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Author SHA1 Message Date
lyken e719d9396d asd 2024-07-11 00:34:06 +08:00
lyken 27f2e8b391 core: irrt general numpy broadcasting 2024-07-10 20:10:14 +08:00
lyken 5f4c406b37 core: irrt general numpy slicing 2024-07-10 20:10:14 +08:00
lyken 31ab9675ca core: more irrt 2024-07-10 20:10:14 +08:00
lyken 5fd5d65377 core: build.rs rewrite regex to capture `= type` 2024-07-10 20:10:14 +08:00
lyken 01042aecfb core: move irrt c++ sources to /nac3core/irrt 2024-07-10 20:10:14 +08:00
lyken 8754f252f6 core: IRRT -Werror=return-type 2024-07-10 20:10:14 +08:00
lyken 17207a4ebe core: add irrt_test 2024-07-10 20:10:14 +08:00
lyken e3a4675fc6 core: comment out numpy 2024-07-10 20:10:05 +08:00
105 changed files with 8667 additions and 12216 deletions

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1
.gitignore vendored
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@ -1,4 +1,3 @@
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@ -8,17 +8,17 @@ repos:
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types: [file, rust]
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description: Runs cargo clippy on the codebase.
args: [develop, -c, cargo, clippy, --tests]
args: [clippy, --tests]

443
Cargo.lock generated
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@ -774,7 +749,7 @@ dependencies = [
"phf_shared 0.11.2",
"proc-macro2",
"quote",
"syn 2.0.85",
"syn 2.0.70",
]
[[package]]
@ -803,18 +778,15 @@ checksum = "5be167a7af36ee22fe3115051bc51f6e6c7054c9348e28deb4f49bd6f705a315"
[[package]]
name = "portable-atomic"
version = "1.9.0"
version = "1.6.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "cc9c68a3f6da06753e9335d63e27f6b9754dd1920d941135b7ea8224f141adb2"
checksum = "7170ef9988bc169ba16dd36a7fa041e5c4cbeb6a35b76d4c03daded371eae7c0"
[[package]]
name = "ppv-lite86"
version = "0.2.20"
version = "0.2.17"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "77957b295656769bb8ad2b6a6b09d897d94f05c41b069aede1fcdaa675eaea04"
dependencies = [
"zerocopy",
]
checksum = "5b40af805b3121feab8a3c29f04d8ad262fa8e0561883e7653e024ae4479e6de"
[[package]]
name = "precomputed-hash"
@ -824,9 +796,9 @@ checksum = "925383efa346730478fb4838dbe9137d2a47675ad789c546d150a6e1dd4ab31c"
[[package]]
name = "proc-macro2"
version = "1.0.89"
version = "1.0.86"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "f139b0662de085916d1fb67d2b4169d1addddda1919e696f3252b740b629986e"
checksum = "5e719e8df665df0d1c8fbfd238015744736151d4445ec0836b8e628aae103b77"
dependencies = [
"unicode-ident",
]
@ -878,7 +850,7 @@ dependencies = [
"proc-macro2",
"pyo3-macros-backend",
"quote",
"syn 2.0.85",
"syn 2.0.70",
]
[[package]]
@ -891,14 +863,14 @@ dependencies = [
"proc-macro2",
"pyo3-build-config",
"quote",
"syn 2.0.85",
"syn 2.0.70",
]
[[package]]
name = "quote"
version = "1.0.37"
version = "1.0.36"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "b5b9d34b8991d19d98081b46eacdd8eb58c6f2b201139f7c5f643cc155a633af"
checksum = "0fa76aaf39101c457836aec0ce2316dbdc3ab723cdda1c6bd4e6ad4208acaca7"
dependencies = [
"proc-macro2",
]
@ -955,18 +927,29 @@ dependencies = [
[[package]]
name = "redox_syscall"
version = "0.5.7"
version = "0.5.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "9b6dfecf2c74bce2466cabf93f6664d6998a69eb21e39f4207930065b27b771f"
checksum = "c82cf8cff14456045f55ec4241383baeff27af886adb72ffb2162f99911de0fd"
dependencies = [
"bitflags",
]
[[package]]
name = "regex"
version = "1.11.1"
name = "redox_users"
version = "0.4.5"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "b544ef1b4eac5dc2db33ea63606ae9ffcfac26c1416a2806ae0bf5f56b201191"
checksum = "bd283d9651eeda4b2a83a43c1c91b266c40fd76ecd39a50a8c630ae69dc72891"
dependencies = [
"getrandom",
"libredox",
"thiserror",
]
[[package]]
name = "regex"
version = "1.10.5"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "b91213439dad192326a0d7c6ee3955910425f441d7038e0d6933b0aec5c4517f"
dependencies = [
"aho-corasick",
"memchr",
@ -976,9 +959,9 @@ dependencies = [
[[package]]
name = "regex-automata"
version = "0.4.8"
version = "0.4.7"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "368758f23274712b504848e9d5a6f010445cc8b87a7cdb4d7cbee666c1288da3"
checksum = "38caf58cc5ef2fed281f89292ef23f6365465ed9a41b7a7754eb4e26496c92df"
dependencies = [
"aho-corasick",
"memchr",
@ -987,9 +970,9 @@ dependencies = [
[[package]]
name = "regex-syntax"
version = "0.8.5"
version = "0.8.4"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "2b15c43186be67a4fd63bee50d0303afffcef381492ebe2c5d87f324e1b8815c"
checksum = "7a66a03ae7c801facd77a29370b4faec201768915ac14a721ba36f20bc9c209b"
[[package]]
name = "runkernel"
@ -1000,22 +983,22 @@ dependencies = [
[[package]]
name = "rustix"
version = "0.38.38"
version = "0.38.34"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "aa260229e6538e52293eeb577aabd09945a09d6d9cc0fc550ed7529056c2e32a"
checksum = "70dc5ec042f7a43c4a73241207cecc9873a06d45debb38b329f8541d85c2730f"
dependencies = [
"bitflags",
"errno",
"libc",
"linux-raw-sys",
"windows-sys 0.52.0",
"windows-sys",
]
[[package]]
name = "rustversion"
version = "1.0.18"
version = "1.0.17"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0e819f2bc632f285be6d7cd36e25940d45b2391dd6d9b939e79de557f7014248"
checksum = "955d28af4278de8121b7ebeb796b6a45735dc01436d898801014aced2773a3d6"
[[package]]
name = "ryu"
@ -1046,32 +1029,31 @@ checksum = "61697e0a1c7e512e84a621326239844a24d8207b4669b41bc18b32ea5cbf988b"
[[package]]
name = "serde"
version = "1.0.214"
version = "1.0.204"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "f55c3193aca71c12ad7890f1785d2b73e1b9f63a0bbc353c08ef26fe03fc56b5"
checksum = "bc76f558e0cbb2a839d37354c575f1dc3fdc6546b5be373ba43d95f231bf7c12"
dependencies = [
"serde_derive",
]
[[package]]
name = "serde_derive"
version = "1.0.214"
version = "1.0.204"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "de523f781f095e28fa605cdce0f8307e451cc0fd14e2eb4cd2e98a355b147766"
checksum = "e0cd7e117be63d3c3678776753929474f3b04a43a080c744d6b0ae2a8c28e222"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.85",
"syn 2.0.70",
]
[[package]]
name = "serde_json"
version = "1.0.132"
version = "1.0.120"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "d726bfaff4b320266d395898905d0eba0345aae23b54aee3a737e260fd46db03"
checksum = "4e0d21c9a8cae1235ad58a00c11cb40d4b1e5c784f1ef2c537876ed6ffd8b7c5"
dependencies = [
"itoa",
"memchr",
"ryu",
"serde",
]
@ -1088,27 +1070,11 @@ dependencies = [
"yaml-rust",
]
[[package]]
name = "sha3"
version = "0.10.8"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "75872d278a8f37ef87fa0ddbda7802605cb18344497949862c0d4dcb291eba60"
dependencies = [
"digest",
"keccak",
]
[[package]]
name = "shlex"
version = "1.3.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0fda2ff0d084019ba4d7c6f371c95d8fd75ce3524c3cb8fb653a3023f6323e64"
[[package]]
name = "similar"
version = "2.6.0"
version = "2.5.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "1de1d4f81173b03af4c0cbed3c898f6bff5b870e4a7f5d6f4057d62a7a4b686e"
checksum = "fa42c91313f1d05da9b26f267f931cf178d4aba455b4c4622dd7355eb80c6640"
[[package]]
name = "siphasher"
@ -1168,7 +1134,7 @@ dependencies = [
"proc-macro2",
"quote",
"rustversion",
"syn 2.0.85",
"syn 2.0.70",
]
[[package]]
@ -1184,9 +1150,9 @@ dependencies = [
[[package]]
name = "syn"
version = "2.0.85"
version = "2.0.70"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "5023162dfcd14ef8f32034d8bcd4cc5ddc61ef7a247c024a33e24e1f24d21b56"
checksum = "2f0209b68b3613b093e0ec905354eccaedcfe83b8cb37cbdeae64026c3064c16"
dependencies = [
"proc-macro2",
"quote",
@ -1195,31 +1161,31 @@ dependencies = [
[[package]]
name = "target-lexicon"
version = "0.12.16"
version = "0.12.15"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "61c41af27dd6d1e27b1b16b489db798443478cef1f06a660c96db617ba5de3b1"
checksum = "4873307b7c257eddcb50c9bedf158eb669578359fb28428bef438fec8e6ba7c2"
[[package]]
name = "tempfile"
version = "3.13.0"
version = "3.10.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "f0f2c9fc62d0beef6951ccffd757e241266a2c833136efbe35af6cd2567dca5b"
checksum = "85b77fafb263dd9d05cbeac119526425676db3784113aa9295c88498cbf8bff1"
dependencies = [
"cfg-if",
"fastrand",
"once_cell",
"rustix",
"windows-sys 0.59.0",
"windows-sys",
]
[[package]]
name = "term"
version = "1.0.0"
version = "0.7.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "4df4175de05129f31b80458c6df371a15e7fc3fd367272e6bf938e5c351c7ea0"
checksum = "c59df8ac95d96ff9bede18eb7300b0fda5e5d8d90960e76f8e14ae765eedbf1f"
dependencies = [
"home",
"windows-sys 0.52.0",
"dirs-next",
"rustversion",
"winapi",
]
[[package]]
@ -1237,29 +1203,32 @@ dependencies = [
[[package]]
name = "thiserror"
version = "1.0.65"
version = "1.0.61"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "5d11abd9594d9b38965ef50805c5e469ca9cc6f197f883f717e0269a3057b3d5"
checksum = "c546c80d6be4bc6a00c0f01730c08df82eaa7a7a61f11d656526506112cc1709"
dependencies = [
"thiserror-impl",
]
[[package]]
name = "thiserror-impl"
version = "1.0.65"
version = "1.0.61"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "ae71770322cbd277e69d762a16c444af02aa0575ac0d174f0b9562d3b37f8602"
checksum = "46c3384250002a6d5af4d114f2845d37b57521033f30d5c3f46c4d70e1197533"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.85",
"syn 2.0.70",
]
[[package]]
name = "typenum"
version = "1.17.0"
name = "tiny-keccak"
version = "2.0.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "42ff0bf0c66b8238c6f3b578df37d0b7848e55df8577b3f74f92a69acceeb825"
checksum = "2c9d3793400a45f954c52e73d068316d76b6f4e36977e3fcebb13a2721e80237"
dependencies = [
"crunchy",
]
[[package]]
name = "unic-char-property"
@ -1315,27 +1284,27 @@ dependencies = [
[[package]]
name = "unicode-ident"
version = "1.0.13"
version = "1.0.12"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "e91b56cd4cadaeb79bbf1a5645f6b4f8dc5bde8834ad5894a8db35fda9efa1fe"
checksum = "3354b9ac3fae1ff6755cb6db53683adb661634f67557942dea4facebec0fee4b"
[[package]]
name = "unicode-width"
version = "0.1.14"
version = "0.1.13"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "7dd6e30e90baa6f72411720665d41d89b9a3d039dc45b8faea1ddd07f617f6af"
checksum = "0336d538f7abc86d282a4189614dfaa90810dfc2c6f6427eaf88e16311dd225d"
[[package]]
name = "unicode-xid"
version = "0.2.6"
version = "0.2.4"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "ebc1c04c71510c7f702b52b7c350734c9ff1295c464a03335b00bb84fc54f853"
checksum = "f962df74c8c05a667b5ee8bcf162993134c104e96440b663c8daa176dc772d8c"
[[package]]
name = "unicode_names2"
version = "1.3.0"
version = "1.2.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "d1673eca9782c84de5f81b82e4109dcfb3611c8ba0d52930ec4a9478f547b2dd"
checksum = "addeebf294df7922a1164f729fb27ebbbcea99cc32b3bf08afab62757f707677"
dependencies = [
"phf",
"unicode_names2_generator",
@ -1343,9 +1312,9 @@ dependencies = [
[[package]]
name = "unicode_names2_generator"
version = "1.3.0"
version = "1.2.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "b91e5b84611016120197efd7dc93ef76774f4e084cd73c9fb3ea4a86c570c56e"
checksum = "f444b8bba042fe3c1251ffaca35c603f2dc2ccc08d595c65a8c4f76f3e8426c0"
dependencies = [
"getopts",
"log",
@ -1367,9 +1336,9 @@ checksum = "06abde3611657adf66d383f00b093d7faecc7fa57071cce2578660c9f1010821"
[[package]]
name = "version_check"
version = "0.9.5"
version = "0.9.4"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0b928f33d975fc6ad9f86c8f283853ad26bdd5b10b7f1542aa2fa15e2289105a"
checksum = "49874b5167b65d7193b8aba1567f5c7d93d001cafc34600cee003eda787e483f"
[[package]]
name = "walkdir"
@ -1388,14 +1357,36 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "9c8d87e72b64a3b4db28d11ce29237c246188f4f51057d65a7eab63b7987e423"
[[package]]
name = "winapi-util"
version = "0.1.9"
name = "winapi"
version = "0.3.9"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "cf221c93e13a30d793f7645a0e7762c55d169dbb0a49671918a2319d289b10bb"
checksum = "5c839a674fcd7a98952e593242ea400abe93992746761e38641405d28b00f419"
dependencies = [
"windows-sys 0.59.0",
"winapi-i686-pc-windows-gnu",
"winapi-x86_64-pc-windows-gnu",
]
[[package]]
name = "winapi-i686-pc-windows-gnu"
version = "0.4.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "ac3b87c63620426dd9b991e5ce0329eff545bccbbb34f3be09ff6fb6ab51b7b6"
[[package]]
name = "winapi-util"
version = "0.1.8"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "4d4cc384e1e73b93bafa6fb4f1df8c41695c8a91cf9c4c64358067d15a7b6c6b"
dependencies = [
"windows-sys",
]
[[package]]
name = "winapi-x86_64-pc-windows-gnu"
version = "0.4.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "712e227841d057c1ee1cd2fb22fa7e5a5461ae8e48fa2ca79ec42cfc1931183f"
[[package]]
name = "windows-sys"
version = "0.52.0"
@ -1405,15 +1396,6 @@ dependencies = [
"windows-targets",
]
[[package]]
name = "windows-sys"
version = "0.59.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "1e38bc4d79ed67fd075bcc251a1c39b32a1776bbe92e5bef1f0bf1f8c531853b"
dependencies = [
"windows-targets",
]
[[package]]
name = "windows-targets"
version = "0.52.6"
@ -1493,7 +1475,6 @@ version = "0.7.35"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "1b9b4fd18abc82b8136838da5d50bae7bdea537c574d8dc1a34ed098d6c166f0"
dependencies = [
"byteorder",
"zerocopy-derive",
]
@ -1505,5 +1486,5 @@ checksum = "fa4f8080344d4671fb4e831a13ad1e68092748387dfc4f55e356242fae12ce3e"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.85",
"syn 2.0.70",
]

View File

@ -2,11 +2,11 @@
"nodes": {
"nixpkgs": {
"locked": {
"lastModified": 1727348695,
"narHash": "sha256-J+PeFKSDV+pHL7ukkfpVzCOO7mBSrrpJ3svwBFABbhI=",
"lastModified": 1720418205,
"narHash": "sha256-cPJoFPXU44GlhWg4pUk9oUPqurPlCFZ11ZQPk21GTPU=",
"owner": "NixOS",
"repo": "nixpkgs",
"rev": "1925c603f17fc89f4c8f6bf6f631a802ad85d784",
"rev": "655a58a72a6601292512670343087c2d75d859c1",
"type": "github"
},
"original": {

View File

@ -6,7 +6,6 @@
outputs = { self, nixpkgs }:
let
pkgs = import nixpkgs { system = "x86_64-linux"; };
pkgs32 = import nixpkgs { system = "i686-linux"; };
in rec {
packages.x86_64-linux = rec {
llvm-nac3 = pkgs.callPackage ./nix/llvm {};
@ -14,24 +13,9 @@
''
mkdir -p $out/bin
ln -s ${pkgs.llvmPackages_14.clang-unwrapped}/bin/clang $out/bin/clang-irrt
ln -s ${pkgs.llvmPackages_14.clang}/bin/clang $out/bin/clang-irrt-test
ln -s ${pkgs.llvmPackages_14.llvm.out}/bin/llvm-as $out/bin/llvm-as-irrt
'';
demo-linalg-stub = pkgs.rustPlatform.buildRustPackage {
name = "demo-linalg-stub";
src = ./nac3standalone/demo/linalg;
cargoLock = {
lockFile = ./nac3standalone/demo/linalg/Cargo.lock;
};
doCheck = false;
};
demo-linalg-stub32 = pkgs32.rustPlatform.buildRustPackage {
name = "demo-linalg-stub32";
src = ./nac3standalone/demo/linalg;
cargoLock = {
lockFile = ./nac3standalone/demo/linalg/Cargo.lock;
};
doCheck = false;
};
nac3artiq = pkgs.python3Packages.toPythonModule (
pkgs.rustPlatform.buildRustPackage rec {
name = "nac3artiq";
@ -40,8 +24,9 @@
cargoLock = {
lockFile = ./Cargo.lock;
};
cargoTestFlags = [ "--features" "test" ];
passthru.cargoLock = cargoLock;
nativeBuildInputs = [ pkgs.python3 (pkgs.wrapClangMulti pkgs.llvmPackages_14.clang) llvm-tools-irrt pkgs.llvmPackages_14.llvm.out llvm-nac3 ];
nativeBuildInputs = [ pkgs.python3 pkgs.llvmPackages_14.clang llvm-tools-irrt pkgs.llvmPackages_14.llvm.out llvm-nac3 ];
buildInputs = [ pkgs.python3 llvm-nac3 ];
checkInputs = [ (pkgs.python3.withPackages(ps: [ ps.numpy ps.scipy ])) ];
checkPhase =
@ -49,9 +34,7 @@
echo "Checking nac3standalone demos..."
pushd nac3standalone/demo
patchShebangs .
export DEMO_LINALG_STUB=${demo-linalg-stub}/lib/liblinalg.a
export DEMO_LINALG_STUB32=${demo-linalg-stub32}/lib/liblinalg.a
./check_demos.sh -i686
./check_demos.sh
popd
echo "Running Cargo tests..."
cargoCheckHook
@ -168,7 +151,7 @@
buildInputs = with pkgs; [
# build dependencies
packages.x86_64-linux.llvm-nac3
(pkgs.wrapClangMulti llvmPackages_14.clang) llvmPackages_14.llvm.out # for running nac3standalone demos
llvmPackages_14.clang llvmPackages_14.llvm.out # for running nac3standalone demos
packages.x86_64-linux.llvm-tools-irrt
cargo
rustc
@ -180,12 +163,10 @@
clippy
pre-commit
rustfmt
rust-analyzer
];
shellHook =
''
export DEMO_LINALG_STUB=${packages.x86_64-linux.demo-linalg-stub}/lib/liblinalg.a
export DEMO_LINALG_STUB32=${packages.x86_64-linux.demo-linalg-stub32}/lib/liblinalg.a
'';
# https://nixos.wiki/wiki/Rust#Shell.nix_example
RUST_SRC_PATH = "${pkgs.rust.packages.stable.rustPlatform.rustLibSrc}";
};
devShells.x86_64-linux.msys2 = pkgs.mkShell {
name = "nac3-dev-shell-msys2";

View File

@ -12,10 +12,15 @@ crate-type = ["cdylib"]
itertools = "0.13"
pyo3 = { version = "0.21", features = ["extension-module", "gil-refs"] }
parking_lot = "0.12"
tempfile = "3.13"
tempfile = "3.10"
nac3parser = { path = "../nac3parser" }
nac3core = { path = "../nac3core" }
nac3ld = { path = "../nac3ld" }
[dependencies.inkwell]
version = "0.4"
default-features = false
features = ["llvm14-0", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]
[features]
init-llvm-profile = []
no-escape-analysis = ["nac3core/no-escape-analysis"]

View File

@ -1,24 +0,0 @@
from min_artiq import *
from numpy import int32
@nac3
class EmptyList:
core: KernelInvariant[Core]
def __init__(self):
self.core = Core()
@rpc
def get_empty(self) -> list[int32]:
return []
@kernel
def run(self):
a: list[int32] = self.get_empty()
if a != []:
raise ValueError
if __name__ == "__main__":
EmptyList().run()

View File

@ -112,15 +112,10 @@ def extern(function):
register_function(function)
return function
def rpc(arg=None, flags={}):
"""Decorates a function or method to be executed on the host interpreter."""
if arg is None:
def inner_decorator(function):
return rpc(function, flags)
return inner_decorator
register_function(arg)
return arg
def rpc(function):
"""Decorates a function declaration defined by the core device runtime."""
register_function(function)
return function
def kernel(function_or_method):
"""Decorates a function or method to be executed on the core device."""

View File

@ -1,26 +0,0 @@
from min_artiq import *
from numpy import ndarray, zeros as np_zeros
@nac3
class StrFail:
core: KernelInvariant[Core]
def __init__(self):
self.core = Core()
@kernel
def hello(self, arg: str):
pass
@kernel
def consume_ndarray(self, arg: ndarray[str, 1]):
pass
def run(self):
self.hello("world")
self.consume_ndarray(np_zeros([10], dtype=str))
if __name__ == "__main__":
StrFail().run()

File diff suppressed because it is too large Load Diff

View File

@ -16,65 +16,63 @@
clippy::wildcard_imports
)]
use std::{
collections::{HashMap, HashSet},
fs,
io::Write,
process::Command,
rc::Rc,
sync::Arc,
};
use std::collections::{HashMap, HashSet};
use std::fs;
use std::io::Write;
use std::process::Command;
use std::rc::Rc;
use std::sync::Arc;
use itertools::Itertools;
use parking_lot::{Mutex, RwLock};
use pyo3::{
create_exception, exceptions,
prelude::*,
types::{PyBytes, PyDict, PySet},
use inkwell::{
memory_buffer::MemoryBuffer,
module::{Linkage, Module},
passes::PassBuilderOptions,
support::is_multithreaded,
targets::*,
OptimizationLevel,
};
use tempfile::{self, TempDir};
use itertools::Itertools;
use nac3core::codegen::{gen_func_impl, CodeGenLLVMOptions, CodeGenTargetMachineOptions};
use nac3core::toplevel::builtins::get_exn_constructor;
use nac3core::typecheck::typedef::{TypeEnum, Unifier, VarMap};
use nac3parser::{
ast::{ExprKind, Stmt, StmtKind, StrRef},
parser::parse_program,
};
use pyo3::create_exception;
use pyo3::prelude::*;
use pyo3::{exceptions, types::PyBytes, types::PyDict, types::PySet};
use parking_lot::{Mutex, RwLock};
use nac3core::{
codegen::{
concrete_type::ConcreteTypeStore, gen_func_impl, irrt::load_irrt, CodeGenLLVMOptions,
CodeGenTargetMachineOptions, CodeGenTask, WithCall, WorkerRegistry,
},
inkwell::{
context::Context,
memory_buffer::MemoryBuffer,
module::{Linkage, Module},
passes::PassBuilderOptions,
support::is_multithreaded,
targets::*,
OptimizationLevel,
},
nac3parser::{
ast::{Constant, ExprKind, Located, Stmt, StmtKind, StrRef},
parser::parse_program,
},
codegen::irrt::load_irrt,
codegen::{concrete_type::ConcreteTypeStore, CodeGenTask, WithCall, WorkerRegistry},
symbol_resolver::SymbolResolver,
toplevel::{
builtins::get_exn_constructor,
composer::{BuiltinFuncCreator, BuiltinFuncSpec, ComposerConfig, TopLevelComposer},
composer::{ComposerConfig, TopLevelComposer},
DefinitionId, GenCall, TopLevelDef,
},
typecheck::{
type_inferencer::PrimitiveStore,
typedef::{into_var_map, FunSignature, FuncArg, Type, TypeEnum, Unifier, VarMap},
},
typecheck::typedef::{FunSignature, FuncArg},
typecheck::{type_inferencer::PrimitiveStore, typedef::Type},
};
use nac3ld::Linker;
use codegen::{
attributes_writeback, gen_core_log, gen_rtio_log, rpc_codegen_callback, ArtiqCodeGenerator,
use tempfile::{self, TempDir};
use crate::codegen::attributes_writeback;
use crate::{
codegen::{rpc_codegen_callback, ArtiqCodeGenerator},
symbol_resolver::{DeferredEvaluationStore, InnerResolver, PythonHelper, Resolver},
};
use symbol_resolver::{DeferredEvaluationStore, InnerResolver, PythonHelper, Resolver};
use timeline::TimeFns;
mod codegen;
mod symbol_resolver;
mod timeline;
use timeline::TimeFns;
#[derive(PartialEq, Clone, Copy)]
enum Isa {
Host,
@ -128,7 +126,7 @@ struct Nac3 {
isa: Isa,
time_fns: &'static (dyn TimeFns + Sync),
primitive: PrimitiveStore,
builtins: Vec<BuiltinFuncSpec>,
builtins: Vec<(StrRef, FunSignature, Arc<GenCall>)>,
pyid_to_def: Arc<RwLock<HashMap<u64, DefinitionId>>>,
primitive_ids: PrimitivePythonId,
working_directory: TempDir,
@ -195,8 +193,10 @@ impl Nac3 {
body.retain(|stmt| {
if let StmtKind::FunctionDef { ref decorator_list, .. } = stmt.node {
decorator_list.iter().any(|decorator| {
if let Some(id) = decorator_id_string(decorator) {
id == "kernel" || id == "portable" || id == "rpc"
if let ExprKind::Name { id, .. } = decorator.node {
id.to_string() == "kernel"
|| id.to_string() == "portable"
|| id.to_string() == "rpc"
} else {
false
}
@ -209,8 +209,9 @@ impl Nac3 {
}
StmtKind::FunctionDef { ref decorator_list, .. } => {
decorator_list.iter().any(|decorator| {
if let Some(id) = decorator_id_string(decorator) {
id == "extern" || id == "kernel" || id == "portable" || id == "rpc"
if let ExprKind::Name { id, .. } = decorator.node {
let id = id.to_string();
id == "extern" || id == "portable" || id == "kernel" || id == "rpc"
} else {
false
}
@ -263,7 +264,7 @@ impl Nac3 {
arg_names.len(),
));
}
for (i, FuncArg { ty, default_value, name, .. }) in args.iter().enumerate() {
for (i, FuncArg { ty, default_value, name }) in args.iter().enumerate() {
let in_name = match arg_names.get(i) {
Some(n) => n,
None if default_value.is_none() => {
@ -299,64 +300,6 @@ impl Nac3 {
None
}
/// Returns a [`Vec`] of builtins that needs to be initialized during method compilation time.
fn get_lateinit_builtins() -> Vec<Box<BuiltinFuncCreator>> {
vec![
Box::new(|primitives, unifier| {
let arg_ty = unifier.get_fresh_var(Some("T".into()), None);
(
"core_log".into(),
FunSignature {
args: vec![FuncArg {
name: "arg".into(),
ty: arg_ty.ty,
default_value: None,
is_vararg: false,
}],
ret: primitives.none,
vars: into_var_map([arg_ty]),
},
Arc::new(GenCall::new(Box::new(move |ctx, obj, fun, args, generator| {
gen_core_log(ctx, &obj, fun, &args, generator)?;
Ok(None)
}))),
)
}),
Box::new(|primitives, unifier| {
let arg_ty = unifier.get_fresh_var(Some("T".into()), None);
(
"rtio_log".into(),
FunSignature {
args: vec![
FuncArg {
name: "channel".into(),
ty: primitives.str,
default_value: None,
is_vararg: false,
},
FuncArg {
name: "arg".into(),
ty: arg_ty.ty,
default_value: None,
is_vararg: false,
},
],
ret: primitives.none,
vars: into_var_map([arg_ty]),
},
Arc::new(GenCall::new(Box::new(move |ctx, obj, fun, args, generator| {
gen_rtio_log(ctx, &obj, fun, &args, generator)?;
Ok(None)
}))),
)
}),
]
}
fn compile_method<T>(
&self,
obj: &PyAny,
@ -369,7 +312,6 @@ impl Nac3 {
let size_t = self.isa.get_size_type();
let (mut composer, mut builtins_def, mut builtins_ty) = TopLevelComposer::new(
self.builtins.clone(),
Self::get_lateinit_builtins(),
ComposerConfig { kernel_ann: Some("Kernel"), kernel_invariant_ann: "KernelInvariant" },
size_t,
);
@ -446,6 +388,7 @@ impl Nac3 {
pyid_to_type: pyid_to_type.clone(),
primitive_ids: self.primitive_ids.clone(),
global_value_ids: global_value_ids.clone(),
class_names: Mutex::default(),
name_to_pyid: name_to_pyid.clone(),
module: module.clone(),
id_to_pyval: RwLock::default(),
@ -476,25 +419,9 @@ impl Nac3 {
match &stmt.node {
StmtKind::FunctionDef { decorator_list, .. } => {
if decorator_list
.iter()
.any(|decorator| decorator_id_string(decorator) == Some("rpc".to_string()))
{
store_fun
.call1(
py,
(
def_id.0.into_py(py),
module.getattr(py, name.to_string().as_str()).unwrap(),
),
)
.unwrap();
let is_async = decorator_list.iter().any(|decorator| {
decorator_get_flags(decorator)
.iter()
.any(|constant| *constant == Constant::Str("async".into()))
});
rpc_ids.push((None, def_id, is_async));
if decorator_list.iter().any(|decorator| matches!(decorator.node, ExprKind::Name { id, .. } if id == "rpc".into())) {
store_fun.call1(py, (def_id.0.into_py(py), module.getattr(py, name.to_string().as_str()).unwrap())).unwrap();
rpc_ids.push((None, def_id));
}
}
StmtKind::ClassDef { name, body, .. } => {
@ -502,26 +429,19 @@ impl Nac3 {
let class_obj = module.getattr(py, class_name.as_str()).unwrap();
for stmt in body {
if let StmtKind::FunctionDef { name, decorator_list, .. } = &stmt.node {
if decorator_list.iter().any(|decorator| {
decorator_id_string(decorator) == Some("rpc".to_string())
}) {
let is_async = decorator_list.iter().any(|decorator| {
decorator_get_flags(decorator)
.iter()
.any(|constant| *constant == Constant::Str("async".into()))
});
if decorator_list.iter().any(|decorator| matches!(decorator.node, ExprKind::Name { id, .. } if id == "rpc".into())) {
if name == &"__init__".into() {
return Err(CompileError::new_err(format!(
"compilation failed\n----------\nThe constructor of class {} should not be decorated with rpc decorator (at {})",
class_name, stmt.location
)));
}
rpc_ids.push((Some((class_obj.clone(), *name)), def_id, is_async));
rpc_ids.push((Some((class_obj.clone(), *name)), def_id));
}
}
}
}
_ => (),
_ => ()
}
let id = *name_to_pyid.get(&name).unwrap();
@ -560,6 +480,7 @@ impl Nac3 {
pyid_to_type: pyid_to_type.clone(),
primitive_ids: self.primitive_ids.clone(),
global_value_ids: global_value_ids.clone(),
class_names: Mutex::default(),
id_to_pyval: RwLock::default(),
id_to_primitive: RwLock::default(),
field_to_val: RwLock::default(),
@ -576,10 +497,6 @@ impl Nac3 {
.register_top_level(synthesized.pop().unwrap(), Some(resolver.clone()), "", false)
.unwrap();
// Process IRRT
let context = Context::create();
let irrt = load_irrt(&context, resolver.as_ref());
let fun_signature =
FunSignature { args: vec![], ret: self.primitive.none, vars: VarMap::new() };
let mut store = ConcreteTypeStore::new();
@ -617,12 +534,13 @@ impl Nac3 {
let top_level = Arc::new(composer.make_top_level_context());
{
let rpc_codegen = rpc_codegen_callback();
let defs = top_level.definitions.read();
for (class_data, id, is_async) in &rpc_ids {
for (class_data, id) in &rpc_ids {
let mut def = defs[id.0].write();
match &mut *def {
TopLevelDef::Function { codegen_callback, .. } => {
*codegen_callback = Some(rpc_codegen_callback(*is_async));
*codegen_callback = Some(rpc_codegen.clone());
}
TopLevelDef::Class { methods, .. } => {
let (class_def, method_name) = class_data.as_ref().unwrap();
@ -633,7 +551,7 @@ impl Nac3 {
if let TopLevelDef::Function { codegen_callback, .. } =
&mut *defs[id.0].write()
{
*codegen_callback = Some(rpc_codegen_callback(*is_async));
*codegen_callback = Some(rpc_codegen.clone());
store_fun
.call1(
py,
@ -648,11 +566,6 @@ impl Nac3 {
}
}
}
TopLevelDef::Variable { .. } => {
return Err(CompileError::new_err(String::from(
"Unsupported @rpc annotation on global variable",
)))
}
}
}
}
@ -712,9 +625,7 @@ impl Nac3 {
let buffer = buffer.as_slice().into();
membuffer.lock().push(buffer);
})));
let size_t = context
.ptr_sized_int_type(&self.get_llvm_target_machine().get_target_data(), None)
.get_bit_width();
let size_t = if self.isa == Isa::Host { 64 } else { 32 };
let num_threads = if is_multithreaded() { 4 } else { 1 };
let thread_names: Vec<String> = (0..num_threads).map(|_| "main".to_string()).collect();
let threads: Vec<_> = thread_names
@ -731,11 +642,8 @@ impl Nac3 {
let mut generator =
ArtiqCodeGenerator::new("attributes_writeback".to_string(), size_t, self.time_fns);
let context = Context::create();
let context = inkwell::context::Context::create();
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());
let builder = context.create_builder();
let (_, module, _) = gen_func_impl(
&context,
@ -754,7 +662,7 @@ impl Nac3 {
membuffer.lock().push(buffer);
});
// Link all modules into `main`.
let context = inkwell::context::Context::create();
let buffers = membuffers.lock();
let main = context
.create_module_from_ir(MemoryBuffer::create_from_memory_range(&buffers[0], "main"))
@ -783,7 +691,8 @@ impl Nac3 {
)
.unwrap();
main.link_in_module(irrt).map_err(|err| CompileError::new_err(err.to_string()))?;
main.link_in_module(load_irrt(&context))
.map_err(|err| CompileError::new_err(err.to_string()))?;
let mut function_iter = main.get_first_function();
while let Some(func) = function_iter {
@ -869,41 +778,6 @@ impl Nac3 {
}
}
/// Retrieves the Name.id from a decorator, supports decorators with arguments.
fn decorator_id_string(decorator: &Located<ExprKind>) -> Option<String> {
if let ExprKind::Name { id, .. } = decorator.node {
// Bare decorator
return Some(id.to_string());
} else if let ExprKind::Call { func, .. } = &decorator.node {
// Decorators that are calls (e.g. "@rpc()") have Call for the node,
// need to extract the id from within.
if let ExprKind::Name { id, .. } = func.node {
return Some(id.to_string());
}
}
None
}
/// Retrieves flags from a decorator, if any.
fn decorator_get_flags(decorator: &Located<ExprKind>) -> Vec<Constant> {
let mut flags = vec![];
if let ExprKind::Call { keywords, .. } = &decorator.node {
for keyword in keywords {
if keyword.node.arg != Some("flags".into()) {
continue;
}
if let ExprKind::Set { elts } = &keyword.node.value.node {
for elt in elts {
if let ExprKind::Constant { value, .. } = &elt.node {
flags.push(value.clone());
}
}
}
}
}
flags
}
fn link_with_lld(elf_filename: String, obj_filename: String) -> PyResult<()> {
let linker_args = vec![
"-shared".to_string(),
@ -973,7 +847,7 @@ impl Nac3 {
Isa::RiscV32IMA => &timeline::NOW_PINNING_TIME_FNS,
Isa::CortexA9 | Isa::Host => &timeline::EXTERN_TIME_FNS,
};
let (primitive, _) = TopLevelComposer::make_primitives(isa.get_size_type());
let primitive: PrimitiveStore = TopLevelComposer::make_primitives(isa.get_size_type()).0;
let builtins = vec![
(
"now_mu".into(),
@ -989,7 +863,6 @@ impl Nac3 {
name: "t".into(),
ty: primitive.int64,
default_value: None,
is_vararg: false,
}],
ret: primitive.none,
vars: VarMap::new(),
@ -1009,7 +882,6 @@ impl Nac3 {
name: "dt".into(),
ty: primitive.int64,
default_value: None,
is_vararg: false,
}],
ret: primitive.none,
vars: VarMap::new(),

View File

@ -1,30 +1,14 @@
use std::{
collections::{HashMap, HashSet},
sync::{
atomic::{AtomicBool, Ordering::Relaxed},
Arc,
},
use inkwell::{
types::{BasicType, BasicTypeEnum},
values::BasicValueEnum,
AddressSpace,
};
use itertools::Itertools;
use parking_lot::RwLock;
use pyo3::{
types::{PyDict, PyTuple},
PyAny, PyObject, PyResult, Python,
};
use nac3core::{
codegen::{
classes::{NDArrayType, ProxyType},
CodeGenContext, CodeGenerator,
},
inkwell::{
module::Linkage,
types::{BasicType, BasicTypeEnum},
values::BasicValueEnum,
AddressSpace,
},
nac3parser::ast::{self, StrRef},
symbol_resolver::{StaticValue, SymbolResolver, SymbolValue, ValueEnum},
toplevel::{
helper::PrimDef,
@ -36,8 +20,21 @@ use nac3core::{
typedef::{into_var_map, iter_type_vars, Type, TypeEnum, TypeVar, Unifier, VarMap},
},
};
use nac3parser::ast::{self, StrRef};
use parking_lot::{Mutex, RwLock};
use pyo3::{
types::{PyDict, PyTuple},
PyAny, PyObject, PyResult, Python,
};
use std::{
collections::{HashMap, HashSet},
sync::{
atomic::{AtomicBool, Ordering::Relaxed},
Arc,
},
};
use super::PrimitivePythonId;
use crate::PrimitivePythonId;
pub enum PrimitiveValue {
I32(i32),
@ -82,6 +79,7 @@ pub struct InnerResolver {
pub id_to_primitive: RwLock<HashMap<u64, PrimitiveValue>>,
pub field_to_val: RwLock<HashMap<ResolverField, Option<PyFieldHandle>>>,
pub global_value_ids: Arc<RwLock<HashMap<u64, PyObject>>>,
pub class_names: Mutex<HashMap<StrRef, Type>>,
pub pyid_to_def: Arc<RwLock<HashMap<u64, DefinitionId>>>,
pub pyid_to_type: Arc<RwLock<HashMap<u64, Type>>>,
pub primitive_ids: PrimitivePythonId,
@ -135,8 +133,6 @@ impl StaticValue for PythonValue {
format!("{}_const", self.id).as_str(),
);
global.set_constant(true);
// Set linkage of global to private to avoid name collisions
global.set_linkage(Linkage::Private);
global.set_initializer(&ctx.ctx.const_struct(
&[ctx.ctx.i32_type().const_int(u64::from(id), false).into()],
false,
@ -167,7 +163,7 @@ impl StaticValue for PythonValue {
PrimitiveValue::Bool(val) => {
ctx.ctx.i8_type().const_int(u64::from(*val), false).into()
}
PrimitiveValue::Str(val) => ctx.gen_string(generator, val).into(),
PrimitiveValue::Str(val) => ctx.ctx.const_string(val.as_bytes(), true).into(),
});
}
if let Some(global) = ctx.module.get_global(&self.id.to_string()) {
@ -355,7 +351,7 @@ impl InnerResolver {
Ok(Ok((ndarray, false)))
} else if ty_id == self.primitive_ids.tuple {
// do not handle type var param and concrete check here
Ok(Ok((unifier.add_ty(TypeEnum::TTuple { ty: vec![], is_vararg_ctx: false }), false)))
Ok(Ok((unifier.add_ty(TypeEnum::TTuple { ty: vec![] }), false)))
} else if ty_id == self.primitive_ids.option {
Ok(Ok((primitives.option, false)))
} else if ty_id == self.primitive_ids.none {
@ -559,10 +555,7 @@ impl InnerResolver {
Err(err) => return Ok(Err(err)),
_ => return Ok(Err("tuple type needs at least 1 type parameters".to_string()))
};
Ok(Ok((
unifier.add_ty(TypeEnum::TTuple { ty: args, is_vararg_ctx: false }),
true,
)))
Ok(Ok((unifier.add_ty(TypeEnum::TTuple { ty: args }), true)))
}
TypeEnum::TObj { params, obj_id, .. } => {
let subst = {
@ -804,9 +797,7 @@ impl InnerResolver {
.map(|elem| self.get_obj_type(py, elem, unifier, defs, primitives))
.collect();
let types = types?;
Ok(types.map(|types| {
unifier.add_ty(TypeEnum::TTuple { ty: types, is_vararg_ctx: false })
}))
Ok(types.map(|types| unifier.add_ty(TypeEnum::TTuple { ty: types })))
}
// special handling for option type since its class member layout in python side
// is special and cannot be mapped directly to a nac3 type as below
@ -981,7 +972,7 @@ impl InnerResolver {
} else if ty_id == self.primitive_ids.string || ty_id == self.primitive_ids.np_str_ {
let val: String = obj.extract().unwrap();
self.id_to_primitive.write().insert(id, PrimitiveValue::Str(val.clone()));
Ok(Some(ctx.gen_string(generator, val).into()))
Ok(Some(ctx.ctx.const_string(val.as_bytes(), true).into()))
} else if ty_id == self.primitive_ids.float || ty_id == self.primitive_ids.float64 {
let val: f64 = obj.extract().unwrap();
self.id_to_primitive.write().insert(id, PrimitiveValue::F64(val));
@ -1000,15 +991,8 @@ impl InnerResolver {
}
_ => unreachable!("must be list"),
};
let ty = ctx.get_llvm_type(generator, elem_ty);
let size_t = generator.get_size_type(ctx.ctx);
let ty = if len == 0
&& matches!(&*ctx.unifier.get_ty_immutable(elem_ty), TypeEnum::TVar { .. })
{
// The default type for zero-length lists of unknown element type is size_t
size_t.into()
} else {
ctx.get_llvm_type(generator, elem_ty)
};
let arr_ty = ctx
.ctx
.struct_type(&[ty.ptr_type(AddressSpace::default()).into(), size_t.into()], false);
@ -1212,9 +1196,7 @@ impl InnerResolver {
Ok(Some(ndarray.as_pointer_value().into()))
} else if ty_id == self.primitive_ids.tuple {
let expected_ty_enum = ctx.unifier.get_ty_immutable(expected_ty);
let TypeEnum::TTuple { ty, is_vararg_ctx: false } = expected_ty_enum.as_ref() else {
unreachable!()
};
let TypeEnum::TTuple { ty } = expected_ty_enum.as_ref() else { unreachable!() };
let tup_tys = ty.iter();
let elements: &PyTuple = obj.downcast()?;
@ -1470,7 +1452,6 @@ impl SymbolResolver for Resolver {
&self,
id: StrRef,
_: &mut CodeGenContext<'ctx, '_>,
_: &mut dyn CodeGenerator,
) -> Option<ValueEnum<'ctx>> {
let sym_value = {
let id_to_val = self.0.id_to_pyval.read();

View File

@ -1,12 +1,9 @@
use itertools::Either;
use nac3core::{
codegen::CodeGenContext,
inkwell::{
values::{BasicValueEnum, CallSiteValue},
AddressSpace, AtomicOrdering,
},
use inkwell::{
values::{BasicValueEnum, CallSiteValue},
AddressSpace, AtomicOrdering,
};
use itertools::Either;
use nac3core::codegen::CodeGenContext;
/// Functions for manipulating the timeline.
pub trait TimeFns {
@ -34,7 +31,7 @@ impl TimeFns for NowPinningTimeFns64 {
.unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
let now_hiptr = ctx
.builder
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.map(BasicValueEnum::into_pointer_value)
.unwrap();
@ -83,7 +80,7 @@ impl TimeFns for NowPinningTimeFns64 {
.unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
let now_hiptr = ctx
.builder
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.map(BasicValueEnum::into_pointer_value)
.unwrap();
@ -112,7 +109,7 @@ impl TimeFns for NowPinningTimeFns64 {
.unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
let now_hiptr = ctx
.builder
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.map(BasicValueEnum::into_pointer_value)
.unwrap();
@ -210,7 +207,7 @@ impl TimeFns for NowPinningTimeFns {
.unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
let now_hiptr = ctx
.builder
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.map(BasicValueEnum::into_pointer_value)
.unwrap();
@ -261,7 +258,7 @@ impl TimeFns for NowPinningTimeFns {
let time_lo = ctx.builder.build_int_truncate(time, i32_type, "time.lo").unwrap();
let now_hiptr = ctx
.builder
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.map(BasicValueEnum::into_pointer_value)
.unwrap();

View File

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

View File

@ -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>> =
LazyLock::new(|| Mutex::new(StringInterner::with_hasher(FxBuildHasher::default())));
lazy_static! {
static ref INTERNER: Mutex<Interner> =
Mutex::new(StringInterner::with_hasher(FxBuildHasher::default()));
}
thread_local! {
static LOCAL_INTERNER: RefCell<HashMap<String, StrRef>> = RefCell::default();

View File

@ -14,6 +14,9 @@
clippy::wildcard_imports
)]
#[macro_use]
extern crate lazy_static;
mod ast_gen;
mod constant;
#[cfg(feature = "fold")]

View File

@ -1,26 +1,26 @@
[features]
test = []
[package]
name = "nac3core"
version = "0.1.0"
authors = ["M-Labs"]
edition = "2021"
[features]
no-escape-analysis = []
[dependencies]
itertools = "0.13"
crossbeam = "0.8"
indexmap = "2.6"
indexmap = "2.2"
parking_lot = "0.12"
rayon = "1.10"
rayon = "1.8"
nac3parser = { path = "../nac3parser" }
strum = "0.26"
strum_macros = "0.26"
strum = "0.26.2"
strum_macros = "0.26.4"
[dependencies.inkwell]
version = "0.5"
version = "0.4"
default-features = false
features = ["llvm14-0-prefer-dynamic", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]
features = ["llvm14-0", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]
[dev-dependencies]
test-case = "1.2.0"

View File

@ -1,3 +1,4 @@
use regex::Regex;
use std::{
env,
fs::File,
@ -6,53 +7,39 @@ use std::{
process::{Command, Stdio},
};
use regex::Regex;
fn main() {
let out_dir = env::var("OUT_DIR").unwrap();
let out_dir = Path::new(&out_dir);
let irrt_dir = Path::new("irrt");
fn compile_irrt(irrt_dir: &Path, out_dir: &Path) {
let irrt_cpp_path = irrt_dir.join("irrt.cpp");
/*
* HACK: Sadly, clang doesn't let us emit generic LLVM bitcode.
* Compiling for WASM32 and filtering the output with regex is the closest we can get.
*/
let mut flags: Vec<&str> = vec![
let flags: &[&str] = &[
"--target=wasm32",
irrt_cpp_path.to_str().unwrap(),
"-x",
"c++",
"-std=c++20",
"-fno-discard-value-names",
"-fno-exceptions",
"-fno-rtti",
match env::var("PROFILE").as_deref() {
Ok("debug") => "-O0",
Ok("release") => "-O3",
flavor => panic!("Unknown or missing build flavor {flavor:?}"),
},
"-emit-llvm",
"-S",
"-Wall",
"-Wextra",
"-o",
"-",
"-Werror=return-type",
"-I",
irrt_dir.to_str().unwrap(),
irrt_cpp_path.to_str().unwrap(),
"-o",
"-",
];
match env::var("PROFILE").as_deref() {
Ok("debug") => {
flags.push("-O0");
flags.push("-DIRRT_DEBUG_ASSERT");
}
Ok("release") => {
flags.push("-O3");
}
flavor => panic!("Unknown or missing build flavor {flavor:?}"),
}
println!("cargo:rerun-if-changed={}", out_dir.to_str().unwrap());
// Tell Cargo to rerun if any file under `irrt_dir` (recursive) changes
println!("cargo:rerun-if-changed={}", irrt_dir.to_str().unwrap());
// Compile IRRT and capture the LLVM IR output
let output = Command::new("clang-irrt")
.args(flags)
.output()
@ -66,17 +53,11 @@ fn main() {
let output = std::str::from_utf8(&output.stdout).unwrap().replace("\r\n", "\n");
let mut filtered_output = String::with_capacity(output.len());
// Filter out irrelevant IR
//
// Regex:
// - `(?ms:^define.*?\}$)` captures LLVM `define` blocks
// - `(?m:^declare.*?$)` captures LLVM `declare` lines
// - `(?m:^%.+?=\s*type\s*\{.+?\}$)` captures LLVM `type` declarations
// - `(?m:^@.+?=.+$)` captures global constants
let regex_filter = Regex::new(
r"(?ms:^define.*?\}$)|(?m:^declare.*?$)|(?m:^%.+?=\s*type\s*\{.+?\}$)|(?m:^@.+?=.+$)",
)
.unwrap();
// (?ms:^define.*?\}$) to capture `define` blocks
// (?m:^declare.*?$) to capture `declare` blocks
// (?m:^%.+?=\s*type\s*\{.+?\}$) to capture `type` declarations
let regex_filter =
Regex::new(r"(?ms:^define.*?\}$)|(?m:^declare.*?$)|(?m:^%.+?=\s*type\s*\{.+?\}$)").unwrap();
for f in regex_filter.captures_iter(&output) {
assert_eq!(f.len(), 1);
filtered_output.push_str(&f[0]);
@ -87,14 +68,10 @@ fn main() {
.unwrap()
.replace_all(&filtered_output, "");
// For debugging
// Doing `DEBUG_DUMP_IRRT=1 cargo build -p nac3core` dumps the LLVM IR generated
const DEBUG_DUMP_IRRT: &str = "DEBUG_DUMP_IRRT";
println!("cargo:rerun-if-env-changed={DEBUG_DUMP_IRRT}");
if env::var(DEBUG_DUMP_IRRT).is_ok() {
println!("cargo:rerun-if-env-changed=DEBUG_DUMP_IRRT");
if env::var("DEBUG_DUMP_IRRT").is_ok() {
let mut file = File::create(out_dir.join("irrt.ll")).unwrap();
file.write_all(output.as_bytes()).unwrap();
let mut file = File::create(out_dir.join("irrt-filtered.ll")).unwrap();
file.write_all(filtered_output.as_bytes()).unwrap();
}
@ -108,3 +85,50 @@ fn main() {
llvm_as.stdin.as_mut().unwrap().write_all(filtered_output.as_bytes()).unwrap();
assert!(llvm_as.wait().unwrap().success());
}
fn compile_irrt_test(irrt_dir: &Path, out_dir: &Path) {
let irrt_test_cpp_path = irrt_dir.join("irrt_test.cpp");
let exe_path = out_dir.join("irrt_test.out");
let flags: &[&str] = &[
irrt_test_cpp_path.to_str().unwrap(),
"-x",
"c++",
"-I",
irrt_dir.to_str().unwrap(),
"-g",
"-fno-discard-value-names",
"-O0",
"-Wall",
"-Wextra",
"-Werror=return-type",
"-lm", // for `tgamma()`, `lgamma()`
"-o",
exe_path.to_str().unwrap(),
];
Command::new("clang-irrt-test")
.args(flags)
.output()
.map(|o| {
assert!(o.status.success(), "{}", std::str::from_utf8(&o.stderr).unwrap());
o
})
.unwrap();
println!("cargo:rerun-if-changed={}", out_dir.to_str().unwrap());
}
fn main() {
let out_dir = env::var("OUT_DIR").unwrap();
let out_dir = Path::new(&out_dir);
let irrt_dir = Path::new("./irrt");
compile_irrt(irrt_dir, out_dir);
// https://github.com/rust-lang/cargo/issues/2549
// `cargo test -F test` to also build `irrt_test.cpp
if cfg!(feature = "test") {
compile_irrt_test(irrt_dir, out_dir);
}
}

View File

@ -1,6 +1,5 @@
#include "irrt/exception.hpp"
#include "irrt/int_types.hpp"
#include "irrt/list.hpp"
#include "irrt/math.hpp"
#include "irrt/ndarray.hpp"
#include "irrt/slice.hpp"
#include "irrt_everything.hpp"
/*
This file will be read by `clang-irrt` to conveniently produce LLVM IR for `nac3core/codegen`.
*/

437
nac3core/irrt/irrt.hpp Normal file
View File

@ -0,0 +1,437 @@
#ifndef IRRT_DONT_TYPEDEF_INTS
typedef _BitInt(8) int8_t;
typedef unsigned _BitInt(8) uint8_t;
typedef _BitInt(32) int32_t;
typedef unsigned _BitInt(32) uint32_t;
typedef _BitInt(64) int64_t;
typedef unsigned _BitInt(64) uint64_t;
#endif
// NDArray indices are always `uint32_t`.
typedef uint32_t NDIndex;
// The type of an index or a value describing the length of a range/slice is
// always `int32_t`.
typedef int32_t SliceIndex;
template <typename T>
static T max(T a, T b) {
return a > b ? a : b;
}
template <typename T>
static T min(T a, T b) {
return a > b ? b : a;
}
// 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
template <typename T>
static T __nac3_int_exp_impl(T base, T exp) {
T res = 1;
/* repeated squaring method */
do {
if (exp & 1) {
res *= base; /* for n odd */
}
exp >>= 1;
base *= base;
} while (exp);
return res;
}
template <typename SizeT>
static SizeT __nac3_ndarray_calc_size_impl(
const SizeT *list_data,
SizeT list_len,
SizeT begin_idx,
SizeT end_idx
) {
__builtin_assume(end_idx <= list_len);
SizeT num_elems = 1;
for (SizeT i = begin_idx; i < end_idx; ++i) {
SizeT val = list_data[i];
__builtin_assume(val > 0);
num_elems *= val;
}
return num_elems;
}
template <typename SizeT>
static void __nac3_ndarray_calc_nd_indices_impl(
SizeT index,
const SizeT *dims,
SizeT num_dims,
NDIndex *idxs
) {
SizeT stride = 1;
for (SizeT dim = 0; dim < num_dims; dim++) {
SizeT i = num_dims - dim - 1;
__builtin_assume(dims[i] > 0);
idxs[i] = (index / stride) % dims[i];
stride *= dims[i];
}
}
template <typename SizeT>
static SizeT __nac3_ndarray_flatten_index_impl(
const SizeT *dims,
SizeT num_dims,
const NDIndex *indices,
SizeT num_indices
) {
SizeT idx = 0;
SizeT stride = 1;
for (SizeT i = 0; i < num_dims; ++i) {
SizeT ri = num_dims - i - 1;
if (ri < num_indices) {
idx += stride * indices[ri];
}
__builtin_assume(dims[i] > 0);
stride *= dims[ri];
}
return idx;
}
template <typename SizeT>
static void __nac3_ndarray_calc_broadcast_impl(
const SizeT *lhs_dims,
SizeT lhs_ndims,
const SizeT *rhs_dims,
SizeT rhs_ndims,
SizeT *out_dims
) {
SizeT max_ndims = lhs_ndims > rhs_ndims ? lhs_ndims : rhs_ndims;
for (SizeT i = 0; i < max_ndims; ++i) {
const SizeT *lhs_dim_sz = i < lhs_ndims ? &lhs_dims[lhs_ndims - i - 1] : nullptr;
const SizeT *rhs_dim_sz = i < rhs_ndims ? &rhs_dims[rhs_ndims - i - 1] : nullptr;
SizeT *out_dim = &out_dims[max_ndims - i - 1];
if (lhs_dim_sz == nullptr) {
*out_dim = *rhs_dim_sz;
} else if (rhs_dim_sz == nullptr) {
*out_dim = *lhs_dim_sz;
} else if (*lhs_dim_sz == 1) {
*out_dim = *rhs_dim_sz;
} else if (*rhs_dim_sz == 1) {
*out_dim = *lhs_dim_sz;
} else if (*lhs_dim_sz == *rhs_dim_sz) {
*out_dim = *lhs_dim_sz;
} else {
__builtin_unreachable();
}
}
}
template <typename SizeT>
static void __nac3_ndarray_calc_broadcast_idx_impl(
const SizeT *src_dims,
SizeT src_ndims,
const NDIndex *in_idx,
NDIndex *out_idx
) {
for (SizeT i = 0; i < src_ndims; ++i) {
SizeT src_i = src_ndims - i - 1;
out_idx[src_i] = src_dims[src_i] == 1 ? 0 : in_idx[src_i];
}
}
template<typename SizeT>
static void __nac3_ndarray_strides_from_shape_impl(
SizeT ndims,
SizeT *shape,
SizeT *dst_strides
) {
SizeT stride_product = 1;
for (SizeT i = 0; i < ndims; i++) {
int dim_i = ndims - i - 1;
dst_strides[dim_i] = stride_product;
stride_product *= shape[dim_i];
}
}
extern "C" {
#define DEF_nac3_int_exp_(T) \
T __nac3_int_exp_##T(T base, T exp) {\
return __nac3_int_exp_impl(base, exp);\
}
DEF_nac3_int_exp_(int32_t)
DEF_nac3_int_exp_(int64_t)
DEF_nac3_int_exp_(uint32_t)
DEF_nac3_int_exp_(uint64_t)
SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
if (i < 0) {
i = len + i;
}
if (i < 0) {
return 0;
} else if (i > len) {
return len;
}
return i;
}
SliceIndex __nac3_range_slice_len(
const SliceIndex start,
const SliceIndex end,
const SliceIndex step
) {
SliceIndex diff = end - start;
if (diff > 0 && step > 0) {
return ((diff - 1) / step) + 1;
} else if (diff < 0 && step < 0) {
return ((diff + 1) / step) + 1;
} else {
return 0;
}
}
// Handle list assignment and dropping part of the list when
// both dest_step and src_step are +1.
// - All the index must *not* be out-of-bound or negative,
// - The end index is *inclusive*,
// - The length of src and dest slice size should already
// be checked: if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest)
SliceIndex __nac3_list_slice_assign_var_size(
SliceIndex dest_start,
SliceIndex dest_end,
SliceIndex dest_step,
uint8_t *dest_arr,
SliceIndex dest_arr_len,
SliceIndex src_start,
SliceIndex src_end,
SliceIndex src_step,
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 */
if (dest_arr_len == 0) return dest_arr_len;
/* if both step is 1, memmove directly, handle the dropping of the list, and shrink size */
if (src_step == dest_step && dest_step == 1) {
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(
dest_arr + dest_start * size,
src_arr + src_start * size,
src_len * size
);
}
if (dest_len > 0) {
/* dropping */
__builtin_memmove(
dest_arr + (dest_start + src_len) * size,
dest_arr + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size
);
}
/* shrink size */
return dest_arr_len - (dest_len - src_len);
}
/* if two range overlaps, need alloca */
uint8_t need_alloca =
(dest_arr == src_arr)
&& !(
max(dest_start, dest_end) < min(src_start, src_end)
|| max(src_start, src_end) < min(dest_start, dest_end)
);
if (need_alloca) {
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;
}
SliceIndex src_ind = src_start;
SliceIndex dest_ind = 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(dest_arr + dest_ind, src_arr + src_ind, 1);
} else if (size == 4) {
__builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
} else if (size == 8) {
__builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
} else {
/* memcpy for var size, cannot overlap after previous alloca */
__builtin_memcpy(dest_arr + dest_ind * size, 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(
dest_arr + dest_ind * size,
dest_arr + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size
);
return dest_arr_len - (dest_end - dest_ind) - 1;
}
return dest_arr_len;
}
int32_t __nac3_isinf(double x) {
return __builtin_isinf(x);
}
int32_t __nac3_isnan(double x) {
return __builtin_isnan(x);
}
double tgamma(double arg);
double __nac3_gamma(double z) {
// Handling for denormals
// | x | Python gamma(x) | C tgamma(x) |
// --- | ----------------- | --------------- | ----------- |
// (1) | nan | nan | nan |
// (2) | -inf | -inf | inf |
// (3) | inf | inf | inf |
// (4) | 0.0 | inf | inf |
// (5) | {-1.0, -2.0, ...} | inf | nan |
// (1)-(3)
if (__builtin_isinf(z) || __builtin_isnan(z)) {
return z;
}
double v = tgamma(z);
// (4)-(5)
return __builtin_isinf(v) || __builtin_isnan(v) ? __builtin_inf() : v;
}
double lgamma(double arg);
double __nac3_gammaln(double x) {
// libm's handling of value overflows differs from scipy:
// - scipy: gammaln(-inf) -> -inf
// - libm : lgamma(-inf) -> inf
if (__builtin_isinf(x)) {
return x;
}
return lgamma(x);
}
double j0(double x);
double __nac3_j0(double x) {
// libm's handling of value overflows differs from scipy:
// - scipy: j0(inf) -> nan
// - libm : j0(inf) -> 0.0
if (__builtin_isinf(x)) {
return __builtin_nan("");
}
return j0(x);
}
uint32_t __nac3_ndarray_calc_size(
const uint32_t *list_data,
uint32_t list_len,
uint32_t begin_idx,
uint32_t end_idx
) {
return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
}
uint64_t __nac3_ndarray_calc_size64(
const uint64_t *list_data,
uint64_t list_len,
uint64_t begin_idx,
uint64_t end_idx
) {
return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
}
void __nac3_ndarray_calc_nd_indices(
uint32_t index,
const uint32_t* dims,
uint32_t num_dims,
NDIndex* idxs
) {
__nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
}
void __nac3_ndarray_calc_nd_indices64(
uint64_t index,
const uint64_t* dims,
uint64_t num_dims,
NDIndex* idxs
) {
__nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
}
uint32_t __nac3_ndarray_flatten_index(
const uint32_t* dims,
uint32_t num_dims,
const NDIndex* indices,
uint32_t num_indices
) {
return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
}
uint64_t __nac3_ndarray_flatten_index64(
const uint64_t* dims,
uint64_t num_dims,
const NDIndex* indices,
uint64_t num_indices
) {
return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
}
void __nac3_ndarray_calc_broadcast(
const uint32_t *lhs_dims,
uint32_t lhs_ndims,
const uint32_t *rhs_dims,
uint32_t rhs_ndims,
uint32_t *out_dims
) {
return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
}
void __nac3_ndarray_calc_broadcast64(
const uint64_t *lhs_dims,
uint64_t lhs_ndims,
const uint64_t *rhs_dims,
uint64_t rhs_ndims,
uint64_t *out_dims
) {
return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
}
void __nac3_ndarray_calc_broadcast_idx(
const uint32_t *src_dims,
uint32_t src_ndims,
const NDIndex *in_idx,
NDIndex *out_idx
) {
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
}
void __nac3_ndarray_calc_broadcast_idx64(
const uint64_t *src_dims,
uint64_t src_ndims,
const NDIndex *in_idx,
NDIndex *out_idx
) {
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
}
void __nac3_ndarray_strides_from_shape(uint32_t ndims, uint32_t* shape, uint32_t* dst_strides) {
__nac3_ndarray_strides_from_shape_impl(ndims, shape, dst_strides);
}
void __nac3_ndarray_strides_from_shape64(uint64_t ndims, uint64_t* shape, uint64_t* dst_strides) {
__nac3_ndarray_strides_from_shape_impl(ndims, shape, dst_strides);
}
}

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#pragma once
#include "irrt/int_types.hpp"
template<typename SizeT>
struct CSlice {
uint8_t* base;
SizeT len;
};

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#pragma once
// Set in nac3core/build.rs
#ifdef IRRT_DEBUG_ASSERT
#define IRRT_DEBUG_ASSERT_BOOL true
#else
#define IRRT_DEBUG_ASSERT_BOOL false
#endif
#define raise_debug_assert(SizeT, msg, param1, param2, param3) \
raise_exception(SizeT, EXN_ASSERTION_ERROR, "IRRT debug assert failed: " msg, param1, param2, param3)
#define debug_assert_eq(SizeT, lhs, rhs) \
if constexpr (IRRT_DEBUG_ASSERT_BOOL) { \
if ((lhs) != (rhs)) { \
raise_debug_assert(SizeT, "LHS = {0}. RHS = {1}", lhs, rhs, NO_PARAM); \
} \
}
#define debug_assert(SizeT, expr) \
if constexpr (IRRT_DEBUG_ASSERT_BOOL) { \
if (!(expr)) { \
raise_debug_assert(SizeT, "Got false.", NO_PARAM, NO_PARAM, NO_PARAM); \
} \
}

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#pragma once
#include "irrt/cslice.hpp"
#include "irrt/int_types.hpp"
/**
* @brief The int type of ARTIQ exception IDs.
*/
typedef int32_t ExceptionId;
/*
* Set of exceptions C++ IRRT can use.
* Must be synchronized with `setup_irrt_exceptions` in `nac3core/src/codegen/irrt/mod.rs`.
*/
extern "C" {
ExceptionId EXN_INDEX_ERROR;
ExceptionId EXN_VALUE_ERROR;
ExceptionId EXN_ASSERTION_ERROR;
ExceptionId EXN_TYPE_ERROR;
}
/**
* @brief Extern function to `__nac3_raise`
*
* The parameter `err` could be `Exception<int32_t>` or `Exception<int64_t>`. The caller
* must make sure to pass `Exception`s with the correct `SizeT` depending on the `size_t` of the runtime.
*/
extern "C" void __nac3_raise(void* err);
namespace {
/**
* @brief NAC3's Exception struct
*/
template<typename SizeT>
struct Exception {
ExceptionId id;
CSlice<SizeT> filename;
int32_t line;
int32_t column;
CSlice<SizeT> function;
CSlice<SizeT> msg;
int64_t params[3];
};
constexpr int64_t NO_PARAM = 0;
template<typename SizeT>
void _raise_exception_helper(ExceptionId id,
const char* filename,
int32_t line,
const char* function,
const char* msg,
int64_t param0,
int64_t param1,
int64_t param2) {
Exception<SizeT> e = {
.id = id,
.filename = {.base = reinterpret_cast<const uint8_t*>(filename), .len = __builtin_strlen(filename)},
.line = line,
.column = 0,
.function = {.base = reinterpret_cast<const uint8_t*>(function), .len = __builtin_strlen(function)},
.msg = {.base = reinterpret_cast<const uint8_t*>(msg), .len = __builtin_strlen(msg)},
};
e.params[0] = param0;
e.params[1] = param1;
e.params[2] = param2;
__nac3_raise(reinterpret_cast<void*>(&e));
__builtin_unreachable();
}
/**
* @brief Raise an exception with location details (location in the IRRT source files).
* @param SizeT The runtime `size_t` type.
* @param id The ID of the exception to raise.
* @param msg A global constant C-string of the error message.
*
* `param0` to `param2` are optional format arguments of `msg`. They should be set to
* `NO_PARAM` to indicate they are unused.
*/
#define raise_exception(SizeT, id, msg, param0, param1, param2) \
_raise_exception_helper<SizeT>(id, __FILE__, __LINE__, __FUNCTION__, msg, param0, param1, param2)
} // namespace

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#pragma once
#if __STDC_VERSION__ >= 202000
using int8_t = _BitInt(8);
using uint8_t = unsigned _BitInt(8);
using int32_t = _BitInt(32);
using uint32_t = unsigned _BitInt(32);
using int64_t = _BitInt(64);
using uint64_t = unsigned _BitInt(64);
#else
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);
#endif
// NDArray indices are always `uint32_t`.
using NDIndex = 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;

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#pragma once
#include "irrt/int_types.hpp"
#include "irrt/math_util.hpp"
extern "C" {
// Handle list assignment and dropping part of the list when
// both dest_step and src_step are +1.
// - All the index must *not* be out-of-bound or negative,
// - The end index is *inclusive*,
// - The length of src and dest slice size should already
// be checked: if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest)
SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
SliceIndex dest_end,
SliceIndex dest_step,
uint8_t* dest_arr,
SliceIndex dest_arr_len,
SliceIndex src_start,
SliceIndex src_end,
SliceIndex src_step,
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 */
if (dest_arr_len == 0)
return dest_arr_len;
/* if both step is 1, memmove directly, handle the dropping of the list, and shrink size */
if (src_step == dest_step && dest_step == 1) {
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(dest_arr + dest_start * size, src_arr + src_start * size, src_len * size);
}
if (dest_len > 0) {
/* dropping */
__builtin_memmove(dest_arr + (dest_start + src_len) * size, dest_arr + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size);
}
/* shrink size */
return dest_arr_len - (dest_len - src_len);
}
/* if two range overlaps, need alloca */
uint8_t need_alloca = (dest_arr == src_arr)
&& !(max(dest_start, dest_end) < min(src_start, src_end)
|| max(src_start, src_end) < min(dest_start, dest_end));
if (need_alloca) {
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;
}
SliceIndex src_ind = src_start;
SliceIndex dest_ind = 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(dest_arr + dest_ind, src_arr + src_ind, 1);
} else if (size == 4) {
__builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
} else if (size == 8) {
__builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
} else {
/* memcpy for var size, cannot overlap after previous alloca */
__builtin_memcpy(dest_arr + dest_ind * size, 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(dest_arr + dest_ind * size, dest_arr + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size);
return dest_arr_len - (dest_end - dest_ind) - 1;
}
return dest_arr_len;
}
} // extern "C"

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#pragma once
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
template<typename T>
T __nac3_int_exp_impl(T base, T exp) {
T res = 1;
/* repeated squaring method */
do {
if (exp & 1) {
res *= base; /* for n odd */
}
exp >>= 1;
base *= base;
} while (exp);
return res;
}
} // namespace
#define DEF_nac3_int_exp_(T) \
T __nac3_int_exp_##T(T base, T exp) { \
return __nac3_int_exp_impl(base, exp); \
}
extern "C" {
// Putting semicolons here to make clang-format not reformat this into
// a stair shape.
DEF_nac3_int_exp_(int32_t);
DEF_nac3_int_exp_(int64_t);
DEF_nac3_int_exp_(uint32_t);
DEF_nac3_int_exp_(uint64_t);
int32_t __nac3_isinf(double x) {
return __builtin_isinf(x);
}
int32_t __nac3_isnan(double x) {
return __builtin_isnan(x);
}
double tgamma(double arg);
double __nac3_gamma(double z) {
// Handling for denormals
// | x | Python gamma(x) | C tgamma(x) |
// --- | ----------------- | --------------- | ----------- |
// (1) | nan | nan | nan |
// (2) | -inf | -inf | inf |
// (3) | inf | inf | inf |
// (4) | 0.0 | inf | inf |
// (5) | {-1.0, -2.0, ...} | inf | nan |
// (1)-(3)
if (__builtin_isinf(z) || __builtin_isnan(z)) {
return z;
}
double v = tgamma(z);
// (4)-(5)
return __builtin_isinf(v) || __builtin_isnan(v) ? __builtin_inf() : v;
}
double lgamma(double arg);
double __nac3_gammaln(double x) {
// libm's handling of value overflows differs from scipy:
// - scipy: gammaln(-inf) -> -inf
// - libm : lgamma(-inf) -> inf
if (__builtin_isinf(x)) {
return x;
}
return lgamma(x);
}
double j0(double x);
double __nac3_j0(double x) {
// libm's handling of value overflows differs from scipy:
// - scipy: j0(inf) -> nan
// - libm : j0(inf) -> 0.0
if (__builtin_isinf(x)) {
return __builtin_nan("");
}
return j0(x);
}
}

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#pragma once
namespace {
template<typename T>
const T& max(const T& a, const T& b) {
return a > b ? a : b;
}
template<typename T>
const T& min(const T& a, const T& b) {
return a > b ? b : a;
}
} // namespace

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#pragma once
#include "irrt/int_types.hpp"
namespace {
template<typename SizeT>
SizeT __nac3_ndarray_calc_size_impl(const SizeT* list_data, SizeT list_len, SizeT begin_idx, SizeT end_idx) {
__builtin_assume(end_idx <= list_len);
SizeT num_elems = 1;
for (SizeT i = begin_idx; i < end_idx; ++i) {
SizeT val = list_data[i];
__builtin_assume(val > 0);
num_elems *= val;
}
return num_elems;
}
template<typename SizeT>
void __nac3_ndarray_calc_nd_indices_impl(SizeT index, const SizeT* dims, SizeT num_dims, NDIndex* idxs) {
SizeT stride = 1;
for (SizeT dim = 0; dim < num_dims; dim++) {
SizeT i = num_dims - dim - 1;
__builtin_assume(dims[i] > 0);
idxs[i] = (index / stride) % dims[i];
stride *= dims[i];
}
}
template<typename SizeT>
SizeT __nac3_ndarray_flatten_index_impl(const SizeT* dims, SizeT num_dims, const NDIndex* indices, SizeT num_indices) {
SizeT idx = 0;
SizeT stride = 1;
for (SizeT i = 0; i < num_dims; ++i) {
SizeT ri = num_dims - i - 1;
if (ri < num_indices) {
idx += stride * indices[ri];
}
__builtin_assume(dims[i] > 0);
stride *= dims[ri];
}
return idx;
}
template<typename SizeT>
void __nac3_ndarray_calc_broadcast_impl(const SizeT* lhs_dims,
SizeT lhs_ndims,
const SizeT* rhs_dims,
SizeT rhs_ndims,
SizeT* out_dims) {
SizeT max_ndims = lhs_ndims > rhs_ndims ? lhs_ndims : rhs_ndims;
for (SizeT i = 0; i < max_ndims; ++i) {
const SizeT* lhs_dim_sz = i < lhs_ndims ? &lhs_dims[lhs_ndims - i - 1] : nullptr;
const SizeT* rhs_dim_sz = i < rhs_ndims ? &rhs_dims[rhs_ndims - i - 1] : nullptr;
SizeT* out_dim = &out_dims[max_ndims - i - 1];
if (lhs_dim_sz == nullptr) {
*out_dim = *rhs_dim_sz;
} else if (rhs_dim_sz == nullptr) {
*out_dim = *lhs_dim_sz;
} else if (*lhs_dim_sz == 1) {
*out_dim = *rhs_dim_sz;
} else if (*rhs_dim_sz == 1) {
*out_dim = *lhs_dim_sz;
} else if (*lhs_dim_sz == *rhs_dim_sz) {
*out_dim = *lhs_dim_sz;
} else {
__builtin_unreachable();
}
}
}
template<typename SizeT>
void __nac3_ndarray_calc_broadcast_idx_impl(const SizeT* src_dims,
SizeT src_ndims,
const NDIndex* in_idx,
NDIndex* out_idx) {
for (SizeT i = 0; i < src_ndims; ++i) {
SizeT src_i = src_ndims - i - 1;
out_idx[src_i] = src_dims[src_i] == 1 ? 0 : in_idx[src_i];
}
}
} // namespace
extern "C" {
uint32_t __nac3_ndarray_calc_size(const uint32_t* list_data, uint32_t list_len, uint32_t begin_idx, uint32_t end_idx) {
return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
}
uint64_t
__nac3_ndarray_calc_size64(const uint64_t* list_data, uint64_t list_len, uint64_t begin_idx, uint64_t end_idx) {
return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
}
void __nac3_ndarray_calc_nd_indices(uint32_t index, const uint32_t* dims, uint32_t num_dims, NDIndex* idxs) {
__nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
}
void __nac3_ndarray_calc_nd_indices64(uint64_t index, const uint64_t* dims, uint64_t num_dims, NDIndex* idxs) {
__nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
}
uint32_t
__nac3_ndarray_flatten_index(const uint32_t* dims, uint32_t num_dims, const NDIndex* indices, uint32_t num_indices) {
return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
}
uint64_t
__nac3_ndarray_flatten_index64(const uint64_t* dims, uint64_t num_dims, const NDIndex* indices, uint64_t num_indices) {
return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
}
void __nac3_ndarray_calc_broadcast(const uint32_t* lhs_dims,
uint32_t lhs_ndims,
const uint32_t* rhs_dims,
uint32_t rhs_ndims,
uint32_t* out_dims) {
return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
}
void __nac3_ndarray_calc_broadcast64(const uint64_t* lhs_dims,
uint64_t lhs_ndims,
const uint64_t* rhs_dims,
uint64_t rhs_ndims,
uint64_t* out_dims) {
return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
}
void __nac3_ndarray_calc_broadcast_idx(const uint32_t* src_dims,
uint32_t src_ndims,
const NDIndex* in_idx,
NDIndex* out_idx) {
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
}
void __nac3_ndarray_calc_broadcast_idx64(const uint64_t* src_dims,
uint64_t src_ndims,
const NDIndex* in_idx,
NDIndex* out_idx) {
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
}
}

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#pragma once
#include "irrt/int_types.hpp"
extern "C" {
SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
if (i < 0) {
i = len + i;
}
if (i < 0) {
return 0;
} else if (i > len) {
return len;
}
return i;
}
SliceIndex __nac3_range_slice_len(const SliceIndex start, const SliceIndex end, const SliceIndex step) {
SliceIndex diff = end - start;
if (diff > 0 && step > 0) {
return ((diff - 1) / step) + 1;
} else if (diff < 0 && step < 0) {
return ((diff + 1) / step) + 1;
} else {
return 0;
}
}
}

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#pragma once
#include "irrt_utils.hpp"
#include "irrt_typedefs.hpp"
/*
This header contains IRRT implementations
that do not deserved to be categorized (e.g., into numpy, etc.)
Check out other *.hpp files before including them here!!
*/
// The type of an index or a value describing the length of a range/slice is
// always `int32_t`.
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
template <typename T>
T __nac3_int_exp_impl(T base, T exp) {
T res = 1;
/* repeated squaring method */
do {
if (exp & 1) {
res *= base; /* for n odd */
}
exp >>= 1;
base *= base;
} while (exp);
return res;
}
}
extern "C" {
#define DEF_nac3_int_exp_(T) \
T __nac3_int_exp_##T(T base, T exp) {\
return __nac3_int_exp_impl(base, exp);\
}
DEF_nac3_int_exp_(int32_t)
DEF_nac3_int_exp_(int64_t)
DEF_nac3_int_exp_(uint32_t)
DEF_nac3_int_exp_(uint64_t)
SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
if (i < 0) {
i = len + i;
}
if (i < 0) {
return 0;
} else if (i > len) {
return len;
}
return i;
}
SliceIndex __nac3_range_slice_len(
const SliceIndex start,
const SliceIndex end,
const SliceIndex step
) {
SliceIndex diff = end - start;
if (diff > 0 && step > 0) {
return ((diff - 1) / step) + 1;
} else if (diff < 0 && step < 0) {
return ((diff + 1) / step) + 1;
} else {
return 0;
}
}
// Handle list assignment and dropping part of the list when
// both dest_step and src_step are +1.
// - All the index must *not* be out-of-bound or negative,
// - The end index is *inclusive*,
// - The length of src and dest slice size should already
// be checked: if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest)
SliceIndex __nac3_list_slice_assign_var_size(
SliceIndex dest_start,
SliceIndex dest_end,
SliceIndex dest_step,
uint8_t *dest_arr,
SliceIndex dest_arr_len,
SliceIndex src_start,
SliceIndex src_end,
SliceIndex src_step,
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 */
if (dest_arr_len == 0) return dest_arr_len;
/* if both step is 1, memmove directly, handle the dropping of the list, and shrink size */
if (src_step == dest_step && dest_step == 1) {
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(
dest_arr + dest_start * size,
src_arr + src_start * size,
src_len * size
);
}
if (dest_len > 0) {
/* dropping */
__builtin_memmove(
dest_arr + (dest_start + src_len) * size,
dest_arr + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size
);
}
/* shrink size */
return dest_arr_len - (dest_len - src_len);
}
/* if two range overlaps, need alloca */
uint8_t need_alloca =
(dest_arr == src_arr)
&& !(
max(dest_start, dest_end) < min(src_start, src_end)
|| max(src_start, src_end) < min(dest_start, dest_end)
);
if (need_alloca) {
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;
}
SliceIndex src_ind = src_start;
SliceIndex dest_ind = 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(dest_arr + dest_ind, src_arr + src_ind, 1);
} else if (size == 4) {
__builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
} else if (size == 8) {
__builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
} else {
/* memcpy for var size, cannot overlap after previous alloca */
__builtin_memcpy(dest_arr + dest_ind * size, 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(
dest_arr + dest_ind * size,
dest_arr + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size
);
return dest_arr_len - (dest_end - dest_ind) - 1;
}
return dest_arr_len;
}
int32_t __nac3_isinf(double x) {
return __builtin_isinf(x);
}
int32_t __nac3_isnan(double x) {
return __builtin_isnan(x);
}
double tgamma(double arg);
double __nac3_gamma(double z) {
// Handling for denormals
// | x | Python gamma(x) | C tgamma(x) |
// --- | ----------------- | --------------- | ----------- |
// (1) | nan | nan | nan |
// (2) | -inf | -inf | inf |
// (3) | inf | inf | inf |
// (4) | 0.0 | inf | inf |
// (5) | {-1.0, -2.0, ...} | inf | nan |
// (1)-(3)
if (__builtin_isinf(z) || __builtin_isnan(z)) {
return z;
}
double v = tgamma(z);
// (4)-(5)
return __builtin_isinf(v) || __builtin_isnan(v) ? __builtin_inf() : v;
}
double lgamma(double arg);
double __nac3_gammaln(double x) {
// libm's handling of value overflows differs from scipy:
// - scipy: gammaln(-inf) -> -inf
// - libm : lgamma(-inf) -> inf
if (__builtin_isinf(x)) {
return x;
}
return lgamma(x);
}
double j0(double x);
double __nac3_j0(double x) {
// libm's handling of value overflows differs from scipy:
// - scipy: j0(inf) -> nan
// - libm : j0(inf) -> 0.0
if (__builtin_isinf(x)) {
return __builtin_nan("");
}
return j0(x);
}
}

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#pragma once
#include "irrt_utils.hpp"
#include "irrt_typedefs.hpp"
#include "irrt_basic.hpp"
#include "irrt_slice.hpp"
#include "irrt_numpy_ndarray.hpp"
/*
All IRRT implementations.
We don't have any pre-compiled objects, so we are writing all implementations in headers and
concatenate them with `#include` into one massive source file that contains all the IRRT stuff.
*/

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#pragma once
#include "irrt_utils.hpp"
#include "irrt_typedefs.hpp"
#include "irrt_slice.hpp"
/*
NDArray-related implementations.
`*/
// NDArray indices are always `uint32_t`.
using NDIndex = uint32_t;
namespace {
namespace ndarray_util {
template <typename SizeT>
static void set_indices_by_nth(SizeT ndims, const SizeT* shape, SizeT* indices, SizeT nth) {
for (int32_t i = 0; i < ndims; i++) {
int32_t dim_i = ndims - i - 1;
int32_t dim = shape[dim_i];
indices[dim_i] = nth % dim;
nth /= dim;
}
}
// Compute the strides of an ndarray given an ndarray `shape`
// and assuming that the ndarray is *fully C-contagious*.
//
// You might want to read up on https://ajcr.net/stride-guide-part-1/.
template <typename SizeT>
static void set_strides_by_shape(SizeT itemsize, SizeT ndims, SizeT* dst_strides, const SizeT* shape) {
SizeT stride_product = 1;
for (SizeT i = 0; i < ndims; i++) {
int dim_i = ndims - i - 1;
dst_strides[dim_i] = stride_product * itemsize;
stride_product *= shape[dim_i];
}
}
// Compute the size/# of elements of an ndarray given its shape
template <typename SizeT>
static SizeT calc_size_from_shape(SizeT ndims, const SizeT* shape) {
SizeT size = 1;
for (SizeT dim_i = 0; dim_i < ndims; dim_i++) size *= shape[dim_i];
return size;
}
template <typename SizeT>
static bool can_broadcast_shape_to(
const SizeT target_ndims,
const SizeT *target_shape,
const SizeT src_ndims,
const SizeT *src_shape
) {
/*
// See https://numpy.org/doc/stable/user/basics.broadcasting.html
This function handles this example:
```
Image (3d array): 256 x 256 x 3
Scale (1d array): 3
Result (3d array): 256 x 256 x 3
```
Other interesting examples to consider:
- `can_broadcast_shape_to([3], [1, 1, 1, 1, 3]) == true`
- `can_broadcast_shape_to([3], [3, 1]) == false`
- `can_broadcast_shape_to([256, 256, 3], [256, 1, 3]) == true`
In cases when the shapes contain zero(es):
- `can_broadcast_shape_to([0], [1]) == true`
- `can_broadcast_shape_to([0], [2]) == false`
- `can_broadcast_shape_to([0, 4, 0, 0], [1]) == true`
- `can_broadcast_shape_to([0, 4, 0, 0], [1, 1, 1, 1]) == true`
- `can_broadcast_shape_to([0, 4, 0, 0], [1, 4, 1, 1]) == true`
- `can_broadcast_shape_to([4, 3], [0, 3]) == false`
- `can_broadcast_shape_to([4, 3], [0, 0]) == false`
*/
// This is essentially doing the following in Python:
// `for target_dim, src_dim in itertools.zip_longest(target_shape[::-1], src_shape[::-1], fillvalue=1)`
for (SizeT i = 0; i < max(target_ndims, src_ndims); i++) {
SizeT target_dim_i = target_ndims - i - 1;
SizeT src_dim_i = src_ndims - i - 1;
bool target_dim_exists = target_dim_i >= 0;
bool src_dim_exists = src_dim_i >= 0;
SizeT target_dim = target_dim_exists ? target_shape[target_dim_i] : 1;
SizeT src_dim = src_dim_exists ? src_shape[src_dim_i] : 1;
bool ok = src_dim == 1 || target_dim == src_dim;
if (!ok) return false;
}
return true;
}
}
typedef uint8_t NDSliceType;
extern "C" {
const NDSliceType INPUT_SLICE_TYPE_INDEX = 0;
const NDSliceType INPUT_SLICE_TYPE_SLICE = 1;
}
struct NDSlice {
// A poor-man's `std::variant<int, UserRange>`
NDSliceType type;
/*
if type == INPUT_SLICE_TYPE_INDEX => `slice` points to a single `SizeT`
if type == INPUT_SLICE_TYPE_SLICE => `slice` points to a single `UserRange`
*/
uint8_t *slice;
};
namespace ndarray_util {
template<typename SizeT>
SizeT deduce_ndims_after_slicing(SizeT ndims, SizeT num_slices, const NDSlice *slices) {
irrt_assert(num_slices <= ndims);
SizeT final_ndims = ndims;
for (SizeT i = 0; i < num_slices; i++) {
if (slices[i].type == INPUT_SLICE_TYPE_INDEX) {
final_ndims--; // An integer slice demotes the rank by 1
}
}
return final_ndims;
}
}
template <typename SizeT>
struct NDArrayIndicesIter {
SizeT ndims;
const SizeT *shape;
SizeT *indices;
void set_indices_zero() {
__builtin_memset(indices, 0, sizeof(SizeT) * ndims);
}
void next() {
for (SizeT i = 0; i < ndims; i++) {
SizeT dim_i = ndims - i - 1;
indices[dim_i]++;
if (indices[dim_i] < shape[dim_i]) {
break;
} else {
indices[dim_i] = 0;
}
}
}
};
// The NDArray object. `SizeT` is the *signed* size type of this ndarray.
//
// NOTE: The order of fields is IMPORTANT. DON'T TOUCH IT
//
// Some resources you might find helpful:
// - The official numpy implementations:
// - https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst
// - On strides (about reshaping, slicing, C-contagiousness, etc)
// - https://ajcr.net/stride-guide-part-1/.
// - https://ajcr.net/stride-guide-part-2/.
// - https://ajcr.net/stride-guide-part-3/.
template <typename SizeT>
struct NDArray {
// The underlying data this `ndarray` is pointing to.
//
// NOTE: Formally this should be of type `void *`, but clang
// translates `void *` to `i8 *` when run with `-S -emit-llvm`,
// so we will put `uint8_t *` here for clarity.
uint8_t *data;
// The number of bytes of a single element in `data`.
//
// The `SizeT` is treated as `unsigned`.
SizeT itemsize;
// The number of dimensions of this shape.
//
// The `SizeT` is treated as `unsigned`.
SizeT ndims;
// Array shape, with length equal to `ndims`.
//
// The `SizeT` is treated as `unsigned`.
//
// NOTE: `shape` can contain 0.
// (those appear when the user makes an out of bounds slice into an ndarray, e.g., `np.zeros((3, 3))[400:].shape == (0, 3)`)
SizeT *shape;
// Array strides (stride value is in number of bytes, NOT number of elements), with length equal to `ndims`.
//
// The `SizeT` is treated as `signed`.
//
// NOTE: `strides` can have negative numbers.
// (those appear when there is a slice with a negative step, e.g., `my_array[::-1]`)
SizeT *strides;
// Calculate the size/# of elements of an `ndarray`.
// This function corresponds to `np.size(<ndarray>)` or `ndarray.size`
SizeT size() {
return ndarray_util::calc_size_from_shape(ndims, shape);
}
// Calculate the number of bytes of its content of an `ndarray` *in its view*.
// This function corresponds to `ndarray.nbytes`
SizeT nbytes() {
return this->size() * itemsize;
}
void set_pelement_value(uint8_t* pelement, const uint8_t* pvalue) {
__builtin_memcpy(pelement, pvalue, itemsize);
}
uint8_t* get_pelement_by_indices(const SizeT *indices) {
uint8_t* element = data;
for (SizeT dim_i = 0; dim_i < ndims; dim_i++)
element += indices[dim_i] * strides[dim_i];
return element;
}
uint8_t* get_nth_pelement(SizeT nth) {
irrt_assert(0 <= nth);
irrt_assert(nth < this->size());
SizeT* indices = (SizeT*) __builtin_alloca(sizeof(SizeT) * this->ndims);
ndarray_util::set_indices_by_nth(this->ndims, this->shape, indices, nth);
return get_pelement_by_indices(indices);
}
// Get pointer to the first element of this ndarray, assuming
// `this->size() > 0`, i.e., not "degenerate" due to zeroes in `this->shape`)
//
// This is particularly useful for when the ndarray is just containing a single scalar.
uint8_t* get_first_pelement() {
irrt_assert(this->size() > 0);
return this->data; // ...It is simply `this->data`
}
// Is the given `indices` valid/in-bounds?
bool in_bounds(const SizeT *indices) {
for (SizeT dim_i = 0; dim_i < ndims; dim_i++) {
bool dim_ok = indices[dim_i] < shape[dim_i];
if (!dim_ok) return false;
}
return true;
}
// Fill the ndarray with a value
void fill_generic(const uint8_t* pvalue) {
NDArrayIndicesIter<SizeT> iter;
iter.ndims = this->ndims;
iter.shape = this->shape;
iter.indices = (SizeT*) __builtin_alloca(sizeof(SizeT) * ndims);
iter.set_indices_zero();
for (SizeT i = 0; i < this->size(); i++, iter.next()) {
uint8_t* pelement = get_pelement_by_indices(iter.indices);
set_pelement_value(pelement, pvalue);
}
}
// Set the strides of the ndarray with `ndarray_util::set_strides_by_shape`
void set_strides_by_shape() {
ndarray_util::set_strides_by_shape(itemsize, ndims, strides, shape);
}
// https://numpy.org/doc/stable/reference/generated/numpy.eye.html
void set_to_eye(SizeT k, const uint8_t* zero_pvalue, const uint8_t* one_pvalue) {
__builtin_assume(ndims == 2);
// TODO: Better implementation
fill_generic(zero_pvalue);
for (SizeT i = 0; i < min(shape[0], shape[1]); i++) {
SizeT row = i;
SizeT col = i + k;
SizeT indices[2] = { row, col };
if (!in_bounds(indices)) continue;
uint8_t* pelement = get_pelement_by_indices(indices);
set_pelement_value(pelement, one_pvalue);
}
}
// To support numpy complex slices (e.g., `my_array[:50:2,4,:2:-1]`)
//
// Things assumed by this function:
// - `dst_ndarray` is allocated by the caller
// - `dst_ndarray.ndims` has the correct value (according to `ndarray_util::deduce_ndims_after_slicing`).
// - ... and `dst_ndarray.shape` and `dst_ndarray.strides` have been allocated by the caller as well
//
// Other notes:
// - `dst_ndarray->data` does not have to be set, it will be derived.
// - `dst_ndarray->itemsize` does not have to be set, it will be set to `this->itemsize`
// - `dst_ndarray->shape` and `dst_ndarray.strides` can contain empty values
void slice(SizeT num_ndslices, NDSlice* ndslices, NDArray<SizeT>* dst_ndarray) {
// REFERENCE CODE (check out `_index_helper` in `__getitem__`):
// https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L652
irrt_assert(dst_ndarray->ndims == ndarray_util::deduce_ndims_after_slicing(this->ndims, num_ndslices, ndslices));
dst_ndarray->data = this->data;
SizeT this_axis = 0;
SizeT dst_axis = 0;
for (SizeT i = 0; i < num_ndslices; i++) {
NDSlice *ndslice = &ndslices[i];
if (ndslice->type == INPUT_SLICE_TYPE_INDEX) {
// Handle when the ndslice is just a single (possibly negative) integer
// e.g., `my_array[::2, -5, ::-1]`
// ^^------ like this
SizeT index_user = *((SizeT*) ndslice->slice);
SizeT index = resolve_index_in_length(this->shape[this_axis], index_user);
dst_ndarray->data += index * this->strides[this_axis]; // Add offset
// Next
this_axis++;
} else if (ndslice->type == INPUT_SLICE_TYPE_SLICE) {
// Handle when the ndslice is a slice (represented by UserSlice in IRRT)
// e.g., `my_array[::2, -5, ::-1]`
// ^^^------^^^^----- like these
UserSlice<SizeT>* user_slice = (UserSlice<SizeT>*) ndslice->slice;
Slice<SizeT> slice = user_slice->indices(this->shape[this_axis]); // To resolve negative indices and other funny stuff written by the user
// NOTE: There is no need to write special code to handle negative steps/strides.
// This simple implementation meticulously handles both positive and negative steps/strides.
// Check out the tinynumpy and IRRT's test cases if you are not convinced.
dst_ndarray->data += slice.start * this->strides[this_axis]; // Add offset (NOTE: no need to `* itemsize`, strides count in # of bytes)
dst_ndarray->strides[dst_axis] = slice.step * this->strides[this_axis]; // Determine stride
dst_ndarray->shape[dst_axis] = slice.len(); // Determine shape dimension
// Next
dst_axis++;
this_axis++;
} else {
__builtin_unreachable();
}
}
irrt_assert(dst_axis == dst_ndarray->ndims); // Sanity check on the implementation
}
// Similar to `np.broadcast_to(<ndarray>, <target_shape>)`
// Assumptions:
// - `this` has to be fully initialized.
// - `dst_ndarray->ndims` has to be set.
// - `dst_ndarray->shape` has to be set, this determines the shape `this` broadcasts to.
//
// Other notes:
// - `dst_ndarray->data` does not have to be set, it will be set to `this->data`.
// - `dst_ndarray->itemsize` does not have to be set, it will be set to `this->data`.
// - `dst_ndarray->strides` does not have to be set, it will be overwritten.
//
// Cautions:
// ```
// xs = np.zeros((4,))
// ys = np.zero((4, 1))
// ys[:] = xs # ok
//
// xs = np.zeros((1, 4))
// ys = np.zero((4,))
// ys[:] = xs # allowed
// # However `np.broadcast_to(xs, (4,))` would fails, as per numpy's broadcasting rule.
// # and apparently numpy will "deprecate" this? SEE https://github.com/numpy/numpy/issues/21744
// # This implementation will NOT support this assignment.
// ```
void broadcast_to(NDArray<SizeT>* dst_ndarray) {
dst_ndarray->data = this->data;
dst_ndarray->itemsize = this->itemsize;
irrt_assert(
ndarray_util::can_broadcast_shape_to(
dst_ndarray->ndims,
dst_ndarray->shape,
this->ndims,
this->shape
)
);
SizeT stride_product = 1;
for (SizeT i = 0; i < max(this->ndims, dst_ndarray->ndims); i++) {
SizeT this_dim_i = this->ndims - i - 1;
SizeT dst_dim_i = dst_ndarray->ndims - i - 1;
bool this_dim_exists = this_dim_i >= 0;
bool dst_dim_exists = dst_dim_i >= 0;
// TODO: Explain how this works
bool c1 = this_dim_exists && this->shape[this_dim_i] == 1;
bool c2 = dst_dim_exists && dst_ndarray->shape[dst_dim_i] != 1;
if (!this_dim_exists || (c1 && c2)) {
dst_ndarray->strides[dst_dim_i] = 0; // Freeze it in-place
} else {
dst_ndarray->strides[dst_dim_i] = stride_product * this->itemsize;
stride_product *= this->shape[this_dim_i]; // NOTE: this_dim_exist must be true here.
}
}
}
// Simulates `this_ndarray[:] = src_ndarray`, with automatic broadcasting.
// Caution on https://github.com/numpy/numpy/issues/21744
// Also see `NDArray::broadcast_to`
void assign_with(NDArray<SizeT>* src_ndarray) {
irrt_assert(
ndarray_util::can_broadcast_shape_to(
this->ndims,
this->shape,
src_ndarray->ndims,
src_ndarray->shape
)
);
// Broadcast the `src_ndarray` to make the reading process *much* easier
SizeT* broadcasted_src_ndarray_strides = __builtin_alloca(sizeof(SizeT) * this->ndims); // Remember to allocate strides beforehand
NDArray<SizeT> broadcasted_src_ndarray = {
.ndims = this->ndims,
.shape = this->shape,
.strides = broadcasted_src_ndarray_strides
};
src_ndarray->broadcast_to(&broadcasted_src_ndarray);
// Using iter instead of `get_nth_pelement` because it is slightly faster
SizeT* indices = __builtin_alloca(sizeof(SizeT) * this->ndims);
auto iter = NDArrayIndicesIter<SizeT> {
.ndims = this->ndims,
.shape = this->shape,
.indices = indices
};
const SizeT this_size = this->size();
for (SizeT i = 0; i < this_size; i++, iter.next()) {
uint8_t* src_pelement = broadcasted_src_ndarray_strides->get_pelement_by_indices(indices);
uint8_t* this_pelement = this->get_pelement_by_indices(indices);
this->set_pelement_value(src_pelement, src_pelement);
}
}
};
}
extern "C" {
uint32_t __nac3_ndarray_size(NDArray<int32_t>* ndarray) {
return ndarray->size();
}
uint64_t __nac3_ndarray_size64(NDArray<int64_t>* ndarray) {
return ndarray->size();
}
void __nac3_ndarray_fill_generic(NDArray<int32_t>* ndarray, uint8_t* pvalue) {
ndarray->fill_generic(pvalue);
}
void __nac3_ndarray_fill_generic64(NDArray<int64_t>* ndarray, uint8_t* pvalue) {
ndarray->fill_generic(pvalue);
}
// void __nac3_ndarray_slice(NDArray<int32_t>* ndarray, int32_t num_slices, NDSlice<int32_t> *slices, NDArray<int32_t> *dst_ndarray) {
// // ndarray->slice(num_slices, slices, dst_ndarray);
// }
}

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#pragma once
#include "irrt_utils.hpp"
#include "irrt_typedefs.hpp"
namespace {
// A proper slice in IRRT, all negative indices have be resolved to absolute values.
// Even though nac3core's slices are always `int32_t`, we will template slice anyway
// since this struct is used as a general utility.
template <typename T>
struct Slice {
T start;
T stop;
T step;
// The length/The number of elements of the slice if it were a range,
// i.e., the value of `len(range(this->start, this->stop, this->end))`
T len() {
T diff = stop - start;
if (diff > 0 && step > 0) {
return ((diff - 1) / step) + 1;
} else if (diff < 0 && step < 0) {
return ((diff + 1) / step) + 1;
} else {
return 0;
}
}
};
template<typename T>
T resolve_index_in_length(T length, T index) {
irrt_assert(length >= 0);
if (index < 0) {
// Remember that index is negative, so do a plus here
return max(length + index, 0);
} else {
return min(length, index);
}
}
// NOTE: using a bitfield for the `*_defined` is better, at the
// cost of a more annoying implementation in nac3core inkwell
template <typename T>
struct UserSlice {
uint8_t start_defined;
T start;
uint8_t stop_defined;
T stop;
uint8_t step_defined;
T step;
// Like Python's `slice(start, stop, step).indices(length)`
Slice<T> indices(T length) {
// NOTE: This function implements Python's `slice.indices` *FAITHFULLY*.
// SEE: https://github.com/python/cpython/blob/f62161837e68c1c77961435f1b954412dd5c2b65/Objects/sliceobject.c#L546
irrt_assert(length >= 0);
irrt_assert(!step_defined || step != 0); // step_defined -> step != 0; step cannot be zero if specified by user
Slice<T> result;
result.step = step_defined ? step : 1;
bool step_is_negative = result.step < 0;
if (start_defined) {
result.start = resolve_index_in_length(length, start);
} else {
result.start = step_is_negative ? length - 1 : 0;
}
if (stop_defined) {
result.stop = resolve_index_in_length(length, stop);
} else {
result.stop = step_is_negative ? -1 : length;
}
return result;
}
};
}

648
nac3core/irrt/irrt_test.cpp Normal file
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// This file will be compiled like a real C++ program,
// and we do have the luxury to use the standard libraries.
// That is if the nix flakes do not have issues... especially on msys2...
#include <cstdint>
#include <cstdio>
#include <cstdlib>
// Set `IRRT_DONT_TYPEDEF_INTS` because `cstdint` defines them
#define IRRT_DONT_TYPEDEF_INTS
#include "irrt_everything.hpp"
void test_fail() {
printf("[!] Test failed\n");
exit(1);
}
void __begin_test(const char* function_name, const char* file, int line) {
printf("######### Running %s @ %s:%d\n", function_name, file, line);
}
#define BEGIN_TEST() __begin_test(__FUNCTION__, __FILE__, __LINE__)
template <typename T>
void debug_print_array(const char* format, int len, T* as) {
printf("[");
for (int i = 0; i < len; i++) {
if (i != 0) printf(", ");
printf(format, as[i]);
}
printf("]");
}
template <typename T>
void assert_arrays_match(const char* label, const char* format, int len, T* expected, T* got) {
if (!arrays_match(len, expected, got)) {
printf(">>>>>>> %s\n", label);
printf(" Expecting = ");
debug_print_array(format, len, expected);
printf("\n");
printf(" Got = ");
debug_print_array(format, len, got);
printf("\n");
test_fail();
}
}
template <typename T>
void assert_values_match(const char* label, const char* format, T expected, T got) {
if (expected != got) {
printf(">>>>>>> %s\n", label);
printf(" Expecting = ");
printf(format, expected);
printf("\n");
printf(" Got = ");
printf(format, got);
printf("\n");
test_fail();
}
}
void print_repeated(const char *str, int count) {
for (int i = 0; i < count; i++) {
printf("%s", str);
}
}
template<typename SizeT, typename ElementT>
void __print_ndarray_aux(const char *format, bool first, bool last, SizeT* cursor, SizeT depth, NDArray<SizeT>* ndarray) {
// A really lazy recursive implementation
// Add left padding unless its the first entry (since there would be "[[[" before it)
if (!first) {
print_repeated(" ", depth);
}
const SizeT dim = ndarray->shape[depth];
if (depth + 1 == ndarray->ndims) {
// Recursed down to last dimension, print the values in a nice list
printf("[");
SizeT* indices = (SizeT*) __builtin_alloca(sizeof(SizeT) * ndarray->ndims);
for (SizeT i = 0; i < dim; i++) {
ndarray_util::set_indices_by_nth(ndarray->ndims, ndarray->shape, indices, *cursor);
ElementT* pelement = (ElementT*) ndarray->get_pelement_by_indices(indices);
ElementT element = *pelement;
if (i != 0) printf(", "); // List delimiter
printf(format, element);
printf("(@");
debug_print_array("%d", ndarray->ndims, indices);
printf(")");
(*cursor)++;
}
printf("]");
} else {
printf("[");
for (SizeT i = 0; i < ndarray->shape[depth]; i++) {
__print_ndarray_aux<SizeT, ElementT>(
format,
i == 0, // first?
i + 1 == dim, // last?
cursor,
depth + 1,
ndarray
);
}
printf("]");
}
// Add newline unless its the last entry (since there will be "]]]" after it)
if (!last) {
print_repeated("\n", depth);
}
}
template<typename SizeT, typename ElementT>
void print_ndarray(const char *format, NDArray<SizeT>* ndarray) {
if (ndarray->ndims == 0) {
printf("<empty ndarray>");
} else {
SizeT cursor = 0;
__print_ndarray_aux<SizeT, ElementT>(format, true, true, &cursor, 0, ndarray);
}
printf("\n");
}
void test_calc_size_from_shape_normal() {
// Test shapes with normal values
BEGIN_TEST();
int32_t shape[4] = { 2, 3, 5, 7 };
assert_values_match("size", "%d", 210, ndarray_util::calc_size_from_shape<int32_t>(4, shape));
}
void test_calc_size_from_shape_has_zero() {
// Test shapes with 0 in them
BEGIN_TEST();
int32_t shape[4] = { 2, 0, 5, 7 };
assert_values_match("size", "%d", 0, ndarray_util::calc_size_from_shape<int32_t>(4, shape));
}
void test_set_strides_by_shape() {
// Test `set_strides_by_shape()`
BEGIN_TEST();
int32_t shape[4] = { 99, 3, 5, 7 };
int32_t strides[4] = { 0 };
ndarray_util::set_strides_by_shape((int32_t) sizeof(int32_t), 4, strides, shape);
int32_t expected_strides[4] = {
105 * sizeof(int32_t),
35 * sizeof(int32_t),
7 * sizeof(int32_t),
1 * sizeof(int32_t)
};
assert_arrays_match("strides", "%u", 4u, expected_strides, strides);
}
void test_ndarray_indices_iter_normal() {
// Test NDArrayIndicesIter normal behavior
BEGIN_TEST();
int32_t shape[3] = { 1, 2, 3 };
int32_t indices[3] = { 0, 0, 0 };
auto iter = NDArrayIndicesIter<int32_t> {
.ndims = 3,
.shape = shape,
.indices = indices
};
assert_arrays_match("indices #0", "%u", 3u, iter.indices, (int32_t[3]) { 0, 0, 0 });
iter.next();
assert_arrays_match("indices #1", "%u", 3u, iter.indices, (int32_t[3]) { 0, 0, 1 });
iter.next();
assert_arrays_match("indices #2", "%u", 3u, iter.indices, (int32_t[3]) { 0, 0, 2 });
iter.next();
assert_arrays_match("indices #3", "%u", 3u, iter.indices, (int32_t[3]) { 0, 1, 0 });
iter.next();
assert_arrays_match("indices #4", "%u", 3u, iter.indices, (int32_t[3]) { 0, 1, 1 });
iter.next();
assert_arrays_match("indices #5", "%u", 3u, iter.indices, (int32_t[3]) { 0, 1, 2 });
iter.next();
assert_arrays_match("indices #6", "%u", 3u, iter.indices, (int32_t[3]) { 0, 0, 0 }); // Loops back
iter.next();
assert_arrays_match("indices #7", "%u", 3u, iter.indices, (int32_t[3]) { 0, 0, 1 });
}
void test_ndarray_fill_generic() {
// Test ndarray fill_generic
BEGIN_TEST();
// Choose a type that's neither int32_t nor uint64_t (candidates of SizeT) to spice it up
// Also make all the octets non-zero, to see if `memcpy` in `fill_generic` is working perfectly.
uint16_t fill_value = 0xFACE;
uint16_t in_data[6] = { 100, 101, 102, 103, 104, 105 }; // Fill `data` with values that != `999`
int32_t in_itemsize = sizeof(uint16_t);
const int32_t in_ndims = 2;
int32_t in_shape[in_ndims] = { 2, 3 };
int32_t in_strides[in_ndims] = {};
NDArray<int32_t> ndarray = {
.data = (uint8_t*) in_data,
.itemsize = in_itemsize,
.ndims = in_ndims,
.shape = in_shape,
.strides = in_strides,
};
ndarray.set_strides_by_shape();
ndarray.fill_generic((uint8_t*) &fill_value); // `fill_generic` here
uint16_t expected_data[6] = { fill_value, fill_value, fill_value, fill_value, fill_value, fill_value };
assert_arrays_match("data", "0x%hX", 6, expected_data, in_data);
}
void test_ndarray_set_to_eye() {
// Test `set_to_eye` behavior (helper function to implement `np.eye()`)
BEGIN_TEST();
double in_data[9] = { 99.0, 99.0, 99.0, 99.0, 99.0, 99.0, 99.0, 99.0, 99.0 };
int32_t in_itemsize = sizeof(double);
const int32_t in_ndims = 2;
int32_t in_shape[in_ndims] = { 3, 3 };
int32_t in_strides[in_ndims] = {};
NDArray<int32_t> ndarray = {
.data = (uint8_t*) in_data,
.itemsize = in_itemsize,
.ndims = in_ndims,
.shape = in_shape,
.strides = in_strides,
};
ndarray.set_strides_by_shape();
double zero = 0.0;
double one = 1.0;
ndarray.set_to_eye(1, (uint8_t*) &zero, (uint8_t*) &one);
assert_values_match("in_data[0]", "%f", 0.0, in_data[0]);
assert_values_match("in_data[1]", "%f", 1.0, in_data[1]);
assert_values_match("in_data[2]", "%f", 0.0, in_data[2]);
assert_values_match("in_data[3]", "%f", 0.0, in_data[3]);
assert_values_match("in_data[4]", "%f", 0.0, in_data[4]);
assert_values_match("in_data[5]", "%f", 1.0, in_data[5]);
assert_values_match("in_data[6]", "%f", 0.0, in_data[6]);
assert_values_match("in_data[7]", "%f", 0.0, in_data[7]);
assert_values_match("in_data[8]", "%f", 0.0, in_data[8]);
}
void test_slice_1() {
// Test `slice(5, None, None).indices(100) == slice(5, 100, 1)`
BEGIN_TEST();
UserSlice<int> user_slice = {
.start_defined = 1,
.start = 5,
.stop_defined = 0,
.step_defined = 0,
};
auto slice = user_slice.indices(100);
assert_values_match("start", "%d", 5, slice.start);
assert_values_match("stop", "%d", 100, slice.stop);
assert_values_match("step", "%d", 1, slice.step);
}
void test_slice_2() {
// Test `slice(400, 999, None).indices(100) == slice(100, 100, 1)`
BEGIN_TEST();
UserSlice<int> user_slice = {
.start_defined = 1,
.start = 400,
.stop_defined = 0,
.step_defined = 0,
};
auto slice = user_slice.indices(100);
assert_values_match("start", "%d", 100, slice.start);
assert_values_match("stop", "%d", 100, slice.stop);
assert_values_match("step", "%d", 1, slice.step);
}
void test_slice_3() {
// Test `slice(-10, -5, None).indices(100) == slice(90, 95, 1)`
BEGIN_TEST();
UserSlice<int> user_slice = {
.start_defined = 1,
.start = -10,
.stop_defined = 1,
.stop = -5,
.step_defined = 0,
};
auto slice = user_slice.indices(100);
assert_values_match("start", "%d", 90, slice.start);
assert_values_match("stop", "%d", 95, slice.stop);
assert_values_match("step", "%d", 1, slice.step);
}
void test_slice_4() {
// Test `slice(None, None, -5).indices(100) == (99, -1, -5)`
BEGIN_TEST();
UserSlice<int> user_slice = {
.start_defined = 0,
.stop_defined = 0,
.step_defined = 1,
.step = -5
};
auto slice = user_slice.indices(100);
assert_values_match("start", "%d", 99, slice.start);
assert_values_match("stop", "%d", -1, slice.stop);
assert_values_match("step", "%d", -5, slice.step);
}
void test_ndslice_1() {
/*
Reference Python code:
```python
ndarray = np.arange(12, dtype=np.float64).reshape((3, 4));
# array([[ 0., 1., 2., 3.],
# [ 4., 5., 6., 7.],
# [ 8., 9., 10., 11.]])
dst_ndarray = ndarray[-2:, 1::2]
# array([[ 5., 7.],
# [ 9., 11.]])
assert dst_ndarray.shape == (2, 2)
assert dst_ndarray.strides == (32, 16)
assert dst_ndarray[0, 0] == 5.0
assert dst_ndarray[0, 1] == 7.0
assert dst_ndarray[1, 0] == 9.0
assert dst_ndarray[1, 1] == 11.0
```
*/
BEGIN_TEST();
double in_data[12] = { 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 };
int32_t in_itemsize = sizeof(double);
const int32_t in_ndims = 2;
int32_t in_shape[in_ndims] = { 3, 4 };
int32_t in_strides[in_ndims] = {};
NDArray<int32_t> ndarray = {
.data = (uint8_t*) in_data,
.itemsize = in_itemsize,
.ndims = in_ndims,
.shape = in_shape,
.strides = in_strides
};
ndarray.set_strides_by_shape();
// Destination ndarray
// As documented, ndims and shape & strides must be allocated and determined by the caller.
const int32_t dst_ndims = 2;
int32_t dst_shape[dst_ndims] = {999, 999}; // Empty values
int32_t dst_strides[dst_ndims] = {999, 999}; // Empty values
NDArray<int32_t> dst_ndarray = {
.data = nullptr,
.ndims = dst_ndims,
.shape = dst_shape,
.strides = dst_strides
};
// Create the slice in `ndarray[-2::, 1::2]`
UserSlice<int32_t> user_slice_1 = {
.start_defined = 1,
.start = -2,
.stop_defined = 0,
.step_defined = 0
};
UserSlice<int32_t> user_slice_2 = {
.start_defined = 1,
.start = 1,
.stop_defined = 0,
.step_defined = 1,
.step = 2
};
const int32_t num_ndslices = 2;
NDSlice ndslices[num_ndslices] = {
{ .type = INPUT_SLICE_TYPE_SLICE, .slice = (uint8_t*) &user_slice_1 },
{ .type = INPUT_SLICE_TYPE_SLICE, .slice = (uint8_t*) &user_slice_2 }
};
ndarray.slice(num_ndslices, ndslices, &dst_ndarray);
int32_t expected_shape[dst_ndims] = { 2, 2 };
int32_t expected_strides[dst_ndims] = { 32, 16 };
assert_arrays_match("shape", "%d", dst_ndims, expected_shape, dst_ndarray.shape);
assert_arrays_match("strides", "%d", dst_ndims, expected_strides, dst_ndarray.strides);
assert_values_match("dst_ndarray[0, 0]", "%f", 5.0, *((double *) dst_ndarray.get_pelement_by_indices((int32_t[dst_ndims]) { 0, 0 })));
assert_values_match("dst_ndarray[0, 1]", "%f", 7.0, *((double *) dst_ndarray.get_pelement_by_indices((int32_t[dst_ndims]) { 0, 1 })));
assert_values_match("dst_ndarray[1, 0]", "%f", 9.0, *((double *) dst_ndarray.get_pelement_by_indices((int32_t[dst_ndims]) { 1, 0 })));
assert_values_match("dst_ndarray[1, 1]", "%f", 11.0, *((double *) dst_ndarray.get_pelement_by_indices((int32_t[dst_ndims]) { 1, 1 })));
}
void test_ndslice_2() {
/*
```python
ndarray = np.arange(12, dtype=np.float64).reshape((3, 4))
# array([[ 0., 1., 2., 3.],
# [ 4., 5., 6., 7.],
# [ 8., 9., 10., 11.]])
dst_ndarray = ndarray[2, ::-2]
# array([11., 9.])
assert dst_ndarray.shape == (2,)
assert dst_ndarray.strides == (-16,)
assert dst_ndarray[0] == 11.0
assert dst_ndarray[1] == 9.0
dst_ndarray[1, 0] == 99 # If you write to `dst_ndarray`
assert ndarray[1, 3] == 99 # `ndarray` also updates!!
```
*/
BEGIN_TEST();
double in_data[12] = { 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 };
int32_t in_itemsize = sizeof(double);
const int32_t in_ndims = 2;
int32_t in_shape[in_ndims] = { 3, 4 };
int32_t in_strides[in_ndims] = {};
NDArray<int32_t> ndarray = {
.data = (uint8_t*) in_data,
.itemsize = in_itemsize,
.ndims = in_ndims,
.shape = in_shape,
.strides = in_strides
};
ndarray.set_strides_by_shape();
// Destination ndarray
// As documented, ndims and shape & strides must be allocated and determined by the caller.
const int32_t dst_ndims = 1;
int32_t dst_shape[dst_ndims] = {999}; // Empty values
int32_t dst_strides[dst_ndims] = {999}; // Empty values
NDArray<int32_t> dst_ndarray = {
.data = nullptr,
.ndims = dst_ndims,
.shape = dst_shape,
.strides = dst_strides
};
// Create the slice in `ndarray[2, ::-2]`
int32_t user_slice_1 = 2;
UserSlice<int32_t> user_slice_2 = {
.start_defined = 0,
.stop_defined = 0,
.step_defined = 1,
.step = -2
};
const int32_t num_ndslices = 2;
NDSlice ndslices[num_ndslices] = {
{ .type = INPUT_SLICE_TYPE_INDEX, .slice = (uint8_t*) &user_slice_1 },
{ .type = INPUT_SLICE_TYPE_SLICE, .slice = (uint8_t*) &user_slice_2 }
};
ndarray.slice(num_ndslices, ndslices, &dst_ndarray);
int32_t expected_shape[dst_ndims] = { 2 };
int32_t expected_strides[dst_ndims] = { -16 };
assert_arrays_match("shape", "%d", dst_ndims, expected_shape, dst_ndarray.shape);
assert_arrays_match("strides", "%d", dst_ndims, expected_strides, dst_ndarray.strides);
// [5.0, 3.0]
assert_values_match("dst_ndarray[0]", "%f", 11.0, *((double *) dst_ndarray.get_pelement_by_indices((int32_t[dst_ndims]) { 0 })));
assert_values_match("dst_ndarray[1]", "%f", 9.0, *((double *) dst_ndarray.get_pelement_by_indices((int32_t[dst_ndims]) { 1 })));
}
void test_can_broadcast_shape() {
BEGIN_TEST();
assert_values_match(
"can_broadcast_shape_to([3], [1, 1, 1, 1, 3]) == true",
"%d",
true,
ndarray_util::can_broadcast_shape_to(1, (int32_t[]) { 3 }, 5, (int32_t[]) { 1, 1, 1, 1, 3 })
);
assert_values_match(
"can_broadcast_shape_to([3], [3, 1]) == false",
"%d",
false,
ndarray_util::can_broadcast_shape_to(1, (int32_t[]) { 3 }, 2, (int32_t[]) { 3, 1 }));
assert_values_match(
"can_broadcast_shape_to([3], [3]) == true",
"%d",
true,
ndarray_util::can_broadcast_shape_to(1, (int32_t[]) { 3 }, 1, (int32_t[]) { 3 }));
assert_values_match(
"can_broadcast_shape_to([1], [3]) == false",
"%d",
false,
ndarray_util::can_broadcast_shape_to(1, (int32_t[]) { 1 }, 1, (int32_t[]) { 3 }));
assert_values_match(
"can_broadcast_shape_to([1], [1]) == true",
"%d",
true,
ndarray_util::can_broadcast_shape_to(1, (int32_t[]) { 1 }, 1, (int32_t[]) { 1 }));
assert_values_match(
"can_broadcast_shape_to([256, 256, 3], [256, 1, 3]) == true",
"%d",
true,
ndarray_util::can_broadcast_shape_to(3, (int32_t[]) { 256, 256, 3 }, 3, (int32_t[]) { 256, 1, 3 })
);
assert_values_match(
"can_broadcast_shape_to([256, 256, 3], [3]) == true",
"%d",
true,
ndarray_util::can_broadcast_shape_to(3, (int32_t[]) { 256, 256, 3 }, 1, (int32_t[]) { 3 })
);
assert_values_match(
"can_broadcast_shape_to([256, 256, 3], [2]) == false",
"%d",
false,
ndarray_util::can_broadcast_shape_to(3, (int32_t[]) { 256, 256, 3 }, 1, (int32_t[]) { 2 })
);
assert_values_match(
"can_broadcast_shape_to([256, 256, 3], [1]) == true",
"%d",
true,
ndarray_util::can_broadcast_shape_to(3, (int32_t[]) { 256, 256, 3 }, 1, (int32_t[]) { 1 })
);
// In cases when the shapes contain zero(es)
assert_values_match(
"can_broadcast_shape_to([0], [1]) == true",
"%d",
true,
ndarray_util::can_broadcast_shape_to(1, (int32_t[]) { 0 }, 1, (int32_t[]) { 1 })
);
assert_values_match(
"can_broadcast_shape_to([0], [2]) == false",
"%d",
false,
ndarray_util::can_broadcast_shape_to(1, (int32_t[]) { 0 }, 1, (int32_t[]) { 2 })
);
assert_values_match(
"can_broadcast_shape_to([0, 4, 0, 0], [1]) == true",
"%d",
true,
ndarray_util::can_broadcast_shape_to(4, (int32_t[]) { 0, 4, 0, 0 }, 1, (int32_t[]) { 1 })
);
assert_values_match(
"can_broadcast_shape_to([0, 4, 0, 0], [1, 1, 1, 1]) == true",
"%d",
true,
ndarray_util::can_broadcast_shape_to(4, (int32_t[]) { 0, 4, 0, 0 }, 4, (int32_t[]) { 1, 1, 1, 1 })
);
assert_values_match(
"can_broadcast_shape_to([0, 4, 0, 0], [1, 4, 1, 1]) == true",
"%d",
true,
ndarray_util::can_broadcast_shape_to(4, (int32_t[]) { 0, 4, 0, 0 }, 4, (int32_t[]) { 1, 4, 1, 1 })
);
assert_values_match(
"can_broadcast_shape_to([4, 3], [0, 3]) == false",
"%d",
false,
ndarray_util::can_broadcast_shape_to(2, (int32_t[]) { 4, 3 }, 2, (int32_t[]) { 0, 3 })
);
assert_values_match(
"can_broadcast_shape_to([4, 3], [0, 0]) == false",
"%d",
false,
ndarray_util::can_broadcast_shape_to(2, (int32_t[]) { 4, 3 }, 2, (int32_t[]) { 0, 0 })
);
}
void test_ndarray_broadcast_1() {
/*
# array = np.array([[19.9, 29.9, 39.9, 49.9]], dtype=np.float64)
# >>> [[19.9 29.9 39.9 49.9]]
#
# array = np.broadcast_to(array, (2, 3, 4))
# >>> [[[19.9 29.9 39.9 49.9]
# >>> [19.9 29.9 39.9 49.9]
# >>> [19.9 29.9 39.9 49.9]]
# >>> [[19.9 29.9 39.9 49.9]
# >>> [19.9 29.9 39.9 49.9]
# >>> [19.9 29.9 39.9 49.9]]]
#
# assery array.strides == (0, 0, 8)
*/
BEGIN_TEST();
double in_data[4] = { 19.9, 29.9, 39.9, 49.9 };
const int32_t in_ndims = 2;
int32_t in_shape[in_ndims] = {1, 4};
int32_t in_strides[in_ndims] = {};
NDArray<int32_t> ndarray = {
.data = (uint8_t*) in_data,
.itemsize = sizeof(double),
.ndims = in_ndims,
.shape = in_shape,
.strides = in_strides
};
ndarray.set_strides_by_shape();
const int32_t dst_ndims = 3;
int32_t dst_shape[dst_ndims] = {2, 3, 4};
int32_t dst_strides[dst_ndims] = {};
NDArray<int32_t> dst_ndarray = {
.ndims = dst_ndims,
.shape = dst_shape,
.strides = dst_strides
};
ndarray.broadcast_to(&dst_ndarray);
assert_arrays_match("dst_ndarray->strides", "%d", dst_ndims, (int32_t[]) { 0, 0, 8 }, dst_ndarray.strides);
assert_values_match("dst_ndarray[0, 0, 0]", "%f", 19.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 0, 0})));
assert_values_match("dst_ndarray[0, 0, 1]", "%f", 29.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 0, 1})));
assert_values_match("dst_ndarray[0, 0, 2]", "%f", 39.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 0, 2})));
assert_values_match("dst_ndarray[0, 0, 3]", "%f", 49.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 0, 3})));
assert_values_match("dst_ndarray[0, 1, 0]", "%f", 19.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 1, 0})));
assert_values_match("dst_ndarray[0, 1, 1]", "%f", 29.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 1, 1})));
assert_values_match("dst_ndarray[0, 1, 2]", "%f", 39.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 1, 2})));
assert_values_match("dst_ndarray[0, 1, 3]", "%f", 49.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 1, 3})));
assert_values_match("dst_ndarray[1, 2, 3]", "%f", 49.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {1, 2, 3})));
}
int main() {
test_calc_size_from_shape_normal();
test_calc_size_from_shape_has_zero();
test_set_strides_by_shape();
test_ndarray_indices_iter_normal();
test_ndarray_fill_generic();
test_ndarray_set_to_eye();
test_slice_1();
test_slice_2();
test_slice_3();
test_slice_4();
test_ndslice_1();
test_ndslice_2();
test_can_broadcast_shape();
test_ndarray_broadcast_1();
return 0;
}

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@ -0,0 +1,14 @@
#pragma once
// This is made toggleable since `irrt_test.cpp` itself would include
// headers that define the `int_t` family.
#ifndef IRRT_DONT_TYPEDEF_INTS
typedef _BitInt(8) int8_t;
typedef unsigned _BitInt(8) uint8_t;
typedef _BitInt(32) int32_t;
typedef unsigned _BitInt(32) uint32_t;
typedef _BitInt(64) int64_t;
typedef unsigned _BitInt(64) uint64_t;
#endif
typedef int32_t SliceIndex;

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@ -0,0 +1,37 @@
#pragma once
#include "irrt_typedefs.hpp"
namespace {
template <typename T>
T max(T a, T b) {
return a > b ? a : b;
}
template <typename T>
T min(T a, T b) {
return a > b ? b : a;
}
template <typename T>
bool arrays_match(int len, T *as, T *bs) {
for (int i = 0; i < len; i++) {
if (as[i] != bs[i]) return false;
}
return true;
}
void irrt_panic() {
// Crash the program for now.
// TODO: Don't crash the program
// ... or at least produce a good message when doing testing IRRT
uint8_t* death = nullptr;
*death = 0; // TODO: address 0 on hardware might be writable?
}
// TODO: Make this a macro and allow it to be toggled on/off (e.g., debug vs release)
void irrt_assert(bool condition) {
if (!condition) irrt_panic();
}
}

File diff suppressed because it is too large Load Diff

View File

@ -1,16 +1,19 @@
use inkwell::{
context::Context,
types::{AnyTypeEnum, ArrayType, BasicType, BasicTypeEnum, IntType, PointerType, StructType},
values::{ArrayValue, BasicValue, BasicValueEnum, IntValue, PointerValue, StructValue},
AddressSpace, IntPredicate,
};
use super::{
irrt::{call_ndarray_calc_size, call_ndarray_flatten_index},
use crate::codegen::{
// irrt::{call_ndarray_calc_size, call_ndarray_flatten_index},
llvm_intrinsics::call_int_umin,
stmt::gen_for_callback_incrementing,
CodeGenContext, CodeGenerator,
CodeGenContext,
CodeGenerator,
};
use inkwell::context::Context;
use inkwell::types::{ArrayType, BasicType, StructType};
use inkwell::values::{ArrayValue, BasicValue, StructValue};
use inkwell::{
types::{AnyTypeEnum, BasicTypeEnum, IntType, PointerType},
values::{BasicValueEnum, IntValue, PointerValue},
AddressSpace, IntPredicate,
};
use itertools::Itertools;
/// A LLVM type that is used to represent a non-primitive type in NAC3.
pub trait ProxyType<'ctx>: Into<Self::Base> {
@ -1207,25 +1210,27 @@ impl<'ctx> NDArrayType<'ctx> {
ctx: &'ctx Context,
dtype: BasicTypeEnum<'ctx>,
) -> Self {
let llvm_usize = generator.get_size_type(ctx);
todo!()
// struct NDArray { num_dims: size_t, dims: size_t*, data: T* }
//
// * num_dims: Number of dimensions in the array
// * dims: Pointer to an array containing the size of each dimension
// * data: Pointer to an array containing the array data
let llvm_ndarray = ctx
.struct_type(
&[
llvm_usize.into(),
llvm_usize.ptr_type(AddressSpace::default()).into(),
dtype.ptr_type(AddressSpace::default()).into(),
],
false,
)
.ptr_type(AddressSpace::default());
// let llvm_usize = generator.get_size_type(ctx);
NDArrayType::from_type(llvm_ndarray, llvm_usize)
// // struct NDArray { num_dims: size_t, dims: size_t*, data: T* }
// //
// // * num_dims: Number of dimensions in the array
// // * dims: Pointer to an array containing the size of each dimension
// // * data: Pointer to an array containing the array data
// let llvm_ndarray = ctx
// .struct_type(
// &[
// llvm_usize.into(),
// llvm_usize.ptr_type(AddressSpace::default()).into(),
// dtype.ptr_type(AddressSpace::default()).into(),
// ],
// false,
// )
// .ptr_type(AddressSpace::default());
// NDArrayType::from_type(llvm_ndarray, llvm_usize)
}
/// Creates an [`NDArrayType`] from a [`PointerType`].
@ -1249,13 +1254,11 @@ impl<'ctx> NDArrayType<'ctx> {
/// Returns the element type of this `ndarray` type.
#[must_use]
pub fn element_type(&self) -> AnyTypeEnum<'ctx> {
pub fn element_type(&self) -> BasicTypeEnum<'ctx> {
self.as_base_type()
.get_element_type()
.into_struct_type()
.get_field_type_at_index(2)
.map(BasicTypeEnum::into_pointer_type)
.map(PointerType::get_element_type)
.unwrap()
}
}
@ -1405,7 +1408,7 @@ impl<'ctx> NDArrayValue<'ctx> {
/// Returns the double-indirection pointer to the `data` array, as if by calling `getelementptr`
/// on the field.
pub fn ptr_to_data(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
fn ptr_to_data(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
let llvm_i32 = ctx.ctx.i32_type();
let var_name = self.name.map(|v| format!("{v}.data.addr")).unwrap_or_default();
@ -1602,7 +1605,8 @@ impl<'ctx> ArrayLikeValue<'ctx> for NDArrayDataProxy<'ctx, '_> {
ctx: &CodeGenContext<'ctx, '_>,
generator: &G,
) -> IntValue<'ctx> {
call_ndarray_calc_size(generator, ctx, &self.as_slice_value(ctx, generator), (None, None))
todo!()
// call_ndarray_calc_size(generator, ctx, &self.as_slice_value(ctx, generator), (None, None))
}
}
@ -1660,33 +1664,34 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
indices: &Index,
name: Option<&str>,
) -> PointerValue<'ctx> {
let llvm_usize = generator.get_size_type(ctx.ctx);
todo!()
// let llvm_usize = generator.get_size_type(ctx.ctx);
let indices_elem_ty = indices
.ptr_offset(ctx, generator, &llvm_usize.const_zero(), None)
.get_type()
.get_element_type();
let Ok(indices_elem_ty) = IntType::try_from(indices_elem_ty) else {
panic!("Expected list[int32] but got {indices_elem_ty}")
};
assert_eq!(
indices_elem_ty.get_bit_width(),
32,
"Expected list[int32] but got list[int{}]",
indices_elem_ty.get_bit_width()
);
// let indices_elem_ty = indices
// .ptr_offset(ctx, generator, &llvm_usize.const_zero(), None)
// .get_type()
// .get_element_type();
// let Ok(indices_elem_ty) = IntType::try_from(indices_elem_ty) else {
// panic!("Expected list[int32] but got {indices_elem_ty}")
// };
// assert_eq!(
// indices_elem_ty.get_bit_width(),
// 32,
// "Expected list[int32] but got list[int{}]",
// indices_elem_ty.get_bit_width()
// );
let index = call_ndarray_flatten_index(generator, ctx, *self.0, indices);
// let index = call_ndarray_flatten_index(generator, ctx, *self.0, indices);
unsafe {
ctx.builder
.build_in_bounds_gep(
self.base_ptr(ctx, generator),
&[index],
name.unwrap_or_default(),
)
.unwrap()
}
// unsafe {
// ctx.builder
// .build_in_bounds_gep(
// self.base_ptr(ctx, generator),
// &[index],
// name.unwrap_or_default(),
// )
// .unwrap()
// }
}
fn ptr_offset<G: CodeGenerator + ?Sized>(
@ -1718,7 +1723,6 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(len, false),
|generator, ctx, _, i| {
@ -1763,3 +1767,341 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> UntypedArrayLikeMutator<'ctx,
for NDArrayDataProxy<'ctx, '_>
{
}
#[derive(Debug, Clone, Copy)]
pub struct StructField<'ctx> {
/// The GEP index of this struct field.
pub gep_index: u32,
/// Name of this struct field.
///
/// Used for generating names.
pub name: &'static str,
/// The type of this struct field.
pub ty: BasicTypeEnum<'ctx>,
}
pub struct StructFields<'ctx> {
/// Name of the struct.
///
/// Used for generating names.
pub name: &'static str,
/// All the [`StructField`]s of this struct.
///
/// **NOTE:** The index position of a [`StructField`]
/// matches the element's [`StructField::index`].
pub fields: Vec<StructField<'ctx>>,
}
struct StructFieldsBuilder<'ctx> {
gep_index_counter: u32,
/// Name of the struct to be built.
name: &'static str,
fields: Vec<StructField<'ctx>>,
}
impl<'ctx> StructField<'ctx> {
/// TODO: DOCUMENT ME
pub fn gep(
&self,
ctx: &CodeGenContext<'ctx, '_>,
struct_ptr: PointerValue<'ctx>,
) -> PointerValue<'ctx> {
let index_type = ctx.ctx.i32_type(); // TODO: I think I'm not supposed to use i32 for GEP like that
unsafe {
ctx.builder
.build_in_bounds_gep(
struct_ptr,
&[index_type.const_zero(), index_type.const_int(self.gep_index as u64, false)],
self.name,
)
.unwrap()
}
}
/// TODO: DOCUMENT ME
pub fn load(
&self,
ctx: &CodeGenContext<'ctx, '_>,
struct_ptr: PointerValue<'ctx>,
) -> BasicValueEnum<'ctx> {
ctx.builder.build_load(self.gep(ctx, struct_ptr), self.name).unwrap()
}
/// TODO: DOCUMENT ME
pub fn store<V>(&self, ctx: &CodeGenContext<'ctx, '_>, struct_ptr: PointerValue<'ctx>, value: V)
where
V: BasicValue<'ctx>,
{
ctx.builder.build_store(self.gep(ctx, struct_ptr), value).unwrap();
}
}
type IsInstanceError = String;
type IsInstanceResult = Result<(), IsInstanceError>;
pub fn check_basic_types_match<'ctx, A, B>(expected: A, got: B) -> IsInstanceResult
where
A: BasicType<'ctx>,
B: BasicType<'ctx>,
{
let expected = expected.as_basic_type_enum();
let got = got.as_basic_type_enum();
// Put those logic into here,
// otherwise there is always a fallback reporting on any kind of mismatch
match (expected, got) {
(BasicTypeEnum::IntType(expected), BasicTypeEnum::IntType(got)) => {
if expected.get_bit_width() != got.get_bit_width() {
return Err(format!(
"Expected IntType ({expected}-bit(s)), got IntType ({got}-bit(s))"
));
}
}
(expected, got) => {
if expected != got {
return Err(format!("Expected {expected}, got {got}"));
}
}
}
Ok(())
}
impl<'ctx> StructFields<'ctx> {
pub fn num_fields(&self) -> u32 {
self.fields.len() as u32
}
pub fn get_struct_type(&self, ctx: &'ctx Context) -> StructType<'ctx> {
let llvm_fields = self.fields.iter().map(|field| field.ty).collect_vec();
ctx.struct_type(llvm_fields.as_slice(), false)
}
pub fn is_type(&self, scrutinee: StructType<'ctx>) -> IsInstanceResult {
// Check scrutinee's number of struct fields
if scrutinee.count_fields() != self.num_fields() {
return Err(format!(
"Expected {expected_count} field(s) in `{struct_name}` type, got {got_count}",
struct_name = self.name,
expected_count = self.num_fields(),
got_count = scrutinee.count_fields(),
));
}
// Check the scrutinee's field types
for field in self.fields.iter() {
let expected_field_ty = field.ty;
let got_field_ty = scrutinee.get_field_type_at_index(field.gep_index).unwrap();
if let Err(field_err) = check_basic_types_match(expected_field_ty, got_field_ty) {
return Err(format!(
"Field GEP index {gep_index} does not match the expected type of ({struct_name}::{field_name}): {field_err}",
gep_index = field.gep_index,
struct_name = self.name,
field_name = field.name,
));
}
}
// Done
Ok(())
}
}
impl<'ctx> StructFieldsBuilder<'ctx> {
fn start(name: &'static str) -> Self {
StructFieldsBuilder { gep_index_counter: 0, name, fields: Vec::new() }
}
fn add_field(&mut self, name: &'static str, ty: BasicTypeEnum<'ctx>) -> StructField<'ctx> {
let index = self.gep_index_counter;
self.gep_index_counter += 1;
let field = StructField { gep_index: index, name, ty };
self.fields.push(field); // Register into self.fields
field // Return to the caller to conveniently let them do whatever they want
}
fn end(self) -> StructFields<'ctx> {
StructFields { name: self.name, fields: self.fields }
}
}
#[derive(Debug, Clone, Copy)]
pub struct NpArrayType<'ctx> {
pub size_type: IntType<'ctx>,
pub elem_type: BasicTypeEnum<'ctx>,
}
pub struct NpArrayStructFields<'ctx> {
pub whole_struct: StructFields<'ctx>,
pub data: StructField<'ctx>,
pub itemsize: StructField<'ctx>,
pub ndims: StructField<'ctx>,
pub shape: StructField<'ctx>,
pub strides: StructField<'ctx>,
}
impl<'ctx> NpArrayType<'ctx> {
pub fn new_opaque_elem(
ctx: &CodeGenContext<'ctx, '_>,
size_type: IntType<'ctx>,
) -> NpArrayType<'ctx> {
NpArrayType { size_type, elem_type: ctx.ctx.i8_type().as_basic_type_enum() }
}
pub fn get_struct_type(&self, ctx: &'ctx Context) -> StructType<'ctx> {
self.fields().whole_struct.get_struct_type(ctx)
}
pub fn fields(&self) -> NpArrayStructFields<'ctx> {
let mut builder = StructFieldsBuilder::start("NpArray");
let addrspace = AddressSpace::default();
let byte_type = self.size_type.get_context().i8_type();
// Make sure the struct matches PERFECTLY with that defined in `nac3core/irrt`.
let data = builder.add_field("data", byte_type.ptr_type(addrspace).into());
let itemsize = builder.add_field("itemsize", self.size_type.into());
let ndims = builder.add_field("ndims", self.size_type.into());
let shape = builder.add_field("shape", self.size_type.ptr_type(addrspace).into());
let strides = builder.add_field("strides", self.size_type.ptr_type(addrspace).into());
NpArrayStructFields { whole_struct: builder.end(), data, itemsize, ndims, shape, strides }
}
/// Allocate an `ndarray` on stack, with the following notes:
///
/// - `ndarray.ndims` will be initialized to `in_ndims`.
/// - `ndarray.itemsize` will be initialized to the size of `self.elem_type.size_of()`.
/// - `ndarray.shape` and `ndarray.strides` will be allocated on the stack with number of elements being `in_ndims`,
/// all with empty/uninitialized values.
pub fn var_alloc<G>(
&self,
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
in_ndims: IntValue<'ctx>,
name: Option<&str>,
) -> NpArrayValue<'ctx>
where
G: CodeGenerator + ?Sized,
{
let ptr = generator
.gen_var_alloc(ctx, self.get_struct_type(ctx.ctx).as_basic_type_enum(), name)
.unwrap();
// Allocate `in_dims` number of `size_type` on the stack for `shape` and `strides`
let allocated_shape = generator
.gen_array_var_alloc(
ctx,
self.size_type.as_basic_type_enum(),
in_ndims,
Some("allocated_shape"),
)
.unwrap();
let allocated_strides = generator
.gen_array_var_alloc(
ctx,
self.size_type.as_basic_type_enum(),
in_ndims,
Some("allocated_strides"),
)
.unwrap();
let value = NpArrayValue { ty: *self, ptr };
value.store_ndims(ctx, in_ndims);
value.store_itemsize(ctx, self.elem_type.size_of().unwrap());
value.store_shape(ctx, allocated_shape.base_ptr(ctx, generator));
value.store_strides(ctx, allocated_strides.base_ptr(ctx, generator));
return value;
}
}
#[derive(Debug, Clone, Copy)]
pub struct NpArrayValue<'ctx> {
pub ty: NpArrayType<'ctx>,
pub ptr: PointerValue<'ctx>,
}
impl<'ctx> NpArrayValue<'ctx> {
pub fn load_ndims(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
let field = self.ty.fields().ndims;
field.load(ctx, self.ptr).into_int_value()
}
pub fn store_ndims(&self, ctx: &CodeGenContext<'ctx, '_>, value: IntValue<'ctx>) {
let field = self.ty.fields().ndims;
field.store(ctx, self.ptr, value);
}
pub fn load_itemsize(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
let field = self.ty.fields().itemsize;
field.load(ctx, self.ptr).into_int_value()
}
pub fn store_itemsize(&self, ctx: &CodeGenContext<'ctx, '_>, value: IntValue<'ctx>) {
let field = self.ty.fields().itemsize;
field.store(ctx, self.ptr, value);
}
pub fn load_shape(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
let field = self.ty.fields().shape;
field.load(ctx, self.ptr).into_pointer_value()
}
pub fn store_shape(&self, ctx: &CodeGenContext<'ctx, '_>, value: PointerValue<'ctx>) {
let field = self.ty.fields().shape;
field.store(ctx, self.ptr, value);
}
pub fn load_strides(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
let field = self.ty.fields().strides;
field.load(ctx, self.ptr).into_pointer_value()
}
pub fn store_strides(&self, ctx: &CodeGenContext<'ctx, '_>, value: PointerValue<'ctx>) {
let field = self.ty.fields().strides;
field.store(ctx, self.ptr, value);
}
/// TODO: DOCUMENT ME -- NDIMS WOULD NEVER CHANGE!!!!!
pub fn shape_slice(
&self,
ctx: &CodeGenContext<'ctx, '_>,
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
// Get the pointer to `shape`
let field = self.ty.fields().shape;
let shape = field.load(ctx, self.ptr).into_pointer_value();
// Load `ndims`
let ndims = self.load_ndims(ctx);
TypedArrayLikeAdapter {
adapted: ArraySliceValue(shape, ndims, Some(field.name)),
downcast_fn: Box::new(|_ctx, x| x.into_int_value()),
upcast_fn: Box::new(|_ctx, x| x.as_basic_value_enum()),
}
}
/// TODO: DOCUMENT ME -- NDIMS WOULD NEVER CHANGE!!!!!
pub fn strides_slice(
&self,
ctx: &CodeGenContext<'ctx, '_>,
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
// Get the pointer to `strides`
let field = self.ty.fields().strides;
let strides = field.load(ctx, self.ptr).into_pointer_value();
// Load `ndims`
let ndims = self.load_ndims(ctx);
TypedArrayLikeAdapter {
adapted: ArraySliceValue(strides, ndims, Some(field.name)),
downcast_fn: Box::new(|_ctx, x| x.into_int_value()),
upcast_fn: Box::new(|_ctx, x| x.as_basic_value_enum()),
}
}
}

View File

@ -1,9 +1,3 @@
use std::collections::HashMap;
use indexmap::IndexMap;
use nac3parser::ast::StrRef;
use crate::{
symbol_resolver::SymbolValue,
toplevel::DefinitionId,
@ -15,6 +9,10 @@ use crate::{
},
};
use indexmap::IndexMap;
use nac3parser::ast::StrRef;
use std::collections::HashMap;
pub struct ConcreteTypeStore {
store: Vec<ConcreteTypeEnum>,
}
@ -27,7 +25,6 @@ pub struct ConcreteFuncArg {
pub name: StrRef,
pub ty: ConcreteType,
pub default_value: Option<SymbolValue>,
pub is_vararg: bool,
}
#[derive(Clone, Debug)]
@ -49,7 +46,6 @@ pub enum ConcreteTypeEnum {
TPrimitive(Primitive),
TTuple {
ty: Vec<ConcreteType>,
is_vararg_ctx: bool,
},
TObj {
obj_id: DefinitionId,
@ -106,16 +102,8 @@ impl ConcreteTypeStore {
.iter()
.map(|arg| ConcreteFuncArg {
name: arg.name,
ty: if arg.is_vararg {
let tuple_ty = unifier
.add_ty(TypeEnum::TTuple { ty: vec![arg.ty], is_vararg_ctx: true });
self.from_unifier_type(unifier, primitives, tuple_ty, cache)
} else {
self.from_unifier_type(unifier, primitives, arg.ty, cache)
},
ty: self.from_unifier_type(unifier, primitives, arg.ty, cache),
default_value: arg.default_value.clone(),
is_vararg: arg.is_vararg,
})
.collect(),
ret: self.from_unifier_type(unifier, primitives, signature.ret, cache),
@ -170,12 +158,11 @@ impl ConcreteTypeStore {
cache.insert(ty, None);
let ty_enum = unifier.get_ty(ty);
let result = match &*ty_enum {
TypeEnum::TTuple { ty, is_vararg_ctx } => ConcreteTypeEnum::TTuple {
TypeEnum::TTuple { ty } => ConcreteTypeEnum::TTuple {
ty: ty
.iter()
.map(|t| self.from_unifier_type(unifier, primitives, *t, cache))
.collect(),
is_vararg_ctx: *is_vararg_ctx,
},
TypeEnum::TObj { obj_id, fields, params } => ConcreteTypeEnum::TObj {
obj_id: *obj_id,
@ -261,12 +248,11 @@ impl ConcreteTypeStore {
*cache.get_mut(&cty).unwrap() = Some(ty);
return ty;
}
ConcreteTypeEnum::TTuple { ty, is_vararg_ctx } => TypeEnum::TTuple {
ConcreteTypeEnum::TTuple { ty } => TypeEnum::TTuple {
ty: ty
.iter()
.map(|cty| self.to_unifier_type(unifier, primitives, *cty, cache))
.collect(),
is_vararg_ctx: *is_vararg_ctx,
},
ConcreteTypeEnum::TVirtual { ty } => {
TypeEnum::TVirtual { ty: self.to_unifier_type(unifier, primitives, *ty, cache) }
@ -291,7 +277,6 @@ impl ConcreteTypeStore {
name: arg.name,
ty: self.to_unifier_type(unifier, primitives, arg.ty, cache),
default_value: arg.default_value.clone(),
is_vararg: false,
})
.collect(),
ret: self.to_unifier_type(unifier, primitives, *ret, cache),

File diff suppressed because it is too large Load Diff

View File

@ -1,10 +1,8 @@
use inkwell::{
attributes::{Attribute, AttributeLoc},
values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue},
};
use inkwell::attributes::{Attribute, AttributeLoc};
use inkwell::values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue};
use itertools::Either;
use super::CodeGenContext;
use crate::codegen::CodeGenContext;
/// Macro to generate extern function
/// Both function return type and function parameter type are `FloatValue`
@ -15,11 +13,11 @@ use super::CodeGenContext;
/// * `$extern_fn:literal`: Name of underlying extern function
///
/// Optional Arguments:
/// * `$(,$attributes:literal)*)`: Attributes linked with the extern function.
/// The default attributes are "mustprogress", "nofree", "nounwind", "willreturn", and "writeonly".
/// These will be used unless other attributes are specified
/// * `$(,$attributes:literal)*)`: Attributes linked with the extern function
/// The default attributes are "mustprogress", "nofree", "nounwind", "willreturn", and "writeonly"
/// These will be used unless other attributes are specified
/// * `$(,$args:ident)*`: Operands of the extern function
/// The data type of these operands will be set to `FloatValue`
/// The data type of these operands will be set to `FloatValue`
///
macro_rules! generate_extern_fn {
("unary", $fn_name:ident, $extern_fn:literal) => {
@ -132,62 +130,3 @@ pub fn call_ldexp<'ctx>(
.map(Either::unwrap_left)
.unwrap()
}
/// Macro to generate `np_linalg` and `sp_linalg` functions
/// The function takes as input `NDArray` and returns ()
///
/// Arguments:
/// * `$fn_name:ident`: The identifier of the rust function to be generated
/// * `$extern_fn:literal`: Name of underlying extern function
/// * (2/3/4): Number of `NDArray` that function takes as input
///
/// Note:
/// The operands and resulting `NDArray` are both passed as input to the funcion
/// It is the responsibility of caller to ensure that output `NDArray` is properly allocated on stack
/// The function changes the content of the output `NDArray` in-place
macro_rules! generate_linalg_extern_fn {
($fn_name:ident, $extern_fn:literal, 2) => {
generate_linalg_extern_fn!($fn_name, $extern_fn, mat1, mat2);
};
($fn_name:ident, $extern_fn:literal, 3) => {
generate_linalg_extern_fn!($fn_name, $extern_fn, mat1, mat2, mat3);
};
($fn_name:ident, $extern_fn:literal, 4) => {
generate_linalg_extern_fn!($fn_name, $extern_fn, mat1, mat2, mat3, mat4);
};
($fn_name:ident, $extern_fn:literal $(,$input_matrix:ident)*) => {
#[doc = concat!("Invokes the linalg `", stringify!($extern_fn), " function." )]
pub fn $fn_name<'ctx>(
ctx: &mut CodeGenContext<'ctx, '_>
$(,$input_matrix: BasicValueEnum<'ctx>)*,
name: Option<&str>,
){
const FN_NAME: &str = $extern_fn;
let extern_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
let fn_type = ctx.ctx.void_type().fn_type(&[$($input_matrix.get_type().into()),*], false);
let func = ctx.module.add_function(FN_NAME, fn_type, None);
for attr in ["mustprogress", "nofree", "nounwind", "willreturn", "writeonly"] {
func.add_attribute(
AttributeLoc::Function,
ctx.ctx.create_enum_attribute(Attribute::get_named_enum_kind_id(attr), 0),
);
}
func
});
ctx.builder.build_call(extern_fn, &[$($input_matrix.into(),)*], name.unwrap_or_default()).unwrap();
}
};
}
generate_linalg_extern_fn!(call_np_linalg_cholesky, "np_linalg_cholesky", 2);
generate_linalg_extern_fn!(call_np_linalg_qr, "np_linalg_qr", 3);
generate_linalg_extern_fn!(call_np_linalg_svd, "np_linalg_svd", 4);
generate_linalg_extern_fn!(call_np_linalg_inv, "np_linalg_inv", 2);
generate_linalg_extern_fn!(call_np_linalg_pinv, "np_linalg_pinv", 2);
generate_linalg_extern_fn!(call_np_linalg_matrix_power, "np_linalg_matrix_power", 3);
generate_linalg_extern_fn!(call_np_linalg_det, "np_linalg_det", 2);
generate_linalg_extern_fn!(call_sp_linalg_lu, "sp_linalg_lu", 3);
generate_linalg_extern_fn!(call_sp_linalg_schur, "sp_linalg_schur", 3);
generate_linalg_extern_fn!(call_sp_linalg_hessenberg, "sp_linalg_hessenberg", 3);

View File

@ -1,18 +1,16 @@
use crate::{
codegen::{bool_to_i1, bool_to_i8, classes::ArraySliceValue, expr::*, stmt::*, CodeGenContext},
symbol_resolver::ValueEnum,
toplevel::{DefinitionId, TopLevelDef},
typecheck::typedef::{FunSignature, Type},
};
use inkwell::{
context::Context,
types::{BasicTypeEnum, IntType},
values::{BasicValueEnum, IntValue, PointerValue},
};
use nac3parser::ast::{Expr, Stmt, StrRef};
use super::{bool_to_i1, bool_to_i8, classes::ArraySliceValue, expr::*, stmt::*, CodeGenContext};
use crate::{
symbol_resolver::ValueEnum,
toplevel::{DefinitionId, TopLevelDef},
typecheck::typedef::{FunSignature, Type},
};
pub trait CodeGenerator {
/// Return the module name for the code generator.
fn get_name(&self) -> &str;
@ -59,7 +57,6 @@ pub trait CodeGenerator {
/// - fun: Function signature, definition ID and the substitution key.
/// - params: Function parameters. Note that this does not include the object even if the
/// function is a class method.
///
/// Note that this function should check if the function is generated in another thread (due to
/// possible race condition), see the default implementation for an example.
fn gen_func_instance<'ctx>(
@ -126,45 +123,11 @@ pub trait CodeGenerator {
ctx: &mut CodeGenContext<'ctx, '_>,
target: &Expr<Option<Type>>,
value: ValueEnum<'ctx>,
value_ty: Type,
) -> Result<(), String>
where
Self: Sized,
{
gen_assign(self, ctx, target, value, value_ty)
}
/// Generate code for an assignment expression where LHS is a `"target_list"`.
///
/// See <https://docs.python.org/3/reference/simple_stmts.html#assignment-statements>.
fn gen_assign_target_list<'ctx>(
&mut self,
ctx: &mut CodeGenContext<'ctx, '_>,
targets: &Vec<Expr<Option<Type>>>,
value: ValueEnum<'ctx>,
value_ty: Type,
) -> Result<(), String>
where
Self: Sized,
{
gen_assign_target_list(self, ctx, targets, value, value_ty)
}
/// Generate code for an item assignment.
///
/// i.e., `target[key] = value`
fn gen_setitem<'ctx>(
&mut self,
ctx: &mut CodeGenContext<'ctx, '_>,
target: &Expr<Option<Type>>,
key: &Expr<Option<Type>>,
value: ValueEnum<'ctx>,
value_ty: Type,
) -> Result<(), String>
where
Self: Sized,
{
gen_setitem(self, ctx, target, key, value, value_ty)
gen_assign(self, ctx, target, value)
}
/// Generate code for a while expression.

View File

@ -1,30 +1,30 @@
use crate::{typecheck::typedef::Type, util::SizeVariant};
mod test;
use super::{
classes::{
check_basic_types_match, ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue,
NDArrayValue, NpArrayType, NpArrayValue, TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
},
llvm_intrinsics, CodeGenContext, CodeGenerator,
};
use crate::codegen::classes::TypedArrayLikeAccessor;
use crate::codegen::stmt::gen_for_callback_incrementing;
use inkwell::{
attributes::{Attribute, AttributeLoc},
context::Context,
memory_buffer::MemoryBuffer,
module::Module,
types::{BasicTypeEnum, IntType},
values::{BasicValue, BasicValueEnum, CallSiteValue, FloatValue, IntValue},
types::{BasicType, BasicTypeEnum, FunctionType, IntType, PointerType},
values::{BasicValue, BasicValueEnum, CallSiteValue, FloatValue, FunctionValue, IntValue},
AddressSpace, IntPredicate,
};
use itertools::Either;
use nac3parser::ast::Expr;
use super::{
classes::{
ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue,
TypedArrayLikeAccessor, TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
},
llvm_intrinsics,
macros::codegen_unreachable,
stmt::gen_for_callback_incrementing,
CodeGenContext, CodeGenerator,
};
use crate::{symbol_resolver::SymbolResolver, typecheck::typedef::Type};
#[must_use]
pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver) -> Module<'ctx> {
pub fn load_irrt(ctx: &Context) -> Module {
let bitcode_buf = MemoryBuffer::create_from_memory_range(
include_bytes!(concat!(env!("OUT_DIR"), "/irrt.bc")),
"irrt_bitcode_buffer",
@ -40,25 +40,6 @@ pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver)
let function = irrt_mod.get_function(symbol).unwrap();
function.add_attribute(AttributeLoc::Function, ctx.create_enum_attribute(inline_attr, 0));
}
// Initialize all global `EXN_*` exception IDs in IRRT with the [`SymbolResolver`].
let exn_id_type = ctx.i32_type();
let errors = &[
("EXN_INDEX_ERROR", "0:IndexError"),
("EXN_VALUE_ERROR", "0:ValueError"),
("EXN_ASSERTION_ERROR", "0:AssertionError"),
("EXN_TYPE_ERROR", "0:TypeError"),
];
for (irrt_name, symbol_name) in errors {
let exn_id = symbol_resolver.get_string_id(symbol_name);
let exn_id = exn_id_type.const_int(exn_id as u64, false).as_basic_value_enum();
let global = irrt_mod.get_global(irrt_name).unwrap_or_else(|| {
panic!("Exception symbol name '{irrt_name}' should exist in the IRRT LLVM module")
});
global.set_initializer(&exn_id);
}
irrt_mod
}
@ -76,7 +57,7 @@ pub fn integer_power<'ctx, G: CodeGenerator + ?Sized>(
(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),
_ => unreachable!(),
};
let base_type = base.get_type();
let pow_fun = ctx.module.get_function(symbol).unwrap_or_else(|| {
@ -462,7 +443,7 @@ pub fn list_slice_assignment<'ctx, G: CodeGenerator + ?Sized>(
BasicTypeEnum::IntType(t) => t.size_of(),
BasicTypeEnum::PointerType(t) => t.size_of(),
BasicTypeEnum::StructType(t) => t.size_of().unwrap(),
_ => codegen_unreachable!(ctx),
_ => unreachable!(),
};
ctx.builder.build_int_truncate_or_bit_cast(s, int32, "size").unwrap()
}
@ -584,369 +565,475 @@ pub fn call_j0<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> Flo
.unwrap()
}
/// Generates a call to `__nac3_ndarray_calc_size`. Returns an [`IntValue`] representing the
/// calculated total size.
///
/// * `dims` - An [`ArrayLikeIndexer`] containing the size of each dimension.
/// * `range` - The dimension index to begin and end (exclusively) calculating the dimensions for,
/// or [`None`] if starting from the first dimension and ending at the last dimension
/// respectively.
pub fn call_ndarray_calc_size<'ctx, G, Dims>(
generator: &G,
// /// Generates a call to `__nac3_ndarray_calc_size`. Returns an [`IntValue`] representing the
// /// calculated total size.
// ///
// /// * `dims` - An [`ArrayLikeIndexer`] containing the size of each dimension.
// /// * `range` - The dimension index to begin and end (exclusively) calculating the dimensions for,
// /// or [`None`] if starting from the first dimension and ending at the last dimension respectively.
// pub fn call_ndarray_calc_size<'ctx, G, Dims>(
// generator: &G,
// ctx: &CodeGenContext<'ctx, '_>,
// dims: &Dims,
// (begin, end): (Option<IntValue<'ctx>>, Option<IntValue<'ctx>>),
// ) -> IntValue<'ctx>
// where
// G: CodeGenerator + ?Sized,
// Dims: ArrayLikeIndexer<'ctx>,
// {
// let llvm_usize = generator.get_size_type(ctx.ctx);
// let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
//
// let ndarray_calc_size_fn_name = match llvm_usize.get_bit_width() {
// 32 => "__nac3_ndarray_calc_size",
// 64 => "__nac3_ndarray_calc_size64",
// bw => unreachable!("Unsupported size type bit width: {}", bw),
// };
// let ndarray_calc_size_fn_t = llvm_usize.fn_type(
// &[llvm_pusize.into(), llvm_usize.into(), llvm_usize.into(), llvm_usize.into()],
// false,
// );
// let ndarray_calc_size_fn =
// ctx.module.get_function(ndarray_calc_size_fn_name).unwrap_or_else(|| {
// ctx.module.add_function(ndarray_calc_size_fn_name, ndarray_calc_size_fn_t, None)
// });
//
// let begin = begin.unwrap_or_else(|| llvm_usize.const_zero());
// let end = end.unwrap_or_else(|| dims.size(ctx, generator));
// ctx.builder
// .build_call(
// ndarray_calc_size_fn,
// &[
// dims.base_ptr(ctx, generator).into(),
// dims.size(ctx, generator).into(),
// begin.into(),
// end.into(),
// ],
// "",
// )
// .map(CallSiteValue::try_as_basic_value)
// .map(|v| v.map_left(BasicValueEnum::into_int_value))
// .map(Either::unwrap_left)
// .unwrap()
// }
//
// /// Generates a call to `__nac3_ndarray_calc_nd_indices`. Returns a [`TypeArrayLikeAdpater`]
// /// containing `i32` indices of the flattened index.
// ///
// /// * `index` - The index to compute the multidimensional index for.
// /// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
// /// `NDArray`.
// pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
// generator: &G,
// ctx: &mut CodeGenContext<'ctx, '_>,
// index: IntValue<'ctx>,
// ndarray: NDArrayValue<'ctx>,
// ) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
// let llvm_void = ctx.ctx.void_type();
// let llvm_i32 = ctx.ctx.i32_type();
// let llvm_usize = generator.get_size_type(ctx.ctx);
// let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
// let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
//
// let ndarray_calc_nd_indices_fn_name = match llvm_usize.get_bit_width() {
// 32 => "__nac3_ndarray_calc_nd_indices",
// 64 => "__nac3_ndarray_calc_nd_indices64",
// bw => unreachable!("Unsupported size type bit width: {}", bw),
// };
// let ndarray_calc_nd_indices_fn =
// ctx.module.get_function(ndarray_calc_nd_indices_fn_name).unwrap_or_else(|| {
// let fn_type = llvm_void.fn_type(
// &[llvm_usize.into(), llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into()],
// false,
// );
//
// ctx.module.add_function(ndarray_calc_nd_indices_fn_name, fn_type, None)
// });
//
// let ndarray_num_dims = ndarray.load_ndims(ctx);
// let ndarray_dims = ndarray.dim_sizes();
//
// let indices = ctx.builder.build_array_alloca(llvm_i32, ndarray_num_dims, "").unwrap();
//
// ctx.builder
// .build_call(
// ndarray_calc_nd_indices_fn,
// &[
// index.into(),
// ndarray_dims.base_ptr(ctx, generator).into(),
// ndarray_num_dims.into(),
// indices.into(),
// ],
// "",
// )
// .unwrap();
//
// TypedArrayLikeAdapter::from(
// ArraySliceValue::from_ptr_val(indices, ndarray_num_dims, None),
// Box::new(|_, v| v.into_int_value()),
// Box::new(|_, v| v.into()),
// )
// }
//
// fn call_ndarray_flatten_index_impl<'ctx, G, Indices>(
// generator: &G,
// ctx: &CodeGenContext<'ctx, '_>,
// ndarray: NDArrayValue<'ctx>,
// indices: &Indices,
// ) -> IntValue<'ctx>
// where
// G: CodeGenerator + ?Sized,
// Indices: ArrayLikeIndexer<'ctx>,
// {
// let llvm_i32 = ctx.ctx.i32_type();
// let llvm_usize = generator.get_size_type(ctx.ctx);
//
// let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
// let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
//
// debug_assert_eq!(
// IntType::try_from(indices.element_type(ctx, generator))
// .map(IntType::get_bit_width)
// .unwrap_or_default(),
// llvm_i32.get_bit_width(),
// "Expected i32 value for argument `indices` to `call_ndarray_flatten_index_impl`"
// );
// debug_assert_eq!(
// indices.size(ctx, generator).get_type().get_bit_width(),
// llvm_usize.get_bit_width(),
// "Expected usize integer value for argument `indices_size` to `call_ndarray_flatten_index_impl`"
// );
//
// let ndarray_flatten_index_fn_name = match llvm_usize.get_bit_width() {
// 32 => "__nac3_ndarray_flatten_index",
// 64 => "__nac3_ndarray_flatten_index64",
// bw => unreachable!("Unsupported size type bit width: {}", bw),
// };
// let ndarray_flatten_index_fn =
// ctx.module.get_function(ndarray_flatten_index_fn_name).unwrap_or_else(|| {
// let fn_type = llvm_usize.fn_type(
// &[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_usize.into()],
// false,
// );
//
// ctx.module.add_function(ndarray_flatten_index_fn_name, fn_type, None)
// });
//
// let ndarray_num_dims = ndarray.load_ndims(ctx);
// let ndarray_dims = ndarray.dim_sizes();
//
// let index = ctx
// .builder
// .build_call(
// ndarray_flatten_index_fn,
// &[
// ndarray_dims.base_ptr(ctx, generator).into(),
// ndarray_num_dims.into(),
// indices.base_ptr(ctx, generator).into(),
// indices.size(ctx, generator).into(),
// ],
// "",
// )
// .map(CallSiteValue::try_as_basic_value)
// .map(|v| v.map_left(BasicValueEnum::into_int_value))
// .map(Either::unwrap_left)
// .unwrap();
//
// index
// }
//
// /// Generates a call to `__nac3_ndarray_flatten_index`. Returns the flattened index for the
// /// multidimensional index.
// ///
// /// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
// /// `NDArray`.
// /// * `indices` - The multidimensional index to compute the flattened index for.
// pub fn call_ndarray_flatten_index<'ctx, G, Index>(
// generator: &mut G,
// ctx: &mut CodeGenContext<'ctx, '_>,
// ndarray: NDArrayValue<'ctx>,
// indices: &Index,
// ) -> IntValue<'ctx>
// where
// G: CodeGenerator + ?Sized,
// Index: ArrayLikeIndexer<'ctx>,
// {
// call_ndarray_flatten_index_impl(generator, ctx, ndarray, indices)
// }
//
// /// Generates a call to `__nac3_ndarray_calc_broadcast`. Returns a tuple containing the number of
// /// dimension and size of each dimension of the resultant `ndarray`.
// pub fn call_ndarray_calc_broadcast<'ctx, G: CodeGenerator + ?Sized>(
// generator: &mut G,
// ctx: &mut CodeGenContext<'ctx, '_>,
// lhs: NDArrayValue<'ctx>,
// rhs: NDArrayValue<'ctx>,
// ) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
// let llvm_usize = generator.get_size_type(ctx.ctx);
// let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
//
// let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
// 32 => "__nac3_ndarray_calc_broadcast",
// 64 => "__nac3_ndarray_calc_broadcast64",
// bw => unreachable!("Unsupported size type bit width: {}", bw),
// };
// let ndarray_calc_broadcast_fn =
// ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
// let fn_type = llvm_usize.fn_type(
// &[
// llvm_pusize.into(),
// llvm_usize.into(),
// llvm_pusize.into(),
// llvm_usize.into(),
// llvm_pusize.into(),
// ],
// false,
// );
//
// ctx.module.add_function(ndarray_calc_broadcast_fn_name, fn_type, None)
// });
//
// let lhs_ndims = lhs.load_ndims(ctx);
// let rhs_ndims = rhs.load_ndims(ctx);
// let min_ndims = llvm_intrinsics::call_int_umin(ctx, lhs_ndims, rhs_ndims, None);
//
// gen_for_callback_incrementing(
// generator,
// ctx,
// llvm_usize.const_zero(),
// (min_ndims, false),
// |generator, ctx, _, idx| {
// let idx = ctx.builder.build_int_sub(min_ndims, idx, "").unwrap();
// let (lhs_dim_sz, rhs_dim_sz) = unsafe {
// (
// lhs.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None),
// rhs.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None),
// )
// };
//
// let llvm_usize_const_one = llvm_usize.const_int(1, false);
// let lhs_eqz = ctx
// .builder
// .build_int_compare(IntPredicate::EQ, lhs_dim_sz, llvm_usize_const_one, "")
// .unwrap();
// let rhs_eqz = ctx
// .builder
// .build_int_compare(IntPredicate::EQ, rhs_dim_sz, llvm_usize_const_one, "")
// .unwrap();
// let lhs_or_rhs_eqz = ctx.builder.build_or(lhs_eqz, rhs_eqz, "").unwrap();
//
// let lhs_eq_rhs = ctx
// .builder
// .build_int_compare(IntPredicate::EQ, lhs_dim_sz, rhs_dim_sz, "")
// .unwrap();
//
// let is_compatible = ctx.builder.build_or(lhs_or_rhs_eqz, lhs_eq_rhs, "").unwrap();
//
// ctx.make_assert(
// generator,
// is_compatible,
// "0:ValueError",
// "operands could not be broadcast together",
// [None, None, None],
// ctx.current_loc,
// );
//
// Ok(())
// },
// llvm_usize.const_int(1, false),
// )
// .unwrap();
//
// let max_ndims = llvm_intrinsics::call_int_umax(ctx, lhs_ndims, rhs_ndims, None);
// let lhs_dims = lhs.dim_sizes().base_ptr(ctx, generator);
// let lhs_ndims = lhs.load_ndims(ctx);
// let rhs_dims = rhs.dim_sizes().base_ptr(ctx, generator);
// let rhs_ndims = rhs.load_ndims(ctx);
// let out_dims = ctx.builder.build_array_alloca(llvm_usize, max_ndims, "").unwrap();
// let out_dims = ArraySliceValue::from_ptr_val(out_dims, max_ndims, None);
//
// ctx.builder
// .build_call(
// ndarray_calc_broadcast_fn,
// &[
// lhs_dims.into(),
// lhs_ndims.into(),
// rhs_dims.into(),
// rhs_ndims.into(),
// out_dims.base_ptr(ctx, generator).into(),
// ],
// "",
// )
// .unwrap();
//
// TypedArrayLikeAdapter::from(
// out_dims,
// Box::new(|_, v| v.into_int_value()),
// Box::new(|_, v| v.into()),
// )
// }
//
// /// Generates a call to `__nac3_ndarray_calc_broadcast_idx`. Returns an [`ArrayAllocaValue`]
// /// containing the indices used for accessing `array` corresponding to the index of the broadcasted
// /// array `broadcast_idx`.
// pub fn call_ndarray_calc_broadcast_index<
// 'ctx,
// G: CodeGenerator + ?Sized,
// BroadcastIdx: UntypedArrayLikeAccessor<'ctx>,
// >(
// generator: &mut G,
// ctx: &mut CodeGenContext<'ctx, '_>,
// array: NDArrayValue<'ctx>,
// broadcast_idx: &BroadcastIdx,
// ) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
// let llvm_i32 = ctx.ctx.i32_type();
// let llvm_usize = generator.get_size_type(ctx.ctx);
// let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
// let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
//
// let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
// 32 => "__nac3_ndarray_calc_broadcast_idx",
// 64 => "__nac3_ndarray_calc_broadcast_idx64",
// bw => unreachable!("Unsupported size type bit width: {}", bw),
// };
// let ndarray_calc_broadcast_fn =
// ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
// let fn_type = llvm_usize.fn_type(
// &[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_pi32.into()],
// false,
// );
//
// ctx.module.add_function(ndarray_calc_broadcast_fn_name, fn_type, None)
// });
//
// let broadcast_size = broadcast_idx.size(ctx, generator);
// let out_idx = ctx.builder.build_array_alloca(llvm_i32, broadcast_size, "").unwrap();
//
// let array_dims = array.dim_sizes().base_ptr(ctx, generator);
// let array_ndims = array.load_ndims(ctx);
// let broadcast_idx_ptr = unsafe {
// broadcast_idx.ptr_offset_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
// };
//
// ctx.builder
// .build_call(
// ndarray_calc_broadcast_fn,
// &[array_dims.into(), array_ndims.into(), broadcast_idx_ptr.into(), out_idx.into()],
// "",
// )
// .unwrap();
//
// TypedArrayLikeAdapter::from(
// ArraySliceValue::from_ptr_val(out_idx, broadcast_size, None),
// Box::new(|_, v| v.into_int_value()),
// Box::new(|_, v| v.into()),
// )
// }
fn get_size_variant<'ctx>(ty: IntType<'ctx>) -> SizeVariant {
match ty.get_bit_width() {
32 => SizeVariant::Bits32,
64 => SizeVariant::Bits64,
_ => unreachable!("Unsupported int type bit width {}", ty.get_bit_width()),
}
}
fn get_size_type_dependent_function<'ctx, BuildFuncTypeFn>(
ctx: &CodeGenContext<'ctx, '_>,
dims: &Dims,
(begin, end): (Option<IntValue<'ctx>>, Option<IntValue<'ctx>>),
) -> IntValue<'ctx>
size_type: IntType<'ctx>,
base_name: &str,
build_func_type: BuildFuncTypeFn,
) -> FunctionValue<'ctx>
where
G: CodeGenerator + ?Sized,
Dims: ArrayLikeIndexer<'ctx>,
BuildFuncTypeFn: Fn() -> FunctionType<'ctx>,
{
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
let mut fn_name = base_name.to_owned();
match get_size_variant(size_type) {
SizeVariant::Bits32 => {
// The original fn_name is the correct function name
}
SizeVariant::Bits64 => {
// Append "64" at the end, this is the naming convention for 64-bit
fn_name.push_str("64");
}
}
let ndarray_calc_size_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_size",
64 => "__nac3_ndarray_calc_size64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_calc_size_fn_t = llvm_usize.fn_type(
&[llvm_pusize.into(), llvm_usize.into(), llvm_usize.into(), llvm_usize.into()],
false,
);
let ndarray_calc_size_fn =
ctx.module.get_function(ndarray_calc_size_fn_name).unwrap_or_else(|| {
ctx.module.add_function(ndarray_calc_size_fn_name, ndarray_calc_size_fn_t, None)
});
// Get (or declare then get if does not exist) the corresponding function
ctx.module.get_function(&fn_name).unwrap_or_else(|| {
let fn_type = build_func_type();
ctx.module.add_function(&fn_name, fn_type, None)
})
}
fn get_irrt_ndarray_ptr_type<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
size_type: IntType<'ctx>,
) -> PointerType<'ctx> {
let i8_type = ctx.ctx.i8_type();
let ndarray_ty = NpArrayType { size_type, elem_type: i8_type.as_basic_type_enum() };
let struct_ty = ndarray_ty.get_struct_type(ctx.ctx);
struct_ty.ptr_type(AddressSpace::default())
}
fn get_irrt_opaque_uint8_ptr_type<'ctx>(ctx: &CodeGenContext<'ctx, '_>) -> PointerType<'ctx> {
ctx.ctx.i8_type().ptr_type(AddressSpace::default())
}
pub fn call_nac3_ndarray_size<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
ndarray: NpArrayValue<'ctx>,
) -> IntValue<'ctx> {
let size_type = ndarray.ty.size_type;
let function = get_size_type_dependent_function(ctx, size_type, "__nac3_ndarray_size", || {
size_type.fn_type(&[get_irrt_ndarray_ptr_type(ctx, size_type).into()], false)
});
let begin = begin.unwrap_or_else(|| llvm_usize.const_zero());
let end = end.unwrap_or_else(|| dims.size(ctx, generator));
ctx.builder
.build_call(
ndarray_calc_size_fn,
&[
dims.base_ptr(ctx, generator).into(),
dims.size(ctx, generator).into(),
begin.into(),
end.into(),
],
"",
)
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.build_call(function, &[ndarray.ptr.into()], "size")
.unwrap()
.try_as_basic_value()
.unwrap_left()
.into_int_value()
}
/// Generates a call to `__nac3_ndarray_calc_nd_indices`. Returns a [`TypeArrayLikeAdpater`]
/// containing `i32` indices of the flattened index.
///
/// * `index` - The index to compute the multidimensional index for.
/// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
/// `NDArray`.
pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
generator: &G,
ctx: &mut CodeGenContext<'ctx, '_>,
index: IntValue<'ctx>,
ndarray: NDArrayValue<'ctx>,
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
let llvm_void = ctx.ctx.void_type();
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
let ndarray_calc_nd_indices_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_nd_indices",
64 => "__nac3_ndarray_calc_nd_indices64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_calc_nd_indices_fn =
ctx.module.get_function(ndarray_calc_nd_indices_fn_name).unwrap_or_else(|| {
let fn_type = llvm_void.fn_type(
&[llvm_usize.into(), llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into()],
false,
);
ctx.module.add_function(ndarray_calc_nd_indices_fn_name, fn_type, None)
});
let ndarray_num_dims = ndarray.load_ndims(ctx);
let ndarray_dims = ndarray.dim_sizes();
let indices = ctx.builder.build_array_alloca(llvm_i32, ndarray_num_dims, "").unwrap();
ctx.builder
.build_call(
ndarray_calc_nd_indices_fn,
&[
index.into(),
ndarray_dims.base_ptr(ctx, generator).into(),
ndarray_num_dims.into(),
indices.into(),
],
"",
)
.unwrap();
TypedArrayLikeAdapter::from(
ArraySliceValue::from_ptr_val(indices, ndarray_num_dims, None),
Box::new(|_, v| v.into_int_value()),
Box::new(|_, v| v.into()),
)
}
fn call_ndarray_flatten_index_impl<'ctx, G, Indices>(
generator: &G,
pub fn call_nac3_ndarray_fill_generic<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
ndarray: NDArrayValue<'ctx>,
indices: &Indices,
) -> IntValue<'ctx>
where
G: CodeGenerator + ?Sized,
Indices: ArrayLikeIndexer<'ctx>,
{
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
debug_assert_eq!(
IntType::try_from(indices.element_type(ctx, generator))
.map(IntType::get_bit_width)
.unwrap_or_default(),
llvm_i32.get_bit_width(),
"Expected i32 value for argument `indices` to `call_ndarray_flatten_index_impl`"
);
debug_assert_eq!(
indices.size(ctx, generator).get_type().get_bit_width(),
llvm_usize.get_bit_width(),
"Expected usize integer value for argument `indices_size` to `call_ndarray_flatten_index_impl`"
);
let ndarray_flatten_index_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_flatten_index",
64 => "__nac3_ndarray_flatten_index64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_flatten_index_fn =
ctx.module.get_function(ndarray_flatten_index_fn_name).unwrap_or_else(|| {
let fn_type = llvm_usize.fn_type(
&[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_usize.into()],
false,
);
ctx.module.add_function(ndarray_flatten_index_fn_name, fn_type, None)
});
let ndarray_num_dims = ndarray.load_ndims(ctx);
let ndarray_dims = ndarray.dim_sizes();
let index = ctx
.builder
.build_call(
ndarray_flatten_index_fn,
&[
ndarray_dims.base_ptr(ctx, generator).into(),
ndarray_num_dims.into(),
indices.base_ptr(ctx, generator).into(),
indices.size(ctx, generator).into(),
],
"",
)
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
ndarray: NpArrayValue<'ctx>,
fill_value: BasicValueEnum<'ctx>,
) {
// Sanity check on type of `fill_value`
check_basic_types_match(ndarray.ty.elem_type, fill_value.get_type().as_basic_type_enum())
.unwrap();
index
}
/// Generates a call to `__nac3_ndarray_flatten_index`. Returns the flattened index for the
/// multidimensional index.
///
/// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
/// `NDArray`.
/// * `indices` - The multidimensional index to compute the flattened index for.
pub fn call_ndarray_flatten_index<'ctx, G, Index>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
ndarray: NDArrayValue<'ctx>,
indices: &Index,
) -> IntValue<'ctx>
where
G: CodeGenerator + ?Sized,
Index: ArrayLikeIndexer<'ctx>,
{
call_ndarray_flatten_index_impl(generator, ctx, ndarray, indices)
}
/// Generates a call to `__nac3_ndarray_calc_broadcast`. Returns a tuple containing the number of
/// dimension and size of each dimension of the resultant `ndarray`.
pub fn call_ndarray_calc_broadcast<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
lhs: NDArrayValue<'ctx>,
rhs: NDArrayValue<'ctx>,
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_broadcast",
64 => "__nac3_ndarray_calc_broadcast64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_calc_broadcast_fn =
ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
let fn_type = llvm_usize.fn_type(
let size_type = ndarray.ty.size_type;
let function =
get_size_type_dependent_function(ctx, size_type, "__nac3_ndarray_fill_generic", || {
ctx.ctx.void_type().fn_type(
&[
llvm_pusize.into(),
llvm_usize.into(),
llvm_pusize.into(),
llvm_usize.into(),
llvm_pusize.into(),
get_irrt_ndarray_ptr_type(ctx, size_type).into(), // NDArray<SizeT>* ndarray
get_irrt_opaque_uint8_ptr_type(ctx).into(), // uint8_t* pvalue
],
false,
);
ctx.module.add_function(ndarray_calc_broadcast_fn_name, fn_type, None)
)
});
let lhs_ndims = lhs.load_ndims(ctx);
let rhs_ndims = rhs.load_ndims(ctx);
let min_ndims = llvm_intrinsics::call_int_umin(ctx, lhs_ndims, rhs_ndims, None);
// Put `fill_value` onto the stack and get a pointer to it, and that pointer will be `pvalue`
let pvalue = ctx.builder.build_alloca(ndarray.ty.elem_type, "fill_value").unwrap();
ctx.builder.build_store(pvalue, fill_value).unwrap();
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(min_ndims, false),
|generator, ctx, _, idx| {
let idx = ctx.builder.build_int_sub(min_ndims, idx, "").unwrap();
let (lhs_dim_sz, rhs_dim_sz) = unsafe {
(
lhs.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None),
rhs.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None),
)
};
let llvm_usize_const_one = llvm_usize.const_int(1, false);
let lhs_eqz = ctx
.builder
.build_int_compare(IntPredicate::EQ, lhs_dim_sz, llvm_usize_const_one, "")
.unwrap();
let rhs_eqz = ctx
.builder
.build_int_compare(IntPredicate::EQ, rhs_dim_sz, llvm_usize_const_one, "")
.unwrap();
let lhs_or_rhs_eqz = ctx.builder.build_or(lhs_eqz, rhs_eqz, "").unwrap();
let lhs_eq_rhs = ctx
.builder
.build_int_compare(IntPredicate::EQ, lhs_dim_sz, rhs_dim_sz, "")
.unwrap();
let is_compatible = ctx.builder.build_or(lhs_or_rhs_eqz, lhs_eq_rhs, "").unwrap();
ctx.make_assert(
generator,
is_compatible,
"0:ValueError",
"operands could not be broadcast together",
[None, None, None],
ctx.current_loc,
);
Ok(())
},
llvm_usize.const_int(1, false),
)
.unwrap();
let max_ndims = llvm_intrinsics::call_int_umax(ctx, lhs_ndims, rhs_ndims, None);
let lhs_dims = lhs.dim_sizes().base_ptr(ctx, generator);
let lhs_ndims = lhs.load_ndims(ctx);
let rhs_dims = rhs.dim_sizes().base_ptr(ctx, generator);
let rhs_ndims = rhs.load_ndims(ctx);
let out_dims = ctx.builder.build_array_alloca(llvm_usize, max_ndims, "").unwrap();
let out_dims = ArraySliceValue::from_ptr_val(out_dims, max_ndims, None);
// Cast pvalue to `uint8_t*`
let pvalue = ctx.builder.build_pointer_cast(pvalue, get_irrt_opaque_uint8_ptr_type(ctx), "").unwrap();
// Call the IRRT function
ctx.builder
.build_call(
ndarray_calc_broadcast_fn,
function,
&[
lhs_dims.into(),
lhs_ndims.into(),
rhs_dims.into(),
rhs_ndims.into(),
out_dims.base_ptr(ctx, generator).into(),
ndarray.ptr.into(), // ndarray
pvalue.into(), // pvalue
],
"",
)
.unwrap();
TypedArrayLikeAdapter::from(
out_dims,
Box::new(|_, v| v.into_int_value()),
Box::new(|_, v| v.into()),
)
}
/// Generates a call to `__nac3_ndarray_calc_broadcast_idx`. Returns an [`ArrayAllocaValue`]
/// containing the indices used for accessing `array` corresponding to the index of the broadcasted
/// array `broadcast_idx`.
pub fn call_ndarray_calc_broadcast_index<
'ctx,
G: CodeGenerator + ?Sized,
BroadcastIdx: UntypedArrayLikeAccessor<'ctx>,
>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
array: NDArrayValue<'ctx>,
broadcast_idx: &BroadcastIdx,
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_broadcast_idx",
64 => "__nac3_ndarray_calc_broadcast_idx64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_calc_broadcast_fn =
ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
let fn_type = llvm_usize.fn_type(
&[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_pi32.into()],
false,
);
ctx.module.add_function(ndarray_calc_broadcast_fn_name, fn_type, None)
});
let broadcast_size = broadcast_idx.size(ctx, generator);
let out_idx = ctx.builder.build_array_alloca(llvm_i32, broadcast_size, "").unwrap();
let array_dims = array.dim_sizes().base_ptr(ctx, generator);
let array_ndims = array.load_ndims(ctx);
let broadcast_idx_ptr = unsafe {
broadcast_idx.ptr_offset_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
};
ctx.builder
.build_call(
ndarray_calc_broadcast_fn,
&[array_dims.into(), array_ndims.into(), broadcast_idx_ptr.into(), out_idx.into()],
"",
)
.unwrap();
TypedArrayLikeAdapter::from(
ArraySliceValue::from_ptr_val(out_idx, broadcast_size, None),
Box::new(|_, v| v.into_int_value()),
Box::new(|_, v| v.into()),
)
}

View File

@ -0,0 +1,26 @@
#[cfg(test)]
mod tests {
use std::{path::Path, process::Command};
#[test]
fn run_irrt_test() {
assert!(
cfg!(feature = "test"),
"Please do `cargo test -F test` to compile `irrt_test.out` and run test"
);
let irrt_test_out_path = Path::new(concat!(env!("OUT_DIR"), "/irrt_test.out"));
let output = Command::new(irrt_test_out_path.to_str().unwrap()).output().unwrap();
if !output.status.success() {
eprintln!("irrt_test failed with status {}:", output.status);
eprintln!("====== stdout ======");
eprintln!("{}", String::from_utf8(output.stdout).unwrap());
eprintln!("====== stderr ======");
eprintln!("{}", String::from_utf8(output.stderr).unwrap());
eprintln!("====================");
panic!("irrt_test failed");
}
}
}

View File

@ -1,14 +1,12 @@
use inkwell::{
context::Context,
intrinsics::Intrinsic,
types::{AnyTypeEnum::IntType, FloatType},
values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue, PointerValue},
AddressSpace,
};
use crate::codegen::CodeGenContext;
use inkwell::context::Context;
use inkwell::intrinsics::Intrinsic;
use inkwell::types::AnyTypeEnum::IntType;
use inkwell::types::FloatType;
use inkwell::values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue, PointerValue};
use inkwell::AddressSpace;
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 {
@ -37,40 +35,6 @@ fn get_float_intrinsic_repr(ctx: &Context, ft: FloatType) -> &'static str {
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>) {
const FN_NAME: &str = "llvm.va_start";
let intrinsic_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
let llvm_void = ctx.ctx.void_type();
let llvm_i8 = ctx.ctx.i8_type();
let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
let fn_type = llvm_void.fn_type(&[llvm_p0i8.into()], false);
ctx.module.add_function(FN_NAME, fn_type, None)
});
ctx.builder.build_call(intrinsic_fn, &[arglist.into()], "").unwrap();
}
/// 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";
let intrinsic_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
let llvm_void = ctx.ctx.void_type();
let llvm_i8 = ctx.ctx.i8_type();
let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
let fn_type = llvm_void.fn_type(&[llvm_p0i8.into()], false);
ctx.module.add_function(FN_NAME, fn_type, None)
});
ctx.builder.build_call(intrinsic_fn, &[arglist.into()], "").unwrap();
}
/// Invokes the [`llvm.stacksave`](https://llvm.org/docs/LangRef.html#llvm-stacksave-intrinsic)
/// intrinsic.
pub fn call_stacksave<'ctx>(
@ -185,7 +149,7 @@ pub fn call_memcpy_generic<'ctx>(
dest
} else {
ctx.builder
.build_bit_cast(dest, llvm_p0i8, "")
.build_bitcast(dest, llvm_p0i8, "")
.map(BasicValueEnum::into_pointer_value)
.unwrap()
};
@ -193,7 +157,7 @@ pub fn call_memcpy_generic<'ctx>(
src
} else {
ctx.builder
.build_bit_cast(src, llvm_p0i8, "")
.build_bitcast(src, llvm_p0i8, "")
.map(BasicValueEnum::into_pointer_value)
.unwrap()
};
@ -207,9 +171,8 @@ pub fn call_memcpy_generic<'ctx>(
/// * `$ctx:ident`: Reference to the current Code Generation Context
/// * `$name:ident`: Optional name to be assigned to the llvm build call (Option<&str>)
/// * `$llvm_name:literal`: Name of underlying llvm intrinsic function
/// * `$map_fn:ident`: Mapping function to be applied on `BasicValue` (`BasicValue` -> Function Return Type).
/// Use `BasicValueEnum::into_int_value` for Integer return type and
/// `BasicValueEnum::into_float_value` for Float return type
/// * `$map_fn:ident`: Mapping function to be applied on `BasicValue` (`BasicValue` -> Function Return Type)
/// Use `BasicValueEnum::into_int_value` for Integer return type and `BasicValueEnum::into_float_value` for Float return type
/// * `$llvm_ty:ident`: Type of first operand
/// * `,($val:ident)*`: Comma separated list of operands
macro_rules! generate_llvm_intrinsic_fn_body {
@ -225,8 +188,8 @@ macro_rules! generate_llvm_intrinsic_fn_body {
/// Arguments:
/// * `float/int`: Indicates the return and argument type of the function
/// * `$fn_name:ident`: The identifier of the rust function to be generated
/// * `$llvm_name:literal`: Name of underlying llvm intrinsic function.
/// Omit "llvm." prefix from the function name i.e. use "ceil" instead of "llvm.ceil"
/// * `$llvm_name:literal`: Name of underlying llvm intrinsic function
/// Omit "llvm." prefix from the function name i.e. use "ceil" instead of "llvm.ceil"
/// * `$val:ident`: The operand for unary operations
/// * `$val1:ident`, `$val2:ident`: The operands for binary operations
macro_rules! generate_llvm_intrinsic_fn {

View File

@ -1,12 +1,13 @@
use std::{
collections::{HashMap, HashSet},
sync::{
atomic::{AtomicBool, Ordering},
Arc,
use crate::{
codegen::classes::{ListType, NDArrayType, ProxyType, RangeType},
symbol_resolver::{StaticValue, SymbolResolver},
toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, TopLevelContext, TopLevelDef},
typecheck::{
type_inferencer::{CodeLocation, PrimitiveStore},
typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
},
thread,
};
use classes::NpArrayType;
use crossbeam::channel::{unbounded, Receiver, Sender};
use inkwell::{
attributes::{Attribute, AttributeLoc},
@ -24,21 +25,14 @@ use inkwell::{
AddressSpace, IntPredicate, OptimizationLevel,
};
use itertools::Itertools;
use parking_lot::{Condvar, Mutex};
use nac3parser::ast::{Location, Stmt, StrRef};
use crate::{
symbol_resolver::{StaticValue, SymbolResolver},
toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, TopLevelContext, TopLevelDef},
typecheck::{
type_inferencer::{CodeLocation, PrimitiveStore},
typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
},
use parking_lot::{Condvar, Mutex};
use std::collections::{HashMap, HashSet};
use std::sync::{
atomic::{AtomicBool, Ordering},
Arc,
};
use classes::{ListType, NDArrayType, ProxyType, RangeType};
use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
pub use generator::{CodeGenerator, DefaultCodeGenerator};
use std::thread;
pub mod builtin_fns;
pub mod classes;
@ -54,21 +48,8 @@ pub mod stmt;
#[cfg(test)]
mod test;
mod macros {
/// Codegen-variant of [`std::unreachable`] which accepts an instance of [`CodeGenContext`] as
/// its first argument to provide Python source information to indicate the codegen location
/// causing the assertion.
macro_rules! codegen_unreachable {
($ctx:expr $(,)?) => {
std::unreachable!("unreachable code while processing {}", &$ctx.current_loc)
};
($ctx:expr, $($arg:tt)*) => {
std::unreachable!("unreachable code while processing {}: {}", &$ctx.current_loc, std::format!("{}", std::format_args!($($arg)+)))
};
}
pub(crate) use codegen_unreachable;
}
use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
pub use generator::{CodeGenerator, DefaultCodeGenerator};
#[derive(Default)]
pub struct StaticValueStore {
@ -88,16 +69,6 @@ pub struct CodeGenLLVMOptions {
pub target: CodeGenTargetMachineOptions,
}
impl CodeGenLLVMOptions {
/// Creates a [`TargetMachine`] using the target options specified by this struct.
///
/// See [`Target::create_target_machine`].
#[must_use]
pub fn create_target_machine(&self) -> Option<TargetMachine> {
self.target.create_target_machine(self.opt_level)
}
}
/// Additional options for code generation for the target machine.
#[derive(Clone, Debug, Eq, PartialEq)]
pub struct CodeGenTargetMachineOptions {
@ -368,10 +339,6 @@ impl WorkerRegistry {
let mut builder = context.create_builder();
let mut module = context.create_module(generator.get_name());
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",
inkwell::module::FlagBehavior::Warning,
@ -395,10 +362,6 @@ impl WorkerRegistry {
errors.insert(e);
// create a new empty module just to continue codegen and collect errors
module = context.create_module(&format!("{}_recover", generator.get_name()));
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());
}
}
*self.task_count.lock() -= 1;
@ -464,7 +427,7 @@ pub struct CodeGenTask {
fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
ctx: &'ctx Context,
module: &Module<'ctx>,
generator: &G,
generator: &mut G,
unifier: &mut Unifier,
top_level: &TopLevelContext,
type_cache: &mut HashMap<Type, BasicTypeEnum<'ctx>>,
@ -514,7 +477,11 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
ctx, module, generator, unifier, top_level, type_cache, dtype,
);
NDArrayType::new(generator, ctx, element_type).as_base_type().into()
let ndarray_ty = NpArrayType {
size_type: generator.get_size_type(ctx),
elem_type: element_type,
};
ndarray_ty.get_struct_type(ctx).as_basic_type_enum()
}
_ => unreachable!(
@ -558,10 +525,8 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
};
return ty;
}
TTuple { ty, is_vararg_ctx } => {
TTuple { ty } => {
// a struct with fields in the order present in the tuple
assert!(!is_vararg_ctx, "Tuples in vararg context must be instantiated with the correct number of arguments before calling get_llvm_type");
let fields = ty
.iter()
.map(|ty| {
@ -591,7 +556,7 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
fn get_llvm_abi_type<'ctx, G: CodeGenerator + ?Sized>(
ctx: &'ctx Context,
module: &Module<'ctx>,
generator: &G,
generator: &mut G,
unifier: &mut Unifier,
top_level: &TopLevelContext,
type_cache: &mut HashMap<Type, BasicTypeEnum<'ctx>>,
@ -600,11 +565,11 @@ fn get_llvm_abi_type<'ctx, G: CodeGenerator + ?Sized>(
) -> BasicTypeEnum<'ctx> {
// If the type is used in the definition of a function, return `i1` instead of `i8` for ABI
// consistency.
if unifier.unioned(ty, primitives.bool) {
return if unifier.unioned(ty, primitives.bool) {
ctx.bool_type().into()
} else {
get_llvm_type(ctx, module, generator, unifier, top_level, type_cache, ty)
}
};
}
/// Whether `sret` is needed for a return value with type `ty`.
@ -629,40 +594,6 @@ fn need_sret(ty: BasicTypeEnum) -> bool {
need_sret_impl(ty, true)
}
/// Returns the [`BasicTypeEnum`] representing a `va_list` struct for variadic arguments.
fn get_llvm_valist_type<'ctx>(ctx: &'ctx Context, triple: &TargetTriple) -> BasicTypeEnum<'ctx> {
let triple = TargetMachine::normalize_triple(triple);
let triple = triple.as_str().to_str().unwrap();
let arch = triple.split('-').next().unwrap();
let llvm_pi8 = ctx.i8_type().ptr_type(AddressSpace::default());
// Referenced from parseArch() in llvm/lib/Support/Triple.cpp
match arch {
"i386" | "i486" | "i586" | "i686" | "riscv32" => {
ctx.i8_type().ptr_type(AddressSpace::default()).into()
}
"amd64" | "x86_64" | "x86_64h" => {
let llvm_i32 = ctx.i32_type();
let va_list_tag = ctx.opaque_struct_type("struct.__va_list_tag");
va_list_tag.set_body(
&[llvm_i32.into(), llvm_i32.into(), llvm_pi8.into(), llvm_pi8.into()],
false,
);
va_list_tag.into()
}
"armv7" => {
let va_list = ctx.opaque_struct_type("struct.__va_list");
va_list.set_body(&[llvm_pi8.into()], false);
va_list.into()
}
triple => {
todo!("Unsupported platform for varargs: {triple}")
}
}
}
/// Implementation for generating LLVM IR for a function.
pub fn gen_func_impl<
'ctx,
@ -774,7 +705,6 @@ pub fn gen_func_impl<
name: arg.name,
ty: task.store.to_unifier_type(&mut unifier, &primitives, arg.ty, &mut cache),
default_value: arg.default_value.clone(),
is_vararg: arg.is_vararg,
})
.collect_vec(),
task.store.to_unifier_type(&mut unifier, &primitives, *ret, &mut cache),
@ -797,10 +727,7 @@ pub fn gen_func_impl<
let has_sret = ret_type.map_or(false, |ty| need_sret(ty));
let mut params = args
.iter()
.filter(|arg| !arg.is_vararg)
.map(|arg| {
debug_assert!(!arg.is_vararg);
get_llvm_abi_type(
context,
&module,
@ -819,12 +746,9 @@ pub fn gen_func_impl<
params.insert(0, ret_type.unwrap().ptr_type(AddressSpace::default()).into());
}
debug_assert!(matches!(args.iter().filter(|arg| arg.is_vararg).count(), 0..=1));
let vararg_arg = args.iter().find(|arg| arg.is_vararg);
let fn_type = match ret_type {
Some(ret_type) if !has_sret => ret_type.fn_type(&params, vararg_arg.is_some()),
_ => context.void_type().fn_type(&params, vararg_arg.is_some()),
Some(ret_type) if !has_sret => ret_type.fn_type(&params, false),
_ => context.void_type().fn_type(&params, false),
};
let symbol = &task.symbol_name;
@ -852,10 +776,9 @@ pub fn gen_func_impl<
builder.position_at_end(init_bb);
let body_bb = context.append_basic_block(fn_val, "body");
// Store non-vararg argument values into local variables
let mut var_assignment = HashMap::new();
let offset = u32::from(has_sret);
for (n, arg) in args.iter().enumerate().filter(|(_, arg)| !arg.is_vararg) {
for (n, arg) in args.iter().enumerate() {
let param = fn_val.get_nth_param((n as u32) + offset).unwrap();
let local_type = get_llvm_type(
context,
@ -888,8 +811,6 @@ pub fn gen_func_impl<
var_assignment.insert(arg.name, (alloca, None, 0));
}
// TODO: Save vararg parameters as list
let return_buffer = if has_sret {
Some(fn_val.get_nth_param(0).unwrap().into_pointer_value())
} else {
@ -1112,9 +1033,3 @@ fn gen_in_range_check<'ctx>(
ctx.builder.build_int_compare(IntPredicate::SLT, lo, hi, "cmp").unwrap()
}
/// Returns the internal name for the `va_count` argument, used to indicate the number of arguments
/// passed to the variadic function.
fn get_va_count_arg_name(arg_name: StrRef) -> StrRef {
format!("__{}_va_count", &arg_name).into()
}

File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

View File

@ -1,37 +1,34 @@
use std::{
collections::{HashMap, HashSet},
sync::Arc,
};
use indexmap::IndexMap;
use indoc::indoc;
use inkwell::{
targets::{InitializationConfig, Target},
OptimizationLevel,
};
use nac3parser::{
ast::{fold::Fold, FileName, StrRef},
parser::parse_program,
};
use parking_lot::RwLock;
use super::{
classes::{ListType, NDArrayType, ProxyType, RangeType},
concrete_type::ConcreteTypeStore,
CodeGenContext, CodeGenLLVMOptions, CodeGenTargetMachineOptions, CodeGenTask, CodeGenerator,
DefaultCodeGenerator, WithCall, WorkerRegistry,
};
use crate::{
codegen::{
classes::{ListType, NDArrayType, ProxyType, RangeType},
concrete_type::ConcreteTypeStore,
CodeGenContext, CodeGenLLVMOptions, CodeGenTargetMachineOptions, CodeGenTask,
CodeGenerator, DefaultCodeGenerator, WithCall, WorkerRegistry,
},
symbol_resolver::{SymbolResolver, ValueEnum},
toplevel::{
composer::{ComposerConfig, TopLevelComposer},
DefinitionId, FunInstance, TopLevelContext, TopLevelDef,
},
typecheck::{
type_inferencer::{FunctionData, IdentifierInfo, Inferencer, PrimitiveStore},
type_inferencer::{FunctionData, Inferencer, PrimitiveStore},
typedef::{FunSignature, FuncArg, Type, TypeEnum, Unifier, VarMap},
},
};
use indexmap::IndexMap;
use indoc::indoc;
use inkwell::{
targets::{InitializationConfig, Target},
OptimizationLevel,
};
use nac3parser::ast::FileName;
use nac3parser::{
ast::{fold::Fold, StrRef},
parser::parse_program,
};
use parking_lot::RwLock;
use std::collections::{HashMap, HashSet};
use std::sync::Arc;
struct Resolver {
id_to_type: HashMap<StrRef, Type>,
@ -67,7 +64,6 @@ impl SymbolResolver for Resolver {
&self,
_: StrRef,
_: &mut CodeGenContext<'ctx, '_>,
_: &mut dyn CodeGenerator,
) -> Option<ValueEnum<'ctx>> {
unimplemented!()
}
@ -98,7 +94,7 @@ fn test_primitives() {
"};
let statements = parse_program(source, FileName::default()).unwrap();
let composer = TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 32).0;
let composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 32).0;
let mut unifier = composer.unifier.clone();
let primitives = composer.primitives_ty;
let top_level = Arc::new(composer.make_top_level_context());
@ -113,18 +109,8 @@ fn test_primitives() {
let threads = vec![DefaultCodeGenerator::new("test".into(), 32).into()];
let signature = FunSignature {
args: vec![
FuncArg {
name: "a".into(),
ty: primitives.int32,
default_value: None,
is_vararg: false,
},
FuncArg {
name: "b".into(),
ty: primitives.int32,
default_value: None,
is_vararg: false,
},
FuncArg { name: "a".into(), ty: primitives.int32, default_value: None },
FuncArg { name: "b".into(), ty: primitives.int32, default_value: None },
],
ret: primitives.int32,
vars: VarMap::new(),
@ -142,8 +128,7 @@ fn test_primitives() {
};
let mut virtual_checks = Vec::new();
let mut calls = HashMap::new();
let mut identifiers: HashMap<_, _> =
["a".into(), "b".into()].map(|id| (id, IdentifierInfo::default())).into();
let mut identifiers: HashSet<_> = ["a".into(), "b".into()].into();
let mut inferencer = Inferencer {
top_level: &top_level,
function_data: &mut function_data,
@ -204,8 +189,6 @@ fn test_primitives() {
let expected = indoc! {"
; ModuleID = 'test'
source_filename = \"test\"
target datalayout = \"e-m:e-p270:32:32-p271:32:32-p272:64:64-i64:64-f80:128-n8:16:32:64-S128\"
target triple = \"x86_64-unknown-linux-gnu\"
; Function Attrs: mustprogress nofree norecurse nosync nounwind readnone willreturn
define i32 @testing(i32 %0, i32 %1) local_unnamed_addr #0 !dbg !4 {
@ -263,19 +246,14 @@ fn test_simple_call() {
"};
let statements_2 = parse_program(source_2, FileName::default()).unwrap();
let composer = TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 32).0;
let composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 32).0;
let mut unifier = composer.unifier.clone();
let primitives = composer.primitives_ty;
let top_level = Arc::new(composer.make_top_level_context());
unifier.top_level = Some(top_level.clone());
let signature = FunSignature {
args: vec![FuncArg {
name: "a".into(),
ty: primitives.int32,
default_value: None,
is_vararg: false,
}],
args: vec![FuncArg { name: "a".into(), ty: primitives.int32, default_value: None }],
ret: primitives.int32,
vars: VarMap::new(),
};
@ -322,8 +300,7 @@ fn test_simple_call() {
};
let mut virtual_checks = Vec::new();
let mut calls = HashMap::new();
let mut identifiers: HashMap<_, _> =
["a".into(), "foo".into()].map(|id| (id, IdentifierInfo::default())).into();
let mut identifiers: HashSet<_> = ["a".into(), "foo".into()].into();
let mut inferencer = Inferencer {
top_level: &top_level,
function_data: &mut function_data,
@ -391,8 +368,6 @@ fn test_simple_call() {
let expected = indoc! {"
; ModuleID = 'test'
source_filename = \"test\"
target datalayout = \"e-m:e-p270:32:32-p271:32:32-p272:64:64-i64:64-f80:128-n8:16:32:64-S128\"
target triple = \"x86_64-unknown-linux-gnu\"
; Function Attrs: mustprogress nofree norecurse nosync nounwind readnone willreturn
define i32 @testing(i32 %0) local_unnamed_addr #0 !dbg !5 {

View File

@ -19,11 +19,8 @@
clippy::wildcard_imports
)]
// users of nac3core need to use the same version of these dependencies, so expose them as nac3core::*
pub use inkwell;
pub use nac3parser;
pub mod codegen;
pub mod symbol_resolver;
pub mod toplevel;
pub mod typecheck;
pub mod util;

View File

@ -1,15 +1,7 @@
use std::{
collections::{HashMap, HashSet},
fmt::{Debug, Display},
rc::Rc,
sync::Arc,
};
use inkwell::values::{BasicValueEnum, FloatValue, IntValue, PointerValue, StructValue};
use itertools::{chain, izip, Itertools};
use parking_lot::RwLock;
use nac3parser::ast::{Constant, Expr, Location, StrRef};
use std::fmt::Debug;
use std::rc::Rc;
use std::sync::Arc;
use std::{collections::HashMap, collections::HashSet, fmt::Display};
use crate::{
codegen::{CodeGenContext, CodeGenerator},
@ -19,6 +11,10 @@ use crate::{
typedef::{Type, TypeEnum, Unifier, VarMap},
},
};
use inkwell::values::{BasicValueEnum, FloatValue, IntValue, PointerValue, StructValue};
use itertools::{chain, izip, Itertools};
use nac3parser::ast::{Constant, Expr, Location, StrRef};
use parking_lot::RwLock;
#[derive(Clone, PartialEq, Debug)]
pub enum SymbolValue {
@ -82,14 +78,14 @@ impl SymbolValue {
}
Constant::Tuple(t) => {
let expected_ty = unifier.get_ty(expected_ty);
let TypeEnum::TTuple { ty, is_vararg_ctx } = expected_ty.as_ref() else {
let TypeEnum::TTuple { ty } = expected_ty.as_ref() else {
return Err(format!(
"Expected {:?}, but got Tuple",
expected_ty.get_type_name()
));
};
assert!(*is_vararg_ctx || ty.len() == t.len());
assert_eq!(ty.len(), t.len());
let elems = t
.iter()
@ -159,7 +155,7 @@ impl SymbolValue {
SymbolValue::Bool(_) => primitives.bool,
SymbolValue::Tuple(vs) => {
let vs_tys = vs.iter().map(|v| v.get_type(primitives, unifier)).collect::<Vec<_>>();
unifier.add_ty(TypeEnum::TTuple { ty: vs_tys, is_vararg_ctx: false })
unifier.add_ty(TypeEnum::TTuple { ty: vs_tys })
}
SymbolValue::OptionSome(_) | SymbolValue::OptionNone => primitives.option,
}
@ -369,7 +365,6 @@ pub trait SymbolResolver {
&self,
str: StrRef,
ctx: &mut CodeGenContext<'ctx, '_>,
generator: &mut dyn CodeGenerator,
) -> Option<ValueEnum<'ctx>>;
fn get_default_param_value(&self, expr: &Expr) -> Option<SymbolValue>;
@ -487,7 +482,7 @@ pub fn parse_type_annotation<T>(
parse_type_annotation(resolver, top_level_defs, unifier, primitives, elt)
})
.collect::<Result<Vec<_>, _>>()?;
Ok(unifier.add_ty(TypeEnum::TTuple { ty, is_vararg_ctx: false }))
Ok(unifier.add_ty(TypeEnum::TTuple { ty }))
} else {
Err(HashSet::from(["Expected multiple elements for tuple".into()]))
}

View File

@ -1,5 +1,7 @@
use std::iter::once;
use crate::util::SizeVariant;
use helper::{debug_assert_prim_is_allowed, make_exception_fields, PrimDefDetails};
use indexmap::IndexMap;
use inkwell::{
attributes::{Attribute, AttributeLoc},
@ -10,22 +12,22 @@ use inkwell::{
use itertools::Either;
use strum::IntoEnumIterator;
use super::{
helper::{debug_assert_prim_is_allowed, make_exception_fields, PrimDef, PrimDefDetails},
numpy::make_ndarray_ty,
*,
};
use crate::{
codegen::{
builtin_fns,
classes::{ProxyValue, RangeValue},
classes::{ArrayLikeValue, NDArrayValue, ProxyValue, RangeValue, TypedArrayLikeAccessor},
expr::destructure_range,
irrt::*,
numpy::*,
stmt::exn_constructor,
},
symbol_resolver::SymbolValue,
toplevel::{helper::PrimDef, numpy::make_ndarray_ty},
typecheck::typedef::{into_var_map, iter_type_vars, TypeVar, VarMap},
};
use super::*;
type BuiltinInfo = Vec<(Arc<RwLock<TopLevelDef>>, Option<Stmt>)>;
pub fn get_exn_constructor(
@ -44,26 +46,10 @@ pub fn get_exn_constructor(
name: "msg".into(),
ty: string,
default_value: Some(SymbolValue::Str(String::new())),
is_vararg: false,
},
FuncArg {
name: "param0".into(),
ty: int64,
default_value: Some(SymbolValue::I64(0)),
is_vararg: false,
},
FuncArg {
name: "param1".into(),
ty: int64,
default_value: Some(SymbolValue::I64(0)),
is_vararg: false,
},
FuncArg {
name: "param2".into(),
ty: int64,
default_value: Some(SymbolValue::I64(0)),
is_vararg: false,
},
FuncArg { name: "param0".into(), ty: int64, default_value: Some(SymbolValue::I64(0)) },
FuncArg { name: "param1".into(), ty: int64, default_value: Some(SymbolValue::I64(0)) },
FuncArg { name: "param2".into(), ty: int64, default_value: Some(SymbolValue::I64(0)) },
];
let exn_type = unifier.add_ty(TypeEnum::TObj {
obj_id: DefinitionId(class_id),
@ -113,7 +99,7 @@ pub fn get_exn_constructor(
/// * `name`: The name of the implemented NumPy function.
/// * `ret_ty`: The return type of this function.
/// * `param_ty`: The parameters accepted by this function, represented by a tuple of the
/// [parameter type][Type] and the parameter symbol name.
/// [parameter type][Type] and the parameter symbol name.
/// * `codegen_callback`: A lambda generating LLVM IR for the implementation of this function.
fn create_fn_by_codegen(
unifier: &mut Unifier,
@ -129,12 +115,7 @@ fn create_fn_by_codegen(
signature: unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: param_ty
.iter()
.map(|p| FuncArg {
name: p.1.into(),
ty: p.0,
default_value: None,
is_vararg: false,
})
.map(|p| FuncArg { name: p.1.into(), ty: p.0, default_value: None })
.collect(),
ret: ret_ty,
vars: var_map.clone(),
@ -153,7 +134,7 @@ fn create_fn_by_codegen(
/// * `name`: The name of the implemented NumPy function.
/// * `ret_ty`: The return type of this function.
/// * `param_ty`: The parameters accepted by this function, represented by a tuple of the
/// [parameter type][Type] and the parameter symbol name.
/// [parameter type][Type] and the parameter symbol name.
/// * `intrinsic_fn`: The fully-qualified name of the LLVM intrinsic function.
fn create_fn_by_intrinsic(
unifier: &mut Unifier,
@ -215,10 +196,10 @@ fn create_fn_by_intrinsic(
/// * `name`: The name of the implemented NumPy function.
/// * `ret_ty`: The return type of this function.
/// * `param_ty`: The parameters accepted by this function, represented by a tuple of the
/// [parameter type][Type] and the parameter symbol name.
/// [parameter type][Type] and the parameter symbol name.
/// * `extern_fn`: The fully-qualified name of the extern function used as the implementation.
/// * `attrs`: The list of attributes to apply to this function declaration. Note that `nounwind` is
/// already implied by the C ABI.
/// already implied by the C ABI.
fn create_fn_by_extern(
unifier: &mut Unifier,
var_map: &VarMap,
@ -298,19 +279,10 @@ pub fn get_builtins(unifier: &mut Unifier, primitives: &PrimitiveStore) -> Built
.collect()
}
/// A helper enum used by [`BuiltinBuilder`]
#[derive(Clone, Copy)]
enum SizeVariant {
Bits32,
Bits64,
}
impl SizeVariant {
fn of_int(self, primitives: &PrimitiveStore) -> Type {
match self {
SizeVariant::Bits32 => primitives.int32,
SizeVariant::Bits64 => primitives.int64,
}
fn size_variant_to_int_type(variant: SizeVariant, primitives: &PrimitiveStore) -> Type {
match variant {
SizeVariant::Bits32 => primitives.int32,
SizeVariant::Bits64 => primitives.int64,
}
}
@ -366,8 +338,8 @@ impl<'a> BuiltinBuilder<'a> {
let (is_some_ty, unwrap_ty, option_tvar) =
if let TypeEnum::TObj { fields, params, .. } = unifier.get_ty(option).as_ref() {
(
*fields.get(&PrimDef::FunOptionIsSome.simple_name().into()).unwrap(),
*fields.get(&PrimDef::FunOptionUnwrap.simple_name().into()).unwrap(),
*fields.get(&PrimDef::OptionIsSome.simple_name().into()).unwrap(),
*fields.get(&PrimDef::OptionUnwrap.simple_name().into()).unwrap(),
iter_type_vars(params).next().unwrap(),
)
} else {
@ -382,9 +354,9 @@ impl<'a> BuiltinBuilder<'a> {
let ndarray_dtype_tvar = iter_type_vars(ndarray_params).next().unwrap();
let ndarray_ndims_tvar = iter_type_vars(ndarray_params).nth(1).unwrap();
let ndarray_copy_ty =
*ndarray_fields.get(&PrimDef::FunNDArrayCopy.simple_name().into()).unwrap();
*ndarray_fields.get(&PrimDef::NDArrayCopy.simple_name().into()).unwrap();
let ndarray_fill_ty =
*ndarray_fields.get(&PrimDef::FunNDArrayFill.simple_name().into()).unwrap();
*ndarray_fields.get(&PrimDef::NDArrayFill.simple_name().into()).unwrap();
let num_ty = unifier.get_fresh_var_with_range(
&[int32, int64, float, boolean, uint32, uint64],
@ -484,14 +456,14 @@ impl<'a> BuiltinBuilder<'a> {
PrimDef::Exception => self.build_exception_class_related(prim),
PrimDef::Option
| PrimDef::FunOptionIsSome
| PrimDef::FunOptionIsNone
| PrimDef::FunOptionUnwrap
| PrimDef::OptionIsSome
| PrimDef::OptionIsNone
| PrimDef::OptionUnwrap
| PrimDef::FunSome => self.build_option_class_related(prim),
PrimDef::List => self.build_list_class_related(prim),
PrimDef::NDArray | PrimDef::FunNDArrayCopy | PrimDef::FunNDArrayFill => {
PrimDef::NDArray | PrimDef::NDArrayCopy | PrimDef::NDArrayFill => {
self.build_ndarray_class_related(prim)
}
@ -530,9 +502,7 @@ impl<'a> BuiltinBuilder<'a> {
PrimDef::FunMin | PrimDef::FunMax => self.build_min_max_function(prim),
PrimDef::FunNpArgmin | PrimDef::FunNpArgmax | PrimDef::FunNpMin | PrimDef::FunNpMax => {
self.build_np_max_min_function(prim)
}
PrimDef::FunNpMin | PrimDef::FunNpMax => self.build_np_min_max_function(prim),
PrimDef::FunNpMinimum | PrimDef::FunNpMaximum => {
self.build_np_minimum_maximum_function(prim)
@ -576,22 +546,6 @@ impl<'a> BuiltinBuilder<'a> {
| PrimDef::FunNpLdExp
| PrimDef::FunNpHypot
| PrimDef::FunNpNextAfter => self.build_np_2ary_function(prim),
PrimDef::FunNpTranspose | PrimDef::FunNpReshape => {
self.build_np_sp_ndarray_function(prim)
}
PrimDef::FunNpDot
| PrimDef::FunNpLinalgCholesky
| PrimDef::FunNpLinalgQr
| PrimDef::FunNpLinalgSvd
| PrimDef::FunNpLinalgInv
| PrimDef::FunNpLinalgPinv
| PrimDef::FunNpLinalgMatrixPower
| PrimDef::FunNpLinalgDet
| PrimDef::FunSpLinalgLu
| PrimDef::FunSpLinalgSchur
| PrimDef::FunSpLinalgHessenberg => self.build_linalg_methods(prim),
};
if cfg!(debug_assertions) {
@ -600,7 +554,7 @@ impl<'a> BuiltinBuilder<'a> {
match (&tld, prim.details()) {
(
TopLevelDef::Class { name, object_id, .. },
PrimDefDetails::PrimClass { name: exp_name, .. },
PrimDefDetails::PrimClass { name: exp_name },
) => {
let exp_object_id = prim.id();
assert_eq!(name, &exp_name.into());
@ -649,24 +603,17 @@ impl<'a> BuiltinBuilder<'a> {
let make_ctor_signature = |unifier: &mut Unifier| {
unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![
FuncArg {
name: "start".into(),
ty: int32,
default_value: None,
is_vararg: false,
},
FuncArg { name: "start".into(), ty: int32, default_value: None },
FuncArg {
name: "stop".into(),
ty: int32,
// placeholder
default_value: Some(SymbolValue::I32(0)),
is_vararg: false,
},
FuncArg {
name: "step".into(),
ty: int32,
default_value: Some(SymbolValue::I32(1)),
is_vararg: false,
},
],
ret: range,
@ -837,9 +784,9 @@ impl<'a> BuiltinBuilder<'a> {
prim,
&[
PrimDef::Option,
PrimDef::FunOptionIsSome,
PrimDef::FunOptionIsNone,
PrimDef::FunOptionUnwrap,
PrimDef::OptionIsSome,
PrimDef::OptionIsNone,
PrimDef::OptionUnwrap,
PrimDef::FunSome,
],
);
@ -852,9 +799,9 @@ impl<'a> BuiltinBuilder<'a> {
fields: Vec::default(),
attributes: Vec::default(),
methods: vec![
Self::create_method(PrimDef::FunOptionIsSome, self.is_some_ty.0),
Self::create_method(PrimDef::FunOptionIsNone, self.is_some_ty.0),
Self::create_method(PrimDef::FunOptionUnwrap, self.unwrap_ty.0),
Self::create_method(PrimDef::OptionIsSome, self.is_some_ty.0),
Self::create_method(PrimDef::OptionIsNone, self.is_some_ty.0),
Self::create_method(PrimDef::OptionUnwrap, self.unwrap_ty.0),
],
ancestors: vec![TypeAnnotation::CustomClass {
id: prim.id(),
@ -865,7 +812,7 @@ impl<'a> BuiltinBuilder<'a> {
loc: None,
},
PrimDef::FunOptionUnwrap => TopLevelDef::Function {
PrimDef::OptionUnwrap => TopLevelDef::Function {
name: prim.name().into(),
simple_name: prim.simple_name().into(),
signature: self.unwrap_ty.0,
@ -879,7 +826,7 @@ impl<'a> BuiltinBuilder<'a> {
loc: None,
},
PrimDef::FunOptionIsNone | PrimDef::FunOptionIsSome => TopLevelDef::Function {
PrimDef::OptionIsNone | PrimDef::OptionIsSome => TopLevelDef::Function {
name: prim.name().to_string(),
simple_name: prim.simple_name().into(),
signature: self.is_some_ty.0,
@ -900,10 +847,10 @@ impl<'a> BuiltinBuilder<'a> {
};
let returned_int = match prim {
PrimDef::FunOptionIsNone => {
PrimDef::OptionIsNone => {
ctx.builder.build_is_null(ptr, prim.simple_name())
}
PrimDef::FunOptionIsSome => {
PrimDef::OptionIsSome => {
ctx.builder.build_is_not_null(ptr, prim.simple_name())
}
_ => unreachable!(),
@ -922,7 +869,6 @@ impl<'a> BuiltinBuilder<'a> {
name: "n".into(),
ty: self.option_tvar.ty,
default_value: None,
is_vararg: false,
}],
ret: self.primitives.option,
vars: into_var_map([self.option_tvar]),
@ -977,7 +923,7 @@ impl<'a> BuiltinBuilder<'a> {
fn build_ndarray_class_related(&self, prim: PrimDef) -> TopLevelDef {
debug_assert_prim_is_allowed(
prim,
&[PrimDef::NDArray, PrimDef::FunNDArrayCopy, PrimDef::FunNDArrayFill],
&[PrimDef::NDArray, PrimDef::NDArrayCopy, PrimDef::NDArrayFill],
);
match prim {
@ -988,8 +934,8 @@ impl<'a> BuiltinBuilder<'a> {
fields: Vec::default(),
attributes: Vec::default(),
methods: vec![
Self::create_method(PrimDef::FunNDArrayCopy, self.ndarray_copy_ty.0),
Self::create_method(PrimDef::FunNDArrayFill, self.ndarray_fill_ty.0),
Self::create_method(PrimDef::NDArrayCopy, self.ndarray_copy_ty.0),
Self::create_method(PrimDef::NDArrayFill, self.ndarray_fill_ty.0),
],
ancestors: Vec::default(),
constructor: None,
@ -997,7 +943,7 @@ impl<'a> BuiltinBuilder<'a> {
loc: None,
},
PrimDef::FunNDArrayCopy => TopLevelDef::Function {
PrimDef::NDArrayCopy => TopLevelDef::Function {
name: prim.name().into(),
simple_name: prim.simple_name().into(),
signature: self.ndarray_copy_ty.0,
@ -1007,14 +953,15 @@ impl<'a> BuiltinBuilder<'a> {
resolver: None,
codegen_callback: Some(Arc::new(GenCall::new(Box::new(
|ctx, obj, fun, args, generator| {
gen_ndarray_copy(ctx, &obj, fun, &args, generator)
.map(|val| Some(val.as_basic_value_enum()))
todo!()
// gen_ndarray_copy(ctx, &obj, fun, &args, generator)
// .map(|val| Some(val.as_basic_value_enum()))
},
)))),
loc: None,
},
PrimDef::FunNDArrayFill => TopLevelDef::Function {
PrimDef::NDArrayFill => TopLevelDef::Function {
name: prim.name().into(),
simple_name: prim.simple_name().into(),
signature: self.ndarray_fill_ty.0,
@ -1024,8 +971,9 @@ impl<'a> BuiltinBuilder<'a> {
resolver: None,
codegen_callback: Some(Arc::new(GenCall::new(Box::new(
|ctx, obj, fun, args, generator| {
gen_ndarray_fill(ctx, &obj, fun, &args, generator)?;
Ok(None)
todo!()
// gen_ndarray_fill(ctx, &obj, fun, &args, generator)?;
// Ok(None)
},
)))),
loc: None,
@ -1057,7 +1005,6 @@ impl<'a> BuiltinBuilder<'a> {
name: "n".into(),
ty: self.num_or_ndarray_ty.ty,
default_value: None,
is_vararg: false,
}],
ret: self.num_or_ndarray_ty.ty,
vars: self.num_or_ndarray_var_map.clone(),
@ -1106,7 +1053,7 @@ impl<'a> BuiltinBuilder<'a> {
);
// The size variant of the function determines the size of the returned int.
let int_sized = size_variant.of_int(self.primitives);
let int_sized = size_variant_to_int_type(size_variant, self.primitives);
let ndarray_int_sized =
make_ndarray_ty(self.unifier, self.primitives, Some(int_sized), Some(common_ndim.ty));
@ -1131,7 +1078,7 @@ impl<'a> BuiltinBuilder<'a> {
let arg_ty = fun.0.args[0].ty;
let arg = args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
let ret_elem_ty = size_variant.of_int(&ctx.primitives);
let ret_elem_ty = size_variant_to_int_type(size_variant, &ctx.primitives);
Ok(Some(builtin_fns::call_round(generator, ctx, (arg_ty, arg), ret_elem_ty)?))
}),
)
@ -1172,7 +1119,7 @@ impl<'a> BuiltinBuilder<'a> {
make_ndarray_ty(self.unifier, self.primitives, Some(float), Some(common_ndim.ty));
// The size variant of the function determines the type of int returned
let int_sized = size_variant.of_int(self.primitives);
let int_sized = size_variant_to_int_type(size_variant, self.primitives);
let ndarray_int_sized =
make_ndarray_ty(self.unifier, self.primitives, Some(int_sized), Some(common_ndim.ty));
@ -1195,7 +1142,7 @@ impl<'a> BuiltinBuilder<'a> {
let arg_ty = fun.0.args[0].ty;
let arg = args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
let ret_elem_ty = size_variant.of_int(&ctx.primitives);
let ret_elem_ty = size_variant_to_int_type(size_variant, &ctx.primitives);
let func = match kind {
Kind::Ceil => builtin_fns::call_ceil,
Kind::Floor => builtin_fns::call_floor,
@ -1249,7 +1196,7 @@ impl<'a> BuiltinBuilder<'a> {
let func = match prim {
PrimDef::FunNpNDArray | PrimDef::FunNpEmpty => gen_ndarray_empty,
PrimDef::FunNpZeros => gen_ndarray_zeros,
PrimDef::FunNpOnes => gen_ndarray_ones,
PrimDef::FunNpOnes => todo!(), // gen_ndarray_ones,
_ => unreachable!(),
};
func(ctx, &obj, fun, &args, generator).map(|val| Some(val.as_basic_value_enum()))
@ -1277,23 +1224,16 @@ impl<'a> BuiltinBuilder<'a> {
simple_name: prim.simple_name().into(),
signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![
FuncArg {
name: "object".into(),
ty: tv.ty,
default_value: None,
is_vararg: false,
},
FuncArg { name: "object".into(), ty: tv.ty, default_value: None },
FuncArg {
name: "copy".into(),
ty: bool,
default_value: Some(SymbolValue::Bool(true)),
is_vararg: false,
},
FuncArg {
name: "ndmin".into(),
ty: int32,
default_value: Some(SymbolValue::U32(0)),
is_vararg: false,
},
],
ret: ndarray,
@ -1305,8 +1245,9 @@ impl<'a> BuiltinBuilder<'a> {
resolver: None,
codegen_callback: Some(Arc::new(GenCall::new(Box::new(
|ctx, obj, fun, args, generator| {
gen_ndarray_array(ctx, &obj, fun, &args, generator)
.map(|val| Some(val.as_basic_value_enum()))
todo!()
// gen_ndarray_array(ctx, &obj, fun, &args, generator)
// .map(|val| Some(val.as_basic_value_enum()))
},
)))),
loc: None,
@ -1324,8 +1265,9 @@ impl<'a> BuiltinBuilder<'a> {
// type variable
&[(self.list_int32, "shape"), (tv.ty, "fill_value")],
Box::new(move |ctx, obj, fun, args, generator| {
gen_ndarray_full(ctx, &obj, fun, &args, generator)
.map(|val| Some(val.as_basic_value_enum()))
todo!()
// gen_ndarray_full(ctx, &obj, fun, &args, generator)
// .map(|val| Some(val.as_basic_value_enum()))
}),
)
}
@ -1335,24 +1277,17 @@ impl<'a> BuiltinBuilder<'a> {
simple_name: prim.simple_name().into(),
signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![
FuncArg {
name: "N".into(),
ty: int32,
default_value: None,
is_vararg: false,
},
FuncArg { name: "N".into(), ty: int32, default_value: None },
// TODO(Derppening): Default values current do not work?
FuncArg {
name: "M".into(),
ty: int32,
default_value: Some(SymbolValue::OptionNone),
is_vararg: false,
},
FuncArg {
name: "k".into(),
ty: int32,
default_value: Some(SymbolValue::I32(0)),
is_vararg: false,
},
],
ret: self.ndarray_float_2d,
@ -1364,8 +1299,9 @@ impl<'a> BuiltinBuilder<'a> {
resolver: None,
codegen_callback: Some(Arc::new(GenCall::new(Box::new(
|ctx, obj, fun, args, generator| {
gen_ndarray_eye(ctx, &obj, fun, &args, generator)
.map(|val| Some(val.as_basic_value_enum()))
todo!()
// gen_ndarray_eye(ctx, &obj, fun, &args, generator)
// .map(|val| Some(val.as_basic_value_enum()))
},
)))),
loc: None,
@ -1378,8 +1314,9 @@ impl<'a> BuiltinBuilder<'a> {
self.ndarray_float_2d,
&[(int32, "n")],
Box::new(|ctx, obj, fun, args, generator| {
gen_ndarray_identity(ctx, &obj, fun, &args, generator)
.map(|val| Some(val.as_basic_value_enum()))
todo!()
// gen_ndarray_identity(ctx, &obj, fun, &args, generator)
// .map(|val| Some(val.as_basic_value_enum()))
}),
),
_ => unreachable!(),
@ -1396,12 +1333,7 @@ impl<'a> BuiltinBuilder<'a> {
name: prim.name().into(),
simple_name: prim.simple_name().into(),
signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![FuncArg {
name: "s".into(),
ty: str,
default_value: None,
is_vararg: false,
}],
args: vec![FuncArg { name: "s".into(), ty: str, default_value: None }],
ret: str,
vars: VarMap::default(),
})),
@ -1465,21 +1397,31 @@ impl<'a> BuiltinBuilder<'a> {
fn build_len_function(&mut self) -> TopLevelDef {
let prim = PrimDef::FunLen;
// Type handled in [`Inferencer::try_fold_special_call`]
let arg_tvar = self.unifier.get_dummy_var();
let PrimitiveStore { uint64, int32, .. } = *self.primitives;
let tvar = self.unifier.get_fresh_var(Some("L".into()), None);
let list = self
.unifier
.subst(
self.primitives.list,
&into_var_map([TypeVar { id: self.list_tvar.id, ty: tvar.ty }]),
)
.unwrap();
let ndims = self.unifier.get_fresh_const_generic_var(uint64, Some("N".into()), None);
let ndarray = make_ndarray_ty(self.unifier, self.primitives, Some(tvar.ty), Some(ndims.ty));
let arg_ty = self.unifier.get_fresh_var_with_range(
&[list, ndarray, self.primitives.range],
Some("I".into()),
None,
);
TopLevelDef::Function {
name: prim.name().into(),
simple_name: prim.simple_name().into(),
signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![FuncArg {
name: "obj".into(),
ty: arg_tvar.ty,
default_value: None,
is_vararg: false,
}],
ret: self.primitives.int32,
vars: into_var_map([arg_tvar]),
args: vec![FuncArg { name: "ls".into(), ty: arg_ty.ty, default_value: None }],
ret: int32,
vars: into_var_map([tvar, arg_ty]),
})),
var_id: Vec::default(),
instance_to_symbol: HashMap::default(),
@ -1487,10 +1429,86 @@ impl<'a> BuiltinBuilder<'a> {
resolver: None,
codegen_callback: Some(Arc::new(GenCall::new(Box::new(
move |ctx, _, fun, args, generator| {
let range_ty = ctx.primitives.range;
let arg_ty = fun.0.args[0].ty;
let arg = args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
Ok(if ctx.unifier.unioned(arg_ty, range_ty) {
let arg = RangeValue::from_ptr_val(arg.into_pointer_value(), Some("range"));
let (start, end, step) = destructure_range(ctx, arg);
Some(calculate_len_for_slice_range(generator, ctx, start, end, step).into())
} else {
match &*ctx.unifier.get_ty_immutable(arg_ty) {
TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::List.id() => {
let int32 = ctx.ctx.i32_type();
let zero = int32.const_zero();
let len = ctx
.build_gep_and_load(
arg.into_pointer_value(),
&[zero, int32.const_int(1, false)],
None,
)
.into_int_value();
if len.get_type().get_bit_width() == 32 {
Some(len.into())
} else {
Some(
ctx.builder
.build_int_truncate(len, int32, "len2i32")
.map(Into::into)
.unwrap(),
)
}
}
TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
builtin_fns::call_len(generator, ctx, (arg_ty, arg)).map(|ret| Some(ret.into()))
let arg = NDArrayValue::from_ptr_val(
arg.into_pointer_value(),
llvm_usize,
None,
);
let ndims = arg.dim_sizes().size(ctx, generator);
ctx.make_assert(
generator,
ctx.builder
.build_int_compare(
IntPredicate::NE,
ndims,
llvm_usize.const_zero(),
"",
)
.unwrap(),
"0:TypeError",
&format!("{name}() of unsized object", name = prim.name()),
[None, None, None],
ctx.current_loc,
);
let len = unsafe {
arg.dim_sizes().get_typed_unchecked(
ctx,
generator,
&llvm_usize.const_zero(),
None,
)
};
if len.get_type().get_bit_width() == 32 {
Some(len.into())
} else {
Some(
ctx.builder
.build_int_truncate(len, llvm_i32, "len")
.map(Into::into)
.unwrap(),
)
}
}
_ => unreachable!(),
}
})
},
)))),
loc: None,
@ -1506,18 +1524,8 @@ impl<'a> BuiltinBuilder<'a> {
simple_name: prim.simple_name().into(),
signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![
FuncArg {
name: "m".into(),
ty: self.num_ty.ty,
default_value: None,
is_vararg: false,
},
FuncArg {
name: "n".into(),
ty: self.num_ty.ty,
default_value: None,
is_vararg: false,
},
FuncArg { name: "m".into(), ty: self.num_ty.ty, default_value: None },
FuncArg { name: "n".into(), ty: self.num_ty.ty, default_value: None },
],
ret: self.num_ty.ty,
vars: self.num_var_map.clone(),
@ -1545,45 +1553,39 @@ impl<'a> BuiltinBuilder<'a> {
}
}
/// Build the functions `np_max()`, `np_min()`, `np_argmax()` and `np_argmin()`
/// Calls `call_numpy_max_min` with the function name
fn build_np_max_min_function(&mut self, prim: PrimDef) -> TopLevelDef {
debug_assert_prim_is_allowed(
prim,
&[PrimDef::FunNpArgmin, PrimDef::FunNpArgmax, PrimDef::FunNpMin, PrimDef::FunNpMax],
);
/// Build the functions `np_min()` and `np_max()`.
fn build_np_min_max_function(&mut self, prim: PrimDef) -> TopLevelDef {
debug_assert_prim_is_allowed(prim, &[PrimDef::FunNpMin, PrimDef::FunNpMax]);
let (var_map, ret_ty) = match prim {
PrimDef::FunNpArgmax | PrimDef::FunNpArgmin => {
(self.num_or_ndarray_var_map.clone(), self.primitives.int64)
}
PrimDef::FunNpMax | PrimDef::FunNpMin => {
let ret_ty = self.unifier.get_fresh_var(Some("R".into()), None);
let var_map = self
.num_or_ndarray_var_map
.clone()
.into_iter()
.chain(once((ret_ty.id, ret_ty.ty)))
.collect::<IndexMap<_, _>>();
(var_map, ret_ty.ty)
}
_ => unreachable!(),
};
let ret_ty = self.unifier.get_fresh_var(Some("R".into()), None);
let var_map = self
.num_or_ndarray_var_map
.clone()
.into_iter()
.chain(once((ret_ty.id, ret_ty.ty)))
.collect::<IndexMap<_, _>>();
create_fn_by_codegen(
self.unifier,
&var_map,
prim.name(),
ret_ty,
&[(self.num_or_ndarray_ty.ty, "a")],
ret_ty.ty,
&[(self.float_or_ndarray_ty.ty, "a")],
Box::new(move |ctx, _, fun, args, generator| {
let a_ty = fun.0.args[0].ty;
let a = args[0].1.clone().to_basic_value_enum(ctx, generator, a_ty)?;
Ok(Some(builtin_fns::call_numpy_max_min(generator, ctx, (a_ty, a), prim.name())?))
let func = match prim {
PrimDef::FunNpMin => builtin_fns::call_numpy_min,
PrimDef::FunNpMax => builtin_fns::call_numpy_max,
_ => unreachable!(),
};
Ok(Some(func(generator, ctx, (a_ty, a))?))
}),
)
}
/// Build the functions `np_minimum()` and `np_maximum()`.
fn build_np_minimum_maximum_function(&mut self, prim: PrimDef) -> TopLevelDef {
debug_assert_prim_is_allowed(prim, &[PrimDef::FunNpMinimum, PrimDef::FunNpMaximum]);
@ -1599,12 +1601,7 @@ impl<'a> BuiltinBuilder<'a> {
signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: param_ty
.iter()
.map(|p| FuncArg {
name: p.1.into(),
ty: p.0,
default_value: None,
is_vararg: false,
})
.map(|p| FuncArg { name: p.1.into(), ty: p.0, default_value: None })
.collect(),
ret: ret_ty.ty,
vars: into_var_map([x1_ty, x2_ty, ret_ty]),
@ -1645,7 +1642,6 @@ impl<'a> BuiltinBuilder<'a> {
name: "n".into(),
ty: self.num_or_ndarray_ty.ty,
default_value: None,
is_vararg: false,
}],
ret: self.num_or_ndarray_ty.ty,
vars: self.num_or_ndarray_var_map.clone(),
@ -1834,12 +1830,7 @@ impl<'a> BuiltinBuilder<'a> {
signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: param_ty
.iter()
.map(|p| FuncArg {
name: p.1.into(),
ty: p.0,
default_value: None,
is_vararg: false,
})
.map(|p| FuncArg { name: p.1.into(), ty: p.0, default_value: None })
.collect(),
ret: ret_ty.ty,
vars: into_var_map([x1_ty, x2_ty, ret_ty]),
@ -1873,207 +1864,6 @@ impl<'a> BuiltinBuilder<'a> {
}
}
/// Build np/sp functions that take as input `NDArray` only
fn build_np_sp_ndarray_function(&mut self, prim: PrimDef) -> TopLevelDef {
debug_assert_prim_is_allowed(prim, &[PrimDef::FunNpTranspose, PrimDef::FunNpReshape]);
match prim {
PrimDef::FunNpTranspose => {
let ndarray_ty = self.unifier.get_fresh_var_with_range(
&[self.ndarray_num_ty],
Some("T".into()),
None,
);
create_fn_by_codegen(
self.unifier,
&into_var_map([ndarray_ty]),
prim.name(),
ndarray_ty.ty,
&[(ndarray_ty.ty, "x")],
Box::new(move |ctx, _, fun, args, generator| {
let arg_ty = fun.0.args[0].ty;
let arg_val =
args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
Ok(Some(ndarray_transpose(generator, ctx, (arg_ty, arg_val))?))
}),
)
}
// NOTE: on `ndarray_factory_fn_shape_arg_tvar` and
// the `param_ty` for `create_fn_by_codegen`.
//
// Similar to `build_ndarray_from_shape_factory_function` we delegate the responsibility of typechecking
// to [`typecheck::type_inferencer::Inferencer::fold_numpy_function_call_shape_argument`],
// and use a dummy [`TypeVar`] `ndarray_factory_fn_shape_arg_tvar` as a placeholder for `param_ty`.
PrimDef::FunNpReshape => create_fn_by_codegen(
self.unifier,
&VarMap::new(),
prim.name(),
self.ndarray_num_ty,
&[(self.ndarray_num_ty, "x"), (self.ndarray_factory_fn_shape_arg_tvar.ty, "shape")],
Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty;
let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
let x2_ty = fun.0.args[1].ty;
let x2_val = args[1].1.clone().to_basic_value_enum(ctx, generator, x2_ty)?;
Ok(Some(ndarray_reshape(generator, ctx, (x1_ty, x1_val), (x2_ty, x2_val))?))
}),
),
_ => unreachable!(),
}
}
/// Build `np_linalg` and `sp_linalg` functions
///
/// The input to these functions must be floating point `NDArray`
fn build_linalg_methods(&mut self, prim: PrimDef) -> TopLevelDef {
debug_assert_prim_is_allowed(
prim,
&[
PrimDef::FunNpDot,
PrimDef::FunNpLinalgCholesky,
PrimDef::FunNpLinalgQr,
PrimDef::FunNpLinalgSvd,
PrimDef::FunNpLinalgInv,
PrimDef::FunNpLinalgPinv,
PrimDef::FunNpLinalgMatrixPower,
PrimDef::FunNpLinalgDet,
PrimDef::FunSpLinalgLu,
PrimDef::FunSpLinalgSchur,
PrimDef::FunSpLinalgHessenberg,
],
);
match prim {
PrimDef::FunNpDot => create_fn_by_codegen(
self.unifier,
&self.num_or_ndarray_var_map,
prim.name(),
self.num_ty.ty,
&[(self.num_or_ndarray_ty.ty, "x1"), (self.num_or_ndarray_ty.ty, "x2")],
Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty;
let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
let x2_ty = fun.0.args[1].ty;
let x2_val = args[1].1.clone().to_basic_value_enum(ctx, generator, x2_ty)?;
Ok(Some(ndarray_dot(generator, ctx, (x1_ty, x1_val), (x2_ty, x2_val))?))
}),
),
PrimDef::FunNpLinalgCholesky | PrimDef::FunNpLinalgInv | PrimDef::FunNpLinalgPinv => {
create_fn_by_codegen(
self.unifier,
&VarMap::new(),
prim.name(),
self.ndarray_float_2d,
&[(self.ndarray_float_2d, "x1")],
Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty;
let x1_val =
args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
let func = match prim {
PrimDef::FunNpLinalgCholesky => builtin_fns::call_np_linalg_cholesky,
PrimDef::FunNpLinalgInv => builtin_fns::call_np_linalg_inv,
PrimDef::FunNpLinalgPinv => builtin_fns::call_np_linalg_pinv,
_ => unreachable!(),
};
Ok(Some(func(generator, ctx, (x1_ty, x1_val))?))
}),
)
}
PrimDef::FunNpLinalgQr
| PrimDef::FunSpLinalgLu
| PrimDef::FunSpLinalgSchur
| PrimDef::FunSpLinalgHessenberg => {
let ret_ty = self.unifier.add_ty(TypeEnum::TTuple {
ty: vec![self.ndarray_float_2d, self.ndarray_float_2d],
is_vararg_ctx: false,
});
create_fn_by_codegen(
self.unifier,
&VarMap::new(),
prim.name(),
ret_ty,
&[(self.ndarray_float_2d, "x1")],
Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty;
let x1_val =
args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
let func = match prim {
PrimDef::FunNpLinalgQr => builtin_fns::call_np_linalg_qr,
PrimDef::FunSpLinalgLu => builtin_fns::call_sp_linalg_lu,
PrimDef::FunSpLinalgSchur => builtin_fns::call_sp_linalg_schur,
PrimDef::FunSpLinalgHessenberg => {
builtin_fns::call_sp_linalg_hessenberg
}
_ => unreachable!(),
};
Ok(Some(func(generator, ctx, (x1_ty, x1_val))?))
}),
)
}
PrimDef::FunNpLinalgSvd => {
let ret_ty = self.unifier.add_ty(TypeEnum::TTuple {
ty: vec![self.ndarray_float_2d, self.ndarray_float, self.ndarray_float_2d],
is_vararg_ctx: false,
});
create_fn_by_codegen(
self.unifier,
&VarMap::new(),
prim.name(),
ret_ty,
&[(self.ndarray_float_2d, "x1")],
Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty;
let x1_val =
args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
Ok(Some(builtin_fns::call_np_linalg_svd(generator, ctx, (x1_ty, x1_val))?))
}),
)
}
PrimDef::FunNpLinalgMatrixPower => create_fn_by_codegen(
self.unifier,
&VarMap::new(),
prim.name(),
self.ndarray_float_2d,
&[(self.ndarray_float_2d, "x1"), (self.primitives.int32, "power")],
Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty;
let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
let x2_ty = fun.0.args[1].ty;
let x2_val = args[1].1.clone().to_basic_value_enum(ctx, generator, x2_ty)?;
Ok(Some(builtin_fns::call_np_linalg_matrix_power(
generator,
ctx,
(x1_ty, x1_val),
(x2_ty, x2_val),
)?))
}),
),
PrimDef::FunNpLinalgDet => create_fn_by_codegen(
self.unifier,
&VarMap::new(),
prim.name(),
self.primitives.float,
&[(self.ndarray_float_2d, "x1")],
Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty;
let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
Ok(Some(builtin_fns::call_np_linalg_det(generator, ctx, (x1_ty, x1_val))?))
}),
),
_ => unreachable!(),
}
}
fn create_method(prim: PrimDef, method_ty: Type) -> (StrRef, Type, DefinitionId) {
(prim.simple_name().into(), method_ty, prim.id())
}

File diff suppressed because it is too large Load Diff

View File

@ -1,15 +1,13 @@
use std::convert::TryInto;
use crate::symbol_resolver::SymbolValue;
use crate::toplevel::numpy::unpack_ndarray_var_tys;
use crate::typecheck::typedef::{into_var_map, iter_type_vars, Mapping, TypeVarId, VarMap};
use nac3parser::ast::{Constant, Location};
use strum::IntoEnumIterator;
use strum_macros::EnumIter;
use nac3parser::ast::{Constant, ExprKind, Location};
use super::{numpy::unpack_ndarray_var_tys, *};
use crate::{
symbol_resolver::SymbolValue,
typecheck::typedef::{into_var_map, iter_type_vars, Mapping, TypeVarId, VarMap},
};
use super::*;
/// All primitive types and functions in nac3core.
#[derive(Clone, Copy, Debug, EnumIter, PartialEq, Eq)]
@ -29,22 +27,17 @@ pub enum PrimDef {
List,
NDArray,
// Option methods
FunOptionIsSome,
FunOptionIsNone,
FunOptionUnwrap,
// Option-related functions
FunSome,
// NDArray methods
FunNDArrayCopy,
FunNDArrayFill,
// Range methods
FunRangeInit,
// NumPy factory functions
// Member Functions
OptionIsSome,
OptionIsNone,
OptionUnwrap,
NDArrayCopy,
NDArrayFill,
FunInt32,
FunInt64,
FunUInt32,
FunUInt64,
FunFloat,
FunNpNDArray,
FunNpEmpty,
FunNpZeros,
@ -53,17 +46,26 @@ pub enum PrimDef {
FunNpArray,
FunNpEye,
FunNpIdentity,
// Miscellaneous NumPy & SciPy functions
FunRound,
FunRound64,
FunNpRound,
FunRangeInit,
FunStr,
FunBool,
FunFloor,
FunFloor64,
FunNpFloor,
FunCeil,
FunCeil64,
FunNpCeil,
FunLen,
FunMin,
FunNpMin,
FunNpMinimum,
FunNpArgmin,
FunMax,
FunNpMax,
FunNpMaximum,
FunNpArgmax,
FunAbs,
FunNpIsNan,
FunNpIsInf,
FunNpSin,
@ -101,46 +103,15 @@ pub enum PrimDef {
FunNpLdExp,
FunNpHypot,
FunNpNextAfter,
FunNpTranspose,
FunNpReshape,
// Linalg functions
FunNpDot,
FunNpLinalgCholesky,
FunNpLinalgQr,
FunNpLinalgSvd,
FunNpLinalgInv,
FunNpLinalgPinv,
FunNpLinalgMatrixPower,
FunNpLinalgDet,
FunSpLinalgLu,
FunSpLinalgSchur,
FunSpLinalgHessenberg,
// Miscellaneous Python & NAC3 functions
FunInt32,
FunInt64,
FunUInt32,
FunUInt64,
FunFloat,
FunRound,
FunRound64,
FunStr,
FunBool,
FunFloor,
FunFloor64,
FunCeil,
FunCeil64,
FunLen,
FunMin,
FunMax,
FunAbs,
// Top-Level Functions
FunSome,
}
/// Associated details of a [`PrimDef`]
pub enum PrimDefDetails {
PrimFunction { name: &'static str, simple_name: &'static str },
PrimClass { name: &'static str, get_ty_fn: fn(&PrimitiveStore) -> Type },
PrimClass { name: &'static str },
}
impl PrimDef {
@ -182,17 +153,15 @@ impl PrimDef {
#[must_use]
pub fn name(&self) -> &'static str {
match self.details() {
PrimDefDetails::PrimFunction { name, .. } | PrimDefDetails::PrimClass { name, .. } => {
name
}
PrimDefDetails::PrimFunction { name, .. } | PrimDefDetails::PrimClass { name } => name,
}
}
/// Get the associated details of this [`PrimDef`]
#[must_use]
pub fn details(self) -> PrimDefDetails {
fn class(name: &'static str, get_ty_fn: fn(&PrimitiveStore) -> Type) -> PrimDefDetails {
PrimDefDetails::PrimClass { name, get_ty_fn }
fn class(name: &'static str) -> PrimDefDetails {
PrimDefDetails::PrimClass { name }
}
fn fun(name: &'static str, simple_name: Option<&'static str>) -> PrimDefDetails {
@ -200,37 +169,29 @@ impl PrimDef {
}
match self {
// Classes
PrimDef::Int32 => class("int32", |primitives| primitives.int32),
PrimDef::Int64 => class("int64", |primitives| primitives.int64),
PrimDef::Float => class("float", |primitives| primitives.float),
PrimDef::Bool => class("bool", |primitives| primitives.bool),
PrimDef::None => class("none", |primitives| primitives.none),
PrimDef::Range => class("range", |primitives| primitives.range),
PrimDef::Str => class("str", |primitives| primitives.str),
PrimDef::Exception => class("Exception", |primitives| primitives.exception),
PrimDef::UInt32 => class("uint32", |primitives| primitives.uint32),
PrimDef::UInt64 => class("uint64", |primitives| primitives.uint64),
PrimDef::Option => class("Option", |primitives| primitives.option),
PrimDef::List => class("list", |primitives| primitives.list),
PrimDef::NDArray => class("ndarray", |primitives| primitives.ndarray),
// Option methods
PrimDef::FunOptionIsSome => fun("Option.is_some", Some("is_some")),
PrimDef::FunOptionIsNone => fun("Option.is_none", Some("is_none")),
PrimDef::FunOptionUnwrap => fun("Option.unwrap", Some("unwrap")),
// Option-related functions
PrimDef::FunSome => fun("Some", None),
// NDArray methods
PrimDef::FunNDArrayCopy => fun("ndarray.copy", Some("copy")),
PrimDef::FunNDArrayFill => fun("ndarray.fill", Some("fill")),
// Range methods
PrimDef::FunRangeInit => fun("range.__init__", Some("__init__")),
// NumPy factory functions
PrimDef::Int32 => class("int32"),
PrimDef::Int64 => class("int64"),
PrimDef::Float => class("float"),
PrimDef::Bool => class("bool"),
PrimDef::None => class("none"),
PrimDef::Range => class("range"),
PrimDef::Str => class("str"),
PrimDef::Exception => class("Exception"),
PrimDef::UInt32 => class("uint32"),
PrimDef::UInt64 => class("uint64"),
PrimDef::Option => class("Option"),
PrimDef::OptionIsSome => fun("Option.is_some", Some("is_some")),
PrimDef::OptionIsNone => fun("Option.is_none", Some("is_none")),
PrimDef::OptionUnwrap => fun("Option.unwrap", Some("unwrap")),
PrimDef::List => class("list"),
PrimDef::NDArray => class("ndarray"),
PrimDef::NDArrayCopy => fun("ndarray.copy", Some("copy")),
PrimDef::NDArrayFill => fun("ndarray.fill", Some("fill")),
PrimDef::FunInt32 => fun("int32", None),
PrimDef::FunInt64 => fun("int64", None),
PrimDef::FunUInt32 => fun("uint32", None),
PrimDef::FunUInt64 => fun("uint64", None),
PrimDef::FunFloat => fun("float", None),
PrimDef::FunNpNDArray => fun("np_ndarray", None),
PrimDef::FunNpEmpty => fun("np_empty", None),
PrimDef::FunNpZeros => fun("np_zeros", None),
@ -239,17 +200,26 @@ impl PrimDef {
PrimDef::FunNpArray => fun("np_array", None),
PrimDef::FunNpEye => fun("np_eye", None),
PrimDef::FunNpIdentity => fun("np_identity", None),
// Miscellaneous NumPy & SciPy functions
PrimDef::FunRound => fun("round", None),
PrimDef::FunRound64 => fun("round64", None),
PrimDef::FunNpRound => fun("np_round", None),
PrimDef::FunRangeInit => fun("range.__init__", Some("__init__")),
PrimDef::FunStr => fun("str", None),
PrimDef::FunBool => fun("bool", None),
PrimDef::FunFloor => fun("floor", None),
PrimDef::FunFloor64 => fun("floor64", None),
PrimDef::FunNpFloor => fun("np_floor", None),
PrimDef::FunCeil => fun("ceil", None),
PrimDef::FunCeil64 => fun("ceil64", None),
PrimDef::FunNpCeil => fun("np_ceil", None),
PrimDef::FunLen => fun("len", None),
PrimDef::FunMin => fun("min", None),
PrimDef::FunNpMin => fun("np_min", None),
PrimDef::FunNpMinimum => fun("np_minimum", None),
PrimDef::FunNpArgmin => fun("np_argmin", None),
PrimDef::FunMax => fun("max", None),
PrimDef::FunNpMax => fun("np_max", None),
PrimDef::FunNpMaximum => fun("np_maximum", None),
PrimDef::FunNpArgmax => fun("np_argmax", None),
PrimDef::FunAbs => fun("abs", None),
PrimDef::FunNpIsNan => fun("np_isnan", None),
PrimDef::FunNpIsInf => fun("np_isinf", None),
PrimDef::FunNpSin => fun("np_sin", None),
@ -287,40 +257,7 @@ impl PrimDef {
PrimDef::FunNpLdExp => fun("np_ldexp", None),
PrimDef::FunNpHypot => fun("np_hypot", None),
PrimDef::FunNpNextAfter => fun("np_nextafter", None),
PrimDef::FunNpTranspose => fun("np_transpose", None),
PrimDef::FunNpReshape => fun("np_reshape", None),
// Linalg functions
PrimDef::FunNpDot => fun("np_dot", None),
PrimDef::FunNpLinalgCholesky => fun("np_linalg_cholesky", None),
PrimDef::FunNpLinalgQr => fun("np_linalg_qr", None),
PrimDef::FunNpLinalgSvd => fun("np_linalg_svd", None),
PrimDef::FunNpLinalgInv => fun("np_linalg_inv", None),
PrimDef::FunNpLinalgPinv => fun("np_linalg_pinv", None),
PrimDef::FunNpLinalgMatrixPower => fun("np_linalg_matrix_power", None),
PrimDef::FunNpLinalgDet => fun("np_linalg_det", None),
PrimDef::FunSpLinalgLu => fun("sp_linalg_lu", None),
PrimDef::FunSpLinalgSchur => fun("sp_linalg_schur", None),
PrimDef::FunSpLinalgHessenberg => fun("sp_linalg_hessenberg", None),
// Miscellaneous Python & NAC3 functions
PrimDef::FunInt32 => fun("int32", None),
PrimDef::FunInt64 => fun("int64", None),
PrimDef::FunUInt32 => fun("uint32", None),
PrimDef::FunUInt64 => fun("uint64", None),
PrimDef::FunFloat => fun("float", None),
PrimDef::FunRound => fun("round", None),
PrimDef::FunRound64 => fun("round64", None),
PrimDef::FunStr => fun("str", None),
PrimDef::FunBool => fun("bool", None),
PrimDef::FunFloor => fun("floor", None),
PrimDef::FunFloor64 => fun("floor64", None),
PrimDef::FunCeil => fun("ceil", None),
PrimDef::FunCeil64 => fun("ceil64", None),
PrimDef::FunLen => fun("len", None),
PrimDef::FunMin => fun("min", None),
PrimDef::FunMax => fun("max", None),
PrimDef::FunAbs => fun("abs", None),
PrimDef::FunSome => fun("Some", None),
}
}
}
@ -389,9 +326,6 @@ impl TopLevelDef {
r
}
),
TopLevelDef::Variable { name, ty, .. } => {
format!("Variable {{ name: {name:?}, ty: {:?} }}", unifier.stringify(*ty),)
}
}
}
}
@ -474,9 +408,9 @@ impl TopLevelComposer {
let option = unifier.add_ty(TypeEnum::TObj {
obj_id: PrimDef::Option.id(),
fields: vec![
(PrimDef::FunOptionIsSome.simple_name().into(), (is_some_type_fun_ty, true)),
(PrimDef::FunOptionIsNone.simple_name().into(), (is_some_type_fun_ty, true)),
(PrimDef::FunOptionUnwrap.simple_name().into(), (unwrap_fun_ty, true)),
(PrimDef::OptionIsSome.simple_name().into(), (is_some_type_fun_ty, true)),
(PrimDef::OptionIsNone.simple_name().into(), (is_some_type_fun_ty, true)),
(PrimDef::OptionUnwrap.simple_name().into(), (unwrap_fun_ty, true)),
]
.into_iter()
.collect::<HashMap<_, _>>(),
@ -510,7 +444,6 @@ impl TopLevelComposer {
name: "value".into(),
ty: ndarray_dtype_tvar.ty,
default_value: None,
is_vararg: false,
}],
ret: none,
vars: into_var_map([ndarray_dtype_tvar, ndarray_ndims_tvar]),
@ -518,8 +451,8 @@ impl TopLevelComposer {
let ndarray = unifier.add_ty(TypeEnum::TObj {
obj_id: PrimDef::NDArray.id(),
fields: Mapping::from([
(PrimDef::FunNDArrayCopy.simple_name().into(), (ndarray_copy_fun_ty, true)),
(PrimDef::FunNDArrayFill.simple_name().into(), (ndarray_fill_fun_ty, true)),
(PrimDef::NDArrayCopy.simple_name().into(), (ndarray_copy_fun_ty, true)),
(PrimDef::NDArrayFill.simple_name().into(), (ndarray_fill_fun_ty, true)),
]),
params: into_var_map([ndarray_dtype_tvar, ndarray_ndims_tvar]),
});
@ -593,18 +526,6 @@ impl TopLevelComposer {
}
}
#[must_use]
pub fn make_top_level_variable_def(
name: String,
simple_name: StrRef,
ty: Type,
ty_decl: Option<Expr>,
resolver: Option<Arc<dyn SymbolResolver + Send + Sync>>,
loc: Option<Location>,
) -> TopLevelDef {
TopLevelDef::Variable { name, simple_name, ty, ty_decl, resolver, loc }
}
#[must_use]
pub fn make_class_method_name(mut class_name: String, method_name: &str) -> String {
class_name.push('.');
@ -750,16 +671,7 @@ impl TopLevelComposer {
)
}
/// This function returns the fields that have been initialized in the `__init__` function of a class
/// The function takes as input:
/// * `class_id`: The `object_id` of the class whose function is being evaluated (check `TopLevelDef::Class`)
/// * `definition_ast_list`: A list of ast definitions and statements defined in `TopLevelComposer`
/// * `stmts`: The body of function being parsed. Each statment is analyzed to check varaible initialization statements
pub fn get_all_assigned_field(
class_id: usize,
definition_ast_list: &Vec<DefAst>,
stmts: &[Stmt<()>],
) -> Result<HashSet<StrRef>, HashSet<String>> {
pub fn get_all_assigned_field(stmts: &[Stmt<()>]) -> Result<HashSet<StrRef>, HashSet<String>> {
let mut result = HashSet::new();
for s in stmts {
match &s.node {
@ -795,138 +707,30 @@ impl TopLevelComposer {
// TODO: do not check for For and While?
ast::StmtKind::For { body, orelse, .. }
| ast::StmtKind::While { body, orelse, .. } => {
result.extend(Self::get_all_assigned_field(
class_id,
definition_ast_list,
body.as_slice(),
)?);
result.extend(Self::get_all_assigned_field(
class_id,
definition_ast_list,
orelse.as_slice(),
)?);
result.extend(Self::get_all_assigned_field(body.as_slice())?);
result.extend(Self::get_all_assigned_field(orelse.as_slice())?);
}
ast::StmtKind::If { body, orelse, .. } => {
let inited_for_sure = Self::get_all_assigned_field(
class_id,
definition_ast_list,
body.as_slice(),
)?
.intersection(&Self::get_all_assigned_field(
class_id,
definition_ast_list,
orelse.as_slice(),
)?)
.copied()
.collect::<HashSet<_>>();
let inited_for_sure = Self::get_all_assigned_field(body.as_slice())?
.intersection(&Self::get_all_assigned_field(orelse.as_slice())?)
.copied()
.collect::<HashSet<_>>();
result.extend(inited_for_sure);
}
ast::StmtKind::Try { body, orelse, finalbody, .. } => {
let inited_for_sure = Self::get_all_assigned_field(
class_id,
definition_ast_list,
body.as_slice(),
)?
.intersection(&Self::get_all_assigned_field(
class_id,
definition_ast_list,
orelse.as_slice(),
)?)
.copied()
.collect::<HashSet<_>>();
let inited_for_sure = Self::get_all_assigned_field(body.as_slice())?
.intersection(&Self::get_all_assigned_field(orelse.as_slice())?)
.copied()
.collect::<HashSet<_>>();
result.extend(inited_for_sure);
result.extend(Self::get_all_assigned_field(
class_id,
definition_ast_list,
finalbody.as_slice(),
)?);
result.extend(Self::get_all_assigned_field(finalbody.as_slice())?);
}
ast::StmtKind::With { body, .. } => {
result.extend(Self::get_all_assigned_field(
class_id,
definition_ast_list,
body.as_slice(),
)?);
}
// Variables Initialized in function calls
ast::StmtKind::Expr { value, .. } => {
let ExprKind::Call { func, .. } = &value.node else {
continue;
};
let ExprKind::Attribute { value, attr, .. } = &func.node else {
continue;
};
let ExprKind::Name { id, .. } = &value.node else {
continue;
};
// Need to consider the two cases:
// Case 1) Call to class function i.e. id = `self`
// Case 2) Call to class ancestor function i.e. id = ancestor_name
// We leave checking whether function in case 2 belonged to class ancestor or not to type checker
//
// According to current handling of `self`, function definition are fixed and do not change regardless
// of which object is passed as `self` i.e. virtual polymorphism is not supported
// Therefore, we change class id for case 2 to reflect behavior of our compiler
let class_name = if *id == "self".into() {
let ast::StmtKind::ClassDef { name, .. } =
&definition_ast_list[class_id].1.as_ref().unwrap().node
else {
unreachable!()
};
name
} else {
id
};
let parent_method = definition_ast_list.iter().find_map(|def| {
let (
class_def,
Some(ast::Located {
node: ast::StmtKind::ClassDef { name, body, .. },
..
}),
) = &def
else {
return None;
};
let TopLevelDef::Class { object_id: class_id, .. } = &*class_def.read()
else {
unreachable!()
};
if name == class_name {
body.iter().find_map(|m| {
let ast::StmtKind::FunctionDef { name, body, .. } = &m.node else {
return None;
};
if *name == *attr {
return Some((body.clone(), class_id.0));
}
None
})
} else {
None
}
});
// If method body is none then method does not exist
if let Some((method_body, class_id)) = parent_method {
result.extend(Self::get_all_assigned_field(
class_id,
definition_ast_list,
method_body.as_slice(),
)?);
} else {
return Err(HashSet::from([format!(
"{}.{} not found in class {class_name} at {}",
*id, *attr, value.location
)]));
}
result.extend(Self::get_all_assigned_field(body.as_slice())?);
}
ast::StmtKind::Pass { .. }
| ast::StmtKind::Assert { .. }
| ast::StmtKind::AnnAssign { .. } => {}
| ast::StmtKind::Expr { .. } => {}
_ => {
unimplemented!()

View File

@ -6,36 +6,36 @@ use std::{
sync::Arc,
};
use inkwell::values::BasicValueEnum;
use itertools::Itertools;
use parking_lot::RwLock;
use nac3parser::ast::{self, Expr, Location, Stmt, StrRef};
use super::codegen::CodeGenContext;
use super::typecheck::type_inferencer::PrimitiveStore;
use super::typecheck::typedef::{
FunSignature, FuncArg, SharedUnifier, Type, TypeEnum, Unifier, VarMap,
};
use crate::{
codegen::{CodeGenContext, CodeGenerator},
codegen::CodeGenerator,
symbol_resolver::{SymbolResolver, ValueEnum},
typecheck::{
type_inferencer::{CodeLocation, PrimitiveStore},
typedef::{
CallId, FunSignature, FuncArg, SharedUnifier, Type, TypeEnum, TypeVarId, Unifier,
VarMap,
},
type_inferencer::CodeLocation,
typedef::{CallId, TypeVarId},
},
};
use composer::*;
use type_annotation::*;
use inkwell::values::BasicValueEnum;
use itertools::Itertools;
use nac3parser::ast::{self, Location, Stmt, StrRef};
use parking_lot::RwLock;
#[derive(PartialEq, Eq, PartialOrd, Ord, Clone, Copy, Hash, Debug)]
pub struct DefinitionId(pub usize);
pub mod builtins;
pub mod composer;
pub mod helper;
pub mod numpy;
pub mod type_annotation;
use composer::*;
use type_annotation::*;
#[cfg(test)]
mod test;
pub mod type_annotation;
#[derive(PartialEq, Eq, PartialOrd, Ord, Clone, Copy, Hash, Debug)]
pub struct DefinitionId(pub usize);
type GenCallCallback = dyn for<'ctx, 'a> Fn(
&mut CodeGenContext<'ctx, 'a>,
@ -130,14 +130,14 @@ pub enum TopLevelDef {
/// Function instance to symbol mapping
///
/// * Key: String representation of type variable values, sorted by variable ID in ascending
/// order, including type variables associated with the class.
/// order, including type variables associated with the class.
/// * Value: Function symbol name.
instance_to_symbol: HashMap<String, String>,
/// Function instances to annotated AST mapping
///
/// * Key: String representation of type variable values, sorted by variable ID in ascending
/// order, including type variables associated with the class. Excluding rigid type
/// variables.
/// order, including type variables associated with the class. Excluding rigid type
/// variables.
///
/// Rigid type variables that would be substituted when the function is instantiated.
instance_to_stmt: HashMap<String, FunInstance>,
@ -148,25 +148,6 @@ pub enum TopLevelDef {
/// Definition location.
loc: Option<Location>,
},
Variable {
/// Qualified name of the global variable, should be unique globally.
name: String,
/// Simple name, the same as in method/function definition.
simple_name: StrRef,
/// Type of the global variable.
ty: Type,
/// The declared type of the global variable, or [`None`] if no type annotation is provided.
ty_decl: Option<Expr>,
/// Symbol resolver of the module defined the class.
resolver: Option<Arc<dyn SymbolResolver + Send + Sync>>,
/// Definition location.
loc: Option<Location>,
},
}
pub struct TopLevelContext {

View File

@ -1,17 +1,18 @@
use itertools::Itertools;
use super::helper::PrimDef;
use crate::typecheck::{
type_inferencer::PrimitiveStore,
typedef::{Type, TypeEnum, TypeVarId, Unifier, VarMap},
use crate::{
toplevel::helper::PrimDef,
typecheck::{
type_inferencer::PrimitiveStore,
typedef::{Type, TypeEnum, TypeVarId, Unifier, VarMap},
},
};
use itertools::Itertools;
/// Creates a `ndarray` [`Type`] with the given type arguments.
///
/// * `dtype` - The element type of the `ndarray`, or [`None`] if the type variable is not
/// specialized.
/// specialized.
/// * `ndims` - The number of dimensions of the `ndarray`, or [`None`] if the type variable is not
/// specialized.
/// specialized.
pub fn make_ndarray_ty(
unifier: &mut Unifier,
primitives: &PrimitiveStore,
@ -24,9 +25,9 @@ pub fn make_ndarray_ty(
/// Substitutes type variables in `ndarray`.
///
/// * `dtype` - The element type of the `ndarray`, or [`None`] if the type variable is not
/// specialized.
/// specialized.
/// * `ndims` - The number of dimensions of the `ndarray`, or [`None`] if the type variable is not
/// specialized.
/// specialized.
pub fn subst_ndarray_tvars(
unifier: &mut Unifier,
ndarray: Type,

View File

@ -5,7 +5,7 @@ expression: res_vec
[
"Class {\nname: \"Generic_A\",\nancestors: [\"Generic_A[V]\", \"B\"],\nfields: [\"aa\", \"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"foo\", \"fn[[b:T], none]\"), (\"fun\", \"fn[[a:int32], V]\")],\ntype_vars: [\"V\"]\n}\n",
"Function {\nname: \"Generic_A.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"Generic_A.fun\",\nsig: \"fn[[a:int32], V]\",\nvar_id: [TypeVarId(241)]\n}\n",
"Function {\nname: \"Generic_A.fun\",\nsig: \"fn[[a:int32], V]\",\nvar_id: [TypeVarId(245)]\n}\n",
"Class {\nname: \"B\",\nancestors: [\"B\"],\nfields: [\"aa\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"foo\", \"fn[[b:T], none]\")],\ntype_vars: []\n}\n",
"Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"B.foo\",\nsig: \"fn[[b:T], none]\",\nvar_id: []\n}\n",

View File

@ -7,7 +7,7 @@ expression: res_vec
"Function {\nname: \"A.__init__\",\nsig: \"fn[[t:T], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"A.fun\",\nsig: \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\",\nvar_id: []\n}\n",
"Function {\nname: \"A.foo\",\nsig: \"fn[[c:C], none]\",\nvar_id: []\n}\n",
"Class {\nname: \"B\",\nancestors: [\"B[typevar230]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: [\"typevar230\"]\n}\n",
"Class {\nname: \"B\",\nancestors: [\"B[typevar234]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: [\"typevar234\"]\n}\n",
"Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"B.fun\",\nsig: \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\",\nvar_id: []\n}\n",
"Class {\nname: \"C\",\nancestors: [\"C\", \"B[bool]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\", \"e\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: []\n}\n",

View File

@ -5,8 +5,8 @@ expression: res_vec
[
"Function {\nname: \"foo\",\nsig: \"fn[[a:list[int32], b:tuple[T, float]], A[B, bool]]\",\nvar_id: []\n}\n",
"Class {\nname: \"A\",\nancestors: [\"A[T, V]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[v:V], none]\"), (\"fun\", \"fn[[a:T], V]\")],\ntype_vars: [\"T\", \"V\"]\n}\n",
"Function {\nname: \"A.__init__\",\nsig: \"fn[[v:V], none]\",\nvar_id: [TypeVarId(243)]\n}\n",
"Function {\nname: \"A.fun\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(248)]\n}\n",
"Function {\nname: \"A.__init__\",\nsig: \"fn[[v:V], none]\",\nvar_id: [TypeVarId(247)]\n}\n",
"Function {\nname: \"A.fun\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(252)]\n}\n",
"Function {\nname: \"gfun\",\nsig: \"fn[[a:A[list[float], int32]], none]\",\nvar_id: []\n}\n",
"Class {\nname: \"B\",\nancestors: [\"B\"],\nfields: [],\nmethods: [(\"__init__\", \"fn[[], none]\")],\ntype_vars: []\n}\n",
"Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",

View File

@ -3,7 +3,7 @@ source: nac3core/src/toplevel/test.rs
expression: res_vec
---
[
"Class {\nname: \"A\",\nancestors: [\"A[typevar229, typevar230]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[a:A[float, bool], b:B], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\")],\ntype_vars: [\"typevar229\", \"typevar230\"]\n}\n",
"Class {\nname: \"A\",\nancestors: [\"A[typevar233, typevar234]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[a:A[float, bool], b:B], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\")],\ntype_vars: [\"typevar233\", \"typevar234\"]\n}\n",
"Function {\nname: \"A.__init__\",\nsig: \"fn[[a:A[float, bool], b:B], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"A.fun\",\nsig: \"fn[[a:A[float, bool]], A[bool, int32]]\",\nvar_id: []\n}\n",
"Class {\nname: \"B\",\nancestors: [\"B\", \"A[int64, bool]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\"), (\"foo\", \"fn[[b:B], B]\"), (\"bar\", \"fn[[a:A[list[B], int32]], tuple[A[virtual[A[B, int32]], bool], B]]\")],\ntype_vars: []\n}\n",

View File

@ -6,12 +6,12 @@ expression: res_vec
"Class {\nname: \"A\",\nancestors: [\"A\"],\nfields: [\"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[b:B], none]\"), (\"foo\", \"fn[[a:T, b:V], none]\")],\ntype_vars: []\n}\n",
"Function {\nname: \"A.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"A.fun\",\nsig: \"fn[[b:B], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"A.foo\",\nsig: \"fn[[a:T, b:V], none]\",\nvar_id: [TypeVarId(249)]\n}\n",
"Function {\nname: \"A.foo\",\nsig: \"fn[[a:T, b:V], none]\",\nvar_id: [TypeVarId(253)]\n}\n",
"Class {\nname: \"B\",\nancestors: [\"B\", \"C\", \"A\"],\nfields: [\"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[b:B], none]\"), (\"foo\", \"fn[[a:T, b:V], none]\")],\ntype_vars: []\n}\n",
"Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
"Class {\nname: \"C\",\nancestors: [\"C\", \"A\"],\nfields: [\"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[b:B], none]\"), (\"foo\", \"fn[[a:T, b:V], none]\")],\ntype_vars: []\n}\n",
"Function {\nname: \"C.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"C.fun\",\nsig: \"fn[[b:B], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"foo\",\nsig: \"fn[[a:A], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"ff\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(257)]\n}\n",
"Function {\nname: \"ff\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(261)]\n}\n",
]

View File

@ -1,23 +1,21 @@
use std::{collections::HashMap, sync::Arc};
use indoc::indoc;
use parking_lot::Mutex;
use test_case::test_case;
use nac3parser::{
ast::{fold::Fold, FileName},
parser::parse_program,
};
use super::{helper::PrimDef, DefinitionId, *};
use super::*;
use crate::toplevel::helper::PrimDef;
use crate::typecheck::typedef::into_var_map;
use crate::{
codegen::CodeGenContext,
symbol_resolver::{SymbolResolver, ValueEnum},
toplevel::DefinitionId,
typecheck::{
type_inferencer::PrimitiveStore,
typedef::{into_var_map, Type, Unifier},
typedef::{Type, Unifier},
},
};
use indoc::indoc;
use nac3parser::ast::FileName;
use nac3parser::{ast::fold::Fold, parser::parse_program};
use parking_lot::Mutex;
use std::{collections::HashMap, sync::Arc};
use test_case::test_case;
struct ResolverInternal {
id_to_type: Mutex<HashMap<StrRef, Type>>,
@ -64,7 +62,6 @@ impl SymbolResolver for Resolver {
&self,
_: StrRef,
_: &mut CodeGenContext<'ctx, '_>,
_: &mut dyn CodeGenerator,
) -> Option<ValueEnum<'ctx>> {
unimplemented!()
}
@ -120,8 +117,7 @@ impl SymbolResolver for Resolver {
"register"
)]
fn test_simple_register(source: Vec<&str>) {
let mut composer =
TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 64).0;
let mut composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 64).0;
for s in source {
let ast = parse_program(s, FileName::default()).unwrap();
@ -141,8 +137,7 @@ fn test_simple_register(source: Vec<&str>) {
"register"
)]
fn test_simple_register_without_constructor(source: &str) {
let mut composer =
TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 64).0;
let mut composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 64).0;
let ast = parse_program(source, FileName::default()).unwrap();
let ast = ast[0].clone();
composer.register_top_level(ast, None, "", true).unwrap();
@ -176,8 +171,7 @@ fn test_simple_register_without_constructor(source: &str) {
"function compose"
)]
fn test_simple_function_analyze(source: &[&str], tys: &[&str], names: &[&str]) {
let mut composer =
TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 64).0;
let mut composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 64).0;
let internal_resolver = Arc::new(ResolverInternal {
id_to_def: Mutex::default(),
@ -525,8 +519,7 @@ fn test_simple_function_analyze(source: &[&str], tys: &[&str], names: &[&str]) {
)]
fn test_analyze(source: &[&str], res: &[&str]) {
let print = false;
let mut composer =
TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 64).0;
let mut composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 64).0;
let internal_resolver = make_internal_resolver_with_tvar(
vec![
@ -703,8 +696,7 @@ fn test_analyze(source: &[&str], res: &[&str]) {
)]
fn test_inference(source: Vec<&str>, res: &[&str]) {
let print = true;
let mut composer =
TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 64).0;
let mut composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 64).0;
let internal_resolver = make_internal_resolver_with_tvar(
vec![

View File

@ -1,13 +1,9 @@
use strum::IntoEnumIterator;
use super::*;
use crate::symbol_resolver::SymbolValue;
use crate::toplevel::helper::PrimDef;
use crate::typecheck::typedef::VarMap;
use nac3parser::ast::Constant;
use super::{
helper::{PrimDef, PrimDefDetails},
*,
};
use crate::{symbol_resolver::SymbolValue, typecheck::typedef::VarMap};
#[derive(Clone, Debug)]
pub enum TypeAnnotation {
Primitive(Type),
@ -67,9 +63,9 @@ impl TypeAnnotation {
/// Parses an AST expression `expr` into a [`TypeAnnotation`].
///
/// * `locked` - A [`HashMap`] containing the IDs of known definitions, mapped to a [`Vec`] of all
/// generic variables associated with the definition.
/// generic variables associated with the definition.
/// * `type_var` - The type variable associated with the type argument currently being parsed. Pass
/// [`None`] when this function is invoked externally.
/// [`None`] when this function is invoked externally.
pub fn parse_ast_to_type_annotation_kinds<T, S: std::hash::BuildHasher + Clone>(
resolver: &(dyn SymbolResolver + Send + Sync),
top_level_defs: &[Arc<RwLock<TopLevelDef>>],
@ -361,7 +357,6 @@ pub fn parse_ast_to_type_annotation_kinds<T, S: std::hash::BuildHasher + Clone>(
pub fn get_type_from_type_annotation_kinds(
top_level_defs: &[Arc<RwLock<TopLevelDef>>],
unifier: &mut Unifier,
primitives: &PrimitiveStore,
ann: &TypeAnnotation,
subst_list: &mut Option<Vec<Type>>,
) -> Result<Type, HashSet<String>> {
@ -384,141 +379,100 @@ pub fn get_type_from_type_annotation_kinds(
let param_ty = params
.iter()
.map(|x| {
get_type_from_type_annotation_kinds(
top_level_defs,
unifier,
primitives,
x,
subst_list,
)
get_type_from_type_annotation_kinds(top_level_defs, unifier, x, subst_list)
})
.collect::<Result<Vec<_>, _>>()?;
let ty = if let Some(prim_def) = PrimDef::iter().find(|prim| prim.id() == *obj_id) {
// Primitive TopLevelDefs do not contain all fields that are present in their Type
// counterparts, so directly perform subst on the Type instead.
let PrimDefDetails::PrimClass { get_ty_fn, .. } = prim_def.details() else {
unreachable!()
};
let base_ty = get_ty_fn(primitives);
let params =
if let TypeEnum::TObj { params, .. } = &*unifier.get_ty_immutable(base_ty) {
params.clone()
} else {
unreachable!()
};
unifier
.subst(
get_ty_fn(primitives),
&params
.iter()
.zip(param_ty)
.map(|(obj_tv, param)| (*obj_tv.0, param))
.collect(),
)
.unwrap_or(base_ty)
} else {
let subst = {
// check for compatible range
// TODO: if allow type var to be applied(now this disallowed in the parse_to_type_annotation), need more check
let mut result = VarMap::new();
for (tvar, p) in type_vars.iter().zip(param_ty) {
match unifier.get_ty(*tvar).as_ref() {
TypeEnum::TVar {
id,
range,
fields: None,
name,
loc,
is_const_generic: false,
} => {
let ok: bool = {
// create a temp type var and unify to check compatibility
p == *tvar || {
let temp = unifier.get_fresh_var_with_range(
range.as_slice(),
*name,
*loc,
);
unifier.unify(temp.ty, p).is_ok()
}
};
if ok {
result.insert(*id, p);
} else {
return Err(HashSet::from([format!(
"cannot apply type {} to type variable with id {:?}",
unifier.internal_stringify(
p,
&mut |id| format!("class{id}"),
&mut |id| format!("typevar{id}"),
&mut None
),
*id
)]));
let subst = {
// check for compatible range
// TODO: if allow type var to be applied(now this disallowed in the parse_to_type_annotation), need more check
let mut result = VarMap::new();
for (tvar, p) in type_vars.iter().zip(param_ty) {
match unifier.get_ty(*tvar).as_ref() {
TypeEnum::TVar {
id,
range,
fields: None,
name,
loc,
is_const_generic: false,
} => {
let ok: bool = {
// create a temp type var and unify to check compatibility
p == *tvar || {
let temp = unifier.get_fresh_var_with_range(
range.as_slice(),
*name,
*loc,
);
unifier.unify(temp.ty, p).is_ok()
}
};
if ok {
result.insert(*id, p);
} else {
return Err(HashSet::from([format!(
"cannot apply type {} to type variable with id {:?}",
unifier.internal_stringify(
p,
&mut |id| format!("class{id}"),
&mut |id| format!("typevar{id}"),
&mut None
),
*id
)]));
}
TypeEnum::TVar {
id, range, name, loc, is_const_generic: true, ..
} => {
let ty = range[0];
let ok: bool = {
// create a temp type var and unify to check compatibility
p == *tvar || {
let temp =
unifier.get_fresh_const_generic_var(ty, *name, *loc);
unifier.unify(temp.ty, p).is_ok()
}
};
if ok {
result.insert(*id, p);
} else {
return Err(HashSet::from([format!(
"cannot apply type {} to type variable {}",
unifier.stringify(p),
name.unwrap_or_else(|| format!("typevar{id}").into()),
)]));
}
}
_ => unreachable!("must be generic type var"),
}
}
result
};
// Class Attributes keep a copy with Class Definition and are not added to objects
let mut tobj_fields = methods
.iter()
.map(|(name, ty, _)| {
let subst_ty = unifier.subst(*ty, &subst).unwrap_or(*ty);
// methods are immutable
(*name, (subst_ty, false))
})
.collect::<HashMap<_, _>>();
tobj_fields.extend(fields.iter().map(|(name, ty, mutability)| {
let subst_ty = unifier.subst(*ty, &subst).unwrap_or(*ty);
(*name, (subst_ty, *mutability))
}));
let need_subst = !subst.is_empty();
let ty = unifier.add_ty(TypeEnum::TObj {
obj_id: *obj_id,
fields: tobj_fields,
params: subst,
});
if need_subst {
if let Some(wl) = subst_list.as_mut() {
wl.push(ty);
TypeEnum::TVar { id, range, name, loc, is_const_generic: true, .. } => {
let ty = range[0];
let ok: bool = {
// create a temp type var and unify to check compatibility
p == *tvar || {
let temp = unifier.get_fresh_const_generic_var(ty, *name, *loc);
unifier.unify(temp.ty, p).is_ok()
}
};
if ok {
result.insert(*id, p);
} else {
return Err(HashSet::from([format!(
"cannot apply type {} to type variable {}",
unifier.stringify(p),
name.unwrap_or_else(|| format!("typevar{id}").into()),
)]));
}
}
_ => unreachable!("must be generic type var"),
}
}
ty
result
};
// Class Attributes keep a copy with Class Definition and are not added to objects
let mut tobj_fields = methods
.iter()
.map(|(name, ty, _)| {
let subst_ty = unifier.subst(*ty, &subst).unwrap_or(*ty);
// methods are immutable
(*name, (subst_ty, false))
})
.collect::<HashMap<_, _>>();
tobj_fields.extend(fields.iter().map(|(name, ty, mutability)| {
let subst_ty = unifier.subst(*ty, &subst).unwrap_or(*ty);
(*name, (subst_ty, *mutability))
}));
let need_subst = !subst.is_empty();
let ty = unifier.add_ty(TypeEnum::TObj {
obj_id: *obj_id,
fields: tobj_fields,
params: subst,
});
if need_subst {
if let Some(wl) = subst_list.as_mut() {
wl.push(ty);
}
}
Ok(ty)
}
TypeAnnotation::Primitive(ty) | TypeAnnotation::TypeVar(ty) => Ok(*ty),
@ -536,7 +490,6 @@ pub fn get_type_from_type_annotation_kinds(
let ty = get_type_from_type_annotation_kinds(
top_level_defs,
unifier,
primitives,
ty.as_ref(),
subst_list,
)?;
@ -546,16 +499,10 @@ pub fn get_type_from_type_annotation_kinds(
let tys = tys
.iter()
.map(|x| {
get_type_from_type_annotation_kinds(
top_level_defs,
unifier,
primitives,
x,
subst_list,
)
get_type_from_type_annotation_kinds(top_level_defs, unifier, x, subst_list)
})
.collect::<Result<Vec<_>, _>>()?;
Ok(unifier.add_ty(TypeEnum::TTuple { ty: tys, is_vararg_ctx: false }))
Ok(unifier.add_ty(TypeEnum::TTuple { ty: tys }))
}
}
}

View File

@ -1,19 +1,13 @@
use std::{
collections::{HashMap, HashSet},
iter::once,
};
use crate::toplevel::helper::PrimDef;
use super::type_inferencer::Inferencer;
use super::typedef::{Type, TypeEnum};
use nac3parser::ast::{
self, Constant, Expr, ExprKind,
Operator::{LShift, RShift},
Stmt, StmtKind, StrRef,
};
use super::{
type_inferencer::{DeclarationSource, IdentifierInfo, Inferencer},
typedef::{Type, TypeEnum},
};
use crate::toplevel::helper::PrimDef;
use std::{collections::HashSet, iter::once};
impl<'a> Inferencer<'a> {
fn should_have_value(&mut self, expr: &Expr<Option<Type>>) -> Result<(), HashSet<String>> {
@ -27,45 +21,26 @@ impl<'a> Inferencer<'a> {
fn check_pattern(
&mut self,
pattern: &Expr<Option<Type>>,
defined_identifiers: &mut HashMap<StrRef, IdentifierInfo>,
defined_identifiers: &mut HashSet<StrRef>,
) -> Result<(), HashSet<String>> {
match &pattern.node {
ExprKind::Name { id, .. } if id == &"none".into() => {
Err(HashSet::from([format!("cannot assign to a `none` (at {})", pattern.location)]))
}
ExprKind::Name { id, .. } => {
// If `id` refers to a declared symbol, reject this assignment if it is used in the
// context of an (implicit) global variable
if let Some(id_info) = defined_identifiers.get(id) {
if matches!(
id_info.source,
DeclarationSource::Global { is_explicit: Some(false) }
) {
return Err(HashSet::from([format!(
"cannot access local variable '{id}' before it is declared (at {})",
pattern.location
)]));
}
}
if !defined_identifiers.contains_key(id) {
defined_identifiers.insert(*id, IdentifierInfo::default());
if !defined_identifiers.contains(id) {
defined_identifiers.insert(*id);
}
self.should_have_value(pattern)?;
Ok(())
}
ExprKind::List { elts, .. } | ExprKind::Tuple { elts, .. } => {
ExprKind::Tuple { elts, .. } => {
for elt in elts {
self.check_pattern(elt, defined_identifiers)?;
self.should_have_value(elt)?;
}
Ok(())
}
ExprKind::Starred { value, .. } => {
self.check_pattern(value, defined_identifiers)?;
self.should_have_value(value)?;
Ok(())
}
ExprKind::Subscript { value, slice, .. } => {
self.check_expr(value, defined_identifiers)?;
self.should_have_value(value)?;
@ -89,7 +64,7 @@ impl<'a> Inferencer<'a> {
fn check_expr(
&mut self,
expr: &Expr<Option<Type>>,
defined_identifiers: &mut HashMap<StrRef, IdentifierInfo>,
defined_identifiers: &mut HashSet<StrRef>,
) -> Result<(), HashSet<String>> {
// there are some cases where the custom field is None
if let Some(ty) = &expr.custom {
@ -110,7 +85,7 @@ impl<'a> Inferencer<'a> {
return Ok(());
}
self.should_have_value(expr)?;
if !defined_identifiers.contains_key(id) {
if !defined_identifiers.contains(id) {
match self.function_data.resolver.get_symbol_type(
self.unifier,
&self.top_level.definitions.read(),
@ -118,22 +93,7 @@ impl<'a> Inferencer<'a> {
*id,
) {
Ok(_) => {
let is_global = self.is_id_global(*id);
defined_identifiers.insert(
*id,
IdentifierInfo {
source: match is_global {
Some(true) => {
DeclarationSource::Global { is_explicit: Some(false) }
}
Some(false) => {
DeclarationSource::Global { is_explicit: None }
}
None => DeclarationSource::Local,
},
},
);
self.defined_identifiers.insert(*id);
}
Err(e) => {
return Err(HashSet::from([format!(
@ -206,7 +166,9 @@ impl<'a> Inferencer<'a> {
let mut defined_identifiers = defined_identifiers.clone();
for arg in &args.args {
// TODO: should we check the types here?
defined_identifiers.entry(arg.node.arg).or_default();
if !defined_identifiers.contains(&arg.node.arg) {
defined_identifiers.insert(arg.node.arg);
}
}
self.check_expr(body, &mut defined_identifiers)?;
}
@ -245,23 +207,19 @@ impl<'a> Inferencer<'a> {
/// This is a workaround preventing the caller from using a variable `alloca`-ed in the body, which
/// is freed when the function returns.
fn check_return_value_ty(&mut self, ret_ty: Type) -> bool {
if cfg!(feature = "no-escape-analysis") {
true
} else {
match &*self.unifier.get_ty_immutable(ret_ty) {
TypeEnum::TObj { .. } => [
self.primitives.int32,
self.primitives.int64,
self.primitives.uint32,
self.primitives.uint64,
self.primitives.float,
self.primitives.bool,
]
.iter()
.any(|allowed_ty| self.unifier.unioned(ret_ty, *allowed_ty)),
TypeEnum::TTuple { ty, .. } => ty.iter().all(|t| self.check_return_value_ty(*t)),
_ => false,
}
match &*self.unifier.get_ty_immutable(ret_ty) {
TypeEnum::TObj { .. } => [
self.primitives.int32,
self.primitives.int64,
self.primitives.uint32,
self.primitives.uint64,
self.primitives.float,
self.primitives.bool,
]
.iter()
.any(|allowed_ty| self.unifier.unioned(ret_ty, *allowed_ty)),
TypeEnum::TTuple { ty } => ty.iter().all(|t| self.check_return_value_ty(*t)),
_ => false,
}
}
@ -269,7 +227,7 @@ impl<'a> Inferencer<'a> {
fn check_stmt(
&mut self,
stmt: &Stmt<Option<Type>>,
defined_identifiers: &mut HashMap<StrRef, IdentifierInfo>,
defined_identifiers: &mut HashSet<StrRef>,
) -> Result<bool, HashSet<String>> {
match &stmt.node {
StmtKind::For { target, iter, body, orelse, .. } => {
@ -295,11 +253,9 @@ impl<'a> Inferencer<'a> {
let body_returned = self.check_block(body, &mut body_identifiers)?;
let orelse_returned = self.check_block(orelse, &mut orelse_identifiers)?;
for ident in body_identifiers.keys() {
if !defined_identifiers.contains_key(ident)
&& orelse_identifiers.contains_key(ident)
{
defined_identifiers.insert(*ident, IdentifierInfo::default());
for ident in &body_identifiers {
if !defined_identifiers.contains(ident) && orelse_identifiers.contains(ident) {
defined_identifiers.insert(*ident);
}
}
Ok(body_returned && orelse_returned)
@ -330,7 +286,7 @@ impl<'a> Inferencer<'a> {
let mut defined_identifiers = defined_identifiers.clone();
let ast::ExcepthandlerKind::ExceptHandler { name, body, .. } = &handler.node;
if let Some(name) = name {
defined_identifiers.insert(*name, IdentifierInfo::default());
defined_identifiers.insert(*name);
}
self.check_block(body, &mut defined_identifiers)?;
}
@ -394,44 +350,6 @@ impl<'a> Inferencer<'a> {
}
Ok(true)
}
StmtKind::Global { names, .. } => {
for id in names {
if let Some(id_info) = defined_identifiers.get(id) {
if id_info.source == DeclarationSource::Local {
return Err(HashSet::from([format!(
"name '{id}' is referenced prior to global declaration at {}",
stmt.location,
)]));
}
continue;
}
match self.function_data.resolver.get_symbol_type(
self.unifier,
&self.top_level.definitions.read(),
self.primitives,
*id,
) {
Ok(_) => {
defined_identifiers.insert(
*id,
IdentifierInfo {
source: DeclarationSource::Global { is_explicit: Some(true) },
},
);
}
Err(e) => {
return Err(HashSet::from([format!(
"type error at identifier `{}` ({}) at {}",
id, e, stmt.location
)]))
}
}
}
Ok(false)
}
// break, raise, etc.
_ => Ok(false),
}
@ -440,7 +358,7 @@ impl<'a> Inferencer<'a> {
pub fn check_block(
&mut self,
block: &[Stmt<Option<Type>>],
defined_identifiers: &mut HashMap<StrRef, IdentifierInfo>,
defined_identifiers: &mut HashSet<StrRef>,
) -> Result<bool, HashSet<String>> {
let mut ret = false;
for stmt in block {

View File

@ -1,21 +1,17 @@
use std::{cmp::max, collections::HashMap, rc::Rc};
use itertools::{iproduct, Itertools};
use strum::IntoEnumIterator;
use nac3parser::ast::{Cmpop, Operator, StrRef, Unaryop};
use super::{
use crate::symbol_resolver::SymbolValue;
use crate::toplevel::helper::PrimDef;
use crate::toplevel::numpy::{make_ndarray_ty, unpack_ndarray_var_tys};
use crate::typecheck::{
type_inferencer::*,
typedef::{FunSignature, FuncArg, Type, TypeEnum, Unifier, VarMap},
};
use crate::{
symbol_resolver::SymbolValue,
toplevel::{
helper::PrimDef,
numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
},
};
use itertools::{iproduct, Itertools};
use nac3parser::ast::StrRef;
use nac3parser::ast::{Cmpop, Operator, Unaryop};
use std::cmp::max;
use std::collections::HashMap;
use std::rc::Rc;
use strum::IntoEnumIterator;
/// The variant of a binary operator.
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
@ -201,7 +197,6 @@ pub fn impl_binop(
ty: other_ty,
default_value: None,
name: "other".into(),
is_vararg: false,
}],
})),
false,
@ -266,7 +261,6 @@ pub fn impl_cmpop(
ty: other_ty,
default_value: None,
name: "other".into(),
is_vararg: false,
}],
})),
false,
@ -524,23 +518,6 @@ pub fn typeof_binop(
}
Operator::MatMult => {
// NOTE: NumPy matmul's LHS and RHS must both be ndarrays. Scalars are not allowed.
match (&*unifier.get_ty(lhs), &*unifier.get_ty(rhs)) {
(
TypeEnum::TObj { obj_id: lhs_obj_id, .. },
TypeEnum::TObj { obj_id: rhs_obj_id, .. },
) if *lhs_obj_id == primitives.ndarray.obj_id(unifier).unwrap()
&& *rhs_obj_id == primitives.ndarray.obj_id(unifier).unwrap() =>
{
// LHS and RHS have valid types
}
_ => {
let lhs_str = unifier.stringify(lhs);
let rhs_str = unifier.stringify(rhs);
return Err(format!("ndarray.__matmul__ only accepts ndarray operands, but left operand has type {lhs_str}, and right operand has type {rhs_str}"));
}
}
let (_, lhs_ndims) = unpack_ndarray_var_tys(unifier, lhs);
let lhs_ndims = match &*unifier.get_ty_immutable(lhs_ndims) {
TypeEnum::TLiteral { values, .. } => {
@ -701,7 +678,6 @@ pub fn set_primitives_magic_methods(store: &PrimitiveStore, unifier: &mut Unifie
bool: bool_t,
uint32: uint32_t,
uint64: uint64_t,
str: str_t,
list: list_t,
ndarray: ndarray_t,
..
@ -747,9 +723,6 @@ pub fn set_primitives_magic_methods(store: &PrimitiveStore, unifier: &mut Unifie
impl_sign(unifier, store, bool_t, Some(int32_t));
impl_eq(unifier, store, bool_t, &[bool_t, ndarray_bool_t], None);
/* str ========= */
impl_cmpop(unifier, store, str_t, &[str_t], &[Cmpop::Eq, Cmpop::NotEq], Some(bool_t));
/* list ======== */
impl_binop(unifier, store, list_t, &[list_t], Some(list_t), &[Operator::Add]);
impl_binop(unifier, store, list_t, &[int32_t, int64_t], Some(list_t), &[Operator::Mult]);

View File

@ -1,13 +1,14 @@
use std::{collections::HashMap, fmt::Display};
use std::collections::HashMap;
use std::fmt::Display;
use itertools::Itertools;
use nac3parser::ast::{Cmpop, Location, StrRef};
use crate::typecheck::{magic_methods::HasOpInfo, typedef::TypeEnum};
use super::{
magic_methods::{Binop, HasOpInfo},
typedef::{RecordKey, Type, TypeEnum, Unifier},
magic_methods::Binop,
typedef::{RecordKey, Type, Unifier},
};
use itertools::Itertools;
use nac3parser::ast::{Cmpop, Location, StrRef};
#[derive(Debug, Clone)]
pub enum TypeErrorKind {
@ -182,10 +183,9 @@ impl<'a> Display for DisplayTypeError<'a> {
}
result
}
(
TypeEnum::TTuple { ty: ty1, is_vararg_ctx: is_vararg1 },
TypeEnum::TTuple { ty: ty2, is_vararg_ctx: is_vararg2 },
) if !is_vararg1 && !is_vararg2 && ty1.len() != ty2.len() => {
(TypeEnum::TTuple { ty: ty1 }, TypeEnum::TTuple { ty: ty2 })
if ty1.len() != ty2.len() =>
{
let t1 = self.unifier.stringify_with_notes(*t1, &mut notes);
let t2 = self.unifier.stringify_with_notes(*t2, &mut notes);
write!(f, "Tuple length mismatch: got {t1} and {t2}")

File diff suppressed because it is too large Load Diff

View File

@ -1,19 +1,17 @@
use std::iter::zip;
use indexmap::IndexMap;
use indoc::indoc;
use parking_lot::RwLock;
use test_case::test_case;
use nac3parser::{ast::FileName, parser::parse_program};
use super::super::{magic_methods::with_fields, typedef::*};
use super::*;
use crate::{
codegen::{CodeGenContext, CodeGenerator},
codegen::CodeGenContext,
symbol_resolver::ValueEnum,
toplevel::{helper::PrimDef, DefinitionId, TopLevelDef},
typecheck::{magic_methods::with_fields, typedef::*},
};
use indexmap::IndexMap;
use indoc::indoc;
use nac3parser::ast::FileName;
use nac3parser::parser::parse_program;
use parking_lot::RwLock;
use std::iter::zip;
use test_case::test_case;
struct Resolver {
id_to_type: HashMap<StrRef, Type>,
@ -43,7 +41,6 @@ impl SymbolResolver for Resolver {
&self,
_: StrRef,
_: &mut CodeGenContext<'ctx, '_>,
_: &mut dyn CodeGenerator,
) -> Option<ValueEnum<'ctx>> {
unimplemented!()
}
@ -86,12 +83,7 @@ impl TestEnvironment {
});
with_fields(&mut unifier, int32, |unifier, fields| {
let add_ty = unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![FuncArg {
name: "other".into(),
ty: int32,
default_value: None,
is_vararg: false,
}],
args: vec![FuncArg { name: "other".into(), ty: int32, default_value: None }],
ret: int32,
vars: VarMap::new(),
}));
@ -232,12 +224,7 @@ impl TestEnvironment {
});
with_fields(&mut unifier, int32, |unifier, fields| {
let add_ty = unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![FuncArg {
name: "other".into(),
ty: int32,
default_value: None,
is_vararg: false,
}],
args: vec![FuncArg { name: "other".into(), ty: int32, default_value: None }],
ret: int32,
vars: VarMap::new(),
}));
@ -520,7 +507,7 @@ impl TestEnvironment {
primitives: &mut self.primitives,
virtual_checks: &mut self.virtual_checks,
calls: &mut self.calls,
defined_identifiers: HashMap::default(),
defined_identifiers: HashSet::default(),
in_handler: false,
}
}
@ -596,9 +583,8 @@ fn test_basic(source: &str, mapping: &HashMap<&str, &str>, virtuals: &[(&str, &s
println!("source:\n{source}");
let mut env = TestEnvironment::new();
let id_to_name = std::mem::take(&mut env.id_to_name);
let mut defined_identifiers: HashMap<_, _> =
env.identifier_mapping.keys().copied().map(|id| (id, IdentifierInfo::default())).collect();
defined_identifiers.insert("virtual".into(), IdentifierInfo::default());
let mut defined_identifiers: HashSet<_> = env.identifier_mapping.keys().copied().collect();
defined_identifiers.insert("virtual".into());
let mut inferencer = env.get_inferencer();
inferencer.defined_identifiers.clone_from(&defined_identifiers);
let statements = parse_program(source, FileName::default()).unwrap();
@ -743,9 +729,8 @@ fn test_primitive_magic_methods(source: &str, mapping: &HashMap<&str, &str>) {
println!("source:\n{source}");
let mut env = TestEnvironment::basic_test_env();
let id_to_name = std::mem::take(&mut env.id_to_name);
let mut defined_identifiers: HashMap<_, _> =
env.identifier_mapping.keys().copied().map(|id| (id, IdentifierInfo::default())).collect();
defined_identifiers.insert("virtual".into(), IdentifierInfo::default());
let mut defined_identifiers: HashSet<_> = env.identifier_mapping.keys().copied().collect();
defined_identifiers.insert("virtual".into());
let mut inferencer = env.get_inferencer();
inferencer.defined_identifiers.clone_from(&defined_identifiers);
let statements = parse_program(source, FileName::default()).unwrap();

View File

@ -1,28 +1,23 @@
use std::{
borrow::Cow,
cell::RefCell,
collections::{HashMap, HashSet},
fmt::{self, Display},
iter::{repeat, zip},
rc::Rc,
sync::{Arc, Mutex},
};
use indexmap::IndexMap;
use itertools::{repeat_n, Itertools};
use itertools::Itertools;
use std::cell::RefCell;
use std::collections::HashMap;
use std::fmt::{self, Display};
use std::iter::zip;
use std::rc::Rc;
use std::sync::{Arc, Mutex};
use std::{borrow::Cow, collections::HashSet};
use nac3parser::ast::{Cmpop, Location, StrRef, Unaryop};
use super::{
magic_methods::{Binop, HasOpInfo, OpInfo},
type_error::{TypeError, TypeErrorKind},
type_inferencer::PrimitiveStore,
unification_table::{UnificationKey, UnificationTable},
};
use crate::{
symbol_resolver::SymbolValue,
toplevel::{helper::PrimDef, DefinitionId, TopLevelContext, TopLevelDef},
};
use super::magic_methods::Binop;
use super::type_error::{TypeError, TypeErrorKind};
use super::unification_table::{UnificationKey, UnificationTable};
use crate::symbol_resolver::SymbolValue;
use crate::toplevel::helper::PrimDef;
use crate::toplevel::{DefinitionId, TopLevelContext, TopLevelDef};
use crate::typecheck::magic_methods::OpInfo;
use crate::typecheck::type_inferencer::PrimitiveStore;
#[cfg(test)]
mod test;
@ -120,7 +115,6 @@ pub struct FuncArg {
pub name: StrRef,
pub ty: Type,
pub default_value: Option<SymbolValue>,
pub is_vararg: bool,
}
impl FuncArg {
@ -239,12 +233,6 @@ pub enum TypeEnum {
TTuple {
/// The types of elements present in this tuple.
ty: Vec<Type>,
/// Whether this tuple is used in a vararg context.
///
/// If `true`, `ty` must only contain one type, and the tuple is assumed to contain any
/// number of `ty`-typed values.
is_vararg_ctx: bool,
},
/// An object type.
@ -539,7 +527,7 @@ impl Unifier {
TypeEnum::TVirtual { ty } => self.get_instantiations(*ty).map(|ty| {
ty.iter().map(|&ty| self.add_ty(TypeEnum::TVirtual { ty })).collect_vec()
}),
TypeEnum::TTuple { ty, is_vararg_ctx } => {
TypeEnum::TTuple { ty } => {
let tuples = ty
.iter()
.map(|ty| self.get_instantiations(*ty).unwrap_or_else(|| vec![*ty]))
@ -549,12 +537,7 @@ impl Unifier {
None
} else {
Some(
tuples
.into_iter()
.map(|ty| {
self.add_ty(TypeEnum::TTuple { ty, is_vararg_ctx: *is_vararg_ctx })
})
.collect(),
tuples.into_iter().map(|ty| self.add_ty(TypeEnum::TTuple { ty })).collect(),
)
}
}
@ -598,7 +581,7 @@ impl Unifier {
TVar { .. } => allowed_typevars.iter().any(|b| self.unification_table.unioned(a, *b)),
TCall { .. } => false,
TVirtual { ty } => self.is_concrete(*ty, allowed_typevars),
TTuple { ty, .. } => ty.iter().all(|ty| self.is_concrete(*ty, allowed_typevars)),
TTuple { ty } => ty.iter().all(|ty| self.is_concrete(*ty, allowed_typevars)),
TObj { params: vars, .. } => {
vars.values().all(|ty| self.is_concrete(*ty, allowed_typevars))
}
@ -666,7 +649,6 @@ impl Unifier {
// Get details about the function signature/parameters.
let num_params = signature.args.len();
let is_vararg = signature.args.iter().any(|arg| arg.is_vararg);
// Force the type vars in `b` and `signature' to be up-to-date.
let b = self.instantiate_fun(b, signature);
@ -677,8 +659,8 @@ impl Unifier {
let num_args = posargs.len() + kwargs.len();
// Now we check the arguments against the parameters,
// and depending on what `call_info` is, we might change how `unify_call()` behaves
// to improve user error messages when type checking fails.
// and depending on what `call_info` is, we might change how the behavior `unify_call()`
// in hopes to improve user error messages when type checking fails.
match operator_info {
Some(OperatorInfo::IsBinaryOp { self_type, operator }) => {
// The call is written in the form of (say) `a + b`.
@ -755,7 +737,7 @@ impl Unifier {
};
// Check for "too many arguments"
if !is_vararg && num_params < posargs.len() {
if num_params < posargs.len() {
let expected_min_count =
signature.args.iter().filter(|param| param.is_required()).count();
let expected_max_count = num_params;
@ -788,19 +770,6 @@ impl Unifier {
type_check_arg(param.name, param.ty, arg_ty)?;
}
if is_vararg {
debug_assert!(!signature.args.is_empty());
let vararg_args = posargs.iter().skip(signature.args.len());
let vararg_param = signature.args.last().unwrap();
for (&arg_ty, param) in zip(vararg_args, repeat(vararg_param)) {
// `param_info` for this argument would've already been marked as supplied
// during non-vararg posarg typecheck
type_check_arg(param.name, param.ty, arg_ty)?;
}
}
// Now consume all keyword arguments and typecheck them.
for (&param_name, &arg_ty) in kwargs {
// We will also use this opportunity to check if this keyword argument is "legal".
@ -990,10 +959,7 @@ impl Unifier {
self.unify_impl(x, b, false)?;
self.set_a_to_b(a, x);
}
(
TVar { fields: Some(fields), range, is_const_generic: false, .. },
TTuple { ty, .. },
) => {
(TVar { fields: Some(fields), range, is_const_generic: false, .. }, TTuple { ty }) => {
let len = i32::try_from(ty.len()).unwrap();
for (k, v) in fields {
match *k {
@ -1014,18 +980,8 @@ impl Unifier {
self.unify_impl(v.ty, ty[ind as usize], false)
.map_err(|e| e.at(v.loc))?;
}
RecordKey::Str(s) => {
let tuple_fns = [
Cmpop::Eq.op_info().method_name,
Cmpop::NotEq.op_info().method_name,
];
if !tuple_fns.into_iter().any(|op| s.to_string() == op) {
return Err(TypeError::new(
TypeErrorKind::NoSuchField(*k, b),
v.loc,
));
}
RecordKey::Str(_) => {
return Err(TypeError::new(TypeErrorKind::NoSuchField(*k, b), v.loc))
}
}
}
@ -1100,47 +1056,15 @@ impl Unifier {
self.set_a_to_b(a, b);
}
(
TTuple { ty: ty1, is_vararg_ctx: is_vararg1 },
TTuple { ty: ty2, is_vararg_ctx: is_vararg2 },
) => {
// Rules for Tuples:
// - ty1: is_vararg && ty2: is_vararg -> ty1[0] == ty2[0]
// - ty1: is_vararg && ty2: !is_vararg -> type error (not enough info to infer the correct number of arguments)
// - ty1: !is_vararg && ty2: is_vararg -> ty1[..] == ty2[0]
// - ty1: !is_vararg && ty2: !is_vararg -> ty1.len() == ty2.len() && ty1[i] == ty2[i]
debug_assert!(!is_vararg1 || ty1.len() == 1);
debug_assert!(!is_vararg2 || ty2.len() == 1);
match (*is_vararg1, *is_vararg2) {
(true, true) => {
if self.unify_impl(ty1[0], ty2[0], false).is_err() {
return Self::incompatible_types(a, b);
}
}
(true, false) => return Self::incompatible_types(a, b),
(false, true) => {
for y in ty2 {
if self.unify_impl(ty1[0], *y, false).is_err() {
return Self::incompatible_types(a, b);
}
}
}
(false, false) => {
if ty1.len() != ty2.len() {
return Self::incompatible_types(a, b);
}
for (x, y) in ty1.iter().zip(ty2.iter()) {
if self.unify_impl(*x, *y, false).is_err() {
return Self::incompatible_types(a, b);
}
}
(TTuple { ty: ty1 }, TTuple { ty: ty2 }) => {
if ty1.len() != ty2.len() {
return Err(TypeError::new(TypeErrorKind::IncompatibleTypes(a, b), None));
}
for (x, y) in ty1.iter().zip(ty2.iter()) {
if self.unify_impl(*x, *y, false).is_err() {
return Err(TypeError::new(TypeErrorKind::IncompatibleTypes(a, b), None));
}
}
self.set_a_to_b(a, b);
}
(TVar { fields: Some(map), range, .. }, TObj { obj_id, fields, params }) => {
@ -1383,22 +1307,10 @@ impl Unifier {
TypeEnum::TLiteral { values, .. } => {
format!("const({})", values.iter().map(|v| format!("{v:?}")).join(", "))
}
TypeEnum::TTuple { ty, is_vararg_ctx } => {
if *is_vararg_ctx {
debug_assert_eq!(ty.len(), 1);
let field = self.internal_stringify(
*ty.iter().next().unwrap(),
obj_to_name,
var_to_name,
notes,
);
format!("tuple[*{field}]")
} else {
let mut fields = ty
.iter()
.map(|v| self.internal_stringify(*v, obj_to_name, var_to_name, notes));
format!("tuple[{}]", fields.join(", "))
}
TypeEnum::TTuple { ty } => {
let mut fields =
ty.iter().map(|v| self.internal_stringify(*v, obj_to_name, var_to_name, notes));
format!("tuple[{}]", fields.join(", "))
}
TypeEnum::TVirtual { ty } => {
format!(
@ -1423,21 +1335,17 @@ impl Unifier {
.args
.iter()
.map(|arg| {
let vararg_prefix = if arg.is_vararg { "*" } else { "" };
if let Some(dv) = &arg.default_value {
format!(
"{}:{}{}={}",
"{}:{}={}",
arg.name,
vararg_prefix,
self.internal_stringify(arg.ty, obj_to_name, var_to_name, notes),
dv
)
} else {
format!(
"{}:{}{}",
"{}:{}",
arg.name,
vararg_prefix,
self.internal_stringify(arg.ty, obj_to_name, var_to_name, notes)
)
}
@ -1523,7 +1431,7 @@ impl Unifier {
match &*ty {
TypeEnum::TRigidVar { .. } | TypeEnum::TLiteral { .. } => None,
TypeEnum::TVar { id, .. } => mapping.get(id).copied(),
TypeEnum::TTuple { ty, is_vararg_ctx } => {
TypeEnum::TTuple { ty } => {
let mut new_ty = Cow::from(ty);
for (i, t) in ty.iter().enumerate() {
if let Some(t1) = self.subst_impl(*t, mapping, cache) {
@ -1531,10 +1439,7 @@ impl Unifier {
}
}
if matches!(new_ty, Cow::Owned(_)) {
Some(self.add_ty(TypeEnum::TTuple {
ty: new_ty.into_owned(),
is_vararg_ctx: *is_vararg_ctx,
}))
Some(self.add_ty(TypeEnum::TTuple { ty: new_ty.into_owned() }))
} else {
None
}
@ -1694,37 +1599,16 @@ impl Unifier {
}
}
(TVar { range, .. }, _) => self.check_var_compatibility(b, range).or(Err(())),
(
TTuple { ty: ty1, is_vararg_ctx: is_vararg1 },
TTuple { ty: ty2, is_vararg_ctx: is_vararg2 },
) => {
if *is_vararg1 && *is_vararg2 {
let isect_ty = self.get_intersection(ty1[0], ty2[0])?;
Ok(isect_ty.map(|ty| self.add_ty(TTuple { ty: vec![ty], is_vararg_ctx: true })))
(TTuple { ty: ty1 }, TTuple { ty: ty2 }) if ty1.len() == ty2.len() => {
let ty: Vec<_> = zip(ty1.iter(), ty2.iter())
.map(|(a, b)| self.get_intersection(*a, *b))
.try_collect()?;
if ty.iter().any(Option::is_some) {
Ok(Some(self.add_ty(TTuple {
ty: zip(ty, ty1.iter()).map(|(a, b)| a.unwrap_or(*b)).collect(),
})))
} else {
let zip_iter: Box<dyn Iterator<Item = (&Type, &Type)>> =
match (*is_vararg1, *is_vararg2) {
(true, _) => Box::new(repeat_n(&ty1[0], ty2.len()).zip(ty2.iter())),
(_, false) => Box::new(ty1.iter().zip(repeat_n(&ty2[0], ty1.len()))),
_ => {
if ty1.len() != ty2.len() {
return Err(());
}
Box::new(ty1.iter().zip(ty2.iter()))
}
};
let ty: Vec<_> =
zip_iter.map(|(a, b)| self.get_intersection(*a, *b)).try_collect()?;
Ok(if ty.iter().any(Option::is_some) {
Some(self.add_ty(TTuple {
ty: zip(ty, ty1.iter()).map(|(a, b)| a.unwrap_or(*b)).collect(),
is_vararg_ctx: false,
}))
} else {
None
})
Ok(None)
}
}
// TODO(Derppening): #444

View File

@ -1,12 +1,10 @@
use std::collections::HashMap;
use super::super::magic_methods::with_fields;
use super::*;
use indoc::indoc;
use itertools::Itertools;
use std::collections::HashMap;
use test_case::test_case;
use super::*;
use crate::typecheck::magic_methods::with_fields;
impl Unifier {
/// Check whether two types are equal.
fn eq(&mut self, a: Type, b: Type) -> bool {
@ -30,10 +28,7 @@ impl Unifier {
TypeEnum::TVar { fields: Some(map1), .. },
TypeEnum::TVar { fields: Some(map2), .. },
) => self.map_eq2(map1, map2),
(
TypeEnum::TTuple { ty: ty1, is_vararg_ctx: false },
TypeEnum::TTuple { ty: ty2, is_vararg_ctx: false },
) => {
(TypeEnum::TTuple { ty: ty1 }, TypeEnum::TTuple { ty: ty2 }) => {
ty1.len() == ty2.len()
&& ty1.iter().zip(ty2.iter()).all(|(t1, t2)| self.eq(*t1, *t2))
}
@ -183,7 +178,7 @@ impl TestEnvironment {
ty.push(result.0);
s = result.1;
}
(self.unifier.add_ty(TypeEnum::TTuple { ty, is_vararg_ctx: false }), &s[1..])
(self.unifier.add_ty(TypeEnum::TTuple { ty }), &s[1..])
}
"Record" => {
let mut s = &typ[end..];
@ -613,7 +608,7 @@ fn test_instantiation() {
let v1 = env.unifier.get_fresh_var_with_range(&[list_v, int], None, None).ty;
let v2 = env.unifier.get_fresh_var_with_range(&[list_int, float], None, None).ty;
let t = env.unifier.get_dummy_var().ty;
let tuple = env.unifier.add_ty(TypeEnum::TTuple { ty: vec![v, v1, v2], is_vararg_ctx: false });
let tuple = env.unifier.add_ty(TypeEnum::TTuple { ty: vec![v, v1, v2] });
let v3 = env.unifier.get_fresh_var_with_range(&[tuple, t], None, None).ty;
// t = TypeVar('t')
// v = TypeVar('v', int, bool)

5
nac3core/src/util.rs Normal file
View File

@ -0,0 +1,5 @@
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum SizeVariant {
Bits32,
Bits64,
}

View File

@ -238,7 +238,7 @@ impl<'a> EH_Frame<'a> {
/// From the [specification](https://refspecs.linuxfoundation.org/LSB_5.0.0/LSB-Core-generic/LSB-Core-generic/ehframechpt.html):
///
/// > Each CFI record contains a Common Information Entry (CIE) record followed by 1 or more Frame
/// > Description Entry (FDE) records.
/// Description Entry (FDE) records.
pub struct CFI_Record<'a> {
// It refers to the augmentation data that corresponds to 'R' in the augmentation string
fde_pointer_encoding: u8,

View File

@ -21,12 +21,13 @@
clippy::wildcard_imports
)]
use std::{collections::HashMap, mem, ptr, slice, str};
use byteorder::{ByteOrder, LittleEndian};
use dwarf::*;
use elf::*;
use std::collections::HashMap;
use std::{mem, ptr, slice, str};
extern crate byteorder;
use byteorder::{ByteOrder, LittleEndian};
mod dwarf;
mod elf;

View File

@ -8,15 +8,15 @@ license = "MIT"
edition = "2021"
[build-dependencies]
lalrpop = "0.22"
lalrpop = "0.20"
[dependencies]
nac3ast = { path = "../nac3ast" }
lalrpop-util = "0.22"
lalrpop-util = "0.20"
log = "0.4"
unic-emoji-char = "0.9"
unic-ucd-ident = "0.9"
unicode_names2 = "1.3"
unicode_names2 = "1.2"
phf = { version = "0.11", features = ["macros"] }
ahash = "0.8"

View File

@ -1,10 +1,8 @@
use crate::{
ast::{Ident, Location},
error::*,
token::Tok,
};
use crate::ast::Ident;
use crate::ast::Location;
use crate::error::*;
use crate::token::Tok;
use lalrpop_util::ParseError;
use nac3ast::*;
pub fn make_config_comment(

View File

@ -1,11 +1,12 @@
//! Define internal parse error types
//! The goal is to provide a matching and a safe error API, maksing errors from LALR
use std::error::Error;
use std::fmt;
use lalrpop_util::ParseError as LalrpopError;
use crate::{ast::Location, token::Tok};
use crate::ast::Location;
use crate::token::Tok;
use std::error::Error;
use std::fmt;
/// Represents an error during lexical scanning.
#[derive(Debug, PartialEq)]

View File

@ -1,11 +1,12 @@
use std::{iter, mem, str};
use std::iter;
use std::mem;
use std::str;
use crate::ast::{Constant, ConversionFlag, Expr, ExprKind, Location};
use crate::error::{FStringError, FStringErrorType, ParseError};
use crate::parser::parse_expression;
use self::FStringErrorType::*;
use crate::{
ast::{Constant, ConversionFlag, Expr, ExprKind, Location},
error::{FStringError, FStringErrorType, ParseError},
parser::parse_expression,
};
struct FStringParser<'a> {
chars: iter::Peekable<str::Chars<'a>>,

View File

@ -1,11 +1,8 @@
use ahash::RandomState;
use std::collections::HashSet;
use ahash::RandomState;
use crate::{
ast,
error::{LexicalError, LexicalErrorType},
};
use crate::ast;
use crate::error::{LexicalError, LexicalErrorType};
pub struct ArgumentList {
pub args: Vec<ast::Expr>,

View File

@ -1,16 +1,16 @@
//! This module takes care of lexing python source text.
//!
//! This means source code is translated into separate tokens.
use std::{char, cmp::Ordering, num::IntErrorKind, str::FromStr};
use unic_emoji_char::is_emoji_presentation;
use unic_ucd_ident::{is_xid_continue, is_xid_start};
pub use super::token::Tok;
use crate::{
ast::{FileName, Location},
error::{LexicalError, LexicalErrorType},
};
use crate::ast::{FileName, Location};
use crate::error::{LexicalError, LexicalErrorType};
use std::char;
use std::cmp::Ordering;
use std::num::IntErrorKind;
use std::str::FromStr;
use unic_emoji_char::is_emoji_presentation;
use unic_ucd_ident::{is_xid_continue, is_xid_start};
#[derive(Clone, Copy, PartialEq, Debug, Default)]
struct IndentationLevel {

View File

@ -5,16 +5,14 @@
//! parse a whole program, a single statement, or a single
//! expression.
use nac3ast::Location;
use std::iter;
use nac3ast::Location;
use crate::ast::{self, FileName};
use crate::error::ParseError;
use crate::lexer;
pub use crate::mode::Mode;
use crate::{
ast::{self, FileName},
error::ParseError,
lexer, python,
};
use crate::python;
/*
* Parse python code.

View File

@ -1,8 +1,7 @@
//! Different token definitions.
//! Loosely based on token.h from CPython source:
use std::fmt::{self, Write};
use crate::ast;
use std::fmt::{self, Write};
/// Python source code can be tokenized in a sequence of these tokens.
#[derive(Clone, Debug, PartialEq)]

View File

@ -4,13 +4,16 @@ version = "0.1.0"
authors = ["M-Labs"]
edition = "2021"
[features]
no-escape-analysis = ["nac3core/no-escape-analysis"]
[dependencies]
parking_lot = "0.12"
nac3parser = { path = "../nac3parser" }
nac3core = { path = "../nac3core" }
[dependencies.clap]
version = "4.5"
features = ["derive"]
[dependencies.inkwell]
version = "0.4"
default-features = false
features = ["llvm14-0", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]

View File

@ -3,66 +3,23 @@
set -e
if [ -z "$1" ]; then
echo "No argument supplied"
exit 1
echo "Requires at least one argument"
exit 1
fi
declare -a nac3args
while [ $# -gt 1 ]; do
case "$1" in
--help)
echo "Usage: check_demo.sh [--debug] [-i686] -- [NAC3ARGS...] demo"
exit
;;
--debug)
debug=1
;;
-i686)
i686=1
;;
--)
shift
break
;;
*)
echo "Unrecognized argument \"$1\""
exit 1
;;
esac
shift
done
while [ $# -gt 1 ]; do
nac3args+=("$1")
shift
done
demo="$1"
echo "### Checking $demo..."
echo ">>>>>> Running $demo with the Python interpreter"
echo -n "Checking $demo... "
./interpret_demo.py "$demo" > interpreted.log
./run_demo.sh --out run.log "${nac3args[@]}" "$demo"
./run_demo.sh --lli --out run_lli.log "${nac3args[@]}" "$demo"
diff -Nau interpreted.log run.log
diff -Nau interpreted.log run_lli.log
echo "ok"
if [ -n "$i686" ]; then
echo "...... Trying NAC3's 32-bit code generator output"
if [ -n "$debug" ]; then
./run_demo.sh --debug -i686 --out run_32.log -- "${nac3args[@]}" "$demo"
else
./run_demo.sh -i686 --out run_32.log -- "${nac3args[@]}" "$demo"
fi
diff -Nau interpreted.log run_32.log
fi
echo "...... Trying NAC3's 64-bit code generator output"
if [ -n "$debug" ]; then
./run_demo.sh --debug --out run_64.log -- "${nac3args[@]}" "$demo"
else
./run_demo.sh --out run_64.log -- "${nac3args[@]}" "$demo"
fi
diff -Nau interpreted.log run_64.log
echo "...... OK"
rm -f interpreted.log \
run_32.log run_64.log
rm -f interpreted.log run.log run_lli.log

View File

@ -2,11 +2,6 @@
set -e
if [ "$1" == "--help" ]; then
echo "Usage: check_demos.sh [CHECKARGS...] [--] [NAC3ARGS...]"
exit
fi
count=0
for demo in src/*.py; do
./check_demo.sh "$@" "$demo"

View File

@ -6,12 +6,14 @@
#include <stdlib.h>
#include <string.h>
#define usize size_t
double dbl_nan(void) {
return NAN;
return NAN;
}
double dbl_inf(void) {
return INFINITY;
return INFINITY;
}
void output_bool(bool x) {
@ -19,19 +21,19 @@ void output_bool(bool x) {
}
void output_int32(int32_t x) {
printf("%" PRId32 "\n", x);
printf("%"PRId32"\n", x);
}
void output_int64(int64_t x) {
printf("%" PRId64 "\n", x);
printf("%"PRId64"\n", x);
}
void output_uint32(uint32_t x) {
printf("%" PRIu32 "\n", x);
printf("%"PRIu32"\n", x);
}
void output_uint64(uint64_t x) {
printf("%" PRIu64 "\n", x);
printf("%"PRIu64"\n", x);
}
void output_float64(double x) {
@ -52,7 +54,7 @@ void output_range(int32_t range[3]) {
}
void output_asciiart(int32_t x) {
static const char* chars = " .,-:;i+hHM$*#@ ";
static const char *chars = " .,-:;i+hHM$*#@ ";
if (x < 0) {
putchar('\n');
} else {
@ -61,15 +63,15 @@ void output_asciiart(int32_t x) {
}
struct cslice {
void* data;
size_t len;
void *data;
usize len;
};
void output_int32_list(struct cslice* slice) {
const int32_t* data = (int32_t*)slice->data;
void output_int32_list(struct cslice *slice) {
const int32_t *data = (int32_t *) slice->data;
putchar('[');
for (size_t i = 0; i < slice->len; ++i) {
for (usize i = 0; i < slice->len; ++i) {
if (i == slice->len - 1) {
printf("%d", data[i]);
} else {
@ -80,23 +82,23 @@ void output_int32_list(struct cslice* slice) {
putchar('\n');
}
void output_str(struct cslice* slice) {
const char* data = (const char*)slice->data;
void output_str(struct cslice *slice) {
const char *data = (const char *) slice->data;
for (size_t i = 0; i < slice->len; ++i) {
for (usize i = 0; i < slice->len; ++i) {
putchar(data[i]);
}
}
void output_strln(struct cslice* slice) {
void output_strln(struct cslice *slice) {
output_str(slice);
putchar('\n');
}
uint64_t dbg_stack_address(__attribute__((unused)) struct cslice* slice) {
uint64_t dbg_stack_address(__attribute__((unused)) struct cslice *slice) {
int i;
void* ptr = (void*)&i;
return (uintptr_t)ptr;
void *ptr = (void *) &i;
return (uintptr_t) ptr;
}
uint32_t __nac3_personality(uint32_t state, uint32_t exception_object, uint32_t context) {
@ -105,26 +107,8 @@ uint32_t __nac3_personality(uint32_t state, uint32_t exception_object, uint32_t
__builtin_unreachable();
}
// See `struct Exception<'a>` in
// https://github.com/m-labs/artiq/blob/master/artiq/firmware/libeh/eh_artiq.rs
struct Exception {
uint32_t id;
struct cslice file;
uint32_t line;
uint32_t column;
struct cslice function;
struct cslice message;
int64_t param[3];
};
uint32_t __nac3_raise(struct Exception* e) {
printf("__nac3_raise called. Exception details:\n");
printf(" ID: %" PRIu32 "\n", e->id);
printf(" Location: %*s:%" PRIu32 ":%" PRIu32 "\n", (int)e->file.len, (const char*)e->file.data, e->line,
e->column);
printf(" Function: %*s\n", (int)e->function.len, (const char*)e->function.data);
printf(" Message: \"%*s\"\n", (int)e->message.len, (const char*)e->message.data);
printf(" Params: {0}=%" PRId64 ", {1}=%" PRId64 ", {2}=%" PRId64 "\n", e->param[0], e->param[1], e->param[2]);
uint32_t __nac3_raise(uint32_t state, uint32_t exception_object, uint32_t context) {
printf("__nac3_raise(state: %u, exception_object: %u, context: %u)\n", state, exception_object, context);
exit(101);
__builtin_unreachable();
}

View File

@ -6,7 +6,6 @@ import importlib.machinery
import math
import numpy as np
import numpy.typing as npt
import scipy as sp
import pathlib
from numpy import int32, int64, uint32, uint64
@ -168,7 +167,7 @@ def patch(module):
module.ceil64 = _ceil
module.np_ceil = np.ceil
# NumPy NDArray factory functions
# NumPy ndarray functions
module.ndarray = NDArray
module.np_ndarray = np.ndarray
module.np_empty = np.empty
@ -184,10 +183,8 @@ def patch(module):
module.np_isinf = np.isinf
module.np_min = np.min
module.np_minimum = np.minimum
module.np_argmin = np.argmin
module.np_max = np.max
module.np_maximum = np.maximum
module.np_argmax = np.argmax
module.np_sin = np.sin
module.np_cos = np.cos
module.np_exp = np.exp
@ -218,10 +215,8 @@ def patch(module):
module.np_ldexp = np.ldexp
module.np_hypot = np.hypot
module.np_nextafter = np.nextafter
module.np_transpose = np.transpose
module.np_reshape = np.reshape
# SciPy Math functions
# SciPy Math Functions
module.sp_spec_erf = special.erf
module.sp_spec_erfc = special.erfc
module.sp_spec_gamma = special.gamma
@ -229,19 +224,14 @@ def patch(module):
module.sp_spec_j0 = special.j0
module.sp_spec_j1 = special.j1
# Linalg functions
module.np_dot = np.dot
module.np_linalg_cholesky = np.linalg.cholesky
module.np_linalg_qr = np.linalg.qr
module.np_linalg_svd = np.linalg.svd
module.np_linalg_inv = np.linalg.inv
module.np_linalg_pinv = np.linalg.pinv
module.np_linalg_matrix_power = np.linalg.matrix_power
module.np_linalg_det = np.linalg.det
module.sp_linalg_lu = lambda x: sp.linalg.lu(x, True)
module.sp_linalg_schur = sp.linalg.schur
module.sp_linalg_hessenberg = lambda x: sp.linalg.hessenberg(x, True)
# NumPy NDArray Functions
module.np_ndarray = np.ndarray
module.np_empty = np.empty
module.np_zeros = np.zeros
module.np_ones = np.ones
module.np_full = np.full
module.np_eye = np.eye
module.np_identity = np.identity
def file_import(filename, prefix="file_import_"):
filename = pathlib.Path(filename)

View File

@ -1,114 +0,0 @@
# This file is automatically @generated by Cargo.
# It is not intended for manual editing.
version = 3
[[package]]
name = "approx"
version = "0.5.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "cab112f0a86d568ea0e627cc1d6be74a1e9cd55214684db5561995f6dad897c6"
dependencies = [
"num-traits",
]
[[package]]
name = "autocfg"
version = "1.3.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0c4b4d0bd25bd0b74681c0ad21497610ce1b7c91b1022cd21c80c6fbdd9476b0"
[[package]]
name = "cslice"
version = "0.3.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0f8cb7306107e4b10e64994de6d3274bd08996a7c1322a27b86482392f96be0a"
[[package]]
name = "libm"
version = "0.2.8"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "4ec2a862134d2a7d32d7983ddcdd1c4923530833c9f2ea1a44fc5fa473989058"
[[package]]
name = "linalg"
version = "0.1.0"
dependencies = [
"cslice",
"nalgebra",
]
[[package]]
name = "nalgebra"
version = "0.32.6"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "7b5c17de023a86f59ed79891b2e5d5a94c705dbe904a5b5c9c952ea6221b03e4"
dependencies = [
"approx",
"num-complex",
"num-rational",
"num-traits",
"simba",
"typenum",
]
[[package]]
name = "num-complex"
version = "0.4.6"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "73f88a1307638156682bada9d7604135552957b7818057dcef22705b4d509495"
dependencies = [
"num-traits",
]
[[package]]
name = "num-integer"
version = "0.1.46"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "7969661fd2958a5cb096e56c8e1ad0444ac2bbcd0061bd28660485a44879858f"
dependencies = [
"num-traits",
]
[[package]]
name = "num-rational"
version = "0.4.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "f83d14da390562dca69fc84082e73e548e1ad308d24accdedd2720017cb37824"
dependencies = [
"num-integer",
"num-traits",
]
[[package]]
name = "num-traits"
version = "0.2.19"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "071dfc062690e90b734c0b2273ce72ad0ffa95f0c74596bc250dcfd960262841"
dependencies = [
"autocfg",
"libm",
]
[[package]]
name = "paste"
version = "1.0.15"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "57c0d7b74b563b49d38dae00a0c37d4d6de9b432382b2892f0574ddcae73fd0a"
[[package]]
name = "simba"
version = "0.8.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "061507c94fc6ab4ba1c9a0305018408e312e17c041eb63bef8aa726fa33aceae"
dependencies = [
"approx",
"num-complex",
"num-traits",
"paste",
]
[[package]]
name = "typenum"
version = "1.17.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "42ff0bf0c66b8238c6f3b578df37d0b7848e55df8577b3f74f92a69acceeb825"

View File

@ -1,13 +0,0 @@
[package]
name = "linalg"
version = "0.1.0"
edition = "2021"
[lib]
crate-type = ["staticlib"]
[dependencies]
nalgebra = {version = "0.32.6", default-features = false, features = ["libm", "alloc"]}
cslice = "0.3.0"
[workspace]

View File

@ -1,406 +0,0 @@
// Uses `nalgebra` crate to invoke `np_linalg` and `sp_linalg` functions
// When converting between `nalgebra::Matrix` and `NDArray` following considerations are necessary
//
// * Both `nalgebra::Matrix` and `NDArray` require their content to be stored in row-major order
// * `NDArray` data pointer can be directly read and converted to `nalgebra::Matrix` (row and column number must be known)
// * `nalgebra::Matrix::as_slice` returns the content of matrix in column-major order and initial data needs to be transposed before storing it in `NDArray` data pointer
use core::slice;
use nalgebra::DMatrix;
fn report_error(
error_name: &str,
fn_name: &str,
file_name: &str,
line_num: u32,
col_num: u32,
err_msg: &str,
) -> ! {
panic!(
"Exception {} from {} in {}:{}:{}, message: {}",
error_name, fn_name, file_name, line_num, col_num, err_msg
);
}
pub struct InputMatrix {
pub ndims: usize,
pub dims: *const usize,
pub data: *mut f64,
}
impl InputMatrix {
fn get_dims(&mut self) -> Vec<usize> {
let dims = unsafe { slice::from_raw_parts(self.dims, self.ndims) };
dims.to_vec()
}
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_cholesky(mat1: *mut InputMatrix, out: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "np_linalg_cholesky", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
if dim1[0] != dim1[1] {
let err_msg =
format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
report_error("LinAlgError", "np_linalg_cholesky", file!(), line!(), column!(), &err_msg);
}
let outdim = out.get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let result = matrix1.cholesky();
match result {
Some(res) => {
out_slice.copy_from_slice(res.unpack().transpose().as_slice());
}
None => {
report_error(
"LinAlgError",
"np_linalg_cholesky",
file!(),
line!(),
column!(),
"Matrix is not positive definite",
);
}
};
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_qr(
mat1: *mut InputMatrix,
out_q: *mut InputMatrix,
out_r: *mut InputMatrix,
) {
let mat1 = mat1.as_mut().unwrap();
let out_q = out_q.as_mut().unwrap();
let out_r = out_r.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "np_linalg_cholesky", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
let outq_dim = (*out_q).get_dims();
let outr_dim = (*out_r).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_q_slice = unsafe { slice::from_raw_parts_mut(out_q.data, outq_dim[0] * outq_dim[1]) };
let out_r_slice = unsafe { slice::from_raw_parts_mut(out_r.data, outr_dim[0] * outr_dim[1]) };
// Refer to https://github.com/dimforge/nalgebra/issues/735
let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let res = matrix1.qr();
let (q, r) = res.unpack();
// Uses different algo need to match numpy
out_q_slice.copy_from_slice(q.transpose().as_slice());
out_r_slice.copy_from_slice(r.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_svd(
mat1: *mut InputMatrix,
outu: *mut InputMatrix,
outs: *mut InputMatrix,
outvh: *mut InputMatrix,
) {
let mat1 = mat1.as_mut().unwrap();
let outu = outu.as_mut().unwrap();
let outs = outs.as_mut().unwrap();
let outvh = outvh.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "np_linalg_svd", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
let outu_dim = (*outu).get_dims();
let outs_dim = (*outs).get_dims();
let outvh_dim = (*outvh).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_u_slice = unsafe { slice::from_raw_parts_mut(outu.data, outu_dim[0] * outu_dim[1]) };
let out_s_slice = unsafe { slice::from_raw_parts_mut(outs.data, outs_dim[0]) };
let out_vh_slice =
unsafe { slice::from_raw_parts_mut(outvh.data, outvh_dim[0] * outvh_dim[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let result = matrix.svd(true, true);
out_u_slice.copy_from_slice(result.u.unwrap().transpose().as_slice());
out_s_slice.copy_from_slice(result.singular_values.as_slice());
out_vh_slice.copy_from_slice(result.v_t.unwrap().transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_inv(mat1: *mut InputMatrix, out: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "np_linalg_inv", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
if dim1[0] != dim1[1] {
let err_msg =
format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
report_error("LinAlgError", "np_linalg_inv", file!(), line!(), column!(), &err_msg);
}
let outdim = out.get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
if !matrix.is_invertible() {
report_error(
"LinAlgError",
"np_linalg_inv",
file!(),
line!(),
column!(),
"no inverse for Singular Matrix",
);
}
let inv = matrix.try_inverse().unwrap();
out_slice.copy_from_slice(inv.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_pinv(mat1: *mut InputMatrix, out: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "np_linalg_pinv", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
let outdim = out.get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let svd = matrix.svd(true, true);
let inv = svd.pseudo_inverse(1e-15);
match inv {
Ok(m) => {
out_slice.copy_from_slice(m.transpose().as_slice());
}
Err(err_msg) => {
report_error("LinAlgError", "np_linalg_pinv", file!(), line!(), column!(), err_msg);
}
}
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_matrix_power(
mat1: *mut InputMatrix,
mat2: *mut InputMatrix,
out: *mut InputMatrix,
) {
let mat1 = mat1.as_mut().unwrap();
let mat2 = mat2.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D", mat1.ndims);
report_error("ValueError", "np_linalg_matrix_power", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
let power = unsafe { slice::from_raw_parts_mut(mat2.data, 1) };
let power = power[0];
let outdim = out.get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let abs_pow = power.abs();
let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let mut result = matrix1.pow(abs_pow as u32);
if power < 0.0 {
if !result.is_invertible() {
report_error(
"LinAlgError",
"np_linalg_inv",
file!(),
line!(),
column!(),
"no inverse for Singular Matrix",
);
}
result = result.try_inverse().unwrap();
}
out_slice.copy_from_slice(result.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_det(mat1: *mut InputMatrix, out: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "np_linalg_det", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, 1) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
if !matrix.is_square() {
let err_msg =
format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
report_error("LinAlgError", "np_linalg_inv", file!(), line!(), column!(), &err_msg);
}
out_slice[0] = matrix.determinant();
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn sp_linalg_lu(
mat1: *mut InputMatrix,
out_l: *mut InputMatrix,
out_u: *mut InputMatrix,
) {
let mat1 = mat1.as_mut().unwrap();
let out_l = out_l.as_mut().unwrap();
let out_u = out_u.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "sp_linalg_lu", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
let outl_dim = (*out_l).get_dims();
let outu_dim = (*out_u).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_l_slice = unsafe { slice::from_raw_parts_mut(out_l.data, outl_dim[0] * outl_dim[1]) };
let out_u_slice = unsafe { slice::from_raw_parts_mut(out_u.data, outu_dim[0] * outu_dim[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let (_, l, u) = matrix.lu().unpack();
out_l_slice.copy_from_slice(l.transpose().as_slice());
out_u_slice.copy_from_slice(u.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn sp_linalg_schur(
mat1: *mut InputMatrix,
out_t: *mut InputMatrix,
out_z: *mut InputMatrix,
) {
let mat1 = mat1.as_mut().unwrap();
let out_t = out_t.as_mut().unwrap();
let out_z = out_z.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "sp_linalg_schur", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
if dim1[0] != dim1[1] {
let err_msg =
format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
report_error("LinAlgError", "np_linalg_schur", file!(), line!(), column!(), &err_msg);
}
let out_t_dim = (*out_t).get_dims();
let out_z_dim = (*out_z).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_t_slice = unsafe { slice::from_raw_parts_mut(out_t.data, out_t_dim[0] * out_t_dim[1]) };
let out_z_slice = unsafe { slice::from_raw_parts_mut(out_z.data, out_z_dim[0] * out_z_dim[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let (z, t) = matrix.schur().unpack();
out_t_slice.copy_from_slice(t.transpose().as_slice());
out_z_slice.copy_from_slice(z.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn sp_linalg_hessenberg(
mat1: *mut InputMatrix,
out_h: *mut InputMatrix,
out_q: *mut InputMatrix,
) {
let mat1 = mat1.as_mut().unwrap();
let out_h = out_h.as_mut().unwrap();
let out_q = out_q.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "sp_linalg_hessenberg", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
if dim1[0] != dim1[1] {
let err_msg =
format!("last 2 dimensions of the array must be square: {} != {}", dim1[0], dim1[1]);
report_error("LinAlgError", "sp_linalg_hessenberg", file!(), line!(), column!(), &err_msg);
}
let out_h_dim = (*out_h).get_dims();
let out_q_dim = (*out_q).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_h_slice = unsafe { slice::from_raw_parts_mut(out_h.data, out_h_dim[0] * out_h_dim[1]) };
let out_q_slice = unsafe { slice::from_raw_parts_mut(out_q.data, out_q_dim[0] * out_q_dim[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let (q, h) = matrix.hessenberg().unpack();
out_h_slice.copy_from_slice(h.transpose().as_slice());
out_q_slice.copy_from_slice(q.transpose().as_slice());
}

View File

@ -2,9 +2,6 @@
set -e
: "${DEMO_LINALG_STUB:=linalg/target/release/liblinalg.a}"
: "${DEMO_LINALG_STUB32:=linalg/target/i686-unknown-linux-gnu/release/liblinalg.a}"
if [ -z "$1" ]; then
echo "No argument supplied"
exit 1
@ -14,26 +11,25 @@ declare -a nac3args
while [ $# -ge 1 ]; do
case "$1" in
--help)
echo "Usage: run_demo.sh [--help] [--out OUTFILE] [--debug] [-i686] -- [NAC3ARGS...] demo"
echo "Usage: run_demo.sh [--help] [--out OUTFILE] [--lli] [--debug] -- [NAC3ARGS...]"
exit
;;
--out)
shift
outfile="$1"
;;
--lli)
use_lli=1
;;
--debug)
debug=1
;;
-i686)
i686=1
;;
--)
shift
break
;;
*)
echo "Unrecognized argument \"$1\""
exit 1
break
;;
esac
shift
@ -54,19 +50,29 @@ else
fi
rm -f ./*.o ./*.bc demo
if [ -z "$i686" ]; then
if [ -z "$use_lli" ]; then
$nac3standalone "${nac3args[@]}"
clang -c -std=gnu11 -Wall -Wextra -O3 -o demo.o demo.c
clang -o demo module.o demo.o $DEMO_LINALG_STUB -lm -Wl,--no-warn-search-mismatch
else
$nac3standalone --triple i686-unknown-linux-gnu --target-features +sse2 "${nac3args[@]}"
clang -m32 -c -std=gnu11 -Wall -Wextra -O3 -msse2 -o demo.o demo.c
clang -m32 -o demo module.o demo.o $DEMO_LINALG_STUB32 -lm -Wl,--no-warn-search-mismatch
fi
if [ -z "$outfile" ]; then
./demo
clang -c -std=gnu11 -Wall -Wextra -O3 -o demo.o demo.c
clang -lm -o demo module.o demo.o
if [ -z "$outfile" ]; then
./demo
else
./demo > "$outfile"
fi
else
./demo > "$outfile"
$nac3standalone --emit-llvm "${nac3args[@]}"
clang -c -std=gnu11 -Wall -Wextra -O3 -emit-llvm -o demo.bc demo.c
shopt -s nullglob
llvm-link -o nac3out.bc module*.bc main.bc
shopt -u nullglob
if [ -z "$outfile" ]; then
lli --extra-module demo.bc --extra-module irrt.bc nac3out.bc
else
lli --extra-module demo.bc --extra-module irrt.bc nac3out.bc > "$outfile"
fi
fi

View File

@ -1,76 +0,0 @@
@extern
def output_int32(x: int32):
...
@extern
def output_bool(x: bool):
...
def example1():
x, *ys, z = (1, 2, 3, 4, 5)
output_int32(x)
output_int32(len(ys))
output_int32(ys[0])
output_int32(ys[1])
output_int32(ys[2])
output_int32(z)
def example2():
x, y, *zs = (1, 2, 3, 4, 5)
output_int32(x)
output_int32(y)
output_int32(len(zs))
output_int32(zs[0])
output_int32(zs[1])
output_int32(zs[2])
def example3():
*xs, y, z = (1, 2, 3, 4, 5)
output_int32(len(xs))
output_int32(xs[0])
output_int32(xs[1])
output_int32(xs[2])
output_int32(y)
output_int32(z)
def example4():
*xs, y, z = (4, 5)
output_int32(len(xs))
output_int32(y)
output_int32(z)
def example5():
# Example from: https://docs.python.org/3/reference/simple_stmts.html#assignment-statements
x = [0, 1]
i = 0
i, x[i] = 1, 2 # i is updated, then x[i] is updated
output_int32(i)
output_int32(x[0])
output_int32(x[1])
class A:
value: int32
def __init__(self):
self.value = 1000
def example6():
ws = [88, 7, 8]
a = A()
x, [y, *ys, a.value], ws[0], (ws[0],) = 1, (2, False, 4, 5), 99, (6,)
output_int32(x)
output_int32(y)
output_bool(ys[0])
output_int32(ys[1])
output_int32(a.value)
output_int32(ws[0])
output_int32(ws[1])
output_int32(ws[2])
def run() -> int32:
example1()
example2()
example3()
example4()
example5()
example6()
return 0

View File

@ -1,31 +0,0 @@
@extern
def output_int32(x: int32):
...
@extern
def output_int64(x: int64):
...
X: int32 = 0
Y = int64(1)
def f():
global X, Y
X = 1
Y = int64(2)
def run() -> int32:
global X, Y
output_int32(X)
output_int64(Y)
f()
output_int32(X)
output_int64(Y)
X = 0
Y = int64(0)
output_int32(X)
output_int64(Y)
return 0

View File

@ -10,58 +10,23 @@ class A:
def __init__(self, a: int32):
self.a = a
def output_all_fields(self):
output_int32(self.a)
def f1(self):
self.f2()
def set_a(self, a: int32):
self.a = a
def f2(self):
output_int32(self.a)
class B(A):
b: int32
def __init__(self, b: int32):
A.__init__(self, b + 1)
self.set_b(b)
def output_parent_fields(self):
A.output_all_fields(self)
def output_all_fields(self):
A.output_all_fields(self)
output_int32(self.b)
def set_b(self, b: int32):
self.a = b + 1
self.b = b
class C(B):
c: int32
def __init__(self, c: int32):
B.__init__(self, c + 1)
self.c = c
def output_parent_fields(self):
B.output_all_fields(self)
def output_all_fields(self):
B.output_all_fields(self)
output_int32(self.c)
def set_c(self, c: int32):
self.c = c
def run() -> int32:
ccc = C(10)
ccc.output_all_fields()
ccc.set_a(1)
ccc.set_b(2)
ccc.set_c(3)
ccc.output_all_fields()
bbb = B(10)
bbb.set_a(9)
bbb.set_b(8)
bbb.output_all_fields()
ccc.output_all_fields()
aaa = A(5)
bbb = B(2)
aaa.f1()
bbb.f1()
return 0

View File

@ -0,0 +1,3 @@
def run() -> int32:
hello = np_zeros((3, 4))
return 0

View File

@ -114,22 +114,12 @@ def test_ndarray_ones():
n: ndarray[float, 1] = np_ones([1])
output_ndarray_float_1(n)
dim = (1,)
n_tup: ndarray[float, 1] = np_ones(dim)
output_ndarray_float_1(n_tup)
def test_ndarray_full():
n_float: ndarray[float, 1] = np_full([1], 2.0)
output_ndarray_float_1(n_float)
n_i32: ndarray[int32, 1] = np_full([1], 2)
output_ndarray_int32_1(n_i32)
dim = (1,)
n_float_tup: ndarray[float, 1] = np_full(dim, 2.0)
output_ndarray_float_1(n_float_tup)
n_i32_tup: ndarray[int32, 1] = np_full(dim, 2)
output_ndarray_int32_1(n_i32_tup)
def test_ndarray_eye():
n: ndarray[float, 2] = np_eye(2)
output_ndarray_float_2(n)
@ -877,13 +867,6 @@ def test_ndarray_minimum_broadcast_rhs_scalar():
output_ndarray_float_2(min_x_zeros)
output_ndarray_float_2(min_x_ones)
def test_ndarray_argmin():
x = np_array([[1., 2.], [3., 4.]])
y = np_argmin(x)
output_ndarray_float_2(x)
output_int64(y)
def test_ndarray_max():
x = np_identity(2)
y = np_max(x)
@ -927,13 +910,6 @@ def test_ndarray_maximum_broadcast_rhs_scalar():
output_ndarray_float_2(max_x_zeros)
output_ndarray_float_2(max_x_ones)
def test_ndarray_argmax():
x = np_array([[1., 2.], [3., 4.]])
y = np_argmax(x)
output_ndarray_float_2(x)
output_int64(y)
def test_ndarray_abs():
x = np_identity(2)
y = abs(x)
@ -1439,142 +1415,6 @@ def test_ndarray_nextafter_broadcast_rhs_scalar():
output_ndarray_float_2(nextafter_x_zeros)
output_ndarray_float_2(nextafter_x_ones)
def test_ndarray_transpose():
x: ndarray[float, 2] = np_array([[1., 2., 3.], [4., 5., 6.]])
y = np_transpose(x)
z = np_transpose(y)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_reshape():
w: ndarray[float, 1] = np_array([1., 2., 3., 4., 5., 6., 7., 8., 9., 10.])
x = np_reshape(w, (1, 2, 1, -1))
y = np_reshape(x, [2, -1])
z = np_reshape(y, 10)
x1: ndarray[int32, 1] = np_array([1, 2, 3, 4])
x2: ndarray[int32, 2] = np_reshape(x1, (2, 2))
output_ndarray_float_1(w)
output_ndarray_float_2(y)
output_ndarray_float_1(z)
def test_ndarray_dot():
x1: ndarray[float, 1] = np_array([5.0, 1.0, 4.0, 2.0])
y1: ndarray[float, 1] = np_array([5.0, 1.0, 6.0, 6.0])
z1 = np_dot(x1, y1)
x2: ndarray[int32, 1] = np_array([5, 1, 4, 2])
y2: ndarray[int32, 1] = np_array([5, 1, 6, 6])
z2 = np_dot(x2, y2)
x3: ndarray[bool, 1] = np_array([True, True, True, True])
y3: ndarray[bool, 1] = np_array([True, True, True, True])
z3 = np_dot(x3, y3)
z4 = np_dot(2, 3)
z5 = np_dot(2., 3.)
z6 = np_dot(True, False)
output_float64(z1)
output_int32(z2)
output_bool(z3)
output_int32(z4)
output_float64(z5)
output_bool(z6)
def test_ndarray_cholesky():
x: ndarray[float, 2] = np_array([[5.0, 1.0], [1.0, 4.0]])
y = np_linalg_cholesky(x)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_qr():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
y, z = np_linalg_qr(x)
output_ndarray_float_2(x)
# QR Factorization is not unique and gives different results in numpy and nalgebra
# Reverting the decomposition to compare the initial arrays
a = y @ z
output_ndarray_float_2(a)
def test_ndarray_linalg_inv():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
y = np_linalg_inv(x)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_pinv():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5]])
y = np_linalg_pinv(x)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_matrix_power():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
y = np_linalg_matrix_power(x, -9)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_det():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
y = np_linalg_det(x)
output_ndarray_float_2(x)
output_float64(y)
def test_ndarray_schur():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
t, z = sp_linalg_schur(x)
output_ndarray_float_2(x)
# Schur Factorization is not unique and gives different results in scipy and nalgebra
# Reverting the decomposition to compare the initial arrays
a = (z @ t) @ np_linalg_inv(z)
output_ndarray_float_2(a)
def test_ndarray_hessenberg():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 5.0, 8.5]])
h, q = sp_linalg_hessenberg(x)
output_ndarray_float_2(x)
# Hessenberg Factorization is not unique and gives different results in scipy and nalgebra
# Reverting the decomposition to compare the initial arrays
a = (q @ h) @ np_linalg_inv(q)
output_ndarray_float_2(a)
def test_ndarray_lu():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5]])
l, u = sp_linalg_lu(x)
output_ndarray_float_2(x)
output_ndarray_float_2(l)
output_ndarray_float_2(u)
def test_ndarray_svd():
w: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
x, y, z = np_linalg_svd(w)
output_ndarray_float_2(w)
# SVD Factorization is not unique and gives different results in numpy and nalgebra
# Reverting the decomposition to compare the initial arrays
a = x @ z
output_ndarray_float_2(a)
output_ndarray_float_1(y)
def run() -> int32:
test_ndarray_ctor()
test_ndarray_empty()
@ -1679,19 +1519,16 @@ def run() -> int32:
test_ndarray_round()
test_ndarray_floor()
test_ndarray_ceil()
test_ndarray_min()
test_ndarray_minimum()
test_ndarray_minimum_broadcast()
test_ndarray_minimum_broadcast_lhs_scalar()
test_ndarray_minimum_broadcast_rhs_scalar()
test_ndarray_argmin()
test_ndarray_max()
test_ndarray_maximum()
test_ndarray_maximum_broadcast()
test_ndarray_maximum_broadcast_lhs_scalar()
test_ndarray_maximum_broadcast_rhs_scalar()
test_ndarray_argmax()
test_ndarray_abs()
test_ndarray_isnan()
test_ndarray_isinf()
@ -1754,18 +1591,5 @@ def run() -> int32:
test_ndarray_nextafter_broadcast()
test_ndarray_nextafter_broadcast_lhs_scalar()
test_ndarray_nextafter_broadcast_rhs_scalar()
test_ndarray_transpose()
test_ndarray_reshape()
test_ndarray_dot()
test_ndarray_cholesky()
test_ndarray_qr()
test_ndarray_svd()
test_ndarray_linalg_inv()
test_ndarray_pinv()
test_ndarray_matrix_power()
test_ndarray_det()
test_ndarray_lu()
test_ndarray_schur()
test_ndarray_hessenberg()
return 0

View File

@ -1,30 +0,0 @@
@extern
def output_bool(x: bool):
...
def str_eq():
output_bool("" == "")
output_bool("a" == "")
output_bool("a" == "b")
output_bool("b" == "a")
output_bool("a" == "a")
output_bool("test string" == "test string")
output_bool("test string1" == "test string2")
def str_ne():
output_bool("" != "")
output_bool("a" != "")
output_bool("a" != "b")
output_bool("b" != "a")
output_bool("a" != "a")
output_bool("test string" != "test string")
output_bool("test string1" != "test string2")
def run() -> int32:
str_eq()
str_ne()
return 0

View File

@ -1,7 +1,3 @@
@extern
def output_bool(b: bool):
...
@extern
def output_int32_list(x: list[int32]):
...
@ -17,41 +13,6 @@ class A:
self.a = a
self.b = b
def test_tuple_eq():
# 0-len
output_bool(() == ())
# 1-len
output_bool((1,) == ())
output_bool(() == (1,))
output_bool((1,) == (1,))
output_bool((1,) == (2,))
# # 2-len
output_bool((1, 2) == ())
output_bool(() == (1, 2))
output_bool((1,) == (1, 2))
output_bool((1, 2) == (1,))
output_bool((2, 2) == (1, 2))
output_bool((1, 2) == (2, 2))
def test_tuple_ne():
# 0-len
output_bool(() != ())
# 1-len
output_bool((1,) != ())
output_bool(() != (1,))
output_bool((1,) != (1,))
output_bool((1,) != (2,))
# 2-len
output_bool((1, 2) != ())
output_bool(() != (1, 2))
output_bool((1,) != (1, 2))
output_bool((1, 2) != (1,))
output_bool((2, 2) != (1, 2))
output_bool((1, 2) != (2, 2))
def run() -> int32:
data = [0, 1, 2, 3]
@ -64,15 +25,5 @@ def run() -> int32:
output_int32(tl[0][0])
output_int32(tl[0][1])
output_int32(tl[1])
output_int32(len(()))
output_int32(len((1,)))
output_int32(len((1, 2)))
output_int32(len((1, 2, 3)))
output_int32(len((1, 2, 3, 4)))
output_int32(len((1, 2, 3, 4, 5)))
test_tuple_eq()
test_tuple_ne()
return 0

View File

@ -1,11 +0,0 @@
def f(*args: int32):
pass
def run() -> int32:
f()
f(1)
f(1, 2)
f(1, 2, 3)
return 0

View File

@ -1,14 +1,5 @@
use std::{
collections::{HashMap, HashSet},
sync::Arc,
};
use parking_lot::{Mutex, RwLock};
use nac3core::{
codegen::{CodeGenContext, CodeGenerator},
inkwell::{module::Linkage, values::BasicValue},
nac3parser::ast::{self, StrRef},
codegen::CodeGenContext,
symbol_resolver::{SymbolResolver, SymbolValue, ValueEnum},
toplevel::{DefinitionId, TopLevelDef},
typecheck::{
@ -16,10 +7,15 @@ use nac3core::{
typedef::{Type, Unifier},
},
};
use nac3parser::ast::{self, StrRef};
use parking_lot::{Mutex, RwLock};
use std::collections::HashSet;
use std::{collections::HashMap, sync::Arc};
pub struct ResolverInternal {
pub id_to_type: Mutex<HashMap<StrRef, Type>>,
pub id_to_def: Mutex<HashMap<StrRef, DefinitionId>>,
pub class_names: Mutex<HashMap<StrRef, Type>>,
pub module_globals: Mutex<HashMap<StrRef, SymbolValue>>,
pub str_store: Mutex<HashMap<String, i32>>,
}
@ -50,51 +46,20 @@ impl SymbolResolver for Resolver {
fn get_symbol_type(
&self,
unifier: &mut Unifier,
_: &mut Unifier,
_: &[Arc<RwLock<TopLevelDef>>],
primitives: &PrimitiveStore,
_: &PrimitiveStore,
str: StrRef,
) -> Result<Type, String> {
self.0
.id_to_type
.lock()
.get(&str)
.copied()
.or_else(|| {
self.0
.module_globals
.lock()
.get(&str)
.cloned()
.map(|v| v.get_type(primitives, unifier))
})
.ok_or(format!("cannot get type of {str}"))
self.0.id_to_type.lock().get(&str).copied().ok_or(format!("cannot get type of {str}"))
}
fn get_symbol_value<'ctx>(
&self,
str: StrRef,
ctx: &mut CodeGenContext<'ctx, '_>,
generator: &mut dyn CodeGenerator,
_: StrRef,
_: &mut CodeGenContext<'ctx, '_>,
) -> Option<ValueEnum<'ctx>> {
self.0.module_globals.lock().get(&str).cloned().map(|v| {
ctx.module
.get_global(&str.to_string())
.unwrap_or_else(|| {
let ty = v.get_type(&ctx.primitives, &mut ctx.unifier);
let init_val = ctx.gen_symbol_val(generator, &v, ty);
let llvm_ty = init_val.get_type();
let global = ctx.module.add_global(llvm_ty, None, &str.to_string());
global.set_linkage(Linkage::LinkOnceAny);
global.set_initializer(&init_val);
global
})
.as_basic_value_enum()
.into()
})
unimplemented!()
}
fn get_identifier_def(&self, id: StrRef) -> Result<DefinitionId, HashSet<String>> {

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