e2, "").unwrap().as_basic_value_enum())
         }
-
         (BasicValueEnum::FloatValue(e1), BasicValueEnum::FloatValue(e2)) => {
             Ok(ctx.builder.build_float_mul(e1, e2, "").unwrap().as_basic_value_enum())
         }
-
         _ => codegen_unreachable!(
             ctx,
             "{FN_NAME}() not supported for '{}'",

nac3core/src/codegen/object/any.rs

@@ -0,0 +1,12 @@
+use inkwell::values::BasicValueEnum;
+
+use crate::typecheck::typedef::Type;
+
+/// A NAC3 LLVM Python object of any type.
+#[derive(Debug, Clone, Copy)]
+pub struct AnyObject<'ctx> {
+    /// Typechecker type of the object.
+    pub ty: Type,
+    /// LLVM value of the object.
+    pub value: BasicValueEnum<'ctx>,
+}

nac3core/src/codegen/object/list.rs

@@ -0,0 +1,86 @@
+use super::any::AnyObject;
+use crate::{
+    codegen::{model::*, CodeGenContext, CodeGenerator},
+    typecheck::typedef::{iter_type_vars, Type, TypeEnum},
+};
+
+/// Fields of [`List`]
+pub struct ListFields<'ctx, F: FieldTraversal<'ctx>, Item: Model<'ctx>> {
+    /// Array pointer to content
+    pub items: F::Output<Ptr<Item>>,
+    /// Number of items in the array
+    pub len: F::Output<Int<SizeT>>,
+}
+
+/// A list in NAC3.
+#[derive(Debug, Clone, Copy, Default)]
+pub struct List<Item> {
+    /// Model of the list items
+    pub item: Item,
+}
+
+impl<'ctx, Item: Model<'ctx>> StructKind<'ctx> for List<Item> {
+    type Fields<F: FieldTraversal<'ctx>> = ListFields<'ctx, F, Item>;
+
+    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            items: traversal.add("items", Ptr(self.item)),
+            len: traversal.add_auto("len"),
+        }
+    }
+}
+
+impl<'ctx, Item: Model<'ctx>> Instance<'ctx, Ptr<Struct<List<Item>>>> {
+    /// Cast the items pointer to `uint8_t*`.
+    pub fn with_pi8_items<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Ptr<Struct<List<Int<Byte>>>>> {
+        self.pointer_cast(generator, ctx, Struct(List { item: Int(Byte) }))
+    }
+}
+
+/// A NAC3 Python List object.
+#[derive(Debug, Clone, Copy)]
+pub struct ListObject<'ctx> {
+    /// Typechecker type of the list items
+    pub item_type: Type,
+    pub instance: Instance<'ctx, Ptr<Struct<List<Any<'ctx>>>>>,
+}
+
+impl<'ctx> ListObject<'ctx> {
+    /// Create a [`ListObject`] from an LLVM value and its typechecker [`Type`].
+    pub fn from_object<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        object: AnyObject<'ctx>,
+    ) -> Self {
+        // Check typechecker type and extract `item_type`
+        let item_type = match &*ctx.unifier.get_ty(object.ty) {
+            TypeEnum::TObj { obj_id, params, .. }
+                if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
+            {
+                iter_type_vars(params).next().unwrap().ty // Extract `item_type`
+            }
+            _ => {
+                panic!("Expecting type to be a list, but got {}", ctx.unifier.stringify(object.ty))
+            }
+        };
+
+        let plist = Ptr(Struct(List { item: Any(ctx.get_llvm_type(generator, item_type)) }));
+
+        // Create object
+        let value = plist.check_value(generator, ctx.ctx, object.value).unwrap();
+        ListObject { item_type, instance: value }
+    }
+
+    /// Get the `len()` of this list.
+    pub fn len<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<SizeT>> {
+        self.instance.get(generator, ctx, |f| f.len)
+    }
+}

nac3core/src/codegen/object/mod.rs

@@ -0,0 +1,5 @@
+pub mod any;
+pub mod list;
+pub mod ndarray;
+pub mod tuple;
+pub mod utils;

nac3core/src/codegen/object/ndarray/array.rs

@@ -0,0 +1,184 @@
+use super::NDArrayObject;
+use crate::{
+    codegen::{
+        irrt::{
+            call_nac3_ndarray_array_set_and_validate_list_shape,
+            call_nac3_ndarray_array_write_list_to_array,
+        },
+        model::*,
+        object::{any::AnyObject, list::ListObject},
+        stmt::gen_if_else_expr_callback,
+        CodeGenContext, CodeGenerator,
+    },
+    toplevel::helper::{arraylike_flatten_element_type, arraylike_get_ndims},
+    typecheck::typedef::{Type, TypeEnum},
+};
+
+/// Get the expected `dtype` and `ndims` of the ndarray returned by `np_array(list)`.
+fn get_list_object_dtype_and_ndims<'ctx>(
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    list: ListObject<'ctx>,
+) -> (Type, u64) {
+    let dtype = arraylike_flatten_element_type(&mut ctx.unifier, list.item_type);
+
+    let ndims = arraylike_get_ndims(&mut ctx.unifier, list.item_type);
+    let ndims = ndims + 1; // To count `list` itself.
+
+    (dtype, ndims)
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Implementation of `np_array(<list>, copy=True)`
+    fn make_np_array_list_copy_true_impl<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        list: ListObject<'ctx>,
+    ) -> Self {
+        let (dtype, ndims_int) = get_list_object_dtype_and_ndims(ctx, list);
+        let list_value = list.instance.with_pi8_items(generator, ctx);
+
+        // Validate `list` has a consistent shape.
+        // Raise an exception if `list` is something abnormal like `[[1, 2], [3]]`.
+        // If `list` has a consistent shape, deduce the shape and write it to `shape`.
+        let ndims = Int(SizeT).const_int(generator, ctx.ctx, ndims_int, false);
+        let shape = Int(SizeT).array_alloca(generator, ctx, ndims.value);
+        call_nac3_ndarray_array_set_and_validate_list_shape(
+            generator, ctx, list_value, ndims, shape,
+        );
+
+        let ndarray = NDArrayObject::alloca(generator, ctx, dtype, ndims_int);
+        ndarray.copy_shape_from_array(generator, ctx, shape);
+        ndarray.create_data(generator, ctx);
+
+        // Copy all contents from the list.
+        call_nac3_ndarray_array_write_list_to_array(generator, ctx, list_value, ndarray.instance);
+
+        ndarray
+    }
+
+    /// Implementation of `np_array(<list>, copy=None)`
+    fn make_np_array_list_copy_none_impl<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        list: ListObject<'ctx>,
+    ) -> Self {
+        // np_array without copying is only possible `list` is not nested.
+        //
+        // If `list` is `list[T]`, we can create an ndarray with `data` set
+        // to the array pointer of `list`.
+        //
+        // If `list` is `list[list[T]]` or worse, copy.
+
+        let (dtype, ndims) = get_list_object_dtype_and_ndims(ctx, list);
+        if ndims == 1 {
+            // `list` is not nested
+            let ndarray = NDArrayObject::alloca(generator, ctx, dtype, 1);
+
+            // Set data
+            let data = list.instance.get(generator, ctx, |f| f.items).cast_to_pi8(generator, ctx);
+            ndarray.instance.set(ctx, |f| f.data, data);
+
+            // ndarray->shape[0] = list->len;
+            let shape = ndarray.instance.get(generator, ctx, |f| f.shape);
+            let list_len = list.instance.get(generator, ctx, |f| f.len);
+            shape.set_index_const(ctx, 0, list_len);
+
+            // Set strides, the `data` is contiguous
+            ndarray.set_strides_contiguous(generator, ctx);
+
+            ndarray
+        } else {
+            // `list` is nested, copy
+            NDArrayObject::make_np_array_list_copy_true_impl(generator, ctx, list)
+        }
+    }
+
+    /// Implementation of `np_array(<list>, copy=copy)`
+    fn make_np_array_list_impl<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        list: ListObject<'ctx>,
+        copy: Instance<'ctx, Int<Bool>>,
+    ) -> Self {
+        let (dtype, ndims) = get_list_object_dtype_and_ndims(ctx, list);
+
+        let ndarray = gen_if_else_expr_callback(
+            generator,
+            ctx,
+            |_generator, _ctx| Ok(copy.value),
+            |generator, ctx| {
+                let ndarray =
+                    NDArrayObject::make_np_array_list_copy_true_impl(generator, ctx, list);
+                Ok(Some(ndarray.instance.value))
+            },
+            |generator, ctx| {
+                let ndarray =
+                    NDArrayObject::make_np_array_list_copy_none_impl(generator, ctx, list);
+                Ok(Some(ndarray.instance.value))
+            },
+        )
+        .unwrap()
+        .unwrap();
+
+        NDArrayObject::from_value_and_unpacked_types(generator, ctx, ndarray, dtype, ndims)
+    }
+
+    /// Implementation of `np_array(<ndarray>, copy=copy)`.
+    pub fn make_np_array_ndarray_impl<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndarray: NDArrayObject<'ctx>,
+        copy: Instance<'ctx, Int<Bool>>,
+    ) -> Self {
+        let ndarray_val = gen_if_else_expr_callback(
+            generator,
+            ctx,
+            |_generator, _ctx| Ok(copy.value),
+            |generator, ctx| {
+                let ndarray = ndarray.make_copy(generator, ctx); // Force copy
+                Ok(Some(ndarray.instance.value))
+            },
+            |_generator, _ctx| {
+                // No need to copy. Return `ndarray` itself.
+                Ok(Some(ndarray.instance.value))
+            },
+        )
+        .unwrap()
+        .unwrap();
+
+        NDArrayObject::from_value_and_unpacked_types(
+            generator,
+            ctx,
+            ndarray_val,
+            ndarray.dtype,
+            ndarray.ndims,
+        )
+    }
+
+    /// Create a new ndarray like `np.array()`.
+    ///
+    /// NOTE: The `ndmin` argument is not here. You may want to
+    /// do [`NDArrayObject::atleast_nd`] to achieve that.
+    pub fn make_np_array<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        object: AnyObject<'ctx>,
+        copy: Instance<'ctx, Int<Bool>>,
+    ) -> Self {
+        match &*ctx.unifier.get_ty(object.ty) {
+            TypeEnum::TObj { obj_id, .. }
+                if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
+            {
+                let list = ListObject::from_object(generator, ctx, object);
+                NDArrayObject::make_np_array_list_impl(generator, ctx, list, copy)
+            }
+            TypeEnum::TObj { obj_id, .. }
+                if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
+            {
+                let ndarray = NDArrayObject::from_object(generator, ctx, object);
+                NDArrayObject::make_np_array_ndarray_impl(generator, ctx, ndarray, copy)
+            }
+            _ => panic!("Unrecognized object type: {}", ctx.unifier.stringify(object.ty)), // Typechecker ensures this
+        }
+    }
+}

nac3core/src/codegen/object/ndarray/broadcast.rs

@@ -0,0 +1,138 @@
+use itertools::Itertools;
+
+use super::NDArrayObject;
+use crate::codegen::{
+    irrt::{call_nac3_ndarray_broadcast_shapes, call_nac3_ndarray_broadcast_to},
+    model::*,
+    CodeGenContext, CodeGenerator,
+};
+
+/// Fields of [`ShapeEntry`]
+pub struct ShapeEntryFields<'ctx, F: FieldTraversal<'ctx>> {
+    pub ndims: F::Output<Int<SizeT>>,
+    pub shape: F::Output<Ptr<Int<SizeT>>>,
+}
+
+/// An IRRT structure used in broadcasting.
+#[derive(Debug, Clone, Copy, Default)]
+pub struct ShapeEntry;
+
+impl<'ctx> StructKind<'ctx> for ShapeEntry {
+    type Fields<F: FieldTraversal<'ctx>> = ShapeEntryFields<'ctx, F>;
+
+    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+        Self::Fields { ndims: traversal.add_auto("ndims"), shape: traversal.add_auto("shape") }
+    }
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Create a broadcast view on this ndarray with a target shape.
+    ///
+    /// The input shape will be checked to make sure that it contains no negative values.
+    ///
+    /// * `target_ndims` - The ndims type after broadcasting to the given shape.
+    ///   The caller has to figure this out for this function.
+    /// * `target_shape` - An array pointer pointing to the target shape.
+    #[must_use]
+    pub fn broadcast_to<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        target_ndims: u64,
+        target_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) -> Self {
+        let broadcast_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, target_ndims);
+        broadcast_ndarray.copy_shape_from_array(generator, ctx, target_shape);
+
+        call_nac3_ndarray_broadcast_to(generator, ctx, self.instance, broadcast_ndarray.instance);
+        broadcast_ndarray
+    }
+}
+/// A result produced by [`broadcast_all_ndarrays`]
+#[derive(Debug, Clone)]
+pub struct BroadcastAllResult<'ctx> {
+    /// The statically known `ndims` of the broadcast result.
+    pub ndims: u64,
+    /// The broadcasting shape.
+    pub shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    /// Broadcasted views on the inputs.
+    ///
+    /// All of them will have `shape` [`BroadcastAllResult::shape`] and
+    /// `ndims` [`BroadcastAllResult::ndims`]. The length of the vector
+    /// is the same as the input.
+    pub ndarrays: Vec<NDArrayObject<'ctx>>,
+}
+
+/// Helper function to call `call_nac3_ndarray_broadcast_shapes`
+fn broadcast_shapes<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    in_shape_entries: &[(Instance<'ctx, Ptr<Int<SizeT>>>, u64)], // (shape, shape's length/ndims)
+    broadcast_ndims: u64,
+    broadcast_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    // Prepare input shape entries to be passed to `call_nac3_ndarray_broadcast_shapes`.
+    let num_shape_entries = Int(SizeT).const_int(
+        generator,
+        ctx.ctx,
+        u64::try_from(in_shape_entries.len()).unwrap(),
+        false,
+    );
+    let shape_entries = Struct(ShapeEntry).array_alloca(generator, ctx, num_shape_entries.value);
+    for (i, (in_shape, in_ndims)) in in_shape_entries.iter().enumerate() {
+        let pshape_entry = shape_entries.offset_const(ctx, i64::try_from(i).unwrap());
+
+        let in_ndims = Int(SizeT).const_int(generator, ctx.ctx, *in_ndims, false);
+        pshape_entry.set(ctx, |f| f.ndims, in_ndims);
+
+        pshape_entry.set(ctx, |f| f.shape, *in_shape);
+    }
+
+    let broadcast_ndims = Int(SizeT).const_int(generator, ctx.ctx, broadcast_ndims, false);
+    call_nac3_ndarray_broadcast_shapes(
+        generator,
+        ctx,
+        num_shape_entries,
+        shape_entries,
+        broadcast_ndims,
+        broadcast_shape,
+    );
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Broadcast all ndarrays according to `np.broadcast()` and return a [`BroadcastAllResult`]
+    /// containing all the information of the result of the broadcast operation.
+    pub fn broadcast<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndarrays: &[Self],
+    ) -> BroadcastAllResult<'ctx> {
+        assert!(!ndarrays.is_empty());
+
+        // Infer the broadcast output ndims.
+        let broadcast_ndims_int = ndarrays.iter().map(|ndarray| ndarray.ndims).max().unwrap();
+
+        let broadcast_ndims = Int(SizeT).const_int(generator, ctx.ctx, broadcast_ndims_int, false);
+        let broadcast_shape = Int(SizeT).array_alloca(generator, ctx, broadcast_ndims.value);
+
+        let shape_entries = ndarrays
+            .iter()
+            .map(|ndarray| (ndarray.instance.get(generator, ctx, |f| f.shape), ndarray.ndims))
+            .collect_vec();
+        broadcast_shapes(generator, ctx, &shape_entries, broadcast_ndims_int, broadcast_shape);
+
+        // Broadcast all the inputs to shape `dst_shape`.
+        let broadcast_ndarrays: Vec<_> = ndarrays
+            .iter()
+            .map(|ndarray| {
+                ndarray.broadcast_to(generator, ctx, broadcast_ndims_int, broadcast_shape)
+            })
+            .collect_vec();
+
+        BroadcastAllResult {
+            ndims: broadcast_ndims_int,
+            shape: broadcast_shape,
+            ndarrays: broadcast_ndarrays,
+        }
+    }
+}

nac3core/src/codegen/object/ndarray/contiguous.rs

@@ -0,0 +1,133 @@
+use super::NDArrayObject;
+use crate::{
+    codegen::{model::*, CodeGenContext, CodeGenerator},
+    typecheck::typedef::Type,
+};
+
+/// Fields of [`ContiguousNDArray`]
+pub struct ContiguousNDArrayFields<'ctx, F: FieldTraversal<'ctx>, Item: Model<'ctx>> {
+    pub ndims: F::Output<Int<SizeT>>,
+    pub shape: F::Output<Ptr<Int<SizeT>>>,
+    pub data: F::Output<Ptr<Item>>,
+}
+
+/// An ndarray without strides and non-opaque `data` field in NAC3.
+#[derive(Debug, Clone, Copy)]
+pub struct ContiguousNDArray<M> {
+    /// [`Model`] of the items.
+    pub item: M,
+}
+
+impl<'ctx, Item: Model<'ctx>> StructKind<'ctx> for ContiguousNDArray<Item> {
+    type Fields<F: FieldTraversal<'ctx>> = ContiguousNDArrayFields<'ctx, F, Item>;
+
+    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            ndims: traversal.add_auto("ndims"),
+            shape: traversal.add_auto("shape"),
+            data: traversal.add("data", Ptr(self.item)),
+        }
+    }
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Create a [`ContiguousNDArray`] from the contents of this ndarray.
+    ///
+    /// This function may or may not be expensive depending on if this ndarray has contiguous data.
+    ///
+    /// If this ndarray is not C-contiguous, this function will allocate memory on the stack for the `data` field of
+    /// the returned [`ContiguousNDArray`] and copy contents of this ndarray to there.
+    ///
+    /// If this ndarray is C-contiguous, contents of this ndarray will not be copied. The created [`ContiguousNDArray`]
+    /// will share memory with this ndarray.
+    ///
+    /// The `item_model` sets the [`Model`] of the returned [`ContiguousNDArray`]'s `Item` model for type-safety, and
+    /// should match the `ctx.get_llvm_type()` of this ndarray's `dtype`. Otherwise this function panics. Use model [`Any`]
+    /// if you don't care/cannot know the [`Model`] in advance.
+    pub fn make_contiguous_ndarray<G: CodeGenerator + ?Sized, Item: Model<'ctx>>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        item_model: Item,
+    ) -> Instance<'ctx, Ptr<Struct<ContiguousNDArray<Item>>>> {
+        // Sanity check on `self.dtype` and `item_model`.
+        let dtype_llvm = ctx.get_llvm_type(generator, self.dtype);
+        item_model.check_type(generator, ctx.ctx, dtype_llvm).unwrap();
+
+        let cdarray_model = Struct(ContiguousNDArray { item: item_model });
+
+        let current_bb = ctx.builder.get_insert_block().unwrap();
+        let then_bb = ctx.ctx.insert_basic_block_after(current_bb, "then_bb");
+        let else_bb = ctx.ctx.insert_basic_block_after(then_bb, "else_bb");
+        let end_bb = ctx.ctx.insert_basic_block_after(else_bb, "end_bb");
+
+        // Allocate and setup the resulting [`ContiguousNDArray`].
+        let result = cdarray_model.alloca(generator, ctx);
+
+        // Set ndims and shape.
+        let ndims = self.ndims_llvm(generator, ctx.ctx);
+        result.set(ctx, |f| f.ndims, ndims);
+
+        let shape = self.instance.get(generator, ctx, |f| f.shape);
+        result.set(ctx, |f| f.shape, shape);
+
+        let is_contiguous = self.is_c_contiguous(generator, ctx);
+        ctx.builder.build_conditional_branch(is_contiguous.value, then_bb, else_bb).unwrap();
+
+        // Inserting into then_bb; This ndarray is contiguous.
+        ctx.builder.position_at_end(then_bb);
+        let data = self.instance.get(generator, ctx, |f| f.data);
+        let data = data.pointer_cast(generator, ctx, item_model);
+        result.set(ctx, |f| f.data, data);
+        ctx.builder.build_unconditional_branch(end_bb).unwrap();
+
+        // Inserting into else_bb; This ndarray is not contiguous. Do a full-copy on `data`.
+        // `make_copy` produces an ndarray with contiguous `data`.
+        ctx.builder.position_at_end(else_bb);
+        let copied_ndarray = self.make_copy(generator, ctx);
+        let data = copied_ndarray.instance.get(generator, ctx, |f| f.data);
+        let data = data.pointer_cast(generator, ctx, item_model);
+        result.set(ctx, |f| f.data, data);
+        ctx.builder.build_unconditional_branch(end_bb).unwrap();
+
+        // Reposition to end_bb for continuation
+        ctx.builder.position_at_end(end_bb);
+
+        result
+    }
+
+    /// Create an [`NDArrayObject`] from a [`ContiguousNDArray`].
+    ///
+    /// The operation is super cheap. The newly created [`NDArrayObject`] will share the
+    /// same memory as the [`ContiguousNDArray`].
+    ///
+    /// `ndims` has to be provided as [`NDArrayObject`] requires a statically known `ndims` value, despite
+    /// the fact that the information should be contained within the [`ContiguousNDArray`].
+    pub fn from_contiguous_ndarray<G: CodeGenerator + ?Sized, Item: Model<'ctx>>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        carray: Instance<'ctx, Ptr<Struct<ContiguousNDArray<Item>>>>,
+        dtype: Type,
+        ndims: u64,
+    ) -> Self {
+        // Sanity check on `dtype` and `contiguous_array`'s `Item` model.
+        let dtype_llvm = ctx.get_llvm_type(generator, dtype);
+        carray.model.0 .0.item.check_type(generator, ctx.ctx, dtype_llvm).unwrap();
+
+        // TODO: Debug assert `ndims == carray.ndims` to catch bugs.
+
+        // Allocate the resulting ndarray.
+        let ndarray = NDArrayObject::alloca(generator, ctx, dtype, ndims);
+
+        // Copy shape and update strides
+        let shape = carray.get(generator, ctx, |f| f.shape);
+        ndarray.copy_shape_from_array(generator, ctx, shape);
+        ndarray.set_strides_contiguous(generator, ctx);
+
+        // Share data
+        let data = carray.get(generator, ctx, |f| f.data).pointer_cast(generator, ctx, Int(Byte));
+        ndarray.instance.set(ctx, |f| f.data, data);
+
+        ndarray
+    }
+}

nac3core/src/codegen/object/ndarray/factory.rs

@@ -0,0 +1,175 @@
+use inkwell::{values::BasicValueEnum, IntPredicate};
+
+use super::NDArrayObject;
+use crate::{
+    codegen::{
+        irrt::call_nac3_ndarray_util_assert_shape_no_negative, model::*, CodeGenContext,
+        CodeGenerator,
+    },
+    typecheck::typedef::Type,
+};
+
+/// Get the zero value in `np.zeros()` of a `dtype`.
+fn ndarray_zero_value<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    dtype: Type,
+) -> BasicValueEnum<'ctx> {
+    if [ctx.primitives.int32, ctx.primitives.uint32]
+        .iter()
+        .any(|ty| ctx.unifier.unioned(dtype, *ty))
+    {
+        ctx.ctx.i32_type().const_zero().into()
+    } else if [ctx.primitives.int64, ctx.primitives.uint64]
+        .iter()
+        .any(|ty| ctx.unifier.unioned(dtype, *ty))
+    {
+        ctx.ctx.i64_type().const_zero().into()
+    } else if ctx.unifier.unioned(dtype, ctx.primitives.float) {
+        ctx.ctx.f64_type().const_zero().into()
+    } else if ctx.unifier.unioned(dtype, ctx.primitives.bool) {
+        ctx.ctx.bool_type().const_zero().into()
+    } else if ctx.unifier.unioned(dtype, ctx.primitives.str) {
+        ctx.gen_string(generator, "").into()
+    } else {
+        panic!("unrecognized dtype: {}", ctx.unifier.stringify(dtype));
+    }
+}
+
+/// Get the one value in `np.ones()` of a `dtype`.
+fn ndarray_one_value<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    dtype: Type,
+) -> BasicValueEnum<'ctx> {
+    if [ctx.primitives.int32, ctx.primitives.uint32]
+        .iter()
+        .any(|ty| ctx.unifier.unioned(dtype, *ty))
+    {
+        let is_signed = ctx.unifier.unioned(dtype, ctx.primitives.int32);
+        ctx.ctx.i32_type().const_int(1, is_signed).into()
+    } else if [ctx.primitives.int64, ctx.primitives.uint64]
+        .iter()
+        .any(|ty| ctx.unifier.unioned(dtype, *ty))
+    {
+        let is_signed = ctx.unifier.unioned(dtype, ctx.primitives.int64);
+        ctx.ctx.i64_type().const_int(1, is_signed).into()
+    } else if ctx.unifier.unioned(dtype, ctx.primitives.float) {
+        ctx.ctx.f64_type().const_float(1.0).into()
+    } else if ctx.unifier.unioned(dtype, ctx.primitives.bool) {
+        ctx.ctx.bool_type().const_int(1, false).into()
+    } else if ctx.unifier.unioned(dtype, ctx.primitives.str) {
+        ctx.gen_string(generator, "1").into()
+    } else {
+        panic!("unrecognized dtype: {}", ctx.unifier.stringify(dtype));
+    }
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Create an ndarray like `np.empty`.
+    pub fn make_np_empty<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        ndims: u64,
+        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) -> Self {
+        // Validate `shape`
+        let ndims_llvm = Int(SizeT).const_int(generator, ctx.ctx, ndims, false);
+        call_nac3_ndarray_util_assert_shape_no_negative(generator, ctx, ndims_llvm, shape);
+
+        let ndarray = NDArrayObject::alloca(generator, ctx, dtype, ndims);
+        ndarray.copy_shape_from_array(generator, ctx, shape);
+        ndarray.create_data(generator, ctx);
+
+        ndarray
+    }
+
+    /// Create an ndarray like `np.full`.
+    pub fn make_np_full<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        ndims: u64,
+        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+        fill_value: BasicValueEnum<'ctx>,
+    ) -> Self {
+        let ndarray = NDArrayObject::make_np_empty(generator, ctx, dtype, ndims, shape);
+        ndarray.fill(generator, ctx, fill_value);
+        ndarray
+    }
+
+    /// Create an ndarray like `np.zero`.
+    pub fn make_np_zeros<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        ndims: u64,
+        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) -> Self {
+        let fill_value = ndarray_zero_value(generator, ctx, dtype);
+        NDArrayObject::make_np_full(generator, ctx, dtype, ndims, shape, fill_value)
+    }
+
+    /// Create an ndarray like `np.ones`.
+    pub fn make_np_ones<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        ndims: u64,
+        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) -> Self {
+        let fill_value = ndarray_one_value(generator, ctx, dtype);
+        NDArrayObject::make_np_full(generator, ctx, dtype, ndims, shape, fill_value)
+    }
+
+    /// Create an ndarray like `np.eye`.
+    pub fn make_np_eye<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        nrows: Instance<'ctx, Int<SizeT>>,
+        ncols: Instance<'ctx, Int<SizeT>>,
+        offset: Instance<'ctx, Int<SizeT>>,
+    ) -> Self {
+        let ndzero = ndarray_zero_value(generator, ctx, dtype);
+        let ndone = ndarray_one_value(generator, ctx, dtype);
+
+        let ndarray = NDArrayObject::alloca_dynamic_shape(generator, ctx, dtype, &[nrows, ncols]);
+
+        // Create data and make the matrix like look np.eye()
+        ndarray.create_data(generator, ctx);
+        ndarray
+            .foreach(generator, ctx, |generator, ctx, _hooks, nditer| {
+                // NOTE: rows and cols can never be zero here, since this ndarray's `np.size` would be zero
+                // and this loop would not execute.
+
+                // Load up `row_i` and `col_i` from indices.
+                let row_i = nditer.get_indices().get_index_const(generator, ctx, 0);
+                let col_i = nditer.get_indices().get_index_const(generator, ctx, 1);
+
+                let be_one = row_i.add(ctx, offset).compare(ctx, IntPredicate::EQ, col_i);
+                let value = ctx.builder.build_select(be_one.value, ndone, ndzero, "value").unwrap();
+
+                let p = nditer.get_pointer(generator, ctx);
+                ctx.builder.build_store(p, value).unwrap();
+
+                Ok(())
+            })
+            .unwrap();
+
+        ndarray
+    }
+
+    /// Create an ndarray like `np.identity`.
+    pub fn make_np_identity<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        size: Instance<'ctx, Int<SizeT>>,
+    ) -> Self {
+        // Convenient implementation
+        let offset = Int(SizeT).const_0(generator, ctx.ctx);
+        NDArrayObject::make_np_eye(generator, ctx, dtype, size, size, offset)
+    }
+}

nac3core/src/codegen/object/ndarray/indexing.rs

@@ -0,0 +1,226 @@
+use super::NDArrayObject;
+use crate::codegen::{
+    irrt::call_nac3_ndarray_index,
+    model::*,
+    object::utils::slice::{RustSlice, Slice},
+    CodeGenContext, CodeGenerator,
+};
+
+pub type NDIndexType = Byte;
+
+/// Fields of [`NDIndex`]
+#[derive(Debug, Clone, Copy)]
+pub struct NDIndexFields<'ctx, F: FieldTraversal<'ctx>> {
+    pub type_: F::Output<Int<NDIndexType>>,
+    pub data: F::Output<Ptr<Int<Byte>>>,
+}
+
+/// An IRRT representation of an ndarray subscript index.
+#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
+pub struct NDIndex;
+
+impl<'ctx> StructKind<'ctx> for NDIndex {
+    type Fields<F: FieldTraversal<'ctx>> = NDIndexFields<'ctx, F>;
+
+    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+        Self::Fields { type_: traversal.add_auto("type"), data: traversal.add_auto("data") }
+    }
+}
+
+// A convenience enum representing a [`NDIndex`].
+#[derive(Debug, Clone)]
+pub enum RustNDIndex<'ctx> {
+    SingleElement(Instance<'ctx, Int<Int32>>),
+    Slice(RustSlice<'ctx, Int32>),
+    NewAxis,
+    Ellipsis,
+}
+
+impl<'ctx> RustNDIndex<'ctx> {
+    /// Get the value to set `NDIndex::type` for this variant.
+    fn get_type_id(&self) -> u64 {
+        // Defined in IRRT, must be in sync
+        match self {
+            RustNDIndex::SingleElement(_) => 0,
+            RustNDIndex::Slice(_) => 1,
+            RustNDIndex::NewAxis => 2,
+            RustNDIndex::Ellipsis => 3,
+        }
+    }
+
+    /// Serialize this [`RustNDIndex`] by writing it into an LLVM [`NDIndex`].
+    fn write_to_ndindex<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        dst_ndindex_ptr: Instance<'ctx, Ptr<Struct<NDIndex>>>,
+    ) {
+        // Set `dst_ndindex_ptr->type`
+        dst_ndindex_ptr.gep(ctx, |f| f.type_).store(
+            ctx,
+            Int(NDIndexType::default()).const_int(generator, ctx.ctx, self.get_type_id(), false),
+        );
+
+        // Set `dst_ndindex_ptr->data`
+        match self {
+            RustNDIndex::SingleElement(in_index) => {
+                let index_ptr = Int(Int32).alloca(generator, ctx);
+                index_ptr.store(ctx, *in_index);
+
+                dst_ndindex_ptr
+                    .gep(ctx, |f| f.data)
+                    .store(ctx, index_ptr.pointer_cast(generator, ctx, Int(Byte)));
+            }
+            RustNDIndex::Slice(in_rust_slice) => {
+                let user_slice_ptr = Struct(Slice(Int32)).alloca(generator, ctx);
+                in_rust_slice.write_to_slice(generator, ctx, user_slice_ptr);
+
+                dst_ndindex_ptr
+                    .gep(ctx, |f| f.data)
+                    .store(ctx, user_slice_ptr.pointer_cast(generator, ctx, Int(Byte)));
+            }
+            RustNDIndex::NewAxis | RustNDIndex::Ellipsis => {}
+        }
+    }
+
+    /// Serialize a list of `RustNDIndex` as a newly allocated LLVM array of `NDIndex`.
+    pub fn make_ndindices<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        in_ndindices: &[RustNDIndex<'ctx>],
+    ) -> (Instance<'ctx, Int<SizeT>>, Instance<'ctx, Ptr<Struct<NDIndex>>>) {
+        let ndindex_model = Struct(NDIndex);
+
+        // Allocate the LLVM ndindices.
+        let num_ndindices =
+            Int(SizeT).const_int(generator, ctx.ctx, in_ndindices.len() as u64, false);
+        let ndindices = ndindex_model.array_alloca(generator, ctx, num_ndindices.value);
+
+        // Initialize all of them.
+        for (i, in_ndindex) in in_ndindices.iter().enumerate() {
+            let pndindex = ndindices.offset_const(ctx, i64::try_from(i).unwrap());
+            in_ndindex.write_to_ndindex(generator, ctx, pndindex);
+        }
+
+        (num_ndindices, ndindices)
+    }
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Get the expected `ndims` after indexing with `indices`.
+    #[must_use]
+    fn deduce_ndims_after_indexing_with(&self, indices: &[RustNDIndex<'ctx>]) -> u64 {
+        let mut ndims = self.ndims;
+        for index in indices {
+            match index {
+                RustNDIndex::SingleElement(_) => {
+                    ndims -= 1; // Single elements decrements ndims
+                }
+                RustNDIndex::NewAxis => {
+                    ndims += 1; // `np.newaxis` / `none` adds a new axis
+                }
+                RustNDIndex::Ellipsis | RustNDIndex::Slice(_) => {}
+            }
+        }
+        ndims
+    }
+
+    /// Index into the ndarray, and return a newly-allocated view on this ndarray.
+    ///
+    /// This function behaves like NumPy's ndarray indexing, but if the indices index
+    /// into a single element, an unsized ndarray is returned.
+    #[must_use]
+    pub fn index<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        indices: &[RustNDIndex<'ctx>],
+    ) -> Self {
+        let dst_ndims = self.deduce_ndims_after_indexing_with(indices);
+        let dst_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, dst_ndims);
+
+        let (num_indices, indices) = RustNDIndex::make_ndindices(generator, ctx, indices);
+        call_nac3_ndarray_index(
+            generator,
+            ctx,
+            num_indices,
+            indices,
+            self.instance,
+            dst_ndarray.instance,
+        );
+
+        dst_ndarray
+    }
+}
+
+pub mod util {
+    use itertools::Itertools;
+    use nac3parser::ast::{Expr, ExprKind};
+
+    use crate::{
+        codegen::{model::*, object::utils::slice::util::gen_slice, CodeGenContext, CodeGenerator},
+        typecheck::typedef::Type,
+    };
+
+    use super::RustNDIndex;
+
+    /// Generate LLVM code to transform an ndarray subscript expression to
+    /// its list of [`RustNDIndex`]
+    ///
+    /// i.e.,
+    /// ```python
+    /// my_ndarray[::3, 1, :2:]
+    ///            ^^^^^^^^^^^ Then these into a three `RustNDIndex`es
+    /// ```
+    pub fn gen_ndarray_subscript_ndindices<'ctx, G: CodeGenerator>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        subscript: &Expr<Option<Type>>,
+    ) -> Result<Vec<RustNDIndex<'ctx>>, String> {
+        // TODO: Support https://numpy.org/doc/stable/user/basics.indexing.html#dimensional-indexing-tools
+
+        // Annoying notes about `slice`
+        //  - `my_array[5]`
+        //    - slice is a `Constant`
+        //  - `my_array[:5]`
+        //    - slice is a `Slice`
+        //  - `my_array[:]`
+        //    - slice is a `Slice`, but lower upper step would all be `Option::None`
+        //  - `my_array[:, :]`
+        //    - slice is now a `Tuple` of two `Slice`-s
+        //
+        // In summary:
+        //  - when there is a comma "," within [], `slice` will be a `Tuple` of the entries.
+        //  - when there is not comma "," within [] (i.e., just a single entry), `slice` will be that entry itself.
+        //
+        // So we first "flatten" out the slice expression
+        let index_exprs = match &subscript.node {
+            ExprKind::Tuple { elts, .. } => elts.iter().collect_vec(),
+            _ => vec![subscript],
+        };
+
+        // Process all index expressions
+        let mut rust_ndindices: Vec<RustNDIndex> = Vec::with_capacity(index_exprs.len()); // Not using iterators here because `?` is used here.
+        for index_expr in index_exprs {
+            // NOTE: Currently nac3core's slices do not have an object representation,
+            // so the code/implementation looks awkward - we have to do pattern matching on the expression
+            let ndindex = if let ExprKind::Slice { lower, upper, step } = &index_expr.node {
+                // Handle slices
+                let slice = gen_slice(generator, ctx, lower, upper, step)?;
+                RustNDIndex::Slice(slice)
+            } else {
+                // Treat and handle everything else as a single element index.
+                let index = generator.gen_expr(ctx, index_expr)?.unwrap().to_basic_value_enum(
+                    ctx,
+                    generator,
+                    ctx.primitives.int32, // Must be int32, this checks for illegal values
+                )?;
+                let index = Int(Int32).check_value(generator, ctx.ctx, index).unwrap();
+
+                RustNDIndex::SingleElement(index)
+            };
+            rust_ndindices.push(ndindex);
+        }
+        Ok(rust_ndindices)
+    }
+}

nac3core/src/codegen/object/ndarray/map.rs

@@ -0,0 +1,219 @@
+use inkwell::values::BasicValueEnum;
+use itertools::Itertools;
+
+use crate::{
+    codegen::{
+        object::ndarray::{AnyObject, NDArrayObject},
+        stmt::gen_for_callback,
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::Type,
+};
+
+use super::{nditer::NDIterHandle, NDArrayOut, ScalarOrNDArray};
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Generate LLVM IR to broadcast `ndarray`s together, and starmap through them with `mapping` elementwise.
+    ///
+    /// `mapping` is an LLVM IR generator. The input of `mapping` is the list of elements when iterating through
+    /// the input `ndarrays` after broadcasting. The output of `mapping` is the result of the elementwise operation.
+    ///
+    /// `out` specifies whether the result should be a new ndarray or to be written an existing ndarray.
+    pub fn broadcast_starmap<'a, G, MappingFn>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        ndarrays: &[Self],
+        out: NDArrayOut<'ctx>,
+        mapping: MappingFn,
+    ) -> Result<Self, String>
+    where
+        G: CodeGenerator + ?Sized,
+        MappingFn: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            &[BasicValueEnum<'ctx>],
+        ) -> Result<BasicValueEnum<'ctx>, String>,
+    {
+        // Broadcast inputs
+        let broadcast_result = NDArrayObject::broadcast(generator, ctx, ndarrays);
+
+        let out_ndarray = match out {
+            NDArrayOut::NewNDArray { dtype } => {
+                // Create a new ndarray based on the broadcast shape.
+                let result_ndarray =
+                    NDArrayObject::alloca(generator, ctx, dtype, broadcast_result.ndims);
+                result_ndarray.copy_shape_from_array(generator, ctx, broadcast_result.shape);
+                result_ndarray.create_data(generator, ctx);
+                result_ndarray
+            }
+            NDArrayOut::WriteToNDArray { ndarray: result_ndarray } => {
+                // Use an existing ndarray.
+
+                // Check that its shape is compatible with the broadcast shape.
+                result_ndarray.assert_can_be_written_by_out(
+                    generator,
+                    ctx,
+                    broadcast_result.ndims,
+                    broadcast_result.shape,
+                );
+                result_ndarray
+            }
+        };
+
+        // Map element-wise and store results into `mapped_ndarray`.
+        let nditer = NDIterHandle::new(generator, ctx, out_ndarray);
+        gen_for_callback(
+            generator,
+            ctx,
+            Some("broadcast_starmap"),
+            |generator, ctx| {
+                // Create NDIters for all broadcasted input ndarrays.
+                let other_nditers = broadcast_result
+                    .ndarrays
+                    .iter()
+                    .map(|ndarray| NDIterHandle::new(generator, ctx, *ndarray))
+                    .collect_vec();
+                Ok((nditer, other_nditers))
+            },
+            |generator, ctx, (out_nditer, _in_nditers)| {
+                // We can simply use `out_nditer`'s `has_element()`.
+                // `in_nditers`' `has_element()`s should return the same value.
+                Ok(out_nditer.has_element(generator, ctx).value)
+            },
+            |generator, ctx, _hooks, (out_nditer, in_nditers)| {
+                // Get all the scalars from the broadcasted input ndarrays, pass them to `mapping`,
+                // and write to `out_ndarray`.
+                let in_scalars = in_nditers
+                    .iter()
+                    .map(|nditer| nditer.get_scalar(generator, ctx).value)
+                    .collect_vec();
+
+                let result = mapping(generator, ctx, &in_scalars)?;
+
+                let p = out_nditer.get_pointer(generator, ctx);
+                ctx.builder.build_store(p, result).unwrap();
+
+                Ok(())
+            },
+            |generator, ctx, (out_nditer, in_nditers)| {
+                // Advance all iterators
+                out_nditer.next(generator, ctx);
+                in_nditers.iter().for_each(|nditer| nditer.next(generator, ctx));
+                Ok(())
+            },
+        )?;
+
+        Ok(out_ndarray)
+    }
+
+    /// Map through this ndarray with an elementwise function.
+    pub fn map<'a, G, Mapping>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        out: NDArrayOut<'ctx>,
+        mapping: Mapping,
+    ) -> Result<Self, String>
+    where
+        G: CodeGenerator + ?Sized,
+        Mapping: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            BasicValueEnum<'ctx>,
+        ) -> Result<BasicValueEnum<'ctx>, String>,
+    {
+        NDArrayObject::broadcast_starmap(
+            generator,
+            ctx,
+            &[*self],
+            out,
+            |generator, ctx, scalars| mapping(generator, ctx, scalars[0]),
+        )
+    }
+}
+
+impl<'ctx> ScalarOrNDArray<'ctx> {
+    /// Starmap through a list of inputs using `mapping`, where an input could be an ndarray, a scalar.
+    ///
+    /// This function is very helpful when implementing NumPy functions that takes on either scalars or ndarrays or a mix of them
+    /// as their inputs and produces either an ndarray with broadcast, or a scalar if all its inputs are all scalars.
+    ///
+    /// For example ,this function can be used to implement `np.add`, which has the following behaviors:
+    /// - `np.add(3, 4) = 7` # (scalar, scalar) -> scalar
+    /// - `np.add(3, np.array([4, 5, 6]))` # (scalar, ndarray) -> ndarray; the first `scalar` is converted into an ndarray and broadcasted.
+    /// - `np.add(np.array([[1], [2], [3]]), np.array([[4, 5, 6]]))` # (ndarray, ndarray) -> ndarray; there is broadcasting.
+    ///
+    /// ## Details:
+    ///
+    /// If `inputs` are all [`ScalarOrNDArray::Scalar`], the output will be a [`ScalarOrNDArray::Scalar`] with type `ret_dtype`.
+    ///
+    /// Otherwise (if there are any [`ScalarOrNDArray::NDArray`] in `inputs`), all inputs will be 'as-ndarray'-ed into ndarrays,
+    /// then all inputs (now all ndarrays) will be passed to [`NDArrayObject::broadcasting_starmap`] and **create** a new ndarray
+    /// with dtype `ret_dtype`.
+    pub fn broadcasting_starmap<'a, G, MappingFn>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        inputs: &[ScalarOrNDArray<'ctx>],
+        ret_dtype: Type,
+        mapping: MappingFn,
+    ) -> Result<ScalarOrNDArray<'ctx>, String>
+    where
+        G: CodeGenerator + ?Sized,
+        MappingFn: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            &[BasicValueEnum<'ctx>],
+        ) -> Result<BasicValueEnum<'ctx>, String>,
+    {
+        // Check if all inputs are Scalars
+        let all_scalars: Option<Vec<_>> = inputs.iter().map(AnyObject::try_from).try_collect().ok();
+
+        if let Some(scalars) = all_scalars {
+            let scalars = scalars.iter().map(|scalar| scalar.value).collect_vec();
+            let value = mapping(generator, ctx, &scalars)?;
+
+            Ok(ScalarOrNDArray::Scalar(AnyObject { ty: ret_dtype, value }))
+        } else {
+            // Promote all input to ndarrays and map through them.
+            let inputs = inputs.iter().map(|input| input.to_ndarray(generator, ctx)).collect_vec();
+            let ndarray = NDArrayObject::broadcast_starmap(
+                generator,
+                ctx,
+                &inputs,
+                NDArrayOut::NewNDArray { dtype: ret_dtype },
+                mapping,
+            )?;
+            Ok(ScalarOrNDArray::NDArray(ndarray))
+        }
+    }
+
+    /// Map through this [`ScalarOrNDArray`] with an elementwise function.
+    ///
+    /// If this is a scalar, `mapping` will directly act on the scalar. This function will return a [`ScalarOrNDArray::Scalar`] of that result.
+    ///
+    /// If this is an ndarray, `mapping` will be applied to the elements of the ndarray. A new ndarray of the results will be created and
+    /// returned as a [`ScalarOrNDArray::NDArray`].
+    pub fn map<'a, G, Mapping>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        ret_dtype: Type,
+        mapping: Mapping,
+    ) -> Result<ScalarOrNDArray<'ctx>, String>
+    where
+        G: CodeGenerator + ?Sized,
+        Mapping: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            BasicValueEnum<'ctx>,
+        ) -> Result<BasicValueEnum<'ctx>, String>,
+    {
+        ScalarOrNDArray::broadcasting_starmap(
+            generator,
+            ctx,
+            &[*self],
+            ret_dtype,
+            |generator, ctx, scalars| mapping(generator, ctx, scalars[0]),
+        )
+    }
+}

nac3core/src/codegen/object/ndarray/matmul.rs

@@ -0,0 +1,216 @@
+use std::cmp::max;
+
+use nac3parser::ast::Operator;
+
+use super::{util::gen_for_model, NDArrayObject, NDArrayOut};
+use crate::{
+    codegen::{
+        expr::gen_binop_expr_with_values, irrt::call_nac3_ndarray_matmul_calculate_shapes,
+        model::*, object::ndarray::indexing::RustNDIndex, CodeGenContext, CodeGenerator,
+    },
+    typecheck::{magic_methods::Binop, typedef::Type},
+};
+
+/// Perform `np.einsum("...ij,...jk->...ik", in_a, in_b)`.
+///
+/// `dst_dtype` defines the dtype of the returned ndarray.
+fn matmul_at_least_2d<'ctx, G: CodeGenerator>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    dst_dtype: Type,
+    in_a: NDArrayObject<'ctx>,
+    in_b: NDArrayObject<'ctx>,
+) -> NDArrayObject<'ctx> {
+    assert!(in_a.ndims >= 2);
+    assert!(in_b.ndims >= 2);
+
+    // Deduce ndims of the result of matmul.
+    let ndims_int = max(in_a.ndims, in_b.ndims);
+    let ndims = Int(SizeT).const_int(generator, ctx.ctx, ndims_int, false);
+
+    // Broadcasts `in_a.shape[:-2]` and `in_b.shape[:-2]` together and allocate the
+    // destination ndarray to store the result of matmul.
+    let (lhs, rhs, dst) = {
+        let in_lhs_ndims = in_a.ndims_llvm(generator, ctx.ctx);
+        let in_lhs_shape = in_a.instance.get(generator, ctx, |f| f.shape);
+        let in_rhs_ndims = in_b.ndims_llvm(generator, ctx.ctx);
+        let in_rhs_shape = in_b.instance.get(generator, ctx, |f| f.shape);
+        let lhs_shape = Int(SizeT).array_alloca(generator, ctx, ndims.value);
+        let rhs_shape = Int(SizeT).array_alloca(generator, ctx, ndims.value);
+        let dst_shape = Int(SizeT).array_alloca(generator, ctx, ndims.value);
+
+        // Matmul dimension compatibility is checked here.
+        call_nac3_ndarray_matmul_calculate_shapes(
+            generator,
+            ctx,
+            in_lhs_ndims,
+            in_lhs_shape,
+            in_rhs_ndims,
+            in_rhs_shape,
+            ndims,
+            lhs_shape,
+            rhs_shape,
+            dst_shape,
+        );
+
+        let lhs = in_a.broadcast_to(generator, ctx, ndims_int, lhs_shape);
+        let rhs = in_b.broadcast_to(generator, ctx, ndims_int, rhs_shape);
+
+        let dst = NDArrayObject::alloca(generator, ctx, dst_dtype, ndims_int);
+        dst.copy_shape_from_array(generator, ctx, dst_shape);
+        dst.create_data(generator, ctx);
+
+        (lhs, rhs, dst)
+    };
+
+    let len = lhs.instance.get(generator, ctx, |f| f.shape).get_index_const(
+        generator,
+        ctx,
+        i64::try_from(ndims_int - 1).unwrap(),
+    );
+
+    let at_row = i64::try_from(ndims_int - 2).unwrap();
+    let at_col = i64::try_from(ndims_int - 1).unwrap();
+
+    let dst_dtype_llvm = ctx.get_llvm_type(generator, dst_dtype);
+    let dst_zero = dst_dtype_llvm.const_zero();
+
+    dst.foreach(generator, ctx, |generator, ctx, _, hdl| {
+        let pdst_ij = hdl.get_pointer(generator, ctx);
+
+        ctx.builder.build_store(pdst_ij, dst_zero).unwrap();
+
+        let indices = hdl.get_indices();
+        let i = indices.get_index_const(generator, ctx, at_row);
+        let j = indices.get_index_const(generator, ctx, at_col);
+
+        let num_0 = Int(SizeT).const_int(generator, ctx.ctx, 0, false);
+        let num_1 = Int(SizeT).const_int(generator, ctx.ctx, 1, false);
+
+        gen_for_model(generator, ctx, num_0, len, num_1, |generator, ctx, _, k| {
+            // `indices` is modified to index into `a` and `b`, and restored.
+            indices.set_index_const(ctx, at_row, i);
+            indices.set_index_const(ctx, at_col, k);
+            let a_ik = lhs.get_scalar_by_indices(generator, ctx, indices);
+
+            indices.set_index_const(ctx, at_row, k);
+            indices.set_index_const(ctx, at_col, j);
+            let b_kj = rhs.get_scalar_by_indices(generator, ctx, indices);
+
+            // Restore `indices`.
+            indices.set_index_const(ctx, at_row, i);
+            indices.set_index_const(ctx, at_col, j);
+
+            // x = a_[...]ik * b_[...]kj
+            let x = gen_binop_expr_with_values(
+                generator,
+                ctx,
+                (&Some(lhs.dtype), a_ik.value),
+                Binop::normal(Operator::Mult),
+                (&Some(rhs.dtype), b_kj.value),
+                ctx.current_loc,
+            )?
+            .unwrap()
+            .to_basic_value_enum(ctx, generator, dst_dtype)?;
+
+            // dst_[...]ij += x
+            let dst_ij = ctx.builder.build_load(pdst_ij, "").unwrap();
+            let dst_ij = gen_binop_expr_with_values(
+                generator,
+                ctx,
+                (&Some(dst_dtype), dst_ij),
+                Binop::normal(Operator::Add),
+                (&Some(dst_dtype), x),
+                ctx.current_loc,
+            )?
+            .unwrap()
+            .to_basic_value_enum(ctx, generator, dst_dtype)?;
+            ctx.builder.build_store(pdst_ij, dst_ij).unwrap();
+
+            Ok(())
+        })
+    })
+    .unwrap();
+
+    dst
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Perform `np.matmul` according to the rules in
+    /// <https://numpy.org/doc/stable/reference/generated/numpy.matmul.html>.
+    ///
+    /// This function always return an [`NDArrayObject`]. You may want to use [`NDArrayObject::split_unsized`]
+    /// to handle when the output could be a scalar.
+    ///
+    /// `dst_dtype` defines the dtype of the returned ndarray.
+    pub fn matmul<G: CodeGenerator>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        a: Self,
+        b: Self,
+        out: NDArrayOut<'ctx>,
+    ) -> Self {
+        // Sanity check, but type inference should prevent this.
+        assert!(a.ndims > 0 && b.ndims > 0, "np.matmul disallows scalar input");
+
+        /*
+            If both arguments are 2-D they are multiplied like conventional matrices.
+            If either argument is N-D, N > 2, it is treated as a stack of matrices residing in the last two indices and broadcast accordingly.
+            If the first argument is 1-D, it is promoted to a matrix by prepending a 1 to its dimensions. After matrix multiplication the prepended 1 is removed.
+            If the second argument is 1-D, it is promoted to a matrix by appending a 1 to its dimensions. After matrix multiplication the appended 1 is removed.
+        */
+
+        let new_a = if a.ndims == 1 {
+            // Prepend 1 to its dimensions
+            a.index(generator, ctx, &[RustNDIndex::NewAxis, RustNDIndex::Ellipsis])
+        } else {
+            a
+        };
+
+        let new_b = if b.ndims == 1 {
+            // Append 1 to its dimensions
+            b.index(generator, ctx, &[RustNDIndex::Ellipsis, RustNDIndex::NewAxis])
+        } else {
+            b
+        };
+
+        // NOTE: `result` will always be a newly allocated ndarray.
+        // Current implementation cannot do in-place matrix muliplication.
+        let mut result = matmul_at_least_2d(generator, ctx, out.get_dtype(), new_a, new_b);
+
+        // Postprocessing on the result to remove prepended/appended axes.
+        let mut postindices = vec![];
+        let zero = Int(Int32).const_0(generator, ctx.ctx);
+
+        if a.ndims == 1 {
+            // Remove the prepended 1
+            postindices.push(RustNDIndex::SingleElement(zero));
+        }
+
+        if b.ndims == 1 {
+            // Remove the appended 1
+            postindices.push(RustNDIndex::Ellipsis);
+            postindices.push(RustNDIndex::SingleElement(zero));
+        }
+
+        if !postindices.is_empty() {
+            result = result.index(generator, ctx, &postindices);
+        }
+
+        match out {
+            NDArrayOut::NewNDArray { .. } => result,
+            NDArrayOut::WriteToNDArray { ndarray: out_ndarray } => {
+                let result_shape = result.instance.get(generator, ctx, |f| f.shape);
+                out_ndarray.assert_can_be_written_by_out(
+                    generator,
+                    ctx,
+                    result.ndims,
+                    result_shape,
+                );
+
+                out_ndarray.copy_data_from(generator, ctx, result);
+                out_ndarray
+            }
+        }
+    }
+}

nac3core/src/codegen/object/ndarray/mod.rs

@@ -0,0 +1,669 @@
+use inkwell::{
+    context::Context,
+    types::BasicType,
+    values::{BasicValue, BasicValueEnum, PointerValue},
+    AddressSpace,
+};
+
+use super::{any::AnyObject, tuple::TupleObject};
+use crate::{
+    codegen::{
+        irrt::{
+            call_nac3_ndarray_copy_data, call_nac3_ndarray_get_nth_pelement,
+            call_nac3_ndarray_get_pelement_by_indices, call_nac3_ndarray_is_c_contiguous,
+            call_nac3_ndarray_len, call_nac3_ndarray_nbytes,
+            call_nac3_ndarray_set_strides_by_shape, call_nac3_ndarray_size,
+            call_nac3_ndarray_util_assert_output_shape_same,
+        },
+        model::*,
+        CodeGenContext, CodeGenerator,
+    },
+    toplevel::{
+        helper::{create_ndims, extract_ndims},
+        numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
+    },
+    typecheck::typedef::{Type, TypeEnum},
+};
+
+pub mod array;
+pub mod broadcast;
+pub mod contiguous;
+pub mod factory;
+pub mod indexing;
+pub mod map;
+pub mod matmul;
+pub mod nditer;
+pub mod shape_util;
+pub mod view;
+
+/// Fields of [`NDArray`]
+pub struct NDArrayFields<'ctx, F: FieldTraversal<'ctx>> {
+    pub data: F::Output<Ptr<Int<Byte>>>,
+    pub itemsize: F::Output<Int<SizeT>>,
+    pub ndims: F::Output<Int<SizeT>>,
+    pub shape: F::Output<Ptr<Int<SizeT>>>,
+    pub strides: F::Output<Ptr<Int<SizeT>>>,
+}
+
+/// A strided ndarray in NAC3.
+///
+/// See IRRT implementation for details about its fields.
+#[derive(Debug, Clone, Copy, Default)]
+pub struct NDArray;
+
+impl<'ctx> StructKind<'ctx> for NDArray {
+    type Fields<F: FieldTraversal<'ctx>> = NDArrayFields<'ctx, F>;
+
+    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            data: traversal.add_auto("data"),
+            itemsize: traversal.add_auto("itemsize"),
+            ndims: traversal.add_auto("ndims"),
+            shape: traversal.add_auto("shape"),
+            strides: traversal.add_auto("strides"),
+        }
+    }
+}
+
+/// A NAC3 Python ndarray object.
+#[derive(Debug, Clone, Copy)]
+pub struct NDArrayObject<'ctx> {
+    pub dtype: Type,
+    pub ndims: u64,
+    pub instance: Instance<'ctx, Ptr<Struct<NDArray>>>,
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Attempt to convert an [`AnyObject`] into an [`NDArrayObject`].
+    pub fn from_object<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        object: AnyObject<'ctx>,
+    ) -> NDArrayObject<'ctx> {
+        let (dtype, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, object.ty);
+        let ndims = extract_ndims(&ctx.unifier, ndims);
+        Self::from_value_and_unpacked_types(generator, ctx, object.value, dtype, ndims)
+    }
+
+    /// Like [`NDArrayObject::from_object`] but you directly supply the ndarray's
+    /// `dtype` and `ndims`.
+    pub fn from_value_and_unpacked_types<V: BasicValue<'ctx>, G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        value: V,
+        dtype: Type,
+        ndims: u64,
+    ) -> Self {
+        let value = Ptr(Struct(NDArray)).check_value(generator, ctx.ctx, value).unwrap();
+        NDArrayObject { dtype, ndims, instance: value }
+    }
+
+    /// Get this ndarray's `ndims` as an LLVM constant.
+    pub fn ndims_llvm<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> Instance<'ctx, Int<SizeT>> {
+        Int(SizeT).const_int(generator, ctx, self.ndims, false)
+    }
+
+    /// Get the typechecker ndarray type of this [`NDArrayObject`].
+    pub fn get_type(&self, ctx: &mut CodeGenContext<'ctx, '_>) -> Type {
+        let ndims = create_ndims(&mut ctx.unifier, self.ndims);
+        make_ndarray_ty(&mut ctx.unifier, &ctx.primitives, Some(self.dtype), Some(ndims))
+    }
+
+    /// Forget that this is an ndarray and convert into an [`AnyObject`].
+    pub fn to_any(&self, ctx: &mut CodeGenContext<'ctx, '_>) -> AnyObject<'ctx> {
+        let ty = self.get_type(ctx);
+        AnyObject { value: self.instance.value.as_basic_value_enum(), ty }
+    }
+
+    /// Allocate an ndarray on the stack given its `ndims` and `dtype`.
+    ///
+    /// `shape` and `strides` will be automatically allocated onto the stack.
+    ///
+    /// The returned ndarray's content will be:
+    /// - `data`: uninitialized.
+    /// - `itemsize`: set to the `sizeof()` of `dtype`.
+    /// - `ndims`: set to the value of  `ndims`.
+    /// - `shape`: allocated with an array of length `ndims` with uninitialized values.
+    /// - `strides`: allocated with an array of length `ndims` with uninitialized values.
+    pub fn alloca<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        ndims: u64,
+    ) -> Self {
+        let ndarray = Struct(NDArray).alloca(generator, ctx);
+
+        let itemsize = ctx.get_llvm_type(generator, dtype).size_of().unwrap();
+        let itemsize = Int(SizeT).z_extend_or_truncate(generator, ctx, itemsize);
+        ndarray.set(ctx, |f| f.itemsize, itemsize);
+
+        let ndims_val = Int(SizeT).const_int(generator, ctx.ctx, ndims, false);
+        ndarray.set(ctx, |f| f.ndims, ndims_val);
+
+        let shape = Int(SizeT).array_alloca(generator, ctx, ndims_val.value);
+        ndarray.set(ctx, |f| f.shape, shape);
+
+        let strides = Int(SizeT).array_alloca(generator, ctx, ndims_val.value);
+        ndarray.set(ctx, |f| f.strides, strides);
+
+        NDArrayObject { dtype, ndims, instance: ndarray }
+    }
+
+    /// Convenience function. Allocate an [`NDArrayObject`] with a statically known shape.
+    ///
+    /// The returned [`NDArrayObject`]'s `data` and `strides` are uninitialized.
+    pub fn alloca_constant_shape<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        shape: &[u64],
+    ) -> Self {
+        let ndarray = NDArrayObject::alloca(generator, ctx, dtype, shape.len() as u64);
+
+        // Write shape
+        let dst_shape = ndarray.instance.get(generator, ctx, |f| f.shape);
+        for (i, dim) in shape.iter().enumerate() {
+            let dim = Int(SizeT).const_int(generator, ctx.ctx, *dim, false);
+            dst_shape.offset_const(ctx, i64::try_from(i).unwrap()).store(ctx, dim);
+        }
+
+        ndarray
+    }
+
+    /// Convenience function. Allocate an [`NDArrayObject`] with a dynamically known shape.
+    ///
+    /// The returned [`NDArrayObject`]'s `data` and `strides` are uninitialized.
+    pub fn alloca_dynamic_shape<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        shape: &[Instance<'ctx, Int<SizeT>>],
+    ) -> Self {
+        let ndarray = NDArrayObject::alloca(generator, ctx, dtype, shape.len() as u64);
+
+        // Write shape
+        let dst_shape = ndarray.instance.get(generator, ctx, |f| f.shape);
+        for (i, dim) in shape.iter().enumerate() {
+            dst_shape.offset_const(ctx, i64::try_from(i).unwrap()).store(ctx, *dim);
+        }
+
+        ndarray
+    }
+
+    /// Initialize an ndarray's `data` by allocating a buffer on the stack.
+    /// The allocated data buffer is considered to be *owned* by the ndarray.
+    ///
+    /// `strides` of the ndarray will also be updated with `set_strides_by_shape`.
+    ///
+    /// `shape` and `itemsize` of the ndarray ***must*** be initialized first.
+    pub fn create_data<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) {
+        let nbytes = self.nbytes(generator, ctx);
+
+        let data = Int(Byte).array_alloca(generator, ctx, nbytes.value);
+        self.instance.set(ctx, |f| f.data, data);
+
+        self.set_strides_contiguous(generator, ctx);
+    }
+
+    /// Copy shape dimensions from an array.
+    pub fn copy_shape_from_array<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) {
+        let num_items = self.ndims_llvm(generator, ctx.ctx).value;
+        self.instance.get(generator, ctx, |f| f.shape).copy_from(generator, ctx, shape, num_items);
+    }
+
+    /// Copy shape dimensions from an ndarray.
+    /// Panics if `ndims` mismatches.
+    pub fn copy_shape_from_ndarray<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        src_ndarray: NDArrayObject<'ctx>,
+    ) {
+        assert_eq!(self.ndims, src_ndarray.ndims);
+        let src_shape = src_ndarray.instance.get(generator, ctx, |f| f.shape);
+        self.copy_shape_from_array(generator, ctx, src_shape);
+    }
+
+    /// Copy strides dimensions from an array.
+    pub fn copy_strides_from_array<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        strides: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) {
+        let num_items = self.ndims_llvm(generator, ctx.ctx).value;
+        self.instance
+            .get(generator, ctx, |f| f.strides)
+            .copy_from(generator, ctx, strides, num_items);
+    }
+
+    /// Copy strides dimensions from an ndarray.
+    /// Panics if `ndims` mismatches.
+    pub fn copy_strides_from_ndarray<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        src_ndarray: NDArrayObject<'ctx>,
+    ) {
+        assert_eq!(self.ndims, src_ndarray.ndims);
+        let src_strides = src_ndarray.instance.get(generator, ctx, |f| f.strides);
+        self.copy_strides_from_array(generator, ctx, src_strides);
+    }
+
+    /// Get the `np.size()` of this ndarray.
+    pub fn size<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<SizeT>> {
+        call_nac3_ndarray_size(generator, ctx, self.instance)
+    }
+
+    /// Get the `ndarray.nbytes` of this ndarray.
+    pub fn nbytes<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<SizeT>> {
+        call_nac3_ndarray_nbytes(generator, ctx, self.instance)
+    }
+
+    /// Get the `len()` of this ndarray.
+    pub fn len<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<SizeT>> {
+        call_nac3_ndarray_len(generator, ctx, self.instance)
+    }
+
+    /// Check if this ndarray is C-contiguous.
+    ///
+    /// See NumPy's `flags["C_CONTIGUOUS"]`: <https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html#numpy.ndarray.flags>
+    pub fn is_c_contiguous<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<Bool>> {
+        call_nac3_ndarray_is_c_contiguous(generator, ctx, self.instance)
+    }
+
+    /// Get the pointer to the n-th (0-based) element.
+    ///
+    /// The returned pointer has the element type of the LLVM type of this ndarray's `dtype`.
+    pub fn get_nth_pelement<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        nth: Instance<'ctx, Int<SizeT>>,
+    ) -> PointerValue<'ctx> {
+        let elem_ty = ctx.get_llvm_type(generator, self.dtype);
+
+        let p = call_nac3_ndarray_get_nth_pelement(generator, ctx, self.instance, nth);
+        ctx.builder
+            .build_pointer_cast(p.value, elem_ty.ptr_type(AddressSpace::default()), "")
+            .unwrap()
+    }
+
+    /// Get the n-th (0-based) scalar.
+    pub fn get_nth_scalar<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        nth: Instance<'ctx, Int<SizeT>>,
+    ) -> AnyObject<'ctx> {
+        let ptr = self.get_nth_pelement(generator, ctx, nth);
+        let value = ctx.builder.build_load(ptr, "").unwrap();
+        AnyObject { ty: self.dtype, value }
+    }
+
+    /// Get the pointer to the element indexed by `indices`.
+    ///
+    /// The returned pointer has the element type of the LLVM type of this ndarray's `dtype`.
+    pub fn get_pelement_by_indices<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        indices: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) -> PointerValue<'ctx> {
+        let elem_ty = ctx.get_llvm_type(generator, self.dtype);
+
+        let p = call_nac3_ndarray_get_pelement_by_indices(generator, ctx, self.instance, indices);
+        ctx.builder
+            .build_pointer_cast(p.value, elem_ty.ptr_type(AddressSpace::default()), "")
+            .unwrap()
+    }
+
+    /// Get the scalar indexed by `indices`.
+    pub fn get_scalar_by_indices<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        indices: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) -> AnyObject<'ctx> {
+        let ptr = self.get_pelement_by_indices(generator, ctx, indices);
+        let value = ctx.builder.build_load(ptr, "").unwrap();
+        AnyObject { ty: self.dtype, value }
+    }
+
+    /// Call [`call_nac3_ndarray_set_strides_by_shape`] on this ndarray to update `strides`.
+    ///
+    /// Update the ndarray's strides to make the ndarray contiguous.
+    pub fn set_strides_contiguous<G: CodeGenerator + ?Sized>(
+        self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) {
+        call_nac3_ndarray_set_strides_by_shape(generator, ctx, self.instance);
+    }
+
+    /// Clone/Copy this ndarray - Allocate a new ndarray with the same shape as this ndarray and copy the contents over.
+    ///
+    /// The new ndarray will own its data and will be C-contiguous.
+    #[must_use]
+    pub fn make_copy<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Self {
+        let clone = NDArrayObject::alloca(generator, ctx, self.dtype, self.ndims);
+
+        let shape = self.instance.gep(ctx, |f| f.shape).load(generator, ctx);
+        clone.copy_shape_from_array(generator, ctx, shape);
+        clone.create_data(generator, ctx);
+        clone.copy_data_from(generator, ctx, *self);
+        clone
+    }
+
+    /// Copy data from another ndarray.
+    ///
+    /// This ndarray and `src` is that their `np.size()` should be the same. Their shapes
+    /// do not matter. The copying order is determined by how their flattened views look.
+    ///
+    /// Panics if the `dtype`s of ndarrays are different.
+    pub fn copy_data_from<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        src: NDArrayObject<'ctx>,
+    ) {
+        assert!(ctx.unifier.unioned(self.dtype, src.dtype), "self and src dtype should match");
+        call_nac3_ndarray_copy_data(generator, ctx, src.instance, self.instance);
+    }
+
+    /// Returns true if this ndarray is unsized - `ndims == 0` and only contains a scalar.
+    #[must_use]
+    pub fn is_unsized(&self) -> bool {
+        self.ndims == 0
+    }
+
+    /// If this ndarray is unsized, return its sole value as an [`AnyObject`].
+    /// Otherwise, do nothing and return the ndarray itself.
+    pub fn split_unsized<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> ScalarOrNDArray<'ctx> {
+        if self.is_unsized() {
+            // NOTE: `np.size(self) == 0` here is never possible.
+            let zero = Int(SizeT).const_0(generator, ctx.ctx);
+            let value = self.get_nth_scalar(generator, ctx, zero).value;
+
+            ScalarOrNDArray::Scalar(AnyObject { ty: self.dtype, value })
+        } else {
+            ScalarOrNDArray::NDArray(*self)
+        }
+    }
+
+    /// Fill the ndarray with a scalar.
+    ///
+    /// `fill_value` must have the same LLVM type as the `dtype` of this ndarray.
+    pub fn fill<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        value: BasicValueEnum<'ctx>,
+    ) {
+        // TODO: It is possible to optimize this by exploiting contiguous strides with memset.
+        // Probably best to implement in IRRT.
+        self.foreach(generator, ctx, |generator, ctx, _hooks, nditer| {
+            let p = nditer.get_pointer(generator, ctx);
+            ctx.builder.build_store(p, value).unwrap();
+            Ok(())
+        })
+        .unwrap();
+    }
+
+    /// Create the shape tuple of this ndarray like `np.shape(<ndarray>)`.
+    ///
+    /// The returned integers in the tuple are in int32.
+    pub fn make_shape_tuple<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> TupleObject<'ctx> {
+        // TODO: Return a tuple of SizeT
+
+        let mut objects = Vec::with_capacity(self.ndims as usize);
+
+        for i in 0..self.ndims {
+            let dim = self
+                .instance
+                .get(generator, ctx, |f| f.shape)
+                .get_index_const(generator, ctx, i64::try_from(i).unwrap())
+                .truncate_or_bit_cast(generator, ctx, Int32);
+
+            objects.push(AnyObject {
+                ty: ctx.primitives.int32,
+                value: dim.value.as_basic_value_enum(),
+            });
+        }
+
+        TupleObject::from_objects(generator, ctx, objects)
+    }
+
+    /// Create the strides tuple of this ndarray like `<ndarray>.strides`.
+    ///
+    /// The returned integers in the tuple are in int32.
+    pub fn make_strides_tuple<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> TupleObject<'ctx> {
+        // TODO: Return a tuple of SizeT.
+
+        let mut objects = Vec::with_capacity(self.ndims as usize);
+
+        for i in 0..self.ndims {
+            let dim = self
+                .instance
+                .get(generator, ctx, |f| f.strides)
+                .get_index_const(generator, ctx, i64::try_from(i).unwrap())
+                .truncate_or_bit_cast(generator, ctx, Int32);
+
+            objects.push(AnyObject {
+                ty: ctx.primitives.int32,
+                value: dim.value.as_basic_value_enum(),
+            });
+        }
+
+        TupleObject::from_objects(generator, ctx, objects)
+    }
+
+    /// Create an unsized ndarray to contain `object`.
+    pub fn make_unsized<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        object: AnyObject<'ctx>,
+    ) -> NDArrayObject<'ctx> {
+        // We have to put the value on the stack to get a data pointer.
+        let data = ctx.builder.build_alloca(object.value.get_type(), "make_unsized").unwrap();
+        ctx.builder.build_store(data, object.value).unwrap();
+        let data = Ptr(Int(Byte)).pointer_cast(generator, ctx, data);
+
+        let ndarray = NDArrayObject::alloca(generator, ctx, object.ty, 0);
+        ndarray.instance.set(ctx, |f| f.data, data);
+        ndarray
+    }
+    /// Check if this `NDArray` can be used as an `out` ndarray for an operation.
+    ///
+    /// Raise an exception if the shapes do not match.
+    pub fn assert_can_be_written_by_out<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        out_ndims: u64,
+        out_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) {
+        let ndarray_ndims = self.ndims_llvm(generator, ctx.ctx);
+        let ndarray_shape = self.instance.get(generator, ctx, |f| f.shape);
+
+        let output_ndims = Int(SizeT).const_int(generator, ctx.ctx, out_ndims, false);
+        let output_shape = out_shape;
+
+        call_nac3_ndarray_util_assert_output_shape_same(
+            generator,
+            ctx,
+            ndarray_ndims,
+            ndarray_shape,
+            output_ndims,
+            output_shape,
+        );
+    }
+}
+
+/// A convenience enum for implementing functions that acts on scalars or ndarrays or both.
+#[derive(Debug, Clone, Copy)]
+pub enum ScalarOrNDArray<'ctx> {
+    Scalar(AnyObject<'ctx>),
+    NDArray(NDArrayObject<'ctx>),
+}
+
+impl<'ctx> TryFrom<&ScalarOrNDArray<'ctx>> for AnyObject<'ctx> {
+    type Error = ();
+
+    fn try_from(value: &ScalarOrNDArray<'ctx>) -> Result<Self, Self::Error> {
+        match value {
+            ScalarOrNDArray::Scalar(scalar) => Ok(*scalar),
+            ScalarOrNDArray::NDArray(_ndarray) => Err(()),
+        }
+    }
+}
+
+impl<'ctx> TryFrom<&ScalarOrNDArray<'ctx>> for NDArrayObject<'ctx> {
+    type Error = ();
+
+    fn try_from(value: &ScalarOrNDArray<'ctx>) -> Result<Self, Self::Error> {
+        match value {
+            ScalarOrNDArray::Scalar(_scalar) => Err(()),
+            ScalarOrNDArray::NDArray(ndarray) => Ok(*ndarray),
+        }
+    }
+}
+
+impl<'ctx> ScalarOrNDArray<'ctx> {
+    /// Split on `object` either into a scalar or an ndarray.
+    ///
+    /// If `object` is an ndarray, [`ScalarOrNDArray::NDArray`].
+    ///
+    /// For everything else, it is wrapped with [`ScalarOrNDArray::Scalar`].
+    pub fn split_object<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        object: AnyObject<'ctx>,
+    ) -> ScalarOrNDArray<'ctx> {
+        match &*ctx.unifier.get_ty(object.ty) {
+            TypeEnum::TObj { obj_id, .. }
+                if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
+            {
+                let ndarray = NDArrayObject::from_object(generator, ctx, object);
+                ScalarOrNDArray::NDArray(ndarray)
+            }
+            _ => ScalarOrNDArray::Scalar(object),
+        }
+    }
+
+    /// Get the underlying [`BasicValueEnum<'ctx>`] of this [`ScalarOrNDArray`].
+    #[must_use]
+    pub fn to_basic_value_enum(self) -> BasicValueEnum<'ctx> {
+        match self {
+            ScalarOrNDArray::Scalar(scalar) => scalar.value,
+            ScalarOrNDArray::NDArray(ndarray) => ndarray.instance.value.as_basic_value_enum(),
+        }
+    }
+
+    /// Convert this [`ScalarOrNDArray`] to an ndarray - behaves like `np.asarray`.
+    /// - If this is an ndarray, the ndarray is returned.
+    /// - If this is a scalar, this function returns new ndarray created with [`NDArrayObject::make_unsized`].
+    pub fn to_ndarray<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> NDArrayObject<'ctx> {
+        match self {
+            ScalarOrNDArray::NDArray(ndarray) => *ndarray,
+            ScalarOrNDArray::Scalar(scalar) => NDArrayObject::make_unsized(generator, ctx, *scalar),
+        }
+    }
+
+    /// Get the dtype of the ndarray created if this were called with [`ScalarOrNDArray::to_ndarray`].
+    #[must_use]
+    pub fn get_dtype(&self) -> Type {
+        match self {
+            ScalarOrNDArray::NDArray(ndarray) => ndarray.dtype,
+            ScalarOrNDArray::Scalar(scalar) => scalar.ty,
+        }
+    }
+}
+
+/// An helper enum specifying how a function should produce its output.
+///
+/// Many functions in NumPy has an optional `out` parameter (e.g., `matmul`). If `out` is specified
+/// with an ndarray, the result of a function will be written to `out`. If `out` is not specified, a function will
+/// create a new ndarray and store the result in it.
+#[derive(Debug, Clone, Copy)]
+pub enum NDArrayOut<'ctx> {
+    /// Tell a function should create a new ndarray with the expected element type `dtype`.
+    NewNDArray { dtype: Type },
+    /// Tell a function to write the result to `ndarray`.
+    WriteToNDArray { ndarray: NDArrayObject<'ctx> },
+}
+
+impl<'ctx> NDArrayOut<'ctx> {
+    /// Get the dtype of this output.
+    #[must_use]
+    pub fn get_dtype(&self) -> Type {
+        match self {
+            NDArrayOut::NewNDArray { dtype } => *dtype,
+            NDArrayOut::WriteToNDArray { ndarray } => ndarray.dtype,
+        }
+    }
+}
+
+/// A version of [`call_nac3_ndarray_set_strides_by_shape`] in Rust.
+///
+/// This function is used generating strides for globally defined contiguous ndarrays.
+#[must_use]
+pub fn make_contiguous_strides(itemsize: u64, ndims: u64, shape: &[u64]) -> Vec<u64> {
+    let mut strides = Vec::with_capacity(ndims as usize);
+    let mut stride_product = 1u64;
+    for i in 0..ndims {
+        let axis = ndims - i - 1;
+        strides[axis as usize] = stride_product * itemsize;
+        stride_product *= shape[axis as usize];
+    }
+    strides
+}

nac3core/src/codegen/object/ndarray/nditer.rs

@@ -0,0 +1,178 @@
+use inkwell::{types::BasicType, values::PointerValue, AddressSpace};
+
+use super::NDArrayObject;
+use crate::codegen::{
+    irrt::{call_nac3_nditer_has_element, call_nac3_nditer_initialize, call_nac3_nditer_next},
+    model::*,
+    object::any::AnyObject,
+    stmt::{gen_for_callback, BreakContinueHooks},
+    CodeGenContext, CodeGenerator,
+};
+
+/// Fields of [`NDIter`]
+pub struct NDIterFields<'ctx, F: FieldTraversal<'ctx>> {
+    pub ndims: F::Output<Int<SizeT>>,
+    pub shape: F::Output<Ptr<Int<SizeT>>>,
+    pub strides: F::Output<Ptr<Int<SizeT>>>,
+
+    pub indices: F::Output<Ptr<Int<SizeT>>>,
+    pub nth: F::Output<Int<SizeT>>,
+    pub element: F::Output<Ptr<Int<Byte>>>,
+
+    pub size: F::Output<Int<SizeT>>,
+}
+
+/// An IRRT helper structure used to iterate through an ndarray.
+#[derive(Debug, Clone, Copy, Default)]
+pub struct NDIter;
+
+impl<'ctx> StructKind<'ctx> for NDIter {
+    type Fields<F: FieldTraversal<'ctx>> = NDIterFields<'ctx, F>;
+
+    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            ndims: traversal.add_auto("ndims"),
+            shape: traversal.add_auto("shape"),
+            strides: traversal.add_auto("strides"),
+
+            indices: traversal.add_auto("indices"),
+            nth: traversal.add_auto("nth"),
+            element: traversal.add_auto("element"),
+
+            size: traversal.add_auto("size"),
+        }
+    }
+}
+
+/// A helper structure with a convenient interface to interact with [`NDIter`].
+#[derive(Debug, Clone)]
+pub struct NDIterHandle<'ctx> {
+    instance: Instance<'ctx, Ptr<Struct<NDIter>>>,
+    /// The ndarray this [`NDIter`] to iterating over.
+    ndarray: NDArrayObject<'ctx>,
+    /// The current indices of [`NDIter`].
+    indices: Instance<'ctx, Ptr<Int<SizeT>>>,
+}
+
+impl<'ctx> NDIterHandle<'ctx> {
+    /// Allocate an [`NDIter`] that iterates through an ndarray.
+    pub fn new<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndarray: NDArrayObject<'ctx>,
+    ) -> Self {
+        let nditer = Struct(NDIter).alloca(generator, ctx);
+        let ndims = ndarray.ndims_llvm(generator, ctx.ctx);
+
+        // The caller has the responsibility to allocate 'indices' for `NDIter`.
+        let indices = Int(SizeT).array_alloca(generator, ctx, ndims.value);
+        call_nac3_nditer_initialize(generator, ctx, nditer, ndarray.instance, indices);
+
+        NDIterHandle { ndarray, instance: nditer, indices }
+    }
+
+    /// Is the current iteration valid?
+    ///
+    /// If true, then `element`, `indices` and `nth` contain details about the current element.
+    ///
+    /// If `ndarray` is unsized, this returns true only for the first iteration.
+    /// If `ndarray` is 0-sized, this always returns false.
+    #[must_use]
+    pub fn has_element<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<Bool>> {
+        call_nac3_nditer_has_element(generator, ctx, self.instance)
+    }
+
+    /// Go to the next element. If `has_element()` is false, then this has undefined behavior.
+    ///
+    /// If `ndarray` is unsized, this can only be called once.
+    /// If `ndarray` is 0-sized, this can never be called.
+    pub fn next<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) {
+        call_nac3_nditer_next(generator, ctx, self.instance);
+    }
+
+    /// Get pointer to the current element.
+    #[must_use]
+    pub fn get_pointer<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> PointerValue<'ctx> {
+        let elem_ty = ctx.get_llvm_type(generator, self.ndarray.dtype);
+
+        let p = self.instance.get(generator, ctx, |f| f.element);
+        ctx.builder
+            .build_pointer_cast(p.value, elem_ty.ptr_type(AddressSpace::default()), "element")
+            .unwrap()
+    }
+
+    /// Get the value of the current element.
+    #[must_use]
+    pub fn get_scalar<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> AnyObject<'ctx> {
+        let p = self.get_pointer(generator, ctx);
+        let value = ctx.builder.build_load(p, "value").unwrap();
+        AnyObject { ty: self.ndarray.dtype, value }
+    }
+
+    /// Get the index of the current element if this ndarray were a flat ndarray.
+    #[must_use]
+    pub fn get_index<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<SizeT>> {
+        self.instance.get(generator, ctx, |f| f.nth)
+    }
+
+    /// Get the indices of the current element.
+    #[must_use]
+    pub fn get_indices(&self) -> Instance<'ctx, Ptr<Int<SizeT>>> {
+        self.indices
+    }
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Iterate through every element in the ndarray.
+    ///
+    /// `body` has access to [`BreakContinueHooks`] to short-circuit and [`NDIterHandle`] to
+    /// get properties of the current iteration (e.g., the current element, indices, etc.)
+    pub fn foreach<'a, G, F>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        body: F,
+    ) -> Result<(), String>
+    where
+        G: CodeGenerator + ?Sized,
+        F: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            BreakContinueHooks<'ctx>,
+            NDIterHandle<'ctx>,
+        ) -> Result<(), String>,
+    {
+        gen_for_callback(
+            generator,
+            ctx,
+            Some("ndarray_foreach"),
+            |generator, ctx| Ok(NDIterHandle::new(generator, ctx, *self)),
+            |generator, ctx, nditer| Ok(nditer.has_element(generator, ctx).value),
+            |generator, ctx, hooks, nditer| body(generator, ctx, hooks, nditer),
+            |generator, ctx, nditer| {
+                nditer.next(generator, ctx);
+                Ok(())
+            },
+        )
+    }
+}

nac3core/src/codegen/object/ndarray/shape_util.rs

@@ -0,0 +1,104 @@
+use crate::{
+    codegen::{
+        model::*,
+        object::{any::AnyObject, list::ListObject, tuple::TupleObject},
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::TypeEnum,
+};
+use util::gen_for_model;
+
+/// Parse a NumPy-like "int sequence" input and return the int sequence as an array and its length.
+///
+/// * `sequence` - The `sequence` parameter.
+/// * `sequence_ty` - The typechecker type of `sequence`
+///
+/// The `sequence` argument type may only be one of the following:
+///   1. A list of `int32`;   e.g., `np.empty([600, 800, 3])`
+///   2. A tuple of `int32`;  e.g., `np.empty((600, 800, 3))`
+///   3. A scalar `int32`;    e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
+///
+/// All `int32` values will be sign-extended to `SizeT`.
+pub fn parse_numpy_int_sequence<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    input_sequence: AnyObject<'ctx>,
+) -> (Instance<'ctx, Int<SizeT>>, Instance<'ctx, Ptr<Int<SizeT>>>) {
+    let zero = Int(SizeT).const_0(generator, ctx.ctx);
+    let one = Int(SizeT).const_1(generator, ctx.ctx);
+
+    // The result `list` to return.
+    match &*ctx.unifier.get_ty(input_sequence.ty) {
+        TypeEnum::TObj { obj_id, .. }
+            if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
+        {
+            // 1. A list of `int32`; e.g., `np.empty([600, 800, 3])`
+
+            // Check `input_sequence`
+            let input_sequence = ListObject::from_object(generator, ctx, input_sequence);
+
+            let len = input_sequence.instance.get(generator, ctx, |f| f.len);
+            let result = Int(SizeT).array_alloca(generator, ctx, len.value);
+
+            // Load all the `int32`s from the input_sequence, cast them to `SizeT`, and store them into `result`
+            gen_for_model(generator, ctx, zero, len, one, |generator, ctx, _hooks, i| {
+                // Load the i-th int32 in the input sequence
+                let int = input_sequence
+                    .instance
+                    .get(generator, ctx, |f| f.items)
+                    .get_index(generator, ctx, i.value)
+                    .value
+                    .into_int_value();
+
+                // Cast to SizeT
+                let int = Int(SizeT).s_extend_or_bit_cast(generator, ctx, int);
+
+                // Store
+                result.set_index(ctx, i.value, int);
+
+                Ok(())
+            })
+            .unwrap();
+
+            (len, result)
+        }
+        TypeEnum::TTuple { .. } => {
+            // 2. A tuple of ints; e.g., `np.empty((600, 800, 3))`
+
+            let input_sequence = TupleObject::from_object(ctx, input_sequence);
+
+            let len = input_sequence.len(generator, ctx);
+
+            let result = Int(SizeT).array_alloca(generator, ctx, len.value);
+
+            for i in 0..input_sequence.num_elements() {
+                // Get the i-th element off of the tuple and load it into `result`.
+                let int = input_sequence.index(ctx, i).value.into_int_value();
+                let int = Int(SizeT).s_extend_or_bit_cast(generator, ctx, int);
+
+                result.set_index_const(ctx, i64::try_from(i).unwrap(), int);
+            }
+
+            (len, result)
+        }
+        TypeEnum::TObj { obj_id, .. }
+            if *obj_id == ctx.primitives.int32.obj_id(&ctx.unifier).unwrap() =>
+        {
+            // 3. A scalar int; e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
+            let input_int = input_sequence.value.into_int_value();
+
+            let len = Int(SizeT).const_1(generator, ctx.ctx);
+            let result = Int(SizeT).array_alloca(generator, ctx, len.value);
+            let int = Int(SizeT).s_extend_or_bit_cast(generator, ctx, input_int);
+
+            // Storing into result[0]
+            result.store(ctx, int);
+
+            (len, result)
+        }
+        _ => panic!(
+            "encountered unknown sequence type: {}",
+            ctx.unifier.stringify(input_sequence.ty)
+        ),
+    }
+}

nac3core/src/codegen/object/ndarray/view.rs

@@ -0,0 +1,118 @@
+use super::{indexing::RustNDIndex, NDArrayObject};
+use crate::codegen::{
+    irrt::{call_nac3_ndarray_reshape_resolve_and_check_new_shape, call_nac3_ndarray_transpose},
+    model::*,
+    CodeGenContext, CodeGenerator,
+};
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Make sure the ndarray is at least `ndmin`-dimensional.
+    ///
+    /// If this ndarray's `ndims` is less than `ndmin`, a view is created on this with 1s prepended to the shape.
+    /// If this ndarray's `ndims` is not less than `ndmin`, this function does nothing and return this ndarray.
+    #[must_use]
+    pub fn atleast_nd<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndmin: u64,
+    ) -> Self {
+        if self.ndims < ndmin {
+            // Extend the dimensions with np.newaxis.
+            let mut indices = vec![];
+            for _ in self.ndims..ndmin {
+                indices.push(RustNDIndex::NewAxis);
+            }
+            indices.push(RustNDIndex::Ellipsis);
+            self.index(generator, ctx, &indices)
+        } else {
+            *self
+        }
+    }
+
+    /// Create a reshaped view on this ndarray like `np.reshape()`.
+    ///
+    /// If there is a `-1` in `new_shape`, it will be resolved; `new_shape` would **NOT** be modified as a result.
+    ///
+    /// If reshape without copying is impossible, this function will allocate a new ndarray and copy contents.
+    ///
+    /// * `new_ndims` - The number of dimensions of `new_shape` as a [`Type`].
+    /// * `new_shape` - The target shape to do `np.reshape()`.
+    #[must_use]
+    pub fn reshape_or_copy<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        new_ndims: u64,
+        new_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) -> Self {
+        // TODO: The current criterion for whether to do a full copy or not is by checking `is_c_contiguous`,
+        // but this is not optimal - there are cases when the ndarray is not contiguous but could be reshaped
+        // without copying data. Look into how numpy does it.
+
+        let current_bb = ctx.builder.get_insert_block().unwrap();
+        let then_bb = ctx.ctx.insert_basic_block_after(current_bb, "then_bb");
+        let else_bb = ctx.ctx.insert_basic_block_after(then_bb, "else_bb");
+        let end_bb = ctx.ctx.insert_basic_block_after(else_bb, "end_bb");
+
+        let dst_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, new_ndims);
+        dst_ndarray.copy_shape_from_array(generator, ctx, new_shape);
+
+        // Reolsve negative indices
+        let size = self.size(generator, ctx);
+        let dst_ndims = dst_ndarray.ndims_llvm(generator, ctx.ctx);
+        let dst_shape = dst_ndarray.instance.get(generator, ctx, |f| f.shape);
+        call_nac3_ndarray_reshape_resolve_and_check_new_shape(
+            generator, ctx, size, dst_ndims, dst_shape,
+        );
+
+        let is_c_contiguous = self.is_c_contiguous(generator, ctx);
+        ctx.builder.build_conditional_branch(is_c_contiguous.value, then_bb, else_bb).unwrap();
+
+        // Inserting into then_bb: reshape is possible without copying
+        ctx.builder.position_at_end(then_bb);
+        dst_ndarray.set_strides_contiguous(generator, ctx);
+        dst_ndarray.instance.set(ctx, |f| f.data, self.instance.get(generator, ctx, |f| f.data));
+        ctx.builder.build_unconditional_branch(end_bb).unwrap();
+
+        // Inserting into else_bb: reshape is impossible without copying
+        ctx.builder.position_at_end(else_bb);
+        dst_ndarray.create_data(generator, ctx);
+        dst_ndarray.copy_data_from(generator, ctx, *self);
+        ctx.builder.build_unconditional_branch(end_bb).unwrap();
+
+        // Reposition for continuation
+        ctx.builder.position_at_end(end_bb);
+
+        dst_ndarray
+    }
+
+    /// Create a transposed view on this ndarray like `np.transpose(<ndarray>, <axes> = None)`.
+    /// * `axes` - If specified, should be an array of the permutation (negative indices are **allowed**).
+    #[must_use]
+    pub fn transpose<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        axes: Option<Instance<'ctx, Ptr<Int<SizeT>>>>,
+    ) -> Self {
+        // Define models
+        let transposed_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, self.ndims);
+
+        let num_axes = self.ndims_llvm(generator, ctx.ctx);
+
+        // `axes = nullptr` if `axes` is unspecified.
+        let axes = axes.unwrap_or_else(|| Ptr(Int(SizeT)).nullptr(generator, ctx.ctx));
+
+        call_nac3_ndarray_transpose(
+            generator,
+            ctx,
+            self.instance,
+            transposed_ndarray.instance,
+            num_axes,
+            axes,
+        );
+
+        transposed_ndarray
+    }
+}

nac3core/src/codegen/object/tuple.rs

@@ -0,0 +1,98 @@
+use inkwell::values::StructValue;
+use itertools::Itertools;
+
+use super::any::AnyObject;
+use crate::{
+    codegen::{model::*, CodeGenContext, CodeGenerator},
+    typecheck::typedef::{Type, TypeEnum},
+};
+
+/// A NAC3 tuple object.
+///
+/// NOTE: This struct has no copy trait.
+#[derive(Debug, Clone)]
+pub struct TupleObject<'ctx> {
+    /// The type of the tuple.
+    pub tys: Vec<Type>,
+    /// The underlying LLVM struct value of this tuple.
+    pub value: StructValue<'ctx>,
+}
+
+impl<'ctx> TupleObject<'ctx> {
+    pub fn from_object(ctx: &mut CodeGenContext<'ctx, '_>, object: AnyObject<'ctx>) -> Self {
+        // TODO: Keep `is_vararg_ctx` from TTuple?
+
+        // Sanity check on object type.
+        let TypeEnum::TTuple { ty: tys, .. } = &*ctx.unifier.get_ty(object.ty) else {
+            panic!(
+                "Expected type to be a TypeEnum::TTuple, got {}",
+                ctx.unifier.stringify(object.ty)
+            );
+        };
+
+        // Check number of fields
+        let value = object.value.into_struct_value();
+        let value_num_fields = value.get_type().count_fields() as usize;
+        assert!(
+            value_num_fields == tys.len(),
+            "Tuple type has {} item(s), but the LLVM struct value has {} field(s)",
+            tys.len(),
+            value_num_fields
+        );
+
+        TupleObject { tys: tys.clone(), value }
+    }
+
+    /// Convenience function. Create a [`TupleObject`] from an iterator of objects.
+    pub fn from_objects<I, G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        objects: I,
+    ) -> Self
+    where
+        I: IntoIterator<Item = AnyObject<'ctx>>,
+    {
+        let (values, tys): (Vec<_>, Vec<_>) =
+            objects.into_iter().map(|object| (object.value, object.ty)).unzip();
+
+        let llvm_tys = tys.iter().map(|ty| ctx.get_llvm_type(generator, *ty)).collect_vec();
+        let llvm_tuple_ty = ctx.ctx.struct_type(&llvm_tys, false);
+
+        let pllvm_tuple = ctx.builder.build_alloca(llvm_tuple_ty, "tuple").unwrap();
+        for (i, val) in values.into_iter().enumerate() {
+            let pval = ctx.builder.build_struct_gep(pllvm_tuple, i as u32, "value").unwrap();
+            ctx.builder.build_store(pval, val).unwrap();
+        }
+
+        let value = ctx.builder.build_load(pllvm_tuple, "").unwrap().into_struct_value();
+        TupleObject { tys, value }
+    }
+
+    #[must_use]
+    pub fn num_elements(&self) -> usize {
+        self.tys.len()
+    }
+
+    /// Get the `len()` of this tuple.
+    #[must_use]
+    pub fn len<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<SizeT>> {
+        Int(SizeT).const_int(generator, ctx.ctx, self.num_elements() as u64, false)
+    }
+
+    /// Get the `i`-th (0-based) object in this tuple.
+    pub fn index(&self, ctx: &mut CodeGenContext<'ctx, '_>, i: usize) -> AnyObject<'ctx> {
+        assert!(
+            i < self.num_elements(),
+            "Tuple object with length {} have index {i}",
+            self.num_elements()
+        );
+
+        let value = ctx.builder.build_extract_value(self.value, i as u32, "tuple[{i}]").unwrap();
+        let ty = self.tys[i];
+        AnyObject { ty, value }
+    }
+}

nac3core/src/codegen/object/utils/mod.rs

@@ -0,0 +1 @@
+pub mod slice;

nac3core/src/codegen/object/utils/slice.rs

@@ -0,0 +1,125 @@
+use crate::codegen::{model::*, CodeGenContext, CodeGenerator};
+
+/// Fields of [`Slice`]
+#[derive(Debug, Clone)]
+pub struct SliceFields<'ctx, F: FieldTraversal<'ctx>, N: IntKind<'ctx>> {
+    pub start_defined: F::Output<Int<Bool>>,
+    pub start: F::Output<Int<N>>,
+    pub stop_defined: F::Output<Int<Bool>>,
+    pub stop: F::Output<Int<N>>,
+    pub step_defined: F::Output<Int<Bool>>,
+    pub step: F::Output<Int<N>>,
+}
+
+/// An IRRT representation of an (unresolved) slice.
+#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
+pub struct Slice<N>(pub N);
+
+impl<'ctx, N: IntKind<'ctx>> StructKind<'ctx> for Slice<N> {
+    type Fields<F: FieldTraversal<'ctx>> = SliceFields<'ctx, F, N>;
+
+    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            start_defined: traversal.add_auto("start_defined"),
+            start: traversal.add("start", Int(self.0)),
+            stop_defined: traversal.add_auto("stop_defined"),
+            stop: traversal.add("stop", Int(self.0)),
+            step_defined: traversal.add_auto("step_defined"),
+            step: traversal.add("step", Int(self.0)),
+        }
+    }
+}
+
+/// A Rust structure that has [`Slice`] utilities and looks like a [`Slice`] but
+/// `start`, `stop` and `step` are held by LLVM registers only and possibly
+/// [`Option::None`] if unspecified.
+#[derive(Debug, Clone)]
+pub struct RustSlice<'ctx, N: IntKind<'ctx>> {
+    // It is possible that `start`, `stop`, and `step` are all `None`.
+    // We need to know the `int_kind` even when that is the case.
+    pub int_kind: N,
+    pub start: Option<Instance<'ctx, Int<N>>>,
+    pub stop: Option<Instance<'ctx, Int<N>>>,
+    pub step: Option<Instance<'ctx, Int<N>>>,
+}
+
+impl<'ctx, N: IntKind<'ctx>> RustSlice<'ctx, N> {
+    /// Write the contents to an LLVM [`Slice`].
+    pub fn write_to_slice<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        dst_slice_ptr: Instance<'ctx, Ptr<Struct<Slice<N>>>>,
+    ) {
+        let false_ = Int(Bool).const_false(generator, ctx.ctx);
+        let true_ = Int(Bool).const_true(generator, ctx.ctx);
+
+        match self.start {
+            Some(start) => {
+                dst_slice_ptr.gep(ctx, |f| f.start_defined).store(ctx, true_);
+                dst_slice_ptr.gep(ctx, |f| f.start).store(ctx, start);
+            }
+            None => dst_slice_ptr.gep(ctx, |f| f.start_defined).store(ctx, false_),
+        }
+
+        match self.stop {
+            Some(stop) => {
+                dst_slice_ptr.gep(ctx, |f| f.stop_defined).store(ctx, true_);
+                dst_slice_ptr.gep(ctx, |f| f.stop).store(ctx, stop);
+            }
+            None => dst_slice_ptr.gep(ctx, |f| f.stop_defined).store(ctx, false_),
+        }
+
+        match self.step {
+            Some(step) => {
+                dst_slice_ptr.gep(ctx, |f| f.step_defined).store(ctx, true_);
+                dst_slice_ptr.gep(ctx, |f| f.step).store(ctx, step);
+            }
+            None => dst_slice_ptr.gep(ctx, |f| f.step_defined).store(ctx, false_),
+        }
+    }
+}
+
+pub mod util {
+    use nac3parser::ast::Expr;
+
+    use crate::{
+        codegen::{model::*, CodeGenContext, CodeGenerator},
+        typecheck::typedef::Type,
+    };
+
+    use super::RustSlice;
+
+    /// Generate LLVM IR for an [`ExprKind::Slice`] and convert it into a [`RustSlice`].
+    #[allow(clippy::type_complexity)]
+    pub fn gen_slice<'ctx, G: CodeGenerator>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        lower: &Option<Box<Expr<Option<Type>>>>,
+        upper: &Option<Box<Expr<Option<Type>>>>,
+        step: &Option<Box<Expr<Option<Type>>>>,
+    ) -> Result<RustSlice<'ctx, Int32>, String> {
+        let mut help = |value_expr: &Option<Box<Expr<Option<Type>>>>| -> Result<_, String> {
+            Ok(match value_expr {
+                None => None,
+                Some(value_expr) => {
+                    let value_expr = generator
+                        .gen_expr(ctx, value_expr)?
+                        .unwrap()
+                        .to_basic_value_enum(ctx, generator, ctx.primitives.int32)?;
+
+                    let value_expr =
+                        Int(Int32).check_value(generator, ctx.ctx, value_expr).unwrap();
+
+                    Some(value_expr)
+                }
+            })
+        };
+
+        let start = help(lower)?;
+        let stop = help(upper)?;
+        let step = help(step)?;
+
+        Ok(RustSlice { int_kind: Int32, start, stop, step })
+    }
+}

nac3core/src/codegen/stmt.rs

@@ -12,14 +12,16 @@ use nac3parser::ast::{
 };
 
 use super::{
+    classes::{ArrayLikeIndexer, ArraySliceValue, ListValue, RangeValue},
     expr::{destructure_range, gen_binop_expr},
     gen_in_range_check,
     irrt::{handle_slice_indices, list_slice_assignment},
     macros::codegen_unreachable,
-    types::ndarray::NDArrayType,
+    object::{
-    values::{
+        any::AnyObject,
-        ndarray::{RustNDIndex, ScalarOrNDArray},
+        ndarray::{
-        ArrayLikeIndexer, ArraySliceValue, ListValue, ProxyValue, RangeValue,
+            indexing::util::gen_ndarray_subscript_ndindices, NDArrayObject, ScalarOrNDArray,
+        },
     },
     CodeGenContext, CodeGenerator,
 };
@@ -314,7 +316,7 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
                 .unwrap()
                 .to_basic_value_enum(ctx, generator, target_ty)?
                 .into_pointer_value();
-            let target = ListValue::from_pointer_value(target, llvm_usize, None);
+            let target = ListValue::from_ptr_val(target, llvm_usize, None);
 
             if let ExprKind::Slice { .. } = &key.node {
                 // Handle assigning to a slice
@@ -335,7 +337,7 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
 
                 let value =
                     value.to_basic_value_enum(ctx, generator, value_ty)?.into_pointer_value();
-                let value = ListValue::from_pointer_value(value, llvm_usize, None);
+                let value = ListValue::from_ptr_val(value, llvm_usize, None);
 
                 let target_item_ty = ctx.get_llvm_type(generator, target_item_ty);
                 let Some(src_ind) = handle_slice_indices(
@@ -420,42 +422,37 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
                 .gen_expr(ctx, target)?
                 .unwrap()
                 .to_basic_value_enum(ctx, generator, target_ty)?;
+            let target = AnyObject { value: target, ty: target_ty };
 
             // Process key
-            let key = RustNDIndex::from_subscript_expr(generator, ctx, key)?;
+            let key = gen_ndarray_subscript_ndindices(generator, ctx, key)?;
 
             // Process value
             let value = value.to_basic_value_enum(ctx, generator, value_ty)?;
+            let value = AnyObject { value, ty: value_ty };
 
-            // Reference code:
+            /*
-            // ```python
+                Reference code:
-            // target = target[key]
+                ```python
-            // value = np.asarray(value)
+                target = target[key]
-            //
+                value = np.asarray(value)
-            // shape = np.broadcast_shape((target, value))
-            //
-            // target = np.broadcast_to(target, shape)
-            // value = np.broadcast_to(value, shape)
-            //
-            // # ...and finally copy 1-1 from value to target.
-            // ```
 
-            let target = NDArrayType::from_unifier_type(generator, ctx, target_ty)
+                shape = np.broadcast_shape((target, value))
-                .map_value(target.into_pointer_value(), None);
+
+                target = np.broadcast_to(target, shape)
+                value = np.broadcast_to(value, shape)
+
+                ...and finally copy 1-1 from value to target.
+                ```
+            */
+
+            let target = NDArrayObject::from_object(generator, ctx, target);
             let target = target.index(generator, ctx, &key);
 
-            let value = ScalarOrNDArray::from_value(generator, ctx, (value_ty, value))
+            let value =
-                .to_ndarray(generator, ctx);
+                ScalarOrNDArray::split_object(generator, ctx, value).to_ndarray(generator, ctx);
 
-            let broadcast_ndims =
+            let broadcast_result = NDArrayObject::broadcast(generator, ctx, &[target, value]);
-                [target.get_type().ndims(), value.get_type().ndims()].into_iter().max().unwrap();
-            let broadcast_result = NDArrayType::new(
-                generator,
-                ctx.ctx,
-                value.get_type().element_type(),
-                broadcast_ndims,
-            )
-            .broadcast(generator, ctx, &[target, value]);
 
             let target = broadcast_result.ndarrays[0];
             let value = broadcast_result.ndarrays[1];
@@ -512,8 +509,7 @@ pub fn gen_for<G: CodeGenerator>(
         TypeEnum::TObj { obj_id, .. }
             if *obj_id == ctx.primitives.range.obj_id(&ctx.unifier).unwrap() =>
         {
-            let iter_val =
+            let iter_val = RangeValue::from_ptr_val(iter_val.into_pointer_value(), Some("range"));
-                RangeValue::from_pointer_value(iter_val.into_pointer_value(), Some("range"));
             // Internal variable for loop; Cannot be assigned
             let i = generator.gen_var_alloc(ctx, int32.into(), Some("for.i.addr"))?;
             // Variable declared in "target" expression of the loop; Can be reassigned *or* shadowed

nac3core/src/codegen/test.rs

@@ -16,8 +16,8 @@ use nac3parser::{
 use parking_lot::RwLock;
 
 use super::{
+    classes::{ListType, ProxyType, RangeType},
     concrete_type::ConcreteTypeStore,
-    types::{ndarray::NDArrayType, ListType, ProxyType, RangeType},
     CodeGenContext, CodeGenLLVMOptions, CodeGenTargetMachineOptions, CodeGenTask, CodeGenerator,
     DefaultCodeGenerator, WithCall, WorkerRegistry,
 };
@@ -36,6 +36,7 @@ use crate::{
 struct Resolver {
     id_to_type: HashMap<StrRef, Type>,
     id_to_def: RwLock<HashMap<StrRef, DefinitionId>>,
+    class_names: HashMap<StrRef, Type>,
 }
 
 impl Resolver {
@@ -103,9 +104,11 @@ fn test_primitives() {
     let top_level = Arc::new(composer.make_top_level_context());
     unifier.top_level = Some(top_level.clone());
 
-    let resolver =
+    let resolver = Arc::new(Resolver {
-        Arc::new(Resolver { id_to_type: HashMap::new(), id_to_def: RwLock::new(HashMap::new()) })
+        id_to_type: HashMap::new(),
-            as Arc<dyn SymbolResolver + Send + Sync>;
+        id_to_def: RwLock::new(HashMap::new()),
+        class_names: HashMap::default(),
+    }) as Arc<dyn SymbolResolver + Send + Sync>;
 
     let threads = vec![DefaultCodeGenerator::new("test".into(), 32).into()];
     let signature = FunSignature {
@@ -295,7 +298,11 @@ fn test_simple_call() {
         loc: None,
     })));
 
-    let resolver = Resolver { id_to_type: HashMap::new(), id_to_def: RwLock::new(HashMap::new()) };
+    let resolver = Resolver {
+        id_to_type: HashMap::new(),
+        id_to_def: RwLock::new(HashMap::new()),
+        class_names: HashMap::default(),
+    };
     resolver.add_id_def("foo".into(), DefinitionId(foo_id));
     let resolver = Arc::new(resolver) as Arc<dyn SymbolResolver + Send + Sync>;
 
@@ -445,7 +452,7 @@ fn test_classes_list_type_new() {
     let llvm_usize = generator.get_size_type(&ctx);
 
     let llvm_list = ListType::new(&generator, &ctx, llvm_i32.into());
-    assert!(ListType::is_representable(llvm_list.as_base_type(), llvm_usize).is_ok());
+    assert!(ListType::is_type(llvm_list.as_base_type(), llvm_usize).is_ok());
 }
 
 #[test]
@@ -453,17 +460,5 @@ fn test_classes_range_type_new() {
     let ctx = inkwell::context::Context::create();
 
     let llvm_range = RangeType::new(&ctx);
-    assert!(RangeType::is_representable(llvm_range.as_base_type()).is_ok());
+    assert!(RangeType::is_type(llvm_range.as_base_type()).is_ok());
-}
-
-#[test]
-fn test_classes_ndarray_type_new() {
-    let ctx = inkwell::context::Context::create();
-    let generator = DefaultCodeGenerator::new(String::new(), 64);
-
-    let llvm_i32 = ctx.i32_type();
-    let llvm_usize = generator.get_size_type(&ctx);
-
-    let llvm_ndarray = NDArrayType::new(&generator, &ctx, llvm_i32.into(), 2);
-    assert!(NDArrayType::is_representable(llvm_ndarray.as_base_type(), llvm_usize).is_ok());
 }

nac3core/src/codegen/types/list.rs

@@ -1,357 +0,0 @@
-use inkwell::{
-    context::{AsContextRef, Context},
-    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
-    values::{IntValue, PointerValue},
-    AddressSpace, IntPredicate, OptimizationLevel,
-};
-use itertools::Itertools;
-
-use nac3core_derive::StructFields;
-
-use super::ProxyType;
-use crate::{
-    codegen::{
-        types::structure::{
-            check_struct_type_matches_fields, FieldIndexCounter, StructField, StructFields,
-        },
-        values::{ListValue, ProxyValue},
-        CodeGenContext, CodeGenerator,
-    },
-    typecheck::typedef::{iter_type_vars, Type, TypeEnum},
-};
-
-/// Proxy type for a `list` type in LLVM.
-#[derive(Debug, PartialEq, Eq, Clone, Copy)]
-pub struct ListType<'ctx> {
-    ty: PointerType<'ctx>,
-    item: Option<BasicTypeEnum<'ctx>>,
-    llvm_usize: IntType<'ctx>,
-}
-
-#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
-pub struct ListStructFields<'ctx> {
-    /// Array pointer to content.
-    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
-    pub items: StructField<'ctx, PointerValue<'ctx>>,
-
-    /// Number of items in the array.
-    #[value_type(usize)]
-    pub len: StructField<'ctx, IntValue<'ctx>>,
-}
-
-impl<'ctx> ListStructFields<'ctx> {
-    #[must_use]
-    pub fn new_typed(item: BasicTypeEnum<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
-        let mut counter = FieldIndexCounter::default();
-
-        ListStructFields {
-            items: StructField::create(
-                &mut counter,
-                "items",
-                item.ptr_type(AddressSpace::default()),
-            ),
-            len: StructField::create(&mut counter, "len", llvm_usize),
-        }
-    }
-}
-
-impl<'ctx> ListType<'ctx> {
-    /// Checks whether `llvm_ty` represents a `list` type, returning [Err] if it does not.
-    pub fn is_representable(
-        llvm_ty: PointerType<'ctx>,
-        llvm_usize: IntType<'ctx>,
-    ) -> Result<(), String> {
-        let ctx = llvm_ty.get_context();
-
-        let llvm_ty = llvm_ty.get_element_type();
-        let AnyTypeEnum::StructType(llvm_ty) = llvm_ty else {
-            return Err(format!("Expected struct type for `list` type, got {llvm_ty}"));
-        };
-
-        let fields = ListStructFields::new(ctx, llvm_usize);
-
-        check_struct_type_matches_fields(
-            fields,
-            llvm_ty,
-            "list",
-            &[(fields.items.name(), &|ty| {
-                if ty.is_pointer_type() {
-                    Ok(())
-                } else {
-                    Err(format!("Expected T* for `list.items`, got {ty}"))
-                }
-            })],
-        )
-    }
-
-    /// Returns an instance of [`StructFields`] containing all field accessors for this type.
-    #[must_use]
-    fn fields(item: BasicTypeEnum<'ctx>, llvm_usize: IntType<'ctx>) -> ListStructFields<'ctx> {
-        ListStructFields::new_typed(item, llvm_usize)
-    }
-
-    /// See [`ListType::fields`].
-    // TODO: Move this into e.g. StructProxyType
-    #[must_use]
-    pub fn get_fields(&self, _ctx: &impl AsContextRef<'ctx>) -> ListStructFields<'ctx> {
-        Self::fields(self.item.unwrap_or(self.llvm_usize.into()), self.llvm_usize)
-    }
-
-    /// Creates an LLVM type corresponding to the expected structure of a `List`.
-    #[must_use]
-    fn llvm_type(
-        ctx: &'ctx Context,
-        element_type: Option<BasicTypeEnum<'ctx>>,
-        llvm_usize: IntType<'ctx>,
-    ) -> PointerType<'ctx> {
-        let element_type = element_type.unwrap_or(llvm_usize.into());
-
-        let field_tys =
-            Self::fields(element_type, llvm_usize).into_iter().map(|field| field.1).collect_vec();
-
-        ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
-    }
-
-    /// Creates an instance of [`ListType`].
-    #[must_use]
-    pub fn new<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        element_type: BasicTypeEnum<'ctx>,
-    ) -> Self {
-        let llvm_usize = generator.get_size_type(ctx);
-        let llvm_list = Self::llvm_type(ctx, Some(element_type), llvm_usize);
-
-        Self { ty: llvm_list, item: Some(element_type), llvm_usize }
-    }
-
-    /// Creates an instance of [`ListType`] with an unknown element type.
-    #[must_use]
-    pub fn new_untyped<G: CodeGenerator + ?Sized>(generator: &G, ctx: &'ctx Context) -> Self {
-        let llvm_usize = generator.get_size_type(ctx);
-        let llvm_list = Self::llvm_type(ctx, None, llvm_usize);
-
-        Self { ty: llvm_list, item: None, llvm_usize }
-    }
-
-    /// Creates an [`ListType`] from a [unifier type][Type].
-    #[must_use]
-    pub fn from_unifier_type<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        ty: Type,
-    ) -> Self {
-        // Check unifier type and extract `item_type`
-        let elem_type = match &*ctx.unifier.get_ty_immutable(ty) {
-            TypeEnum::TObj { obj_id, params, .. }
-                if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
-            {
-                iter_type_vars(params).next().unwrap().ty
-            }
-
-            _ => panic!("Expected `list` type, but got {}", ctx.unifier.stringify(ty)),
-        };
-
-        let llvm_usize = generator.get_size_type(ctx.ctx);
-        let llvm_elem_type = if let TypeEnum::TVar { .. } = &*ctx.unifier.get_ty_immutable(ty) {
-            None
-        } else {
-            Some(ctx.get_llvm_type(generator, elem_type))
-        };
-
-        Self {
-            ty: Self::llvm_type(ctx.ctx, llvm_elem_type, llvm_usize),
-            item: llvm_elem_type,
-            llvm_usize,
-        }
-    }
-
-    /// Creates an [`ListType`] from a [`PointerType`].
-    #[must_use]
-    pub fn from_type(ptr_ty: PointerType<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
-        debug_assert!(Self::is_representable(ptr_ty, llvm_usize).is_ok());
-
-        let ctx = ptr_ty.get_context();
-
-        // We are just searching for the index off a field - Slot an arbitrary element type in.
-        let item_field_idx =
-            Self::fields(ctx.i8_type().into(), llvm_usize).index_of_field(|f| f.items);
-        let item = unsafe {
-            ptr_ty
-                .get_element_type()
-                .into_struct_type()
-                .get_field_type_at_index_unchecked(item_field_idx)
-                .into_pointer_type()
-                .get_element_type()
-        };
-        let item = BasicTypeEnum::try_from(item).unwrap_or_else(|()| {
-            panic!(
-                "Expected BasicTypeEnum for list element type, got {}",
-                ptr_ty.get_element_type().print_to_string()
-            )
-        });
-
-        ListType { ty: ptr_ty, item: Some(item), llvm_usize }
-    }
-
-    /// Returns the type of the `size` field of this `list` type.
-    #[must_use]
-    pub fn size_type(&self) -> IntType<'ctx> {
-        self.llvm_usize
-    }
-
-    /// Returns the element type of this `list` type.
-    #[must_use]
-    pub fn element_type(&self) -> Option<BasicTypeEnum<'ctx>> {
-        self.item
-    }
-
-    /// Allocates an instance of [`ListValue`] as if by calling `alloca` on the base type.
-    ///
-    /// See [`ProxyType::raw_alloca`].
-    #[must_use]
-    pub fn alloca(
-        &self,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
-            self.raw_alloca(ctx, name),
-            self.llvm_usize,
-            name,
-        )
-    }
-
-    /// Allocates an instance of [`ListValue`] as if by calling `alloca` on the base type.
-    ///
-    /// See [`ProxyType::raw_alloca_var`].
-    #[must_use]
-    pub fn alloca_var<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
-            self.raw_alloca_var(generator, ctx, name),
-            self.llvm_usize,
-            name,
-        )
-    }
-
-    /// Allocates a [`ListValue`] on the stack using `item` of this [`ListType`] instance.
-    ///
-    /// The returned list will contain:
-    ///
-    /// - `data`: Allocated with `len` number of elements.
-    /// - `len`: Initialized to the value of `len` passed to this function.
-    #[must_use]
-    pub fn construct<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        len: IntValue<'ctx>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        let len = ctx.builder.build_int_z_extend(len, self.llvm_usize, "").unwrap();
-
-        // Generate a runtime assertion if allocating a non-empty list with unknown element type
-        if ctx.registry.llvm_options.opt_level == OptimizationLevel::None && self.item.is_none() {
-            let len_eqz = ctx
-                .builder
-                .build_int_compare(IntPredicate::EQ, len, self.llvm_usize.const_zero(), "")
-                .unwrap();
-
-            ctx.make_assert(
-                generator,
-                len_eqz,
-                "0:AssertionError",
-                "Cannot allocate a non-empty list with unknown element type",
-                [None, None, None],
-                ctx.current_loc,
-            );
-        }
-
-        let plist = self.alloca_var(generator, ctx, name);
-        plist.store_size(ctx, generator, len);
-
-        let item = self.item.unwrap_or(self.llvm_usize.into());
-        plist.create_data(ctx, item, None);
-
-        plist
-    }
-
-    /// Convenience function for creating a list with zero elements.
-    ///
-    /// This function is preferred over [`ListType::construct`] if the length is known to always be
-    /// 0, as this function avoids injecting an IR assertion for checking if a non-empty untyped
-    /// list is being allocated.
-    ///
-    /// The returned list will contain:
-    ///
-    /// - `data`: Initialized to `(T*) 0`.
-    /// - `len`: Initialized to `0`.
-    #[must_use]
-    pub fn construct_empty<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        let plist = self.alloca_var(generator, ctx, name);
-
-        plist.store_size(ctx, generator, self.llvm_usize.const_zero());
-        plist.create_data(ctx, self.item.unwrap_or(self.llvm_usize.into()), None);
-
-        plist
-    }
-
-    /// Converts an existing value into a [`ListValue`].
-    #[must_use]
-    pub fn map_value(
-        &self,
-        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(value, self.llvm_usize, name)
-    }
-}
-
-impl<'ctx> ProxyType<'ctx> for ListType<'ctx> {
-    type Base = PointerType<'ctx>;
-    type Value = ListValue<'ctx>;
-
-    fn is_type<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        llvm_ty: impl BasicType<'ctx>,
-    ) -> Result<(), String> {
-        if let BasicTypeEnum::PointerType(ty) = llvm_ty.as_basic_type_enum() {
-            <Self as ProxyType<'ctx>>::is_representable(generator, ctx, ty)
-        } else {
-            Err(format!("Expected pointer type, got {llvm_ty:?}"))
-        }
-    }
-
-    fn is_representable<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        llvm_ty: Self::Base,
-    ) -> Result<(), String> {
-        Self::is_representable(llvm_ty, generator.get_size_type(ctx))
-    }
-
-    fn alloca_type(&self) -> impl BasicType<'ctx> {
-        self.as_base_type().get_element_type().into_struct_type()
-    }
-
-    fn as_base_type(&self) -> Self::Base {
-        self.ty
-    }
-}
-
-impl<'ctx> From<ListType<'ctx>> for PointerType<'ctx> {
-    fn from(value: ListType<'ctx>) -> Self {
-        value.as_base_type()
-    }
-}

nac3core/src/codegen/types/mod.rs

@@ -1,125 +0,0 @@
-//! This module contains abstraction over all intrinsic composite types of NAC3.
-//!
-//! # `raw_alloca` vs `alloca` vs `construct`
-//!
-//! There are three ways of creating a new object instance using the abstractions provided by this
-//! module.
-//!
-//! - `raw_alloca`: Allocates the object on the stack, returning an instance of
-//!   [`impl BasicValue`][inkwell::values::BasicValue]. This is similar to a `malloc` expression in
-//!   C++ but the object is allocated on the stack.
-//! - `alloca`: Similar to `raw_alloca`, but also wraps the allocated object with
-//!   [`<Self as ProxyType<'ctx>>::Value`][ProxyValue], and returns the wrapped object. The returned
-//!   object will not initialize any value or fields. This is similar to a type-safe `malloc`
-//!   expression in C++ but the object is allocated on the stack.
-//! - `construct`: Similar to `alloca`, but performs some initialization on the value or fields of
-//!   the returned object. This is similar to a `new` expression in C++ but the object is allocated
-//!   on the stack.
-
-use inkwell::{
-    context::Context,
-    types::BasicType,
-    values::{IntValue, PointerValue},
-};
-
-use super::{
-    values::{ArraySliceValue, ProxyValue},
-    {CodeGenContext, CodeGenerator},
-};
-pub use list::*;
-pub use range::*;
-pub use tuple::*;
-
-mod list;
-pub mod ndarray;
-mod range;
-pub mod structure;
-mod tuple;
-pub mod utils;
-
-/// A LLVM type that is used to represent a corresponding type in NAC3.
-pub trait ProxyType<'ctx>: Into<Self::Base> {
-    /// The LLVM type of which values of this type possess. This is usually a
-    /// [LLVM pointer type][PointerType] for any non-primitive types.
-    type Base: BasicType<'ctx>;
-
-    /// The type of values represented by this type.
-    type Value: ProxyValue<'ctx, Type = Self>;
-
-    fn is_type<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        llvm_ty: impl BasicType<'ctx>,
-    ) -> Result<(), String>;
-
-    /// Checks whether `llvm_ty` can be represented by this [`ProxyType`].
-    fn is_representable<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        llvm_ty: Self::Base,
-    ) -> Result<(), String>;
-
-    /// Returns the type that should be used in `alloca` IR statements.
-    fn alloca_type(&self) -> impl BasicType<'ctx>;
-
-    /// Creates a new value of this type by invoking `alloca` at the current builder location,
-    /// returning a [`PointerValue`] instance representing the allocated value.
-    fn raw_alloca(
-        &self,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        name: Option<&'ctx str>,
-    ) -> PointerValue<'ctx> {
-        ctx.builder
-            .build_alloca(self.alloca_type().as_basic_type_enum(), name.unwrap_or_default())
-            .unwrap()
-    }
-
-    /// Creates a new value of this type by invoking `alloca` at the beginning of the function,
-    /// returning a [`PointerValue`] instance representing the allocated value.
-    fn raw_alloca_var<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        name: Option<&'ctx str>,
-    ) -> PointerValue<'ctx> {
-        generator.gen_var_alloc(ctx, self.alloca_type().as_basic_type_enum(), name).unwrap()
-    }
-
-    /// Creates a new array value of this type by invoking `alloca` at the current builder location,
-    /// returning an [`ArraySliceValue`] encapsulating the resulting array.
-    fn array_alloca(
-        &self,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        size: IntValue<'ctx>,
-        name: Option<&'ctx str>,
-    ) -> ArraySliceValue<'ctx> {
-        ArraySliceValue::from_ptr_val(
-            ctx.builder
-                .build_array_alloca(
-                    self.alloca_type().as_basic_type_enum(),
-                    size,
-                    name.unwrap_or_default(),
-                )
-                .unwrap(),
-            size,
-            name,
-        )
-    }
-
-    /// Creates a new array value of this type by invoking `alloca` at the beginning of the
-    /// function, returning an [`ArraySliceValue`] encapsulating the resulting array.
-    fn array_alloca_var<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        size: IntValue<'ctx>,
-        name: Option<&'ctx str>,
-    ) -> ArraySliceValue<'ctx> {
-        generator
-            .gen_array_var_alloc(ctx, self.alloca_type().as_basic_type_enum(), size, name)
-            .unwrap()
-    }
-
-    /// Returns the [base type][Self::Base] of this proxy.
-    fn as_base_type(&self) -> Self::Base;
-}

nac3core/src/codegen/types/ndarray/array.rs

@@ -1,243 +0,0 @@
-use inkwell::{
-    types::BasicTypeEnum,
-    values::{BasicValueEnum, IntValue},
-    AddressSpace,
-};
-
-use crate::{
-    codegen::{
-        irrt,
-        stmt::gen_if_else_expr_callback,
-        types::{ndarray::NDArrayType, ListType, ProxyType},
-        values::{
-            ndarray::NDArrayValue, ArrayLikeValue, ArraySliceValue, ListValue, ProxyValue,
-            TypedArrayLikeAdapter, TypedArrayLikeMutator,
-        },
-        CodeGenContext, CodeGenerator,
-    },
-    toplevel::helper::{arraylike_flatten_element_type, arraylike_get_ndims},
-    typecheck::typedef::{Type, TypeEnum},
-};
-
-/// Get the expected `dtype` and `ndims` of the ndarray returned by `np_array(<list>)`.
-fn get_list_object_dtype_and_ndims<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    list_ty: Type,
-) -> (BasicTypeEnum<'ctx>, u64) {
-    let dtype = arraylike_flatten_element_type(&mut ctx.unifier, list_ty);
-    let ndims = arraylike_get_ndims(&mut ctx.unifier, list_ty);
-
-    (ctx.get_llvm_type(generator, dtype), ndims)
-}
-
-impl<'ctx> NDArrayType<'ctx> {
-    /// Implementation of `np_array(<list>, copy=True)`
-    fn construct_numpy_array_from_list_copy_true_impl<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        (list_ty, list): (Type, ListValue<'ctx>),
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        let (dtype, ndims_int) = get_list_object_dtype_and_ndims(generator, ctx, list_ty);
-        assert!(self.ndims >= ndims_int);
-        assert_eq!(dtype, self.dtype);
-
-        let list_value = list.as_i8_list(generator, ctx);
-
-        // Validate `list` has a consistent shape.
-        // Raise an exception if `list` is something abnormal like `[[1, 2], [3]]`.
-        // If `list` has a consistent shape, deduce the shape and write it to `shape`.
-        let ndims = self.llvm_usize.const_int(ndims_int, false);
-        let shape = ctx.builder.build_array_alloca(self.llvm_usize, ndims, "").unwrap();
-        let shape = ArraySliceValue::from_ptr_val(shape, ndims, None);
-        let shape = TypedArrayLikeAdapter::from(
-            shape,
-            |_, _, val| val.into_int_value(),
-            |_, _, val| val.into(),
-        );
-        irrt::ndarray::call_nac3_ndarray_array_set_and_validate_list_shape(
-            generator, ctx, list_value, ndims, &shape,
-        );
-
-        let ndarray = Self::new(generator, ctx.ctx, dtype, ndims_int)
-            .construct_uninitialized(generator, ctx, name);
-        ndarray.copy_shape_from_array(generator, ctx, shape.base_ptr(ctx, generator));
-        unsafe { ndarray.create_data(generator, ctx) };
-
-        // Copy all contents from the list.
-        irrt::ndarray::call_nac3_ndarray_array_write_list_to_array(
-            generator, ctx, list_value, ndarray,
-        );
-
-        ndarray
-    }
-
-    /// Implementation of `np_array(<list>, copy=None)`
-    fn construct_numpy_array_from_list_copy_none_impl<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        (list_ty, list): (Type, ListValue<'ctx>),
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        // np_array without copying is only possible `list` is not nested.
-        //
-        // If `list` is `list[T]`, we can create an ndarray with `data` set
-        // to the array pointer of `list`.
-        //
-        // If `list` is `list[list[T]]` or worse, copy.
-
-        let (dtype, ndims) = get_list_object_dtype_and_ndims(generator, ctx, list_ty);
-        if ndims == 1 {
-            // `list` is not nested
-            assert_eq!(ndims, 1);
-            assert!(self.ndims >= ndims);
-            assert_eq!(dtype, self.dtype);
-
-            let llvm_pi8 = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
-
-            let ndarray = Self::new(generator, ctx.ctx, dtype, 1)
-                .construct_uninitialized(generator, ctx, name);
-
-            // Set data
-            let data = ctx
-                .builder
-                .build_pointer_cast(list.data().base_ptr(ctx, generator), llvm_pi8, "")
-                .unwrap();
-            ndarray.store_data(ctx, data);
-
-            // ndarray->shape[0] = list->len;
-            let shape = ndarray.shape();
-            let list_len = list.load_size(ctx, None);
-            unsafe {
-                shape.set_typed_unchecked(ctx, generator, &self.llvm_usize.const_zero(), list_len);
-            }
-
-            // Set strides, the `data` is contiguous
-            ndarray.set_strides_contiguous(generator, ctx);
-
-            ndarray
-        } else {
-            // `list` is nested, copy
-            self.construct_numpy_array_from_list_copy_true_impl(
-                generator,
-                ctx,
-                (list_ty, list),
-                name,
-            )
-        }
-    }
-
-    /// Implementation of `np_array(<list>, copy=copy)`
-    fn construct_numpy_array_list_impl<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        (list_ty, list): (Type, ListValue<'ctx>),
-        copy: IntValue<'ctx>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        assert_eq!(copy.get_type(), ctx.ctx.bool_type());
-
-        let (dtype, ndims) = get_list_object_dtype_and_ndims(generator, ctx, list_ty);
-
-        let ndarray = gen_if_else_expr_callback(
-            generator,
-            ctx,
-            |_generator, _ctx| Ok(copy),
-            |generator, ctx| {
-                let ndarray = self.construct_numpy_array_from_list_copy_true_impl(
-                    generator,
-                    ctx,
-                    (list_ty, list),
-                    name,
-                );
-                Ok(Some(ndarray.as_base_value()))
-            },
-            |generator, ctx| {
-                let ndarray = self.construct_numpy_array_from_list_copy_none_impl(
-                    generator,
-                    ctx,
-                    (list_ty, list),
-                    name,
-                );
-                Ok(Some(ndarray.as_base_value()))
-            },
-        )
-        .unwrap()
-        .map(BasicValueEnum::into_pointer_value)
-        .unwrap();
-
-        NDArrayType::new(generator, ctx.ctx, dtype, ndims).map_value(ndarray, None)
-    }
-
-    /// Implementation of `np_array(<ndarray>, copy=copy)`.
-    pub fn construct_numpy_array_ndarray_impl<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        ndarray: NDArrayValue<'ctx>,
-        copy: IntValue<'ctx>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        assert_eq!(ndarray.get_type().dtype, self.dtype);
-        assert!(self.ndims >= ndarray.get_type().ndims);
-        assert_eq!(copy.get_type(), ctx.ctx.bool_type());
-
-        let ndarray_val = gen_if_else_expr_callback(
-            generator,
-            ctx,
-            |_generator, _ctx| Ok(copy),
-            |generator, ctx| {
-                let ndarray = ndarray.make_copy(generator, ctx); // Force copy
-                Ok(Some(ndarray.as_base_value()))
-            },
-            |_generator, _ctx| {
-                // No need to copy. Return `ndarray` itself.
-                Ok(Some(ndarray.as_base_value()))
-            },
-        )
-        .unwrap()
-        .map(BasicValueEnum::into_pointer_value)
-        .unwrap();
-
-        ndarray.get_type().map_value(ndarray_val, name)
-    }
-
-    /// Create a new ndarray like
-    /// [`np.array()`](https://numpy.org/doc/stable/reference/generated/numpy.array.html).
-    ///
-    /// Note that the returned [`NDArrayValue`] may have fewer dimensions than is specified by this
-    /// instance. Use [`NDArrayValue::atleast_nd`] on the returned value if an `ndarray` instance
-    /// with the exact number of dimensions is needed.
-    pub fn construct_numpy_array<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        (object_ty, object): (Type, BasicValueEnum<'ctx>),
-        copy: IntValue<'ctx>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        match &*ctx.unifier.get_ty_immutable(object_ty) {
-            TypeEnum::TObj { obj_id, .. }
-                if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
-            {
-                let list = ListType::from_unifier_type(generator, ctx, object_ty)
-                    .map_value(object.into_pointer_value(), None);
-                self.construct_numpy_array_list_impl(generator, ctx, (object_ty, list), copy, name)
-            }
-
-            TypeEnum::TObj { obj_id, .. }
-                if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
-            {
-                let ndarray = NDArrayType::from_unifier_type(generator, ctx, object_ty)
-                    .map_value(object.into_pointer_value(), None);
-                self.construct_numpy_array_ndarray_impl(generator, ctx, ndarray, copy, name)
-            }
-
-            _ => panic!("Unrecognized object type: {}", ctx.unifier.stringify(object_ty)), // Typechecker ensures this
-        }
-    }
-}

nac3core/src/codegen/types/ndarray/broadcast.rs

@@ -1,176 +0,0 @@
-use inkwell::{
-    context::{AsContextRef, Context},
-    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
-    values::{IntValue, PointerValue},
-    AddressSpace,
-};
-use itertools::Itertools;
-
-use nac3core_derive::StructFields;
-
-use crate::codegen::{
-    types::{
-        structure::{check_struct_type_matches_fields, StructField, StructFields},
-        ProxyType,
-    },
-    values::{ndarray::ShapeEntryValue, ProxyValue},
-    CodeGenContext, CodeGenerator,
-};
-
-#[derive(Debug, PartialEq, Eq, Clone, Copy)]
-pub struct ShapeEntryType<'ctx> {
-    ty: PointerType<'ctx>,
-    llvm_usize: IntType<'ctx>,
-}
-
-#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
-pub struct ShapeEntryStructFields<'ctx> {
-    #[value_type(usize)]
-    pub ndims: StructField<'ctx, IntValue<'ctx>>,
-    #[value_type(usize.ptr_type(AddressSpace::default()))]
-    pub shape: StructField<'ctx, PointerValue<'ctx>>,
-}
-
-impl<'ctx> ShapeEntryType<'ctx> {
-    /// Checks whether `llvm_ty` represents a [`ShapeEntryType`], returning [Err] if it does not.
-    pub fn is_representable(
-        llvm_ty: PointerType<'ctx>,
-        llvm_usize: IntType<'ctx>,
-    ) -> Result<(), String> {
-        let ctx = llvm_ty.get_context();
-
-        let llvm_ndarray_ty = llvm_ty.get_element_type();
-        let AnyTypeEnum::StructType(llvm_ndarray_ty) = llvm_ndarray_ty else {
-            return Err(format!(
-                "Expected struct type for `ShapeEntry` type, got {llvm_ndarray_ty}"
-            ));
-        };
-
-        check_struct_type_matches_fields(
-            Self::fields(ctx, llvm_usize),
-            llvm_ndarray_ty,
-            "NDArray",
-            &[],
-        )
-    }
-
-    /// Returns an instance of [`StructFields`] containing all field accessors for this type.
-    #[must_use]
-    fn fields(
-        ctx: impl AsContextRef<'ctx>,
-        llvm_usize: IntType<'ctx>,
-    ) -> ShapeEntryStructFields<'ctx> {
-        ShapeEntryStructFields::new(ctx, llvm_usize)
-    }
-
-    /// See [`ShapeEntryStructFields::fields`].
-    // TODO: Move this into e.g. StructProxyType
-    #[must_use]
-    pub fn get_fields(&self, ctx: impl AsContextRef<'ctx>) -> ShapeEntryStructFields<'ctx> {
-        Self::fields(ctx, self.llvm_usize)
-    }
-
-    /// Creates an LLVM type corresponding to the expected structure of a `ShapeEntry`.
-    #[must_use]
-    fn llvm_type(ctx: &'ctx Context, llvm_usize: IntType<'ctx>) -> PointerType<'ctx> {
-        let field_tys =
-            Self::fields(ctx, llvm_usize).into_iter().map(|field| field.1).collect_vec();
-
-        ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
-    }
-
-    /// Creates an instance of [`ShapeEntryType`].
-    #[must_use]
-    pub fn new<G: CodeGenerator + ?Sized>(generator: &G, ctx: &'ctx Context) -> Self {
-        let llvm_usize = generator.get_size_type(ctx);
-        let llvm_ty = Self::llvm_type(ctx, llvm_usize);
-
-        Self { ty: llvm_ty, llvm_usize }
-    }
-
-    /// Creates a [`ShapeEntryType`] from a [`PointerType`] representing an `ShapeEntry`.
-    #[must_use]
-    pub fn from_type(ptr_ty: PointerType<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
-        debug_assert!(Self::is_representable(ptr_ty, llvm_usize).is_ok());
-
-        Self { ty: ptr_ty, llvm_usize }
-    }
-
-    /// Allocates an instance of [`ShapeEntryValue`] as if by calling `alloca` on the base type.
-    #[must_use]
-    pub fn alloca(
-        &self,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
-            self.raw_alloca(ctx, name),
-            self.llvm_usize,
-            name,
-        )
-    }
-
-    /// Allocates an instance of [`ShapeEntryValue`] as if by calling `alloca` on the base type.
-    #[must_use]
-    pub fn alloca_var<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
-            self.raw_alloca_var(generator, ctx, name),
-            self.llvm_usize,
-            name,
-        )
-    }
-
-    /// Converts an existing value into a [`ShapeEntryValue`].
-    #[must_use]
-    pub fn map_value(
-        &self,
-        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(value, self.llvm_usize, name)
-    }
-}
-
-impl<'ctx> ProxyType<'ctx> for ShapeEntryType<'ctx> {
-    type Base = PointerType<'ctx>;
-    type Value = ShapeEntryValue<'ctx>;
-
-    fn is_type<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        llvm_ty: impl BasicType<'ctx>,
-    ) -> Result<(), String> {
-        if let BasicTypeEnum::PointerType(ty) = llvm_ty.as_basic_type_enum() {
-            <Self as ProxyType<'ctx>>::is_representable(generator, ctx, ty)
-        } else {
-            Err(format!("Expected pointer type, got {llvm_ty:?}"))
-        }
-    }
-
-    fn is_representable<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        llvm_ty: Self::Base,
-    ) -> Result<(), String> {
-        Self::is_representable(llvm_ty, generator.get_size_type(ctx))
-    }
-
-    fn alloca_type(&self) -> impl BasicType<'ctx> {
-        self.as_base_type().get_element_type().into_struct_type()
-    }
-
-    fn as_base_type(&self) -> Self::Base {
-        self.ty
-    }
-}
-
-impl<'ctx> From<ShapeEntryType<'ctx>> for PointerType<'ctx> {
-    fn from(value: ShapeEntryType<'ctx>) -> Self {
-        value.as_base_type()
-    }
-}

nac3core/src/codegen/types/ndarray/contiguous.rs

@@ -1,250 +0,0 @@
-use inkwell::{
-    context::Context,
-    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
-    values::{IntValue, PointerValue},
-    AddressSpace,
-};
-use itertools::Itertools;
-
-use nac3core_derive::StructFields;
-
-use crate::{
-    codegen::{
-        types::{
-            structure::{
-                check_struct_type_matches_fields, FieldIndexCounter, StructField, StructFields,
-            },
-            ProxyType,
-        },
-        values::{ndarray::ContiguousNDArrayValue, ProxyValue},
-        CodeGenContext, CodeGenerator,
-    },
-    toplevel::numpy::unpack_ndarray_var_tys,
-    typecheck::typedef::Type,
-};
-
-#[derive(Debug, PartialEq, Eq, Clone, Copy)]
-pub struct ContiguousNDArrayType<'ctx> {
-    ty: PointerType<'ctx>,
-    item: BasicTypeEnum<'ctx>,
-    llvm_usize: IntType<'ctx>,
-}
-
-#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
-pub struct ContiguousNDArrayStructFields<'ctx> {
-    #[value_type(usize)]
-    pub ndims: StructField<'ctx, IntValue<'ctx>>,
-    #[value_type(usize.ptr_type(AddressSpace::default()))]
-    pub shape: StructField<'ctx, PointerValue<'ctx>>,
-    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
-    pub data: StructField<'ctx, PointerValue<'ctx>>,
-}
-
-impl<'ctx> ContiguousNDArrayStructFields<'ctx> {
-    #[must_use]
-    pub fn new_typed(item: BasicTypeEnum<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
-        let mut counter = FieldIndexCounter::default();
-
-        ContiguousNDArrayStructFields {
-            ndims: StructField::create(&mut counter, "ndims", llvm_usize),
-            shape: StructField::create(
-                &mut counter,
-                "shape",
-                llvm_usize.ptr_type(AddressSpace::default()),
-            ),
-            data: StructField::create(&mut counter, "data", item.ptr_type(AddressSpace::default())),
-        }
-    }
-}
-
-impl<'ctx> ContiguousNDArrayType<'ctx> {
-    /// Checks whether `llvm_ty` represents a `ndarray` type, returning [Err] if it does not.
-    pub fn is_representable(
-        llvm_ty: PointerType<'ctx>,
-        llvm_usize: IntType<'ctx>,
-    ) -> Result<(), String> {
-        let ctx = llvm_ty.get_context();
-
-        let llvm_ty = llvm_ty.get_element_type();
-        let AnyTypeEnum::StructType(llvm_ty) = llvm_ty else {
-            return Err(format!(
-                "Expected struct type for `ContiguousNDArray` type, got {llvm_ty}"
-            ));
-        };
-
-        let fields = ContiguousNDArrayStructFields::new(ctx, llvm_usize);
-
-        check_struct_type_matches_fields(
-            fields,
-            llvm_ty,
-            "ContiguousNDArray",
-            &[(fields.data.name(), &|ty| {
-                if ty.is_pointer_type() {
-                    Ok(())
-                } else {
-                    Err(format!("Expected T* for `ContiguousNDArray.data`, got {ty}"))
-                }
-            })],
-        )
-    }
-
-    /// Returns an instance of [`StructFields`] containing all field accessors for this type.
-    #[must_use]
-    fn fields(
-        item: BasicTypeEnum<'ctx>,
-        llvm_usize: IntType<'ctx>,
-    ) -> ContiguousNDArrayStructFields<'ctx> {
-        ContiguousNDArrayStructFields::new_typed(item, llvm_usize)
-    }
-
-    /// See [`NDArrayType::fields`].
-    // TODO: Move this into e.g. StructProxyType
-    #[must_use]
-    pub fn get_fields(&self) -> ContiguousNDArrayStructFields<'ctx> {
-        Self::fields(self.item, self.llvm_usize)
-    }
-
-    /// Creates an LLVM type corresponding to the expected structure of an `NDArray`.
-    #[must_use]
-    fn llvm_type(
-        ctx: &'ctx Context,
-        item: BasicTypeEnum<'ctx>,
-        llvm_usize: IntType<'ctx>,
-    ) -> PointerType<'ctx> {
-        let field_tys =
-            Self::fields(item, llvm_usize).into_iter().map(|field| field.1).collect_vec();
-
-        ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
-    }
-
-    /// Creates an instance of [`ContiguousNDArrayType`].
-    #[must_use]
-    pub fn new<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        item: BasicTypeEnum<'ctx>,
-    ) -> Self {
-        let llvm_usize = generator.get_size_type(ctx);
-        let llvm_cndarray = Self::llvm_type(ctx, item, llvm_usize);
-
-        Self { ty: llvm_cndarray, item, llvm_usize }
-    }
-
-    /// Creates an [`ContiguousNDArrayType`] from a [unifier type][Type].
-    #[must_use]
-    pub fn from_unifier_type<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        ty: Type,
-    ) -> Self {
-        let (dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
-
-        let llvm_dtype = ctx.get_llvm_type(generator, dtype);
-        let llvm_usize = generator.get_size_type(ctx.ctx);
-
-        Self { ty: Self::llvm_type(ctx.ctx, llvm_dtype, llvm_usize), item: llvm_dtype, llvm_usize }
-    }
-
-    /// Creates an [`ContiguousNDArrayType`] from a [`PointerType`] representing an `NDArray`.
-    #[must_use]
-    pub fn from_type(
-        ptr_ty: PointerType<'ctx>,
-        item: BasicTypeEnum<'ctx>,
-        llvm_usize: IntType<'ctx>,
-    ) -> Self {
-        debug_assert!(Self::is_representable(ptr_ty, llvm_usize).is_ok());
-
-        Self { ty: ptr_ty, item, llvm_usize }
-    }
-
-    /// Allocates an instance of [`ContiguousNDArrayValue`] as if by calling `alloca` on the base
-    /// type.
-    ///
-    /// See [`ProxyType::raw_alloca`].
-    #[must_use]
-    pub fn alloca(
-        &self,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
-            self.raw_alloca(ctx, name),
-            self.item,
-            self.llvm_usize,
-            name,
-        )
-    }
-
-    /// Allocates an instance of [`ContiguousNDArrayValue`] as if by calling `alloca` on the base
-    /// type.
-    ///
-    /// See [`ProxyType::raw_alloca_var`].
-    #[must_use]
-    pub fn alloca_var<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
-            self.raw_alloca_var(generator, ctx, name),
-            self.item,
-            self.llvm_usize,
-            name,
-        )
-    }
-
-    /// Converts an existing value into a [`ContiguousNDArrayValue`].
-    #[must_use]
-    pub fn map_value(
-        &self,
-        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
-            value,
-            self.item,
-            self.llvm_usize,
-            name,
-        )
-    }
-}
-
-impl<'ctx> ProxyType<'ctx> for ContiguousNDArrayType<'ctx> {
-    type Base = PointerType<'ctx>;
-    type Value = ContiguousNDArrayValue<'ctx>;
-
-    fn is_type<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        llvm_ty: impl BasicType<'ctx>,
-    ) -> Result<(), String> {
-        if let BasicTypeEnum::PointerType(ty) = llvm_ty.as_basic_type_enum() {
-            <Self as ProxyType<'ctx>>::is_representable(generator, ctx, ty)
-        } else {
-            Err(format!("Expected pointer type, got {llvm_ty:?}"))
-        }
-    }
-
-    fn is_representable<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        llvm_ty: Self::Base,
-    ) -> Result<(), String> {
-        Self::is_representable(llvm_ty, generator.get_size_type(ctx))
-    }
-
-    fn alloca_type(&self) -> impl BasicType<'ctx> {
-        self.as_base_type().get_element_type().into_struct_type()
-    }
-
-    fn as_base_type(&self) -> Self::Base {
-        self.ty
-    }
-}
-
-impl<'ctx> From<ContiguousNDArrayType<'ctx>> for PointerType<'ctx> {
-    fn from(value: ContiguousNDArrayType<'ctx>) -> Self {
-        value.as_base_type()
-    }
-}

nac3core/src/codegen/types/ndarray/factory.rs

@@ -1,236 +0,0 @@
-use inkwell::{
-    values::{BasicValueEnum, IntValue},
-    IntPredicate,
-};
-
-use super::NDArrayType;
-use crate::{
-    codegen::{
-        irrt, types::ProxyType, values::TypedArrayLikeAccessor, CodeGenContext, CodeGenerator,
-    },
-    typecheck::typedef::Type,
-};
-
-/// Get the zero value in `np.zeros()` of a `dtype`.
-fn ndarray_zero_value<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    dtype: Type,
-) -> BasicValueEnum<'ctx> {
-    if [ctx.primitives.int32, ctx.primitives.uint32]
-        .iter()
-        .any(|ty| ctx.unifier.unioned(dtype, *ty))
-    {
-        ctx.ctx.i32_type().const_zero().into()
-    } else if [ctx.primitives.int64, ctx.primitives.uint64]
-        .iter()
-        .any(|ty| ctx.unifier.unioned(dtype, *ty))
-    {
-        ctx.ctx.i64_type().const_zero().into()
-    } else if ctx.unifier.unioned(dtype, ctx.primitives.float) {
-        ctx.ctx.f64_type().const_zero().into()
-    } else if ctx.unifier.unioned(dtype, ctx.primitives.bool) {
-        ctx.ctx.bool_type().const_zero().into()
-    } else if ctx.unifier.unioned(dtype, ctx.primitives.str) {
-        ctx.gen_string(generator, "").into()
-    } else {
-        panic!("unrecognized dtype: {}", ctx.unifier.stringify(dtype));
-    }
-}
-
-/// Get the one value in `np.ones()` of a `dtype`.
-fn ndarray_one_value<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    dtype: Type,
-) -> BasicValueEnum<'ctx> {
-    if [ctx.primitives.int32, ctx.primitives.uint32]
-        .iter()
-        .any(|ty| ctx.unifier.unioned(dtype, *ty))
-    {
-        let is_signed = ctx.unifier.unioned(dtype, ctx.primitives.int32);
-        ctx.ctx.i32_type().const_int(1, is_signed).into()
-    } else if [ctx.primitives.int64, ctx.primitives.uint64]
-        .iter()
-        .any(|ty| ctx.unifier.unioned(dtype, *ty))
-    {
-        let is_signed = ctx.unifier.unioned(dtype, ctx.primitives.int64);
-        ctx.ctx.i64_type().const_int(1, is_signed).into()
-    } else if ctx.unifier.unioned(dtype, ctx.primitives.float) {
-        ctx.ctx.f64_type().const_float(1.0).into()
-    } else if ctx.unifier.unioned(dtype, ctx.primitives.bool) {
-        ctx.ctx.bool_type().const_int(1, false).into()
-    } else if ctx.unifier.unioned(dtype, ctx.primitives.str) {
-        ctx.gen_string(generator, "1").into()
-    } else {
-        panic!("unrecognized dtype: {}", ctx.unifier.stringify(dtype));
-    }
-}
-
-impl<'ctx> NDArrayType<'ctx> {
-    /// Create an ndarray like
-    /// [`np.empty`](https://numpy.org/doc/stable/reference/generated/numpy.empty.html).
-    pub fn construct_numpy_empty<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        let ndarray = self.construct_uninitialized(generator, ctx, name);
-
-        // Validate `shape`
-        irrt::ndarray::call_nac3_ndarray_util_assert_shape_no_negative(generator, ctx, shape);
-
-        ndarray.copy_shape_from_array(generator, ctx, shape.base_ptr(ctx, generator));
-        unsafe { ndarray.create_data(generator, ctx) };
-
-        ndarray
-    }
-
-    /// Create an ndarray like
-    /// [`np.full`](https://numpy.org/doc/stable/reference/generated/numpy.full.html).
-    pub fn construct_numpy_full<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-        fill_value: BasicValueEnum<'ctx>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        let ndarray = self.construct_numpy_empty(generator, ctx, shape, name);
-        ndarray.fill(generator, ctx, fill_value);
-        ndarray
-    }
-
-    /// Create an ndarray like
-    /// [`np.zero`](https://numpy.org/doc/stable/reference/generated/numpy.zeros.html).
-    pub fn construct_numpy_zeros<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        dtype: Type,
-        shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        assert_eq!(
-            ctx.get_llvm_type(generator, dtype),
-            self.dtype,
-            "Expected LLVM dtype={} but got {}",
-            self.dtype.print_to_string(),
-            ctx.get_llvm_type(generator, dtype).print_to_string(),
-        );
-
-        let fill_value = ndarray_zero_value(generator, ctx, dtype);
-        self.construct_numpy_full(generator, ctx, shape, fill_value, name)
-    }
-
-    /// Create an ndarray like
-    /// [`np.ones`](https://numpy.org/doc/stable/reference/generated/numpy.ones.html).
-    pub fn construct_numpy_ones<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        dtype: Type,
-        shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        assert_eq!(
-            ctx.get_llvm_type(generator, dtype),
-            self.dtype,
-            "Expected LLVM dtype={} but got {}",
-            self.dtype.print_to_string(),
-            ctx.get_llvm_type(generator, dtype).print_to_string(),
-        );
-
-        let fill_value = ndarray_one_value(generator, ctx, dtype);
-        self.construct_numpy_full(generator, ctx, shape, fill_value, name)
-    }
-
-    /// Create an ndarray like
-    /// [`np.eye`](https://numpy.org/doc/stable/reference/generated/numpy.eye.html).
-    #[allow(clippy::too_many_arguments)]
-    pub fn construct_numpy_eye<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        dtype: Type,
-        nrows: IntValue<'ctx>,
-        ncols: IntValue<'ctx>,
-        offset: IntValue<'ctx>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        assert_eq!(
-            ctx.get_llvm_type(generator, dtype),
-            self.dtype,
-            "Expected LLVM dtype={} but got {}",
-            self.dtype.print_to_string(),
-            ctx.get_llvm_type(generator, dtype).print_to_string(),
-        );
-        assert_eq!(nrows.get_type(), self.llvm_usize);
-        assert_eq!(ncols.get_type(), self.llvm_usize);
-        assert_eq!(offset.get_type(), self.llvm_usize);
-
-        let ndzero = ndarray_zero_value(generator, ctx, dtype);
-        let ndone = ndarray_one_value(generator, ctx, dtype);
-
-        let ndarray = self.construct_dyn_shape(generator, ctx, &[nrows, ncols], name);
-
-        // Create data and make the matrix like look np.eye()
-        unsafe {
-            ndarray.create_data(generator, ctx);
-        }
-        ndarray
-            .foreach(generator, ctx, |generator, ctx, _, nditer| {
-                // NOTE: rows and cols can never be zero here, since this ndarray's `np.size` would be zero
-                // and this loop would not execute.
-
-                let indices = nditer.get_indices();
-
-                let row_i = unsafe {
-                    indices.get_typed_unchecked(ctx, generator, &self.llvm_usize.const_zero(), None)
-                };
-                let col_i = unsafe {
-                    indices.get_typed_unchecked(
-                        ctx,
-                        generator,
-                        &self.llvm_usize.const_int(1, false),
-                        None,
-                    )
-                };
-
-                let be_one = ctx
-                    .builder
-                    .build_int_compare(
-                        IntPredicate::EQ,
-                        ctx.builder.build_int_add(row_i, offset, "").unwrap(),
-                        col_i,
-                        "",
-                    )
-                    .unwrap();
-                let value = ctx.builder.build_select(be_one, ndone, ndzero, "value").unwrap();
-
-                let p = nditer.get_pointer(ctx);
-                ctx.builder.build_store(p, value).unwrap();
-
-                Ok(())
-            })
-            .unwrap();
-
-        ndarray
-    }
-
-    /// Create an ndarray like
-    /// [`np.identity`](https://numpy.org/doc/stable/reference/generated/numpy.identity.html).
-    pub fn construct_numpy_identity<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        dtype: Type,
-        size: IntValue<'ctx>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        let offset = self.llvm_usize.const_zero();
-        self.construct_numpy_eye(generator, ctx, dtype, size, size, offset, name)
-    }
-}

nac3core/src/codegen/types/ndarray/indexing.rs

@@ -1,205 +0,0 @@
-use inkwell::{
-    context::{AsContextRef, Context},
-    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
-    values::{IntValue, PointerValue},
-    AddressSpace,
-};
-use itertools::Itertools;
-
-use nac3core_derive::StructFields;
-
-use crate::codegen::{
-    types::{
-        structure::{check_struct_type_matches_fields, StructField, StructFields},
-        ProxyType,
-    },
-    values::{
-        ndarray::{NDIndexValue, RustNDIndex},
-        ArrayLikeIndexer, ArraySliceValue, ProxyValue,
-    },
-    CodeGenContext, CodeGenerator,
-};
-
-#[derive(Debug, PartialEq, Eq, Clone, Copy)]
-pub struct NDIndexType<'ctx> {
-    ty: PointerType<'ctx>,
-    llvm_usize: IntType<'ctx>,
-}
-
-#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
-pub struct NDIndexStructFields<'ctx> {
-    #[value_type(i8_type())]
-    pub type_: StructField<'ctx, IntValue<'ctx>>,
-    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
-    pub data: StructField<'ctx, PointerValue<'ctx>>,
-}
-
-impl<'ctx> NDIndexType<'ctx> {
-    /// Checks whether `llvm_ty` represents a `ndindex` type, returning [Err] if it does not.
-    pub fn is_representable(
-        llvm_ty: PointerType<'ctx>,
-        llvm_usize: IntType<'ctx>,
-    ) -> Result<(), String> {
-        let ctx = llvm_ty.get_context();
-
-        let llvm_ty = llvm_ty.get_element_type();
-        let AnyTypeEnum::StructType(llvm_ty) = llvm_ty else {
-            return Err(format!(
-                "Expected struct type for `ContiguousNDArray` type, got {llvm_ty}"
-            ));
-        };
-
-        let fields = NDIndexStructFields::new(ctx, llvm_usize);
-
-        check_struct_type_matches_fields(fields, llvm_ty, "NDIndex", &[])
-    }
-
-    #[must_use]
-    fn fields(
-        ctx: impl AsContextRef<'ctx>,
-        llvm_usize: IntType<'ctx>,
-    ) -> NDIndexStructFields<'ctx> {
-        NDIndexStructFields::new(ctx, llvm_usize)
-    }
-
-    #[must_use]
-    pub fn get_fields(&self) -> NDIndexStructFields<'ctx> {
-        Self::fields(self.ty.get_context(), self.llvm_usize)
-    }
-
-    #[must_use]
-    fn llvm_type(ctx: &'ctx Context, llvm_usize: IntType<'ctx>) -> PointerType<'ctx> {
-        let field_tys =
-            Self::fields(ctx, llvm_usize).into_iter().map(|field| field.1).collect_vec();
-
-        ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
-    }
-
-    #[must_use]
-    pub fn new<G: CodeGenerator + ?Sized>(generator: &G, ctx: &'ctx Context) -> Self {
-        let llvm_usize = generator.get_size_type(ctx);
-        let llvm_ndindex = Self::llvm_type(ctx, llvm_usize);
-
-        Self { ty: llvm_ndindex, llvm_usize }
-    }
-
-    #[must_use]
-    pub fn from_type(ptr_ty: PointerType<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
-        debug_assert!(Self::is_representable(ptr_ty, llvm_usize).is_ok());
-
-        Self { ty: ptr_ty, llvm_usize }
-    }
-
-    /// Allocates an instance of [`NDIndexValue`] as if by calling `alloca` on the base type.
-    ///
-    /// See [`ProxyType::raw_alloca`].
-    #[must_use]
-    pub fn alloca(
-        &self,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
-            self.raw_alloca(ctx, name),
-            self.llvm_usize,
-            name,
-        )
-    }
-    /// Allocates an instance of [`NDIndexValue`] as if by calling `alloca` on the base type.
-    ///
-    /// See [`ProxyType::raw_alloca_var`].
-    #[must_use]
-    pub fn alloca_var<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
-            self.raw_alloca_var(generator, ctx, name),
-            self.llvm_usize,
-            name,
-        )
-    }
-
-    /// Serialize a list of [`RustNDIndex`] as a newly allocated LLVM array of [`NDIndexValue`].
-    #[must_use]
-    pub fn construct_ndindices<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        in_ndindices: &[RustNDIndex<'ctx>],
-    ) -> ArraySliceValue<'ctx> {
-        // Allocate the LLVM ndindices.
-        let num_ndindices = self.llvm_usize.const_int(in_ndindices.len() as u64, false);
-        let ndindices = self.array_alloca_var(generator, ctx, num_ndindices, None);
-
-        // Initialize all of them.
-        for (i, in_ndindex) in in_ndindices.iter().enumerate() {
-            let pndindex = unsafe {
-                ndindices.ptr_offset_unchecked(
-                    ctx,
-                    generator,
-                    &ctx.ctx.i64_type().const_int(u64::try_from(i).unwrap(), false),
-                    None,
-                )
-            };
-
-            in_ndindex.write_to_ndindex(
-                generator,
-                ctx,
-                NDIndexValue::from_pointer_value(pndindex, self.llvm_usize, None),
-            );
-        }
-
-        ndindices
-    }
-
-    #[must_use]
-    pub fn map_value(
-        &self,
-        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(value, self.llvm_usize, name)
-    }
-}
-
-impl<'ctx> ProxyType<'ctx> for NDIndexType<'ctx> {
-    type Base = PointerType<'ctx>;
-    type Value = NDIndexValue<'ctx>;
-
-    fn is_type<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        llvm_ty: impl BasicType<'ctx>,
-    ) -> Result<(), String> {
-        if let BasicTypeEnum::PointerType(ty) = llvm_ty.as_basic_type_enum() {
-            <Self as ProxyType<'ctx>>::is_representable(generator, ctx, ty)
-        } else {
-            Err(format!("Expected pointer type, got {llvm_ty:?}"))
-        }
-    }
-
-    fn is_representable<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        llvm_ty: Self::Base,
-    ) -> Result<(), String> {
-        Self::is_representable(llvm_ty, generator.get_size_type(ctx))
-    }
-
-    fn alloca_type(&self) -> impl BasicType<'ctx> {
-        self.as_base_type().get_element_type().into_struct_type()
-    }
-
-    fn as_base_type(&self) -> Self::Base {
-        self.ty
-    }
-}
-
-impl<'ctx> From<NDIndexType<'ctx>> for PointerType<'ctx> {
-    fn from(value: NDIndexType<'ctx>) -> Self {
-        value.as_base_type()
-    }
-}

nac3core/src/codegen/types/ndarray/map.rs

@@ -1,187 +0,0 @@
-use inkwell::{types::BasicTypeEnum, values::BasicValueEnum};
-use itertools::Itertools;
-
-use crate::codegen::{
-    stmt::gen_for_callback,
-    types::{
-        ndarray::{NDArrayType, NDIterType},
-        ProxyType,
-    },
-    values::{
-        ndarray::{NDArrayOut, NDArrayValue, ScalarOrNDArray},
-        ArrayLikeValue, ProxyValue,
-    },
-    CodeGenContext, CodeGenerator,
-};
-
-impl<'ctx> NDArrayType<'ctx> {
-    /// Generate LLVM IR to broadcast `ndarray`s together, and starmap through them with `mapping`
-    /// elementwise.
-    ///
-    /// `mapping` is an LLVM IR generator. The input of `mapping` is the list of elements when
-    /// iterating through the input `ndarrays` after broadcasting. The output of `mapping` is the
-    /// result of the elementwise operation.
-    ///
-    /// `out` specifies whether the result should be a new ndarray or to be written an existing
-    /// ndarray.
-    pub fn broadcast_starmap<'a, G, MappingFn>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, 'a>,
-        ndarrays: &[NDArrayValue<'ctx>],
-        out: NDArrayOut<'ctx>,
-        mapping: MappingFn,
-    ) -> Result<<Self as ProxyType<'ctx>>::Value, String>
-    where
-        G: CodeGenerator + ?Sized,
-        MappingFn: FnOnce(
-            &mut G,
-            &mut CodeGenContext<'ctx, 'a>,
-            &[BasicValueEnum<'ctx>],
-        ) -> Result<BasicValueEnum<'ctx>, String>,
-    {
-        // Broadcast inputs
-        let broadcast_result = self.broadcast(generator, ctx, ndarrays);
-
-        let out_ndarray = match out {
-            NDArrayOut::NewNDArray { dtype } => {
-                // Create a new ndarray based on the broadcast shape.
-                let result_ndarray =
-                    NDArrayType::new(generator, ctx.ctx, dtype, broadcast_result.ndims)
-                        .construct_uninitialized(generator, ctx, None);
-                result_ndarray.copy_shape_from_array(
-                    generator,
-                    ctx,
-                    broadcast_result.shape.base_ptr(ctx, generator),
-                );
-                unsafe {
-                    result_ndarray.create_data(generator, ctx);
-                }
-                result_ndarray
-            }
-
-            NDArrayOut::WriteToNDArray { ndarray: result_ndarray } => {
-                // Use an existing ndarray.
-
-                // Check that its shape is compatible with the broadcast shape.
-                result_ndarray.assert_can_be_written_by_out(generator, ctx, broadcast_result.shape);
-                result_ndarray
-            }
-        };
-
-        // Map element-wise and store results into `mapped_ndarray`.
-        let nditer = NDIterType::new(generator, ctx.ctx).construct(generator, ctx, out_ndarray);
-        gen_for_callback(
-            generator,
-            ctx,
-            Some("broadcast_starmap"),
-            |generator, ctx| {
-                // Create NDIters for all broadcasted input ndarrays.
-                let other_nditers = broadcast_result
-                    .ndarrays
-                    .iter()
-                    .map(|ndarray| {
-                        NDIterType::new(generator, ctx.ctx).construct(generator, ctx, *ndarray)
-                    })
-                    .collect_vec();
-                Ok((nditer, other_nditers))
-            },
-            |generator, ctx, (out_nditer, _in_nditers)| {
-                // We can simply use `out_nditer`'s `has_element()`.
-                // `in_nditers`' `has_element()`s should return the same value.
-                Ok(out_nditer.has_element(generator, ctx))
-            },
-            |generator, ctx, _hooks, (out_nditer, in_nditers)| {
-                // Get all the scalars from the broadcasted input ndarrays, pass them to `mapping`,
-                // and write to `out_ndarray`.
-                let in_scalars =
-                    in_nditers.iter().map(|nditer| nditer.get_scalar(ctx)).collect_vec();
-
-                let result = mapping(generator, ctx, &in_scalars)?;
-
-                let p = out_nditer.get_pointer(ctx);
-                ctx.builder.build_store(p, result).unwrap();
-
-                Ok(())
-            },
-            |generator, ctx, (out_nditer, in_nditers)| {
-                // Advance all iterators
-                out_nditer.next(generator, ctx);
-                in_nditers.iter().for_each(|nditer| nditer.next(generator, ctx));
-                Ok(())
-            },
-        )?;
-
-        Ok(out_ndarray)
-    }
-}
-
-impl<'ctx> ScalarOrNDArray<'ctx> {
-    /// Starmap through a list of inputs using `mapping`, where an input could be an ndarray, a
-    /// scalar.
-    ///
-    /// This function is very helpful when implementing NumPy functions that takes on either scalars
-    /// or ndarrays or a mix of them as their inputs and produces either an ndarray with broadcast,
-    /// or a scalar if all its inputs are all scalars.
-    ///
-    /// For example ,this function can be used to implement `np.add`, which has the following
-    /// behaviors:
-    ///
-    /// - `np.add(3, 4) = 7` # (scalar, scalar) -> scalar
-    /// - `np.add(3, np.array([4, 5, 6]))` # (scalar, ndarray) -> ndarray; the first `scalar` is
-    ///   converted into an ndarray and broadcasted.
-    /// - `np.add(np.array([[1], [2], [3]]), np.array([[4, 5, 6]]))` # (ndarray, ndarray) ->
-    ///   ndarray; there is broadcasting.
-    ///
-    /// ## Details:
-    ///
-    /// If `inputs` are all [`ScalarOrNDArray::Scalar`], the output will be a
-    /// [`ScalarOrNDArray::Scalar`] with type `ret_dtype`.
-    ///
-    /// Otherwise (if there are any [`ScalarOrNDArray::NDArray`] in `inputs`), all inputs will be
-    /// 'as-ndarray'-ed into ndarrays, then all inputs (now all ndarrays) will be passed to
-    /// [`NDArrayValue::broadcasting_starmap`] and **create** a new ndarray with dtype `ret_dtype`.
-    pub fn broadcasting_starmap<'a, G, MappingFn>(
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, 'a>,
-        inputs: &[ScalarOrNDArray<'ctx>],
-        ret_dtype: BasicTypeEnum<'ctx>,
-        mapping: MappingFn,
-    ) -> Result<ScalarOrNDArray<'ctx>, String>
-    where
-        G: CodeGenerator + ?Sized,
-        MappingFn: FnOnce(
-            &mut G,
-            &mut CodeGenContext<'ctx, 'a>,
-            &[BasicValueEnum<'ctx>],
-        ) -> Result<BasicValueEnum<'ctx>, String>,
-    {
-        // Check if all inputs are Scalars
-        let all_scalars: Option<Vec<_>> =
-            inputs.iter().map(BasicValueEnum::<'ctx>::try_from).try_collect().ok();
-
-        if let Some(scalars) = all_scalars {
-            let scalars = scalars.iter().copied().collect_vec();
-            let value = mapping(generator, ctx, &scalars)?;
-
-            Ok(ScalarOrNDArray::Scalar(value))
-        } else {
-            // Promote all input to ndarrays and map through them.
-            let inputs = inputs.iter().map(|input| input.to_ndarray(generator, ctx)).collect_vec();
-            let ndarray = NDArrayType::new_broadcast(
-                generator,
-                ctx.ctx,
-                ret_dtype,
-                &inputs.iter().map(NDArrayValue::get_type).collect_vec(),
-            )
-            .broadcast_starmap(
-                generator,
-                ctx,
-                &inputs,
-                NDArrayOut::NewNDArray { dtype: ret_dtype },
-                mapping,
-            )?;
-            Ok(ScalarOrNDArray::NDArray(ndarray))
-        }
-    }
-}

nac3core/src/codegen/types/ndarray/mod.rs

@@ -1,452 +0,0 @@
-use inkwell::{
-    context::{AsContextRef, Context},
-    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
-    values::{BasicValue, IntValue, PointerValue},
-    AddressSpace,
-};
-use itertools::Itertools;
-
-use nac3core_derive::StructFields;
-
-use super::{
-    structure::{check_struct_type_matches_fields, StructField, StructFields},
-    ProxyType,
-};
-use crate::{
-    codegen::{
-        values::{ndarray::NDArrayValue, ProxyValue, TypedArrayLikeMutator},
-        {CodeGenContext, CodeGenerator},
-    },
-    toplevel::{helper::extract_ndims, numpy::unpack_ndarray_var_tys},
-    typecheck::typedef::Type,
-};
-pub use broadcast::*;
-pub use contiguous::*;
-pub use indexing::*;
-pub use nditer::*;
-
-mod array;
-mod broadcast;
-mod contiguous;
-pub mod factory;
-mod indexing;
-mod map;
-mod nditer;
-
-/// Proxy type for a `ndarray` type in LLVM.
-#[derive(Debug, PartialEq, Eq, Clone, Copy)]
-pub struct NDArrayType<'ctx> {
-    ty: PointerType<'ctx>,
-    dtype: BasicTypeEnum<'ctx>,
-    ndims: u64,
-    llvm_usize: IntType<'ctx>,
-}
-
-#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
-pub struct NDArrayStructFields<'ctx> {
-    /// The size of each `NDArray` element in bytes.
-    #[value_type(usize)]
-    pub itemsize: StructField<'ctx, IntValue<'ctx>>,
-    /// Number of dimensions in the array.
-    #[value_type(usize)]
-    pub ndims: StructField<'ctx, IntValue<'ctx>>,
-    /// Pointer to an array containing the shape of the `NDArray`.
-    #[value_type(usize.ptr_type(AddressSpace::default()))]
-    pub shape: StructField<'ctx, PointerValue<'ctx>>,
-    /// Pointer to an array indicating the number of bytes between each element at a dimension
-    #[value_type(usize.ptr_type(AddressSpace::default()))]
-    pub strides: StructField<'ctx, PointerValue<'ctx>>,
-    /// Pointer to an array containing the array data
-    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
-    pub data: StructField<'ctx, PointerValue<'ctx>>,
-}
-
-impl<'ctx> NDArrayType<'ctx> {
-    /// Checks whether `llvm_ty` represents a `ndarray` type, returning [Err] if it does not.
-    pub fn is_representable(
-        llvm_ty: PointerType<'ctx>,
-        llvm_usize: IntType<'ctx>,
-    ) -> Result<(), String> {
-        let ctx = llvm_ty.get_context();
-
-        let llvm_ndarray_ty = llvm_ty.get_element_type();
-        let AnyTypeEnum::StructType(llvm_ndarray_ty) = llvm_ndarray_ty else {
-            return Err(format!("Expected struct type for `NDArray` type, got {llvm_ndarray_ty}"));
-        };
-
-        check_struct_type_matches_fields(
-            Self::fields(ctx, llvm_usize),
-            llvm_ndarray_ty,
-            "NDArray",
-            &[],
-        )
-    }
-
-    /// Returns an instance of [`StructFields`] containing all field accessors for this type.
-    #[must_use]
-    fn fields(
-        ctx: impl AsContextRef<'ctx>,
-        llvm_usize: IntType<'ctx>,
-    ) -> NDArrayStructFields<'ctx> {
-        NDArrayStructFields::new(ctx, llvm_usize)
-    }
-
-    /// See [`NDArrayType::fields`].
-    // TODO: Move this into e.g. StructProxyType
-    #[must_use]
-    pub fn get_fields(&self, ctx: impl AsContextRef<'ctx>) -> NDArrayStructFields<'ctx> {
-        Self::fields(ctx, self.llvm_usize)
-    }
-
-    /// Creates an LLVM type corresponding to the expected structure of an `NDArray`.
-    #[must_use]
-    fn llvm_type(ctx: &'ctx Context, llvm_usize: IntType<'ctx>) -> PointerType<'ctx> {
-        let field_tys =
-            Self::fields(ctx, llvm_usize).into_iter().map(|field| field.1).collect_vec();
-
-        ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
-    }
-
-    /// Creates an instance of [`NDArrayType`].
-    #[must_use]
-    pub fn new<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        dtype: BasicTypeEnum<'ctx>,
-        ndims: u64,
-    ) -> Self {
-        let llvm_usize = generator.get_size_type(ctx);
-        let llvm_ndarray = Self::llvm_type(ctx, llvm_usize);
-
-        NDArrayType { ty: llvm_ndarray, dtype, ndims, llvm_usize }
-    }
-
-    /// Creates an instance of [`NDArrayType`] as a result of a broadcast operation over one or more
-    /// `ndarray` operands.
-    #[must_use]
-    pub fn new_broadcast<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        dtype: BasicTypeEnum<'ctx>,
-        inputs: &[NDArrayType<'ctx>],
-    ) -> Self {
-        assert!(!inputs.is_empty());
-
-        Self::new(generator, ctx, dtype, inputs.iter().map(NDArrayType::ndims).max().unwrap())
-    }
-
-    /// Creates an instance of [`NDArrayType`] with `ndims` of 0.
-    #[must_use]
-    pub fn new_unsized<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        dtype: BasicTypeEnum<'ctx>,
-    ) -> Self {
-        let llvm_usize = generator.get_size_type(ctx);
-        let llvm_ndarray = Self::llvm_type(ctx, llvm_usize);
-
-        NDArrayType { ty: llvm_ndarray, dtype, ndims: 0, llvm_usize }
-    }
-
-    /// Creates an [`NDArrayType`] from a [unifier type][Type].
-    #[must_use]
-    pub fn from_unifier_type<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        ty: Type,
-    ) -> Self {
-        let (dtype, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
-
-        let llvm_dtype = ctx.get_llvm_type(generator, dtype);
-        let llvm_usize = generator.get_size_type(ctx.ctx);
-        let ndims = extract_ndims(&ctx.unifier, ndims);
-
-        NDArrayType {
-            ty: Self::llvm_type(ctx.ctx, llvm_usize),
-            dtype: llvm_dtype,
-            ndims,
-            llvm_usize,
-        }
-    }
-
-    /// Creates an [`NDArrayType`] from a [`PointerType`] representing an `NDArray`.
-    #[must_use]
-    pub fn from_type(
-        ptr_ty: PointerType<'ctx>,
-        dtype: BasicTypeEnum<'ctx>,
-        ndims: u64,
-        llvm_usize: IntType<'ctx>,
-    ) -> Self {
-        debug_assert!(Self::is_representable(ptr_ty, llvm_usize).is_ok());
-
-        NDArrayType { ty: ptr_ty, dtype, ndims, llvm_usize }
-    }
-
-    /// Returns the type of the `size` field of this `ndarray` type.
-    #[must_use]
-    pub fn size_type(&self) -> IntType<'ctx> {
-        self.llvm_usize
-    }
-
-    /// Returns the element type of this `ndarray` type.
-    #[must_use]
-    pub fn element_type(&self) -> BasicTypeEnum<'ctx> {
-        self.dtype
-    }
-
-    /// Returns the number of dimensions of this `ndarray` type.
-    #[must_use]
-    pub fn ndims(&self) -> u64 {
-        self.ndims
-    }
-
-    /// Allocates an instance of [`NDArrayValue`] as if by calling `alloca` on the base type.
-    ///
-    /// See [`ProxyType::raw_alloca`].
-    #[must_use]
-    pub fn alloca(
-        &self,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
-            self.raw_alloca(ctx, name),
-            self.dtype,
-            self.ndims,
-            self.llvm_usize,
-            name,
-        )
-    }
-
-    /// Allocates an instance of [`NDArrayValue`] as if by calling `alloca` on the base type.
-    ///
-    /// See [`ProxyType::raw_alloca_var`].
-    #[must_use]
-    pub fn alloca_var<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
-            self.raw_alloca_var(generator, ctx, name),
-            self.dtype,
-            self.ndims,
-            self.llvm_usize,
-            name,
-        )
-    }
-
-    /// Allocates an [`NDArrayValue`] on the stack and initializes all fields as follows:
-    ///
-    /// - `data`: uninitialized.
-    /// - `itemsize`: set to the size of `self.dtype`.
-    /// - `ndims`: set to the value of  `ndims`.
-    /// - `shape`: allocated on the stack with an array of length `ndims` with uninitialized values.
-    /// - `strides`: allocated on the stack with an array of length `ndims` with uninitialized
-    ///   values.
-    #[must_use]
-    fn construct_impl<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        ndims: IntValue<'ctx>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        let ndarray = self.alloca_var(generator, ctx, name);
-
-        let itemsize = ctx
-            .builder
-            .build_int_truncate_or_bit_cast(self.dtype.size_of().unwrap(), self.llvm_usize, "")
-            .unwrap();
-        ndarray.store_itemsize(ctx, generator, itemsize);
-
-        ndarray.store_ndims(ctx, generator, ndims);
-
-        ndarray.create_shape(ctx, self.llvm_usize, ndims);
-        ndarray.create_strides(ctx, self.llvm_usize, ndims);
-
-        ndarray
-    }
-
-    /// Allocate an [`NDArrayValue`] on the stack using `dtype` and `ndims` of this [`NDArrayType`]
-    /// instance.
-    ///
-    /// The returned ndarray's content will be:
-    /// - `data`: uninitialized.
-    /// - `itemsize`: set to the size of `dtype`.
-    /// - `ndims`: set to the value of `self.ndims`.
-    /// - `shape`: allocated on the stack with an array of length `ndims` with uninitialized values.
-    /// - `strides`: allocated on the stack with an array of length `ndims` with uninitialized
-    ///   values.
-    #[must_use]
-    pub fn construct_uninitialized<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        let ndims = self.llvm_usize.const_int(self.ndims, false);
-
-        self.construct_impl(generator, ctx, ndims, name)
-    }
-
-    /// Convenience function. Allocate an [`NDArrayValue`] with a statically known shape.
-    ///
-    /// The returned [`NDArrayValue`]'s `data` and `strides` are uninitialized.
-    #[must_use]
-    pub fn construct_const_shape<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        shape: &[u64],
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        assert_eq!(shape.len() as u64, self.ndims);
-
-        let ndarray = Self::new(generator, ctx.ctx, self.dtype, shape.len() as u64)
-            .construct_uninitialized(generator, ctx, name);
-
-        let llvm_usize = generator.get_size_type(ctx.ctx);
-
-        // Write shape
-        let ndarray_shape = ndarray.shape();
-        for (i, dim) in shape.iter().enumerate() {
-            let dim = llvm_usize.const_int(*dim, false);
-            unsafe {
-                ndarray_shape.set_typed_unchecked(
-                    ctx,
-                    generator,
-                    &llvm_usize.const_int(i as u64, false),
-                    dim,
-                );
-            }
-        }
-
-        ndarray
-    }
-
-    /// Convenience function. Allocate an [`NDArrayValue`] with a dynamically known shape.
-    ///
-    /// The returned [`NDArrayValue`]'s `data` and `strides` are uninitialized.
-    #[must_use]
-    pub fn construct_dyn_shape<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        shape: &[IntValue<'ctx>],
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        assert_eq!(shape.len() as u64, self.ndims);
-
-        let ndarray = Self::new(generator, ctx.ctx, self.dtype, shape.len() as u64)
-            .construct_uninitialized(generator, ctx, name);
-
-        let llvm_usize = generator.get_size_type(ctx.ctx);
-
-        // Write shape
-        let ndarray_shape = ndarray.shape();
-        for (i, dim) in shape.iter().enumerate() {
-            assert_eq!(
-                dim.get_type(),
-                llvm_usize,
-                "Expected {} but got {}",
-                llvm_usize.print_to_string(),
-                dim.get_type().print_to_string()
-            );
-            unsafe {
-                ndarray_shape.set_typed_unchecked(
-                    ctx,
-                    generator,
-                    &llvm_usize.const_int(i as u64, false),
-                    *dim,
-                );
-            }
-        }
-
-        ndarray
-    }
-
-    /// Create an unsized ndarray to contain `value`.
-    #[must_use]
-    pub fn construct_unsized<G: CodeGenerator + ?Sized>(
-        &self,
-        generator: &mut G,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        value: &impl BasicValue<'ctx>,
-        name: Option<&'ctx str>,
-    ) -> NDArrayValue<'ctx> {
-        let value = value.as_basic_value_enum();
-
-        assert_eq!(value.get_type(), self.dtype);
-        assert_eq!(self.ndims, 0);
-
-        // We have to put the value on the stack to get a data pointer.
-        let data = ctx.builder.build_alloca(value.get_type(), "construct_unsized").unwrap();
-        ctx.builder.build_store(data, value).unwrap();
-        let data = ctx
-            .builder
-            .build_pointer_cast(data, ctx.ctx.i8_type().ptr_type(AddressSpace::default()), "")
-            .unwrap();
-
-        let ndarray = Self::new_unsized(generator, ctx.ctx, value.get_type())
-            .construct_uninitialized(generator, ctx, name);
-        ctx.builder.build_store(ndarray.ptr_to_data(ctx), data).unwrap();
-        ndarray
-    }
-
-    /// Converts an existing value into a [`NDArrayValue`].
-    #[must_use]
-    pub fn map_value(
-        &self,
-        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
-        name: Option<&'ctx str>,
-    ) -> <Self as ProxyType<'ctx>>::Value {
-        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
-            value,
-            self.dtype,
-            self.ndims,
-            self.llvm_usize,
-            name,
-        )
-    }
-}
-
-impl<'ctx> ProxyType<'ctx> for NDArrayType<'ctx> {
-    type Base = PointerType<'ctx>;
-    type Value = NDArrayValue<'ctx>;
-
-    fn is_type<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        llvm_ty: impl BasicType<'ctx>,
-    ) -> Result<(), String> {
-        if let BasicTypeEnum::PointerType(ty) = llvm_ty.as_basic_type_enum() {
-            <Self as ProxyType<'ctx>>::is_representable(generator, ctx, ty)
-        } else {
-            Err(format!("Expected pointer type, got {llvm_ty:?}"))
-        }
-    }
-
-    fn is_representable<G: CodeGenerator + ?Sized>(
-        generator: &G,
-        ctx: &'ctx Context,
-        llvm_ty: Self::Base,
-    ) -> Result<(), String> {
-        Self::is_representable(llvm_ty, generator.get_size_type(ctx))
-    }
-
-    fn alloca_type(&self) -> impl BasicType<'ctx> {
-        self.as_base_type().get_element_type().into_struct_type()
-    }
-
-    fn as_base_type(&self) -> Self::Base {
-        self.ty
-    }
-}
-
-impl<'ctx> From<NDArrayType<'ctx>> for PointerType<'ctx> {
-    fn from(value: NDArrayType<'ctx>) -> Self {
-        value.as_base_type()
-    }
-}