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@ -1,32 +1,3 @@
|
|||
BasedOnStyle: LLVM
|
||||
|
||||
Language: Cpp
|
||||
Standard: Cpp11
|
||||
|
||||
AccessModifierOffset: -1
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||||
AlignEscapedNewlines: Left
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||||
AlwaysBreakAfterReturnType: None
|
||||
AlwaysBreakTemplateDeclarations: Yes
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AllowAllParametersOfDeclarationOnNextLine: false
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AllowShortFunctionsOnASingleLine: Inline
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||||
BinPackParameters: false
|
||||
BreakBeforeBinaryOperators: NonAssignment
|
||||
BreakBeforeTernaryOperators: true
|
||||
BreakConstructorInitializers: AfterColon
|
||||
BreakInheritanceList: AfterColon
|
||||
ColumnLimit: 120
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||||
ConstructorInitializerAllOnOneLineOrOnePerLine: true
|
||||
ContinuationIndentWidth: 4
|
||||
DerivePointerAlignment: false
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||||
IndentCaseLabels: true
|
||||
IndentPPDirectives: None
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||||
BasedOnStyle: Google
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||||
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MaxEmptyLinesToKeep: 1
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PointerAlignment: Left
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ReflowComments: true
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SortIncludes: false
|
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SortUsingDeclarations: true
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SpaceAfterTemplateKeyword: false
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SpacesBeforeTrailingComments: 2
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TabWidth: 4
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||||
UseTab: Never
|
||||
ReflowComments: false
|
||||
|
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@ -1,4 +1,3 @@
|
|||
__pycache__
|
||||
/target
|
||||
/nac3standalone/demo/linalg/target
|
||||
nix/windows/msys2
|
||||
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|
|
|||
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@ -8,17 +8,17 @@ repos:
|
|||
hooks:
|
||||
- id: nac3-cargo-fmt
|
||||
name: nac3 cargo format
|
||||
entry: nix
|
||||
entry: cargo
|
||||
language: system
|
||||
types: [file, rust]
|
||||
pass_filenames: false
|
||||
description: Runs cargo fmt on the codebase.
|
||||
args: [develop, -c, cargo, fmt, --all]
|
||||
args: [fmt]
|
||||
- id: nac3-cargo-clippy
|
||||
name: nac3 cargo clippy
|
||||
entry: nix
|
||||
entry: cargo
|
||||
language: system
|
||||
types: [file, rust]
|
||||
pass_filenames: false
|
||||
description: Runs cargo clippy on the codebase.
|
||||
args: [develop, -c, cargo, clippy, --tests]
|
||||
args: [clippy, --tests]
|
||||
|
|
|
|||
|
|
@ -60,7 +60,7 @@ version = "1.1.1"
|
|||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "6d36fc52c7f6c869915e99412912f22093507da8d9e942ceaf66fe4b7c14422a"
|
||||
dependencies = [
|
||||
"windows-sys 0.52.0",
|
||||
"windows-sys",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
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@ -70,7 +70,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
|
|||
checksum = "5bf74e1b6e971609db8ca7a9ce79fd5768ab6ae46441c572e46cf596f59e57f8"
|
||||
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|
||||
"anstyle",
|
||||
"windows-sys 0.52.0",
|
||||
"windows-sys",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -90,18 +90,18 @@ checksum = "0c4b4d0bd25bd0b74681c0ad21497610ce1b7c91b1022cd21c80c6fbdd9476b0"
|
|||
|
||||
[[package]]
|
||||
name = "bit-set"
|
||||
version = "0.6.0"
|
||||
version = "0.5.3"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "f0481a0e032742109b1133a095184ee93d88f3dc9e0d28a5d033dc77a073f44f"
|
||||
checksum = "0700ddab506f33b20a03b13996eccd309a48e5ff77d0d95926aa0210fb4e95f1"
|
||||
dependencies = [
|
||||
"bit-vec",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "bit-vec"
|
||||
version = "0.7.0"
|
||||
version = "0.6.3"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
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|
||||
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|
||||
|
||||
[[package]]
|
||||
name = "bitflags"
|
||||
|
|
@ -109,15 +109,6 @@ version = "2.6.0"
|
|||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "b048fb63fd8b5923fc5aa7b340d8e156aec7ec02f0c78fa8a6ddc2613f6f71de"
|
||||
|
||||
[[package]]
|
||||
name = "block-buffer"
|
||||
version = "0.10.4"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "3078c7629b62d3f0439517fa394996acacc5cbc91c5a20d8c658e77abd503a71"
|
||||
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|
||||
"generic-array",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "byteorder"
|
||||
version = "1.5.0"
|
||||
|
|
@ -126,12 +117,9 @@ checksum = "1fd0f2584146f6f2ef48085050886acf353beff7305ebd1ae69500e27c67f64b"
|
|||
|
||||
[[package]]
|
||||
name = "cc"
|
||||
version = "1.1.18"
|
||||
version = "1.1.6"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
[[package]]
|
||||
name = "cfg-if"
|
||||
|
|
@ -141,9 +129,9 @@ checksum = "baf1de4339761588bc0619e3cbc0120ee582ebb74b53b4efbf79117bd2da40fd"
|
|||
|
||||
[[package]]
|
||||
name = "clap"
|
||||
version = "4.5.17"
|
||||
version = "4.5.11"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
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|
||||
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|
||||
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|
||||
"clap_builder",
|
||||
"clap_derive",
|
||||
|
|
@ -151,9 +139,9 @@ dependencies = [
|
|||
|
||||
[[package]]
|
||||
name = "clap_builder"
|
||||
version = "4.5.17"
|
||||
version = "4.5.11"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
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|
||||
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|
||||
dependencies = [
|
||||
"anstream",
|
||||
"anstyle",
|
||||
|
|
@ -163,14 +151,14 @@ dependencies = [
|
|||
|
||||
[[package]]
|
||||
name = "clap_derive"
|
||||
version = "4.5.13"
|
||||
version = "4.5.11"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "501d359d5f3dcaf6ecdeee48833ae73ec6e42723a1e52419c79abf9507eec0a0"
|
||||
checksum = "5d029b67f89d30bbb547c89fd5161293c0aec155fc691d7924b64550662db93e"
|
||||
dependencies = [
|
||||
"heck 0.5.0",
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.77",
|
||||
"syn 2.0.72",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -194,16 +182,7 @@ dependencies = [
|
|||
"encode_unicode",
|
||||
"lazy_static",
|
||||
"libc",
|
||||
"windows-sys 0.52.0",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "cpufeatures"
|
||||
version = "0.2.14"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "608697df725056feaccfa42cffdaeeec3fccc4ffc38358ecd19b243e716a78e0"
|
||||
dependencies = [
|
||||
"libc",
|
||||
"windows-sys",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -263,24 +242,10 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
|
|||
checksum = "22ec99545bb0ed0ea7bb9b8e1e9122ea386ff8a48c0922e43f36d45ab09e0e80"
|
||||
|
||||
[[package]]
|
||||
name = "crypto-common"
|
||||
version = "0.1.6"
|
||||
name = "crunchy"
|
||||
version = "0.2.2"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
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|
||||
dependencies = [
|
||||
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|
||||
"typenum",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "digest"
|
||||
version = "0.10.7"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "9ed9a281f7bc9b7576e61468ba615a66a5c8cfdff42420a70aa82701a3b1e292"
|
||||
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|
||||
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|
||||
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||||
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|
||||
checksum = "7a81dae078cea95a014a339291cec439d2f232ebe854a9d672b796c6afafa9b7"
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||||
|
||||
[[package]]
|
||||
name = "dirs-next"
|
||||
|
|
@ -337,14 +302,14 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
|
|||
checksum = "534c5cf6194dfab3db3242765c03bbe257cf92f22b38f6bc0c58d59108a820ba"
|
||||
dependencies = [
|
||||
"libc",
|
||||
"windows-sys 0.52.0",
|
||||
"windows-sys",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "fastrand"
|
||||
version = "2.1.1"
|
||||
version = "2.1.0"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "e8c02a5121d4ea3eb16a80748c74f5549a5665e4c21333c6098f283870fbdea6"
|
||||
checksum = "9fc0510504f03c51ada170672ac806f1f105a88aa97a5281117e1ddc3368e51a"
|
||||
|
||||
[[package]]
|
||||
name = "fixedbitset"
|
||||
|
|
@ -361,16 +326,6 @@ dependencies = [
|
|||
"byteorder",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "generic-array"
|
||||
version = "0.14.7"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "85649ca51fd72272d7821adaf274ad91c288277713d9c18820d8499a7ff69e9a"
|
||||
dependencies = [
|
||||
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|
||||
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|
||||
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|
||||
|
||||
[[package]]
|
||||
name = "getopts"
|
||||
version = "0.2.21"
|
||||
|
|
@ -430,9 +385,9 @@ dependencies = [
|
|||
|
||||
[[package]]
|
||||
name = "indexmap"
|
||||
version = "2.5.0"
|
||||
version = "2.2.6"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
@ -446,9 +401,9 @@ checksum = "b248f5224d1d606005e02c97f5aa4e88eeb230488bcc03bc9ca4d7991399f2b5"
|
|||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
|
|
@ -460,13 +415,13 @@ dependencies = [
|
|||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
[[package]]
|
||||
|
|
@ -489,6 +444,15 @@ version = "1.70.1"
|
|||
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|
||||
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|
||||
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|
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|
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|
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||||
|
|
@ -504,42 +468,33 @@ version = "1.0.11"
|
|||
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|
||||
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|
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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||||
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|
||||
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||||
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|
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|
|
@ -552,9 +507,9 @@ checksum = "bbd2bcb4c963f2ddae06a2efc7e9f3591312473c50c6685e1f298068316e66fe"
|
|||
|
||||
[[package]]
|
||||
name = "libc"
|
||||
version = "0.2.158"
|
||||
version = "0.2.155"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "d8adc4bb1803a324070e64a98ae98f38934d91957a99cfb3a43dcbc01bc56439"
|
||||
checksum = "97b3888a4aecf77e811145cadf6eef5901f4782c53886191b2f693f24761847c"
|
||||
|
||||
[[package]]
|
||||
name = "libloading"
|
||||
|
|
@ -636,9 +591,11 @@ dependencies = [
|
|||
name = "nac3artiq"
|
||||
version = "0.1.0"
|
||||
dependencies = [
|
||||
"itertools",
|
||||
"inkwell",
|
||||
"itertools 0.13.0",
|
||||
"nac3core",
|
||||
"nac3ld",
|
||||
"nac3parser",
|
||||
"parking_lot",
|
||||
"pyo3",
|
||||
"tempfile",
|
||||
|
|
@ -659,11 +616,11 @@ name = "nac3core"
|
|||
version = "0.1.0"
|
||||
dependencies = [
|
||||
"crossbeam",
|
||||
"indexmap 2.5.0",
|
||||
"indexmap 2.2.6",
|
||||
"indoc",
|
||||
"inkwell",
|
||||
"insta",
|
||||
"itertools",
|
||||
"itertools 0.13.0",
|
||||
"nac3parser",
|
||||
"parking_lot",
|
||||
"rayon",
|
||||
|
|
@ -701,7 +658,9 @@ name = "nac3standalone"
|
|||
version = "0.1.0"
|
||||
dependencies = [
|
||||
"clap",
|
||||
"inkwell",
|
||||
"nac3core",
|
||||
"nac3parser",
|
||||
"parking_lot",
|
||||
]
|
||||
|
||||
|
|
@ -747,7 +706,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
|
|||
checksum = "b4c5cc86750666a3ed20bdaf5ca2a0344f9c67674cae0515bec2da16fbaa47db"
|
||||
dependencies = [
|
||||
"fixedbitset",
|
||||
"indexmap 2.5.0",
|
||||
"indexmap 2.2.6",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -790,7 +749,7 @@ dependencies = [
|
|||
"phf_shared 0.11.2",
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.77",
|
||||
"syn 2.0.72",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -825,12 +784,9 @@ checksum = "da544ee218f0d287a911e9c99a39a8c9bc8fcad3cb8db5959940044ecfc67265"
|
|||
|
||||
[[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"
|
||||
|
|
@ -894,7 +850,7 @@ dependencies = [
|
|||
"proc-macro2",
|
||||
"pyo3-macros-backend",
|
||||
"quote",
|
||||
"syn 2.0.77",
|
||||
"syn 2.0.72",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -907,14 +863,14 @@ dependencies = [
|
|||
"proc-macro2",
|
||||
"pyo3-build-config",
|
||||
"quote",
|
||||
"syn 2.0.77",
|
||||
"syn 2.0.72",
|
||||
]
|
||||
|
||||
[[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",
|
||||
]
|
||||
|
|
@ -971,18 +927,18 @@ dependencies = [
|
|||
|
||||
[[package]]
|
||||
name = "redox_syscall"
|
||||
version = "0.5.4"
|
||||
version = "0.5.3"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "0884ad60e090bf1345b93da0a5de8923c93884cd03f40dfcfddd3b4bee661853"
|
||||
checksum = "2a908a6e00f1fdd0dfd9c0eb08ce85126f6d8bbda50017e74bc4a4b7d4a926a4"
|
||||
dependencies = [
|
||||
"bitflags",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "redox_users"
|
||||
version = "0.4.6"
|
||||
version = "0.4.5"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "ba009ff324d1fc1b900bd1fdb31564febe58a8ccc8a6fdbb93b543d33b13ca43"
|
||||
checksum = "bd283d9651eeda4b2a83a43c1c91b266c40fd76ecd39a50a8c630ae69dc72891"
|
||||
dependencies = [
|
||||
"getrandom",
|
||||
"libredox",
|
||||
|
|
@ -991,9 +947,9 @@ dependencies = [
|
|||
|
||||
[[package]]
|
||||
name = "regex"
|
||||
version = "1.10.6"
|
||||
version = "1.10.5"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "4219d74c6b67a3654a9fbebc4b419e22126d13d2f3c4a07ee0cb61ff79a79619"
|
||||
checksum = "b91213439dad192326a0d7c6ee3955910425f441d7038e0d6933b0aec5c4517f"
|
||||
dependencies = [
|
||||
"aho-corasick",
|
||||
"memchr",
|
||||
|
|
@ -1027,15 +983,15 @@ dependencies = [
|
|||
|
||||
[[package]]
|
||||
name = "rustix"
|
||||
version = "0.38.37"
|
||||
version = "0.38.34"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "8acb788b847c24f28525660c4d7758620a7210875711f79e7f663cc152726811"
|
||||
checksum = "70dc5ec042f7a43c4a73241207cecc9873a06d45debb38b329f8541d85c2730f"
|
||||
dependencies = [
|
||||
"bitflags",
|
||||
"errno",
|
||||
"libc",
|
||||
"linux-raw-sys",
|
||||
"windows-sys 0.52.0",
|
||||
"windows-sys",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -1073,32 +1029,31 @@ checksum = "61697e0a1c7e512e84a621326239844a24d8207b4669b41bc18b32ea5cbf988b"
|
|||
|
||||
[[package]]
|
||||
name = "serde"
|
||||
version = "1.0.210"
|
||||
version = "1.0.204"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "c8e3592472072e6e22e0a54d5904d9febf8508f65fb8552499a1abc7d1078c3a"
|
||||
checksum = "bc76f558e0cbb2a839d37354c575f1dc3fdc6546b5be373ba43d95f231bf7c12"
|
||||
dependencies = [
|
||||
"serde_derive",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "serde_derive"
|
||||
version = "1.0.210"
|
||||
version = "1.0.204"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "243902eda00fad750862fc144cea25caca5e20d615af0a81bee94ca738f1df1f"
|
||||
checksum = "e0cd7e117be63d3c3678776753929474f3b04a43a080c744d6b0ae2a8c28e222"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.77",
|
||||
"syn 2.0.72",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "serde_json"
|
||||
version = "1.0.128"
|
||||
version = "1.0.120"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "6ff5456707a1de34e7e37f2a6fd3d3f808c318259cbd01ab6377795054b483d8"
|
||||
checksum = "4e0d21c9a8cae1235ad58a00c11cb40d4b1e5c784f1ef2c537876ed6ffd8b7c5"
|
||||
dependencies = [
|
||||
"itoa",
|
||||
"memchr",
|
||||
"ryu",
|
||||
"serde",
|
||||
]
|
||||
|
|
@ -1115,22 +1070,6 @@ 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"
|
||||
|
|
@ -1195,7 +1134,7 @@ dependencies = [
|
|||
"proc-macro2",
|
||||
"quote",
|
||||
"rustversion",
|
||||
"syn 2.0.77",
|
||||
"syn 2.0.72",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -1211,9 +1150,9 @@ dependencies = [
|
|||
|
||||
[[package]]
|
||||
name = "syn"
|
||||
version = "2.0.77"
|
||||
version = "2.0.72"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "9f35bcdf61fd8e7be6caf75f429fdca8beb3ed76584befb503b1569faee373ed"
|
||||
checksum = "dc4b9b9bf2add8093d3f2c0204471e951b2285580335de42f9d2534f3ae7a8af"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
|
|
@ -1222,21 +1161,20 @@ 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 = "3.12.0"
|
||||
version = "3.10.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "04cbcdd0c794ebb0d4cf35e88edd2f7d2c4c3e9a5a6dab322839b321c6a87a64"
|
||||
checksum = "85b77fafb263dd9d05cbeac119526425676db3784113aa9295c88498cbf8bff1"
|
||||
dependencies = [
|
||||
"cfg-if",
|
||||
"fastrand",
|
||||
"once_cell",
|
||||
"rustix",
|
||||
"windows-sys 0.59.0",
|
||||
"windows-sys",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -1280,14 +1218,17 @@ checksum = "a4558b58466b9ad7ca0f102865eccc95938dca1a74a856f2b57b6629050da261"
|
|||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.77",
|
||||
"syn 2.0.72",
|
||||
]
|
||||
|
||||
[[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"
|
||||
|
|
@ -1343,9 +1284,9 @@ 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"
|
||||
|
|
@ -1355,15 +1296,15 @@ checksum = "0336d538f7abc86d282a4189614dfaa90810dfc2c6f6427eaf88e16311dd225d"
|
|||
|
||||
[[package]]
|
||||
name = "unicode-xid"
|
||||
version = "0.2.5"
|
||||
version = "0.2.4"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "229730647fbc343e3a80e463c1db7f78f3855d3f3739bee0dda773c9a037c90a"
|
||||
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",
|
||||
|
|
@ -1371,9 +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",
|
||||
|
|
@ -1433,11 +1374,11 @@ checksum = "ac3b87c63620426dd9b991e5ce0329eff545bccbbb34f3be09ff6fb6ab51b7b6"
|
|||
|
||||
[[package]]
|
||||
name = "winapi-util"
|
||||
version = "0.1.9"
|
||||
version = "0.1.8"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "cf221c93e13a30d793f7645a0e7762c55d169dbb0a49671918a2319d289b10bb"
|
||||
checksum = "4d4cc384e1e73b93bafa6fb4f1df8c41695c8a91cf9c4c64358067d15a7b6c6b"
|
||||
dependencies = [
|
||||
"windows-sys 0.59.0",
|
||||
"windows-sys",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -1455,15 +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"
|
||||
|
|
@ -1543,7 +1475,6 @@ version = "0.7.35"
|
|||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "1b9b4fd18abc82b8136838da5d50bae7bdea537c574d8dc1a34ed098d6c166f0"
|
||||
dependencies = [
|
||||
"byteorder",
|
||||
"zerocopy-derive",
|
||||
]
|
||||
|
||||
|
|
@ -1555,5 +1486,5 @@ checksum = "fa4f8080344d4671fb4e831a13ad1e68092748387dfc4f55e356242fae12ce3e"
|
|||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.77",
|
||||
"syn 2.0.72",
|
||||
]
|
||||
|
|
|
|||
|
|
@ -2,11 +2,11 @@
|
|||
"nodes": {
|
||||
"nixpkgs": {
|
||||
"locked": {
|
||||
"lastModified": 1725432240,
|
||||
"narHash": "sha256-+yj+xgsfZaErbfYM3T+QvEE2hU7UuE+Jf0fJCJ8uPS0=",
|
||||
"lastModified": 1721924956,
|
||||
"narHash": "sha256-Sb1jlyRO+N8jBXEX9Pg9Z1Qb8Bw9QyOgLDNMEpmjZ2M=",
|
||||
"owner": "NixOS",
|
||||
"repo": "nixpkgs",
|
||||
"rev": "ad416d066ca1222956472ab7d0555a6946746a80",
|
||||
"rev": "5ad6a14c6bf098e98800b091668718c336effc95",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
|
|
|
|||
28
flake.nix
28
flake.nix
|
|
@ -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 $out/bin/llvm-as-irrt
|
||||
'';
|
||||
demo-linalg-stub = pkgs.rustPlatform.buildRustPackage {
|
||||
name = "demo-linalg-stub";
|
||||
src = ./nac3standalone/demo/linalg;
|
||||
cargoLock = {
|
||||
lockFile = ./nac3standalone/demo/linalg/Cargo.lock;
|
||||
};
|
||||
doCheck = false;
|
||||
};
|
||||
demo-linalg-stub32 = pkgs32.rustPlatform.buildRustPackage {
|
||||
name = "demo-linalg-stub32";
|
||||
src = ./nac3standalone/demo/linalg;
|
||||
cargoLock = {
|
||||
lockFile = ./nac3standalone/demo/linalg/Cargo.lock;
|
||||
};
|
||||
doCheck = false;
|
||||
};
|
||||
nac3artiq = pkgs.python3Packages.toPythonModule (
|
||||
pkgs.rustPlatform.buildRustPackage rec {
|
||||
name = "nac3artiq";
|
||||
|
|
@ -40,6 +24,7 @@
|
|||
cargoLock = {
|
||||
lockFile = ./Cargo.lock;
|
||||
};
|
||||
cargoTestFlags = [ "--features" "test" ];
|
||||
passthru.cargoLock = cargoLock;
|
||||
nativeBuildInputs = [ pkgs.python3 (pkgs.wrapClangMulti pkgs.llvmPackages_14.clang) llvm-tools-irrt pkgs.llvmPackages_14.llvm.out llvm-nac3 ];
|
||||
buildInputs = [ pkgs.python3 llvm-nac3 ];
|
||||
|
|
@ -49,9 +34,7 @@
|
|||
echo "Checking nac3standalone demos..."
|
||||
pushd nac3standalone/demo
|
||||
patchShebangs .
|
||||
export DEMO_LINALG_STUB=${demo-linalg-stub}/lib/liblinalg.a
|
||||
export DEMO_LINALG_STUB32=${demo-linalg-stub32}/lib/liblinalg.a
|
||||
./check_demos.sh -i686
|
||||
./check_demos.sh
|
||||
popd
|
||||
echo "Running Cargo tests..."
|
||||
cargoCheckHook
|
||||
|
|
@ -181,11 +164,6 @@
|
|||
pre-commit
|
||||
rustfmt
|
||||
];
|
||||
shellHook =
|
||||
''
|
||||
export DEMO_LINALG_STUB=${packages.x86_64-linux.demo-linalg-stub}/lib/liblinalg.a
|
||||
export DEMO_LINALG_STUB32=${packages.x86_64-linux.demo-linalg-stub32}/lib/liblinalg.a
|
||||
'';
|
||||
};
|
||||
devShells.x86_64-linux.msys2 = pkgs.mkShell {
|
||||
name = "nac3-dev-shell-msys2";
|
||||
|
|
|
|||
|
|
@ -13,9 +13,14 @@ itertools = "0.13"
|
|||
pyo3 = { version = "0.21", features = ["extension-module", "gil-refs"] }
|
||||
parking_lot = "0.12"
|
||||
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"]
|
||||
|
|
|
|||
|
|
@ -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."""
|
||||
|
|
|
|||
|
|
@ -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
|
|
@ -23,9 +23,7 @@ use std::process::Command;
|
|||
use std::rc::Rc;
|
||||
use std::sync::Arc;
|
||||
|
||||
use itertools::Itertools;
|
||||
use nac3core::codegen::{gen_func_impl, CodeGenLLVMOptions, CodeGenTargetMachineOptions};
|
||||
use nac3core::inkwell::{
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
memory_buffer::MemoryBuffer,
|
||||
module::{Linkage, Module},
|
||||
|
|
@ -34,10 +32,12 @@ use nac3core::inkwell::{
|
|||
targets::*,
|
||||
OptimizationLevel,
|
||||
};
|
||||
use itertools::Itertools;
|
||||
use nac3core::codegen::{gen_func_impl, CodeGenLLVMOptions, CodeGenTargetMachineOptions};
|
||||
use nac3core::toplevel::builtins::get_exn_constructor;
|
||||
use nac3core::typecheck::typedef::{into_var_map, TypeEnum, Unifier, VarMap};
|
||||
use nac3core::nac3parser::{
|
||||
ast::{Constant, ExprKind, Located, Stmt, StmtKind, StrRef},
|
||||
use nac3core::typecheck::typedef::{TypeEnum, Unifier, VarMap};
|
||||
use nac3parser::{
|
||||
ast::{ExprKind, Stmt, StmtKind, StrRef},
|
||||
parser::parse_program,
|
||||
};
|
||||
use pyo3::create_exception;
|
||||
|
|
@ -51,7 +51,7 @@ use nac3core::{
|
|||
codegen::{concrete_type::ConcreteTypeStore, CodeGenTask, WithCall, WorkerRegistry},
|
||||
symbol_resolver::SymbolResolver,
|
||||
toplevel::{
|
||||
composer::{BuiltinFuncCreator, BuiltinFuncSpec, ComposerConfig, TopLevelComposer},
|
||||
composer::{ComposerConfig, TopLevelComposer},
|
||||
DefinitionId, GenCall, TopLevelDef,
|
||||
},
|
||||
typecheck::typedef::{FunSignature, FuncArg},
|
||||
|
|
@ -60,13 +60,13 @@ use nac3core::{
|
|||
|
||||
use nac3ld::Linker;
|
||||
|
||||
use tempfile::{self, TempDir};
|
||||
|
||||
use crate::codegen::attributes_writeback;
|
||||
use crate::{
|
||||
codegen::{
|
||||
attributes_writeback, gen_core_log, gen_rtio_log, rpc_codegen_callback, ArtiqCodeGenerator,
|
||||
},
|
||||
codegen::{rpc_codegen_callback, ArtiqCodeGenerator},
|
||||
symbol_resolver::{DeferredEvaluationStore, InnerResolver, PythonHelper, Resolver},
|
||||
};
|
||||
use tempfile::{self, TempDir};
|
||||
|
||||
mod codegen;
|
||||
mod symbol_resolver;
|
||||
|
|
@ -127,7 +127,7 @@ 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,
|
||||
|
|
@ -194,8 +194,10 @@ 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
|
||||
}
|
||||
|
|
@ -208,8 +210,9 @@ 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
|
||||
}
|
||||
|
|
@ -262,7 +265,7 @@ 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() => {
|
||||
|
|
@ -298,64 +301,6 @@ 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,
|
||||
|
|
@ -368,7 +313,6 @@ 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,
|
||||
);
|
||||
|
|
@ -445,6 +389,7 @@ 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(),
|
||||
|
|
@ -475,25 +420,9 @@ 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, .. } => {
|
||||
|
|
@ -501,26 +430,19 @@ 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();
|
||||
|
|
@ -559,6 +481,7 @@ 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(),
|
||||
|
|
@ -575,10 +498,6 @@ 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();
|
||||
|
|
@ -616,12 +535,13 @@ 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();
|
||||
|
|
@ -632,7 +552,7 @@ 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,
|
||||
|
|
@ -706,7 +626,7 @@ impl Nac3 {
|
|||
let buffer = buffer.as_slice().into();
|
||||
membuffer.lock().push(buffer);
|
||||
})));
|
||||
let size_t = context
|
||||
let size_t = Context::create()
|
||||
.ptr_sized_int_type(&self.get_llvm_target_machine().get_target_data(), None)
|
||||
.get_bit_width();
|
||||
let num_threads = if is_multithreaded() { 4 } else { 1 };
|
||||
|
|
@ -725,7 +645,7 @@ 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());
|
||||
|
|
@ -748,7 +668,7 @@ 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"))
|
||||
|
|
@ -777,7 +697,8 @@ 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 {
|
||||
|
|
@ -863,41 +784,6 @@ 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(),
|
||||
|
|
@ -967,7 +853,7 @@ 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(),
|
||||
|
|
@ -983,7 +869,6 @@ impl Nac3 {
|
|||
name: "t".into(),
|
||||
ty: primitive.int64,
|
||||
default_value: None,
|
||||
is_vararg: false,
|
||||
}],
|
||||
ret: primitive.none,
|
||||
vars: VarMap::new(),
|
||||
|
|
@ -1003,7 +888,6 @@ impl Nac3 {
|
|||
name: "dt".into(),
|
||||
ty: primitive.int64,
|
||||
default_value: None,
|
||||
is_vararg: false,
|
||||
}],
|
||||
ret: primitive.none,
|
||||
vars: VarMap::new(),
|
||||
|
|
|
|||
|
|
@ -1,12 +1,9 @@
|
|||
use crate::PrimitivePythonId;
|
||||
use itertools::Itertools;
|
||||
use nac3core::inkwell::{
|
||||
module::Linkage,
|
||||
use inkwell::{
|
||||
types::{BasicType, BasicTypeEnum},
|
||||
values::BasicValueEnum,
|
||||
AddressSpace,
|
||||
};
|
||||
use nac3core::nac3parser::ast::{self, StrRef};
|
||||
use itertools::Itertools;
|
||||
use nac3core::{
|
||||
codegen::{
|
||||
classes::{NDArrayType, ProxyType},
|
||||
|
|
@ -23,7 +20,8 @@ use nac3core::{
|
|||
typedef::{into_var_map, iter_type_vars, Type, TypeEnum, TypeVar, Unifier, VarMap},
|
||||
},
|
||||
};
|
||||
use parking_lot::RwLock;
|
||||
use nac3parser::ast::{self, StrRef};
|
||||
use parking_lot::{Mutex, RwLock};
|
||||
use pyo3::{
|
||||
types::{PyDict, PyTuple},
|
||||
PyAny, PyObject, PyResult, Python,
|
||||
|
|
@ -36,6 +34,8 @@ use std::{
|
|||
},
|
||||
};
|
||||
|
||||
use crate::PrimitivePythonId;
|
||||
|
||||
pub enum PrimitiveValue {
|
||||
I32(i32),
|
||||
I64(i64),
|
||||
|
|
@ -79,6 +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,
|
||||
|
|
@ -132,8 +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,
|
||||
|
|
@ -164,7 +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()) {
|
||||
|
|
@ -352,7 +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 {
|
||||
|
|
@ -556,10 +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 = {
|
||||
|
|
@ -801,9 +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
|
||||
|
|
@ -978,7 +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));
|
||||
|
|
@ -1209,9 +1203,7 @@ 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()?;
|
||||
|
|
|
|||
|
|
@ -1,9 +1,9 @@
|
|||
use itertools::Either;
|
||||
use nac3core::codegen::CodeGenContext;
|
||||
use nac3core::inkwell::{
|
||||
use inkwell::{
|
||||
values::{BasicValueEnum, CallSiteValue},
|
||||
AddressSpace, AtomicOrdering,
|
||||
};
|
||||
use itertools::Either;
|
||||
use nac3core::codegen::CodeGenContext;
|
||||
|
||||
/// Functions for manipulating the timeline.
|
||||
pub trait TimeFns {
|
||||
|
|
@ -31,7 +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();
|
||||
|
||||
|
|
@ -80,7 +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();
|
||||
|
||||
|
|
@ -109,7 +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();
|
||||
|
||||
|
|
@ -207,7 +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();
|
||||
|
||||
|
|
@ -258,7 +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();
|
||||
|
||||
|
|
|
|||
|
|
@ -1,12 +1,12 @@
|
|||
[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"
|
||||
|
|
@ -14,13 +14,13 @@ indexmap = "2.2"
|
|||
parking_lot = "0.12"
|
||||
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"
|
||||
|
|
|
|||
|
|
@ -3,29 +3,44 @@ use std::{
|
|||
env,
|
||||
fs::File,
|
||||
io::Write,
|
||||
path::Path,
|
||||
path::{Path, PathBuf},
|
||||
process::{Command, Stdio},
|
||||
};
|
||||
|
||||
fn main() {
|
||||
let out_dir = env::var("OUT_DIR").unwrap();
|
||||
let out_dir = Path::new(&out_dir);
|
||||
let irrt_dir = Path::new("irrt");
|
||||
const CMD_IRRT_CLANG: &str = "clang-irrt";
|
||||
const CMD_IRRT_CLANG_TEST: &str = "clang-irrt-test";
|
||||
const CMD_IRRT_LLVM_AS: &str = "llvm-as-irrt";
|
||||
|
||||
let irrt_cpp_path = irrt_dir.join("irrt.cpp");
|
||||
fn get_out_dir() -> PathBuf {
|
||||
PathBuf::from(env::var("OUT_DIR").unwrap())
|
||||
}
|
||||
|
||||
fn get_irrt_dir() -> &'static Path {
|
||||
Path::new("irrt")
|
||||
}
|
||||
|
||||
/// Compile `irrt.cpp` for use in `src/codegen`
|
||||
fn compile_irrt_cpp() {
|
||||
let out_dir = get_out_dir();
|
||||
let irrt_dir = get_irrt_dir();
|
||||
|
||||
/*
|
||||
* 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 irrt_cpp_path = irrt_dir.join("irrt.cpp");
|
||||
let flags: &[&str] = &[
|
||||
"--target=wasm32",
|
||||
"-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",
|
||||
|
|
@ -37,22 +52,11 @@ fn main() {
|
|||
irrt_cpp_path.to_str().unwrap(),
|
||||
];
|
||||
|
||||
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:?}"),
|
||||
}
|
||||
|
||||
// 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")
|
||||
let output = Command::new(CMD_IRRT_CLANG)
|
||||
.args(flags)
|
||||
.output()
|
||||
.map(|o| {
|
||||
|
|
@ -98,7 +102,9 @@ fn main() {
|
|||
file.write_all(filtered_output.as_bytes()).unwrap();
|
||||
}
|
||||
|
||||
let mut llvm_as = Command::new("llvm-as-irrt")
|
||||
// Assemble the emitted and filtered IR to .bc
|
||||
// That .bc will be integrated into nac3core's codegen
|
||||
let mut llvm_as = Command::new(CMD_IRRT_LLVM_AS)
|
||||
.stdin(Stdio::piped())
|
||||
.arg("-o")
|
||||
.arg(out_dir.join("irrt.bc"))
|
||||
|
|
@ -107,3 +113,48 @@ fn main() {
|
|||
llvm_as.stdin.as_mut().unwrap().write_all(filtered_output.as_bytes()).unwrap();
|
||||
assert!(llvm_as.wait().unwrap().success());
|
||||
}
|
||||
|
||||
/// Compile `irrt_test.cpp` for testing
|
||||
fn compile_irrt_test_cpp() {
|
||||
let out_dir = get_out_dir();
|
||||
let irrt_dir = get_irrt_dir();
|
||||
|
||||
let exe_path = out_dir.join("irrt_test.out"); // Output path of the compiled test executable
|
||||
let irrt_test_cpp_path = irrt_dir.join("irrt_test.cpp");
|
||||
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(CMD_IRRT_CLANG_TEST)
|
||||
.args(flags)
|
||||
.output()
|
||||
.map(|o| {
|
||||
assert!(o.status.success(), "{}", std::str::from_utf8(&o.stderr).unwrap());
|
||||
o
|
||||
})
|
||||
.unwrap();
|
||||
println!("cargo:rerun-if-changed={}", irrt_dir.to_str().unwrap());
|
||||
}
|
||||
|
||||
fn main() {
|
||||
compile_irrt_cpp();
|
||||
|
||||
// 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_cpp();
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1,6 +1,10 @@
|
|||
#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"
|
||||
#define IRRT_DEFINE_TYPEDEF_INTS
|
||||
#include <irrt_everything.hpp>
|
||||
|
||||
/*
|
||||
* All IRRT implementations.
|
||||
*
|
||||
* We don't have 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.
|
||||
*/
|
||||
|
|
@ -0,0 +1,39 @@
|
|||
#pragma once
|
||||
|
||||
#include <irrt/int_defs.hpp>
|
||||
|
||||
/*
|
||||
This file defines all ARTIQ-specific structures
|
||||
*/
|
||||
|
||||
/**
|
||||
* @brief ARTIQ's `cslice` object
|
||||
*
|
||||
* See https://docs.rs/cslice/0.3.0/src/cslice/lib.rs.html#33-37
|
||||
*/
|
||||
template <typename SizeT>
|
||||
struct CSlice {
|
||||
const char *base;
|
||||
SizeT len;
|
||||
};
|
||||
|
||||
/**
|
||||
* @brief Int type of ARTIQ's `Exception` IDs.
|
||||
*/
|
||||
typedef uint32_t ExceptionId;
|
||||
|
||||
/**
|
||||
* @brief ARTIQ's `Exception` object
|
||||
*
|
||||
* See https://github.com/m-labs/artiq/blob/b0d2705c385f64b6e6711c1726cd9178f40b598e/artiq/firmware/libeh/eh_artiq.rs#L1C1-L17C1
|
||||
*/
|
||||
template <typename SizeT>
|
||||
struct Exception {
|
||||
ExceptionId id;
|
||||
CSlice<SizeT> file;
|
||||
uint32_t line;
|
||||
uint32_t column;
|
||||
CSlice<SizeT> function;
|
||||
CSlice<SizeT> message;
|
||||
uint32_t param;
|
||||
};
|
||||
|
|
@ -0,0 +1,347 @@
|
|||
#pragma once
|
||||
|
||||
#include <irrt/int_defs.hpp>
|
||||
#include <irrt/slice.hpp>
|
||||
#include <irrt/utils.hpp>
|
||||
|
||||
// NDArray indices are always `uint32_t`.
|
||||
using NDIndexInt = uint32_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;
|
||||
}
|
||||
|
||||
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, NDIndexInt* 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 NDIndexInt* 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 NDIndexInt* in_idx,
|
||||
NDIndexInt* 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" {
|
||||
#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 + size + size + 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, NDIndexInt* 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, NDIndexInt* 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 NDIndexInt* 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 NDIndexInt* 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 NDIndexInt* in_idx,
|
||||
NDIndexInt* 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 NDIndexInt* in_idx,
|
||||
NDIndexInt* out_idx) {
|
||||
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx,
|
||||
out_idx);
|
||||
}
|
||||
} // extern "C"
|
||||
|
|
@ -1,9 +0,0 @@
|
|||
#pragma once
|
||||
|
||||
#include "irrt/int_types.hpp"
|
||||
|
||||
template<typename SizeT>
|
||||
struct CSlice {
|
||||
uint8_t* base;
|
||||
SizeT len;
|
||||
};
|
||||
|
|
@ -1,25 +0,0 @@
|
|||
#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); \
|
||||
} \
|
||||
}
|
||||
|
|
@ -0,0 +1,92 @@
|
|||
#pragma once
|
||||
|
||||
#include <irrt/artiq_defs.hpp>
|
||||
#include <irrt/int_defs.hpp>
|
||||
#include <irrt/utils.hpp>
|
||||
|
||||
namespace {
|
||||
/**
|
||||
* @brief A (limited) set of known Exception IDs usable in IRRT
|
||||
*/
|
||||
struct ErrorContextExceptions {
|
||||
ExceptionId index_error;
|
||||
ExceptionId value_error;
|
||||
ExceptionId assertion_error;
|
||||
ExceptionId runtime_error;
|
||||
ExceptionId type_error;
|
||||
};
|
||||
|
||||
/**
|
||||
* @brief The IRRT error context object
|
||||
*
|
||||
* This object contains all the details needed to propagate Python-like Exceptions in
|
||||
* IRRT - within IRRT itself or propagate out of extern calls from nac3core.
|
||||
*/
|
||||
struct ErrorContext {
|
||||
const ErrorContextExceptions *exceptions;
|
||||
|
||||
// Exception thrown by IRRT
|
||||
ExceptionId exception_id;
|
||||
// Points to empty c-string if there is no thrown Exception
|
||||
const char *msg;
|
||||
uint64_t param1;
|
||||
uint64_t param2;
|
||||
uint64_t param3;
|
||||
|
||||
void initialize(const ErrorContextExceptions *exceptions) {
|
||||
this->exceptions = exceptions;
|
||||
clear_error();
|
||||
}
|
||||
|
||||
void clear_error() {
|
||||
// NOTE: Point the msg to an empty str.
|
||||
// Don't set it to nullptr - to implement `has_exception`
|
||||
this->msg = "";
|
||||
}
|
||||
|
||||
void set_exception(ExceptionId exception_id, const char *msg,
|
||||
uint64_t param1 = 0, uint64_t param2 = 0,
|
||||
uint64_t param3 = 0) {
|
||||
this->exception_id = exception_id;
|
||||
this->msg = msg;
|
||||
this->param1 = param1;
|
||||
this->param2 = param2;
|
||||
this->param3 = param3;
|
||||
}
|
||||
|
||||
bool has_exception() { return !cstr_utils::is_empty(msg); }
|
||||
|
||||
template <typename SizeT>
|
||||
void get_exception_str(CSlice<SizeT> *dst_str) {
|
||||
dst_str->base = msg;
|
||||
dst_str->len = (SizeT)cstr_utils::length(msg);
|
||||
}
|
||||
};
|
||||
} // namespace
|
||||
|
||||
extern "C" {
|
||||
void __nac3_error_context_initialize(ErrorContext *errctx,
|
||||
ErrorContextExceptions *exceptions) {
|
||||
errctx->initialize(exceptions);
|
||||
}
|
||||
|
||||
bool __nac3_error_context_has_exception(ErrorContext *errctx) {
|
||||
return errctx->has_exception();
|
||||
}
|
||||
|
||||
void __nac3_error_context_get_exception_str(ErrorContext *errctx,
|
||||
CSlice<int32_t> *dst_str) {
|
||||
errctx->get_exception_str<int32_t>(dst_str);
|
||||
}
|
||||
|
||||
void __nac3_error_context_get_exception_str64(ErrorContext *errctx,
|
||||
CSlice<int64_t> *dst_str) {
|
||||
errctx->get_exception_str<int64_t>(dst_str);
|
||||
}
|
||||
|
||||
// Used for testing
|
||||
void __nac3_error_dummy_raise(ErrorContext *errctx) {
|
||||
errctx->set_exception(errctx->exceptions->runtime_error,
|
||||
"Error thrown from __nac3_error_dummy_raise");
|
||||
}
|
||||
}
|
||||
|
|
@ -1,82 +0,0 @@
|
|||
#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
|
||||
|
|
@ -0,0 +1,12 @@
|
|||
#pragma once
|
||||
|
||||
// This is made toggleable since `irrt_test.cpp` itself would include
|
||||
// headers that define these typedefs
|
||||
#ifdef IRRT_DEFINE_TYPEDEF_INTS
|
||||
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);
|
||||
#endif
|
||||
|
|
@ -1,22 +0,0 @@
|
|||
#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;
|
||||
|
|
@ -1,75 +0,0 @@
|
|||
#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"
|
||||
|
|
@ -1,93 +0,0 @@
|
|||
#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);
|
||||
}
|
||||
}
|
||||
|
|
@ -1,13 +0,0 @@
|
|||
#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
|
||||
|
|
@ -1,144 +0,0 @@
|
|||
#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);
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,315 @@
|
|||
#pragma once
|
||||
|
||||
#include <irrt/error_context.hpp>
|
||||
#include <irrt/int_defs.hpp>
|
||||
#include <irrt/ndarray/def.hpp>
|
||||
|
||||
namespace {
|
||||
namespace ndarray {
|
||||
namespace basic {
|
||||
namespace util {
|
||||
/**
|
||||
* @brief Asserts that `shape` does not contain negative dimensions.
|
||||
*
|
||||
* @param ndims Number of dimensions in `shape`
|
||||
* @param shape The shape to check on
|
||||
*/
|
||||
template <typename SizeT>
|
||||
void assert_shape_no_negative(ErrorContext* errctx, SizeT ndims,
|
||||
const SizeT* shape) {
|
||||
for (SizeT axis = 0; axis < ndims; axis++) {
|
||||
if (shape[axis] < 0) {
|
||||
errctx->set_exception(
|
||||
errctx->exceptions->value_error,
|
||||
"negative dimensions are not allowed; axis {0} "
|
||||
"has dimension {1}",
|
||||
axis, shape[axis]);
|
||||
return;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Returns the number of elements of an ndarray given its shape.
|
||||
*
|
||||
* @param ndims Number of dimensions in `shape`
|
||||
* @param shape The shape of the ndarray
|
||||
*/
|
||||
template <typename SizeT>
|
||||
SizeT calc_size_from_shape(SizeT ndims, const SizeT* shape) {
|
||||
SizeT size = 1;
|
||||
for (SizeT axis = 0; axis < ndims; axis++) size *= shape[axis];
|
||||
return size;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Compute the array indices of the `nth` (0-based) element of an ndarray given only its shape.
|
||||
*
|
||||
* @param ndims Number of elements in `shape` and `indices`
|
||||
* @param shape The shape of the ndarray
|
||||
* @param indices The returned indices indexing the ndarray with shape `shape`.
|
||||
* @param nth The index of the element of interest.
|
||||
*/
|
||||
template <typename SizeT>
|
||||
void set_indices_by_nth(SizeT ndims, const SizeT* shape, SizeT* indices,
|
||||
SizeT nth) {
|
||||
for (int32_t i = 0; i < ndims; i++) {
|
||||
int32_t axis = ndims - i - 1;
|
||||
int32_t dim = shape[axis];
|
||||
|
||||
indices[axis] = nth % dim;
|
||||
nth /= dim;
|
||||
}
|
||||
}
|
||||
} // namespace util
|
||||
|
||||
/**
|
||||
* @brief Return the number of elements of an `ndarray`
|
||||
*
|
||||
* This function corresponds to `<an_ndarray>.size`
|
||||
*/
|
||||
template <typename SizeT>
|
||||
SizeT size(const NDArray<SizeT>* ndarray) {
|
||||
return util::calc_size_from_shape(ndarray->ndims, ndarray->shape);
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Return of the number of its content of an `ndarray`.
|
||||
*
|
||||
* This function corresponds to `<an_ndarray>.nbytes`.
|
||||
*/
|
||||
template <typename SizeT>
|
||||
SizeT nbytes(const NDArray<SizeT>* ndarray) {
|
||||
return size(ndarray) * ndarray->itemsize;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Update the strides of an ndarray given an ndarray `shape`
|
||||
* and assuming that the ndarray is fully c-contagious.
|
||||
*
|
||||
* You might want to read https://ajcr.net/stride-guide-part-1/.
|
||||
*/
|
||||
template <typename SizeT>
|
||||
void set_strides_by_shape(NDArray<SizeT>* ndarray) {
|
||||
SizeT stride_product = 1;
|
||||
for (SizeT i = 0; i < ndarray->ndims; i++) {
|
||||
int axis = ndarray->ndims - i - 1;
|
||||
ndarray->strides[axis] = stride_product * ndarray->itemsize;
|
||||
stride_product *= ndarray->shape[axis];
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Return the pointer to the element indexed by `indices`.
|
||||
*/
|
||||
template <typename SizeT>
|
||||
uint8_t* get_pelement_by_indices(const NDArray<SizeT>* ndarray,
|
||||
const SizeT* indices) {
|
||||
uint8_t* element = ndarray->data;
|
||||
for (SizeT dim_i = 0; dim_i < ndarray->ndims; dim_i++)
|
||||
element += indices[dim_i] * ndarray->strides[dim_i];
|
||||
return element;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Return the pointer to the nth (0-based) element in a flattened view of `ndarray`.
|
||||
*/
|
||||
template <typename SizeT>
|
||||
uint8_t* get_nth_pelement(const NDArray<SizeT>* ndarray, SizeT nth) {
|
||||
SizeT* indices = (SizeT*)__builtin_alloca(sizeof(SizeT) * ndarray->ndims);
|
||||
util::set_indices_by_nth(ndarray->ndims, ndarray->shape, indices, nth);
|
||||
return get_pelement_by_indices(ndarray, indices);
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Like `get_nth_pelement` but asserts that `nth` is in bounds.
|
||||
*/
|
||||
template <typename SizeT>
|
||||
uint8_t* checked_get_nth_pelement(ErrorContext* errctx,
|
||||
const NDArray<SizeT>* ndarray, SizeT nth) {
|
||||
SizeT arr_size = ndarray->size();
|
||||
if (!(0 <= nth && nth < arr_size)) {
|
||||
errctx->set_exception(
|
||||
errctx->exceptions->index_error,
|
||||
"index {0} is out of bounds, valid range is {1} <= index < {2}",
|
||||
nth, 0, arr_size);
|
||||
return 0;
|
||||
}
|
||||
return get_nth_pelement(ndarray, nth);
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Set an element in `ndarray`.
|
||||
*
|
||||
* @param pelement Pointer to the element in `ndarray` to be set.
|
||||
* @param pvalue Pointer to the value `pelement` will be set to.
|
||||
*/
|
||||
template <typename SizeT>
|
||||
void set_pelement_value(NDArray<SizeT>* ndarray, uint8_t* pelement,
|
||||
const uint8_t* pvalue) {
|
||||
__builtin_memcpy(pelement, pvalue, ndarray->itemsize);
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Get the `len()` of an ndarray, and asserts that `ndarray` is a sized object.
|
||||
*
|
||||
* This function corresponds to `<an_ndarray>.__len__`.
|
||||
*
|
||||
* @param dst_length The returned result
|
||||
*/
|
||||
template <typename SizeT>
|
||||
void len(ErrorContext* errctx, const NDArray<SizeT>* ndarray,
|
||||
SliceIndex* dst_length) {
|
||||
// numpy prohibits `__len__` on unsized objects
|
||||
if (ndarray->ndims == 0) {
|
||||
errctx->set_exception(errctx->exceptions->type_error,
|
||||
"len() of unsized object");
|
||||
return;
|
||||
}
|
||||
|
||||
*dst_length = (SliceIndex)ndarray->shape[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Copy data from one ndarray to another of the exact same size and itemsize.
|
||||
*
|
||||
* Both ndarrays will be viewed in their flatten views when copying the elements.
|
||||
*/
|
||||
template <typename SizeT>
|
||||
void copy_data(const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
|
||||
__builtin_assume(src_ndarray->itemsize == dst_ndarray->itemsize);
|
||||
|
||||
for (SizeT i = 0; i < size(src_ndarray); i++) {
|
||||
auto src_element = ndarray::basic::get_nth_pelement(src_ndarray, i);
|
||||
auto dst_element = ndarray::basic::get_nth_pelement(dst_ndarray, i);
|
||||
ndarray::basic::set_pelement_value(dst_ndarray, dst_element,
|
||||
src_element);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Return a boolean indicating if `ndarray` is (C-)contiguous.
|
||||
*
|
||||
* You may want to see: ndarray's rules for C-contiguity: https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45
|
||||
*/
|
||||
template <typename SizeT>
|
||||
bool is_c_contiguous(const NDArray<SizeT>* ndarray) {
|
||||
// Other references:
|
||||
// - tinynumpy's implementation: https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L102
|
||||
// - ndarray's flags["C_CONTIGUOUS"]: https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html#numpy.ndarray.flags
|
||||
// - ndarray's rules for C-contiguity: https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45
|
||||
|
||||
// From https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45:
|
||||
//
|
||||
// The traditional rule is that for an array to be flagged as C contiguous,
|
||||
// the following must hold:
|
||||
//
|
||||
// strides[-1] == itemsize
|
||||
// strides[i] == shape[i+1] * strides[i + 1]
|
||||
// [...]
|
||||
// According to these rules, a 0- or 1-dimensional array is either both
|
||||
// C- and F-contiguous, or neither; and an array with 2+ dimensions
|
||||
// can be C- or F- contiguous, or neither, but not both. Though there
|
||||
// there are exceptions for arrays with zero or one item, in the first
|
||||
// case the check is relaxed up to and including the first dimension
|
||||
// with shape[i] == 0. In the second case `strides == itemsize` will
|
||||
// can be true for all dimensions and both flags are set.
|
||||
|
||||
if (ndarray->ndims == 0) {
|
||||
return true;
|
||||
}
|
||||
|
||||
if (ndarray->strides[ndarray->ndims - 1] != ndarray->itemsize) {
|
||||
return false;
|
||||
}
|
||||
|
||||
for (SizeT i = 0; i < ndarray->ndims - 1; i++) {
|
||||
if (ndarray->strides[i] !=
|
||||
ndarray->shape[i + 1] + ndarray->strides[i + 1]) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
} // namespace basic
|
||||
} // namespace ndarray
|
||||
} // namespace
|
||||
|
||||
extern "C" {
|
||||
using namespace ndarray::basic;
|
||||
|
||||
uint32_t __nac3_ndarray_size(NDArray<int32_t>* ndarray) {
|
||||
return size(ndarray);
|
||||
}
|
||||
|
||||
uint64_t __nac3_ndarray_size64(NDArray<int64_t>* ndarray) {
|
||||
return size(ndarray);
|
||||
}
|
||||
|
||||
uint32_t __nac3_ndarray_nbytes(NDArray<int32_t>* ndarray) {
|
||||
return nbytes(ndarray);
|
||||
}
|
||||
|
||||
uint64_t __nac3_ndarray_nbytes64(NDArray<int64_t>* ndarray) {
|
||||
return nbytes(ndarray);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_len(ErrorContext* errctx, NDArray<int32_t>* ndarray,
|
||||
SliceIndex* dst_len) {
|
||||
return len(errctx, ndarray, dst_len);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_len64(ErrorContext* errctx, NDArray<int64_t>* ndarray,
|
||||
SliceIndex* dst_len) {
|
||||
return len(errctx, ndarray, dst_len);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_util_assert_shape_no_negative(ErrorContext* errctx,
|
||||
int32_t ndims,
|
||||
int32_t* shape) {
|
||||
util::assert_shape_no_negative(errctx, ndims, shape);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_util_assert_shape_no_negative64(ErrorContext* errctx,
|
||||
int64_t ndims,
|
||||
int64_t* shape) {
|
||||
util::assert_shape_no_negative(errctx, ndims, shape);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_set_strides_by_shape(NDArray<int32_t>* ndarray) {
|
||||
set_strides_by_shape(ndarray);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_set_strides_by_shape64(NDArray<int64_t>* ndarray) {
|
||||
set_strides_by_shape(ndarray);
|
||||
}
|
||||
|
||||
bool __nac3_ndarray_is_c_contiguous(NDArray<int32_t>* ndarray) {
|
||||
return is_c_contiguous(ndarray);
|
||||
}
|
||||
|
||||
bool __nac3_ndarray_is_c_contiguous64(NDArray<int64_t>* ndarray) {
|
||||
return is_c_contiguous(ndarray);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_copy_data(NDArray<int32_t>* src_ndarray,
|
||||
NDArray<int32_t>* dst_ndarray) {
|
||||
copy_data(src_ndarray, dst_ndarray);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_copy_data64(NDArray<int64_t>* src_ndarray,
|
||||
NDArray<int64_t>* dst_ndarray) {
|
||||
copy_data(src_ndarray, dst_ndarray);
|
||||
}
|
||||
|
||||
uint8_t* __nac3_ndarray_get_nth_pelement(NDArray<int32_t>* ndarray,
|
||||
int32_t index) {
|
||||
return get_nth_pelement(ndarray, index);
|
||||
}
|
||||
|
||||
uint8_t* __nac3_ndarray_get_nth_pelement64(NDArray<int64_t>* ndarray,
|
||||
int64_t index) {
|
||||
return get_nth_pelement(ndarray, index);
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,221 @@
|
|||
#pragma once
|
||||
|
||||
#include <irrt/error_context.hpp>
|
||||
#include <irrt/int_defs.hpp>
|
||||
#include <irrt/ndarray/def.hpp>
|
||||
#include <irrt/slice.hpp>
|
||||
|
||||
namespace {
|
||||
template <typename SizeT>
|
||||
struct ShapeEntry {
|
||||
SizeT ndims;
|
||||
SizeT* shape;
|
||||
};
|
||||
} // namespace
|
||||
|
||||
namespace {
|
||||
namespace ndarray {
|
||||
namespace broadcast {
|
||||
namespace util {
|
||||
/**
|
||||
* @brief Return true if `src_shape` can broadcast to `dst_shape`.
|
||||
*/
|
||||
template <typename SizeT>
|
||||
bool can_broadcast_shape_to(SizeT target_ndims, const SizeT* target_shape,
|
||||
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;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Performs `np.broadcast_shapes`
|
||||
*/
|
||||
template <typename SizeT>
|
||||
void broadcast_shapes(ErrorContext* errctx, SizeT num_shapes,
|
||||
const ShapeEntry<SizeT>* shapes, SizeT dst_ndims,
|
||||
SizeT* dst_shape) {
|
||||
// `dst_ndims` must be `max([shape.ndims for shape in shapes])`, but the caller has to calculate it/provide it
|
||||
// for this function since it should already know in order to allocate `dst_shape` in the first place.
|
||||
// `dst_shape` must be pre-allocated.
|
||||
// `dst_shape` does not have to be initialized
|
||||
|
||||
// TODO: Implementation is not obvious
|
||||
|
||||
// This is essentially a `mconcat` where the neutral element is `[1, 1, 1, 1, ...]`, and the operation is commutative.
|
||||
|
||||
// Set `dst_shape` to all `1`s.
|
||||
for (SizeT dst_axis = 0; dst_axis < dst_ndims; dst_axis++) {
|
||||
dst_shape[dst_axis] = 0;
|
||||
}
|
||||
|
||||
for (SizeT i = 0; i < num_shapes; i++) {
|
||||
ShapeEntry<SizeT> entry = shapes[i];
|
||||
SizeT entry_axis = entry.ndims - i;
|
||||
SizeT dst_axis = dst_ndims - i;
|
||||
|
||||
SizeT entry_dim = entry.shape[entry_axis];
|
||||
SizeT dst_dim = dst_shape[dst_axis];
|
||||
|
||||
if (dst_dim == 1) {
|
||||
dst_shape[dst_axis] = entry_dim;
|
||||
} else if (entry_dim == 1) {
|
||||
// Do nothing
|
||||
} else if (entry_dim == dst_dim) {
|
||||
// Do nothing
|
||||
} else {
|
||||
errctx->set_exception(errctx->exceptions->value_error,
|
||||
"shape mismatch: objects cannot be broadcast "
|
||||
"to a single shape.");
|
||||
return;
|
||||
}
|
||||
}
|
||||
}
|
||||
} // namespace util
|
||||
|
||||
/**
|
||||
* @brief Perform `np.broadcast_to(<ndarray>, <target_shape>)` and appropriate assertions.
|
||||
*
|
||||
* Cautious note on https://github.com/numpy/numpy/issues/21744..
|
||||
*
|
||||
* This function attempts to broadcast `src_ndarray` to a new shape defined by `dst_ndarray.shape`,
|
||||
* and return the result by modifying `dst_ndarray`.
|
||||
*
|
||||
* # Notes on `dst_ndarray`
|
||||
* The caller is responsible for allocating space for the resulting ndarray.
|
||||
* Here is what this function expects from `dst_ndarray` when called:
|
||||
* - `dst_ndarray->data` does not have to be initialized.
|
||||
* - `dst_ndarray->itemsize` does not have to be initialized.
|
||||
* - `dst_ndarray->ndims` must be initialized, determining the length of `dst_ndarray->shape`
|
||||
* - `dst_ndarray->shape` must be allocated, and must contain the desired target broadcast shape.
|
||||
* - `dst_ndarray->strides` must be allocated, through it can contain uninitialized values.
|
||||
* When this function call ends:
|
||||
* - `dst_ndarray->data` is set to `src_ndarray->data` (`dst_ndarray` is just a view to `src_ndarray`)
|
||||
* - `dst_ndarray->itemsize` is set to `src_ndarray->itemsize`
|
||||
* - `dst_ndarray->ndims` is unchanged.
|
||||
* - `dst_ndarray->shape` is unchanged.
|
||||
* - `dst_ndarray->strides` is updated accordingly by how ndarray broadcast_to works.
|
||||
*/
|
||||
template <typename SizeT>
|
||||
void broadcast_to(ErrorContext* errctx, const NDArray<SizeT>* src_ndarray,
|
||||
NDArray<SizeT>* dst_ndarray) {
|
||||
/*
|
||||
* 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.
|
||||
* ```
|
||||
*/
|
||||
|
||||
if (!ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
dst_ndarray->ndims, dst_ndarray->shape, src_ndarray->ndims,
|
||||
src_ndarray->shape)) {
|
||||
errctx->set_exception(errctx->exceptions->value_error,
|
||||
"operands could not be broadcast together");
|
||||
return;
|
||||
}
|
||||
|
||||
dst_ndarray->data = src_ndarray->data;
|
||||
dst_ndarray->itemsize = src_ndarray->itemsize;
|
||||
|
||||
// TODO: Implementation is not obvious
|
||||
SizeT stride_product = 1;
|
||||
for (SizeT i = 0; i < max(src_ndarray->ndims, dst_ndarray->ndims); i++) {
|
||||
SizeT src_ndarray_dim_i = src_ndarray->ndims - i - 1;
|
||||
SizeT dst_dim_i = dst_ndarray->ndims - i - 1;
|
||||
|
||||
bool src_ndarray_dim_exists = src_ndarray_dim_i >= 0;
|
||||
bool dst_dim_exists = dst_dim_i >= 0;
|
||||
|
||||
bool c1 = src_ndarray_dim_exists &&
|
||||
src_ndarray->shape[src_ndarray_dim_i] == 1;
|
||||
bool c2 = dst_dim_exists && dst_ndarray->shape[dst_dim_i] != 1;
|
||||
if (!src_ndarray_dim_exists || (c1 && c2)) {
|
||||
dst_ndarray->strides[dst_dim_i] = 0; // Freeze it in-place
|
||||
} else {
|
||||
dst_ndarray->strides[dst_dim_i] =
|
||||
stride_product * src_ndarray->itemsize;
|
||||
stride_product *= src_ndarray->shape[src_ndarray_dim_i];
|
||||
}
|
||||
}
|
||||
}
|
||||
} // namespace broadcast
|
||||
} // namespace ndarray
|
||||
} // namespace
|
||||
|
||||
extern "C" {
|
||||
using namespace ndarray::broadcast;
|
||||
|
||||
void __nac3_ndarray_broadcast_to(ErrorContext* errctx,
|
||||
NDArray<int32_t>* src_ndarray,
|
||||
NDArray<int32_t>* dst_ndarray) {
|
||||
broadcast_to(errctx, src_ndarray, dst_ndarray);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_broadcast_to64(ErrorContext* errctx,
|
||||
NDArray<int64_t>* src_ndarray,
|
||||
NDArray<int64_t>* dst_ndarray) {
|
||||
broadcast_to(errctx, src_ndarray, dst_ndarray);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_broadcast_shapes(ErrorContext* errctx, int32_t num_shapes,
|
||||
const ShapeEntry<int32_t>* shapes,
|
||||
int32_t dst_ndims, int32_t* dst_shape) {
|
||||
ndarray::broadcast::util::broadcast_shapes(errctx, num_shapes, shapes,
|
||||
dst_ndims, dst_shape);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_broadcast_shapes64(ErrorContext* errctx, int64_t num_shapes,
|
||||
const ShapeEntry<int64_t>* shapes,
|
||||
int64_t dst_ndims, int64_t* dst_shape) {
|
||||
ndarray::broadcast::util::broadcast_shapes(errctx, num_shapes, shapes,
|
||||
dst_ndims, dst_shape);
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,44 @@
|
|||
#pragma once
|
||||
|
||||
namespace {
|
||||
/**
|
||||
* @brief The NDArray object
|
||||
*
|
||||
* The official numpy implementations: https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst
|
||||
*/
|
||||
template <typename SizeT>
|
||||
struct NDArray {
|
||||
/**
|
||||
* @brief The underlying data this `ndarray` is pointing to.
|
||||
*
|
||||
* Must be set to `nullptr` to indicate that this NDArray's `data` is uninitialized.
|
||||
*/
|
||||
uint8_t* data;
|
||||
|
||||
/**
|
||||
* @brief The number of bytes of a single element in `data`.
|
||||
*/
|
||||
SizeT itemsize;
|
||||
|
||||
/**
|
||||
* @brief The number of dimensions of this shape.
|
||||
*/
|
||||
SizeT ndims;
|
||||
|
||||
/**
|
||||
* @brief The NDArray shape, with length equal to `ndims`.
|
||||
*
|
||||
* Note that it may contain 0.
|
||||
*/
|
||||
SizeT* shape;
|
||||
|
||||
/**
|
||||
* @brief Array strides, with length equal to `ndims`
|
||||
*
|
||||
* The stride values are in units of bytes, not number of elements.
|
||||
*
|
||||
* Note that `strides` can have negative values.
|
||||
*/
|
||||
SizeT* strides;
|
||||
};
|
||||
} // namespace
|
||||
|
|
@ -0,0 +1,200 @@
|
|||
#pragma once
|
||||
|
||||
#include <irrt/error_context.hpp>
|
||||
#include <irrt/ndarray/basic.hpp>
|
||||
#include <irrt/ndarray/def.hpp>
|
||||
#include <irrt/slice.hpp>
|
||||
|
||||
namespace {
|
||||
typedef uint8_t NDIndexType;
|
||||
|
||||
/**
|
||||
* @brief A single element index
|
||||
*
|
||||
* See https://numpy.org/doc/stable/user/basics.indexing.html#single-element-indexing
|
||||
*
|
||||
* `data` points to a `SliceIndex`.
|
||||
*/
|
||||
const NDIndexType ND_INDEX_TYPE_SINGLE_ELEMENT = 0;
|
||||
/**
|
||||
* @brief A slice index
|
||||
*
|
||||
* See https://numpy.org/doc/stable/user/basics.indexing.html#slicing-and-striding
|
||||
*
|
||||
* `data` points to a `UserRange`.
|
||||
*/
|
||||
const NDIndexType ND_INDEX_TYPE_SLICE = 1;
|
||||
|
||||
/**
|
||||
* @brief An index used in ndarray indexing
|
||||
*/
|
||||
struct NDIndex {
|
||||
/**
|
||||
* @brief Enum tag to specify the type of index.
|
||||
*
|
||||
* Please see comments of each enum constant.
|
||||
*/
|
||||
NDIndexType type;
|
||||
|
||||
/**
|
||||
* @brief The accompanying data associated with `type`.
|
||||
*
|
||||
* Please see comments of each enum constant.
|
||||
*/
|
||||
uint8_t* data;
|
||||
};
|
||||
} // namespace
|
||||
|
||||
namespace {
|
||||
namespace ndarray {
|
||||
namespace indexing {
|
||||
namespace util {
|
||||
|
||||
/**
|
||||
* @brief Return the expected rank of the resulting ndarray
|
||||
* created by indexing an ndarray of rank `ndims` using `indexes`.
|
||||
*/
|
||||
template <typename SizeT>
|
||||
void deduce_ndims_after_indexing(ErrorContext* errctx, SizeT* final_ndims,
|
||||
SizeT ndims, SizeT num_indexes,
|
||||
const NDIndex* indexes) {
|
||||
if (num_indexes > ndims) {
|
||||
errctx->set_exception(errctx->exceptions->index_error,
|
||||
"too many indices for array: array is "
|
||||
"{0}-dimensional, but {1} were indexed",
|
||||
ndims, num_indexes);
|
||||
return;
|
||||
}
|
||||
|
||||
*final_ndims = ndims;
|
||||
for (SizeT i = 0; i < num_indexes; i++) {
|
||||
if (indexes[i].type == ND_INDEX_TYPE_SINGLE_ELEMENT) {
|
||||
// An index demotes the rank by 1
|
||||
(*final_ndims)--;
|
||||
}
|
||||
}
|
||||
}
|
||||
} // namespace util
|
||||
|
||||
/**
|
||||
* @brief Perform ndarray "basic indexing" (https://numpy.org/doc/stable/user/basics.indexing.html#basic-indexing)
|
||||
*
|
||||
* This is function very similar to performing `dst_ndarray = src_ndarray[indexes]` in Python (where the variables
|
||||
* can all be found in the parameter of this function).
|
||||
*
|
||||
* In other words, this function takes in an ndarray (`src_ndarray`), index it with `indexes`, and return the
|
||||
* indexed array (by writing the result to `dst_ndarray`).
|
||||
*
|
||||
* This function also does proper assertions on `indexes`.
|
||||
*
|
||||
* # Notes on `dst_ndarray`
|
||||
* The caller is responsible for allocating space for the resulting ndarray.
|
||||
* Here is what this function expects from `dst_ndarray` when called:
|
||||
* - `dst_ndarray->data` does not have to be initialized.
|
||||
* - `dst_ndarray->itemsize` does not have to be initialized.
|
||||
* - `dst_ndarray->ndims` must be initialized, and it must be equal to the expected `ndims` of the `dst_ndarray` after
|
||||
* indexing `src_ndarray` with `indexes`.
|
||||
* - `dst_ndarray->shape` must be allocated, through it can contain uninitialized values.
|
||||
* - `dst_ndarray->strides` must be allocated, through it can contain uninitialized values.
|
||||
* When this function call ends:
|
||||
* - `dst_ndarray->data` is set to `src_ndarray->data` (`dst_ndarray` is just a view to `src_ndarray`)
|
||||
* - `dst_ndarray->itemsize` is set to `src_ndarray->itemsize`
|
||||
* - `dst_ndarray->ndims` is unchanged.
|
||||
* - `dst_ndarray->shape` is updated according to how `src_ndarray` is indexed.
|
||||
* - `dst_ndarray->strides` is updated accordingly by how ndarray indexing works.
|
||||
*
|
||||
* @param indexes Indexes to index `src_ndarray`, ordered in the same way you would write them in Python.
|
||||
* @param src_ndarray The NDArray to be indexed.
|
||||
* @param dst_ndarray The resulting NDArray after indexing. Further details in the comments above,
|
||||
*/
|
||||
template <typename SizeT>
|
||||
void index(ErrorContext* errctx, SizeT num_indexes, const NDIndex* indexes,
|
||||
const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
|
||||
// Reference code: https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L652
|
||||
|
||||
dst_ndarray->data = src_ndarray->data;
|
||||
dst_ndarray->itemsize = src_ndarray->itemsize;
|
||||
|
||||
SizeT src_axis = 0;
|
||||
SizeT dst_axis = 0;
|
||||
|
||||
for (SliceIndex i = 0; i < num_indexes; i++) {
|
||||
const NDIndex* index = &indexes[i];
|
||||
if (index->type == ND_INDEX_TYPE_SINGLE_ELEMENT) {
|
||||
SliceIndex input = *((SliceIndex*)index->data);
|
||||
SliceIndex k = slice::resolve_index_in_length(
|
||||
src_ndarray->shape[src_axis], input);
|
||||
|
||||
if (k == slice::OUT_OF_BOUNDS) {
|
||||
errctx->set_exception(errctx->exceptions->index_error,
|
||||
"index {0} is out of bounds for axis {1} "
|
||||
"with size {2}",
|
||||
input, src_axis,
|
||||
src_ndarray->shape[src_axis]);
|
||||
return;
|
||||
}
|
||||
|
||||
dst_ndarray->data += k * src_ndarray->strides[src_axis];
|
||||
|
||||
src_axis++;
|
||||
} else if (index->type == ND_INDEX_TYPE_SLICE) {
|
||||
UserSlice* input = (UserSlice*)index->data;
|
||||
|
||||
Slice slice;
|
||||
input->indices_checked(errctx, src_ndarray->shape[src_axis],
|
||||
&slice);
|
||||
if (errctx->has_exception()) {
|
||||
return;
|
||||
}
|
||||
|
||||
dst_ndarray->data +=
|
||||
(SizeT)slice.start * src_ndarray->strides[src_axis];
|
||||
dst_ndarray->strides[dst_axis] =
|
||||
((SizeT)slice.step) * src_ndarray->strides[src_axis];
|
||||
dst_ndarray->shape[dst_axis] = (SizeT)slice.len();
|
||||
|
||||
dst_axis++;
|
||||
src_axis++;
|
||||
} else {
|
||||
__builtin_unreachable();
|
||||
}
|
||||
}
|
||||
|
||||
for (; dst_axis < dst_ndarray->ndims; dst_axis++, src_axis++) {
|
||||
dst_ndarray->shape[dst_axis] = src_ndarray->shape[src_axis];
|
||||
dst_ndarray->strides[dst_axis] = src_ndarray->strides[src_axis];
|
||||
}
|
||||
}
|
||||
} // namespace indexing
|
||||
} // namespace ndarray
|
||||
} // namespace
|
||||
|
||||
extern "C" {
|
||||
using namespace ndarray::indexing;
|
||||
|
||||
void __nac3_ndarray_indexing_deduce_ndims_after_indexing(
|
||||
ErrorContext* errctx, int32_t* result, int32_t ndims, int32_t num_indexes,
|
||||
const NDIndex* indexes) {
|
||||
ndarray::indexing::util::deduce_ndims_after_indexing(errctx, result, ndims,
|
||||
num_indexes, indexes);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_indexing_deduce_ndims_after_indexing64(
|
||||
ErrorContext* errctx, int64_t* result, int64_t ndims, int64_t num_indexes,
|
||||
const NDIndex* indexes) {
|
||||
ndarray::indexing::util::deduce_ndims_after_indexing(errctx, result, ndims,
|
||||
num_indexes, indexes);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_index(ErrorContext* errctx, int32_t num_indexes,
|
||||
NDIndex* indexes, NDArray<int32_t>* src_ndarray,
|
||||
NDArray<int32_t>* dst_ndarray) {
|
||||
index(errctx, num_indexes, indexes, src_ndarray, dst_ndarray);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_index64(ErrorContext* errctx, int64_t num_indexes,
|
||||
NDIndex* indexes, NDArray<int64_t>* src_ndarray,
|
||||
NDArray<int64_t>* dst_ndarray) {
|
||||
index(errctx, num_indexes, indexes, src_ndarray, dst_ndarray);
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,117 @@
|
|||
#pragma once
|
||||
|
||||
#include <irrt/error_context.hpp>
|
||||
#include <irrt/int_defs.hpp>
|
||||
#include <irrt/ndarray/def.hpp>
|
||||
|
||||
namespace {
|
||||
namespace ndarray {
|
||||
namespace reshape {
|
||||
namespace util {
|
||||
|
||||
/**
|
||||
* @brief Perform assertions on and resolve unknown dimensions in `new_shape` in `np.reshape(<ndarray>, new_shape)`
|
||||
*
|
||||
* If `new_shape` indeed contains unknown dimensions (specified with `-1`, just like numpy), `new_shape` will be
|
||||
* modified to contain the resolved dimension.
|
||||
*
|
||||
* To perform assertions on and resolve unknown dimensions in `new_shape`, we don't need the actual
|
||||
* `<ndarray>` object itself, but only the `.size` of the `<ndarray>`.
|
||||
*
|
||||
* @param size The `.size` of `<ndarray>`
|
||||
* @param new_ndims Number of elements in `new_shape`
|
||||
* @param new_shape Target shape to reshape to
|
||||
*/
|
||||
template <typename SizeT>
|
||||
void resolve_and_check_new_shape(ErrorContext* errctx, SizeT size,
|
||||
SizeT new_ndims, SizeT* new_shape) {
|
||||
// Is there a -1 in `new_shape`?
|
||||
bool neg1_exists = false;
|
||||
// Location of -1, only initialized if `neg1_exists` is true
|
||||
SizeT neg1_axis_i;
|
||||
// The computed ndarray size of `new_shape`
|
||||
SizeT new_size = 1;
|
||||
|
||||
for (SizeT axis_i = 0; axis_i < new_ndims; axis_i++) {
|
||||
SizeT dim = new_shape[axis_i];
|
||||
if (dim < 0) {
|
||||
if (dim == -1) {
|
||||
if (neg1_exists) {
|
||||
// Multiple `-1` found. Throw an error.
|
||||
errctx->set_exception(
|
||||
errctx->exceptions->value_error,
|
||||
"can only specify one unknown dimension");
|
||||
return;
|
||||
} else {
|
||||
neg1_exists = true;
|
||||
neg1_axis_i = axis_i;
|
||||
}
|
||||
} else {
|
||||
// TODO: What? In `np.reshape` any negative dimensions is
|
||||
// treated like its `-1`.
|
||||
//
|
||||
// Try running `np.zeros((3, 4)).reshape((-999, 2))`
|
||||
//
|
||||
// It is not documented by numpy.
|
||||
// Throw an error for now...
|
||||
|
||||
errctx->set_exception(
|
||||
errctx->exceptions->value_error,
|
||||
"Found negative dimension {0} on axis {1}", dim, axis_i);
|
||||
return;
|
||||
}
|
||||
} else {
|
||||
new_size *= dim;
|
||||
}
|
||||
}
|
||||
|
||||
bool can_reshape;
|
||||
if (neg1_exists) {
|
||||
// Let `x` be the unknown dimension
|
||||
// solve `x * <new_size> = <size>`
|
||||
if (new_size == 0 && size == 0) {
|
||||
// `x` has infinitely many solutions
|
||||
can_reshape = false;
|
||||
} else if (new_size == 0 && size != 0) {
|
||||
// `x` has no solutions
|
||||
can_reshape = false;
|
||||
} else if (size % new_size != 0) {
|
||||
// `x` has no integer solutions
|
||||
can_reshape = false;
|
||||
} else {
|
||||
can_reshape = true;
|
||||
new_shape[neg1_axis_i] = size / new_size; // Resolve dimension
|
||||
}
|
||||
} else {
|
||||
can_reshape = (new_size == size);
|
||||
}
|
||||
|
||||
if (!can_reshape) {
|
||||
errctx->set_exception(
|
||||
errctx->exceptions->value_error,
|
||||
"cannot reshape array of size {0} into given shape", size);
|
||||
return;
|
||||
}
|
||||
}
|
||||
} // namespace util
|
||||
} // namespace reshape
|
||||
} // namespace ndarray
|
||||
} // namespace
|
||||
|
||||
extern "C" {
|
||||
|
||||
void __nac3_ndarray_resolve_and_check_new_shape(ErrorContext* errctx,
|
||||
int32_t size, int32_t new_ndims,
|
||||
int32_t* new_shape) {
|
||||
ndarray::reshape::util::resolve_and_check_new_shape(errctx, size, new_ndims,
|
||||
new_shape);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_resolve_and_check_new_shape64(ErrorContext* errctx,
|
||||
int64_t size,
|
||||
int64_t new_ndims,
|
||||
int64_t* new_shape) {
|
||||
ndarray::reshape::util::resolve_and_check_new_shape(errctx, size, new_ndims,
|
||||
new_shape);
|
||||
}
|
||||
}
|
||||
|
|
@ -1,28 +1,166 @@
|
|||
#pragma once
|
||||
|
||||
#include "irrt/int_types.hpp"
|
||||
#include <irrt/error_context.hpp>
|
||||
#include <irrt/int_defs.hpp>
|
||||
#include <irrt/slice.hpp>
|
||||
#include <irrt/utils.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;
|
||||
}
|
||||
// The type of an index or a value describing the length of a
|
||||
// range/slice is always `int32_t`.
|
||||
using SliceIndex = int32_t;
|
||||
|
||||
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;
|
||||
namespace {
|
||||
|
||||
/**
|
||||
* @brief A Python-like slice with resolved indices.
|
||||
*
|
||||
* "Resolved indices" means that `start` and `stop` must be positive and are
|
||||
* bound to a known length.
|
||||
*/
|
||||
struct Slice {
|
||||
SliceIndex start;
|
||||
SliceIndex stop;
|
||||
SliceIndex step;
|
||||
|
||||
/**
|
||||
* @brief Calculate and return the length / the number of the slice.
|
||||
*
|
||||
* If this were a Python range, this function would be `len(range(start, stop, step))`.
|
||||
*/
|
||||
SliceIndex len() {
|
||||
SliceIndex 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;
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
namespace slice {
|
||||
/**
|
||||
* @brief Resolve a slice index under a given length like Python indexing.
|
||||
*
|
||||
* In Python, if you have a `list` of length 100, `list[-1]` resolves to
|
||||
* `list[99]`, so `resolve_index_in_length_clamped(100, -1)` returns `99`.
|
||||
*
|
||||
* If `length` is 0, 0 is returned for any value of `index`.
|
||||
*
|
||||
* If `index` is out of bounds, clamps the returned value between `0` and
|
||||
* `length - 1` (inclusive).
|
||||
*
|
||||
*/
|
||||
SliceIndex resolve_index_in_length_clamped(SliceIndex length,
|
||||
SliceIndex index) {
|
||||
if (index < 0) {
|
||||
return max<SliceIndex>(length + index, 0);
|
||||
} else {
|
||||
return 0;
|
||||
return min<SliceIndex>(length, index);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const SliceIndex OUT_OF_BOUNDS = -1;
|
||||
|
||||
/**
|
||||
* @brief Like `resolve_index_in_length_clamped`, but returns `OUT_OF_BOUNDS`
|
||||
* if `index` is out of bounds.
|
||||
*/
|
||||
SliceIndex resolve_index_in_length(SliceIndex length, SliceIndex index) {
|
||||
SliceIndex resolved = index < 0 ? length + index : index;
|
||||
if (0 <= resolved && resolved < length) {
|
||||
return resolved;
|
||||
} else {
|
||||
return OUT_OF_BOUNDS;
|
||||
}
|
||||
}
|
||||
} // namespace slice
|
||||
|
||||
/**
|
||||
* @brief A Python-like slice with **unresolved** indices.
|
||||
*/
|
||||
struct UserSlice {
|
||||
bool start_defined;
|
||||
SliceIndex start;
|
||||
|
||||
bool stop_defined;
|
||||
SliceIndex stop;
|
||||
|
||||
bool step_defined;
|
||||
SliceIndex step;
|
||||
|
||||
UserSlice() { this->reset(); }
|
||||
|
||||
void reset() {
|
||||
this->start_defined = false;
|
||||
this->stop_defined = false;
|
||||
this->step_defined = false;
|
||||
}
|
||||
|
||||
void set_start(SliceIndex start) {
|
||||
this->start_defined = true;
|
||||
this->start = start;
|
||||
}
|
||||
|
||||
void set_stop(SliceIndex stop) {
|
||||
this->stop_defined = true;
|
||||
this->stop = stop;
|
||||
}
|
||||
|
||||
void set_step(SliceIndex step) {
|
||||
this->step_defined = true;
|
||||
this->step = step;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Resolve this slice.
|
||||
*
|
||||
* In Python, this would be `slice(start, stop, step).indices(length)`.
|
||||
*
|
||||
* @return A `Slice` with the resolved indices.
|
||||
*/
|
||||
Slice indices(SliceIndex length) {
|
||||
Slice result;
|
||||
|
||||
result.step = step_defined ? step : 1;
|
||||
bool step_is_negative = result.step < 0;
|
||||
|
||||
if (start_defined) {
|
||||
result.start =
|
||||
slice::resolve_index_in_length_clamped(length, start);
|
||||
} else {
|
||||
result.start = step_is_negative ? length - 1 : 0;
|
||||
}
|
||||
|
||||
if (stop_defined) {
|
||||
result.stop = slice::resolve_index_in_length_clamped(length, stop);
|
||||
} else {
|
||||
result.stop = step_is_negative ? -1 : length;
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Like `.indices()` but with assertions.
|
||||
*/
|
||||
void indices_checked(ErrorContext* errctx, SliceIndex length,
|
||||
Slice* result) {
|
||||
if (length < 0) {
|
||||
errctx->set_exception(errctx->exceptions->value_error,
|
||||
"length should not be negative, got {0}",
|
||||
length);
|
||||
return;
|
||||
}
|
||||
|
||||
if (this->step_defined && this->step == 0) {
|
||||
errctx->set_exception(errctx->exceptions->value_error,
|
||||
"slice step cannot be zero");
|
||||
return;
|
||||
}
|
||||
|
||||
*result = this->indices(length);
|
||||
}
|
||||
};
|
||||
} // namespace
|
||||
|
|
@ -0,0 +1,104 @@
|
|||
#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;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Compare contents of two arrays with the same length.
|
||||
*/
|
||||
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;
|
||||
}
|
||||
|
||||
namespace cstr_utils {
|
||||
/**
|
||||
* @brief Return true if `str` is empty.
|
||||
*/
|
||||
bool is_empty(const char* str) { return str[0] == '\0'; }
|
||||
|
||||
/**
|
||||
* @brief Implementation of `strcmp()`
|
||||
*/
|
||||
int8_t compare(const char* a, const char* b) {
|
||||
uint32_t i = 0;
|
||||
while (true) {
|
||||
if (a[i] < b[i]) {
|
||||
return -1;
|
||||
} else if (a[i] > b[i]) {
|
||||
return 1;
|
||||
} else {
|
||||
if (a[i] == '\0') {
|
||||
return 0;
|
||||
} else {
|
||||
i++;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Return true two strings have the same content.
|
||||
*/
|
||||
int8_t equal(const char* a, const char* b) { return compare(a, b) == 0; }
|
||||
|
||||
/**
|
||||
* @brief Implementation of `strlen()`.
|
||||
*/
|
||||
uint32_t length(const char* str) {
|
||||
uint32_t length = 0;
|
||||
while (*str != '\0') {
|
||||
length++;
|
||||
str++;
|
||||
}
|
||||
return length;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Copy a null-terminated string to a buffer with limited size and guaranteed null-termination.
|
||||
*
|
||||
* `dst_max_size` must be greater than 0, otherwise this function has undefined behavior.
|
||||
*
|
||||
* This function attempts to copy everything from `src` from `dst`, and *always* null-terminates `dst`.
|
||||
*
|
||||
* If the size of `dst` is too small, the final byte (`dst[dst_max_size - 1]`) of `dst` will be set to
|
||||
* the null terminator.
|
||||
*
|
||||
* @param src String to copy from.
|
||||
* @param dst Buffer to copy string to.
|
||||
* @param dst_max_size
|
||||
* Number of bytes of this buffer, including the space needed for the null terminator.
|
||||
* Must be greater than 0.
|
||||
* @return If `dst` is too small to contain everything in `src`.
|
||||
*/
|
||||
bool copy(const char* src, char* dst, uint32_t dst_max_size) {
|
||||
for (uint32_t i = 0; i < dst_max_size; i++) {
|
||||
bool is_last = i + 1 == dst_max_size;
|
||||
if (is_last && src[i] != '\0') {
|
||||
dst[i] = '\0';
|
||||
return false;
|
||||
}
|
||||
|
||||
if (src[i] == '\0') {
|
||||
dst[i] = '\0';
|
||||
return true;
|
||||
}
|
||||
|
||||
dst[i] = src[i];
|
||||
}
|
||||
|
||||
__builtin_unreachable();
|
||||
}
|
||||
} // namespace cstr_utils
|
||||
} // namespace
|
||||
|
|
@ -0,0 +1,13 @@
|
|||
#pragma once
|
||||
|
||||
#include <irrt/artiq_defs.hpp>
|
||||
#include <irrt/core.hpp>
|
||||
#include <irrt/error_context.hpp>
|
||||
#include <irrt/int_defs.hpp>
|
||||
#include <irrt/ndarray/basic.hpp>
|
||||
#include <irrt/ndarray/broadcast.hpp>
|
||||
#include <irrt/ndarray/def.hpp>
|
||||
#include <irrt/ndarray/indexing.hpp>
|
||||
#include <irrt/ndarray/reshape.hpp>
|
||||
#include <irrt/slice.hpp>
|
||||
#include <irrt/utils.hpp>
|
||||
|
|
@ -0,0 +1,20 @@
|
|||
// 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>
|
||||
#include <test/test_core.hpp>
|
||||
#include <test/test_ndarray_basic.hpp>
|
||||
#include <test/test_ndarray_broadcast.hpp>
|
||||
#include <test/test_ndarray_indexing.hpp>
|
||||
#include <test/test_slice.hpp>
|
||||
|
||||
int main() {
|
||||
test::core::run();
|
||||
test::slice::run();
|
||||
test::ndarray_basic::run();
|
||||
test::ndarray_indexing::run();
|
||||
test::ndarray_broadcast::run();
|
||||
return 0;
|
||||
}
|
||||
|
|
@ -0,0 +1,11 @@
|
|||
#pragma once
|
||||
|
||||
#include <cstdint>
|
||||
#include <cstdio>
|
||||
#include <cstdlib>
|
||||
#include <irrt_everything.hpp>
|
||||
#include <test/util.hpp>
|
||||
|
||||
/*
|
||||
Include this header for every test_*.cpp
|
||||
*/
|
||||
|
|
@ -0,0 +1,16 @@
|
|||
#pragma once
|
||||
|
||||
#include <test/includes.hpp>
|
||||
|
||||
namespace test {
|
||||
namespace core {
|
||||
void test_int_exp() {
|
||||
BEGIN_TEST();
|
||||
|
||||
assert_values_match(125, __nac3_int_exp_impl<int32_t>(5, 3));
|
||||
assert_values_match(3125, __nac3_int_exp_impl<int32_t>(5, 5));
|
||||
}
|
||||
|
||||
void run() { test_int_exp(); }
|
||||
} // namespace core
|
||||
} // namespace test
|
||||
|
|
@ -0,0 +1,30 @@
|
|||
#pragma once
|
||||
|
||||
#include <test/includes.hpp>
|
||||
|
||||
namespace test {
|
||||
namespace ndarray_basic {
|
||||
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(
|
||||
210, ndarray::basic::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(
|
||||
0, ndarray::basic::util::calc_size_from_shape<int32_t>(4, shape));
|
||||
}
|
||||
|
||||
void run() {
|
||||
test_calc_size_from_shape_normal();
|
||||
test_calc_size_from_shape_has_zero();
|
||||
}
|
||||
} // namespace ndarray_basic
|
||||
} // namespace test
|
||||
|
|
@ -0,0 +1,129 @@
|
|||
#pragma once
|
||||
|
||||
#include <test/includes.hpp>
|
||||
|
||||
namespace test {
|
||||
namespace ndarray_broadcast {
|
||||
void test_can_broadcast_shape() {
|
||||
BEGIN_TEST();
|
||||
|
||||
assert_values_match(true,
|
||||
ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
1, (int32_t[]){3}, 5, (int32_t[]){1, 1, 1, 1, 3}));
|
||||
assert_values_match(false, ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
1, (int32_t[]){3}, 2, (int32_t[]){3, 1}));
|
||||
assert_values_match(true, ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
1, (int32_t[]){3}, 1, (int32_t[]){3}));
|
||||
assert_values_match(false, ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
1, (int32_t[]){1}, 1, (int32_t[]){3}));
|
||||
assert_values_match(true, ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
1, (int32_t[]){1}, 1, (int32_t[]){1}));
|
||||
assert_values_match(
|
||||
true, ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
3, (int32_t[]){256, 256, 3}, 3, (int32_t[]){256, 1, 3}));
|
||||
assert_values_match(true,
|
||||
ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
3, (int32_t[]){256, 256, 3}, 1, (int32_t[]){3}));
|
||||
assert_values_match(false,
|
||||
ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
3, (int32_t[]){256, 256, 3}, 1, (int32_t[]){2}));
|
||||
assert_values_match(true,
|
||||
ndarray::broadcast::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(true, ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
1, (int32_t[]){0}, 1, (int32_t[]){1}));
|
||||
assert_values_match(false, ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
1, (int32_t[]){0}, 1, (int32_t[]){2}));
|
||||
assert_values_match(true,
|
||||
ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
4, (int32_t[]){0, 4, 0, 0}, 1, (int32_t[]){1}));
|
||||
assert_values_match(
|
||||
true, ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
4, (int32_t[]){0, 4, 0, 0}, 4, (int32_t[]){1, 1, 1, 1}));
|
||||
assert_values_match(
|
||||
true, ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
4, (int32_t[]){0, 4, 0, 0}, 4, (int32_t[]){1, 4, 1, 1}));
|
||||
assert_values_match(false, ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
2, (int32_t[]){4, 3}, 2, (int32_t[]){0, 3}));
|
||||
assert_values_match(false, ndarray::broadcast::util::can_broadcast_shape_to(
|
||||
2, (int32_t[]){4, 3}, 2, (int32_t[]){0, 0}));
|
||||
}
|
||||
|
||||
void test_ndarray_broadcast() {
|
||||
/*
|
||||
# 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::basic::set_strides_by_shape(&ndarray);
|
||||
|
||||
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};
|
||||
|
||||
ErrorContext errctx = create_testing_errctx();
|
||||
ndarray::broadcast::broadcast_to(&errctx, &ndarray, &dst_ndarray);
|
||||
assert_errctx_no_exception(&errctx);
|
||||
|
||||
assert_arrays_match(dst_ndims, ((int32_t[]){0, 0, 8}), dst_ndarray.strides);
|
||||
|
||||
assert_values_match(19.9,
|
||||
*((double*)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, ((int32_t[]){0, 0, 0}))));
|
||||
assert_values_match(29.9,
|
||||
*((double*)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, ((int32_t[]){0, 0, 1}))));
|
||||
assert_values_match(39.9,
|
||||
*((double*)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, ((int32_t[]){0, 0, 2}))));
|
||||
assert_values_match(49.9,
|
||||
*((double*)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, ((int32_t[]){0, 0, 3}))));
|
||||
assert_values_match(19.9,
|
||||
*((double*)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, ((int32_t[]){0, 1, 0}))));
|
||||
assert_values_match(29.9,
|
||||
*((double*)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, ((int32_t[]){0, 1, 1}))));
|
||||
assert_values_match(39.9,
|
||||
*((double*)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, ((int32_t[]){0, 1, 2}))));
|
||||
assert_values_match(49.9,
|
||||
*((double*)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, ((int32_t[]){0, 1, 3}))));
|
||||
assert_values_match(49.9,
|
||||
*((double*)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, ((int32_t[]){1, 2, 3}))));
|
||||
}
|
||||
|
||||
void run() {
|
||||
test_can_broadcast_shape();
|
||||
test_ndarray_broadcast();
|
||||
}
|
||||
} // namespace ndarray_broadcast
|
||||
} // namespace test
|
||||
|
|
@ -0,0 +1,220 @@
|
|||
#pragma once
|
||||
|
||||
#include <test/includes.hpp>
|
||||
|
||||
namespace test {
|
||||
namespace ndarray_indexing {
|
||||
void test_normal_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();
|
||||
|
||||
// Prepare src_ndarray
|
||||
double src_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 src_itemsize = sizeof(double);
|
||||
const int32_t src_ndims = 2;
|
||||
int32_t src_shape[src_ndims] = {3, 4};
|
||||
int32_t src_strides[src_ndims] = {};
|
||||
NDArray<int32_t> src_ndarray = {.data = (uint8_t *)src_data,
|
||||
.itemsize = src_itemsize,
|
||||
.ndims = src_ndims,
|
||||
.shape = src_shape,
|
||||
.strides = src_strides};
|
||||
ndarray::basic::set_strides_by_shape(&src_ndarray);
|
||||
|
||||
// Prepare dst_ndarray
|
||||
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 subscripts in `ndarray[-2::, 1::2]`
|
||||
UserSlice subscript_1;
|
||||
subscript_1.set_start(-2);
|
||||
|
||||
UserSlice subscript_2;
|
||||
subscript_2.set_start(1);
|
||||
subscript_2.set_step(2);
|
||||
|
||||
const int32_t num_indexes = 2;
|
||||
NDIndex indexes[num_indexes] = {
|
||||
{.type = ND_INDEX_TYPE_SLICE, .data = (uint8_t *)&subscript_1},
|
||||
{.type = ND_INDEX_TYPE_SLICE, .data = (uint8_t *)&subscript_2}};
|
||||
|
||||
ErrorContext errctx = create_testing_errctx();
|
||||
ndarray::indexing::index(&errctx, num_indexes, indexes, &src_ndarray,
|
||||
&dst_ndarray);
|
||||
assert_errctx_no_exception(&errctx);
|
||||
|
||||
int32_t expected_shape[dst_ndims] = {2, 2};
|
||||
int32_t expected_strides[dst_ndims] = {32, 16};
|
||||
|
||||
assert_arrays_match(dst_ndims, expected_shape, dst_ndarray.shape);
|
||||
assert_arrays_match(dst_ndims, expected_strides, dst_ndarray.strides);
|
||||
|
||||
// dst_ndarray[0, 0]
|
||||
assert_values_match(5.0,
|
||||
*((double *)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, (int32_t[dst_ndims]){0, 0})));
|
||||
// dst_ndarray[0, 1]
|
||||
assert_values_match(7.0,
|
||||
*((double *)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, (int32_t[dst_ndims]){0, 1})));
|
||||
// dst_ndarray[1, 0]
|
||||
assert_values_match(9.0,
|
||||
*((double *)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, (int32_t[dst_ndims]){1, 0})));
|
||||
// dst_ndarray[1, 1]
|
||||
assert_values_match(11.0,
|
||||
*((double *)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, (int32_t[dst_ndims]){1, 1})));
|
||||
}
|
||||
|
||||
void test_normal_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
|
||||
```
|
||||
*/
|
||||
BEGIN_TEST();
|
||||
|
||||
// Prepare src_ndarray
|
||||
double src_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 src_itemsize = sizeof(double);
|
||||
const int32_t src_ndims = 2;
|
||||
int32_t src_shape[src_ndims] = {3, 4};
|
||||
int32_t src_strides[src_ndims] = {};
|
||||
NDArray<int32_t> src_ndarray = {.data = (uint8_t *)src_data,
|
||||
.itemsize = src_itemsize,
|
||||
.ndims = src_ndims,
|
||||
.shape = src_shape,
|
||||
.strides = src_strides};
|
||||
ndarray::basic::set_strides_by_shape(&src_ndarray);
|
||||
|
||||
// Prepare dst_ndarray
|
||||
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 subscripts in `ndarray[2, ::-2]`
|
||||
int32_t subscript_1 = 2;
|
||||
|
||||
UserSlice subscript_2;
|
||||
subscript_2.set_step(-2);
|
||||
|
||||
const int32_t num_indexes = 2;
|
||||
NDIndex indexes[num_indexes] = {
|
||||
{.type = ND_INDEX_TYPE_SINGLE_ELEMENT, .data = (uint8_t *)&subscript_1},
|
||||
{.type = ND_INDEX_TYPE_SLICE, .data = (uint8_t *)&subscript_2}};
|
||||
|
||||
ErrorContext errctx = create_testing_errctx();
|
||||
ndarray::indexing::index(&errctx, num_indexes, indexes, &src_ndarray,
|
||||
&dst_ndarray);
|
||||
assert_errctx_no_exception(&errctx);
|
||||
|
||||
int32_t expected_shape[dst_ndims] = {2};
|
||||
int32_t expected_strides[dst_ndims] = {-16};
|
||||
assert_arrays_match(dst_ndims, expected_shape, dst_ndarray.shape);
|
||||
assert_arrays_match(dst_ndims, expected_strides, dst_ndarray.strides);
|
||||
|
||||
assert_values_match(11.0,
|
||||
*((double *)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, (int32_t[dst_ndims]){0})));
|
||||
assert_values_match(9.0,
|
||||
*((double *)ndarray::basic::get_pelement_by_indices(
|
||||
&dst_ndarray, (int32_t[dst_ndims]){1})));
|
||||
}
|
||||
|
||||
void test_index_subscript_out_of_bounds() {
|
||||
/*
|
||||
# Consider `my_array`
|
||||
|
||||
print(my_array.shape)
|
||||
# (4, 5, 6)
|
||||
|
||||
my_array[2, 100] # error, index subscript at axis 1 is out of bounds
|
||||
*/
|
||||
BEGIN_TEST();
|
||||
|
||||
// Prepare src_ndarray
|
||||
const int32_t src_ndims = 2;
|
||||
int32_t src_shape[src_ndims] = {3, 4};
|
||||
int32_t src_strides[src_ndims] = {};
|
||||
NDArray<int32_t> src_ndarray = {
|
||||
.data = (uint8_t *)nullptr, // placeholder, we wouldn't access it
|
||||
.itemsize = sizeof(double), // placeholder
|
||||
.ndims = src_ndims,
|
||||
.shape = src_shape,
|
||||
.strides = src_strides};
|
||||
ndarray::basic::set_strides_by_shape(&src_ndarray);
|
||||
|
||||
// Create the subscripts in `my_array[2, 100]`
|
||||
int32_t subscript_1 = 2;
|
||||
int32_t subscript_2 = 100;
|
||||
|
||||
const int32_t num_indexes = 2;
|
||||
NDIndex indexes[num_indexes] = {
|
||||
{.type = ND_INDEX_TYPE_SINGLE_ELEMENT, .data = (uint8_t *)&subscript_1},
|
||||
{.type = ND_INDEX_TYPE_SINGLE_ELEMENT,
|
||||
.data = (uint8_t *)&subscript_2}};
|
||||
|
||||
// Prepare dst_ndarray
|
||||
const int32_t dst_ndims = 0;
|
||||
int32_t dst_shape[dst_ndims] = {};
|
||||
int32_t dst_strides[dst_ndims] = {};
|
||||
NDArray<int32_t> dst_ndarray = {.data = nullptr, // placehloder
|
||||
.ndims = dst_ndims,
|
||||
.shape = dst_shape,
|
||||
.strides = dst_strides};
|
||||
|
||||
ErrorContext errctx = create_testing_errctx();
|
||||
ndarray::indexing::index(&errctx, num_indexes, indexes, &src_ndarray,
|
||||
&dst_ndarray);
|
||||
assert_errctx_has_exception(&errctx, errctx.exceptions->index_error);
|
||||
}
|
||||
|
||||
void run() {
|
||||
test_normal_1();
|
||||
test_normal_2();
|
||||
test_index_subscript_out_of_bounds();
|
||||
}
|
||||
} // namespace ndarray_indexing
|
||||
} // namespace test
|
||||
|
|
@ -0,0 +1,92 @@
|
|||
#pragma once
|
||||
|
||||
#include <irrt_everything.hpp>
|
||||
#include <test/includes.hpp>
|
||||
|
||||
namespace test {
|
||||
namespace slice {
|
||||
void test_slice_normal() {
|
||||
// Normal situation
|
||||
BEGIN_TEST();
|
||||
|
||||
UserSlice user_slice;
|
||||
user_slice.set_stop(5);
|
||||
|
||||
Slice slice = user_slice.indices(100);
|
||||
|
||||
printf("%d, %d, %d\n", slice.start, slice.stop, slice.step);
|
||||
|
||||
assert_values_match(0, slice.start);
|
||||
assert_values_match(5, slice.stop);
|
||||
assert_values_match(1, slice.step);
|
||||
}
|
||||
|
||||
void test_slice_start_too_large() {
|
||||
// Start is too large and should be clamped to length
|
||||
BEGIN_TEST();
|
||||
|
||||
UserSlice user_slice;
|
||||
user_slice.set_start(400);
|
||||
|
||||
Slice slice = user_slice.indices(100);
|
||||
|
||||
assert_values_match(100, slice.start);
|
||||
assert_values_match(100, slice.stop);
|
||||
assert_values_match(1, slice.step);
|
||||
}
|
||||
|
||||
void test_slice_negative_start_stop() {
|
||||
// Negative start/stop should be resolved
|
||||
BEGIN_TEST();
|
||||
|
||||
UserSlice user_slice;
|
||||
user_slice.set_start(-10);
|
||||
user_slice.set_stop(-5);
|
||||
|
||||
Slice slice = user_slice.indices(100);
|
||||
|
||||
assert_values_match(90, slice.start);
|
||||
assert_values_match(95, slice.stop);
|
||||
assert_values_match(1, slice.step);
|
||||
}
|
||||
|
||||
void test_slice_only_negative_step() {
|
||||
// Things like `[::-5]` should be handled correctly
|
||||
BEGIN_TEST();
|
||||
|
||||
UserSlice user_slice;
|
||||
user_slice.set_step(-5);
|
||||
|
||||
Slice slice = user_slice.indices(100);
|
||||
|
||||
assert_values_match(99, slice.start);
|
||||
assert_values_match(-1, slice.stop);
|
||||
assert_values_match(-5, slice.step);
|
||||
}
|
||||
|
||||
void test_slice_step_zero() {
|
||||
// Step = 0 is a value error
|
||||
BEGIN_TEST();
|
||||
|
||||
ErrorContext errctx = create_testing_errctx();
|
||||
|
||||
UserSlice user_slice;
|
||||
user_slice.set_start(2);
|
||||
user_slice.set_stop(12);
|
||||
user_slice.set_step(0);
|
||||
|
||||
Slice slice;
|
||||
user_slice.indices_checked(&errctx, 100, &slice);
|
||||
|
||||
assert_errctx_has_exception(&errctx, errctx.exceptions->value_error);
|
||||
}
|
||||
|
||||
void run() {
|
||||
test_slice_normal();
|
||||
test_slice_start_too_large();
|
||||
test_slice_negative_start_stop();
|
||||
test_slice_only_negative_step();
|
||||
test_slice_step_zero();
|
||||
}
|
||||
} // namespace slice
|
||||
} // namespace test
|
||||
|
|
@ -0,0 +1,188 @@
|
|||
#pragma once
|
||||
|
||||
#include <cstdio>
|
||||
#include <cstdlib>
|
||||
|
||||
template <class T>
|
||||
void print_value(const T& value);
|
||||
|
||||
template <>
|
||||
void print_value(const bool& value) {
|
||||
printf("%s", value ? "true" : "false");
|
||||
}
|
||||
|
||||
template <>
|
||||
void print_value(const int8_t& value) {
|
||||
printf("%d", value);
|
||||
}
|
||||
|
||||
template <>
|
||||
void print_value(const int32_t& value) {
|
||||
printf("%d", value);
|
||||
}
|
||||
|
||||
template <>
|
||||
void print_value(const uint8_t& value) {
|
||||
printf("%u", value);
|
||||
}
|
||||
|
||||
template <>
|
||||
void print_value(const uint32_t& value) {
|
||||
printf("%u", value);
|
||||
}
|
||||
|
||||
template <>
|
||||
void print_value(const float& value) {
|
||||
printf("%f", value);
|
||||
}
|
||||
|
||||
template <>
|
||||
void print_value(const double& value) {
|
||||
printf("%f", value);
|
||||
}
|
||||
|
||||
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__)
|
||||
|
||||
void test_fail() {
|
||||
printf("[!] Test failed. Exiting with status code 1.\n");
|
||||
exit(1);
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
void debug_print_array(int len, const T* as) {
|
||||
printf("[");
|
||||
for (int i = 0; i < len; i++) {
|
||||
if (i != 0) printf(", ");
|
||||
print_value(as[i]);
|
||||
}
|
||||
printf("]");
|
||||
}
|
||||
|
||||
void print_assertion_passed(const char* file, int line) {
|
||||
printf("[*] Assertion passed on %s:%d\n", file, line);
|
||||
}
|
||||
|
||||
void print_assertion_failed(const char* file, int line) {
|
||||
printf("[!] Assertion failed on %s:%d\n", file, line);
|
||||
}
|
||||
|
||||
void __assert_true(const char* file, int line, bool cond) {
|
||||
if (cond) {
|
||||
print_assertion_passed(file, line);
|
||||
} else {
|
||||
print_assertion_failed(file, line);
|
||||
test_fail();
|
||||
}
|
||||
}
|
||||
|
||||
#define assert_true(cond) __assert_true(__FILE__, __LINE__, cond)
|
||||
|
||||
template <typename T>
|
||||
void __assert_arrays_match(const char* file, int line, int len,
|
||||
const T* expected, const T* got) {
|
||||
if (arrays_match(len, expected, got)) {
|
||||
print_assertion_passed(file, line);
|
||||
} else {
|
||||
print_assertion_failed(file, line);
|
||||
printf("Expect = ");
|
||||
debug_print_array(len, expected);
|
||||
printf("\n");
|
||||
printf(" Got = ");
|
||||
debug_print_array(len, got);
|
||||
printf("\n");
|
||||
test_fail();
|
||||
}
|
||||
}
|
||||
|
||||
#define assert_arrays_match(len, expected, got) \
|
||||
__assert_arrays_match(__FILE__, __LINE__, len, expected, got)
|
||||
|
||||
template <typename T>
|
||||
void __assert_values_match(const char* file, int line, T expected, T got) {
|
||||
if (expected == got) {
|
||||
print_assertion_passed(file, line);
|
||||
} else {
|
||||
print_assertion_failed(file, line);
|
||||
printf("Expect = ");
|
||||
print_value(expected);
|
||||
printf("\n");
|
||||
printf(" Got = ");
|
||||
print_value(got);
|
||||
printf("\n");
|
||||
test_fail();
|
||||
}
|
||||
}
|
||||
|
||||
#define assert_values_match(expected, got) \
|
||||
__assert_values_match(__FILE__, __LINE__, expected, got)
|
||||
|
||||
// A fake set of ExceptionIds for testing only
|
||||
const ErrorContextExceptions TEST_ERROR_CONTEXT_EXCEPTIONS = {
|
||||
.index_error = 0,
|
||||
.value_error = 1,
|
||||
.assertion_error = 2,
|
||||
.runtime_error = 3,
|
||||
.type_error = 4,
|
||||
};
|
||||
|
||||
ErrorContext create_testing_errctx() {
|
||||
// Everything is global so it is fine to directly return a struct
|
||||
// ErrorContext
|
||||
ErrorContext errctx;
|
||||
errctx.initialize(&TEST_ERROR_CONTEXT_EXCEPTIONS);
|
||||
return errctx;
|
||||
}
|
||||
|
||||
void print_errctx_content(ErrorContext* errctx) {
|
||||
if (errctx->has_exception()) {
|
||||
printf(
|
||||
"(Exception ID %d): %s ... where param1 = %ld, param2 = %ld, "
|
||||
"param3 = "
|
||||
"%ld\n",
|
||||
errctx->exception_id, errctx->msg, errctx->param1, errctx->param2,
|
||||
errctx->param3);
|
||||
} else {
|
||||
printf("<no exception>\n");
|
||||
}
|
||||
}
|
||||
|
||||
void __assert_errctx_no_exception(const char* file, int line,
|
||||
ErrorContext* errctx) {
|
||||
if (errctx->has_exception()) {
|
||||
print_assertion_failed(file, line);
|
||||
printf("Expecting no exception but caught the following:\n\n");
|
||||
print_errctx_content(errctx);
|
||||
test_fail();
|
||||
}
|
||||
}
|
||||
|
||||
#define assert_errctx_no_exception(errctx) \
|
||||
__assert_errctx_no_exception(__FILE__, __LINE__, errctx)
|
||||
|
||||
void __assert_errctx_has_exception(const char* file, int line,
|
||||
ErrorContext* errctx,
|
||||
ExceptionId expected_exception_id) {
|
||||
if (errctx->has_exception()) {
|
||||
if (errctx->exception_id != expected_exception_id) {
|
||||
print_assertion_failed(file, line);
|
||||
printf(
|
||||
"Expecting exception id %d but got exception id %d. Error "
|
||||
"caught:\n\n",
|
||||
expected_exception_id, errctx->exception_id);
|
||||
print_errctx_content(errctx);
|
||||
test_fail();
|
||||
}
|
||||
} else {
|
||||
print_assertion_failed(file, line);
|
||||
printf("Expecting an exception, but there is none.");
|
||||
test_fail();
|
||||
}
|
||||
}
|
||||
|
||||
#define assert_errctx_has_exception(errctx, expected_exception_id) \
|
||||
__assert_errctx_has_exception(__FILE__, __LINE__, errctx, \
|
||||
expected_exception_id)
|
||||
|
|
@ -1,94 +1,26 @@
|
|||
use inkwell::types::BasicTypeEnum;
|
||||
use inkwell::values::{BasicValue, BasicValueEnum, IntValue, PointerValue};
|
||||
use inkwell::values::BasicValueEnum;
|
||||
use inkwell::{FloatPredicate, IntPredicate, OptimizationLevel};
|
||||
use itertools::Itertools;
|
||||
|
||||
use crate::codegen::classes::{
|
||||
ArrayLikeValue, NDArrayValue, ProxyValue, RangeValue, TypedArrayLikeAccessor,
|
||||
UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
|
||||
};
|
||||
use crate::codegen::expr::destructure_range;
|
||||
use crate::codegen::irrt::calculate_len_for_slice_range;
|
||||
use crate::codegen::macros::codegen_unreachable;
|
||||
use crate::codegen::classes::{NDArrayValue, ProxyValue, UntypedArrayLikeAccessor};
|
||||
use crate::codegen::numpy::ndarray_elementwise_unaryop_impl;
|
||||
use crate::codegen::stmt::gen_for_callback_incrementing;
|
||||
use crate::codegen::{extern_fns, irrt, llvm_intrinsics, numpy, CodeGenContext, CodeGenerator};
|
||||
use crate::toplevel::helper::PrimDef;
|
||||
use crate::toplevel::numpy::unpack_ndarray_var_tys;
|
||||
use crate::typecheck::typedef::{Type, TypeEnum};
|
||||
use crate::typecheck::typedef::Type;
|
||||
|
||||
/// Shorthand for [`unreachable!()`] when a type of argument is not supported.
|
||||
///
|
||||
/// The generated message will contain the function name and the name of the unsupported type.
|
||||
fn unsupported_type(ctx: &CodeGenContext<'_, '_>, fn_name: &str, tys: &[Type]) -> ! {
|
||||
codegen_unreachable!(
|
||||
ctx,
|
||||
unreachable!(
|
||||
"{fn_name}() not supported for '{}'",
|
||||
tys.iter().map(|ty| format!("'{}'", ctx.unifier.stringify(*ty))).join(", "),
|
||||
)
|
||||
}
|
||||
|
||||
/// Invokes the `len` builtin function.
|
||||
pub fn call_len<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
n: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<IntValue<'ctx>, String> {
|
||||
let llvm_i32 = ctx.ctx.i32_type();
|
||||
let range_ty = ctx.primitives.range;
|
||||
let (arg_ty, arg) = n;
|
||||
|
||||
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);
|
||||
calculate_len_for_slice_range(generator, ctx, start, end, step)
|
||||
} else {
|
||||
match &*ctx.unifier.get_ty_immutable(arg_ty) {
|
||||
TypeEnum::TTuple { ty, .. } => llvm_i32.const_int(ty.len() as u64, false),
|
||||
TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::List.id() => {
|
||||
let zero = llvm_i32.const_zero();
|
||||
let len = ctx
|
||||
.build_gep_and_load(
|
||||
arg.into_pointer_value(),
|
||||
&[zero, llvm_i32.const_int(1, false)],
|
||||
None,
|
||||
)
|
||||
.into_int_value();
|
||||
ctx.builder.build_int_truncate_or_bit_cast(len, llvm_i32, "len").unwrap()
|
||||
}
|
||||
TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
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",
|
||||
"len() of unsized object",
|
||||
[None, None, None],
|
||||
ctx.current_loc,
|
||||
);
|
||||
|
||||
let len = unsafe {
|
||||
arg.dim_sizes().get_typed_unchecked(
|
||||
ctx,
|
||||
generator,
|
||||
&llvm_usize.const_zero(),
|
||||
None,
|
||||
)
|
||||
};
|
||||
|
||||
ctx.builder.build_int_truncate_or_bit_cast(len, llvm_i32, "len").unwrap()
|
||||
}
|
||||
_ => codegen_unreachable!(ctx),
|
||||
}
|
||||
})
|
||||
}
|
||||
|
||||
/// Invokes the `int32` builtin function.
|
||||
pub fn call_int32<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
|
|
@ -99,6 +31,7 @@ pub fn call_int32<'ctx, G: CodeGenerator + ?Sized>(
|
|||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
let (n_ty, n) = n;
|
||||
|
||||
Ok(match n {
|
||||
BasicValueEnum::IntValue(n) if matches!(n.get_type().get_bit_width(), 1 | 8) => {
|
||||
debug_assert!(ctx.unifier.unioned(n_ty, ctx.primitives.bool));
|
||||
|
|
@ -669,7 +602,7 @@ pub fn call_ceil<'ctx, G: CodeGenerator + ?Sized>(
|
|||
ret_elem_ty,
|
||||
None,
|
||||
NDArrayValue::from_ptr_val(n, llvm_usize, None),
|
||||
|generator, ctx, val| call_ceil(generator, ctx, (elem_ty, val), ret_elem_ty),
|
||||
|generator, ctx, val| call_floor(generator, ctx, (elem_ty, val), ret_elem_ty),
|
||||
)?;
|
||||
|
||||
ndarray.as_base_value().into()
|
||||
|
|
@ -786,7 +719,7 @@ pub fn call_numpy_minimum<'ctx, G: CodeGenerator + ?Sized>(
|
|||
} else if is_ndarray2 {
|
||||
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
|
||||
} else {
|
||||
codegen_unreachable!(ctx)
|
||||
unreachable!()
|
||||
};
|
||||
|
||||
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
|
||||
|
|
@ -890,7 +823,7 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
|
|||
match fn_name {
|
||||
"np_argmin" | "np_argmax" => llvm_int64.const_zero().into(),
|
||||
"np_max" | "np_min" => a,
|
||||
_ => codegen_unreachable!(ctx),
|
||||
_ => unreachable!(),
|
||||
}
|
||||
}
|
||||
BasicValueEnum::PointerValue(n)
|
||||
|
|
@ -945,7 +878,7 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
|
|||
"np_argmax" | "np_max" => {
|
||||
call_max(ctx, (elem_ty, accumulator), (elem_ty, elem))
|
||||
}
|
||||
_ => codegen_unreachable!(ctx),
|
||||
_ => unreachable!(),
|
||||
};
|
||||
|
||||
let updated_idx = match (accumulator, result) {
|
||||
|
|
@ -982,7 +915,7 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
|
|||
match fn_name {
|
||||
"np_argmin" | "np_argmax" => ctx.builder.build_load(res_idx, "").unwrap(),
|
||||
"np_max" | "np_min" => ctx.builder.build_load(accumulator_addr, "").unwrap(),
|
||||
_ => codegen_unreachable!(ctx),
|
||||
_ => unreachable!(),
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -1048,7 +981,7 @@ pub fn call_numpy_maximum<'ctx, G: CodeGenerator + ?Sized>(
|
|||
} else if is_ndarray2 {
|
||||
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
|
||||
} else {
|
||||
codegen_unreachable!(ctx)
|
||||
unreachable!()
|
||||
};
|
||||
|
||||
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
|
||||
|
|
@ -1078,9 +1011,9 @@ pub fn call_numpy_maximum<'ctx, G: CodeGenerator + ?Sized>(
|
|||
/// * `(arg_ty, arg_val)`: The [`Type`] and llvm value of the input argument.
|
||||
/// * `fn_name`: The name of the function, only used when throwing an error with [`unsupported_type`]
|
||||
/// * `get_ret_elem_type`: A function that takes in the input scalar [`Type`], and returns the function's return scalar [`Type`].
|
||||
/// Return a constant [`Type`] here if the return type does not depend on the input type.
|
||||
/// Return a constant [`Type`] here if the return type does not depend on the input type.
|
||||
/// * `on_scalar`: The function that acts on the scalars of the input. Returns [`Option::None`]
|
||||
/// if the scalar type & value are faulty and should panic with [`unsupported_type`].
|
||||
/// if the scalar type & value are faulty and should panic with [`unsupported_type`].
|
||||
fn helper_call_numpy_unary_elementwise<'ctx, OnScalarFn, RetElemFn, G>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
|
|
@ -1191,9 +1124,9 @@ pub fn call_abs<'ctx, G: CodeGenerator + ?Sized>(
|
|||
/// * `$name:ident`: The identifier of the rust function to be generated.
|
||||
/// * `$fn_name:literal`: To be passed to the `fn_name` parameter of [`helper_call_numpy_unary_elementwise`]
|
||||
/// * `$get_ret_elem_type:expr`: To be passed to the `get_ret_elem_type` parameter of [`helper_call_numpy_unary_elementwise`].
|
||||
/// But there is no need to make it a reference.
|
||||
/// But there is no need to make it a reference.
|
||||
/// * `$on_scalar:expr`: To be passed to the `on_scalar` parameter of [`helper_call_numpy_unary_elementwise`].
|
||||
/// But there is no need to make it a reference.
|
||||
/// But there is no need to make it a reference.
|
||||
macro_rules! create_helper_call_numpy_unary_elementwise {
|
||||
($name:ident, $fn_name:literal, $get_ret_elem_type:expr, $on_scalar:expr) => {
|
||||
#[allow(clippy::redundant_closure_call)]
|
||||
|
|
@ -1220,7 +1153,7 @@ macro_rules! create_helper_call_numpy_unary_elementwise {
|
|||
/// * `$name:ident`: The identifier of the rust function to be generated.
|
||||
/// * `$fn_name:literal`: To be passed to the `fn_name` parameter of [`helper_call_numpy_unary_elementwise`].
|
||||
/// * `$on_scalar:expr`: The closure (see below for its type) that acts on float scalar values and returns
|
||||
/// the boolean results of LLVM type `i1`. The returned `i1` value will be converted into an `i8`.
|
||||
/// the boolean results of LLVM type `i1`. The returned `i1` value will be converted into an `i8`.
|
||||
///
|
||||
/// ```ignore
|
||||
/// // Type of `$on_scalar:expr`
|
||||
|
|
@ -1488,7 +1421,7 @@ pub fn call_numpy_arctan2<'ctx, G: CodeGenerator + ?Sized>(
|
|||
} else if is_ndarray2 {
|
||||
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
|
||||
} else {
|
||||
codegen_unreachable!(ctx)
|
||||
unreachable!()
|
||||
};
|
||||
|
||||
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
|
||||
|
|
@ -1555,7 +1488,7 @@ pub fn call_numpy_copysign<'ctx, G: CodeGenerator + ?Sized>(
|
|||
} else if is_ndarray2 {
|
||||
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
|
||||
} else {
|
||||
codegen_unreachable!(ctx)
|
||||
unreachable!()
|
||||
};
|
||||
|
||||
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
|
||||
|
|
@ -1622,7 +1555,7 @@ pub fn call_numpy_fmax<'ctx, G: CodeGenerator + ?Sized>(
|
|||
} else if is_ndarray2 {
|
||||
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
|
||||
} else {
|
||||
codegen_unreachable!(ctx)
|
||||
unreachable!()
|
||||
};
|
||||
|
||||
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
|
||||
|
|
@ -1689,7 +1622,7 @@ pub fn call_numpy_fmin<'ctx, G: CodeGenerator + ?Sized>(
|
|||
} else if is_ndarray2 {
|
||||
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
|
||||
} else {
|
||||
codegen_unreachable!(ctx)
|
||||
unreachable!()
|
||||
};
|
||||
|
||||
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
|
||||
|
|
@ -1812,7 +1745,7 @@ pub fn call_numpy_hypot<'ctx, G: CodeGenerator + ?Sized>(
|
|||
} else if is_ndarray2 {
|
||||
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
|
||||
} else {
|
||||
codegen_unreachable!(ctx)
|
||||
unreachable!()
|
||||
};
|
||||
|
||||
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
|
||||
|
|
@ -1879,7 +1812,7 @@ pub fn call_numpy_nextafter<'ctx, G: CodeGenerator + ?Sized>(
|
|||
} else if is_ndarray2 {
|
||||
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
|
||||
} else {
|
||||
codegen_unreachable!(ctx)
|
||||
unreachable!()
|
||||
};
|
||||
|
||||
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
|
||||
|
|
@ -1903,501 +1836,3 @@ pub fn call_numpy_nextafter<'ctx, G: CodeGenerator + ?Sized>(
|
|||
_ => unsupported_type(ctx, FN_NAME, &[x1_ty, x2_ty]),
|
||||
})
|
||||
}
|
||||
|
||||
/// Allocates a struct with the fields specified by `out_matrices` and returns a pointer to it
|
||||
fn build_output_struct<'ctx>(
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
out_matrices: Vec<BasicValueEnum<'ctx>>,
|
||||
) -> PointerValue<'ctx> {
|
||||
let field_ty =
|
||||
out_matrices.iter().map(BasicValueEnum::get_type).collect::<Vec<BasicTypeEnum>>();
|
||||
let out_ty = ctx.ctx.struct_type(&field_ty, false);
|
||||
let out_ptr = ctx.builder.build_alloca(out_ty, "").unwrap();
|
||||
|
||||
for (i, v) in out_matrices.into_iter().enumerate() {
|
||||
unsafe {
|
||||
let ptr = ctx
|
||||
.builder
|
||||
.build_in_bounds_gep(
|
||||
out_ptr,
|
||||
&[
|
||||
ctx.ctx.i32_type().const_zero(),
|
||||
ctx.ctx.i32_type().const_int(i as u64, false),
|
||||
],
|
||||
"",
|
||||
)
|
||||
.unwrap();
|
||||
ctx.builder.build_store(ptr, v).unwrap();
|
||||
}
|
||||
}
|
||||
out_ptr
|
||||
}
|
||||
|
||||
/// Invokes the `np_linalg_cholesky` linalg function
|
||||
pub fn call_np_linalg_cholesky<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
x1: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String> {
|
||||
const FN_NAME: &str = "np_linalg_cholesky";
|
||||
let (x1_ty, x1) = x1;
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
if let BasicValueEnum::PointerValue(n1) = x1 {
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
|
||||
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
|
||||
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty]);
|
||||
};
|
||||
|
||||
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
|
||||
let dim0 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
|
||||
.into_int_value()
|
||||
};
|
||||
let dim1 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
|
||||
.into_int_value()
|
||||
};
|
||||
|
||||
let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim1])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
|
||||
extern_fns::call_np_linalg_cholesky(ctx, x1, out, None);
|
||||
Ok(out)
|
||||
} else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty])
|
||||
}
|
||||
}
|
||||
|
||||
/// Invokes the `np_linalg_qr` linalg function
|
||||
pub fn call_np_linalg_qr<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
x1: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String> {
|
||||
const FN_NAME: &str = "np_linalg_qr";
|
||||
let (x1_ty, x1) = x1;
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
if let BasicValueEnum::PointerValue(n1) = x1 {
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
|
||||
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
|
||||
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
|
||||
unimplemented!("{FN_NAME} operates on float type NdArrays only");
|
||||
};
|
||||
|
||||
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
|
||||
let dim0 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
|
||||
.into_int_value()
|
||||
};
|
||||
let dim1 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
|
||||
.into_int_value()
|
||||
};
|
||||
let k = llvm_intrinsics::call_int_smin(ctx, dim0, dim1, None);
|
||||
|
||||
let out_q = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, k])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
let out_r = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[k, dim1])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
|
||||
extern_fns::call_np_linalg_qr(ctx, x1, out_q, out_r, None);
|
||||
|
||||
let out_ptr = build_output_struct(ctx, vec![out_q, out_r]);
|
||||
|
||||
Ok(ctx.builder.build_load(out_ptr, "QR_Factorization_result").map(Into::into).unwrap())
|
||||
} else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty])
|
||||
}
|
||||
}
|
||||
|
||||
/// Invokes the `np_linalg_svd` linalg function
|
||||
pub fn call_np_linalg_svd<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
x1: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String> {
|
||||
const FN_NAME: &str = "np_linalg_svd";
|
||||
let (x1_ty, x1) = x1;
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
if let BasicValueEnum::PointerValue(n1) = x1 {
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
|
||||
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
|
||||
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty]);
|
||||
};
|
||||
|
||||
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
|
||||
|
||||
let dim0 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
|
||||
.into_int_value()
|
||||
};
|
||||
let dim1 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
|
||||
.into_int_value()
|
||||
};
|
||||
let k = llvm_intrinsics::call_int_smin(ctx, dim0, dim1, None);
|
||||
|
||||
let out_u = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
let out_s = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[k])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
let out_vh = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim1, dim1])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
|
||||
extern_fns::call_np_linalg_svd(ctx, x1, out_u, out_s, out_vh, None);
|
||||
|
||||
let out_ptr = build_output_struct(ctx, vec![out_u, out_s, out_vh]);
|
||||
|
||||
Ok(ctx.builder.build_load(out_ptr, "SVD_Factorization_result").map(Into::into).unwrap())
|
||||
} else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty])
|
||||
}
|
||||
}
|
||||
|
||||
/// Invokes the `np_linalg_inv` linalg function
|
||||
pub fn call_np_linalg_inv<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
x1: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String> {
|
||||
const FN_NAME: &str = "np_linalg_inv";
|
||||
let (x1_ty, x1) = x1;
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
if let BasicValueEnum::PointerValue(n1) = x1 {
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
|
||||
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
|
||||
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty]);
|
||||
};
|
||||
|
||||
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
|
||||
let dim0 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
|
||||
.into_int_value()
|
||||
};
|
||||
let dim1 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
|
||||
.into_int_value()
|
||||
};
|
||||
|
||||
let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim1])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
|
||||
extern_fns::call_np_linalg_inv(ctx, x1, out, None);
|
||||
Ok(out)
|
||||
} else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty])
|
||||
}
|
||||
}
|
||||
|
||||
/// Invokes the `np_linalg_pinv` linalg function
|
||||
pub fn call_np_linalg_pinv<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
x1: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String> {
|
||||
const FN_NAME: &str = "np_linalg_pinv";
|
||||
let (x1_ty, x1) = x1;
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
if let BasicValueEnum::PointerValue(n1) = x1 {
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
|
||||
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
|
||||
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty]);
|
||||
};
|
||||
|
||||
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
|
||||
|
||||
let dim0 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
|
||||
.into_int_value()
|
||||
};
|
||||
let dim1 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
|
||||
.into_int_value()
|
||||
};
|
||||
|
||||
let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim1, dim0])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
|
||||
extern_fns::call_np_linalg_pinv(ctx, x1, out, None);
|
||||
Ok(out)
|
||||
} else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty])
|
||||
}
|
||||
}
|
||||
|
||||
/// Invokes the `sp_linalg_lu` linalg function
|
||||
pub fn call_sp_linalg_lu<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
x1: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String> {
|
||||
const FN_NAME: &str = "sp_linalg_lu";
|
||||
let (x1_ty, x1) = x1;
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
if let BasicValueEnum::PointerValue(n1) = x1 {
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
|
||||
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
|
||||
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty]);
|
||||
};
|
||||
|
||||
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
|
||||
|
||||
let dim0 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
|
||||
.into_int_value()
|
||||
};
|
||||
let dim1 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
|
||||
.into_int_value()
|
||||
};
|
||||
let k = llvm_intrinsics::call_int_smin(ctx, dim0, dim1, None);
|
||||
|
||||
let out_l = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, k])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
let out_u = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[k, dim1])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
|
||||
extern_fns::call_sp_linalg_lu(ctx, x1, out_l, out_u, None);
|
||||
|
||||
let out_ptr = build_output_struct(ctx, vec![out_l, out_u]);
|
||||
Ok(ctx.builder.build_load(out_ptr, "LU_Factorization_result").map(Into::into).unwrap())
|
||||
} else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty])
|
||||
}
|
||||
}
|
||||
|
||||
/// Invokes the `np_linalg_matrix_power` linalg function
|
||||
pub fn call_np_linalg_matrix_power<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
x1: (Type, BasicValueEnum<'ctx>),
|
||||
x2: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String> {
|
||||
const FN_NAME: &str = "np_linalg_matrix_power";
|
||||
let (x1_ty, x1) = x1;
|
||||
let (x2_ty, x2) = x2;
|
||||
let x2 = call_float(generator, ctx, (x2_ty, x2)).unwrap();
|
||||
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
if let (BasicValueEnum::PointerValue(n1), BasicValueEnum::FloatValue(n2)) = (x1, x2) {
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
|
||||
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
|
||||
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty, x2_ty]);
|
||||
};
|
||||
|
||||
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
|
||||
// Changing second parameter to a `NDArray` for uniformity in function call
|
||||
let n2_array = numpy::create_ndarray_const_shape(
|
||||
generator,
|
||||
ctx,
|
||||
elem_ty,
|
||||
&[llvm_usize.const_int(1, false)],
|
||||
)
|
||||
.unwrap();
|
||||
unsafe {
|
||||
n2_array.data().set_unchecked(
|
||||
ctx,
|
||||
generator,
|
||||
&llvm_usize.const_zero(),
|
||||
n2.as_basic_value_enum(),
|
||||
);
|
||||
};
|
||||
let n2_array = n2_array.as_base_value().as_basic_value_enum();
|
||||
|
||||
let outdim0 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
|
||||
.into_int_value()
|
||||
};
|
||||
let outdim1 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
|
||||
.into_int_value()
|
||||
};
|
||||
|
||||
let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[outdim0, outdim1])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
|
||||
extern_fns::call_np_linalg_matrix_power(ctx, x1, n2_array, out, None);
|
||||
Ok(out)
|
||||
} else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty, x2_ty])
|
||||
}
|
||||
}
|
||||
|
||||
/// Invokes the `np_linalg_det` linalg function
|
||||
pub fn call_np_linalg_det<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
x1: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String> {
|
||||
const FN_NAME: &str = "np_linalg_matrix_power";
|
||||
let (x1_ty, x1) = x1;
|
||||
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
if let BasicValueEnum::PointerValue(_) = x1 {
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
|
||||
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
|
||||
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty]);
|
||||
};
|
||||
|
||||
// Changing second parameter to a `NDArray` for uniformity in function call
|
||||
let out = numpy::create_ndarray_const_shape(
|
||||
generator,
|
||||
ctx,
|
||||
elem_ty,
|
||||
&[llvm_usize.const_int(1, false)],
|
||||
)
|
||||
.unwrap();
|
||||
extern_fns::call_np_linalg_det(ctx, x1, out.as_base_value().as_basic_value_enum(), None);
|
||||
let res =
|
||||
unsafe { out.data().get_unchecked(ctx, generator, &llvm_usize.const_zero(), None) };
|
||||
Ok(res)
|
||||
} else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty])
|
||||
}
|
||||
}
|
||||
|
||||
/// Invokes the `sp_linalg_schur` linalg function
|
||||
pub fn call_sp_linalg_schur<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
x1: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String> {
|
||||
const FN_NAME: &str = "sp_linalg_schur";
|
||||
let (x1_ty, x1) = x1;
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
if let BasicValueEnum::PointerValue(n1) = x1 {
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
|
||||
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
|
||||
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty]);
|
||||
};
|
||||
|
||||
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
|
||||
|
||||
let dim0 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
|
||||
.into_int_value()
|
||||
};
|
||||
let out_t = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
let out_z = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
|
||||
extern_fns::call_sp_linalg_schur(ctx, x1, out_t, out_z, None);
|
||||
|
||||
let out_ptr = build_output_struct(ctx, vec![out_t, out_z]);
|
||||
Ok(ctx.builder.build_load(out_ptr, "Schur_Factorization_result").map(Into::into).unwrap())
|
||||
} else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty])
|
||||
}
|
||||
}
|
||||
|
||||
/// Invokes the `sp_linalg_hessenberg` linalg function
|
||||
pub fn call_sp_linalg_hessenberg<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
x1: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String> {
|
||||
const FN_NAME: &str = "sp_linalg_hessenberg";
|
||||
let (x1_ty, x1) = x1;
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
if let BasicValueEnum::PointerValue(n1) = x1 {
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
|
||||
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
|
||||
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty]);
|
||||
};
|
||||
|
||||
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
|
||||
|
||||
let dim0 = unsafe {
|
||||
n1.dim_sizes()
|
||||
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
|
||||
.into_int_value()
|
||||
};
|
||||
let out_h = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
let out_q = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
|
||||
.unwrap()
|
||||
.as_base_value()
|
||||
.as_basic_value_enum();
|
||||
extern_fns::call_sp_linalg_hessenberg(ctx, x1, out_h, out_q, None);
|
||||
|
||||
let out_ptr = build_output_struct(ctx, vec![out_h, out_q]);
|
||||
Ok(ctx
|
||||
.builder
|
||||
.build_load(out_ptr, "Hessenberg_decomposition_result")
|
||||
.map(Into::into)
|
||||
.unwrap())
|
||||
} else {
|
||||
unsupported_type(ctx, FN_NAME, &[x1_ty])
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1250,13 +1250,11 @@ 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()
|
||||
}
|
||||
}
|
||||
|
|
@ -1406,7 +1404,7 @@ 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();
|
||||
|
||||
|
|
|
|||
|
|
@ -25,7 +25,6 @@ pub struct ConcreteFuncArg {
|
|||
pub name: StrRef,
|
||||
pub ty: ConcreteType,
|
||||
pub default_value: Option<SymbolValue>,
|
||||
pub is_vararg: bool,
|
||||
}
|
||||
|
||||
#[derive(Clone, Debug)]
|
||||
|
|
@ -47,7 +46,6 @@ pub enum ConcreteTypeEnum {
|
|||
TPrimitive(Primitive),
|
||||
TTuple {
|
||||
ty: Vec<ConcreteType>,
|
||||
is_vararg_ctx: bool,
|
||||
},
|
||||
TObj {
|
||||
obj_id: DefinitionId,
|
||||
|
|
@ -104,16 +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),
|
||||
|
|
@ -168,12 +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,
|
||||
|
|
@ -259,12 +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) }
|
||||
|
|
@ -289,7 +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
|
|
@ -13,11 +13,11 @@ use crate::codegen::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, $extern_fn:literal) => {
|
||||
|
|
@ -130,62 +130,3 @@ pub fn call_ldexp<'ctx>(
|
|||
.map(Either::unwrap_left)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Macro to generate `np_linalg` and `sp_linalg` functions
|
||||
/// The function takes as input `NDArray` and returns ()
|
||||
///
|
||||
/// Arguments:
|
||||
/// * `$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);
|
||||
|
|
|
|||
|
|
@ -57,7 +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>(
|
||||
|
|
@ -132,39 +131,6 @@ pub trait CodeGenerator {
|
|||
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)
|
||||
}
|
||||
|
||||
/// Generate code for a while expression.
|
||||
/// Return true if the while loop must early return
|
||||
fn gen_while(
|
||||
|
|
|
|||
|
|
@ -0,0 +1,198 @@
|
|||
use super::util::{function::CallFunction, get_sizet_dependent_function_name};
|
||||
use crate::codegen::{
|
||||
model::*,
|
||||
structure::{cslice::CSlice, exception::ExceptionId},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
#[allow(clippy::struct_field_names)]
|
||||
pub struct ErrorContextExceptionsFields<F: FieldVisitor> {
|
||||
pub index_error: F::Field<IntModel<ExceptionId>>,
|
||||
pub value_error: F::Field<IntModel<ExceptionId>>,
|
||||
pub assertion_error: F::Field<IntModel<ExceptionId>>,
|
||||
pub runtime_error: F::Field<IntModel<ExceptionId>>,
|
||||
pub type_error: F::Field<IntModel<ExceptionId>>,
|
||||
}
|
||||
|
||||
/// Corresponds to IRRT's `struct ErrorContextExceptions`
|
||||
#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
|
||||
pub struct ErrorContextExceptions;
|
||||
|
||||
impl StructKind for ErrorContextExceptions {
|
||||
type Fields<F: FieldVisitor> = ErrorContextExceptionsFields<F>;
|
||||
|
||||
fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields {
|
||||
index_error: visitor.add("index_error"),
|
||||
value_error: visitor.add("value_error"),
|
||||
assertion_error: visitor.add("assertion_error"),
|
||||
runtime_error: visitor.add("runtime_error"),
|
||||
type_error: visitor.add("type_error"),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub struct ErrorContextFields<F: FieldVisitor> {
|
||||
pub exceptions: F::Field<PtrModel<StructModel<ErrorContextExceptions>>>,
|
||||
pub exception_id: F::Field<IntModel<ExceptionId>>,
|
||||
pub msg: F::Field<PtrModel<IntModel<Byte>>>,
|
||||
pub param1: F::Field<IntModel<Int64>>,
|
||||
pub param2: F::Field<IntModel<Int64>>,
|
||||
pub param3: F::Field<IntModel<Int64>>,
|
||||
}
|
||||
|
||||
/// Corresponds to IRRT's `struct ErrorContext`
|
||||
#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
|
||||
pub struct ErrorContext;
|
||||
|
||||
impl StructKind for ErrorContext {
|
||||
type Fields<F: FieldVisitor> = ErrorContextFields<F>;
|
||||
|
||||
fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields {
|
||||
exceptions: visitor.add("exceptions"),
|
||||
exception_id: visitor.add("exception_id"),
|
||||
msg: visitor.add("msg"),
|
||||
param1: visitor.add("param1"),
|
||||
param2: visitor.add("param2"),
|
||||
param3: visitor.add("param3"),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Build an [`ErrorContextExceptions`] loaded with resolved [`ExceptionID`]s according to the [`SymbolResolver`].
|
||||
fn build_error_context_exceptions<'ctx>(
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
) -> Ptr<'ctx, StructModel<ErrorContextExceptions>> {
|
||||
let exceptions =
|
||||
StructModel(ErrorContextExceptions).alloca(tyctx, ctx, "error_context_exceptions");
|
||||
let i32_model = IntModel(Int32);
|
||||
|
||||
let get_string_id = |string_id| {
|
||||
i32_model.constant(tyctx, ctx.ctx, ctx.resolver.get_string_id(string_id) as u64)
|
||||
};
|
||||
|
||||
exceptions.gep(ctx, |f| f.index_error).store(ctx, get_string_id("0:IndexError"));
|
||||
exceptions.gep(ctx, |f| f.value_error).store(ctx, get_string_id("0:ValueError"));
|
||||
exceptions.gep(ctx, |f| f.assertion_error).store(ctx, get_string_id("0:AssertionError"));
|
||||
exceptions.gep(ctx, |f| f.runtime_error).store(ctx, get_string_id("0:RuntimeError"));
|
||||
exceptions.gep(ctx, |f| f.type_error).store(ctx, get_string_id("0:TypeError"));
|
||||
|
||||
exceptions
|
||||
}
|
||||
|
||||
pub fn call_nac3_error_context_initialize<'ctx>(
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
perrctx: Ptr<'ctx, StructModel<ErrorContext>>,
|
||||
pexceptions: Ptr<'ctx, StructModel<ErrorContextExceptions>>,
|
||||
) {
|
||||
CallFunction::begin(tyctx, ctx, "__nac3_error_context_initialize")
|
||||
.arg("errctx", perrctx)
|
||||
.arg("exceptions", pexceptions)
|
||||
.returning_void();
|
||||
}
|
||||
|
||||
pub fn call_nac3_error_context_has_exception<'ctx>(
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
perrctx: Ptr<'ctx, StructModel<ErrorContext>>,
|
||||
) -> Int<'ctx, Bool> {
|
||||
CallFunction::begin(tyctx, ctx, "__nac3_error_context_has_exception")
|
||||
.arg("errctx", perrctx)
|
||||
.returning("has_exception")
|
||||
}
|
||||
|
||||
pub fn call_nac3_error_context_get_exception_str<'ctx>(
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
perrctx: Ptr<'ctx, StructModel<ErrorContext>>,
|
||||
dst_str: Ptr<'ctx, StructModel<CSlice>>,
|
||||
) {
|
||||
CallFunction::begin(
|
||||
tyctx,
|
||||
ctx,
|
||||
&get_sizet_dependent_function_name(tyctx, "__nac3_error_context_get_exception_str"),
|
||||
)
|
||||
.arg("errctx", perrctx)
|
||||
.arg("dst_str", dst_str)
|
||||
.returning_void();
|
||||
}
|
||||
|
||||
/// Setup a [`ErrorContext`] that could be passed to IRRT functions taking in a `ErrorContext* errctx`
|
||||
/// for error reporting purposes.
|
||||
///
|
||||
/// Also see: [`check_error_context`]
|
||||
pub fn setup_error_context<'ctx>(
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
) -> Ptr<'ctx, StructModel<ErrorContext>> {
|
||||
let errctx_model = StructModel(ErrorContext);
|
||||
|
||||
let exceptions = build_error_context_exceptions(tyctx, ctx);
|
||||
let errctx_ptr = errctx_model.alloca(tyctx, ctx, "errctx");
|
||||
|
||||
call_nac3_error_context_initialize(tyctx, ctx, errctx_ptr, exceptions);
|
||||
|
||||
errctx_ptr
|
||||
}
|
||||
|
||||
/// Check a [`ErrorContext`] to see if it contains error. **If there is an error,
|
||||
/// a Pythonic exception will be raised in the firmware**.
|
||||
pub fn check_error_context<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
perrctx: Ptr<'ctx, StructModel<ErrorContext>>,
|
||||
) {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let cslice_model = StructModel(CSlice);
|
||||
|
||||
let current_bb = ctx.builder.get_insert_block().unwrap();
|
||||
let irrt_has_exception_bb = ctx.ctx.insert_basic_block_after(current_bb, "irrt_has_exception");
|
||||
let end_bb = ctx.ctx.insert_basic_block_after(irrt_has_exception_bb, "end");
|
||||
|
||||
// Inserting into `current_bb`
|
||||
let has_exception = call_nac3_error_context_has_exception(tyctx, ctx, perrctx);
|
||||
ctx.builder
|
||||
.build_conditional_branch(has_exception.value, irrt_has_exception_bb, end_bb)
|
||||
.unwrap();
|
||||
|
||||
// Inserting into `irrt_has_exception_bb`
|
||||
ctx.builder.position_at_end(irrt_has_exception_bb);
|
||||
|
||||
// Load all the values for `ctx.make_assert_impl_by_id`
|
||||
let pexception_str = cslice_model.alloca(tyctx, ctx, "exception_str");
|
||||
call_nac3_error_context_get_exception_str(tyctx, ctx, perrctx, pexception_str);
|
||||
|
||||
let exception_id = perrctx.gep(ctx, |f| f.exception_id).load(tyctx, ctx, "exception_id");
|
||||
let msg = pexception_str.load(tyctx, ctx, "msg");
|
||||
let param1 = perrctx.gep(ctx, |f| f.param1).load(tyctx, ctx, "param1");
|
||||
let param2 = perrctx.gep(ctx, |f| f.param2).load(tyctx, ctx, "param2");
|
||||
let param3 = perrctx.gep(ctx, |f| f.param3).load(tyctx, ctx, "param3");
|
||||
|
||||
ctx.raise_exn_impl(
|
||||
generator,
|
||||
exception_id,
|
||||
msg,
|
||||
[Some(param1), Some(param2), Some(param3)],
|
||||
ctx.current_loc,
|
||||
);
|
||||
|
||||
// Position to `end_bb` for continuation
|
||||
ctx.builder.position_at_end(end_bb);
|
||||
}
|
||||
|
||||
pub fn call_nac3_dummy_raise<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext,
|
||||
) {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
let errctx = setup_error_context(tyctx, ctx);
|
||||
CallFunction::begin(tyctx, ctx, "__nac3_error_dummy_raise")
|
||||
.arg("errctx", errctx)
|
||||
.returning_void();
|
||||
|
||||
check_error_context(generator, ctx, errctx);
|
||||
}
|
||||
|
|
@ -1,29 +1,35 @@
|
|||
use crate::{symbol_resolver::SymbolResolver, typecheck::typedef::Type};
|
||||
use crate::typecheck::typedef::Type;
|
||||
|
||||
pub mod error_context;
|
||||
pub mod ndarray;
|
||||
pub mod slice;
|
||||
mod test;
|
||||
mod util;
|
||||
|
||||
use super::model::*;
|
||||
use super::{
|
||||
classes::{
|
||||
ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue,
|
||||
TypedArrayLikeAccessor, TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
|
||||
TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
|
||||
},
|
||||
llvm_intrinsics,
|
||||
macros::codegen_unreachable,
|
||||
stmt::gen_for_callback_incrementing,
|
||||
CodeGenContext, CodeGenerator,
|
||||
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},
|
||||
values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue},
|
||||
AddressSpace, IntPredicate,
|
||||
};
|
||||
use itertools::Either;
|
||||
use nac3parser::ast::Expr;
|
||||
|
||||
#[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",
|
||||
|
|
@ -39,25 +45,6 @@ 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
|
||||
}
|
||||
|
||||
|
|
@ -75,7 +62,7 @@ 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(|| {
|
||||
|
|
@ -434,14 +421,29 @@ pub fn list_slice_assignment<'ctx, G: CodeGenerator + ?Sized>(
|
|||
.unwrap();
|
||||
let cond_1 = ctx.builder.build_and(dest_step_eq_one, src_slt_dest, "slice_cond_1").unwrap();
|
||||
let cond = ctx.builder.build_or(src_eq_dest, cond_1, "slice_cond").unwrap();
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
cond,
|
||||
"0:ValueError",
|
||||
"attempt to assign sequence of size {0} to slice of size {1} with step size {2}",
|
||||
[Some(src_slice_len), Some(dest_slice_len), Some(dest_idx.2)],
|
||||
ctx.current_loc,
|
||||
);
|
||||
|
||||
// TODO: Temporary fix. Rewrite `list_slice_assignment` later
|
||||
// Exception params should have been i64
|
||||
{
|
||||
let type_context = generator.type_context(ctx.ctx);
|
||||
let param_model = IntModel(Int64);
|
||||
|
||||
let src_slice_len =
|
||||
param_model.s_extend_or_bit_cast(type_context, ctx, src_slice_len, "src_slice_len");
|
||||
let dest_slice_len =
|
||||
param_model.s_extend_or_bit_cast(type_context, ctx, dest_slice_len, "dest_slice_len");
|
||||
let dest_idx_2 =
|
||||
param_model.s_extend_or_bit_cast(type_context, ctx, dest_idx.2, "dest_idx_2");
|
||||
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
cond,
|
||||
"0:ValueError",
|
||||
"attempt to assign sequence of size {0} to slice of size {1} with step size {2}",
|
||||
[Some(src_slice_len.value), Some(dest_slice_len.value), Some(dest_idx_2.value)],
|
||||
ctx.current_loc,
|
||||
);
|
||||
}
|
||||
|
||||
let new_len = {
|
||||
let args = vec![
|
||||
|
|
@ -461,7 +463,7 @@ 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()
|
||||
}
|
||||
|
|
@ -588,8 +590,7 @@ pub fn call_j0<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> Flo
|
|||
///
|
||||
/// * `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.
|
||||
/// 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, '_>,
|
||||
|
|
@ -606,7 +607,7 @@ where
|
|||
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),
|
||||
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()],
|
||||
|
|
@ -641,7 +642,7 @@ where
|
|||
///
|
||||
/// * `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`.
|
||||
/// `NDArray`.
|
||||
pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
|
|
@ -657,7 +658,7 @@ pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
|
|||
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),
|
||||
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(|| {
|
||||
|
|
@ -726,7 +727,7 @@ where
|
|||
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),
|
||||
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(|| {
|
||||
|
|
@ -765,7 +766,7 @@ where
|
|||
/// multidimensional index.
|
||||
///
|
||||
/// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
|
||||
/// `NDArray`.
|
||||
/// `NDArray`.
|
||||
/// * `indices` - The multidimensional index to compute the flattened index for.
|
||||
pub fn call_ndarray_flatten_index<'ctx, G, Index>(
|
||||
generator: &mut G,
|
||||
|
|
@ -794,7 +795,7 @@ pub fn call_ndarray_calc_broadcast<'ctx, G: CodeGenerator + ?Sized>(
|
|||
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),
|
||||
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(|| {
|
||||
|
|
@ -914,7 +915,7 @@ pub fn call_ndarray_calc_broadcast_index<
|
|||
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),
|
||||
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(|| {
|
||||
|
|
|
|||
|
|
@ -0,0 +1,153 @@
|
|||
use crate::codegen::irrt::error_context::{check_error_context, setup_error_context};
|
||||
use crate::codegen::irrt::slice::SliceIndex;
|
||||
use crate::codegen::irrt::util::function::CallFunction;
|
||||
use crate::codegen::irrt::util::get_sizet_dependent_function_name;
|
||||
use crate::codegen::model::*;
|
||||
use crate::codegen::structure::ndarray::NpArray;
|
||||
use crate::codegen::{CodeGenContext, CodeGenerator};
|
||||
|
||||
pub fn call_nac3_ndarray_size<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndarray_ptr: Ptr<'ctx, StructModel<NpArray>>,
|
||||
) -> Int<'ctx, SizeT> {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
CallFunction::begin(
|
||||
tyctx,
|
||||
ctx,
|
||||
&get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_size"),
|
||||
)
|
||||
.arg("ndarray", ndarray_ptr)
|
||||
.returning("size")
|
||||
}
|
||||
|
||||
pub fn call_nac3_ndarray_nbytes<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndarray_ptr: Ptr<'ctx, StructModel<NpArray>>,
|
||||
) -> Int<'ctx, SizeT> {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
CallFunction::begin(
|
||||
tyctx,
|
||||
ctx,
|
||||
&get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_nbytes"),
|
||||
)
|
||||
.arg("ndarray", ndarray_ptr)
|
||||
.returning("nbytes")
|
||||
}
|
||||
|
||||
pub fn call_nac3_ndarray_len<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndarray_ptr: Ptr<'ctx, StructModel<NpArray>>,
|
||||
) -> Int<'ctx, SliceIndex> {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let slice_index_model = IntModel(SliceIndex::default());
|
||||
|
||||
let dst_len = slice_index_model.alloca(tyctx, ctx, "dst_len");
|
||||
|
||||
let errctx = setup_error_context(tyctx, ctx);
|
||||
CallFunction::begin(
|
||||
tyctx,
|
||||
ctx,
|
||||
&get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_len"),
|
||||
)
|
||||
.arg("errctx", errctx)
|
||||
.arg("ndarray", ndarray_ptr)
|
||||
.arg("dst_len", dst_len)
|
||||
.returning_void();
|
||||
check_error_context(generator, ctx, errctx);
|
||||
|
||||
dst_len.load(tyctx, ctx, "len")
|
||||
}
|
||||
|
||||
pub fn call_nac3_ndarray_util_assert_shape_no_negative<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndims: Int<'ctx, SizeT>,
|
||||
shape: Ptr<'ctx, IntModel<SizeT>>,
|
||||
) {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
let errctx = setup_error_context(tyctx, ctx);
|
||||
CallFunction::begin(
|
||||
tyctx,
|
||||
ctx,
|
||||
&get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_util_assert_shape_no_negative"),
|
||||
)
|
||||
.arg("errctx", errctx)
|
||||
.arg("ndims", ndims)
|
||||
.arg("shape", shape)
|
||||
.returning_void();
|
||||
check_error_context(generator, ctx, errctx);
|
||||
}
|
||||
|
||||
pub fn call_nac3_ndarray_set_strides_by_shape<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndarray_ptr: Ptr<'ctx, StructModel<NpArray>>,
|
||||
) {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
CallFunction::begin(
|
||||
tyctx,
|
||||
ctx,
|
||||
&get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_set_strides_by_shape"),
|
||||
)
|
||||
.arg("ndarray", ndarray_ptr)
|
||||
.returning_void();
|
||||
}
|
||||
|
||||
pub fn call_nac3_ndarray_is_c_contiguous<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndarray_ptr: Ptr<'ctx, StructModel<NpArray>>,
|
||||
) -> Int<'ctx, Bool> {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
CallFunction::begin(
|
||||
tyctx,
|
||||
ctx,
|
||||
&get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_is_c_contiguous"),
|
||||
)
|
||||
.arg("ndarray", ndarray_ptr)
|
||||
.returning("is_c_contiguous")
|
||||
}
|
||||
|
||||
pub fn call_nac3_ndarray_copy_data<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
src_ndarray: Ptr<'ctx, StructModel<NpArray>>,
|
||||
dst_ndarray: Ptr<'ctx, StructModel<NpArray>>,
|
||||
) {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
CallFunction::begin(
|
||||
tyctx,
|
||||
ctx,
|
||||
&get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_copy_data"),
|
||||
)
|
||||
.arg("src_ndarray", src_ndarray)
|
||||
.arg("dst_ndarray", dst_ndarray)
|
||||
.returning_void();
|
||||
}
|
||||
|
||||
pub fn call_nac3_ndarray_get_nth_pelement<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
pndarray: Ptr<'ctx, StructModel<NpArray>>,
|
||||
index: Int<'ctx, SizeT>,
|
||||
) -> Ptr<'ctx, IntModel<Byte>> {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
CallFunction::begin(
|
||||
tyctx,
|
||||
ctx,
|
||||
&get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_get_nth_pelement"),
|
||||
)
|
||||
.arg("ndarray", pndarray)
|
||||
.arg("index", index)
|
||||
.returning("pelement")
|
||||
}
|
||||
|
|
@ -0,0 +1,74 @@
|
|||
use crate::codegen::{
|
||||
irrt::{
|
||||
error_context::{check_error_context, setup_error_context},
|
||||
util::{function::CallFunction, get_sizet_dependent_function_name},
|
||||
},
|
||||
model::*,
|
||||
structure::ndarray::NpArray,
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
pub fn call_nac3_ndarray_broadcast_to<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
src_ndarray: Ptr<'ctx, StructModel<NpArray>>,
|
||||
dst_ndarray: Ptr<'ctx, StructModel<NpArray>>,
|
||||
) {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
let perrctx = setup_error_context(tyctx, ctx);
|
||||
CallFunction::begin(
|
||||
tyctx,
|
||||
ctx,
|
||||
&get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_broadcast_to"),
|
||||
)
|
||||
.arg("errctx", perrctx)
|
||||
.arg("src_ndarray", src_ndarray)
|
||||
.arg("dst_ndarray", dst_ndarray)
|
||||
.returning_void();
|
||||
|
||||
check_error_context(generator, ctx, perrctx);
|
||||
}
|
||||
|
||||
/// Fields of [`ShapeEntry`]
|
||||
pub struct ShapeEntryFields<F: FieldVisitor> {
|
||||
pub ndims: F::Field<IntModel<SizeT>>,
|
||||
pub shape: F::Field<PtrModel<IntModel<SizeT>>>,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct ShapeEntry;
|
||||
|
||||
impl StructKind for ShapeEntry {
|
||||
type Fields<F: FieldVisitor> = ShapeEntryFields<F>;
|
||||
|
||||
fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields { ndims: visitor.add("ndims"), shape: visitor.add("shape") }
|
||||
}
|
||||
}
|
||||
|
||||
pub fn call_nac3_ndarray_broadcast_shapes<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
num_shape_entries: Int<'ctx, SizeT>,
|
||||
shape_entries: Ptr<'ctx, StructModel<ShapeEntry>>,
|
||||
dst_ndims: Int<'ctx, SizeT>,
|
||||
dst_shape: Ptr<'ctx, IntModel<SizeT>>,
|
||||
) {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
let perrctx = setup_error_context(tyctx, ctx);
|
||||
CallFunction::begin(
|
||||
tyctx,
|
||||
ctx,
|
||||
&get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_broadcast_shapes"),
|
||||
)
|
||||
.arg("errctx", perrctx)
|
||||
.arg("num_shapes", num_shape_entries)
|
||||
.arg("shapes", shape_entries)
|
||||
.arg("dst_ndims", dst_ndims)
|
||||
.arg("dst_shape", dst_shape)
|
||||
.returning_void();
|
||||
|
||||
check_error_context(generator, ctx, perrctx);
|
||||
}
|
||||
|
|
@ -0,0 +1,170 @@
|
|||
use crate::codegen::{
|
||||
irrt::{
|
||||
error_context::{check_error_context, setup_error_context},
|
||||
slice::{RustUserSlice, SliceIndex, UserSlice},
|
||||
util::{function::CallFunction, get_sizet_dependent_function_name},
|
||||
},
|
||||
model::*,
|
||||
structure::ndarray::NpArray,
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
pub type NDIndexType = Byte;
|
||||
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct NDIndexFields<F: FieldVisitor> {
|
||||
pub type_: F::Field<IntModel<NDIndexType>>, // Defined to be uint8_t in IRRT
|
||||
pub data: F::Field<PtrModel<IntModel<Byte>>>,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
|
||||
pub struct NDIndex;
|
||||
|
||||
impl StructKind for NDIndex {
|
||||
type Fields<F: FieldVisitor> = NDIndexFields<F>;
|
||||
|
||||
fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields { type_: visitor.add("type"), data: visitor.add("data") }
|
||||
}
|
||||
}
|
||||
|
||||
// An enum variant to store the content
|
||||
// and type of an NDIndex in high level.
|
||||
#[derive(Debug, Clone)]
|
||||
pub enum RustNDIndex<'ctx> {
|
||||
SingleElement(Int<'ctx, SliceIndex>),
|
||||
Slice(RustUserSlice<'ctx>),
|
||||
}
|
||||
|
||||
impl<'ctx> RustNDIndex<'ctx> {
|
||||
fn get_type_id(&self) -> u64 {
|
||||
// Defined in IRRT, must be in sync
|
||||
match self {
|
||||
RustNDIndex::SingleElement(_) => 0,
|
||||
RustNDIndex::Slice(_) => 1,
|
||||
}
|
||||
}
|
||||
|
||||
fn write_to_ndindex(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
dst_ndindex_ptr: Ptr<'ctx, StructModel<NDIndex>>,
|
||||
) {
|
||||
let ndindex_type_model = IntModel(NDIndexType::default());
|
||||
let slice_index_model = IntModel(SliceIndex::default());
|
||||
let user_slice_model = StructModel(UserSlice);
|
||||
|
||||
// Set `dst_ndindex_ptr->type`
|
||||
dst_ndindex_ptr
|
||||
.gep(ctx, |f| f.type_)
|
||||
.store(ctx, ndindex_type_model.constant(tyctx, ctx.ctx, self.get_type_id()));
|
||||
|
||||
// Set `dst_ndindex_ptr->data`
|
||||
let data = match self {
|
||||
RustNDIndex::SingleElement(in_index) => {
|
||||
let index_ptr = slice_index_model.alloca(tyctx, ctx, "index");
|
||||
index_ptr.store(ctx, *in_index);
|
||||
index_ptr.transmute(tyctx, ctx, IntModel(Byte), "")
|
||||
}
|
||||
RustNDIndex::Slice(in_rust_slice) => {
|
||||
let user_slice_ptr = user_slice_model.alloca(tyctx, ctx, "user_slice");
|
||||
in_rust_slice.write_to_user_slice(tyctx, ctx, user_slice_ptr);
|
||||
user_slice_ptr.transmute(tyctx, ctx, IntModel(Byte), "")
|
||||
}
|
||||
};
|
||||
dst_ndindex_ptr.gep(ctx, |f| f.data).store(ctx, data);
|
||||
}
|
||||
|
||||
/// Allocate an array of `NDIndex`es on the stack and return its stack pointer.
|
||||
pub fn alloca_ndindexes(
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
in_ndindexes: &[RustNDIndex<'ctx>],
|
||||
) -> (Int<'ctx, SizeT>, Ptr<'ctx, StructModel<NDIndex>>) {
|
||||
let sizet_model = IntModel(SizeT);
|
||||
let ndindex_model = StructModel(NDIndex);
|
||||
|
||||
let num_ndindexes = sizet_model.constant(tyctx, ctx.ctx, in_ndindexes.len() as u64);
|
||||
let ndindexes = ndindex_model.array_alloca(tyctx, ctx, num_ndindexes.value, "ndindexes");
|
||||
for (i, in_ndindex) in in_ndindexes.iter().enumerate() {
|
||||
let i = sizet_model.constant(tyctx, ctx.ctx, i as u64);
|
||||
let pndindex = ndindexes.offset(tyctx, ctx, i.value, "");
|
||||
in_ndindex.write_to_ndindex(tyctx, ctx, pndindex);
|
||||
}
|
||||
|
||||
(num_ndindexes, ndindexes)
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn deduce_ndims_after_indexing(indices: &[RustNDIndex], original_ndims: u64) -> u64 {
|
||||
let mut final_ndims = original_ndims;
|
||||
for index in indices {
|
||||
match index {
|
||||
RustNDIndex::SingleElement(_) => {
|
||||
final_ndims -= 1;
|
||||
}
|
||||
RustNDIndex::Slice(_) => {}
|
||||
}
|
||||
}
|
||||
final_ndims
|
||||
}
|
||||
}
|
||||
|
||||
pub fn call_nac3_ndarray_indexing_deduce_ndims_after_indexing<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndims: Int<'ctx, SizeT>,
|
||||
num_ndindexes: Int<'ctx, SizeT>,
|
||||
ndindexs: Ptr<'ctx, StructModel<NDIndex>>,
|
||||
) -> Int<'ctx, SizeT> {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let sizet_model = IntModel(SizeT);
|
||||
|
||||
let pfinal_ndims = sizet_model.alloca(tyctx, ctx, "pfinal_ndims");
|
||||
|
||||
let errctx_ptr = setup_error_context(tyctx, ctx);
|
||||
CallFunction::begin(
|
||||
tyctx,
|
||||
ctx,
|
||||
&get_sizet_dependent_function_name(
|
||||
tyctx,
|
||||
"__nac3_ndarray_indexing_deduce_ndims_after_indexing",
|
||||
),
|
||||
)
|
||||
.arg("errctx", errctx_ptr)
|
||||
.arg("result", pfinal_ndims)
|
||||
.arg("ndims", ndims)
|
||||
.arg("num_ndindexs", num_ndindexes)
|
||||
.arg("ndindexs", ndindexs)
|
||||
.returning_void();
|
||||
check_error_context(generator, ctx, errctx_ptr);
|
||||
|
||||
pfinal_ndims.load(tyctx, ctx, "final_ndims")
|
||||
}
|
||||
|
||||
pub fn call_nac3_ndarray_index<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
num_indexes: Int<'ctx, SizeT>,
|
||||
indexes: Ptr<'ctx, StructModel<NDIndex>>,
|
||||
src_ndarray: Ptr<'ctx, StructModel<NpArray>>,
|
||||
dst_ndarray: Ptr<'ctx, StructModel<NpArray>>,
|
||||
) {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
let perrctx = setup_error_context(tyctx, ctx);
|
||||
CallFunction::begin(
|
||||
tyctx,
|
||||
ctx,
|
||||
&get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_index"),
|
||||
)
|
||||
.arg("errctx", perrctx)
|
||||
.arg("num_indexes", num_indexes)
|
||||
.arg("indexes", indexes)
|
||||
.arg("src_ndarray", src_ndarray)
|
||||
.arg("dst_ndarray", dst_ndarray)
|
||||
.returning_void();
|
||||
|
||||
check_error_context(generator, ctx, perrctx);
|
||||
}
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
pub mod basic;
|
||||
pub mod broadcast;
|
||||
pub mod indexing;
|
||||
pub mod reshape;
|
||||
|
|
@ -0,0 +1,31 @@
|
|||
use crate::codegen::{
|
||||
irrt::{
|
||||
error_context::{check_error_context, setup_error_context},
|
||||
util::{function::CallFunction, get_sizet_dependent_function_name},
|
||||
},
|
||||
model::*,
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
pub fn call_nac3_ndarray_resolve_and_check_new_shape<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
size: Int<'ctx, SizeT>,
|
||||
new_ndims: Int<'ctx, SizeT>,
|
||||
new_shape: Ptr<'ctx, IntModel<SizeT>>,
|
||||
) {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
let perrctx = setup_error_context(tyctx, ctx);
|
||||
CallFunction::begin(
|
||||
tyctx,
|
||||
ctx,
|
||||
&get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_resolve_and_check_new_shape"),
|
||||
)
|
||||
.arg("errctx", perrctx)
|
||||
.arg("size", size)
|
||||
.arg("new_ndims", new_ndims)
|
||||
.arg("new_shape", new_shape)
|
||||
.returning_void();
|
||||
check_error_context(generator, ctx, perrctx);
|
||||
}
|
||||
|
|
@ -0,0 +1,81 @@
|
|||
use crate::codegen::{model::*, CodeGenContext};
|
||||
|
||||
// nac3core's slicing index/length values are always int32_t
|
||||
pub type SliceIndex = Int32;
|
||||
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct UserSliceFields<F: FieldVisitor> {
|
||||
pub start_defined: F::Field<IntModel<Bool>>,
|
||||
pub start: F::Field<IntModel<SliceIndex>>,
|
||||
pub stop_defined: F::Field<IntModel<Bool>>,
|
||||
pub stop: F::Field<IntModel<SliceIndex>>,
|
||||
pub step_defined: F::Field<IntModel<Bool>>,
|
||||
pub step: F::Field<IntModel<SliceIndex>>,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
|
||||
pub struct UserSlice;
|
||||
|
||||
impl StructKind for UserSlice {
|
||||
type Fields<F: FieldVisitor> = UserSliceFields<F>;
|
||||
|
||||
fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields {
|
||||
start_defined: visitor.add("start_defined"),
|
||||
start: visitor.add("start"),
|
||||
stop_defined: visitor.add("stop_defined"),
|
||||
stop: visitor.add("stop"),
|
||||
step_defined: visitor.add("step_defined"),
|
||||
step: visitor.add("step"),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct RustUserSlice<'ctx> {
|
||||
pub start: Option<Int<'ctx, SliceIndex>>,
|
||||
pub stop: Option<Int<'ctx, SliceIndex>>,
|
||||
pub step: Option<Int<'ctx, SliceIndex>>,
|
||||
}
|
||||
|
||||
impl<'ctx> RustUserSlice<'ctx> {
|
||||
// Set the values of an LLVM UserSlice
|
||||
// in the format of Python's `slice()`
|
||||
pub fn write_to_user_slice(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
dst_slice_ptr: Ptr<'ctx, StructModel<UserSlice>>,
|
||||
) {
|
||||
let bool_model = IntModel(Bool);
|
||||
|
||||
let false_ = bool_model.constant(tyctx, ctx.ctx, 0);
|
||||
let true_ = bool_model.constant(tyctx, ctx.ctx, 1);
|
||||
|
||||
// TODO: Code duplication. Probably okay...?
|
||||
|
||||
match self.start {
|
||||
Some(start) => {
|
||||
dst_slice_ptr.gep(ctx, |f| f.start_defined).store(ctx, true_);
|
||||
dst_slice_ptr.gep(ctx, |f| f.start).store(ctx, start);
|
||||
}
|
||||
None => dst_slice_ptr.gep(ctx, |f| f.start_defined).store(ctx, false_),
|
||||
}
|
||||
|
||||
match self.stop {
|
||||
Some(stop) => {
|
||||
dst_slice_ptr.gep(ctx, |f| f.stop_defined).store(ctx, true_);
|
||||
dst_slice_ptr.gep(ctx, |f| f.stop).store(ctx, stop);
|
||||
}
|
||||
None => dst_slice_ptr.gep(ctx, |f| f.stop_defined).store(ctx, false_),
|
||||
}
|
||||
|
||||
match self.step {
|
||||
Some(step) => {
|
||||
dst_slice_ptr.gep(ctx, |f| f.step_defined).store(ctx, true_);
|
||||
dst_slice_ptr.gep(ctx, |f| f.step).store(ctx, step);
|
||||
}
|
||||
None => dst_slice_ptr.gep(ctx, |f| f.step_defined).store(ctx, false_),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -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");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,103 @@
|
|||
use crate::codegen::model::*;
|
||||
|
||||
// When [`TypeContext::size_type`] is 32-bits, the function name is "{fn_name}".
|
||||
// When [`TypeContext::size_type`] is 64-bits, the function name is "{fn_name}64".
|
||||
#[must_use]
|
||||
pub fn get_sizet_dependent_function_name(tyctx: TypeContext<'_>, name: &str) -> String {
|
||||
let mut name = name.to_owned();
|
||||
match tyctx.size_type.get_bit_width() {
|
||||
32 => {}
|
||||
64 => name.push_str("64"),
|
||||
bit_width => {
|
||||
panic!("Unsupported int type bit width {bit_width}, must be either 32-bits or 64-bits")
|
||||
}
|
||||
}
|
||||
name
|
||||
}
|
||||
|
||||
pub mod function {
|
||||
use crate::codegen::{model::*, CodeGenContext};
|
||||
use inkwell::{
|
||||
types::{BasicMetadataTypeEnum, BasicType, FunctionType},
|
||||
values::{AnyValue, BasicMetadataValueEnum, BasicValue, BasicValueEnum, CallSiteValue},
|
||||
};
|
||||
use itertools::Itertools;
|
||||
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
struct Arg<'ctx> {
|
||||
ty: BasicMetadataTypeEnum<'ctx>,
|
||||
val: BasicMetadataValueEnum<'ctx>,
|
||||
}
|
||||
|
||||
/// Helper structure to reduce IRRT Inkwell function call boilerplate
|
||||
/// TODO: Optimize
|
||||
pub struct CallFunction<'ctx, 'a, 'b, 'c> {
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'b CodeGenContext<'ctx, 'a>,
|
||||
/// Function name
|
||||
name: &'c str,
|
||||
/// Call arguments
|
||||
args: Vec<Arg<'ctx>>,
|
||||
}
|
||||
|
||||
impl<'ctx, 'a, 'b, 'c> CallFunction<'ctx, 'a, 'b, 'c> {
|
||||
pub fn begin(
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'b CodeGenContext<'ctx, 'a>,
|
||||
name: &'c str,
|
||||
) -> Self {
|
||||
CallFunction { tyctx, ctx, name, args: Vec::new() }
|
||||
}
|
||||
|
||||
/// Push a call argument to the function call.
|
||||
///
|
||||
/// The `_name` parameter is there for self-documentation purposes.
|
||||
#[allow(clippy::needless_pass_by_value)]
|
||||
pub fn arg<M: Model>(mut self, _name: &str, arg: Instance<'ctx, M>) -> Self {
|
||||
let arg = Arg {
|
||||
ty: arg.model.get_type(self.tyctx, self.ctx.ctx).as_basic_type_enum().into(),
|
||||
val: arg.value.as_basic_value_enum().into(),
|
||||
};
|
||||
self.args.push(arg);
|
||||
self
|
||||
}
|
||||
|
||||
/// Like [`CallFunction::returning_`] but `return_model` is automatically inferred.
|
||||
pub fn returning<M: Model>(self, name: &str) -> Instance<'ctx, M> {
|
||||
self.returning_(name, M::default())
|
||||
}
|
||||
|
||||
/// Call the function and expect the function to return a value of type of `return_model`.
|
||||
pub fn returning_<M: Model>(self, name: &str, return_model: M) -> Instance<'ctx, M> {
|
||||
let ret_ty = return_model.get_type(self.tyctx, self.ctx.ctx);
|
||||
|
||||
let ret = self.get_function(|tys| ret_ty.fn_type(tys, false), name);
|
||||
let ret = BasicValueEnum::try_from(ret.as_any_value_enum()).unwrap(); // Must work
|
||||
let ret = return_model.check_value(self.tyctx, self.ctx.ctx, ret).unwrap(); // Must work
|
||||
ret
|
||||
}
|
||||
|
||||
/// Call the function and expect the function to return a void-type.
|
||||
pub fn returning_void(self) {
|
||||
let ret_ty = self.ctx.ctx.void_type();
|
||||
|
||||
let _ = self.get_function(|tys| ret_ty.fn_type(tys, false), "");
|
||||
}
|
||||
|
||||
fn get_function<F>(&self, make_fn_type: F, return_value_name: &str) -> CallSiteValue<'ctx>
|
||||
where
|
||||
F: FnOnce(&[BasicMetadataTypeEnum<'ctx>]) -> FunctionType<'ctx>,
|
||||
{
|
||||
// Get the LLVM function, declare the function if it doesn't exist - it will be defined by other
|
||||
// components of NAC3.
|
||||
let func = self.ctx.module.get_function(self.name).unwrap_or_else(|| {
|
||||
let tys = self.args.iter().map(|arg| arg.ty).collect_vec();
|
||||
let fn_type = make_fn_type(&tys);
|
||||
self.ctx.module.add_function(self.name, fn_type, None)
|
||||
});
|
||||
|
||||
let vals = self.args.iter().map(|arg| arg.val).collect_vec();
|
||||
self.ctx.builder.build_call(func, &vals, return_value_name).unwrap()
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -35,40 +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>(
|
||||
|
|
@ -183,7 +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()
|
||||
};
|
||||
|
|
@ -191,7 +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()
|
||||
};
|
||||
|
|
@ -205,9 +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 {
|
||||
|
|
@ -223,8 +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 {
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
use crate::{
|
||||
codegen::classes::{ListType, NDArrayType, ProxyType, RangeType},
|
||||
codegen::classes::{ListType, ProxyType, RangeType},
|
||||
symbol_resolver::{StaticValue, SymbolResolver},
|
||||
toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, TopLevelContext, TopLevelDef},
|
||||
toplevel::{helper::PrimDef, TopLevelContext, TopLevelDef},
|
||||
typecheck::{
|
||||
type_inferencer::{CodeLocation, PrimitiveStore},
|
||||
typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
|
||||
|
|
@ -24,6 +24,7 @@ use inkwell::{
|
|||
AddressSpace, IntPredicate, OptimizationLevel,
|
||||
};
|
||||
use itertools::Itertools;
|
||||
use model::*;
|
||||
use nac3parser::ast::{Location, Stmt, StrRef};
|
||||
use parking_lot::{Condvar, Mutex};
|
||||
use std::collections::{HashMap, HashSet};
|
||||
|
|
@ -32,6 +33,7 @@ use std::sync::{
|
|||
Arc,
|
||||
};
|
||||
use std::thread;
|
||||
use structure::{cslice::CSlice, exception::Exception, ndarray::NpArray};
|
||||
|
||||
pub mod builtin_fns;
|
||||
pub mod classes;
|
||||
|
|
@ -41,8 +43,12 @@ pub mod extern_fns;
|
|||
mod generator;
|
||||
pub mod irrt;
|
||||
pub mod llvm_intrinsics;
|
||||
pub mod model;
|
||||
pub mod numpy;
|
||||
pub mod numpy_new;
|
||||
pub mod stmt;
|
||||
pub mod structure;
|
||||
pub mod util;
|
||||
|
||||
#[cfg(test)]
|
||||
mod test;
|
||||
|
|
@ -50,22 +56,6 @@ mod test;
|
|||
use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
|
||||
pub use generator::{CodeGenerator, DefaultCodeGenerator};
|
||||
|
||||
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;
|
||||
}
|
||||
|
||||
#[derive(Default)]
|
||||
pub struct StaticValueStore {
|
||||
pub lookup: HashMap<Vec<(usize, u64)>, usize>,
|
||||
|
|
@ -184,11 +174,11 @@ pub struct CodeGenContext<'ctx, 'a> {
|
|||
pub registry: &'a WorkerRegistry,
|
||||
|
||||
/// Cache for constant strings.
|
||||
pub const_strings: HashMap<String, BasicValueEnum<'ctx>>,
|
||||
pub const_strings: HashMap<String, Struct<'ctx, CSlice>>,
|
||||
|
||||
/// [`BasicBlock`] containing all `alloca` statements for the current function.
|
||||
pub init_bb: BasicBlock<'ctx>,
|
||||
pub exception_val: Option<PointerValue<'ctx>>,
|
||||
pub exception_val: Option<Ptr<'ctx, StructModel<Exception>>>,
|
||||
|
||||
/// The header and exit basic blocks of a loop in this context. See
|
||||
/// <https://llvm.org/docs/LoopTerminology.html> for explanation of these terminology.
|
||||
|
|
@ -460,7 +450,7 @@ 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>>,
|
||||
|
|
@ -505,12 +495,9 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
|
|||
}
|
||||
|
||||
TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
|
||||
let (dtype, _) = unpack_ndarray_var_tys(unifier, ty);
|
||||
let element_type = get_llvm_type(
|
||||
ctx, module, generator, unifier, top_level, type_cache, dtype,
|
||||
);
|
||||
|
||||
NDArrayType::new(generator, ctx, element_type).as_base_type().into()
|
||||
let tyctx = generator.type_context(ctx);
|
||||
let pndarray_model = PtrModel(StructModel(NpArray));
|
||||
pndarray_model.get_type(tyctx, ctx).into()
|
||||
}
|
||||
|
||||
_ => unreachable!(
|
||||
|
|
@ -554,10 +541,8 @@ 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| {
|
||||
|
|
@ -587,7 +572,7 @@ 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>>,
|
||||
|
|
@ -596,11 +581,11 @@ 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`.
|
||||
|
|
@ -625,40 +610,6 @@ 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,
|
||||
|
|
@ -716,43 +667,20 @@ pub fn gen_func_impl<
|
|||
..primitives
|
||||
};
|
||||
|
||||
let mut type_cache: HashMap<_, _> = [
|
||||
let type_context = generator.type_context(context);
|
||||
let cslice_model = StructModel(CSlice);
|
||||
let pexn_model = PtrModel(StructModel(Exception));
|
||||
|
||||
let mut type_cache: HashMap<_, BasicTypeEnum<'ctx>> = [
|
||||
(primitives.int32, context.i32_type().into()),
|
||||
(primitives.int64, context.i64_type().into()),
|
||||
(primitives.uint32, context.i32_type().into()),
|
||||
(primitives.uint64, context.i64_type().into()),
|
||||
(primitives.float, context.f64_type().into()),
|
||||
(primitives.bool, context.i8_type().into()),
|
||||
(primitives.str, {
|
||||
let name = "str";
|
||||
match module.get_struct_type(name) {
|
||||
None => {
|
||||
let str_type = context.opaque_struct_type("str");
|
||||
let fields = [
|
||||
context.i8_type().ptr_type(AddressSpace::default()).into(),
|
||||
generator.get_size_type(context).into(),
|
||||
];
|
||||
str_type.set_body(&fields, false);
|
||||
str_type.into()
|
||||
}
|
||||
Some(t) => t.as_basic_type_enum(),
|
||||
}
|
||||
}),
|
||||
(primitives.str, cslice_model.get_type(type_context, context).into()),
|
||||
(primitives.range, RangeType::new(context).as_base_type().into()),
|
||||
(primitives.exception, {
|
||||
let name = "Exception";
|
||||
if let Some(t) = module.get_struct_type(name) {
|
||||
t.ptr_type(AddressSpace::default()).as_basic_type_enum()
|
||||
} else {
|
||||
let exception = context.opaque_struct_type("Exception");
|
||||
let int32 = context.i32_type().into();
|
||||
let int64 = context.i64_type().into();
|
||||
let str_ty = module.get_struct_type("str").unwrap().as_basic_type_enum();
|
||||
let fields = [int32, str_ty, int32, int32, str_ty, str_ty, int64, int64, int64];
|
||||
exception.set_body(&fields, false);
|
||||
exception.ptr_type(AddressSpace::default()).as_basic_type_enum()
|
||||
}
|
||||
}),
|
||||
(primitives.exception, pexn_model.get_type(type_context, context).into()),
|
||||
]
|
||||
.iter()
|
||||
.copied()
|
||||
|
|
@ -770,7 +698,6 @@ 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),
|
||||
|
|
@ -793,10 +720,7 @@ 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,
|
||||
|
|
@ -815,12 +739,9 @@ 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(¶ms, vararg_arg.is_some()),
|
||||
_ => context.void_type().fn_type(¶ms, vararg_arg.is_some()),
|
||||
Some(ret_type) if !has_sret => ret_type.fn_type(¶ms, false),
|
||||
_ => context.void_type().fn_type(¶ms, false),
|
||||
};
|
||||
|
||||
let symbol = &task.symbol_name;
|
||||
|
|
@ -850,9 +771,7 @@ pub fn gen_func_impl<
|
|||
|
||||
let mut var_assignment = HashMap::new();
|
||||
let offset = u32::from(has_sret);
|
||||
|
||||
// Store non-vararg argument values into local variables
|
||||
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,
|
||||
|
|
@ -885,8 +804,6 @@ 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 {
|
||||
|
|
@ -1109,9 +1026,3 @@ 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()
|
||||
}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,161 @@
|
|||
use std::fmt;
|
||||
|
||||
use inkwell::{context::Context, types::*, values::*};
|
||||
|
||||
use super::*;
|
||||
use crate::codegen::{CodeGenContext, CodeGenerator};
|
||||
|
||||
#[derive(Clone, Copy)]
|
||||
pub struct TypeContext<'ctx> {
|
||||
pub size_type: IntType<'ctx>,
|
||||
}
|
||||
|
||||
pub trait HasTypeContext {
|
||||
fn type_context<'ctx>(&self, ctx: &'ctx Context) -> TypeContext<'ctx>;
|
||||
}
|
||||
|
||||
impl<T: CodeGenerator + ?Sized> HasTypeContext for T {
|
||||
fn type_context<'ctx>(&self, ctx: &'ctx Context) -> TypeContext<'ctx> {
|
||||
TypeContext { size_type: self.get_size_type(ctx) }
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct ModelError(pub String);
|
||||
|
||||
impl ModelError {
|
||||
pub(super) fn under_context(mut self, context: &str) -> Self {
|
||||
self.0.push_str(" ... in ");
|
||||
self.0.push_str(context);
|
||||
self
|
||||
}
|
||||
}
|
||||
|
||||
/// A [`Model`] is a singleton object that uniquely identifies a [`BasicType`]
|
||||
/// solely from a [`CodeGenerator`] and a [`Context`].
|
||||
pub trait Model: CheckType + fmt::Debug + Clone + Copy + Default {
|
||||
type Value<'ctx>: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>>;
|
||||
type Type<'ctx>: BasicType<'ctx>;
|
||||
|
||||
/// Return the [`BasicType`] of this model.
|
||||
fn get_type<'ctx>(&self, tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> Self::Type<'ctx>;
|
||||
|
||||
/// Check if a [`BasicType`] is the same type of this model.
|
||||
fn check_type<'ctx, T: BasicType<'ctx>>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'ctx Context,
|
||||
ty: T,
|
||||
) -> Result<(), ModelError> {
|
||||
let ty = ty.as_basic_type_enum();
|
||||
self.check_type_impl(tyctx, ctx, ty.as_basic_type_enum())
|
||||
}
|
||||
|
||||
/// Create an instance from a value with [`Instance::model`] being this model.
|
||||
///
|
||||
/// Caller must make sure the type of `value` and the type of this `model` are equivalent.
|
||||
fn believe_value<'ctx>(&self, value: Self::Value<'ctx>) -> Instance<'ctx, Self> {
|
||||
Instance { model: *self, value }
|
||||
}
|
||||
|
||||
/// Check if a [`BasicValue`]'s type is equivalent to the type of this model.
|
||||
/// Wrap it into an [`Instance`] if it is.
|
||||
fn check_value<'ctx, V: BasicValue<'ctx>>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'ctx Context,
|
||||
value: V,
|
||||
) -> Result<Instance<'ctx, Self>, ModelError> {
|
||||
let value = value.as_basic_value_enum();
|
||||
self.check_type(tyctx, ctx, value.get_type())
|
||||
.map_err(|err| err.under_context("the value {value:?}"))?;
|
||||
|
||||
let Ok(value) = Self::Value::try_from(value) else {
|
||||
unreachable!("check_type() has bad implementation")
|
||||
};
|
||||
Ok(self.believe_value(value))
|
||||
}
|
||||
|
||||
// Allocate a value on the stack and return its pointer.
|
||||
fn alloca<'ctx>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
name: &str,
|
||||
) -> Ptr<'ctx, Self> {
|
||||
let pmodel = PtrModel(*self);
|
||||
let p = ctx.builder.build_alloca(self.get_type(tyctx, ctx.ctx), name).unwrap();
|
||||
pmodel.believe_value(p)
|
||||
}
|
||||
|
||||
// Allocate an array on the stack and return its pointer.
|
||||
fn array_alloca<'ctx>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
len: IntValue<'ctx>,
|
||||
name: &str,
|
||||
) -> Ptr<'ctx, Self> {
|
||||
let pmodel = PtrModel(*self);
|
||||
let p = ctx.builder.build_array_alloca(self.get_type(tyctx, ctx.ctx), len, name).unwrap();
|
||||
pmodel.believe_value(p)
|
||||
}
|
||||
|
||||
fn var_alloca<'ctx, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
name: Option<&str>,
|
||||
) -> Result<Ptr<'ctx, Self>, String> {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
let pmodel = PtrModel(*self);
|
||||
let p = generator.gen_var_alloc(
|
||||
ctx,
|
||||
self.get_type(tyctx, ctx.ctx).as_basic_type_enum(),
|
||||
name,
|
||||
)?;
|
||||
Ok(pmodel.believe_value(p))
|
||||
}
|
||||
|
||||
fn array_var_alloca<'ctx, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
len: IntValue<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> Result<Ptr<'ctx, Self>, String> {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
// TODO: Remove ArraySliceValue
|
||||
let pmodel = PtrModel(*self);
|
||||
let p = generator.gen_array_var_alloc(
|
||||
ctx,
|
||||
self.get_type(tyctx, ctx.ctx).as_basic_type_enum(),
|
||||
len,
|
||||
name,
|
||||
)?;
|
||||
Ok(pmodel.believe_value(PointerValue::from(p)))
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct Instance<'ctx, M: Model> {
|
||||
/// The model of this instance.
|
||||
pub model: M,
|
||||
/// The value of this instance.
|
||||
///
|
||||
/// Caller must make sure the type of `value` and the type of this `model` are equivalent,
|
||||
/// down to having the same [`IntType::get_bit_width`] in case of [`IntType`] for example.
|
||||
pub value: M::Value<'ctx>,
|
||||
}
|
||||
|
||||
// NOTE: Must be Rust object-safe - This must be typeable for a Rust trait object.
|
||||
pub trait CheckType {
|
||||
fn check_type_impl<'ctx>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'ctx Context,
|
||||
ty: BasicTypeEnum<'ctx>,
|
||||
) -> Result<(), ModelError>;
|
||||
}
|
||||
|
|
@ -0,0 +1,228 @@
|
|||
use std::fmt;
|
||||
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
types::{BasicTypeEnum, IntType},
|
||||
values::IntValue,
|
||||
IntPredicate,
|
||||
};
|
||||
|
||||
use crate::codegen::{CodeGenContext, CodeGenerator};
|
||||
|
||||
use super::*;
|
||||
|
||||
pub trait IntKind: fmt::Debug + Clone + Copy + Default {
|
||||
fn get_int_type<'ctx>(&self, tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> IntType<'ctx>;
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Bool;
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Byte;
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Int32;
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Int64;
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct SizeT;
|
||||
|
||||
impl IntKind for Bool {
|
||||
fn get_int_type<'ctx>(&self, _tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> IntType<'ctx> {
|
||||
ctx.bool_type()
|
||||
}
|
||||
}
|
||||
|
||||
impl IntKind for Byte {
|
||||
fn get_int_type<'ctx>(&self, _tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> IntType<'ctx> {
|
||||
ctx.i8_type()
|
||||
}
|
||||
}
|
||||
|
||||
impl IntKind for Int32 {
|
||||
fn get_int_type<'ctx>(&self, _tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> IntType<'ctx> {
|
||||
ctx.i32_type()
|
||||
}
|
||||
}
|
||||
|
||||
impl IntKind for Int64 {
|
||||
fn get_int_type<'ctx>(&self, _tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> IntType<'ctx> {
|
||||
ctx.i64_type()
|
||||
}
|
||||
}
|
||||
|
||||
impl IntKind for SizeT {
|
||||
fn get_int_type<'ctx>(&self, tyctx: TypeContext<'ctx>, _ctx: &'ctx Context) -> IntType<'ctx> {
|
||||
tyctx.size_type
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct IntModel<N: IntKind>(pub N);
|
||||
pub type Int<'ctx, N> = Instance<'ctx, IntModel<N>>;
|
||||
|
||||
impl<N: IntKind> CheckType for IntModel<N> {
|
||||
fn check_type_impl<'ctx>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'ctx Context,
|
||||
ty: BasicTypeEnum<'ctx>,
|
||||
) -> Result<(), ModelError> {
|
||||
let Ok(ty) = IntType::try_from(ty) else {
|
||||
return Err(ModelError(format!("Expecting IntType, but got {ty:?}")));
|
||||
};
|
||||
|
||||
let exp_ty = self.0.get_int_type(tyctx, ctx);
|
||||
if ty.get_bit_width() != exp_ty.get_bit_width() {
|
||||
return Err(ModelError(format!(
|
||||
"Expecting IntType to have {} bit(s), but got {} bit(s)",
|
||||
exp_ty.get_bit_width(),
|
||||
ty.get_bit_width()
|
||||
)));
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
impl<N: IntKind> Model for IntModel<N> {
|
||||
type Value<'ctx> = IntValue<'ctx>;
|
||||
type Type<'ctx> = IntType<'ctx>;
|
||||
|
||||
#[must_use]
|
||||
fn get_type<'ctx>(&self, tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> Self::Type<'ctx> {
|
||||
self.0.get_int_type(tyctx, ctx)
|
||||
}
|
||||
}
|
||||
|
||||
impl<N: IntKind> IntModel<N> {
|
||||
pub fn constant<'ctx>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'ctx Context,
|
||||
value: u64,
|
||||
) -> Int<'ctx, N> {
|
||||
let value = self.get_type(tyctx, ctx).const_int(value, false);
|
||||
self.believe_value(value)
|
||||
}
|
||||
|
||||
pub fn const_0<'ctx>(&self, tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> Int<'ctx, N> {
|
||||
self.constant(tyctx, ctx, 0)
|
||||
}
|
||||
|
||||
pub fn const_1<'ctx>(&self, tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> Int<'ctx, N> {
|
||||
self.constant(tyctx, ctx, 1)
|
||||
}
|
||||
|
||||
pub fn s_extend_or_bit_cast<'ctx>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
value: IntValue<'ctx>,
|
||||
name: &str,
|
||||
) -> Int<'ctx, N> {
|
||||
let value = ctx
|
||||
.builder
|
||||
.build_int_s_extend_or_bit_cast(value, self.get_type(tyctx, ctx.ctx), name)
|
||||
.unwrap();
|
||||
self.believe_value(value)
|
||||
}
|
||||
|
||||
pub fn truncate<'ctx>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
value: IntValue<'ctx>,
|
||||
name: &str,
|
||||
) -> Int<'ctx, N> {
|
||||
let value =
|
||||
ctx.builder.build_int_truncate(value, self.get_type(tyctx, ctx.ctx), name).unwrap();
|
||||
self.believe_value(value)
|
||||
}
|
||||
}
|
||||
|
||||
impl IntModel<Bool> {
|
||||
#[must_use]
|
||||
pub fn const_false<'ctx>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'ctx Context,
|
||||
) -> Int<'ctx, Bool> {
|
||||
self.constant(tyctx, ctx, 0)
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn const_true<'ctx>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'ctx Context,
|
||||
) -> Int<'ctx, Bool> {
|
||||
self.constant(tyctx, ctx, 1)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, N: IntKind> Int<'ctx, N> {
|
||||
pub fn s_extend_or_bit_cast<NewN: IntKind, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
to_int_kind: NewN,
|
||||
name: &str,
|
||||
) -> Int<'ctx, NewN> {
|
||||
IntModel(to_int_kind).s_extend_or_bit_cast(tyctx, ctx, self.value, name)
|
||||
}
|
||||
|
||||
pub fn truncate<NewN: IntKind, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
to_int_kind: NewN,
|
||||
name: &str,
|
||||
) -> Int<'ctx, NewN> {
|
||||
IntModel(to_int_kind).truncate(tyctx, ctx, self.value, name)
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn add<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
other: Int<'ctx, N>,
|
||||
name: &str,
|
||||
) -> Int<'ctx, N> {
|
||||
let value = ctx.builder.build_int_add(self.value, other.value, name).unwrap();
|
||||
self.model.believe_value(value)
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn sub<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
other: Int<'ctx, N>,
|
||||
name: &str,
|
||||
) -> Int<'ctx, N> {
|
||||
let value = ctx.builder.build_int_sub(self.value, other.value, name).unwrap();
|
||||
self.model.believe_value(value)
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn mul<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
other: Int<'ctx, N>,
|
||||
name: &str,
|
||||
) -> Int<'ctx, N> {
|
||||
let value = ctx.builder.build_int_mul(self.value, other.value, name).unwrap();
|
||||
self.model.believe_value(value)
|
||||
}
|
||||
|
||||
pub fn compare<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
op: IntPredicate,
|
||||
other: Int<'ctx, N>,
|
||||
name: &str,
|
||||
) -> Int<'ctx, Bool> {
|
||||
let bool_model = IntModel(Bool);
|
||||
let value = ctx.builder.build_int_compare(op, self.value, other.value, name).unwrap();
|
||||
bool_model.believe_value(value)
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,12 @@
|
|||
mod core;
|
||||
mod int;
|
||||
mod ptr;
|
||||
mod slice;
|
||||
mod structure;
|
||||
pub mod util;
|
||||
|
||||
pub use core::*;
|
||||
pub use int::*;
|
||||
pub use ptr::*;
|
||||
pub use slice::*;
|
||||
pub use structure::*;
|
||||
|
|
@ -0,0 +1,142 @@
|
|||
use inkwell::{
|
||||
context::Context,
|
||||
types::{BasicType, BasicTypeEnum, PointerType},
|
||||
values::{IntValue, PointerValue},
|
||||
AddressSpace,
|
||||
};
|
||||
|
||||
use crate::codegen::CodeGenContext;
|
||||
|
||||
use super::*;
|
||||
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct PtrModel<Element>(pub Element);
|
||||
pub type Ptr<'ctx, Element> = Instance<'ctx, PtrModel<Element>>;
|
||||
|
||||
impl<Element: CheckType> CheckType for PtrModel<Element> {
|
||||
fn check_type_impl<'ctx>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'ctx Context,
|
||||
ty: BasicTypeEnum<'ctx>,
|
||||
) -> Result<(), super::ModelError> {
|
||||
let Ok(ty) = PointerType::try_from(ty) else {
|
||||
return Err(ModelError(format!("Expecting PointerType, but got {ty:?}")));
|
||||
};
|
||||
|
||||
let elem_ty = ty.get_element_type();
|
||||
let Ok(elem_ty) = BasicTypeEnum::try_from(elem_ty) else {
|
||||
return Err(ModelError(format!(
|
||||
"Expecting pointer element type to be a BasicTypeEnum, but got {elem_ty:?}"
|
||||
)));
|
||||
};
|
||||
|
||||
// TODO: inkwell `get_element_type()` will be deprecated.
|
||||
// Remove the check for `get_element_type()` when the time comes.
|
||||
self.0
|
||||
.check_type_impl(tyctx, ctx, elem_ty)
|
||||
.map_err(|err| err.under_context("a PointerType"))?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
impl<Element: Model> Model for PtrModel<Element> {
|
||||
type Value<'ctx> = PointerValue<'ctx>;
|
||||
type Type<'ctx> = PointerType<'ctx>;
|
||||
|
||||
fn get_type<'ctx>(&self, tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> Self::Type<'ctx> {
|
||||
self.0.get_type(tyctx, ctx).ptr_type(AddressSpace::default())
|
||||
}
|
||||
}
|
||||
|
||||
impl<Element: Model> PtrModel<Element> {
|
||||
/// Return a ***constant*** nullptr.
|
||||
pub fn nullptr<'ctx>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'ctx Context,
|
||||
) -> Ptr<'ctx, Element> {
|
||||
let ptr = self.get_type(tyctx, ctx).const_null();
|
||||
self.believe_value(ptr)
|
||||
}
|
||||
|
||||
pub fn transmute<'ctx>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
ptr: PointerValue<'ctx>,
|
||||
name: &str,
|
||||
) -> Ptr<'ctx, Element> {
|
||||
let ptr = ctx.builder.build_pointer_cast(ptr, self.get_type(tyctx, ctx.ctx), name).unwrap();
|
||||
self.believe_value(ptr)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, Element: Model> Ptr<'ctx, Element> {
|
||||
/// Offset the pointer by [`inkwell::builder::Builder::build_in_bounds_gep`].
|
||||
#[must_use]
|
||||
pub fn offset(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
offset: IntValue<'ctx>,
|
||||
name: &str,
|
||||
) -> Ptr<'ctx, Element> {
|
||||
let new_ptr =
|
||||
unsafe { ctx.builder.build_in_bounds_gep(self.value, &[offset], name).unwrap() };
|
||||
self.model.check_value(tyctx, ctx.ctx, new_ptr).unwrap()
|
||||
}
|
||||
|
||||
// Load the `i`-th element (0-based) on the array with [`inkwell::builder::Builder::build_in_bounds_gep`].
|
||||
pub fn ix(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
i: IntValue<'ctx>,
|
||||
name: &str,
|
||||
) -> Instance<'ctx, Element> {
|
||||
self.offset(tyctx, ctx, i, name).load(tyctx, ctx, name)
|
||||
}
|
||||
|
||||
/// Load the value with [`inkwell::builder::Builder::build_load`].
|
||||
pub fn load(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
name: &str,
|
||||
) -> Instance<'ctx, Element> {
|
||||
let value = ctx.builder.build_load(self.value, name).unwrap();
|
||||
self.model.0.check_value(tyctx, ctx.ctx, value).unwrap() // If unwrap() panics, there is a logic error.
|
||||
}
|
||||
|
||||
/// Store a value with [`inkwell::builder::Builder::build_store`].
|
||||
pub fn store(&self, ctx: &CodeGenContext<'ctx, '_>, value: Instance<'ctx, Element>) {
|
||||
ctx.builder.build_store(self.value, value.value).unwrap();
|
||||
}
|
||||
|
||||
/// Return a casted pointer of element type `NewElement` with [`inkwell::builder::Builder::build_pointer_cast`].
|
||||
pub fn transmute<NewElement: Model>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
new_model: NewElement,
|
||||
name: &str,
|
||||
) -> Ptr<'ctx, NewElement> {
|
||||
PtrModel(new_model).transmute(tyctx, ctx, self.value, name)
|
||||
}
|
||||
|
||||
/// Check if the pointer is null with [`inkwell::builder::Builder::build_is_null`].
|
||||
pub fn is_null(&self, ctx: &CodeGenContext<'ctx, '_>, name: &str) -> Int<'ctx, Bool> {
|
||||
let bool_model = IntModel(Bool);
|
||||
let value = ctx.builder.build_is_null(self.value, name).unwrap();
|
||||
bool_model.believe_value(value)
|
||||
}
|
||||
|
||||
/// Check if the pointer is not null with [`inkwell::builder::Builder::build_is_not_null`].
|
||||
pub fn is_not_null(&self, ctx: &CodeGenContext<'ctx, '_>, name: &str) -> Int<'ctx, Bool> {
|
||||
let bool_model = IntModel(Bool);
|
||||
let value = ctx.builder.build_is_not_null(self.value, name).unwrap();
|
||||
bool_model.believe_value(value)
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,72 @@
|
|||
use crate::codegen::{CodeGenContext, CodeGenerator};
|
||||
|
||||
use super::*;
|
||||
|
||||
/// A slice - literally just a pointer and a length value.
|
||||
///
|
||||
/// NOTE: This is NOT a [`Model`].
|
||||
pub struct ArraySlice<'ctx, Len: IntKind, Item: Model> {
|
||||
pub base: Ptr<'ctx, Item>,
|
||||
pub len: Int<'ctx, Len>,
|
||||
}
|
||||
|
||||
impl<'ctx, Len: IntKind, Item: Model> ArraySlice<'ctx, Len, Item> {
|
||||
/// Get the `idx`-nth element of this [`ArraySlice`], but doesn't do an assertion to see if `idx` is out of bounds or not.
|
||||
///
|
||||
/// Also see [`ArraySlice::ix`].
|
||||
pub fn ix_unchecked(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
idx: Int<'ctx, Len>,
|
||||
name: &str,
|
||||
) -> Ptr<'ctx, Item> {
|
||||
let element_ptr = unsafe {
|
||||
ctx.builder.build_in_bounds_gep(self.base.value, &[idx.value], name).unwrap()
|
||||
};
|
||||
self.base.model.check_value(tyctx, ctx.ctx, element_ptr).unwrap()
|
||||
}
|
||||
|
||||
/// Call [`ArraySlice::ix_unchecked`], but checks if `idx` is in bounds, otherwise a runtime `IndexError` will be thrown.
|
||||
pub fn ix<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
idx: Int<'ctx, Len>,
|
||||
name: &str,
|
||||
) -> Ptr<'ctx, Item> {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let len_model = IntModel(Len::default());
|
||||
|
||||
// Assert `0 <= idx < length` and throw an Exception if `idx` is out of bounds
|
||||
let lower_bounded = ctx
|
||||
.builder
|
||||
.build_int_compare(
|
||||
inkwell::IntPredicate::SLE,
|
||||
len_model.constant(tyctx, ctx.ctx, 0).value,
|
||||
idx.value,
|
||||
"lower_bounded",
|
||||
)
|
||||
.unwrap();
|
||||
let upper_bounded = ctx
|
||||
.builder
|
||||
.build_int_compare(
|
||||
inkwell::IntPredicate::SLT,
|
||||
idx.value,
|
||||
self.len.value,
|
||||
"upper_bounded",
|
||||
)
|
||||
.unwrap();
|
||||
let bounded = ctx.builder.build_and(lower_bounded, upper_bounded, "bounded").unwrap();
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
bounded,
|
||||
"0:IndexError",
|
||||
"nac3core LLVM codegen attempting to access out of bounds array index {0}. Must satisfy 0 <= index < {2}",
|
||||
[ Some(idx.value), Some(self.len.value), None],
|
||||
ctx.current_loc
|
||||
);
|
||||
|
||||
self.ix_unchecked(tyctx, ctx, idx, name)
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,174 @@
|
|||
use std::fmt;
|
||||
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
types::{BasicType, BasicTypeEnum, StructType},
|
||||
values::StructValue,
|
||||
};
|
||||
use itertools::izip;
|
||||
|
||||
use crate::codegen::CodeGenContext;
|
||||
|
||||
use super::*;
|
||||
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct GepField<M: Model> {
|
||||
pub gep_index: u64,
|
||||
pub name: &'static str,
|
||||
pub model: M,
|
||||
}
|
||||
|
||||
pub trait FieldVisitor {
|
||||
type Field<M: Model + 'static>;
|
||||
|
||||
fn add<M: Model + 'static>(&mut self, name: &'static str) -> Self::Field<M>;
|
||||
}
|
||||
|
||||
pub struct GepFieldVisitor {
|
||||
gep_index_counter: u64,
|
||||
}
|
||||
|
||||
impl FieldVisitor for GepFieldVisitor {
|
||||
type Field<M: Model + 'static> = GepField<M>;
|
||||
|
||||
fn add<M: Model + 'static>(&mut self, name: &'static str) -> Self::Field<M> {
|
||||
let gep_index = self.gep_index_counter;
|
||||
self.gep_index_counter += 1;
|
||||
Self::Field { gep_index, name, model: M::default() }
|
||||
}
|
||||
}
|
||||
|
||||
struct TypeFieldVisitor<'ctx> {
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'ctx Context,
|
||||
field_types: Vec<BasicTypeEnum<'ctx>>,
|
||||
}
|
||||
|
||||
impl<'ctx> FieldVisitor for TypeFieldVisitor<'ctx> {
|
||||
type Field<M: Model + 'static> = ();
|
||||
|
||||
fn add<M: Model + 'static>(&mut self, _name: &'static str) -> Self::Field<M> {
|
||||
self.field_types.push(M::default().get_type(self.tyctx, self.ctx).as_basic_type_enum());
|
||||
}
|
||||
}
|
||||
|
||||
struct CheckTypeEntry {
|
||||
check_type: Box<dyn CheckType + 'static>,
|
||||
name: &'static str,
|
||||
}
|
||||
|
||||
struct CheckTypeFieldVisitor<'ctx> {
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'ctx Context,
|
||||
check_types: Vec<CheckTypeEntry>,
|
||||
}
|
||||
|
||||
impl<'ctx> FieldVisitor for CheckTypeFieldVisitor<'ctx> {
|
||||
type Field<M: Model + 'static> = ();
|
||||
|
||||
fn add<M: Model + 'static>(&mut self, name: &'static str) -> Self::Field<M> {
|
||||
self.check_types.push(CheckTypeEntry { check_type: Box::<M>::default(), name });
|
||||
}
|
||||
}
|
||||
|
||||
pub trait StructKind: fmt::Debug + Clone + Copy + Default {
|
||||
type Fields<F: FieldVisitor>;
|
||||
|
||||
fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F>;
|
||||
|
||||
fn fields(&self) -> Self::Fields<GepFieldVisitor> {
|
||||
self.visit_fields(&mut GepFieldVisitor { gep_index_counter: 0 })
|
||||
}
|
||||
|
||||
fn get_struct_type<'ctx>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'ctx Context,
|
||||
) -> StructType<'ctx> {
|
||||
let mut visitor = TypeFieldVisitor { tyctx, ctx, field_types: Vec::new() };
|
||||
self.visit_fields(&mut visitor);
|
||||
|
||||
ctx.struct_type(&visitor.field_types, false)
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct StructModel<S: StructKind>(pub S);
|
||||
pub type Struct<'ctx, S> = Instance<'ctx, StructModel<S>>;
|
||||
|
||||
impl<S: StructKind> CheckType for StructModel<S> {
|
||||
fn check_type_impl<'ctx>(
|
||||
&self,
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &'ctx Context,
|
||||
ty: BasicTypeEnum<'ctx>,
|
||||
) -> Result<(), ModelError> {
|
||||
let ty = ty.as_basic_type_enum();
|
||||
let Ok(ty) = StructType::try_from(ty) else {
|
||||
return Err(ModelError(format!("Expecting StructType, but got {ty:?}")));
|
||||
};
|
||||
|
||||
let field_types = ty.get_field_types();
|
||||
|
||||
let check_types = {
|
||||
let mut builder = CheckTypeFieldVisitor { tyctx, ctx, check_types: Vec::new() };
|
||||
self.0.visit_fields(&mut builder);
|
||||
builder.check_types
|
||||
};
|
||||
|
||||
if check_types.len() != field_types.len() {
|
||||
return Err(ModelError(format!(
|
||||
"Expecting StructType to have {} field(s), but got {} field(s)",
|
||||
check_types.len(),
|
||||
field_types.len()
|
||||
)));
|
||||
}
|
||||
|
||||
for (field_i, (entry, field_type)) in izip!(check_types, field_types).enumerate() {
|
||||
let field_at = field_i + 1;
|
||||
|
||||
entry.check_type.check_type_impl(tyctx, ctx, field_type).map_err(|err| {
|
||||
err.under_context(format!("struct field #{field_at} '{}'", entry.name).as_str())
|
||||
})?;
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
impl<S: StructKind> Model for StructModel<S> {
|
||||
type Value<'ctx> = StructValue<'ctx>;
|
||||
type Type<'ctx> = StructType<'ctx>;
|
||||
|
||||
fn get_type<'ctx>(&self, tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> Self::Type<'ctx> {
|
||||
self.0.get_struct_type(tyctx, ctx)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, S: StructKind> Ptr<'ctx, StructModel<S>> {
|
||||
pub fn gep<M, GetField>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
get_field: GetField,
|
||||
) -> Ptr<'ctx, M>
|
||||
where
|
||||
M: Model,
|
||||
GetField: FnOnce(S::Fields<GepFieldVisitor>) -> GepField<M>,
|
||||
{
|
||||
let field = get_field(self.model.0 .0.fields());
|
||||
let llvm_i32 = ctx.ctx.i32_type(); // must be i32, if its i64 then rust segfaults
|
||||
|
||||
let ptr = unsafe {
|
||||
ctx.builder
|
||||
.build_in_bounds_gep(
|
||||
self.value,
|
||||
&[llvm_i32.const_zero(), llvm_i32.const_int(field.gep_index, false)],
|
||||
field.name,
|
||||
)
|
||||
.unwrap()
|
||||
};
|
||||
|
||||
let ptr_model = PtrModel(field.model);
|
||||
ptr_model.believe_value(ptr)
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,23 @@
|
|||
use inkwell::{types::BasicType, values::IntValue};
|
||||
|
||||
use crate::codegen::{llvm_intrinsics::call_memcpy_generic, CodeGenContext};
|
||||
|
||||
use super::*;
|
||||
|
||||
pub fn gen_model_memcpy<'ctx, M: Model>(
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
dst: Ptr<'ctx, M>,
|
||||
src: Ptr<'ctx, M>,
|
||||
num_elements: IntValue<'ctx>,
|
||||
volatile: bool,
|
||||
) {
|
||||
let bool_model = IntModel(Bool);
|
||||
|
||||
let itemsize = M::default().get_type(tyctx, ctx.ctx).size_of().unwrap();
|
||||
let totalsize =
|
||||
ctx.builder.build_int_mul(itemsize, num_elements, "model_memcpy_totalsize").unwrap();
|
||||
let is_volatile = bool_model.constant(tyctx, ctx.ctx, u64::from(volatile));
|
||||
|
||||
call_memcpy_generic(ctx, dst.value, src.value, totalsize, is_volatile.value);
|
||||
}
|
||||
|
|
@ -12,7 +12,6 @@ use crate::{
|
|||
call_ndarray_calc_size,
|
||||
},
|
||||
llvm_intrinsics::{self, call_memcpy_generic},
|
||||
macros::codegen_unreachable,
|
||||
stmt::{gen_for_callback_incrementing, gen_for_range_callback, gen_if_else_expr_callback},
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
|
|
@ -27,15 +26,12 @@ use crate::{
|
|||
typedef::{FunSignature, Type, TypeEnum},
|
||||
},
|
||||
};
|
||||
use inkwell::types::{AnyTypeEnum, BasicTypeEnum, PointerType};
|
||||
use inkwell::{
|
||||
types::BasicType,
|
||||
values::{BasicValueEnum, IntValue, PointerValue},
|
||||
AddressSpace, IntPredicate, OptimizationLevel,
|
||||
};
|
||||
use inkwell::{
|
||||
types::{AnyTypeEnum, BasicTypeEnum, PointerType},
|
||||
values::BasicValue,
|
||||
};
|
||||
use nac3parser::ast::{Operator, StrRef};
|
||||
|
||||
/// Creates an uninitialized `NDArray` instance.
|
||||
|
|
@ -163,7 +159,7 @@ where
|
|||
///
|
||||
/// * `elem_ty` - The element type of the `NDArray`.
|
||||
/// * `shape` - The shape of the `NDArray`, represented am array of [`IntValue`]s.
|
||||
pub fn create_ndarray_const_shape<'ctx, G: CodeGenerator + ?Sized>(
|
||||
fn create_ndarray_const_shape<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
elem_ty: Type,
|
||||
|
|
@ -258,9 +254,9 @@ fn ndarray_zero_value<'ctx, G: CodeGenerator + ?Sized>(
|
|||
} else if ctx.unifier.unioned(elem_ty, ctx.primitives.bool) {
|
||||
ctx.ctx.bool_type().const_zero().into()
|
||||
} else if ctx.unifier.unioned(elem_ty, ctx.primitives.str) {
|
||||
ctx.gen_string(generator, "").into()
|
||||
ctx.gen_string(generator, "").value.into()
|
||||
} else {
|
||||
codegen_unreachable!(ctx)
|
||||
unreachable!()
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -286,9 +282,9 @@ fn ndarray_one_value<'ctx, G: CodeGenerator + ?Sized>(
|
|||
} else if ctx.unifier.unioned(elem_ty, ctx.primitives.bool) {
|
||||
ctx.ctx.bool_type().const_int(1, false).into()
|
||||
} else if ctx.unifier.unioned(elem_ty, ctx.primitives.str) {
|
||||
ctx.gen_string(generator, "1").into()
|
||||
ctx.gen_string(generator, "1").value.into()
|
||||
} else {
|
||||
codegen_unreachable!(ctx)
|
||||
unreachable!()
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -356,7 +352,7 @@ fn call_ndarray_empty_impl<'ctx, G: CodeGenerator + ?Sized>(
|
|||
|
||||
create_ndarray_const_shape(generator, ctx, elem_ty, &[shape_int])
|
||||
}
|
||||
_ => codegen_unreachable!(ctx),
|
||||
_ => unreachable!(),
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -627,7 +623,7 @@ fn call_ndarray_full_impl<'ctx, G: CodeGenerator + ?Sized>(
|
|||
} else if fill_value.is_int_value() || fill_value.is_float_value() {
|
||||
fill_value
|
||||
} else {
|
||||
codegen_unreachable!(ctx)
|
||||
unreachable!()
|
||||
};
|
||||
|
||||
Ok(value)
|
||||
|
|
@ -942,7 +938,7 @@ fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
|
|||
.build_store(
|
||||
lst,
|
||||
ctx.builder
|
||||
.build_bit_cast(object.as_base_value(), llvm_plist_i8, "")
|
||||
.build_bitcast(object.as_base_value(), llvm_plist_i8, "")
|
||||
.unwrap(),
|
||||
)
|
||||
.unwrap();
|
||||
|
|
@ -964,7 +960,7 @@ fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
|
|||
.builder
|
||||
.build_load(lst, "")
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.map(|v| ctx.builder.build_bit_cast(v, plist_plist_i8, "").unwrap())
|
||||
.map(|v| ctx.builder.build_bitcast(v, plist_plist_i8, "").unwrap())
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap();
|
||||
let this_dim = ListValue::from_ptr_val(this_dim, llvm_usize, None);
|
||||
|
|
@ -983,9 +979,7 @@ fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
|
|||
ctx.builder
|
||||
.build_store(
|
||||
lst,
|
||||
ctx.builder
|
||||
.build_bit_cast(next_dim, llvm_plist_i8, "")
|
||||
.unwrap(),
|
||||
ctx.builder.build_bitcast(next_dim, llvm_plist_i8, "").unwrap(),
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
|
|
@ -1074,15 +1068,15 @@ fn call_ndarray_eye_impl<'ctx, G: CodeGenerator + ?Sized>(
|
|||
/// Copies a slice of an [`NDArrayValue`] to another.
|
||||
///
|
||||
/// - `dst_arr`: The [`NDArrayValue`] instance of the destination array. The `ndims` and `dim_sz`
|
||||
/// fields should be populated before calling this function.
|
||||
/// fields should be populated before calling this function.
|
||||
/// - `dst_slice_ptr`: The [`PointerValue`] to the first element of the currently processing
|
||||
/// dimensional slice in the destination array.
|
||||
/// dimensional slice in the destination array.
|
||||
/// - `src_arr`: The [`NDArrayValue`] instance of the source array.
|
||||
/// - `src_slice_ptr`: The [`PointerValue`] to the first element of the currently processing
|
||||
/// dimensional slice in the source array.
|
||||
/// dimensional slice in the source array.
|
||||
/// - `dim`: The index of the currently processing dimension.
|
||||
/// - `slices`: List of all slices, with the first element corresponding to the slice applicable to
|
||||
/// this dimension. The `start`/`stop` values of each slice must be non-negative indices.
|
||||
/// this dimension. The `start`/`stop` values of each slice must be non-negative indices.
|
||||
fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
|
|
@ -1187,7 +1181,7 @@ fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
|
|||
///
|
||||
/// * `elem_ty` - The element type of the `NDArray`.
|
||||
/// - `slices`: List of all slices, with the first element corresponding to the slice applicable to
|
||||
/// this dimension. The `start`/`stop` values of each slice must be positive indices.
|
||||
/// this dimension. The `start`/`stop` values of each slice must be positive indices.
|
||||
pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
|
|
@ -1352,7 +1346,7 @@ where
|
|||
///
|
||||
/// * `elem_ty` - The element type of the `NDArray`.
|
||||
/// * `res` - The `ndarray` instance to write results into, or [`None`] if the result should be
|
||||
/// written to a new `ndarray`.
|
||||
/// written to a new `ndarray`.
|
||||
/// * `value_fn` - Function mapping the two input elements into the result.
|
||||
///
|
||||
/// # Panic
|
||||
|
|
@ -1439,7 +1433,7 @@ where
|
|||
///
|
||||
/// * `elem_ty` - The element type of the `NDArray`.
|
||||
/// * `res` - The `ndarray` instance to write results into, or [`None`] if the result should be
|
||||
/// written to a new `ndarray`.
|
||||
/// written to a new `ndarray`.
|
||||
pub fn ndarray_matmul_2d<'ctx, G: CodeGenerator>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
|
|
@ -2023,7 +2017,7 @@ pub fn gen_ndarray_fill<'ctx>(
|
|||
} else if value_arg.is_int_value() || value_arg.is_float_value() {
|
||||
value_arg
|
||||
} else {
|
||||
codegen_unreachable!(ctx)
|
||||
unreachable!()
|
||||
};
|
||||
|
||||
Ok(value)
|
||||
|
|
@ -2032,497 +2026,3 @@ pub fn gen_ndarray_fill<'ctx>(
|
|||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// Generates LLVM IR for `ndarray.transpose`.
|
||||
pub fn ndarray_transpose<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
x1: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String> {
|
||||
const FN_NAME: &str = "ndarray_transpose";
|
||||
let (x1_ty, x1) = x1;
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
if let BasicValueEnum::PointerValue(n1) = x1 {
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
|
||||
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
|
||||
let n_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
|
||||
|
||||
// Dimensions are reversed in the transposed array
|
||||
let out = create_ndarray_dyn_shape(
|
||||
generator,
|
||||
ctx,
|
||||
elem_ty,
|
||||
&n1,
|
||||
|_, ctx, n| Ok(n.load_ndims(ctx)),
|
||||
|generator, ctx, n, idx| {
|
||||
let new_idx = ctx.builder.build_int_sub(n.load_ndims(ctx), idx, "").unwrap();
|
||||
let new_idx = ctx
|
||||
.builder
|
||||
.build_int_sub(new_idx, new_idx.get_type().const_int(1, false), "")
|
||||
.unwrap();
|
||||
unsafe { Ok(n.dim_sizes().get_typed_unchecked(ctx, generator, &new_idx, None)) }
|
||||
},
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
gen_for_callback_incrementing(
|
||||
generator,
|
||||
ctx,
|
||||
None,
|
||||
llvm_usize.const_zero(),
|
||||
(n_sz, false),
|
||||
|generator, ctx, _, idx| {
|
||||
let elem = unsafe { n1.data().get_unchecked(ctx, generator, &idx, None) };
|
||||
|
||||
let new_idx = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
|
||||
let rem_idx = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
|
||||
ctx.builder.build_store(new_idx, llvm_usize.const_zero()).unwrap();
|
||||
ctx.builder.build_store(rem_idx, idx).unwrap();
|
||||
|
||||
// Incrementally calculate the new index in the transposed array
|
||||
// For each index, we first decompose it into the n-dims and use those to reconstruct the new index
|
||||
// The formula used for indexing is:
|
||||
// idx = dim_n * ( ... (dim2 * (dim0 * dim1) + dim1) + dim2 ... ) + dim_n
|
||||
gen_for_callback_incrementing(
|
||||
generator,
|
||||
ctx,
|
||||
None,
|
||||
llvm_usize.const_zero(),
|
||||
(n1.load_ndims(ctx), false),
|
||||
|generator, ctx, _, ndim| {
|
||||
let ndim_rev =
|
||||
ctx.builder.build_int_sub(n1.load_ndims(ctx), ndim, "").unwrap();
|
||||
let ndim_rev = ctx
|
||||
.builder
|
||||
.build_int_sub(ndim_rev, llvm_usize.const_int(1, false), "")
|
||||
.unwrap();
|
||||
let dim = unsafe {
|
||||
n1.dim_sizes().get_typed_unchecked(ctx, generator, &ndim_rev, None)
|
||||
};
|
||||
|
||||
let rem_idx_val =
|
||||
ctx.builder.build_load(rem_idx, "").unwrap().into_int_value();
|
||||
let new_idx_val =
|
||||
ctx.builder.build_load(new_idx, "").unwrap().into_int_value();
|
||||
|
||||
let add_component =
|
||||
ctx.builder.build_int_unsigned_rem(rem_idx_val, dim, "").unwrap();
|
||||
let rem_idx_val =
|
||||
ctx.builder.build_int_unsigned_div(rem_idx_val, dim, "").unwrap();
|
||||
|
||||
let new_idx_val = ctx.builder.build_int_mul(new_idx_val, dim, "").unwrap();
|
||||
let new_idx_val =
|
||||
ctx.builder.build_int_add(new_idx_val, add_component, "").unwrap();
|
||||
|
||||
ctx.builder.build_store(rem_idx, rem_idx_val).unwrap();
|
||||
ctx.builder.build_store(new_idx, new_idx_val).unwrap();
|
||||
|
||||
Ok(())
|
||||
},
|
||||
llvm_usize.const_int(1, false),
|
||||
)?;
|
||||
|
||||
let new_idx_val = ctx.builder.build_load(new_idx, "").unwrap().into_int_value();
|
||||
unsafe { out.data().set_unchecked(ctx, generator, &new_idx_val, elem) };
|
||||
Ok(())
|
||||
},
|
||||
llvm_usize.const_int(1, false),
|
||||
)?;
|
||||
|
||||
Ok(out.as_base_value().into())
|
||||
} else {
|
||||
codegen_unreachable!(
|
||||
ctx,
|
||||
"{FN_NAME}() not supported for '{}'",
|
||||
format!("'{}'", ctx.unifier.stringify(x1_ty))
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
/// LLVM-typed implementation for generating the implementation for `ndarray.reshape`.
|
||||
///
|
||||
/// * `x1` - `NDArray` to reshape.
|
||||
/// * `shape` - The `shape` parameter used to construct the new `NDArray`.
|
||||
/// Just like numpy, the `shape` argument can be:
|
||||
/// 1. A list of `int32`; e.g., `np.reshape(arr, [600, -1, 3])`
|
||||
/// 2. A tuple of `int32`; e.g., `np.reshape(arr, (-1, 800, 3))`
|
||||
/// 3. A scalar `int32`; e.g., `np.reshape(arr, 3)`
|
||||
///
|
||||
/// Note that unlike other generating functions, one of the dimensions in the shape can be negative.
|
||||
pub fn ndarray_reshape<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
x1: (Type, BasicValueEnum<'ctx>),
|
||||
shape: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String> {
|
||||
const FN_NAME: &str = "ndarray_reshape";
|
||||
let (x1_ty, x1) = x1;
|
||||
let (_, shape) = shape;
|
||||
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
if let BasicValueEnum::PointerValue(n1) = x1 {
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
|
||||
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
|
||||
let n_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
|
||||
|
||||
let acc = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
|
||||
let num_neg = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
|
||||
ctx.builder.build_store(acc, llvm_usize.const_int(1, false)).unwrap();
|
||||
ctx.builder.build_store(num_neg, llvm_usize.const_zero()).unwrap();
|
||||
|
||||
let out = match shape {
|
||||
BasicValueEnum::PointerValue(shape_list_ptr)
|
||||
if ListValue::is_instance(shape_list_ptr, llvm_usize).is_ok() =>
|
||||
{
|
||||
// 1. A list of ints; e.g., `np.reshape(arr, [int64(600), int64(800, -1])`
|
||||
|
||||
let shape_list = ListValue::from_ptr_val(shape_list_ptr, llvm_usize, None);
|
||||
// Check for -1 in dimensions
|
||||
gen_for_callback_incrementing(
|
||||
generator,
|
||||
ctx,
|
||||
None,
|
||||
llvm_usize.const_zero(),
|
||||
(shape_list.load_size(ctx, None), false),
|
||||
|generator, ctx, _, idx| {
|
||||
let ele =
|
||||
shape_list.data().get(ctx, generator, &idx, None).into_int_value();
|
||||
let ele = ctx.builder.build_int_s_extend(ele, llvm_usize, "").unwrap();
|
||||
|
||||
gen_if_else_expr_callback(
|
||||
generator,
|
||||
ctx,
|
||||
|_, ctx| {
|
||||
Ok(ctx
|
||||
.builder
|
||||
.build_int_compare(
|
||||
IntPredicate::SLT,
|
||||
ele,
|
||||
llvm_usize.const_zero(),
|
||||
"",
|
||||
)
|
||||
.unwrap())
|
||||
},
|
||||
|_, ctx| -> Result<Option<IntValue>, String> {
|
||||
let num_neg_value =
|
||||
ctx.builder.build_load(num_neg, "").unwrap().into_int_value();
|
||||
let num_neg_value = ctx
|
||||
.builder
|
||||
.build_int_add(
|
||||
num_neg_value,
|
||||
llvm_usize.const_int(1, false),
|
||||
"",
|
||||
)
|
||||
.unwrap();
|
||||
ctx.builder.build_store(num_neg, num_neg_value).unwrap();
|
||||
Ok(None)
|
||||
},
|
||||
|_, ctx| {
|
||||
let acc_value =
|
||||
ctx.builder.build_load(acc, "").unwrap().into_int_value();
|
||||
let acc_value =
|
||||
ctx.builder.build_int_mul(acc_value, ele, "").unwrap();
|
||||
ctx.builder.build_store(acc, acc_value).unwrap();
|
||||
Ok(None)
|
||||
},
|
||||
)?;
|
||||
Ok(())
|
||||
},
|
||||
llvm_usize.const_int(1, false),
|
||||
)?;
|
||||
let acc_val = ctx.builder.build_load(acc, "").unwrap().into_int_value();
|
||||
let rem = ctx.builder.build_int_unsigned_div(n_sz, acc_val, "").unwrap();
|
||||
// Generate the output shape by filling -1 with `rem`
|
||||
create_ndarray_dyn_shape(
|
||||
generator,
|
||||
ctx,
|
||||
elem_ty,
|
||||
&shape_list,
|
||||
|_, ctx, _| Ok(shape_list.load_size(ctx, None)),
|
||||
|generator, ctx, shape_list, idx| {
|
||||
let dim =
|
||||
shape_list.data().get(ctx, generator, &idx, None).into_int_value();
|
||||
let dim = ctx.builder.build_int_s_extend(dim, llvm_usize, "").unwrap();
|
||||
|
||||
Ok(gen_if_else_expr_callback(
|
||||
generator,
|
||||
ctx,
|
||||
|_, ctx| {
|
||||
Ok(ctx
|
||||
.builder
|
||||
.build_int_compare(
|
||||
IntPredicate::SLT,
|
||||
dim,
|
||||
llvm_usize.const_zero(),
|
||||
"",
|
||||
)
|
||||
.unwrap())
|
||||
},
|
||||
|_, _| Ok(Some(rem)),
|
||||
|_, _| Ok(Some(dim)),
|
||||
)?
|
||||
.unwrap()
|
||||
.into_int_value())
|
||||
},
|
||||
)
|
||||
}
|
||||
BasicValueEnum::StructValue(shape_tuple) => {
|
||||
// 2. A tuple of `int32`; e.g., `np.reshape(arr, (-1, 800, 3))`
|
||||
|
||||
let ndims = shape_tuple.get_type().count_fields();
|
||||
// Check for -1 in dims
|
||||
for dim_i in 0..ndims {
|
||||
let dim = ctx
|
||||
.builder
|
||||
.build_extract_value(shape_tuple, dim_i, "")
|
||||
.unwrap()
|
||||
.into_int_value();
|
||||
let dim = ctx.builder.build_int_s_extend(dim, llvm_usize, "").unwrap();
|
||||
|
||||
gen_if_else_expr_callback(
|
||||
generator,
|
||||
ctx,
|
||||
|_, ctx| {
|
||||
Ok(ctx
|
||||
.builder
|
||||
.build_int_compare(
|
||||
IntPredicate::SLT,
|
||||
dim,
|
||||
llvm_usize.const_zero(),
|
||||
"",
|
||||
)
|
||||
.unwrap())
|
||||
},
|
||||
|_, ctx| -> Result<Option<IntValue>, String> {
|
||||
let num_negs =
|
||||
ctx.builder.build_load(num_neg, "").unwrap().into_int_value();
|
||||
let num_negs = ctx
|
||||
.builder
|
||||
.build_int_add(num_negs, llvm_usize.const_int(1, false), "")
|
||||
.unwrap();
|
||||
ctx.builder.build_store(num_neg, num_negs).unwrap();
|
||||
Ok(None)
|
||||
},
|
||||
|_, ctx| {
|
||||
let acc_val = ctx.builder.build_load(acc, "").unwrap().into_int_value();
|
||||
let acc_val = ctx.builder.build_int_mul(acc_val, dim, "").unwrap();
|
||||
ctx.builder.build_store(acc, acc_val).unwrap();
|
||||
Ok(None)
|
||||
},
|
||||
)?;
|
||||
}
|
||||
|
||||
let acc_val = ctx.builder.build_load(acc, "").unwrap().into_int_value();
|
||||
let rem = ctx.builder.build_int_unsigned_div(n_sz, acc_val, "").unwrap();
|
||||
let mut shape = Vec::with_capacity(ndims as usize);
|
||||
|
||||
// Reconstruct shape filling negatives with rem
|
||||
for dim_i in 0..ndims {
|
||||
let dim = ctx
|
||||
.builder
|
||||
.build_extract_value(shape_tuple, dim_i, "")
|
||||
.unwrap()
|
||||
.into_int_value();
|
||||
let dim = ctx.builder.build_int_s_extend(dim, llvm_usize, "").unwrap();
|
||||
|
||||
let dim = gen_if_else_expr_callback(
|
||||
generator,
|
||||
ctx,
|
||||
|_, ctx| {
|
||||
Ok(ctx
|
||||
.builder
|
||||
.build_int_compare(
|
||||
IntPredicate::SLT,
|
||||
dim,
|
||||
llvm_usize.const_zero(),
|
||||
"",
|
||||
)
|
||||
.unwrap())
|
||||
},
|
||||
|_, _| Ok(Some(rem)),
|
||||
|_, _| Ok(Some(dim)),
|
||||
)?
|
||||
.unwrap()
|
||||
.into_int_value();
|
||||
shape.push(dim);
|
||||
}
|
||||
create_ndarray_const_shape(generator, ctx, elem_ty, shape.as_slice())
|
||||
}
|
||||
BasicValueEnum::IntValue(shape_int) => {
|
||||
// 3. A scalar `int32`; e.g., `np.reshape(arr, 3)`
|
||||
let shape_int = gen_if_else_expr_callback(
|
||||
generator,
|
||||
ctx,
|
||||
|_, ctx| {
|
||||
Ok(ctx
|
||||
.builder
|
||||
.build_int_compare(
|
||||
IntPredicate::SLT,
|
||||
shape_int,
|
||||
llvm_usize.const_zero(),
|
||||
"",
|
||||
)
|
||||
.unwrap())
|
||||
},
|
||||
|_, _| Ok(Some(n_sz)),
|
||||
|_, ctx| {
|
||||
Ok(Some(ctx.builder.build_int_s_extend(shape_int, llvm_usize, "").unwrap()))
|
||||
},
|
||||
)?
|
||||
.unwrap()
|
||||
.into_int_value();
|
||||
create_ndarray_const_shape(generator, ctx, elem_ty, &[shape_int])
|
||||
}
|
||||
_ => codegen_unreachable!(ctx),
|
||||
}
|
||||
.unwrap();
|
||||
|
||||
// Only allow one dimension to be negative
|
||||
let num_negs = ctx.builder.build_load(num_neg, "").unwrap().into_int_value();
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
ctx.builder
|
||||
.build_int_compare(IntPredicate::ULT, num_negs, llvm_usize.const_int(2, false), "")
|
||||
.unwrap(),
|
||||
"0:ValueError",
|
||||
"can only specify one unknown dimension",
|
||||
[None, None, None],
|
||||
ctx.current_loc,
|
||||
);
|
||||
|
||||
// The new shape must be compatible with the old shape
|
||||
let out_sz = call_ndarray_calc_size(generator, ctx, &out.dim_sizes(), (None, None));
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
ctx.builder.build_int_compare(IntPredicate::EQ, out_sz, n_sz, "").unwrap(),
|
||||
"0:ValueError",
|
||||
"cannot reshape array of size {0} into provided shape of size {1}",
|
||||
[Some(n_sz), Some(out_sz), None],
|
||||
ctx.current_loc,
|
||||
);
|
||||
|
||||
gen_for_callback_incrementing(
|
||||
generator,
|
||||
ctx,
|
||||
None,
|
||||
llvm_usize.const_zero(),
|
||||
(n_sz, false),
|
||||
|generator, ctx, _, idx| {
|
||||
let elem = unsafe { n1.data().get_unchecked(ctx, generator, &idx, None) };
|
||||
unsafe { out.data().set_unchecked(ctx, generator, &idx, elem) };
|
||||
Ok(())
|
||||
},
|
||||
llvm_usize.const_int(1, false),
|
||||
)?;
|
||||
|
||||
Ok(out.as_base_value().into())
|
||||
} else {
|
||||
codegen_unreachable!(
|
||||
ctx,
|
||||
"{FN_NAME}() not supported for '{}'",
|
||||
format!("'{}'", ctx.unifier.stringify(x1_ty))
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
/// Generates LLVM IR for `ndarray.dot`.
|
||||
/// Calculate inner product of two vectors or literals
|
||||
/// For matrix multiplication use `np_matmul`
|
||||
///
|
||||
/// The input `NDArray` are flattened and treated as 1D
|
||||
/// The operation is equivalent to `np.dot(arr1.ravel(), arr2.ravel())`
|
||||
pub fn ndarray_dot<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
x1: (Type, BasicValueEnum<'ctx>),
|
||||
x2: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String> {
|
||||
const FN_NAME: &str = "ndarray_dot";
|
||||
let (x1_ty, x1) = x1;
|
||||
let (_, x2) = x2;
|
||||
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
match (x1, x2) {
|
||||
(BasicValueEnum::PointerValue(n1), BasicValueEnum::PointerValue(n2)) => {
|
||||
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
|
||||
let n2 = NDArrayValue::from_ptr_val(n2, llvm_usize, None);
|
||||
|
||||
let n1_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
|
||||
let n2_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
|
||||
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
ctx.builder.build_int_compare(IntPredicate::EQ, n1_sz, n2_sz, "").unwrap(),
|
||||
"0:ValueError",
|
||||
"shapes ({0}), ({1}) not aligned",
|
||||
[Some(n1_sz), Some(n2_sz), None],
|
||||
ctx.current_loc,
|
||||
);
|
||||
|
||||
let identity =
|
||||
unsafe { n1.data().get_unchecked(ctx, generator, &llvm_usize.const_zero(), None) };
|
||||
let acc = ctx.builder.build_alloca(identity.get_type(), "").unwrap();
|
||||
ctx.builder.build_store(acc, identity.get_type().const_zero()).unwrap();
|
||||
|
||||
gen_for_callback_incrementing(
|
||||
generator,
|
||||
ctx,
|
||||
None,
|
||||
llvm_usize.const_zero(),
|
||||
(n1_sz, false),
|
||||
|generator, ctx, _, idx| {
|
||||
let elem1 = unsafe { n1.data().get_unchecked(ctx, generator, &idx, None) };
|
||||
let elem2 = unsafe { n2.data().get_unchecked(ctx, generator, &idx, None) };
|
||||
|
||||
let product = match elem1 {
|
||||
BasicValueEnum::IntValue(e1) => ctx
|
||||
.builder
|
||||
.build_int_mul(e1, elem2.into_int_value(), "")
|
||||
.unwrap()
|
||||
.as_basic_value_enum(),
|
||||
BasicValueEnum::FloatValue(e1) => ctx
|
||||
.builder
|
||||
.build_float_mul(e1, elem2.into_float_value(), "")
|
||||
.unwrap()
|
||||
.as_basic_value_enum(),
|
||||
_ => codegen_unreachable!(ctx),
|
||||
};
|
||||
let acc_val = ctx.builder.build_load(acc, "").unwrap();
|
||||
let acc_val = match acc_val {
|
||||
BasicValueEnum::IntValue(e1) => ctx
|
||||
.builder
|
||||
.build_int_add(e1, product.into_int_value(), "")
|
||||
.unwrap()
|
||||
.as_basic_value_enum(),
|
||||
BasicValueEnum::FloatValue(e1) => ctx
|
||||
.builder
|
||||
.build_float_add(e1, product.into_float_value(), "")
|
||||
.unwrap()
|
||||
.as_basic_value_enum(),
|
||||
_ => codegen_unreachable!(ctx),
|
||||
};
|
||||
ctx.builder.build_store(acc, acc_val).unwrap();
|
||||
|
||||
Ok(())
|
||||
},
|
||||
llvm_usize.const_int(1, false),
|
||||
)?;
|
||||
let acc_val = ctx.builder.build_load(acc, "").unwrap();
|
||||
Ok(acc_val)
|
||||
}
|
||||
(BasicValueEnum::IntValue(e1), BasicValueEnum::IntValue(e2)) => {
|
||||
Ok(ctx.builder.build_int_mul(e1, e2, "").unwrap().as_basic_value_enum())
|
||||
}
|
||||
(BasicValueEnum::FloatValue(e1), BasicValueEnum::FloatValue(e2)) => {
|
||||
Ok(ctx.builder.build_float_mul(e1, e2, "").unwrap().as_basic_value_enum())
|
||||
}
|
||||
_ => codegen_unreachable!(
|
||||
ctx,
|
||||
"{FN_NAME}() not supported for '{}'",
|
||||
format!("'{}'", ctx.unifier.stringify(x1_ty))
|
||||
),
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,113 @@
|
|||
use itertools::Itertools;
|
||||
|
||||
use crate::{
|
||||
codegen::{
|
||||
irrt::ndarray::broadcast::{
|
||||
call_nac3_ndarray_broadcast_shapes, call_nac3_ndarray_broadcast_to, ShapeEntry,
|
||||
},
|
||||
model::*,
|
||||
numpy_new::util::{create_ndims, extract_ndims},
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
typecheck::typedef::Type,
|
||||
};
|
||||
|
||||
use super::object::NDArrayObject;
|
||||
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct BroadcastAllResult<'ctx> {
|
||||
/// The statically known `ndims` of the broadcast result.
|
||||
pub ndims: u64,
|
||||
/// The broadcasting shape.
|
||||
pub shape: Ptr<'ctx, IntModel<SizeT>>,
|
||||
/// Broadcasted views on the inputs.
|
||||
///
|
||||
/// All of them will have `shape` [`BroadcastAllResult::shape`] and
|
||||
/// `ndims` [`BroadcastAllResult::ndims`]. The length of the vector
|
||||
/// is the same as the input.
|
||||
pub ndarrays: Vec<NDArrayObject<'ctx>>,
|
||||
}
|
||||
|
||||
// TODO: DOCUMENT: Behaves like `np.broadcast()`, except returns results differently.
|
||||
pub fn broadcast_all_ndarrays<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndarrays: Vec<NDArrayObject<'ctx>>,
|
||||
) -> BroadcastAllResult<'ctx> {
|
||||
assert!(!ndarrays.is_empty());
|
||||
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let sizet_model = IntModel(SizeT);
|
||||
let shape_model = StructModel(ShapeEntry);
|
||||
|
||||
// We can deduce the final ndims statically and immediately.
|
||||
// It should be `max([ ndarray.ndims for ndarray in ndarrays ])`.
|
||||
let broadcast_ndims =
|
||||
ndarrays.iter().map(|ndarray| extract_ndims(&ctx.unifier, ndarray.ndims)).max().unwrap();
|
||||
let broadcast_ndims_ty = create_ndims(&mut ctx.unifier, broadcast_ndims);
|
||||
|
||||
// NOTE: Now prepare before calling `call_nac3_ndarray_broadcast_shapes`
|
||||
|
||||
// Prepare input shape entries
|
||||
let num_shape_entries =
|
||||
sizet_model.constant(tyctx, ctx.ctx, u64::try_from(ndarrays.len()).unwrap());
|
||||
let shape_entries =
|
||||
shape_model.array_alloca(tyctx, ctx, num_shape_entries.value, "shape_entries");
|
||||
for (i, ndarray) in ndarrays.iter().enumerate() {
|
||||
let i = sizet_model.constant(tyctx, ctx.ctx, i as u64).value;
|
||||
|
||||
let this_shape = ndarray.instance.gep(ctx, |f| f.shape).load(tyctx, ctx, "this_shape");
|
||||
let this_ndims = ndarray.instance.gep(ctx, |f| f.ndims).load(tyctx, ctx, "this_ndims");
|
||||
|
||||
let shape_entry = shape_entries.offset(tyctx, ctx, i, "shape_entry");
|
||||
shape_entry.gep(ctx, |f| f.shape).store(ctx, this_shape);
|
||||
shape_entry.gep(ctx, |f| f.ndims).store(ctx, this_ndims);
|
||||
}
|
||||
|
||||
// Prepare destination
|
||||
let dst_ndims = sizet_model.constant(tyctx, ctx.ctx, broadcast_ndims);
|
||||
let dst_shape = sizet_model.array_alloca(tyctx, ctx, dst_ndims.value, "dst_shape");
|
||||
|
||||
call_nac3_ndarray_broadcast_shapes(
|
||||
generator,
|
||||
ctx,
|
||||
num_shape_entries,
|
||||
shape_entries,
|
||||
dst_ndims,
|
||||
dst_shape,
|
||||
);
|
||||
|
||||
// Now that we know about the broadcasting shape, broadcast all the inputs.
|
||||
|
||||
// Broadcast all the inputs to shape `dst_shape`
|
||||
let broadcasted_ndarrays = ndarrays
|
||||
.into_iter()
|
||||
.map(|ndarray| ndarray.broadcast_to(generator, ctx, broadcast_ndims_ty, dst_shape))
|
||||
.collect_vec();
|
||||
|
||||
BroadcastAllResult { ndims: broadcast_ndims, shape: dst_shape, ndarrays: broadcasted_ndarrays }
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
/// Broadcast an ndarray to a target shape.
|
||||
#[must_use]
|
||||
pub fn broadcast_to<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
target_ndims_ty: Type,
|
||||
target_shape: Ptr<'ctx, IntModel<SizeT>>,
|
||||
) -> Self {
|
||||
// Please see comment in IRRT on how the caller should prepare `dst_ndarray`
|
||||
let dst_ndarray = NDArrayObject::alloca(
|
||||
generator,
|
||||
ctx,
|
||||
target_ndims_ty,
|
||||
self.dtype,
|
||||
"broadcast_ndarray_to_dst",
|
||||
);
|
||||
dst_ndarray.copy_shape(generator, ctx, target_shape);
|
||||
call_nac3_ndarray_broadcast_to(generator, ctx, self.instance, dst_ndarray.instance);
|
||||
dst_ndarray
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,217 @@
|
|||
use inkwell::{
|
||||
types::BasicType,
|
||||
values::{BasicValue, BasicValueEnum, PointerValue},
|
||||
AddressSpace,
|
||||
};
|
||||
use nac3parser::ast::StrRef;
|
||||
|
||||
use crate::{
|
||||
codegen::{
|
||||
model::*,
|
||||
numpy_new::util::{alloca_ndarray, init_ndarray_data_by_alloca, init_ndarray_shape},
|
||||
structure::ndarray::NpArray,
|
||||
util::shape::make_shape_writer,
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
symbol_resolver::ValueEnum,
|
||||
toplevel::DefinitionId,
|
||||
typecheck::typedef::{FunSignature, Type},
|
||||
};
|
||||
|
||||
use super::util::gen_foreach_ndarray_elements;
|
||||
|
||||
/// Helper function to create an ndarray with uninitialized values
|
||||
///
|
||||
/// * `elem_ty` - The [`Type`] of the ndarray elements
|
||||
/// * `shape` - The user input shape argument
|
||||
/// * `shape_ty` - The [`Type`] of the shape argument
|
||||
/// * `name` - LLVM IR name of the returned ndarray
|
||||
fn create_empty_ndarray<'ctx, G>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
elem_ty: Type,
|
||||
shape: BasicValueEnum<'ctx>,
|
||||
shape_ty: Type,
|
||||
name: &str,
|
||||
) -> Result<Ptr<'ctx, StructModel<NpArray>>, String>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
{
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let sizet_model = IntModel(SizeT);
|
||||
|
||||
let shape_writer = make_shape_writer(generator, ctx, shape, shape_ty);
|
||||
let ndims = shape_writer.len;
|
||||
|
||||
let ndarray = alloca_ndarray(generator, ctx, ndims, name);
|
||||
init_ndarray_shape(generator, ctx, ndarray, &shape_writer)?;
|
||||
|
||||
let itemsize = ctx.get_llvm_type(generator, elem_ty).size_of().unwrap();
|
||||
let itemsize = sizet_model.check_value(tyctx, ctx.ctx, itemsize).unwrap();
|
||||
ndarray.gep(ctx, |f| f.itemsize).store(ctx, itemsize);
|
||||
|
||||
// Needs `itemsize` and `shape` initialized
|
||||
init_ndarray_data_by_alloca(generator, ctx, ndarray);
|
||||
|
||||
Ok(ndarray)
|
||||
}
|
||||
|
||||
/// Helper function to create an ndarray full of a value.
|
||||
///
|
||||
/// * `elem_ty` - The [`Type`] of the ndarray elements and the fill value
|
||||
/// * `shape` - The user input shape argument
|
||||
/// * `shape_ty` - The [`Type`] of the shape argument
|
||||
/// * `fill_value` - The user specified fill value
|
||||
/// * `name` - LLVM IR name of the returned ndarray
|
||||
fn create_full_ndarray<'ctx, G>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
elem_ty: Type,
|
||||
shape: BasicValueEnum<'ctx>,
|
||||
shape_ty: Type,
|
||||
fill_value: BasicValueEnum<'ctx>,
|
||||
name: &str,
|
||||
) -> Result<Ptr<'ctx, StructModel<NpArray>>, String>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
{
|
||||
let pndarray = create_empty_ndarray(generator, ctx, elem_ty, shape, shape_ty, name)?;
|
||||
gen_foreach_ndarray_elements(
|
||||
generator,
|
||||
ctx,
|
||||
pndarray,
|
||||
|_generator, ctx, _hooks, _i, pelement| {
|
||||
// Cannot use Model here, fill_value's type is not statically known.
|
||||
let pfill_value_ty = fill_value.get_type().ptr_type(AddressSpace::default());
|
||||
let pelement =
|
||||
ctx.builder.build_pointer_cast(pelement.value, pfill_value_ty, "pelement").unwrap();
|
||||
ctx.builder.build_store(pelement, fill_value).unwrap();
|
||||
Ok(())
|
||||
},
|
||||
)?;
|
||||
Ok(pndarray)
|
||||
}
|
||||
|
||||
/// Generates LLVM IR for `np.empty`.
|
||||
pub fn gen_ndarray_empty<'ctx>(
|
||||
context: &mut CodeGenContext<'ctx, '_>,
|
||||
obj: &Option<(Type, ValueEnum<'ctx>)>,
|
||||
fun: (&FunSignature, DefinitionId),
|
||||
args: &[(Option<StrRef>, ValueEnum<'ctx>)],
|
||||
generator: &mut dyn CodeGenerator,
|
||||
) -> Result<PointerValue<'ctx>, String> {
|
||||
assert!(obj.is_none());
|
||||
assert_eq!(args.len(), 1);
|
||||
|
||||
// Parse arguments
|
||||
let shape_ty = fun.0.args[0].ty;
|
||||
let shape = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
|
||||
|
||||
// Implementation
|
||||
let ndarray_ptr = create_empty_ndarray(
|
||||
generator,
|
||||
context,
|
||||
context.primitives.float,
|
||||
shape,
|
||||
shape_ty,
|
||||
"ndarray",
|
||||
)?;
|
||||
Ok(ndarray_ptr.value)
|
||||
}
|
||||
|
||||
/// Generates LLVM IR for `np.zeros`.
|
||||
pub fn gen_ndarray_zeros<'ctx>(
|
||||
context: &mut CodeGenContext<'ctx, '_>,
|
||||
obj: &Option<(Type, ValueEnum<'ctx>)>,
|
||||
fun: (&FunSignature, DefinitionId),
|
||||
args: &[(Option<StrRef>, ValueEnum<'ctx>)],
|
||||
generator: &mut dyn CodeGenerator,
|
||||
) -> Result<PointerValue<'ctx>, String> {
|
||||
assert!(obj.is_none());
|
||||
assert_eq!(args.len(), 1);
|
||||
|
||||
// Parse arguments
|
||||
let shape_ty = fun.0.args[0].ty;
|
||||
let shape = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
|
||||
|
||||
// Implementation
|
||||
// NOTE: Currently nac3's `np.zeros` is always `float64`.
|
||||
let float64_ty = context.primitives.float;
|
||||
let float64_llvm_type = context.get_llvm_type(generator, float64_ty).into_float_type();
|
||||
|
||||
let ndarray_ptr = create_full_ndarray(
|
||||
generator,
|
||||
context,
|
||||
float64_ty, // `elem_ty` is always `float64`
|
||||
shape,
|
||||
shape_ty,
|
||||
float64_llvm_type.const_zero().as_basic_value_enum(),
|
||||
"ndarray",
|
||||
)?;
|
||||
Ok(ndarray_ptr.value)
|
||||
}
|
||||
|
||||
/// Generates LLVM IR for `np.ones`.
|
||||
pub fn gen_ndarray_ones<'ctx>(
|
||||
context: &mut CodeGenContext<'ctx, '_>,
|
||||
obj: &Option<(Type, ValueEnum<'ctx>)>,
|
||||
fun: (&FunSignature, DefinitionId),
|
||||
args: &[(Option<StrRef>, ValueEnum<'ctx>)],
|
||||
generator: &mut dyn CodeGenerator,
|
||||
) -> Result<PointerValue<'ctx>, String> {
|
||||
assert!(obj.is_none());
|
||||
assert_eq!(args.len(), 1);
|
||||
|
||||
// Parse arguments
|
||||
let shape_ty = fun.0.args[0].ty;
|
||||
let shape = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
|
||||
|
||||
// Implementation
|
||||
// NOTE: Currently nac3's `np.ones` is always `float64`.
|
||||
let float64_ty = context.primitives.float;
|
||||
let float64_llvm_type = context.get_llvm_type(generator, float64_ty).into_float_type();
|
||||
|
||||
let ndarray_ptr = create_full_ndarray(
|
||||
generator,
|
||||
context,
|
||||
float64_ty, // `elem_ty` is always `float64`
|
||||
shape,
|
||||
shape_ty,
|
||||
float64_llvm_type.const_float(1.0).as_basic_value_enum(),
|
||||
"ndarray",
|
||||
)?;
|
||||
Ok(ndarray_ptr.value)
|
||||
}
|
||||
|
||||
/// Generates LLVM IR for `np.full`.
|
||||
pub fn gen_ndarray_full<'ctx>(
|
||||
context: &mut CodeGenContext<'ctx, '_>,
|
||||
obj: &Option<(Type, ValueEnum<'ctx>)>,
|
||||
fun: (&FunSignature, DefinitionId),
|
||||
args: &[(Option<StrRef>, ValueEnum<'ctx>)],
|
||||
generator: &mut dyn CodeGenerator,
|
||||
) -> Result<PointerValue<'ctx>, String> {
|
||||
assert!(obj.is_none());
|
||||
assert_eq!(args.len(), 2);
|
||||
|
||||
// Parse argument #1 shape
|
||||
let shape_ty = fun.0.args[0].ty;
|
||||
let shape_arg = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
|
||||
|
||||
// Parse argument #2 fill_value
|
||||
let fill_value_ty = fun.0.args[1].ty;
|
||||
let fill_value_arg =
|
||||
args[1].1.clone().to_basic_value_enum(context, generator, fill_value_ty)?;
|
||||
|
||||
// Implementation
|
||||
let ndarray_ptr = create_full_ndarray(
|
||||
generator,
|
||||
context,
|
||||
fill_value_ty,
|
||||
shape_arg,
|
||||
shape_ty,
|
||||
fill_value_arg,
|
||||
"ndarray",
|
||||
)?;
|
||||
Ok(ndarray_ptr.value)
|
||||
}
|
||||
|
|
@ -0,0 +1,76 @@
|
|||
use crate::{
|
||||
codegen::{
|
||||
irrt::ndarray::indexing::{call_nac3_ndarray_index, RustNDIndex},
|
||||
model::*,
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
typecheck::typedef::{Type, Unifier},
|
||||
};
|
||||
|
||||
use super::{
|
||||
object::{NDArrayObject, ScalarObject, ScalarOrNDArray},
|
||||
util::{create_ndims, extract_ndims},
|
||||
};
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
pub fn deduce_ndims_after_indexing_with(
|
||||
&self,
|
||||
unifier: &mut Unifier,
|
||||
indexes: &[RustNDIndex<'ctx>],
|
||||
) -> Type {
|
||||
let ndims = extract_ndims(unifier, self.ndims);
|
||||
let new_ndims = RustNDIndex::deduce_ndims_after_indexing(indexes, ndims);
|
||||
create_ndims(unifier, new_ndims)
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn index_always_ndarray<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
indexes: &[RustNDIndex<'ctx>],
|
||||
name: &str,
|
||||
) -> Self {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
let dst_ndims = self.deduce_ndims_after_indexing_with(&mut ctx.unifier, indexes);
|
||||
let dst_ndarray = NDArrayObject::alloca(generator, ctx, dst_ndims, self.dtype, name);
|
||||
|
||||
let (num_indexes, indexes) = RustNDIndex::alloca_ndindexes(tyctx, ctx, indexes);
|
||||
call_nac3_ndarray_index(
|
||||
generator,
|
||||
ctx,
|
||||
num_indexes,
|
||||
indexes,
|
||||
self.instance,
|
||||
dst_ndarray.instance,
|
||||
);
|
||||
|
||||
dst_ndarray
|
||||
}
|
||||
|
||||
pub fn index<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
indexes: &[RustNDIndex<'ctx>],
|
||||
name: &str,
|
||||
) -> ScalarOrNDArray<'ctx> {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let sizet_model = IntModel(SizeT);
|
||||
|
||||
let subndarray = self.index_always_ndarray(generator, ctx, indexes, name);
|
||||
if subndarray.is_unsized(&ctx.unifier) {
|
||||
// TODO: This actually never fails, don't use the `checked_` version.
|
||||
let value = subndarray.checked_get_nth_element(
|
||||
generator,
|
||||
ctx,
|
||||
sizet_model.const_0(tyctx, ctx.ctx),
|
||||
name,
|
||||
);
|
||||
ScalarOrNDArray::Scalar(ScalarObject { dtype: self.dtype, value })
|
||||
} else {
|
||||
ScalarOrNDArray::NDArray(subndarray)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,6 @@
|
|||
pub mod broadcast;
|
||||
pub mod factory;
|
||||
pub mod indexing;
|
||||
pub mod object;
|
||||
pub mod util;
|
||||
pub mod view;
|
||||
|
|
@ -0,0 +1,69 @@
|
|||
use inkwell::values::{BasicValue, BasicValueEnum};
|
||||
|
||||
use crate::{
|
||||
codegen::{model::*, structure::ndarray::NpArray, CodeGenContext},
|
||||
toplevel::numpy::unpack_ndarray_var_tys,
|
||||
typecheck::typedef::{Type, TypeEnum},
|
||||
};
|
||||
|
||||
/// An LLVM ndarray instance with its typechecker [`Type`]s.
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct NDArrayObject<'ctx> {
|
||||
pub dtype: Type,
|
||||
pub ndims: Type,
|
||||
pub instance: Ptr<'ctx, StructModel<NpArray>>,
|
||||
}
|
||||
|
||||
/// An LLVM numpy scalar with its [`Type`].
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct ScalarObject<'ctx> {
|
||||
pub dtype: Type,
|
||||
pub value: BasicValueEnum<'ctx>,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub enum ScalarOrNDArray<'ctx> {
|
||||
Scalar(ScalarObject<'ctx>),
|
||||
NDArray(NDArrayObject<'ctx>),
|
||||
}
|
||||
|
||||
impl<'ctx> ScalarOrNDArray<'ctx> {
|
||||
/// Get the underlying [`BasicValueEnum<'ctx>`] of this [`ScalarOrNDArray`].
|
||||
#[must_use]
|
||||
pub fn to_basic_value_enum(self) -> BasicValueEnum<'ctx> {
|
||||
match self {
|
||||
ScalarOrNDArray::Scalar(scalar) => scalar.value,
|
||||
ScalarOrNDArray::NDArray(ndarray) => ndarray.instance.value.as_basic_value_enum(),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> From<ScalarOrNDArray<'ctx>> for BasicValueEnum<'ctx> {
|
||||
fn from(input: ScalarOrNDArray<'ctx>) -> BasicValueEnum<'ctx> {
|
||||
input.to_basic_value_enum()
|
||||
}
|
||||
}
|
||||
|
||||
/// Split an [`BasicValueEnum<'ctx>`] into a [`ScalarOrNDArray`] depending
|
||||
/// on its [`Type`].
|
||||
pub fn split_scalar_or_ndarray<'ctx>(
|
||||
tyctx: TypeContext<'ctx>,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
input: BasicValueEnum<'ctx>,
|
||||
input_ty: Type,
|
||||
) -> ScalarOrNDArray<'ctx> {
|
||||
let pndarray_model = PtrModel(StructModel(NpArray));
|
||||
|
||||
let input_ty_enum = ctx.unifier.get_ty(input_ty);
|
||||
match &*input_ty_enum {
|
||||
TypeEnum::TObj { obj_id, .. }
|
||||
if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
|
||||
{
|
||||
let value = pndarray_model.check_value(tyctx, ctx.ctx, input).unwrap();
|
||||
let (dtype, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, input_ty);
|
||||
|
||||
ScalarOrNDArray::NDArray(NDArrayObject { dtype, ndims, instance: value })
|
||||
}
|
||||
_ => ScalarOrNDArray::Scalar(ScalarObject { dtype: input_ty, value: input }),
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,328 @@
|
|||
use inkwell::{
|
||||
types::BasicType,
|
||||
values::{BasicValueEnum, PointerValue},
|
||||
AddressSpace,
|
||||
};
|
||||
use util::gen_model_memcpy;
|
||||
|
||||
use crate::{
|
||||
codegen::{
|
||||
irrt::ndarray::basic::{
|
||||
call_nac3_ndarray_copy_data, call_nac3_ndarray_get_nth_pelement,
|
||||
call_nac3_ndarray_is_c_contiguous, call_nac3_ndarray_nbytes,
|
||||
call_nac3_ndarray_set_strides_by_shape, call_nac3_ndarray_size,
|
||||
call_nac3_ndarray_util_assert_shape_no_negative,
|
||||
},
|
||||
model::*,
|
||||
stmt::BreakContinueHooks,
|
||||
structure::ndarray::NpArray,
|
||||
util::{array_writer::ArrayWriter, control::gen_model_for},
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
symbol_resolver::SymbolValue,
|
||||
typecheck::typedef::{Type, TypeEnum, Unifier},
|
||||
};
|
||||
|
||||
use super::object::{NDArrayObject, ScalarOrNDArray};
|
||||
|
||||
/// Extract an ndarray's `ndims` [type][`Type`] in `u64`. Panic if not possible.
|
||||
#[must_use]
|
||||
pub fn extract_ndims(unifier: &Unifier, ndims_ty: Type) -> u64 {
|
||||
let ndims_ty_enum = unifier.get_ty_immutable(ndims_ty);
|
||||
let TypeEnum::TLiteral { values, .. } = &*ndims_ty_enum else {
|
||||
panic!("ndims_ty should be a TLiteral");
|
||||
};
|
||||
|
||||
assert_eq!(values.len(), 1, "ndims_ty TLiteral should only contain 1 value");
|
||||
|
||||
let ndims = values[0].clone();
|
||||
u64::try_from(ndims).unwrap()
|
||||
}
|
||||
|
||||
/// Return an ndarray's `ndims` as a typechecker [`Type`] from its `u64` value.
|
||||
pub fn create_ndims(unifier: &mut Unifier, ndims: u64) -> Type {
|
||||
unifier.get_fresh_literal(vec![SymbolValue::U64(ndims)], None)
|
||||
}
|
||||
|
||||
/// Allocate an ndarray on the stack given its `ndims`.
|
||||
///
|
||||
/// `shape` and `strides` will be automatically allocated on the stack.
|
||||
///
|
||||
/// The returned ndarray's content will be:
|
||||
/// - `data`: `nullptr`
|
||||
/// - `itemsize`: **uninitialized** value
|
||||
/// - `ndims`: initialized value, set to the input `ndims`
|
||||
/// - `shape`: initialized pointer to an allocated stack with **uninitialized** values
|
||||
/// - `strides`: initialized pointer to an allocated stack with **uninitialized** values
|
||||
pub fn alloca_ndarray<'ctx, G>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndims: Int<'ctx, SizeT>,
|
||||
name: &str,
|
||||
) -> Ptr<'ctx, StructModel<NpArray>>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
{
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
let sizet_model = IntModel(SizeT);
|
||||
let ndarray_model = StructModel(NpArray);
|
||||
let ndarray_data_model = PtrModel(IntModel(Byte));
|
||||
|
||||
// Setup ndarray
|
||||
let ndarray_ptr = ndarray_model.alloca(tyctx, ctx, name);
|
||||
let shape = sizet_model.array_alloca(tyctx, ctx, ndims.value, "shape");
|
||||
let strides = sizet_model.array_alloca(tyctx, ctx, ndims.value, "strides");
|
||||
|
||||
ndarray_ptr.gep(ctx, |f| f.data).store(ctx, ndarray_data_model.nullptr(tyctx, ctx.ctx));
|
||||
ndarray_ptr.gep(ctx, |f| f.ndims).store(ctx, ndims);
|
||||
ndarray_ptr.gep(ctx, |f| f.shape).store(ctx, shape);
|
||||
ndarray_ptr.gep(ctx, |f| f.strides).store(ctx, strides);
|
||||
|
||||
ndarray_ptr
|
||||
}
|
||||
|
||||
/// Initialize an ndarray's `shape` and asserts on.
|
||||
/// `shape`'s values and prohibit illegal inputs like negative dimensions.
|
||||
pub fn init_ndarray_shape<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
pndarray: Ptr<'ctx, StructModel<NpArray>>,
|
||||
shape_writer: &ArrayWriter<'ctx, G, SizeT, IntModel<SizeT>>,
|
||||
) -> Result<(), String> {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let shape = pndarray.gep(ctx, |f| f.shape).load(tyctx, ctx, "shape");
|
||||
(shape_writer.write)(generator, ctx, shape)?;
|
||||
call_nac3_ndarray_util_assert_shape_no_negative(generator, ctx, shape_writer.len, shape);
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// Initialize an ndarray's `data` by allocating a buffer on the stack.
|
||||
/// The allocated data buffer is considered to be *owned* by the ndarray.
|
||||
///
|
||||
/// `strides` of the ndarray will also be updated with `set_strides_by_shape`.
|
||||
///
|
||||
/// `shape` and `itemsize` of the ndarray ***must*** be initialized first.
|
||||
pub fn init_ndarray_data_by_alloca<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
pndarray: Ptr<'ctx, StructModel<NpArray>>,
|
||||
) {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let ndarray_data_model = IntModel(Byte);
|
||||
|
||||
let nbytes = call_nac3_ndarray_nbytes(generator, ctx, pndarray);
|
||||
let data = ndarray_data_model.array_alloca(tyctx, ctx, nbytes.value, "data");
|
||||
pndarray.gep(ctx, |f| f.data).store(ctx, data);
|
||||
call_nac3_ndarray_set_strides_by_shape(generator, ctx, pndarray);
|
||||
}
|
||||
|
||||
/// Iterate through all elements in an ndarray.
|
||||
///
|
||||
/// `body` is given the index of an element and an opaque pointer (as an `uint8_t*`, you might want to cast it) to the element.
|
||||
///
|
||||
/// Short-circuiting is possible with the given [`BreakContinueHooks`].
|
||||
pub fn gen_foreach_ndarray_elements<'ctx, G, F>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
pndarray: Ptr<'ctx, StructModel<NpArray>>,
|
||||
body: F,
|
||||
) -> Result<(), String>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
F: Fn(
|
||||
&mut G,
|
||||
&mut CodeGenContext<'ctx, '_>,
|
||||
BreakContinueHooks<'ctx>,
|
||||
Int<'ctx, SizeT>,
|
||||
Ptr<'ctx, IntModel<Byte>>,
|
||||
) -> Result<(), String>,
|
||||
{
|
||||
// TODO: Make this more efficient - use a special NDArray iterator?
|
||||
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
let sizet_model = IntModel(SizeT);
|
||||
let size = call_nac3_ndarray_size(generator, ctx, pndarray);
|
||||
|
||||
gen_model_for(
|
||||
generator,
|
||||
ctx,
|
||||
sizet_model.const_0(tyctx, ctx.ctx),
|
||||
size,
|
||||
sizet_model.const_1(tyctx, ctx.ctx),
|
||||
|generator, ctx, hooks, index| {
|
||||
let pelement = call_nac3_ndarray_get_nth_pelement(generator, ctx, pndarray, index);
|
||||
body(generator, ctx, hooks, index, pelement)
|
||||
},
|
||||
)
|
||||
}
|
||||
|
||||
impl<'ctx> ScalarOrNDArray<'ctx> {
|
||||
/// Convert `input` to an ndarray - behaves like `np.asarray`.
|
||||
pub fn as_ndarray<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> NDArrayObject<'ctx> {
|
||||
match self {
|
||||
ScalarOrNDArray::NDArray(ndarray) => *ndarray,
|
||||
ScalarOrNDArray::Scalar(scalar) => {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let pbyte_model = PtrModel(IntModel(Byte));
|
||||
|
||||
// We have to put the value on the stack to get a data pointer.
|
||||
let data =
|
||||
ctx.builder.build_alloca(scalar.value.get_type(), "as_ndarray_scalar").unwrap();
|
||||
ctx.builder.build_store(data, scalar.value).unwrap();
|
||||
let data = pbyte_model.transmute(tyctx, ctx, data, "data");
|
||||
|
||||
let ndims_ty = create_ndims(&mut ctx.unifier, 0);
|
||||
let ndarray = NDArrayObject::alloca(
|
||||
generator,
|
||||
ctx,
|
||||
ndims_ty,
|
||||
scalar.dtype,
|
||||
"scalar_as_ndarray",
|
||||
);
|
||||
ndarray.instance.gep(ctx, |f| f.data).store(ctx, data);
|
||||
|
||||
// No need to initialize/setup strides or shapes - because `ndims` is 0.
|
||||
// So we only have to set `data`, `itemsize`, and `ndims = 0`.
|
||||
|
||||
ndarray
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
pub fn alloca<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndims: Type,
|
||||
dtype: Type,
|
||||
name: &str,
|
||||
) -> Self {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let sizet_model = IntModel(SizeT);
|
||||
|
||||
let ndims_int = sizet_model.constant(tyctx, ctx.ctx, extract_ndims(&ctx.unifier, ndims));
|
||||
let instance = alloca_ndarray(generator, ctx, ndims_int, name);
|
||||
|
||||
// Set itemsize
|
||||
let dtype_ty = ctx.get_llvm_type(generator, dtype);
|
||||
let itemsize = dtype_ty.size_of().unwrap();
|
||||
let itemsize = sizet_model.s_extend_or_bit_cast(tyctx, ctx, itemsize, "itemsize");
|
||||
instance.gep(ctx, |f| f.itemsize).store(ctx, itemsize);
|
||||
|
||||
NDArrayObject { dtype, ndims, instance }
|
||||
}
|
||||
|
||||
pub fn copy_shape<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
src_shape: Ptr<'ctx, IntModel<SizeT>>,
|
||||
) {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let sizet_model = IntModel(SizeT);
|
||||
|
||||
let self_shape = self.instance.gep(ctx, |f| f.shape).load(tyctx, ctx, "self_shape");
|
||||
let ndims_int =
|
||||
sizet_model.constant(tyctx, ctx.ctx, extract_ndims(&ctx.unifier, self.ndims));
|
||||
gen_model_memcpy(tyctx, ctx, self_shape, src_shape, ndims_int.value, false);
|
||||
}
|
||||
|
||||
pub fn copy_shape_from<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
src_ndarray: NDArrayObject<'ctx>,
|
||||
) {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let src_shape = src_ndarray.instance.gep(ctx, |f| f.shape).load(tyctx, ctx, "src_shape");
|
||||
self.copy_shape(generator, ctx, src_shape);
|
||||
}
|
||||
|
||||
pub fn update_strides_by_shape<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) {
|
||||
call_nac3_ndarray_set_strides_by_shape(generator, ctx, self.instance);
|
||||
}
|
||||
|
||||
pub fn checked_get_nth_pelement<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
i: Int<'ctx, SizeT>,
|
||||
name: &str,
|
||||
) -> PointerValue<'ctx> {
|
||||
let elem_ty = ctx.get_llvm_type(generator, self.dtype);
|
||||
|
||||
let p = call_nac3_ndarray_get_nth_pelement(generator, ctx, self.instance, i);
|
||||
ctx.builder
|
||||
.build_pointer_cast(p.value, elem_ty.ptr_type(AddressSpace::default()), name)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
pub fn checked_get_nth_element<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
i: Int<'ctx, SizeT>,
|
||||
name: &str,
|
||||
) -> BasicValueEnum<'ctx> {
|
||||
let pelement = self.checked_get_nth_pelement(generator, ctx, i, "pelement");
|
||||
ctx.builder.build_load(pelement, name).unwrap()
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn is_unsized(&self, unifier: &Unifier) -> bool {
|
||||
extract_ndims(unifier, self.ndims) == 0
|
||||
}
|
||||
|
||||
pub fn size<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> Int<'ctx, SizeT> {
|
||||
call_nac3_ndarray_size(generator, ctx, self.instance)
|
||||
}
|
||||
|
||||
pub fn nbytes<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> Int<'ctx, SizeT> {
|
||||
call_nac3_ndarray_nbytes(generator, ctx, self.instance)
|
||||
}
|
||||
|
||||
pub fn is_c_contiguous<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> Int<'ctx, Bool> {
|
||||
call_nac3_ndarray_is_c_contiguous(generator, ctx, self.instance)
|
||||
}
|
||||
|
||||
pub fn alloca_owned_data<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) {
|
||||
init_ndarray_data_by_alloca(generator, ctx, self.instance);
|
||||
}
|
||||
|
||||
pub fn copy_data_from<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
src: NDArrayObject<'ctx>,
|
||||
) {
|
||||
assert!(ctx.unifier.unioned(self.dtype, src.dtype), "self and src dtype should match");
|
||||
call_nac3_ndarray_copy_data(generator, ctx, src.instance, self.instance);
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,114 @@
|
|||
use inkwell::values::PointerValue;
|
||||
use nac3parser::ast::StrRef;
|
||||
|
||||
use crate::{
|
||||
codegen::{
|
||||
irrt::ndarray::reshape::call_nac3_ndarray_resolve_and_check_new_shape,
|
||||
model::*,
|
||||
numpy_new::{object::split_scalar_or_ndarray, util::extract_ndims},
|
||||
util::shape::make_shape_writer,
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
symbol_resolver::ValueEnum,
|
||||
toplevel::{numpy::unpack_ndarray_var_tys, DefinitionId},
|
||||
typecheck::typedef::{FunSignature, Type},
|
||||
};
|
||||
|
||||
use super::object::NDArrayObject;
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
#[must_use]
|
||||
pub fn reshape_or_copy<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
new_ndims: Type,
|
||||
new_shape: Ptr<'ctx, IntModel<SizeT>>,
|
||||
) -> Self {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
let current_bb = ctx.builder.get_insert_block().unwrap();
|
||||
let then_bb = ctx.ctx.insert_basic_block_after(current_bb, "then_bb");
|
||||
let else_bb = ctx.ctx.insert_basic_block_after(then_bb, "else_bb");
|
||||
let end_bb = ctx.ctx.insert_basic_block_after(else_bb, "end_bb");
|
||||
|
||||
let dst_ndarray =
|
||||
NDArrayObject::alloca(generator, ctx, new_ndims, self.dtype, "reshaped_ndarray");
|
||||
dst_ndarray.copy_shape(generator, ctx, new_shape);
|
||||
dst_ndarray.update_strides_by_shape(generator, ctx);
|
||||
|
||||
let is_c_contiguous = self.is_c_contiguous(generator, ctx);
|
||||
ctx.builder.build_conditional_branch(is_c_contiguous.value, then_bb, else_bb).unwrap();
|
||||
|
||||
// Inserting into then_bb: reshape is possible without copying
|
||||
ctx.builder.position_at_end(then_bb);
|
||||
dst_ndarray
|
||||
.instance
|
||||
.gep(ctx, |f| f.data)
|
||||
.store(ctx, dst_ndarray.instance.gep(ctx, |f| f.data).load(tyctx, ctx, "data"));
|
||||
ctx.builder.build_unconditional_branch(end_bb).unwrap();
|
||||
|
||||
// Inserting into else_bb: reshape is impossible without copying
|
||||
ctx.builder.position_at_end(else_bb);
|
||||
dst_ndarray.alloca_owned_data(generator, ctx);
|
||||
dst_ndarray.copy_data_from(generator, ctx, *self);
|
||||
ctx.builder.build_unconditional_branch(end_bb).unwrap();
|
||||
|
||||
// Reposition for continuation
|
||||
ctx.builder.position_at_end(end_bb);
|
||||
|
||||
dst_ndarray
|
||||
}
|
||||
}
|
||||
|
||||
/// Generates LLVM IR for `np.reshape`.
|
||||
pub fn gen_ndarray_reshape<'ctx>(
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
obj: &Option<(Type, ValueEnum<'ctx>)>,
|
||||
fun: (&FunSignature, DefinitionId),
|
||||
args: &[(Option<StrRef>, ValueEnum<'ctx>)],
|
||||
generator: &mut dyn CodeGenerator,
|
||||
) -> Result<PointerValue<'ctx>, String> {
|
||||
assert!(obj.is_none());
|
||||
assert_eq!(args.len(), 2);
|
||||
|
||||
// Parse argument #1 input
|
||||
let input_ty = fun.0.args[0].ty;
|
||||
let input_arg = args[0].1.clone().to_basic_value_enum(ctx, generator, input_ty)?;
|
||||
|
||||
// Parse argument #2 shape
|
||||
let shape_ty = fun.0.args[1].ty;
|
||||
let shape_arg = args[1].1.clone().to_basic_value_enum(ctx, generator, shape_ty)?;
|
||||
|
||||
// Define models
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let sizet_model = IntModel(SizeT);
|
||||
|
||||
// Extract reshaped_ndims
|
||||
let (_, reshaped_ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, fun.0.ret);
|
||||
let reshaped_ndims_int = extract_ndims(&ctx.unifier, reshaped_ndims);
|
||||
|
||||
// Process `input`
|
||||
let ndarray =
|
||||
split_scalar_or_ndarray(tyctx, ctx, input_arg, input_ty).as_ndarray(generator, ctx);
|
||||
|
||||
// Process the shape input from user and resolve negative indices
|
||||
let new_shape = make_shape_writer(generator, ctx, shape_arg, shape_ty).alloca_array_and_write(
|
||||
generator,
|
||||
ctx,
|
||||
"new_shape",
|
||||
)?;
|
||||
let size = ndarray.size(generator, ctx);
|
||||
call_nac3_ndarray_resolve_and_check_new_shape(
|
||||
generator,
|
||||
ctx,
|
||||
size,
|
||||
sizet_model.constant(tyctx, ctx.ctx, reshaped_ndims_int),
|
||||
new_shape,
|
||||
);
|
||||
|
||||
// Reshape
|
||||
let reshaped_ndarray = ndarray.reshape_or_copy(generator, ctx, reshaped_ndims, new_shape);
|
||||
|
||||
Ok(reshaped_ndarray.instance.value)
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,43 @@
|
|||
use crate::codegen::{model::*, CodeGenContext};
|
||||
|
||||
/// Fields of [`CSlice<'ctx>`].
|
||||
pub struct CSliceFields<F: FieldVisitor> {
|
||||
/// Pointer to the data.
|
||||
pub base: F::Field<PtrModel<IntModel<Byte>>>,
|
||||
/// Number of bytes of the data.
|
||||
pub len: F::Field<IntModel<SizeT>>,
|
||||
}
|
||||
|
||||
/// See <https://crates.io/crates/cslice>.
|
||||
///
|
||||
/// Additionally, see <https://github.com/m-labs/artiq/blob/b0d2705c385f64b6e6711c1726cd9178f40b598e/artiq/firmware/libeh/eh_artiq.rs>)
|
||||
/// for ARTIQ-specific notes.
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct CSlice;
|
||||
|
||||
impl StructKind for CSlice {
|
||||
type Fields<F: FieldVisitor> = CSliceFields<F>;
|
||||
|
||||
fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields { base: visitor.add("base"), len: visitor.add("len") }
|
||||
}
|
||||
}
|
||||
|
||||
impl StructModel<CSlice> {
|
||||
/// Create a [`CSlice`].
|
||||
///
|
||||
/// `base` and `len` must be LLVM global constants.
|
||||
pub fn create_const<'ctx>(
|
||||
&self,
|
||||
type_context: TypeContext<'ctx>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
base: Ptr<'ctx, IntModel<Byte>>,
|
||||
len: Int<'ctx, SizeT>,
|
||||
) -> Struct<'ctx, CSlice> {
|
||||
let value = self
|
||||
.0
|
||||
.get_struct_type(type_context, ctx.ctx)
|
||||
.const_named_struct(&[base.value.into(), len.value.into()]);
|
||||
self.believe_value(value)
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,57 @@
|
|||
use crate::codegen::model::*;
|
||||
|
||||
use super::cslice::CSlice;
|
||||
|
||||
/// The LLVM int type of an Exception ID.
|
||||
pub type ExceptionId = Int32;
|
||||
|
||||
/// Fields of [`Exception<'ctx>`]
|
||||
///
|
||||
/// The definition came from `pub struct Exception<'a>` in
|
||||
/// <https://github.com/m-labs/artiq/blob/master/artiq/firmware/libeh/eh_artiq.rs>.
|
||||
pub struct ExceptionFields<F: FieldVisitor> {
|
||||
/// nac3core's ID of the exception
|
||||
pub id: F::Field<IntModel<ExceptionId>>,
|
||||
/// The name of the file this `Exception` was raised in.
|
||||
pub filename: F::Field<StructModel<CSlice>>,
|
||||
/// The line number in the file this `Exception` was raised in.
|
||||
pub line: F::Field<IntModel<Int32>>,
|
||||
/// The column number in the file this `Exception` was raised in.
|
||||
pub column: F::Field<IntModel<Int32>>,
|
||||
/// The name of the Python function this `Exception` was raised in.
|
||||
pub function: F::Field<StructModel<CSlice>>,
|
||||
/// The message of this Exception.
|
||||
///
|
||||
/// The message can optionally contain integer parameters `{0}`, `{1}`, and `{2}` in its string,
|
||||
/// where they will be substituted by `params[0]`, `params[1]`, and `params[2]` respectively (as `int64_t`s).
|
||||
/// Here is an example:
|
||||
///
|
||||
/// ```ignore
|
||||
/// "Index {0} is out of bounds! List only has {1} element(s)."
|
||||
/// ```
|
||||
///
|
||||
/// In this case, `params[0]` and `params[1]` must be specified, and `params[2]` is ***unused***.
|
||||
/// Having only 3 parameters is a constraint in ARTIQ.
|
||||
pub msg: F::Field<StructModel<CSlice>>,
|
||||
pub params: [F::Field<IntModel<Int64>>; 3],
|
||||
}
|
||||
|
||||
/// nac3core & ARTIQ's Exception
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Exception;
|
||||
|
||||
impl StructKind for Exception {
|
||||
type Fields<F: FieldVisitor> = ExceptionFields<F>;
|
||||
|
||||
fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields {
|
||||
id: visitor.add("id"),
|
||||
filename: visitor.add("filename"),
|
||||
line: visitor.add("line"),
|
||||
column: visitor.add("column"),
|
||||
function: visitor.add("function"),
|
||||
msg: visitor.add("msg"),
|
||||
params: [visitor.add("params[0]"), visitor.add("params[1]"), visitor.add("params[2]")],
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
pub mod cslice;
|
||||
pub mod exception;
|
||||
pub mod ndarray;
|
||||
|
|
@ -0,0 +1,27 @@
|
|||
use crate::codegen::*;
|
||||
|
||||
pub struct NpArrayFields<F: FieldVisitor> {
|
||||
pub data: F::Field<PtrModel<IntModel<Byte>>>,
|
||||
pub itemsize: F::Field<IntModel<SizeT>>,
|
||||
pub ndims: F::Field<IntModel<SizeT>>,
|
||||
pub shape: F::Field<PtrModel<IntModel<SizeT>>>,
|
||||
pub strides: F::Field<PtrModel<IntModel<SizeT>>>,
|
||||
}
|
||||
|
||||
// TODO: Rename to `NDArray` when the old NDArray is removed.
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct NpArray;
|
||||
|
||||
impl StructKind for NpArray {
|
||||
type Fields<F: FieldVisitor> = NpArrayFields<F>;
|
||||
|
||||
fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields {
|
||||
data: visitor.add("data"),
|
||||
itemsize: visitor.add("itemsize"),
|
||||
ndims: visitor.add("ndims"),
|
||||
shape: visitor.add("shape"),
|
||||
strides: visitor.add("strides"),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -94,7 +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());
|
||||
|
|
@ -109,18 +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(),
|
||||
|
|
@ -258,19 +248,14 @@ 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(),
|
||||
};
|
||||
|
|
|
|||
|
|
@ -0,0 +1,34 @@
|
|||
use crate::codegen::{model::*, CodeGenContext, CodeGenerator};
|
||||
|
||||
/// A closure containing details on how to write to/initialize an array.
|
||||
#[allow(clippy::type_complexity)]
|
||||
pub struct ArrayWriter<'ctx, G: CodeGenerator + ?Sized, Len: IntKind, Item: Model> {
|
||||
/// Number of items to write
|
||||
pub len: Int<'ctx, Len>,
|
||||
/// Implementation to write to an array given its base pointer.
|
||||
pub write: Box<
|
||||
dyn Fn(
|
||||
&mut G,
|
||||
&mut CodeGenContext<'ctx, '_>,
|
||||
Ptr<'ctx, Item>, // Base pointer
|
||||
) -> Result<(), String>
|
||||
+ 'ctx,
|
||||
>,
|
||||
}
|
||||
|
||||
impl<'ctx, G: CodeGenerator + ?Sized, Len: IntKind, Item: Model> ArrayWriter<'ctx, G, Len, Item> {
|
||||
pub fn alloca_array_and_write(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
name: &str,
|
||||
) -> Result<Ptr<'ctx, Item>, String> {
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
|
||||
let item_model = Item::default();
|
||||
|
||||
let item_array = item_model.array_alloca(tyctx, ctx, self.len.value, name);
|
||||
(self.write)(generator, ctx, item_array)?;
|
||||
Ok(item_array)
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,42 @@
|
|||
use crate::codegen::{
|
||||
model::*,
|
||||
stmt::{gen_for_callback_incrementing, BreakContinueHooks},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
// TODO: Document
|
||||
// TODO: Rename function
|
||||
/// Only allows positive steps
|
||||
pub fn gen_model_for<'ctx, 'a, G, F, I>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, 'a>,
|
||||
start: Int<'ctx, I>,
|
||||
stop: Int<'ctx, I>,
|
||||
step: Int<'ctx, I>,
|
||||
body: F,
|
||||
) -> Result<(), String>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
F: FnOnce(
|
||||
&mut G,
|
||||
&mut CodeGenContext<'ctx, 'a>,
|
||||
BreakContinueHooks<'ctx>,
|
||||
Int<'ctx, I>,
|
||||
) -> Result<(), String>,
|
||||
I: IntKind,
|
||||
{
|
||||
let int_model = IntModel(I::default());
|
||||
|
||||
gen_for_callback_incrementing(
|
||||
generator,
|
||||
ctx,
|
||||
None,
|
||||
start.value,
|
||||
(stop.value, false),
|
||||
|g, ctx, hooks, i| {
|
||||
let i = int_model.believe_value(i);
|
||||
body(g, ctx, hooks, i)
|
||||
},
|
||||
step.value,
|
||||
)
|
||||
}
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
pub mod array_writer;
|
||||
pub mod control;
|
||||
pub mod shape;
|
||||
|
|
@ -0,0 +1,127 @@
|
|||
use inkwell::values::BasicValueEnum;
|
||||
|
||||
use crate::{
|
||||
codegen::{
|
||||
classes::{ListValue, UntypedArrayLikeAccessor},
|
||||
model::*,
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
typecheck::typedef::{Type, TypeEnum},
|
||||
};
|
||||
|
||||
use super::{array_writer::ArrayWriter, control::gen_model_for};
|
||||
|
||||
// TODO: Generalize to complex iterables under a common interface
|
||||
/// Create an [`ArrayWriter`] from a NumPy-like `shape` argument input.
|
||||
/// * `shape` - The `shape` parameter.
|
||||
/// * `shape_ty` - The element type of the `NDArray`.
|
||||
///
|
||||
/// The `shape` argument type may only be one of the following:
|
||||
/// 1. A list of `int32`; e.g., `np.empty([600, 800, 3])`
|
||||
/// 2. A tuple of `int32`; e.g., `np.empty((600, 800, 3))`
|
||||
/// 3. A scalar `int32`; e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
|
||||
///
|
||||
/// The `int32` values will be sign-extended to `SizeT`
|
||||
pub fn make_shape_writer<'ctx, G>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
shape: BasicValueEnum<'ctx>,
|
||||
shape_ty: Type,
|
||||
) -> ArrayWriter<'ctx, G, SizeT, IntModel<SizeT>>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
{
|
||||
let tyctx = generator.type_context(ctx.ctx);
|
||||
let sizet_model = IntModel(SizeT);
|
||||
|
||||
match &*ctx.unifier.get_ty(shape_ty) {
|
||||
TypeEnum::TObj { obj_id, .. }
|
||||
if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
|
||||
{
|
||||
// 1. A list of `int32`; e.g., `np.empty([600, 800, 3])`
|
||||
|
||||
// TODO: Remove ListValue with Model
|
||||
|
||||
let shape = ListValue::from_ptr_val(shape.into_pointer_value(), tyctx.size_type, None);
|
||||
let len =
|
||||
sizet_model.check_value(tyctx, ctx.ctx, shape.load_size(ctx, Some("len"))).unwrap();
|
||||
|
||||
ArrayWriter {
|
||||
len,
|
||||
write: Box::new(move |generator, ctx, dst_array| {
|
||||
gen_model_for(
|
||||
generator,
|
||||
ctx,
|
||||
sizet_model.constant(tyctx, ctx.ctx, 0),
|
||||
len,
|
||||
sizet_model.constant(tyctx, ctx.ctx, 1),
|
||||
|generator, ctx, _hooks, i| {
|
||||
let dim =
|
||||
shape.data().get(ctx, generator, &i.value, None).into_int_value();
|
||||
let dim = sizet_model.s_extend_or_bit_cast(tyctx, ctx, dim, "");
|
||||
|
||||
dst_array.offset(tyctx, ctx, i.value, "pdim").store(ctx, dim);
|
||||
Ok(())
|
||||
},
|
||||
)
|
||||
}),
|
||||
}
|
||||
}
|
||||
TypeEnum::TTuple { ty: tuple_types } => {
|
||||
// 2. A tuple of ints; e.g., `np.empty((600, 800, 3))`
|
||||
|
||||
let ndims = tuple_types.len();
|
||||
|
||||
// A tuple has to be a StructValue
|
||||
// Read [`codegen::expr::gen_expr`] to see how `nac3core` translates a Python tuple into LLVM.
|
||||
let shape = shape.into_struct_value();
|
||||
|
||||
ArrayWriter {
|
||||
len: sizet_model.constant(tyctx, ctx.ctx, ndims as u64),
|
||||
write: Box::new(move |_generator, ctx, dst_array| {
|
||||
for axis in 0..ndims {
|
||||
let dim = ctx
|
||||
.builder
|
||||
.build_extract_value(shape, axis as u32, format!("dim{axis}").as_str())
|
||||
.unwrap()
|
||||
.into_int_value();
|
||||
let dim = sizet_model.s_extend_or_bit_cast(tyctx, ctx, dim, "");
|
||||
|
||||
dst_array
|
||||
.offset(
|
||||
tyctx,
|
||||
ctx,
|
||||
sizet_model.constant(tyctx, ctx.ctx, axis as u64).value,
|
||||
"pdim",
|
||||
)
|
||||
.store(ctx, dim);
|
||||
}
|
||||
Ok(())
|
||||
}),
|
||||
}
|
||||
}
|
||||
TypeEnum::TObj { obj_id, .. }
|
||||
if *obj_id == ctx.primitives.int32.obj_id(&ctx.unifier).unwrap() =>
|
||||
{
|
||||
// 3. A scalar int; e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
|
||||
|
||||
// The value has to be an integer
|
||||
let shape_int = shape.into_int_value();
|
||||
|
||||
ArrayWriter {
|
||||
len: sizet_model.constant(tyctx, ctx.ctx, 1),
|
||||
write: Box::new(move |_generator, ctx, dst_array| {
|
||||
let dim = sizet_model.s_extend_or_bit_cast(tyctx, ctx, shape_int, "");
|
||||
|
||||
// Set shape[0] = shape_int
|
||||
dst_array
|
||||
.offset(tyctx, ctx, sizet_model.constant(tyctx, ctx.ctx, 0).value, "pdim")
|
||||
.store(ctx, dim);
|
||||
|
||||
Ok(())
|
||||
}),
|
||||
}
|
||||
}
|
||||
_ => panic!("encountered shape type"),
|
||||
}
|
||||
}
|
||||
|
|
@ -19,10 +19,6 @@
|
|||
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;
|
||||
|
|
|
|||
|
|
@ -78,14 +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()
|
||||
|
|
@ -155,7 +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,
|
||||
}
|
||||
|
|
@ -482,7 +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()]))
|
||||
}
|
||||
|
|
|
|||
|
|
@ -9,14 +9,20 @@ use inkwell::{
|
|||
IntPredicate,
|
||||
};
|
||||
use itertools::Either;
|
||||
use ndarray::basic::call_nac3_ndarray_len;
|
||||
use strum::IntoEnumIterator;
|
||||
|
||||
use crate::{
|
||||
codegen::{
|
||||
builtin_fns,
|
||||
classes::{ProxyValue, RangeValue},
|
||||
expr::destructure_range,
|
||||
irrt::*,
|
||||
model::*,
|
||||
numpy::*,
|
||||
numpy_new,
|
||||
stmt::exn_constructor,
|
||||
structure::ndarray::NpArray,
|
||||
},
|
||||
symbol_resolver::SymbolValue,
|
||||
toplevel::{helper::PrimDef, numpy::make_ndarray_ty},
|
||||
|
|
@ -43,26 +49,10 @@ 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),
|
||||
|
|
@ -112,7 +102,7 @@ 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,
|
||||
|
|
@ -128,12 +118,7 @@ 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(),
|
||||
|
|
@ -152,7 +137,7 @@ 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,
|
||||
|
|
@ -214,10 +199,10 @@ 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,
|
||||
|
|
@ -511,6 +496,8 @@ impl<'a> BuiltinBuilder<'a> {
|
|||
| PrimDef::FunNpEye
|
||||
| PrimDef::FunNpIdentity => self.build_ndarray_other_factory_function(prim),
|
||||
|
||||
PrimDef::FunNpReshape => self.build_ndarray_view_functions(prim),
|
||||
|
||||
PrimDef::FunStr => self.build_str_function(),
|
||||
|
||||
PrimDef::FunFloor | PrimDef::FunFloor64 | PrimDef::FunCeil | PrimDef::FunCeil64 => {
|
||||
|
|
@ -575,22 +562,6 @@ 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) {
|
||||
|
|
@ -648,24 +619,17 @@ 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,
|
||||
|
|
@ -921,7 +885,6 @@ 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]),
|
||||
|
|
@ -1056,7 +1019,6 @@ 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(),
|
||||
|
|
@ -1246,9 +1208,11 @@ impl<'a> BuiltinBuilder<'a> {
|
|||
&[(self.ndarray_factory_fn_shape_arg_tvar.ty, "shape")],
|
||||
Box::new(move |ctx, obj, fun, args, generator| {
|
||||
let func = match prim {
|
||||
PrimDef::FunNpNDArray | PrimDef::FunNpEmpty => gen_ndarray_empty,
|
||||
PrimDef::FunNpZeros => gen_ndarray_zeros,
|
||||
PrimDef::FunNpOnes => gen_ndarray_ones,
|
||||
PrimDef::FunNpNDArray | PrimDef::FunNpEmpty => {
|
||||
numpy_new::factory::gen_ndarray_empty
|
||||
}
|
||||
PrimDef::FunNpZeros => numpy_new::factory::gen_ndarray_zeros,
|
||||
PrimDef::FunNpOnes => numpy_new::factory::gen_ndarray_ones,
|
||||
_ => unreachable!(),
|
||||
};
|
||||
func(ctx, &obj, fun, &args, generator).map(|val| Some(val.as_basic_value_enum()))
|
||||
|
|
@ -1276,23 +1240,16 @@ 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,
|
||||
|
|
@ -1323,7 +1280,7 @@ 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)
|
||||
numpy_new::factory::gen_ndarray_full(ctx, &obj, fun, &args, generator)
|
||||
.map(|val| Some(val.as_basic_value_enum()))
|
||||
}),
|
||||
)
|
||||
|
|
@ -1334,24 +1291,17 @@ 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,
|
||||
|
|
@ -1385,6 +1335,41 @@ impl<'a> BuiltinBuilder<'a> {
|
|||
}
|
||||
}
|
||||
|
||||
// Build functions related to NDArray views
|
||||
fn build_ndarray_view_functions(&mut self, prim: PrimDef) -> TopLevelDef {
|
||||
debug_assert_prim_is_allowed(prim, &[PrimDef::FunNpReshape]);
|
||||
|
||||
match prim {
|
||||
PrimDef::FunNpReshape => {
|
||||
// TODO: Support scalar inputs, e.g., `np.reshape(99, (1, 1, 1, 1))`
|
||||
|
||||
let new_ndim_ty = self.unifier.get_fresh_var(Some("NewNDim".into()), None);
|
||||
let returned_ndarray_ty = make_ndarray_ty(
|
||||
self.unifier,
|
||||
self.primitives,
|
||||
Some(self.ndarray_dtype_tvar.ty),
|
||||
Some(new_ndim_ty.ty),
|
||||
);
|
||||
|
||||
create_fn_by_codegen(
|
||||
self.unifier,
|
||||
&into_var_map([self.ndarray_dtype_tvar, self.ndarray_ndims_tvar, new_ndim_ty]),
|
||||
prim.name(),
|
||||
returned_ndarray_ty,
|
||||
&[
|
||||
(self.primitives.ndarray, "array"),
|
||||
(self.ndarray_factory_fn_shape_arg_tvar.ty, "shape"),
|
||||
],
|
||||
Box::new(|ctx, obj, fun, args, generator| {
|
||||
numpy_new::view::gen_ndarray_reshape(ctx, &obj, fun, &args, generator)
|
||||
.map(|val| Some(val.as_basic_value_enum()))
|
||||
}),
|
||||
)
|
||||
}
|
||||
_ => unreachable!(),
|
||||
}
|
||||
}
|
||||
|
||||
/// Build the `str()` function.
|
||||
fn build_str_function(&mut self) -> TopLevelDef {
|
||||
let prim = PrimDef::FunStr;
|
||||
|
|
@ -1395,12 +1380,7 @@ 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(),
|
||||
})),
|
||||
|
|
@ -1464,21 +1444,31 @@ 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(),
|
||||
|
|
@ -1486,10 +1476,48 @@ 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 tyctx = generator.type_context(ctx.ctx);
|
||||
let pndarray_model = PtrModel(StructModel(NpArray));
|
||||
|
||||
builtin_fns::call_len(generator, ctx, (arg_ty, arg)).map(|ret| Some(ret.into()))
|
||||
let ndarray =
|
||||
pndarray_model.check_value(tyctx, ctx.ctx, arg).unwrap();
|
||||
let len = call_nac3_ndarray_len(generator, ctx, ndarray);
|
||||
Some(len.value.as_basic_value_enum())
|
||||
}
|
||||
_ => unreachable!(),
|
||||
}
|
||||
})
|
||||
},
|
||||
)))),
|
||||
loc: None,
|
||||
|
|
@ -1505,18 +1533,8 @@ 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(),
|
||||
|
|
@ -1598,12 +1616,7 @@ 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]),
|
||||
|
|
@ -1644,7 +1657,6 @@ 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(),
|
||||
|
|
@ -1833,12 +1845,7 @@ 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]),
|
||||
|
|
@ -1872,207 +1879,6 @@ 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())
|
||||
}
|
||||
|
|
|
|||
|
|
@ -23,7 +23,7 @@ impl Default for ComposerConfig {
|
|||
}
|
||||
}
|
||||
|
||||
pub type DefAst = (Arc<RwLock<TopLevelDef>>, Option<Stmt<()>>);
|
||||
type DefAst = (Arc<RwLock<TopLevelDef>>, Option<Stmt<()>>);
|
||||
pub struct TopLevelComposer {
|
||||
// list of top level definitions, same as top level context
|
||||
pub definition_ast_list: Vec<DefAst>,
|
||||
|
|
@ -44,27 +44,12 @@ pub struct TopLevelComposer {
|
|||
pub size_t: u32,
|
||||
}
|
||||
|
||||
/// The specification for a builtin function, consisting of the function name, the function
|
||||
/// signature, and a [code generation callback][`GenCall`].
|
||||
pub type BuiltinFuncSpec = (StrRef, FunSignature, Arc<GenCall>);
|
||||
|
||||
/// A function that creates a [`BuiltinFuncSpec`] using the provided [`PrimitiveStore`] and
|
||||
/// [`Unifier`].
|
||||
pub type BuiltinFuncCreator = dyn Fn(&PrimitiveStore, &mut Unifier) -> BuiltinFuncSpec;
|
||||
|
||||
impl TopLevelComposer {
|
||||
/// return a composer and things to make a "primitive" symbol resolver, so that the symbol
|
||||
/// resolver can later figure out primitive tye definitions when passed a primitive type name
|
||||
///
|
||||
/// `lateinit_builtins` are specifically for the ARTIQ module. Since the [`Unifier`] instance
|
||||
/// used to create builtin functions do not persist until method compilation, any types
|
||||
/// created (e.g. [`TypeEnum::TVar`]) also do not persist. Those functions should be instead put
|
||||
/// in `lateinit_builtins`, where they will be instantiated with the [`Unifier`] instance used
|
||||
/// for method compilation.
|
||||
/// resolver can later figure out primitive type definitions when passed a primitive type name
|
||||
#[must_use]
|
||||
pub fn new(
|
||||
builtins: Vec<BuiltinFuncSpec>,
|
||||
lateinit_builtins: Vec<Box<BuiltinFuncCreator>>,
|
||||
builtins: Vec<(StrRef, FunSignature, Arc<GenCall>)>,
|
||||
core_config: ComposerConfig,
|
||||
size_t: u32,
|
||||
) -> (Self, HashMap<StrRef, DefinitionId>, HashMap<StrRef, Type>) {
|
||||
|
|
@ -134,13 +119,7 @@ impl TopLevelComposer {
|
|||
}
|
||||
}
|
||||
|
||||
// Materialize lateinit_builtins, now that the unifier is ready
|
||||
let lateinit_builtins = lateinit_builtins
|
||||
.into_iter()
|
||||
.map(|builtin| builtin(&primitives_ty, &mut unifier))
|
||||
.collect_vec();
|
||||
|
||||
for (name, sig, codegen_callback) in builtins.into_iter().chain(lateinit_builtins) {
|
||||
for (name, sig, codegen_callback) in builtins {
|
||||
let fun_sig = unifier.add_ty(TypeEnum::TFunc(sig));
|
||||
builtin_ty.insert(name, fun_sig);
|
||||
builtin_id.insert(name, DefinitionId(definition_ast_list.len()));
|
||||
|
|
@ -881,73 +860,7 @@ impl TopLevelComposer {
|
|||
let resolver = &**resolver;
|
||||
|
||||
let mut function_var_map = VarMap::new();
|
||||
|
||||
let vararg = args
|
||||
.vararg
|
||||
.as_ref()
|
||||
.map(|vararg| -> Result<_, HashSet<String>> {
|
||||
let vararg = vararg.as_ref();
|
||||
|
||||
let annotation = vararg
|
||||
.node
|
||||
.annotation
|
||||
.as_ref()
|
||||
.ok_or_else(|| {
|
||||
HashSet::from([format!(
|
||||
"function parameter `{}` needs type annotation at {}",
|
||||
vararg.node.arg, vararg.location
|
||||
)])
|
||||
})?
|
||||
.as_ref();
|
||||
|
||||
let type_annotation = parse_ast_to_type_annotation_kinds(
|
||||
resolver,
|
||||
temp_def_list.as_slice(),
|
||||
unifier,
|
||||
primitives_store,
|
||||
annotation,
|
||||
// NOTE: since only class need this, for function
|
||||
// it should be fine to be empty map
|
||||
HashMap::new(),
|
||||
)?;
|
||||
|
||||
let type_vars_within =
|
||||
get_type_var_contained_in_type_annotation(&type_annotation)
|
||||
.into_iter()
|
||||
.map(|x| -> Result<TypeVar, HashSet<String>> {
|
||||
let TypeAnnotation::TypeVar(ty) = x else {
|
||||
unreachable!("must be type var annotation kind")
|
||||
};
|
||||
|
||||
let id = Self::get_var_id(ty, unifier)?;
|
||||
Ok(TypeVar { id, ty })
|
||||
})
|
||||
.collect::<Result<Vec<_>, _>>()?;
|
||||
for var in type_vars_within {
|
||||
if let Some(prev_ty) = function_var_map.insert(var.id, var.ty) {
|
||||
// if already have the type inserted, make sure they are the same thing
|
||||
assert_eq!(prev_ty, var.ty);
|
||||
}
|
||||
}
|
||||
|
||||
let ty = get_type_from_type_annotation_kinds(
|
||||
temp_def_list.as_ref(),
|
||||
unifier,
|
||||
primitives_store,
|
||||
&type_annotation,
|
||||
&mut None,
|
||||
)?;
|
||||
|
||||
Ok(FuncArg {
|
||||
name: vararg.node.arg,
|
||||
ty,
|
||||
default_value: Some(SymbolValue::Tuple(Vec::default())),
|
||||
is_vararg: true,
|
||||
})
|
||||
})
|
||||
.transpose()?;
|
||||
|
||||
let mut arg_types = {
|
||||
let arg_types = {
|
||||
// make sure no duplicate parameter
|
||||
let mut defined_parameter_name: HashSet<_> = HashSet::new();
|
||||
for x in &args.args {
|
||||
|
|
@ -1048,18 +961,11 @@ impl TopLevelComposer {
|
|||
v
|
||||
}),
|
||||
},
|
||||
is_vararg: false,
|
||||
})
|
||||
})
|
||||
.collect::<Result<Vec<_>, _>>()?
|
||||
};
|
||||
|
||||
if let Some(vararg) = vararg {
|
||||
arg_types.push(vararg);
|
||||
};
|
||||
|
||||
let arg_types = arg_types;
|
||||
|
||||
let return_ty = {
|
||||
if let Some(returns) = returns {
|
||||
let return_ty_annotation = {
|
||||
|
|
@ -1311,7 +1217,6 @@ impl TopLevelComposer {
|
|||
})
|
||||
}
|
||||
},
|
||||
is_vararg: false,
|
||||
};
|
||||
// push the dummy type and the type annotation
|
||||
// into the list for later unification
|
||||
|
|
@ -1737,25 +1642,21 @@ impl TopLevelComposer {
|
|||
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,
|
||||
},
|
||||
],
|
||||
ret: self_type,
|
||||
|
|
@ -1822,12 +1723,7 @@ impl TopLevelComposer {
|
|||
if *name != init_str_id {
|
||||
unreachable!("must be init function here")
|
||||
}
|
||||
|
||||
let all_inited = Self::get_all_assigned_field(
|
||||
object_id.0,
|
||||
definition_ast_list,
|
||||
body.as_slice(),
|
||||
)?;
|
||||
let all_inited = Self::get_all_assigned_field(body.as_slice())?;
|
||||
for (f, _, _) in fields {
|
||||
if !all_inited.contains(f) {
|
||||
return Err(HashSet::from([
|
||||
|
|
@ -1894,8 +1790,7 @@ impl TopLevelComposer {
|
|||
} = &mut *function_def
|
||||
{
|
||||
let signature_ty_enum = unifier.get_ty(*signature);
|
||||
let TypeEnum::TFunc(FunSignature { args, ret, vars, .. }) =
|
||||
signature_ty_enum.as_ref()
|
||||
let TypeEnum::TFunc(FunSignature { args, ret, vars }) = signature_ty_enum.as_ref()
|
||||
else {
|
||||
unreachable!("must be typeenum::tfunc")
|
||||
};
|
||||
|
|
@ -1971,7 +1866,6 @@ impl TopLevelComposer {
|
|||
name: a.name,
|
||||
ty: unifier.subst(a.ty, &subst).unwrap_or(a.ty),
|
||||
default_value: a.default_value.clone(),
|
||||
is_vararg: false,
|
||||
})
|
||||
.collect_vec()
|
||||
};
|
||||
|
|
@ -2058,16 +1952,6 @@ impl TopLevelComposer {
|
|||
instance_to_symbol.insert(String::new(), simple_name.to_string());
|
||||
continue;
|
||||
}
|
||||
if !decorator_list.is_empty() {
|
||||
if let ast::ExprKind::Call { func, .. } = &decorator_list[0].node {
|
||||
if matches!(&func.node,
|
||||
ast::ExprKind::Name{ id, .. } if id == &"rpc".into())
|
||||
{
|
||||
instance_to_symbol.insert(String::new(), simple_name.to_string());
|
||||
continue;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
let fun_body = body
|
||||
.into_iter()
|
||||
|
|
|
|||
|
|
@ -3,7 +3,6 @@ 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 ast::ExprKind;
|
||||
use nac3parser::ast::{Constant, Location};
|
||||
use strum::IntoEnumIterator;
|
||||
use strum_macros::EnumIter;
|
||||
|
|
@ -53,6 +52,9 @@ pub enum PrimDef {
|
|||
FunNpEye,
|
||||
FunNpIdentity,
|
||||
|
||||
// NumPy view functions
|
||||
FunNpReshape,
|
||||
|
||||
// Miscellaneous NumPy & SciPy functions
|
||||
FunNpRound,
|
||||
FunNpFloor,
|
||||
|
|
@ -100,21 +102,6 @@ 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,
|
||||
|
|
@ -239,6 +226,9 @@ impl PrimDef {
|
|||
PrimDef::FunNpEye => fun("np_eye", None),
|
||||
PrimDef::FunNpIdentity => fun("np_identity", None),
|
||||
|
||||
// NumPy view functions
|
||||
PrimDef::FunNpReshape => fun("np_reshape", None),
|
||||
|
||||
// Miscellaneous NumPy & SciPy functions
|
||||
PrimDef::FunNpRound => fun("np_round", None),
|
||||
PrimDef::FunNpFloor => fun("np_floor", None),
|
||||
|
|
@ -286,21 +276,6 @@ 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),
|
||||
|
|
@ -506,7 +481,6 @@ 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]),
|
||||
|
|
@ -734,16 +708,7 @@ 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 {
|
||||
|
|
@ -779,138 +744,30 @@ 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!()
|
||||
|
|
|
|||
|
|
@ -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>,
|
||||
|
|
|
|||
|
|
@ -10,9 +10,9 @@ 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,
|
||||
|
|
@ -25,9 +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,
|
||||
|
|
|
|||
|
|
@ -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(248)]\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",
|
||||
|
|
|
|||
|
|
@ -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[typevar237]\", \"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: [\"typevar237\"]\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",
|
||||
|
|
|
|||
|
|
@ -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(250)]\n}\n",
|
||||
"Function {\nname: \"A.fun\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(255)]\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",
|
||||
|
|
|
|||
|
|
@ -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[typevar236, typevar237]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[a:A[float, bool], b:B], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\")],\ntype_vars: [\"typevar236\", \"typevar237\"]\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",
|
||||
|
|
|
|||
|
|
@ -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(256)]\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(264)]\n}\n",
|
||||
]
|
||||
|
|
|
|||
|
|
@ -117,8 +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();
|
||||
|
|
@ -138,8 +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();
|
||||
|
|
@ -173,8 +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(),
|
||||
|
|
@ -522,8 +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![
|
||||
|
|
@ -700,8 +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![
|
||||
|
|
|
|||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue