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26 Commits
master ... ndstrides-

Author SHA1 Message Date
lyken
991103c6f0 WIP: core: remove outdated comment 2024-07-17 09:57:15 +08:00
lyken
d3a5c5a48a core: document codegen/model (incomplete) 2024-07-16 13:05:16 +08:00
lyken
496171a4a5 WIP: stuck on #460 2024-07-16 12:28:08 +08:00
lyken
d90604b713 WIP 2024-07-16 00:27:50 +08:00
lyken
0946bd86ea core: irrt proper ndarray subscript & more 
Details:
- improve irrt model
- len() on ndarrays
 2024-07-15 21:05:01 +08:00
lyken
29734ce3af core: irrt fix minor formatting 2024-07-15 12:05:47 +08:00
lyken
b940b0a3a1 core: irrt refactor print & add print_ndarray 2024-07-15 12:05:17 +08:00
lyken
b12d7fcb2d core: irrt improve test_ndarray_subscript 
- rewrote some comments
- add test_ndsubscript_index_subscript_out_of_bounds
 2024-07-15 11:54:32 +08:00
lyken
628965e519 core: irrt reformat & more progress 
progress details:
- organize test suite sources with namespaces
- organize ndarray implementations with namespaces
- remove extraneous code/comment
- add more tests
- some renaming
- fix pre-existing bugs
- ndarray::subscript now throw errors
 2024-07-15 11:50:45 +08:00
lyken
61dd9762d8 core: irrt add unchecked ndarray broadcasting 2024-07-15 00:49:07 +08:00
lyken
cc8103152f core: irrt add unchecked ndarray slicing 2024-07-15 00:48:14 +08:00
lyken
b8c0d5836f core: replace NDArray type in get_llvm_type() 2024-07-15 00:01:02 +08:00
lyken
0cc7e41c6f core: fix new irrt ndarray issues 2024-07-15 00:00:41 +08:00
lyken
d92cccb85e core: irrt split ndarray.hpp 2024-07-14 23:35:50 +08:00
lyken
3344a2bcd3 core: new np_{zeros,ones,fill} + some irrt model additions 2024-07-14 23:16:28 +08:00
lyken
51a099b602 core: irrt error context mechanism 2024-07-14 22:34:23 +08:00
lyken
1f2bb80812 core: lift SizeVariant to /util.rs 2024-07-14 22:34:23 +08:00
lyken
709844b855 core: inkwell model abstraction 2024-07-14 22:34:21 +08:00
lyken
73937730e0 core: -I irrt/ & #include absolute paths 2024-07-14 17:09:48 +08:00
lyken
5faac4b9d4 core: build.rs to capture IR global constants 2024-07-13 23:37:26 +08:00
lyken
c4d54b198b core: add llvm.lifetime.{start.end} 2024-07-13 23:37:26 +08:00
lyken
9ad7a78dbe core: build.rs rewrite regex to capture = type 2024-07-13 23:37:26 +08:00
lyken
1721ebac66 core: introduce irrt_test 2024-07-13 23:37:24 +08:00
lyken
f033639415 core: split irrt.cpp into headers 2024-07-12 21:53:15 +08:00
lyken
3116f11814 core: comment build.rs & move irrt to its own dir 2024-07-12 21:52:55 +08:00
lyken
5047379ac0 core: irrt build with -W=return-type 2024-07-12 21:19:38 +08:00
108 changed files with 6006 additions and 7450 deletions
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32
.clang-format
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1
.gitignore vendored
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@ -1,4 +1,3 @@
__pycache__
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/nac3standalone/demo/linalg/target
nix/windows/msys2

200
Cargo.lock generated
View File

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name = "serde"
version = "1.0.209"
version = "1.0.204"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "99fce0ffe7310761ca6bf9faf5115afbc19688edd00171d81b1bb1b116c63e09"
checksum = "bc76f558e0cbb2a839d37354c575f1dc3fdc6546b5be373ba43d95f231bf7c12"
dependencies = [
"serde_derive",
]
[[package]]
name = "serde_derive"
version = "1.0.209"
version = "1.0.204"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "a5831b979fd7b5439637af1752d535ff49f4860c0f341d1baeb6faf0f4242170"
checksum = "e0cd7e117be63d3c3678776753929474f3b04a43a080c744d6b0ae2a8c28e222"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.76",
"syn 2.0.70",
]
[[package]]
name = "serde_json"
version = "1.0.127"
version = "1.0.120"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "8043c06d9f82bd7271361ed64f415fe5e12a77fdb52e573e7f06a516dea329ad"
checksum = "4e0d21c9a8cae1235ad58a00c11cb40d4b1e5c784f1ef2c537876ed6ffd8b7c5"
dependencies = [
"itoa",
"memchr",
"ryu",
"serde",
]
@ -1077,17 +1070,11 @@ dependencies = [
"yaml-rust",
]
[[package]]
name = "shlex"
version = "1.3.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0fda2ff0d084019ba4d7c6f371c95d8fd75ce3524c3cb8fb653a3023f6323e64"
[[package]]
name = "similar"
version = "2.6.0"
version = "2.5.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "1de1d4f81173b03af4c0cbed3c898f6bff5b870e4a7f5d6f4057d62a7a4b686e"
checksum = "fa42c91313f1d05da9b26f267f931cf178d4aba455b4c4622dd7355eb80c6640"
[[package]]
name = "siphasher"
@ -1147,7 +1134,7 @@ dependencies = [
"proc-macro2",
"quote",
"rustversion",
"syn 2.0.76",
"syn 2.0.70",
]
[[package]]
@ -1163,9 +1150,9 @@ dependencies = [
[[package]]
name = "syn"
version = "2.0.76"
version = "2.0.70"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "578e081a14e0cefc3279b0472138c513f37b41a08d5a3cca9b6e4e8ceb6cd525"
checksum = "2f0209b68b3613b093e0ec905354eccaedcfe83b8cb37cbdeae64026c3064c16"
dependencies = [
"proc-macro2",
"quote",
@ -1174,21 +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]]
@ -1217,22 +1203,22 @@ dependencies = [
[[package]]
name = "thiserror"
version = "1.0.63"
version = "1.0.61"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "c0342370b38b6a11b6cc11d6a805569958d54cfa061a29969c3b5ce2ea405724"
checksum = "c546c80d6be4bc6a00c0f01730c08df82eaa7a7a61f11d656526506112cc1709"
dependencies = [
"thiserror-impl",
]
[[package]]
name = "thiserror-impl"
version = "1.0.63"
version = "1.0.61"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "a4558b58466b9ad7ca0f102865eccc95938dca1a74a856f2b57b6629050da261"
checksum = "46c3384250002a6d5af4d114f2845d37b57521033f30d5c3f46c4d70e1197533"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.76",
"syn 2.0.70",
]
[[package]]
@ -1310,9 +1296,9 @@ 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"
@ -1350,9 +1336,9 @@ checksum = "06abde3611657adf66d383f00b093d7faecc7fa57071cce2578660c9f1010821"
[[package]]
name = "version_check"
version = "0.9.5"
version = "0.9.4"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0b928f33d975fc6ad9f86c8f283853ad26bdd5b10b7f1542aa2fa15e2289105a"
checksum = "49874b5167b65d7193b8aba1567f5c7d93d001cafc34600cee003eda787e483f"
[[package]]
name = "walkdir"
@ -1388,11 +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]]
@ -1410,15 +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"
@ -1498,7 +1475,6 @@ version = "0.7.35"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "1b9b4fd18abc82b8136838da5d50bae7bdea537c574d8dc1a34ed098d6c166f0"
dependencies = [
"byteorder",
"zerocopy-derive",
]
@ -1510,5 +1486,5 @@ checksum = "fa4f8080344d4671fb4e831a13ad1e68092748387dfc4f55e356242fae12ce3e"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.76",
"syn 2.0.70",
]

6
flake.lock generated
View File

@ -2,11 +2,11 @@
"nodes": {
"nixpkgs": {
"locked": {
"lastModified": 1724819573,
"narHash": "sha256-GnR7/ibgIH1vhoy8cYdmXE6iyZqKqFxQSVkFgosBh6w=",
"lastModified": 1720418205,
"narHash": "sha256-cPJoFPXU44GlhWg4pUk9oUPqurPlCFZ11ZQPk21GTPU=",
"owner": "NixOS",
"repo": "nixpkgs",
"rev": "71e91c409d1e654808b2621f28a327acfdad8dc2",
"rev": "655a58a72a6601292512670343087c2d75d859c1",
"type": "github"
},
"original": {

35
flake.nix
View File

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

1
nac3artiq/Cargo.toml
View File

@ -24,4 +24,3 @@ features = ["llvm14-0", "target-x86", "target-arm", "target-riscv", "no-libffi-l
[features]
init-llvm-profile = []
no-escape-analysis = ["nac3core/no-escape-analysis"]

24
nac3artiq/demo/list_cmp.py
View File

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

26
nac3artiq/demo/str_abi.py
View File

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

964
nac3artiq/src/codegen.rs
View File

File diff suppressed because it is too large Load Diff

98
nac3artiq/src/lib.rs
View File

@ -24,7 +24,6 @@ use std::rc::Rc;
use std::sync::Arc;
use inkwell::{
context::Context,
memory_buffer::MemoryBuffer,
module::{Linkage, Module},
passes::PassBuilderOptions,
@ -35,7 +34,7 @@ use inkwell::{
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::typecheck::typedef::{TypeEnum, Unifier, VarMap};
use nac3parser::{
ast::{ExprKind, Stmt, StmtKind, StrRef},
parser::parse_program,
@ -51,7 +50,7 @@ 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 +59,13 @@ 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 +126,7 @@ struct Nac3 {
isa: Isa,
time_fns: &'static (dyn TimeFns + Sync),
primitive: PrimitiveStore,
builtins: Vec<BuiltinFuncSpec>,
builtins: Vec<(StrRef, FunSignature, Arc<GenCall>)>,
pyid_to_def: Arc<RwLock<HashMap<u64, DefinitionId>>>,
primitive_ids: PrimitivePythonId,
working_directory: TempDir,
@ -265,7 +264,7 @@ impl Nac3 {
arg_names.len(),
));
}
for (i, FuncArg { ty, default_value, name, .. }) in args.iter().enumerate() {
for (i, FuncArg { ty, default_value, name }) in args.iter().enumerate() {
let in_name = match arg_names.get(i) {
Some(n) => n,
None if default_value.is_none() => {
@ -301,64 +300,6 @@ impl Nac3 {
None
}
/// Returns a [`Vec`] of builtins that needs to be initialized during method compilation time.
fn get_lateinit_builtins() -> Vec<Box<BuiltinFuncCreator>> {
vec![
Box::new(|primitives, unifier| {
let arg_ty = unifier.get_fresh_var(Some("T".into()), None);
(
"core_log".into(),
FunSignature {
args: vec![FuncArg {
name: "arg".into(),
ty: arg_ty.ty,
default_value: None,
is_vararg: false,
}],
ret: primitives.none,
vars: into_var_map([arg_ty]),
},
Arc::new(GenCall::new(Box::new(move |ctx, obj, fun, args, generator| {
gen_core_log(ctx, &obj, fun, &args, generator)?;
Ok(None)
}))),
)
}),
Box::new(|primitives, unifier| {
let arg_ty = unifier.get_fresh_var(Some("T".into()), None);
(
"rtio_log".into(),
FunSignature {
args: vec![
FuncArg {
name: "channel".into(),
ty: primitives.str,
default_value: None,
is_vararg: false,
},
FuncArg {
name: "arg".into(),
ty: arg_ty.ty,
default_value: None,
is_vararg: false,
},
],
ret: primitives.none,
vars: into_var_map([arg_ty]),
},
Arc::new(GenCall::new(Box::new(move |ctx, obj, fun, args, generator| {
gen_rtio_log(ctx, &obj, fun, &args, generator)?;
Ok(None)
}))),
)
}),
]
}
fn compile_method<T>(
&self,
obj: &PyAny,
@ -371,7 +312,6 @@ impl Nac3 {
let size_t = self.isa.get_size_type();
let (mut composer, mut builtins_def, mut builtins_ty) = TopLevelComposer::new(
self.builtins.clone(),
Self::get_lateinit_builtins(),
ComposerConfig { kernel_ann: Some("Kernel"), kernel_invariant_ann: "KernelInvariant" },
size_t,
);
@ -448,6 +388,7 @@ impl Nac3 {
pyid_to_type: pyid_to_type.clone(),
primitive_ids: self.primitive_ids.clone(),
global_value_ids: global_value_ids.clone(),
class_names: Mutex::default(),
name_to_pyid: name_to_pyid.clone(),
module: module.clone(),
id_to_pyval: RwLock::default(),
@ -539,6 +480,7 @@ impl Nac3 {
pyid_to_type: pyid_to_type.clone(),
primitive_ids: self.primitive_ids.clone(),
global_value_ids: global_value_ids.clone(),
class_names: Mutex::default(),
id_to_pyval: RwLock::default(),
id_to_primitive: RwLock::default(),
field_to_val: RwLock::default(),
@ -555,10 +497,6 @@ impl Nac3 {
.register_top_level(synthesized.pop().unwrap(), Some(resolver.clone()), "", false)
.unwrap();
// Process IRRT
let context = inkwell::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();
@ -687,9 +625,7 @@ impl Nac3 {
let buffer = buffer.as_slice().into();
membuffer.lock().push(buffer);
})));
let size_t = Context::create()
.ptr_sized_int_type(&self.get_llvm_target_machine().get_target_data(), None)
.get_bit_width();
let size_t = if self.isa == Isa::Host { 64 } else { 32 };
let num_threads = if is_multithreaded() { 4 } else { 1 };
let thread_names: Vec<String> = (0..num_threads).map(|_| "main".to_string()).collect();
let threads: Vec<_> = thread_names
@ -708,9 +644,6 @@ impl Nac3 {
ArtiqCodeGenerator::new("attributes_writeback".to_string(), size_t, self.time_fns);
let context = inkwell::context::Context::create();
let module = context.create_module("attributes_writeback");
let target_machine = self.llvm_options.create_target_machine().unwrap();
module.set_data_layout(&target_machine.get_target_data().get_data_layout());
module.set_triple(&target_machine.get_triple());
let builder = context.create_builder();
let (_, module, _) = gen_func_impl(
&context,
@ -729,7 +662,7 @@ impl Nac3 {
membuffer.lock().push(buffer);
});
// Link all modules into `main`.
let context = inkwell::context::Context::create();
let buffers = membuffers.lock();
let main = context
.create_module_from_ir(MemoryBuffer::create_from_memory_range(&buffers[0], "main"))
@ -758,7 +691,8 @@ impl Nac3 {
)
.unwrap();
main.link_in_module(irrt).map_err(|err| CompileError::new_err(err.to_string()))?;
main.link_in_module(load_irrt(&context))
.map_err(|err| CompileError::new_err(err.to_string()))?;
let mut function_iter = main.get_first_function();
while let Some(func) = function_iter {
@ -913,7 +847,7 @@ impl Nac3 {
Isa::RiscV32IMA => &timeline::NOW_PINNING_TIME_FNS,
Isa::CortexA9 | Isa::Host => &timeline::EXTERN_TIME_FNS,
};
let (primitive, _) = TopLevelComposer::make_primitives(isa.get_size_type());
let primitive: PrimitiveStore = TopLevelComposer::make_primitives(isa.get_size_type()).0;
let builtins = vec![
(
"now_mu".into(),
@ -929,7 +863,6 @@ impl Nac3 {
name: "t".into(),
ty: primitive.int64,
default_value: None,
is_vararg: false,
}],
ret: primitive.none,
vars: VarMap::new(),
@ -949,7 +882,6 @@ impl Nac3 {
name: "dt".into(),
ty: primitive.int64,
default_value: None,
is_vararg: false,
}],
ret: primitive.none,
vars: VarMap::new(),

37
nac3artiq/src/symbol_resolver.rs
View File

@ -1,6 +1,4 @@
use crate::PrimitivePythonId;
use inkwell::{
module::Linkage,
types::{BasicType, BasicTypeEnum},
values::BasicValueEnum,
AddressSpace,
@ -23,7 +21,7 @@ use nac3core::{
},
};
use nac3parser::ast::{self, StrRef};
use parking_lot::RwLock;
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));
@ -997,15 +991,8 @@ impl InnerResolver {
}
_ => unreachable!("must be list"),
};
let ty = ctx.get_llvm_type(generator, elem_ty);
let size_t = generator.get_size_type(ctx.ctx);
let ty = if len == 0
&& matches!(&*ctx.unifier.get_ty_immutable(elem_ty), TypeEnum::TVar { .. })
{
// The default type for zero-length lists of unknown element type is size_t
size_t.into()
} else {
ctx.get_llvm_type(generator, elem_ty)
};
let arr_ty = ctx
.ctx
.struct_type(&[ty.ptr_type(AddressSpace::default()).into(), size_t.into()], false);
@ -1209,9 +1196,7 @@ impl InnerResolver {
Ok(Some(ndarray.as_pointer_value().into()))
} else if ty_id == self.primitive_ids.tuple {
let expected_ty_enum = ctx.unifier.get_ty_immutable(expected_ty);
let TypeEnum::TTuple { ty, is_vararg_ctx: false } = expected_ty_enum.as_ref() else {
unreachable!()
};
let TypeEnum::TTuple { ty } = expected_ty_enum.as_ref() else { unreachable!() };
let tup_tys = ty.iter();
let elements: &PyTuple = obj.downcast()?;

10
nac3core/Cargo.toml
View File

@ -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"
@ -14,8 +14,8 @@ 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 = "0.4"

100
nac3core/build.rs
View File

@ -3,56 +3,61 @@ 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",
"-Wextra",
"-o",
"-",
"-Werror=return-type",
"-I",
irrt_dir.to_str().unwrap(),
"-o",
"-",
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 +103,9 @@ 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 +114,50 @@ 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()`
"-I",
irrt_dir.to_str().unwrap(),
"-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();
}
}

15
nac3core/irrt/irrt.cpp
View File

@ -1,6 +1,9 @@
#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 any pre-compiled objects, so we are writing all implementations in headers and
concatenate them with `#include` into one massive source file that contains all the IRRT stuff.
*/

402
nac3core/irrt/irrt/core.hpp Normal file
View File

@ -0,0 +1,402 @@
#pragma once
#include <irrt/utils.hpp>
#include <irrt/int_defs.hpp>
// 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;
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,
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" {
#define DEF_nac3_int_exp_(T) \
T __nac3_int_exp_##T(T base, T exp) {\
return __nac3_int_exp_impl(base, exp);\
}
DEF_nac3_int_exp_(int32_t)
DEF_nac3_int_exp_(int64_t)
DEF_nac3_int_exp_(uint32_t)
DEF_nac3_int_exp_(uint64_t)
SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
if (i < 0) {
i = len + i;
}
if (i < 0) {
return 0;
} else if (i > len) {
return len;
}
return i;
}
SliceIndex __nac3_range_slice_len(
const SliceIndex start,
const SliceIndex end,
const SliceIndex step
) {
SliceIndex diff = end - start;
if (diff > 0 && step > 0) {
return ((diff - 1) / step) + 1;
} else if (diff < 0 && step < 0) {
return ((diff + 1) / step) + 1;
} else {
return 0;
}
}
// Handle list assignment and dropping part of the list when
// both dest_step and src_step are +1.
// - All the index must *not* be out-of-bound or negative,
// - The end index is *inclusive*,
// - The length of src and dest slice size should already
// be checked: if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest)
SliceIndex __nac3_list_slice_assign_var_size(
SliceIndex dest_start,
SliceIndex dest_end,
SliceIndex dest_step,
uint8_t* dest_arr,
SliceIndex dest_arr_len,
SliceIndex src_start,
SliceIndex src_end,
SliceIndex src_step,
uint8_t* src_arr,
SliceIndex src_arr_len,
const SliceIndex size
) {
/* if dest_arr_len == 0, do nothing since we do not support extending list */
if (dest_arr_len == 0) return dest_arr_len;
/* if both step is 1, memmove directly, handle the dropping of the list, and shrink size */
if (src_step == dest_step && dest_step == 1) {
const SliceIndex src_len = (src_end >= src_start) ? (src_end - src_start + 1) : 0;
const SliceIndex dest_len = (dest_end >= dest_start) ? (dest_end - dest_start + 1) : 0;
if (src_len > 0) {
__builtin_memmove(
dest_arr + dest_start * size,
src_arr + src_start * size,
src_len * size
);
}
if (dest_len > 0) {
/* dropping */
__builtin_memmove(
dest_arr + (dest_start + src_len) * size,
dest_arr + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size
);
}
/* shrink size */
return dest_arr_len - (dest_len - src_len);
}
/* if two range overlaps, need alloca */
uint8_t need_alloca =
(dest_arr == src_arr)
&& !(
max(dest_start, dest_end) < min(src_start, src_end)
|| max(src_start, src_end) < min(dest_start, dest_end)
);
if (need_alloca) {
uint8_t* tmp = reinterpret_cast<uint8_t *>(__builtin_alloca(src_arr_len * size));
__builtin_memcpy(tmp, src_arr, src_arr_len * size);
src_arr = tmp;
}
SliceIndex src_ind = src_start;
SliceIndex dest_ind = dest_start;
for (;
(src_step > 0) ? (src_ind <= src_end) : (src_ind >= src_end);
src_ind += src_step, dest_ind += dest_step
) {
/* for constant optimization */
if (size == 1) {
__builtin_memcpy(dest_arr + dest_ind, src_arr + src_ind, 1);
} else if (size == 4) {
__builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
} else if (size == 8) {
__builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
} else {
/* memcpy for var size, cannot overlap after previous alloca */
__builtin_memcpy(dest_arr + dest_ind * size, src_arr + src_ind * size, size);
}
}
/* only dest_step == 1 can we shrink the dest list. */
/* size should be ensured prior to calling this function */
if (dest_step == 1 && dest_end >= dest_start) {
__builtin_memmove(
dest_arr + dest_ind * size,
dest_arr + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size
);
return dest_arr_len - (dest_end - dest_ind) - 1;
}
return dest_arr_len;
}
int32_t __nac3_isinf(double x) {
return __builtin_isinf(x);
}
int32_t __nac3_isnan(double x) {
return __builtin_isnan(x);
}
double tgamma(double arg);
double __nac3_gamma(double z) {
// Handling for denormals
// | x | Python gamma(x) | C tgamma(x) |
// --- | ----------------- | --------------- | ----------- |
// (1) | nan | nan | nan |
// (2) | -inf | -inf | inf |
// (3) | inf | inf | inf |
// (4) | 0.0 | inf | inf |
// (5) | {-1.0, -2.0, ...} | inf | nan |
// (1)-(3)
if (__builtin_isinf(z) || __builtin_isnan(z)) {
return z;
}
double v = tgamma(z);
// (4)-(5)
return __builtin_isinf(v) || __builtin_isnan(v) ? __builtin_inf() : v;
}
double lgamma(double arg);
double __nac3_gammaln(double x) {
// libm's handling of value overflows differs from scipy:
// - scipy: gammaln(-inf) -> -inf
// - libm : lgamma(-inf) -> inf
if (__builtin_isinf(x)) {
return x;
}
return lgamma(x);
}
double j0(double x);
double __nac3_j0(double x) {
// libm's handling of value overflows differs from scipy:
// - scipy: j0(inf) -> nan
// - libm : j0(inf) -> 0.0
if (__builtin_isinf(x)) {
return __builtin_nan("");
}
return j0(x);
}
uint32_t __nac3_ndarray_calc_size(
const uint32_t* list_data,
uint32_t list_len,
uint32_t begin_idx,
uint32_t end_idx
) {
return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
}
uint64_t __nac3_ndarray_calc_size64(
const uint64_t* list_data,
uint64_t list_len,
uint64_t begin_idx,
uint64_t end_idx
) {
return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
}
void __nac3_ndarray_calc_nd_indices(
uint32_t index,
const uint32_t* dims,
uint32_t num_dims,
NDIndex* idxs
) {
__nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
}
void __nac3_ndarray_calc_nd_indices64(
uint64_t index,
const uint64_t* dims,
uint64_t num_dims,
NDIndex* idxs
) {
__nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
}
uint32_t __nac3_ndarray_flatten_index(
const uint32_t* dims,
uint32_t num_dims,
const NDIndex* indices,
uint32_t num_indices
) {
return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
}
uint64_t __nac3_ndarray_flatten_index64(
const uint64_t* dims,
uint64_t num_dims,
const NDIndex* indices,
uint64_t num_indices
) {
return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
}
void __nac3_ndarray_calc_broadcast(
const uint32_t* lhs_dims,
uint32_t lhs_ndims,
const uint32_t* rhs_dims,
uint32_t rhs_ndims,
uint32_t* out_dims
) {
return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
}
void __nac3_ndarray_calc_broadcast64(
const uint64_t* lhs_dims,
uint64_t lhs_ndims,
const uint64_t* rhs_dims,
uint64_t rhs_ndims,
uint64_t* out_dims
) {
return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
}
void __nac3_ndarray_calc_broadcast_idx(
const uint32_t* src_dims,
uint32_t src_ndims,
const NDIndex* in_idx,
NDIndex* out_idx
) {
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
}
void __nac3_ndarray_calc_broadcast_idx64(
const uint64_t* src_dims,
uint64_t src_ndims,
const NDIndex* in_idx,
NDIndex* out_idx
) {
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
}
} // extern "C"

9
nac3core/irrt/irrt/cslice.hpp
View File

@ -1,9 +0,0 @@
#pragma once
#include "irrt/int_types.hpp"
template<typename SizeT>
struct CSlice {
uint8_t* base;
SizeT len;
};

25
nac3core/irrt/irrt/debug.hpp
View File

@ -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); \
} \
}

85
nac3core/irrt/irrt/error_context.hpp Normal file
View File

@ -0,0 +1,85 @@
#pragma once
#include <irrt/int_defs.hpp>
#include <irrt/utils.hpp>
namespace {
// nac3core's "str" struct type definition
template <typename SizeT>
struct Str {
const char* content;
SizeT length;
};
// A limited set of errors IRRT could use.
typedef uint32_t ErrorId;
struct ErrorIds {
ErrorId index_error;
ErrorId value_error;
ErrorId assertion_error;
ErrorId runtime_error;
ErrorId type_error;
};
struct ErrorContext {
// Context
const ErrorIds* error_ids;
// Error thrown by IRRT
ErrorId error_id;
const char* message_template; // MUST BE `&'static`
int64_t param1;
int64_t param2;
int64_t param3;
void initialize(const ErrorIds* error_ids) {
this->error_ids = error_ids;
clear_error();
}
void clear_error() {
// Point the message_template to an empty str. Don't set it to nullptr as a sentinel
this->message_template = "";
}
void set_error(ErrorId error_id, const char* message, int64_t param1 = 0, int64_t param2 = 0, int64_t param3 = 0) {
this->error_id = error_id;
this->message_template = message;
this->param1 = param1;
this->param2 = param2;
this->param3 = param3;
}
bool has_error() {
return !cstr_utils::is_empty(message_template);
}
template <typename SizeT>
void get_error_str(Str<SizeT> *dst_str) {
dst_str->content = message_template;
dst_str->length = (SizeT) cstr_utils::length(message_template);
}
};
}
extern "C" {
void __nac3_error_context_initialize(ErrorContext* errctx, const ErrorIds* error_ids) {
errctx->initialize(error_ids);
}
bool __nac3_error_context_has_no_error(ErrorContext* errctx) {
return !errctx->has_error();
}
void __nac3_error_context_get_error_str(ErrorContext* errctx, Str<int32_t> *dst_str) {
errctx->get_error_str<int32_t>(dst_str);
}
void __nac3_error_context_get_error_str64(ErrorContext* errctx, Str<int64_t> *dst_str) {
errctx->get_error_str<int64_t>(dst_str);
}
void __nac3_error_dummy_raise(ErrorContext* errctx) {
errctx->set_error(errctx->error_ids->runtime_error, "THROWN FROM __nac3_error_dummy_raise!!!!!!");
}
}

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

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nac3core/irrt/irrt/int_defs.hpp Normal file
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#pragma once
// This is made toggleable since `irrt_test.cpp` itself would include
// headers that define these typedefs
#ifdef IRRT_DEFINE_TYPEDEF_INTS
typedef _BitInt(8) int8_t;
typedef unsigned _BitInt(8) uint8_t;
typedef _BitInt(32) int32_t;
typedef unsigned _BitInt(32) uint32_t;
typedef _BitInt(64) int64_t;
typedef unsigned _BitInt(64) uint64_t;
#endif

13
nac3core/irrt/irrt/int_types.hpp
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#pragma once
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);
// NDArray indices are always `uint32_t`.
using NDIndex = uint32_t;
// The type of an index or a value describing the length of a range/slice is always `int32_t`.
using SliceIndex = int32_t;

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nac3core/irrt/irrt/list.hpp
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#pragma once
#include "irrt/int_types.hpp"
#include "irrt/math_util.hpp"
extern "C" {
// Handle list assignment and dropping part of the list when
// both dest_step and src_step are +1.
// - All the index must *not* be out-of-bound or negative,
// - The end index is *inclusive*,
// - The length of src and dest slice size should already
// be checked: if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest)
SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
SliceIndex dest_end,
SliceIndex dest_step,
uint8_t* dest_arr,
SliceIndex dest_arr_len,
SliceIndex src_start,
SliceIndex src_end,
SliceIndex src_step,
uint8_t* src_arr,
SliceIndex src_arr_len,
const SliceIndex size) {
/* if dest_arr_len == 0, do nothing since we do not support extending list */
if (dest_arr_len == 0)
return dest_arr_len;
/* if both step is 1, memmove directly, handle the dropping of the list, and shrink size */
if (src_step == dest_step && dest_step == 1) {
const SliceIndex src_len = (src_end >= src_start) ? (src_end - src_start + 1) : 0;
const SliceIndex dest_len = (dest_end >= dest_start) ? (dest_end - dest_start + 1) : 0;
if (src_len > 0) {
__builtin_memmove(dest_arr + dest_start * size, src_arr + src_start * size, src_len * size);
}
if (dest_len > 0) {
/* dropping */
__builtin_memmove(dest_arr + (dest_start + src_len) * size, dest_arr + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size);
}
/* shrink size */
return dest_arr_len - (dest_len - src_len);
}
/* if two range overlaps, need alloca */
uint8_t need_alloca = (dest_arr == src_arr)
&& !(max(dest_start, dest_end) < min(src_start, src_end)
|| max(src_start, src_end) < min(dest_start, dest_end));
if (need_alloca) {
uint8_t* tmp = reinterpret_cast<uint8_t*>(__builtin_alloca(src_arr_len * size));
__builtin_memcpy(tmp, src_arr, src_arr_len * size);
src_arr = tmp;
}
SliceIndex src_ind = src_start;
SliceIndex dest_ind = dest_start;
for (; (src_step > 0) ? (src_ind <= src_end) : (src_ind >= src_end); src_ind += src_step, dest_ind += dest_step) {
/* for constant optimization */
if (size == 1) {
__builtin_memcpy(dest_arr + dest_ind, src_arr + src_ind, 1);
} else if (size == 4) {
__builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
} else if (size == 8) {
__builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
} else {
/* memcpy for var size, cannot overlap after previous alloca */
__builtin_memcpy(dest_arr + dest_ind * size, src_arr + src_ind * size, size);
}
}
/* only dest_step == 1 can we shrink the dest list. */
/* size should be ensured prior to calling this function */
if (dest_step == 1 && dest_end >= dest_start) {
__builtin_memmove(dest_arr + dest_ind * size, dest_arr + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size);
return dest_arr_len - (dest_end - dest_ind) - 1;
}
return dest_arr_len;
}
} // extern "C"

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nac3core/irrt/irrt/math.hpp
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#pragma once
namespace {
// adapted from GNU Scientific Library: https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
// need to make sure `exp >= 0` before calling this function
template<typename T>
T __nac3_int_exp_impl(T base, T exp) {
T res = 1;
/* repeated squaring method */
do {
if (exp & 1) {
res *= base; /* for n odd */
}
exp >>= 1;
base *= base;
} while (exp);
return res;
}
} // namespace
#define DEF_nac3_int_exp_(T) \
T __nac3_int_exp_##T(T base, T exp) { \
return __nac3_int_exp_impl(base, exp); \
}
extern "C" {
// Putting semicolons here to make clang-format not reformat this into
// a stair shape.
DEF_nac3_int_exp_(int32_t);
DEF_nac3_int_exp_(int64_t);
DEF_nac3_int_exp_(uint32_t);
DEF_nac3_int_exp_(uint64_t);
int32_t __nac3_isinf(double x) {
return __builtin_isinf(x);
}
int32_t __nac3_isnan(double x) {
return __builtin_isnan(x);
}
double tgamma(double arg);
double __nac3_gamma(double z) {
// Handling for denormals
// | x | Python gamma(x) | C tgamma(x) |
// --- | ----------------- | --------------- | ----------- |
// (1) | nan | nan | nan |
// (2) | -inf | -inf | inf |
// (3) | inf | inf | inf |
// (4) | 0.0 | inf | inf |
// (5) | {-1.0, -2.0, ...} | inf | nan |
// (1)-(3)
if (__builtin_isinf(z) || __builtin_isnan(z)) {
return z;
}
double v = tgamma(z);
// (4)-(5)
return __builtin_isinf(v) || __builtin_isnan(v) ? __builtin_inf() : v;
}
double lgamma(double arg);
double __nac3_gammaln(double x) {
// libm's handling of value overflows differs from scipy:
// - scipy: gammaln(-inf) -> -inf
// - libm : lgamma(-inf) -> inf
if (__builtin_isinf(x)) {
return x;
}
return lgamma(x);
}
double j0(double x);
double __nac3_j0(double x) {
// libm's handling of value overflows differs from scipy:
// - scipy: j0(inf) -> nan
// - libm : j0(inf) -> 0.0
if (__builtin_isinf(x)) {
return __builtin_nan("");
}
return j0(x);
}
}

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nac3core/irrt/irrt/math_util.hpp
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#pragma once
namespace {
template<typename T>
const T& max(const T& a, const T& b) {
return a > b ? a : b;
}
template<typename T>
const T& min(const T& a, const T& b) {
return a > b ? b : a;
}
} // namespace

144
nac3core/irrt/irrt/ndarray.hpp
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#pragma once
#include "irrt/int_types.hpp"
namespace {
template<typename SizeT>
SizeT __nac3_ndarray_calc_size_impl(const SizeT* list_data, SizeT list_len, SizeT begin_idx, SizeT end_idx) {
__builtin_assume(end_idx <= list_len);
SizeT num_elems = 1;
for (SizeT i = begin_idx; i < end_idx; ++i) {
SizeT val = list_data[i];
__builtin_assume(val > 0);
num_elems *= val;
}
return num_elems;
}
template<typename SizeT>
void __nac3_ndarray_calc_nd_indices_impl(SizeT index, const SizeT* dims, SizeT num_dims, NDIndex* idxs) {
SizeT stride = 1;
for (SizeT dim = 0; dim < num_dims; dim++) {
SizeT i = num_dims - dim - 1;
__builtin_assume(dims[i] > 0);
idxs[i] = (index / stride) % dims[i];
stride *= dims[i];
}
}
template<typename SizeT>
SizeT __nac3_ndarray_flatten_index_impl(const SizeT* dims, SizeT num_dims, const NDIndex* indices, SizeT num_indices) {
SizeT idx = 0;
SizeT stride = 1;
for (SizeT i = 0; i < num_dims; ++i) {
SizeT ri = num_dims - i - 1;
if (ri < num_indices) {
idx += stride * indices[ri];
}
__builtin_assume(dims[i] > 0);
stride *= dims[ri];
}
return idx;
}
template<typename SizeT>
void __nac3_ndarray_calc_broadcast_impl(const SizeT* lhs_dims,
SizeT lhs_ndims,
const SizeT* rhs_dims,
SizeT rhs_ndims,
SizeT* out_dims) {
SizeT max_ndims = lhs_ndims > rhs_ndims ? lhs_ndims : rhs_ndims;
for (SizeT i = 0; i < max_ndims; ++i) {
const SizeT* lhs_dim_sz = i < lhs_ndims ? &lhs_dims[lhs_ndims - i - 1] : nullptr;
const SizeT* rhs_dim_sz = i < rhs_ndims ? &rhs_dims[rhs_ndims - i - 1] : nullptr;
SizeT* out_dim = &out_dims[max_ndims - i - 1];
if (lhs_dim_sz == nullptr) {
*out_dim = *rhs_dim_sz;
} else if (rhs_dim_sz == nullptr) {
*out_dim = *lhs_dim_sz;
} else if (*lhs_dim_sz == 1) {
*out_dim = *rhs_dim_sz;
} else if (*rhs_dim_sz == 1) {
*out_dim = *lhs_dim_sz;
} else if (*lhs_dim_sz == *rhs_dim_sz) {
*out_dim = *lhs_dim_sz;
} else {
__builtin_unreachable();
}
}
}
template<typename SizeT>
void __nac3_ndarray_calc_broadcast_idx_impl(const SizeT* src_dims,
SizeT src_ndims,
const NDIndex* in_idx,
NDIndex* out_idx) {
for (SizeT i = 0; i < src_ndims; ++i) {
SizeT src_i = src_ndims - i - 1;
out_idx[src_i] = src_dims[src_i] == 1 ? 0 : in_idx[src_i];
}
}
} // namespace
extern "C" {
uint32_t __nac3_ndarray_calc_size(const uint32_t* list_data, uint32_t list_len, uint32_t begin_idx, uint32_t end_idx) {
return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
}
uint64_t
__nac3_ndarray_calc_size64(const uint64_t* list_data, uint64_t list_len, uint64_t begin_idx, uint64_t end_idx) {
return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
}
void __nac3_ndarray_calc_nd_indices(uint32_t index, const uint32_t* dims, uint32_t num_dims, NDIndex* idxs) {
__nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
}
void __nac3_ndarray_calc_nd_indices64(uint64_t index, const uint64_t* dims, uint64_t num_dims, NDIndex* idxs) {
__nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
}
uint32_t
__nac3_ndarray_flatten_index(const uint32_t* dims, uint32_t num_dims, const NDIndex* indices, uint32_t num_indices) {
return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
}
uint64_t
__nac3_ndarray_flatten_index64(const uint64_t* dims, uint64_t num_dims, const NDIndex* indices, uint64_t num_indices) {
return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
}
void __nac3_ndarray_calc_broadcast(const uint32_t* lhs_dims,
uint32_t lhs_ndims,
const uint32_t* rhs_dims,
uint32_t rhs_ndims,
uint32_t* out_dims) {
return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
}
void __nac3_ndarray_calc_broadcast64(const uint64_t* lhs_dims,
uint64_t lhs_ndims,
const uint64_t* rhs_dims,
uint64_t rhs_ndims,
uint64_t* out_dims) {
return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
}
void __nac3_ndarray_calc_broadcast_idx(const uint32_t* src_dims,
uint32_t src_ndims,
const NDIndex* in_idx,
NDIndex* out_idx) {
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
}
void __nac3_ndarray_calc_broadcast_idx64(const uint64_t* src_dims,
uint64_t src_ndims,
const NDIndex* in_idx,
NDIndex* out_idx) {
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
}
}

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#pragma once
#include <irrt/int_defs.hpp>
#include <irrt/error_context.hpp>
#include <irrt/numpy/ndarray_def.hpp>
namespace { namespace ndarray { namespace basic {
namespace util {
// throw an error if there is an axis with negative dimension
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_error(
errctx->error_ids->value_error,
"negative dimensions are not allowed; axis {0} has dimension {1}",
axis, shape[axis]
);
return;
}
}
}
// compute the size/# of elements of an ndarray given its shape
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;
}
// compute the strides of an ndarray given an ndarray `shape`
// and assuming that the ndarray is *fully c-contagious*.
//
// you might want to read up on https://ajcr.net/stride-guide-part-1/.
//
// this function might be used in isolation without an ndarray. that's
// why it separated out into its own util function.
template <typename SizeT>
void set_strides_by_shape(SizeT itemsize, SizeT ndims, SizeT* dst_strides, const SizeT* shape) {
SizeT stride_product = 1;
for (SizeT i = 0; i < ndims; i++) {
int axis = ndims - i - 1;
dst_strides[axis] = stride_product * itemsize;
stride_product *= shape[axis];
}
}
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;
}
}
}
// calculate the size/# of elements of an `ndarray`.
// this function corresponds to `np.size(<ndarray>)` or `ndarray.size`
template <typename SizeT>
SizeT size(NDArray<SizeT>* ndarray) {
return util::calc_size_from_shape(ndarray->ndims, ndarray->shape);
}
// calculate the number of bytes of its content of an `ndarray` *in its view*.
// this function corresponds to `ndarray.nbytes`
template <typename SizeT>
SizeT nbytes(NDArray<SizeT>* ndarray) {
return size(ndarray) * ndarray->itemsize;
}
template <typename SizeT>
void set_strides_by_shape(NDArray<SizeT>* ndarray) {
util::set_strides_by_shape(ndarray->itemsize, ndarray->ndims, ndarray->strides, ndarray->shape);
}
template <typename SizeT>
uint8_t* get_pelement_by_indices(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;
}
template <typename SizeT>
uint8_t* get_nth_pelement(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);
}
// get the pointer to the nth element of the ndarray as if it were flattened.
template <typename SizeT>
uint8_t* checked_get_nth_pelement(NDArray<SizeT>* ndarray, ErrorContext* errctx, SizeT nth) {
SizeT arr_size = ndarray->size();
if (!(0 <= nth && nth < arr_size)) {
errctx->set_error(
errctx->error_ids->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);
}
template <typename SizeT>
void set_pelement_value(NDArray<SizeT>* ndarray, uint8_t* pelement, const uint8_t* pvalue) {
__builtin_memcpy(pelement, pvalue, ndarray->itemsize);
}
template <typename SizeT>
void len(ErrorContext* errctx, NDArray<SizeT>* ndarray, SliceIndex* dst_length) {
// Error if the ndarray is "unsized" (i.e, ndims == 0)
if (ndarray->ndims == 0) {
// Error copied from python by doing `len(np.zeros(()))`
errctx->set_error(
errctx->error_ids->type_error,
"len() of unsized object"
);
return; // Terminate
}
*dst_length = (SliceIndex) ndarray->shape[0];
}
// Copy data from one ndarray to another *OF THE EXACT SAME* ndims, shape, and itemsize.
template <typename SizeT>
void copy_data(const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
__builtin_assume(src_ndarray->ndims == dst_ndarray->ndims);
__builtin_assume(src_ndarray->itemsize == dst_ndarray->itemsize);
for (SizeT i = 0; i < src_ndarray->size; 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);
}
}
// `copy_data()` with assertions to check ndims, shape, and itemsize between the two ndarrays.
template <typename SizeT>
void copy_data_checked(ErrorContext* errctx, const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
// NOTE: Out of all error types, runtime error seems appropriate
// Check ndims
if (src_ndarray->ndims != dst_ndarray->ndims) {
errctx->set_error(
errctx->error_ids->runtime_error,
"IRRT copy_data_checked input arrays `ndims` are mismatched"
);
return; // Terminate
}
// Check shape
if (!arrays_match(src_ndarray->ndims, src_ndarray->shape, dst_ndarray->shape)) {
errctx->set_error(
errctx->error_ids->runtime_error,
"IRRT copy_data_checked input arrays `shape` are mismatched"
);
return; // Terminate
}
// Check itemsize
if (src_ndarray->itemsize != dst_ndarray->itemsize) {
errctx->set_error(
errctx->error_ids->runtime_error,
"IRRT copy_data_checked input arrays `itemsize` are mismatched"
);
return; // Terminate
}
copy_data(src_ndarray, dst_ndarray);
}
} } }
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);
}
}

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#include <irrt/numpy/ndarray_def.hpp>
namespace { namespace ndarray { namespace broadcast {
namespace util {
template <typename SizeT>
void assert_broadcast_shape_to(
ErrorContext* errctx,
const SizeT target_ndims,
const SizeT* target_shape,
const SizeT src_ndims,
const SizeT* src_shape
) {
/*
// See https://numpy.org/doc/stable/user/basics.broadcasting.html
This function handles this example:
```
Image (3d array): 256 x 256 x 3
Scale (1d array): 3
Result (3d array): 256 x 256 x 3
```
Other interesting examples to consider:
- `can_broadcast_shape_to([3], [1, 1, 1, 1, 3]) ... ok`
- `can_broadcast_shape_to([3], [3, 1]) == false`
- `can_broadcast_shape_to([256, 256, 3], [256, 1, 3]) ... ok`
In cases when the shapes contain zero(es):
- `can_broadcast_shape_to([0], [1]) ... ok`
- `can_broadcast_shape_to([0], [2]) == false`
- `can_broadcast_shape_to([0, 4, 0, 0], [1]) ... ok`
- `can_broadcast_shape_to([0, 4, 0, 0], [1, 1, 1, 1]) ... ok`
- `can_broadcast_shape_to([0, 4, 0, 0], [1, 4, 1, 1]) ... ok`
- `can_broadcast_shape_to([4, 3], [0, 3]) == false`
- `can_broadcast_shape_to([4, 3], [0, 0]) == false`
*/
// Target ndims must not be smaller than source ndims
// e.g., `np.broadcast_to(np.zeros((1, 1, 1, 1)), (1, ))` is prohibited by numpy
if (target_ndims < src_ndims) {
// Error copied from python by doing the `np.broadcast_to(np.zeros((1, 1, 1, 1)), (1, ))`
errctx->set_error(
errctx->error_ids->value_error,
"input operand has more dimensions than allowed by the axis remapping"
);
return; // Terminate
}
// Implements the rules in https://numpy.org/doc/stable/user/basics.broadcasting.html
for (SizeT i = 0; i < src_ndims; i++) {
SizeT target_axis = target_ndims - i - 1;
SizeT src_axis = src_ndims - i - 1;
bool target_dim_exists = target_axis >= 0;
bool src_dim_exists = src_axis >= 0;
SizeT target_dim = target_dim_exists ? target_shape[target_axis] : 1;
SizeT src_dim = src_dim_exists ? src_shape[src_axis] : 1;
bool ok = src_dim == 1 || target_dim == src_dim;
if (!ok) {
// Error copied from python by doing `np.broadcast_to(np.zeros((3, 1)), (1, 1)),
// but this is the true numpy error:
// "ValueError: operands could not be broadcast together with remapped shapes [original->remapped]: (3,1) and requested shape (1,1)"
// TODO: we cannot show more than 3 parameters!!
errctx->set_error(
errctx->error_ids->value_error,
"operands could not be broadcast together with remapping shapes [original->remapped]"
);
return; // Terminate
}
}
}
}
// Similar to `np.broadcast_to(<ndarray>, <target_shape>)`
// Assumptions:
// - `src_ndarray` has to be fully initialized.
// - `dst_ndarray->ndims` has to be set.
// - `dst_ndarray->shape` has to be set, this determines the shape `this` broadcasts to.
//
// Other notes:
// - `dst_ndarray->data` does not have to be set, it will be set to `src_ndarray->data`.
// - `dst_ndarray->itemsize` does not have to be set, it will be set to `src_ndarray->data`.
// - `dst_ndarray->strides` does not have to be set, it will be overwritten.
//
// Cautions:
// ```
// xs = np.zeros((4,))
// ys = np.zero((4, 1))
// ys[:] = xs # ok
//
// xs = np.zeros((1, 4))
// ys = np.zero((4,))
// ys[:] = xs # allowed
// # However `np.broadcast_to(xs, (4,))` would fails, as per numpy's broadcasting rule.
// # and apparently numpy will "deprecate" this? SEE https://github.com/numpy/numpy/issues/21744
// # This implementation will NOT support this assignment.
// ```
template <typename SizeT>
void broadcast_to(ErrorContext* errctx, NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
dst_ndarray->data = src_ndarray->data;
dst_ndarray->itemsize = src_ndarray->itemsize;
ndarray::broadcast::util::assert_broadcast_shape_to(
errctx,
dst_ndarray->ndims,
dst_ndarray->shape,
src_ndarray->ndims,
src_ndarray->shape
);
if (errctx->has_error()) {
return; // Propagate error
}
SizeT stride_product = 1;
for (SizeT i = 0; i < max(src_ndarray->ndims, dst_ndarray->ndims); i++) {
SizeT this_dim_i = src_ndarray->ndims - i - 1;
SizeT dst_dim_i = dst_ndarray->ndims - i - 1;
bool this_dim_exists = this_dim_i >= 0;
bool dst_dim_exists = dst_dim_i >= 0;
// TODO: Explain how this works
bool c1 = this_dim_exists && src_ndarray->shape[this_dim_i] == 1;
bool c2 = dst_dim_exists && dst_ndarray->shape[dst_dim_i] != 1;
if (!this_dim_exists || (c1 && c2)) {
dst_ndarray->strides[dst_dim_i] = 0; // Freeze it in-place
} else {
dst_ndarray->strides[dst_dim_i] = stride_product * src_ndarray->itemsize;
stride_product *= src_ndarray->shape[this_dim_i]; // NOTE: this_dim_exist must be true here.
}
}
}
} } }

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#pragma once
namespace {
// The NDArray object. `SizeT` is the *signed* size type of this ndarray.
//
// NOTE: The order of fields is IMPORTANT. DON'T TOUCH IT
//
// Some resources you might find helpful:
// - The official numpy implementations:
// - https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst
// - On strides (about reshaping, slicing, C-contagiousness, etc)
// - https://ajcr.net/stride-guide-part-1/.
// - https://ajcr.net/stride-guide-part-2/.
// - https://ajcr.net/stride-guide-part-3/.
template <typename SizeT>
struct NDArray {
// The underlying data this `ndarray` is pointing to.
//
// NOTE: Formally this should be of type `void *`, but clang
// translates `void *` to `i8 *` when run with `-S -emit-llvm`,
// so we will put `uint8_t *` here for clarity.
//
// This pointer should point to the first element of the ndarray directly
uint8_t *data;
// The number of bytes of a single element in `data`.
//
// The `SizeT` is treated as `unsigned`.
SizeT itemsize;
// The number of dimensions of this shape.
//
// The `SizeT` is treated as `unsigned`.
SizeT ndims;
// Array shape, with length equal to `ndims`.
//
// The `SizeT` is treated as `unsigned`.
//
// NOTE: `shape` can contain 0.
// (those appear when the user makes an out of bounds slice into an ndarray, e.g., `np.zeros((3, 3))[400:].shape == (0, 3)`)
SizeT *shape;
// Array strides (stride value is in number of bytes, NOT number of elements), with length equal to `ndims`.
//
// The `SizeT` is treated as `signed`.
//
// NOTE: `strides` can have negative numbers.
// (those appear when there is a slice with a negative step, e.g., `my_array[::-1]`)
SizeT *strides;
};
// Because ndarray is so complicated, its functions are splitted into
// different files and namespaces.
}

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#pragma once
#include <irrt/numpy/ndarray_def.hpp>
#include <irrt/numpy/ndarray_basic.hpp>
namespace { namespace ndarray { namespace fill {
// Fill the ndarray with a value
template <typename SizeT>
void fill_generic(NDArray<SizeT>* ndarray, const uint8_t* pvalue) {
const SizeT size = ndarray::basic::size(ndarray);
for (SizeT i = 0; i < size; i++) {
uint8_t* pelement = ndarray::basic::get_nth_pelement(ndarray, i); // No need for checked_get_nth_pelement
ndarray::basic::set_pelement_value(ndarray, pelement, pvalue);
}
}
} } }
extern "C" {
using namespace ndarray::fill;
void __nac3_ndarray_fill_generic(NDArray<int32_t>* ndarray, uint8_t* pvalue) {
fill_generic(ndarray, pvalue);
}
void __nac3_ndarray_fill_generic64(NDArray<int64_t>* ndarray, uint8_t* pvalue) {
fill_generic(ndarray, pvalue);
}
}

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#pragma once
#include <irrt/slice.hpp>
#include <irrt/numpy/ndarray_def.hpp>
#include <irrt/numpy/ndarray_basic.hpp>
#include <irrt/error_context.hpp>
namespace {
typedef uint8_t NDSubscriptType;
const NDSubscriptType INPUT_SUBSCRIPT_TYPE_INDEX = 0;
const NDSubscriptType INPUT_SUBSCRIPT_TYPE_SLICE = 1;
struct NDSubscript {
// A poor-man's enum variant type
NDSubscriptType type;
/*
if type == INPUT_SUBSCRIPT_TYPE_INDEX => `slice` points to a single `SliceIndex`
if type == INPUT_SUBSCRIPT_TYPE_SLICE => `slice` points to a single `UserRange`
`SizeT` is controlled by the caller: `NDSubscript` only cares about where that
slice is (the pointer), `NDSubscript` does not care/know about the actual `sizeof()`
of the slice value.
*/
uint8_t* data;
};
}
namespace { namespace ndarray { namespace subscript {
namespace util {
template<typename SizeT>
void deduce_ndims_after_slicing(ErrorContext* errctx, SizeT* result, SizeT ndims, SizeT num_ndsubscripts, const NDSubscript* ndsubscripts) {
if (num_ndsubscripts > ndims) {
// Error copied from python by doing `np.zeros((3, 4))[:, :, :]`
errctx->set_error(
errctx->error_ids->index_error,
"too many indices for array: array is {0}-dimensional, but {1} were indexed",
ndims, num_ndsubscripts
);
return; // Terminate
}
SizeT final_ndims = ndims;
for (SizeT i = 0; i < num_ndsubscripts; i++) {
if (ndsubscripts[i].type == INPUT_SUBSCRIPT_TYPE_INDEX) {
final_ndims--; // An index demotes the rank by 1
}
}
*result = final_ndims;
}
}
// To support numpy "basic indexing" https://numpy.org/doc/stable/user/basics.indexing.html#basic-indexing
// "Advanced indexing" https://numpy.org/doc/stable/user/basics.indexing.html#advanced-indexing is not supported
//
// This function supports:
// - "scalar indexing",
// - "slicing and strides",
// - and "dimensional indexing tools" (TODO, but this is really easy to implement).
//
// Things assumed by this function:
// - `dst_ndarray` is allocated by the caller
// - `dst_ndarray.ndims` has the correct value (according to `ndarray::util::deduce_ndims_after_slicing`).
// - ... and `dst_ndarray.shape` and `dst_ndarray.strides` have been allocated by the caller as well
//
// Other notes:
// - `dst_ndarray->data` does not have to be set, it will be derived.
// - `dst_ndarray->itemsize` does not have to be set, it will be set to `src_ndarray->itemsize`
// - `dst_ndarray->shape` and `dst_ndarray.strides` can contain empty values
template <typename SizeT>
void subscript(ErrorContext* errctx, SliceIndex num_subscripts, NDSubscript* subscripts, NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
// REFERENCE CODE (check out `_index_helper` in `__getitem__`):
// https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L652
// irrt_assert(dst_ndarray->ndims == ndarray::util::deduce_ndims_after_slicing(src_ndarray->ndims, num_subscripts, subscripts));
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_subscripts; i++) {
NDSubscript *ndsubscript = &subscripts[i];
if (ndsubscript->type == INPUT_SUBSCRIPT_TYPE_INDEX) {
// Handle when the ndsubscript is just a single (possibly negative) integer
// e.g., `my_array[::2, -5, ::-1]`
// ^^------ like this
SliceIndex input_index = *((SliceIndex*) ndsubscript->data);
SliceIndex index = slice::resolve_index_in_length(src_ndarray->shape[src_axis], input_index);
if (index == slice::OUT_OF_BOUNDS) {
// Error message copied from numpy by doing `np.zeros((3, 4))[100]`
errctx->set_error(
errctx->error_ids->index_error,
"index {0} is out of bounds for axis {1} with size {2}",
input_index, src_axis, src_ndarray->shape[src_axis]
);
return; // Terminate
}
dst_ndarray->data += index * src_ndarray->strides[src_axis]; // Add offset
// Next
src_axis++;
} else if (ndsubscript->type == INPUT_SUBSCRIPT_TYPE_SLICE) {
// Handle when the ndsubscript is a slice (represented by UserSlice in IRRT)
// e.g., `my_array[::2, -5, ::-1]`
// ^^^------^^^^----- like these
UserSlice* input_user_slice = (UserSlice*) ndsubscript->data;
// TODO: use checked indices
Slice slice;
input_user_slice->indices_checked(errctx, src_ndarray->shape[src_axis], &slice); // To resolve negative indices and other funny stuff written by the user
if (errctx->has_error()) {
return; // Propagate error
}
// NOTE: There is no need to write special code to handle negative steps/strides.
// This simple implementation meticulously handles both positive and negative steps/strides.
// Check out the tinynumpy and IRRT's test cases if you are not convinced.
dst_ndarray->data += (SizeT) slice.start * src_ndarray->strides[src_axis]; // Add offset (NOTE: no need to `* itemsize`, strides count in # of bytes)
dst_ndarray->strides[dst_axis] = ((SizeT) slice.step) * src_ndarray->strides[src_axis]; // Determine stride
dst_ndarray->shape[dst_axis] = (SizeT) slice.len(); // Determine shape dimension
// Next
dst_axis++;
src_axis++;
} else {
__builtin_unreachable();
}
}
/*
Reference python code:
```python
dst_ndarray.shape.extend(src_ndarray.shape[src_axis:])
dst_ndarray.strides.extend(src_ndarray.strides[src_axis:])
```
*/
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];
}
}
} } }
extern "C" {
using namespace ndarray::subscript;
void __nac3_ndarray_subscript_deduce_ndims_after_slicing(ErrorContext* errctx, int32_t* result, int32_t ndims, int32_t num_ndsubscripts, const NDSubscript* ndsubscripts) {
ndarray::subscript::util::deduce_ndims_after_slicing(errctx, result, ndims, num_ndsubscripts, ndsubscripts);
}
void __nac3_ndarray_subscript_deduce_ndims_after_slicing64(ErrorContext* errctx, int64_t* result, int64_t ndims, int64_t num_ndsubscripts, const NDSubscript* ndsubscripts) {
ndarray::subscript::util::deduce_ndims_after_slicing(errctx, result, ndims, num_ndsubscripts, ndsubscripts);
}
void __nac3_ndarray_subscript(ErrorContext* errctx, SliceIndex num_subscripts, NDSubscript* subscripts, NDArray<int32_t>* src_ndarray, NDArray<int32_t> *dst_ndarray) {
subscript(errctx, num_subscripts, subscripts, src_ndarray, dst_ndarray);
}
void __nac3_ndarray_subscript64(ErrorContext* errctx, SliceIndex num_subscripts, NDSubscript* subscripts, NDArray<int64_t>* src_ndarray, NDArray<int64_t> *dst_ndarray) {
subscript(errctx, num_subscripts, subscripts, src_ndarray, dst_ndarray);
}
}

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#pragma once
#include "irrt/int_types.hpp"
#include <irrt/int_defs.hpp>
#include <irrt/slice.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;
}
namespace {
struct Slice {
SliceIndex start;
SliceIndex stop;
SliceIndex step;
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;
// The length/The number of elements of the slice if it were a range,
// i.e., the value of `len(range(this->start, this->stop, this->end))`
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 {
// "Resolve" an index value under a length in Python lists.
// If you have a `list` of length 100, `list[-1]` would resolve to `list[100-1] == list[99]`.
//
// If length == 0, this function returns 0
//
// If index is out of bounds, this function clamps the value
// (to `list[0]` or `list[-1]` in the context of a list and depending on if index is + or -)
SliceIndex resolve_index_in_length_clamped(SliceIndex length, SliceIndex index) {
if (index < 0) {
// Remember that index is negative, so do a plus here
return max<SliceIndex>(length + index, 0);
} else {
return min<SliceIndex>(length, index);
}
}
const SliceIndex OUT_OF_BOUNDS = -1;
// Like `resolve_index_in_length`.
// But also checks if the resolved index is in
// bounds (function returns true) or out of bounds
// (function returns false); `0 <= resolved index < length` is false).
SliceIndex resolve_index_in_length(SliceIndex length, SliceIndex index) {
SliceIndex resolved = index < 0 ? length + index : index;
bool in_bounds = 0 <= resolved && resolved < length;
return in_bounds ? resolved : OUT_OF_BOUNDS;
}
}
}
// A user-written Python-like slice.
//
// i.e., this slice is a triple of either an int or nothing. (e.g., `my_array[:10:2]`, `start` is None)
//
// You can "resolve" a `UserSlice` by using `user_slice.indices(<length>)`
struct UserSlice {
// Did the user specify `start`? If 0, `start` is undefined (and contains an empty value)
bool start_defined;
SliceIndex start;
// Similar to `start_defined`
bool stop_defined;
SliceIndex stop;
// Similar to `start_defined`
bool step_defined;
SliceIndex step;
// Convenient constructor for C++ internal use only (say testing)
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;
}
// Like Python's `slice(start, stop, step).indices(length)`
void indices(SliceIndex length, Slice* result) {
// NOTE: This function implements Python's `slice.indices` *FAITHFULLY*.
// SEE: https://github.com/python/cpython/blob/f62161837e68c1c77961435f1b954412dd5c2b65/Objects/sliceobject.c#L546
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;
}
}
// `indices()` but asserts `this->step != 0` and `this->length >= 0`
void indices_checked(ErrorContext* errctx, SliceIndex length, Slice* result) {
if (length < 0) {
errctx->set_error(
errctx->error_ids->value_error,
"length should not be negative, got {0}", // Edited. Error message copied from python by doing `slice(0, 0, 0).indices(100)`
length
);
return;
}
if (this->step_defined && this->step == 0) {
// Error message
errctx->set_error(
errctx->error_ids->value_error,
"slice step cannot be zero" // Error message copied from python by doing `slice(0, 0, 0).indices(100)`
);
return;
}
this->indices(length, result);
}
};
}

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#pragma once
#include <irrt/int_defs.hpp>
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;
}
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 {
bool is_empty(const char* str) {
return str[0] == '\0';
}
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 { // a[i] == b[i]
if (a[i] == '\0') {
return 0;
} else {
i++;
}
}
}
}
int8_t equal(const char* a, const char* b) {
return compare(a, b) == 0;
}
uint32_t length(const char* str) {
uint32_t length = 0;
while (*str != '\0') {
length++;
str++;
}
return length;
}
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();
}
}
}

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#pragma once
#include <irrt/core.hpp>
#include <irrt/error_context.hpp>
#include <irrt/int_defs.hpp>
#include <irrt/numpy/ndarray_basic.hpp>
#include <irrt/numpy/ndarray_broadcast.hpp>
#include <irrt/numpy/ndarray_def.hpp>
#include <irrt/numpy/ndarray_fill.hpp>
#include <irrt/numpy/ndarray_subscript.hpp>
#include <irrt/slice.hpp>
#include <irrt/utils.hpp>

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// This file will be compiled like a real C++ program,
// and we do have the luxury to use the standard libraries.
// That is if the nix flakes do not have issues... especially on msys2...
#include <cstdint>
#include <cstdio>
#include <cstdlib>
#include <irrt_everything.hpp>
#include <test/core.hpp>
#include <test/test_core.hpp>
#include <test/test_ndarray_basic.hpp>
#include <test/test_ndarray_subscript.hpp>
#include <test/test_ndarray_broadcast.hpp>
#include <test/test_slice.hpp>
int main() {
// Be wise about the order of suites!!
test::core::run();
test::slice::run();
test::ndarray_basic::run();
test::ndarray_subscript::run();
test::ndarray_broadcast::run();
return 0;
}

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#pragma once
// Include this header for every test_*.cpp
#include <cstdint>
#include <cstdio>
#include <cstdlib>
#include <test/print.hpp>
// Some utils can be used here
#include <irrt/utils.hpp>
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);
}
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 = ");
print_array(len, expected);
printf("\n");
printf(" Got = ");
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 ErrorIds for testing only
const ErrorIds TEST_ERROR_IDS = {
.index_error = 0,
.value_error = 1,
.assertion_error = 2,
.runtime_error = 3,
};
ErrorContext create_testing_errctx() {
// Everything is global so it is fine to directly return a struct ErrorContext
ErrorContext errctx;
errctx.initialize(&TEST_ERROR_IDS);
return errctx;
}
void print_errctx_content(ErrorContext* errctx) {
if (errctx->has_error()) {
printf(
"(Error ID %d): %s ... where param1 = %ld, param2 = %ld, param3 = %ld\n",
errctx->error_id,
errctx->message_template,
errctx->param1,
errctx->param2,
errctx->param3
);
} else {
printf("<no error>\n");
}
}
void __assert_errctx_no_error(const char* file, int line, ErrorContext* errctx) {
if (errctx->has_error()) {
print_assertion_failed(file, line);
printf("Expecting no error but caught the following:\n\n");
print_errctx_content(errctx);
test_fail();
}
}
#define assert_errctx_no_error(errctx) __assert_errctx_no_error(__FILE__, __LINE__, errctx)
void __assert_errctx_has_error(const char* file, int line, ErrorContext* errctx, ErrorId expected_error_id) {
if (errctx->has_error()) {
if (errctx->error_id == expected_error_id) {
// OK
} else {
// Otherwise it got the wrong kind of error
print_assertion_failed(file, line);
printf(
"Expecting error id %d but got error id %d. Error caught:\n\n",
expected_error_id,
errctx->error_id
);
print_errctx_content(errctx);
test_fail();
}
} else {
print_assertion_failed(file, line);
printf("Expecting an error, but there is none.");
test_fail();
}
}
#define assert_errctx_has_error(errctx, expected_error_id) __assert_errctx_has_error(__FILE__, __LINE__, errctx, expected_error_id)

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#pragma once
#include <cstdlib>
#include <cstdio>
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 print_repeated(const char *str, int count) {
for (int i = 0; i < count; i++) {
printf("%s", str);
}
}
template <typename T>
void print_array(int len, const T* as) {
printf("[");
for (int i = 0; i < len; i++) {
if (i != 0) printf(", ");
print_value(as[i]);
}
printf("]");
}
template<typename ElementT, typename SizeT>
void __print_ndarray_aux(bool first, bool last, SizeT* cursor, SizeT depth, NDArray<SizeT>* ndarray) {
// A really lazy recursive implementation
// Add left padding unless its the first entry (since there would be "[[[" before it)
if (!first) {
print_repeated(" ", depth);
}
const SizeT dim = ndarray->shape[depth];
if (depth + 1 == ndarray->ndims) {
// Recursed down to last dimension, print the values in a nice list
printf("[");
SizeT* indices = (SizeT*) __builtin_alloca(sizeof(SizeT) * ndarray->ndims);
for (SizeT i = 0; i < dim; i++) {
ndarray::basic::util::set_indices_by_nth(ndarray->ndims, ndarray->shape, indices, *cursor);
ElementT* pelement = (ElementT*) ndarray::basic::get_pelement_by_indices<SizeT>(ndarray, indices);
ElementT element = *pelement;
if (i != 0) printf(", "); // List delimiter
print_value(element);
printf("(@");
print_array(ndarray->ndims, indices);
printf(")");
(*cursor)++;
}
printf("]");
} else {
printf("[");
for (SizeT i = 0; i < ndarray->shape[depth]; i++) {
__print_ndarray_aux<ElementT, SizeT>(
i == 0, // first?
i + 1 == dim, // last?
cursor,
depth + 1,
ndarray
);
}
printf("]");
}
// Add newline unless its the last entry (since there will be "]]]" after it)
if (!last) {
print_repeated("\n", depth);
}
}
template <typename ElementT, typename SizeT>
void print_ndarray(NDArray<SizeT>* ndarray) {
if (ndarray->ndims == 0) {
printf("<empty ndarray>");
} else {
SizeT cursor = 0;
__print_ndarray_aux<ElementT, SizeT>(true, true, &cursor, 0, ndarray);
}
printf("\n");
}

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#pragma once
#include <test/core.hpp>
#include <irrt_everything.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();
}
}
}

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nac3core/irrt/test/test_ndarray_basic.hpp Normal file
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#pragma once
#include <test/core.hpp>
#include <irrt_everything.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 test_set_strides_by_shape() {
// Test `set_strides_by_shape()`
BEGIN_TEST();
int32_t shape[4] = { 99, 3, 5, 7 };
int32_t strides[4] = { 0 };
ndarray::basic::util::set_strides_by_shape((int32_t) sizeof(int32_t), 4, strides, shape);
int32_t expected_strides[4] = {
105 * sizeof(int32_t),
35 * sizeof(int32_t),
7 * sizeof(int32_t),
1 * sizeof(int32_t)
};
assert_arrays_match(4, expected_strides, strides);
}
void run() {
test_calc_size_from_shape_normal();
test_calc_size_from_shape_has_zero();
test_set_strides_by_shape();
}
}
}

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nac3core/irrt/test/test_ndarray_broadcast.hpp Normal file
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#pragma once
#include <test/core.hpp>
#include <irrt_everything.hpp>
namespace test { namespace ndarray_broadcast {
void test_ndarray_broadcast_1() {
/*
```python
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]]]
assert array.strides == (0, 0, 8)
# and then pick some values in `array` and check them...
```
*/
BEGIN_TEST();
// Prepare src_ndarray
double src_data[4] = { 19.9, 29.9, 39.9, 49.9 };
const int32_t src_ndims = 2;
int32_t src_shape[src_ndims] = {1, 4};
int32_t src_strides[src_ndims] = {};
NDArray<int32_t> src_ndarray = {
.data = (uint8_t*) src_data,
.itemsize = sizeof(double),
.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 = 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
};
// Broadcast
ErrorContext errctx = create_testing_errctx();
ndarray::broadcast::broadcast_to(&errctx, &src_ndarray, &dst_ndarray);
assert_errctx_no_error(&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_ndarray_broadcast_1();
}
}}

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#pragma once
#include <test/core.hpp>
#include <irrt_everything.hpp>
namespace test { namespace ndarray_subscript {
void test_ndsubscript_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_ndsubscripts = 2;
NDSubscript ndsubscripts[num_ndsubscripts] = {
{ .type = INPUT_SUBSCRIPT_TYPE_SLICE, .data = (uint8_t*) &subscript_1 },
{ .type = INPUT_SUBSCRIPT_TYPE_SLICE, .data = (uint8_t*) &subscript_2 }
};
ErrorContext errctx = create_testing_errctx();
ndarray::subscript::subscript(&errctx, num_ndsubscripts, ndsubscripts, &src_ndarray, &dst_ndarray);
assert_errctx_no_error(&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_ndsubscript_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_ndsubscripts = 2;
NDSubscript ndsubscripts[num_ndsubscripts] = {
{ .type = INPUT_SUBSCRIPT_TYPE_INDEX, .data = (uint8_t*) &subscript_1 },
{ .type = INPUT_SUBSCRIPT_TYPE_SLICE, .data = (uint8_t*) &subscript_2 }
};
ErrorContext errctx = create_testing_errctx();
ndarray::subscript::subscript(&errctx, num_ndsubscripts, ndsubscripts, &src_ndarray, &dst_ndarray);
assert_errctx_no_error(&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_ndsubscript_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_ndsubscripts = 2;
NDSubscript ndsubscripts[num_ndsubscripts] = {
{ .type = INPUT_SUBSCRIPT_TYPE_INDEX, .data = (uint8_t*) &subscript_1 },
{ .type = INPUT_SUBSCRIPT_TYPE_INDEX, .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::subscript::subscript(&errctx, num_ndsubscripts, ndsubscripts, &src_ndarray, &dst_ndarray);
assert_errctx_has_error(&errctx, errctx.error_ids->index_error);
}
void run() {
test_ndsubscript_normal_1();
test_ndsubscript_normal_2();
test_ndsubscript_index_subscript_out_of_bounds();
}
} }

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#pragma once
#include <test/core.hpp>
#include <irrt_everything.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, &slice);
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, &slice);
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, &slice);
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, &slice);
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_error(&errctx, errctx.error_ids->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();
}
}
}

610
nac3core/src/codegen/builtin_fns.rs
View File

@ -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)
@ -930,7 +863,6 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_int64.const_int(1, false),
(n_sz, false),
|generator, ctx, _, idx| {
@ -945,7 +877,7 @@ 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 +914,7 @@ 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 +980,7 @@ 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 +1010,9 @@ 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 +1123,9 @@ 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, $on_scalar:expr) => {
#[allow(clippy::redundant_closure_call)]
@ -1220,7 +1152,7 @@ macro_rules! create_helper_call_numpy_unary_elementwise {
/// * `$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 +1420,7 @@ 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 +1487,7 @@ 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 +1554,7 @@ 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 +1621,7 @@ 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 +1744,7 @@ 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 +1811,7 @@ 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 +1835,3 @@ 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])
}
}

3
nac3core/src/codegen/classes.rs
View File

@ -1404,7 +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();
@ -1717,7 +1717,6 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(len, false),
|generator, ctx, _, i| {

19
nac3core/src/codegen/concrete_type.rs
View File

@ -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),

1232
nac3core/src/codegen/expr.rs
View File

File diff suppressed because it is too large Load Diff

67
nac3core/src/codegen/extern_fns.rs
View File

@ -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);

34
nac3core/src/codegen/generator.rs
View File

@ -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(

187
nac3core/src/codegen/irrt/error_context.rs Normal file
View File

@ -0,0 +1,187 @@
use crate::codegen::{model::*, CodeGenContext, CodeGenerator};
use super::util::{get_sized_dependent_function_name, FunctionBuilder};
pub struct StrFields<'ctx> {
pub content: Field<PointerModel<FixedIntModel<Byte>>>,
pub length: Field<IntModel<'ctx>>,
}
#[derive(Debug, Clone, Copy)]
pub struct Str<'ctx> {
pub sizet: IntModel<'ctx>,
}
impl<'ctx> IsStruct<'ctx> for Str<'ctx> {
type Fields = StrFields<'ctx>;
fn struct_name(&self) -> &'static str {
"Str"
}
fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields {
Self::Fields {
content: builder.add_field_auto("content"),
length: builder.add_field("length", self.sizet),
}
}
}
type ErrorId = Int32;
pub struct ErrorIdsFields {
pub index_error: Field<FixedIntModel<ErrorId>>,
pub value_error: Field<FixedIntModel<ErrorId>>,
pub assertion_error: Field<FixedIntModel<ErrorId>>,
pub runtime_error: Field<FixedIntModel<ErrorId>>,
pub type_error: Field<FixedIntModel<ErrorId>>,
}
#[derive(Debug, Clone, Copy)]
pub struct ErrorIds;
impl<'ctx> IsStruct<'ctx> for ErrorIds {
type Fields = ErrorIdsFields;
fn struct_name(&self) -> &'static str {
"ErrorIds"
}
fn build_fields(&self, builder: &mut FieldBuilder) -> Self::Fields {
Self::Fields {
index_error: builder.add_field_auto("index_error"),
value_error: builder.add_field_auto("value_error"),
assertion_error: builder.add_field_auto("assertion_error"),
runtime_error: builder.add_field_auto("runtime_error"),
type_error: builder.add_field_auto("type_error"),
}
}
}
pub struct ErrorContextFields {
pub error_id: Field<FixedIntModel<ErrorId>>,
pub message_template: Field<PointerModel<FixedIntModel<Byte>>>,
pub param1: Field<FixedIntModel<Int64>>,
pub param2: Field<FixedIntModel<Int64>>,
pub param3: Field<FixedIntModel<Int64>>,
}
#[derive(Debug, Clone, Copy)]
pub struct ErrorContext;
impl<'ctx> IsStruct<'ctx> for ErrorContext {
type Fields = ErrorContextFields;
fn struct_name(&self) -> &'static str {
"ErrorIds"
}
fn build_fields(&self, builder: &mut FieldBuilder) -> Self::Fields {
Self::Fields {
error_id: builder.add_field_auto("error_id"),
message_template: builder.add_field_auto("message_template"),
param1: builder.add_field_auto("param1"),
param2: builder.add_field_auto("param2"),
param3: builder.add_field_auto("param3"),
}
}
}
// Prepare ErrorIds
fn build_error_ids<'ctx>(ctx: &CodeGenContext<'ctx, '_>) -> Pointer<'ctx, StructModel<ErrorIds>> {
// ErrorIdsLens.get_fields(ctx.ctx).assertion_error.
let error_ids = StructModel(ErrorIds).alloca(ctx, "error_ids");
let i32_model = FixedIntModel(Int32);
// i32_model.make_constant()
let get_string_id =
|string_id| i32_model.constant(ctx.ctx, ctx.resolver.get_string_id(string_id) as u64);
error_ids.gep(ctx, |f| f.index_error).store(ctx, get_string_id("0:IndexError"));
error_ids.gep(ctx, |f| f.value_error).store(ctx, get_string_id("0:ValueError"));
error_ids.gep(ctx, |f| f.assertion_error).store(ctx, get_string_id("0:AssertionError"));
error_ids.gep(ctx, |f| f.runtime_error).store(ctx, get_string_id("0:RuntimeError"));
error_ids.gep(ctx, |f| f.type_error).store(ctx, get_string_id("0:TypeError"));
error_ids
}
pub fn call_nac3_error_context_initialize<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
perrctx: Pointer<'ctx, StructModel<ErrorContext>>,
perror_ids: Pointer<'ctx, StructModel<ErrorIds>>,
) {
FunctionBuilder::begin(ctx, "__nac3_error_context_initialize")
.arg("errctx", PointerModel(StructModel(ErrorContext)), perrctx)
.arg("error_ids", PointerModel(StructModel(ErrorIds)), perror_ids)
.returning_void();
}
pub fn call_nac3_error_context_has_no_error<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
errctx: Pointer<'ctx, StructModel<ErrorContext>>,
) -> FixedInt<'ctx, Bool> {
FunctionBuilder::begin(ctx, "__nac3_error_context_has_no_error")
.arg("errctx", PointerModel(StructModel(ErrorContext)), errctx)
.returning("has_error", FixedIntModel(Bool))
}
pub fn call_nac3_error_context_get_error_str<'ctx>(
sizet: IntModel<'ctx>,
ctx: &CodeGenContext<'ctx, '_>,
errctx: Pointer<'ctx, StructModel<ErrorContext>>,
dst_str: Pointer<'ctx, StructModel<Str<'ctx>>>,
) {
FunctionBuilder::begin(
ctx,
&get_sized_dependent_function_name(sizet, "__nac3_error_context_get_error_str"),
)
.arg("errctx", PointerModel(StructModel(ErrorContext)), errctx)
.arg("dst_str", PointerModel(StructModel(Str { sizet })), dst_str)
.returning_void();
}
pub fn prepare_error_context<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
) -> Pointer<'ctx, StructModel<ErrorContext>> {
let error_ids = build_error_ids(ctx);
let errctx_ptr = StructModel(ErrorContext).alloca(ctx, "errctx");
call_nac3_error_context_initialize(ctx, errctx_ptr, error_ids);
errctx_ptr
}
pub fn check_error_context<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
errctx_ptr: Pointer<'ctx, StructModel<ErrorContext>>,
) {
let sizet = IntModel(generator.get_size_type(ctx.ctx));
let has_error = call_nac3_error_context_has_no_error(ctx, errctx_ptr);
let pstr = StructModel(Str { sizet }).alloca(ctx, "error_str");
call_nac3_error_context_get_error_str(sizet, ctx, errctx_ptr, pstr);
let error_id = errctx_ptr.gep(ctx, |f| f.error_id).load(ctx, "error_id");
let error_str = pstr.load(ctx, "error_str");
let param1 = errctx_ptr.gep(ctx, |f| f.param1).load(ctx, "param1");
let param2 = errctx_ptr.gep(ctx, |f| f.param2).load(ctx, "param2");
let param3 = errctx_ptr.gep(ctx, |f| f.param3).load(ctx, "param3");
ctx.make_assert_impl_by_id(
generator,
has_error.value,
error_id.value,
error_str.get_llvm_value(),
[Some(param1.value), Some(param2.value), Some(param3.value)],
ctx.current_loc,
);
}
pub fn call_nac3_dummy_raise<G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext,
) {
let errctx = prepare_error_context(ctx);
FunctionBuilder::begin(ctx, "__nac3_error_dummy_raise")
.arg("errctx", PointerModel(StructModel(ErrorContext)), errctx)
.returning_void();
check_error_context(generator, ctx, errctx);
}

61
nac3core/src/codegen/irrt/mod.rs
View File

@ -1,29 +1,33 @@
use crate::{symbol_resolver::SymbolResolver, typecheck::typedef::Type};
use crate::typecheck::typedef::Type;
pub mod error_context;
pub mod numpy;
mod test;
mod util;
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 +43,6 @@ 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 +60,7 @@ 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(|| {
@ -461,7 +446,7 @@ 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 +573,7 @@ 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 +590,7 @@ 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 +625,7 @@ 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 +641,7 @@ 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 +710,7 @@ 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 +749,7 @@ 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 +778,7 @@ 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(|| {
@ -819,7 +803,6 @@ pub fn call_ndarray_calc_broadcast<'ctx, G: CodeGenerator + ?Sized>(
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(min_ndims, false),
|generator, ctx, _, idx| {
@ -914,7 +897,7 @@ 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(|| {

4
nac3core/src/codegen/irrt/numpy/mod.rs Normal file
View File

@ -0,0 +1,4 @@
pub mod ndarray;
pub mod shape;
pub mod slice;
pub mod subscript;

254
nac3core/src/codegen/irrt/numpy/ndarray.rs Normal file
View File

@ -0,0 +1,254 @@
use inkwell::types::{BasicType, BasicTypeEnum};
use crate::codegen::{
irrt::{
error_context::{check_error_context, prepare_error_context, ErrorContext},
util::{get_sized_dependent_function_name, FunctionBuilder},
},
model::*,
CodeGenContext, CodeGenerator,
};
use super::{
shape::Producer,
slice::{SliceIndex, SliceIndexModel},
};
pub struct NpArrayFields<'ctx> {
pub data: Field<PointerModel<ByteModel>>,
pub itemsize: Field<IntModel<'ctx>>,
pub ndims: Field<IntModel<'ctx>>,
pub shape: Field<PointerModel<IntModel<'ctx>>>,
pub strides: Field<PointerModel<IntModel<'ctx>>>,
}
#[derive(Debug, Clone, Copy)]
pub struct NpArray<'ctx> {
pub sizet: IntModel<'ctx>,
}
impl<'ctx> IsStruct<'ctx> for NpArray<'ctx> {
type Fields = NpArrayFields<'ctx>;
fn struct_name(&self) -> &'static str {
"NDArray"
}
fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields {
NpArrayFields {
data: builder.add_field_auto("data"),
itemsize: builder.add_field("itemsize", self.sizet),
ndims: builder.add_field("ndims", self.sizet),
shape: builder.add_field("shape", PointerModel(self.sizet)),
strides: builder.add_field("strides", PointerModel(self.sizet)),
}
}
}
impl<'ctx> Pointer<'ctx, StructModel<NpArray<'ctx>>> {
pub fn shape_slice(&self, ctx: &CodeGenContext<'ctx, '_>) -> ArraySlice<'ctx, IntModel<'ctx>> {
let ndims = self.gep(ctx, |f| f.ndims).load(ctx, "ndims");
let shape_base_ptr = self.gep(ctx, |f| f.shape).load(ctx, "shape");
ArraySlice { num_elements: ndims, pointer: shape_base_ptr }
}
pub fn strides_slice(
&self,
ctx: &CodeGenContext<'ctx, '_>,
) -> ArraySlice<'ctx, IntModel<'ctx>> {
let ndims = self.gep(ctx, |f| f.ndims).load(ctx, "ndims");
let strides_base_ptr = self.gep(ctx, |f| f.strides).load(ctx, "strides");
ArraySlice { num_elements: ndims, pointer: strides_base_ptr }
}
}
pub fn alloca_ndarray<'ctx, G>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
elem_type: BasicTypeEnum<'ctx>,
ndims: Int<'ctx>,
name: &str,
) -> Result<Pointer<'ctx, StructModel<NpArray<'ctx>>>, String>
where
G: CodeGenerator + ?Sized,
{
let sizet = IntModel(generator.get_size_type(ctx.ctx));
// Allocate ndarray
let ndarray_ptr = StructModel(NpArray { sizet }).alloca(ctx, name);
// Set ndims
ndarray_ptr.gep(ctx, |f| f.ndims).store(ctx, ndims);
// Set itemsize
let itemsize = Int(elem_type.size_of().unwrap());
ndarray_ptr.gep(ctx, |f| f.itemsize).store(ctx, itemsize.signed_cast_to_int(ctx, sizet, ""));
// Allocate and set shape
let shape_array = sizet.array_alloca(ctx, ndims, "shape");
ndarray_ptr.gep(ctx, |f| f.shape).store(ctx, shape_array.pointer);
// Allocate and set strides
let strides_array = sizet.array_alloca(ctx, ndims, "strides");
ndarray_ptr.gep(ctx, |f| f.strides).store(ctx, strides_array.pointer);
Ok(ndarray_ptr)
}
pub enum NDArrayInitMode<'ctx, G: CodeGenerator + ?Sized> {
NDims { ndims: Int<'ctx> },
Shape { shape: Producer<'ctx, G, IntModel<'ctx>> },
ShapeAndAllocaData { shape: Producer<'ctx, G, IntModel<'ctx>> },
}
/// TODO: DOCUMENT ME
pub fn alloca_ndarray_and_init<'ctx, G>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
elem_type: BasicTypeEnum<'ctx>,
init_mode: NDArrayInitMode<'ctx, G>,
name: &str,
) -> Result<Pointer<'ctx, StructModel<NpArray<'ctx>>>, String>
where
G: CodeGenerator + ?Sized,
{
// It is implemented verbosely in order to make the initialization modes super clear in their intent.
match init_mode {
NDArrayInitMode::NDims { ndims } => {
let ndarray_ptr = alloca_ndarray(generator, ctx, elem_type, ndims, name)?;
Ok(ndarray_ptr)
}
NDArrayInitMode::Shape { shape } => {
let ndims = shape.count;
let ndarray_ptr = alloca_ndarray(generator, ctx, elem_type, ndims, name)?;
// Fill `ndarray.shape`
(shape.write_to_array)(generator, ctx, &ndarray_ptr.shape_slice(ctx))?;
// Check if `shape` has bad inputs
call_nac3_ndarray_util_assert_shape_no_negative(
generator,
ctx,
ndims,
ndarray_ptr.gep(ctx, |f| f.shape).load(ctx, "shape"),
);
// NOTE: DO NOT DO `set_strides_by_shape` HERE.
// Simply this is because we specified that `SetShape` wouldn't do `set_strides_by_shape`
Ok(ndarray_ptr)
}
NDArrayInitMode::ShapeAndAllocaData { shape } => {
let ndims = shape.count;
let ndarray_ptr = alloca_ndarray(generator, ctx, elem_type, ndims, name)?;
// Fill `ndarray.shape`
(shape.write_to_array)(generator, ctx, &ndarray_ptr.shape_slice(ctx))?;
// Check if `shape` has bad inputs
call_nac3_ndarray_util_assert_shape_no_negative(
generator,
ctx,
ndims,
ndarray_ptr.gep(ctx, |f| f.shape).load(ctx, "shape"),
);
// Now we populate `ndarray.data` by alloca-ing.
// But first, we need to know the size of the ndarray to know how many elements to alloca,
// since calculating nbytes of an ndarray requires `ndarray.shape` to be set.
let ndarray_nbytes = call_nac3_ndarray_nbytes(ctx, ndarray_ptr);
// Alloca `data` and assign it to `ndarray.data`
let data_array = FixedIntModel(Byte).array_alloca(ctx, ndarray_nbytes, "data");
ndarray_ptr.gep(ctx, |f| f.data).store(ctx, data_array.pointer);
// Finally, do `set_strides_by_shape`
// Check out https://ajcr.net/stride-guide-part-1/ to see what numpy "strides" are.
call_nac3_ndarray_set_strides_by_shape(ctx, ndarray_ptr);
Ok(ndarray_ptr)
}
}
}
fn call_nac3_ndarray_util_assert_shape_no_negative<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
ndims: Int<'ctx>,
shape_ptr: Pointer<'ctx, IntModel<'ctx>>,
) {
let sizet = IntModel(generator.get_size_type(ctx.ctx));
let errctx = prepare_error_context(ctx);
FunctionBuilder::begin(
ctx,
&get_sized_dependent_function_name(sizet, "__nac3_ndarray_util_assert_shape_no_negative"),
)
.arg("errctx", PointerModel(StructModel(ErrorContext)), errctx)
.arg("ndims", sizet, ndims)
.arg("shape", PointerModel(sizet), shape_ptr)
.returning_void();
check_error_context(generator, ctx, errctx);
}
fn call_nac3_ndarray_set_strides_by_shape<'ctx>(
ctx: &mut CodeGenContext<'ctx, '_>,
ndarray_ptr: Pointer<'ctx, StructModel<NpArray<'ctx>>>,
) {
let sizet = ndarray_ptr.element.0.sizet;
FunctionBuilder::begin(
ctx,
&get_sized_dependent_function_name(sizet, "__nac3_ndarray_set_strides_by_shape"),
)
.arg("ndarray", PointerModel(StructModel(NpArray { sizet })), ndarray_ptr)
.returning_void();
}
pub fn call_nac3_ndarray_nbytes<'ctx>(
ctx: &mut CodeGenContext<'ctx, '_>,
ndarray_ptr: Pointer<'ctx, StructModel<NpArray<'ctx>>>,
) -> Int<'ctx> {
let sizet = ndarray_ptr.element.0.sizet;
FunctionBuilder::begin(ctx, &get_sized_dependent_function_name(sizet, "__nac3_ndarray_nbytes"))
.arg("ndarray", PointerModel(StructModel(NpArray { sizet })), ndarray_ptr)
.returning("nbytes", sizet)
}
pub fn call_nac3_ndarray_fill_generic<'ctx>(
ctx: &mut CodeGenContext<'ctx, '_>,
ndarray_ptr: Pointer<'ctx, StructModel<NpArray<'ctx>>>,
fill_value_ptr: Pointer<'ctx, ByteModel>,
) {
let sizet = ndarray_ptr.element.0.sizet;
FunctionBuilder::begin(
ctx,
&get_sized_dependent_function_name(sizet, "__nac3_ndarray_fill_generic"),
)
.arg("ndarray", PointerModel(StructModel(NpArray { sizet })), ndarray_ptr)
.arg("pvalue", PointerModel(FixedIntModel(Byte)), fill_value_ptr)
.returning_void();
}
pub fn call_nac3_ndarray_len<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
ndarray_ptr: Pointer<'ctx, StructModel<NpArray<'ctx>>>,
) -> SliceIndex<'ctx> {
let sizet = ndarray_ptr.element.0.sizet;
let slice_index_model = SliceIndexModel::default();
let dst_len = slice_index_model.alloca(ctx, "dst_len");
let errctx = prepare_error_context(ctx);
FunctionBuilder::begin(ctx, &get_sized_dependent_function_name(sizet, "__nac3_ndarray_len"))
.arg("errctx", PointerModel(StructModel(ErrorContext)), errctx)
.arg("ndarray", PointerModel(StructModel(NpArray { sizet })), ndarray_ptr)
.arg("dst_len", PointerModel(slice_index_model), dst_len)
.returning_void();
check_error_context(generator, ctx, errctx);
dst_len.load(ctx, "len")
}

162
nac3core/src/codegen/irrt/numpy/shape.rs Normal file
View File

@ -0,0 +1,162 @@
use inkwell::values::BasicValueEnum;
use crate::{
codegen::{
classes::{ListValue, UntypedArrayLikeAccessor},
model::*,
stmt::gen_for_callback_incrementing,
CodeGenContext, CodeGenerator,
},
typecheck::typedef::{Type, TypeEnum},
};
pub type ProducerWriteToArray<'ctx, G, E> = Box<
dyn Fn(&mut G, &mut CodeGenContext<'ctx, '_>, &ArraySlice<'ctx, E>) -> Result<(), String>
+ 'ctx,
>;
pub struct Producer<'ctx, G: CodeGenerator + ?Sized, E: Model<'ctx>> {
pub count: Int<'ctx>,
pub write_to_array: ProducerWriteToArray<'ctx, G, E>,
}
/// TODO: UPDATE DOCUMENTATION
/// LLVM-typed implementation for generating a [`Producer`] that sets a list of ints.
///
/// * `elem_ty` - The element type of the `NDArray`.
/// * `shape` - The `shape` parameter used to construct the `NDArray`.
///
/// ### Notes on `shape`
///
/// Just like numpy, the `shape` argument can be:
/// 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])`
///
/// See also [`typecheck::type_inferencer::fold_numpy_function_call_shape_argument`] to
/// learn how `shape` gets from being a Python user expression to here.
pub fn parse_input_shape_arg<'ctx, G>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
shape: BasicValueEnum<'ctx>,
shape_ty: Type,
) -> Producer<'ctx, G, IntModel<'ctx>>
where
G: CodeGenerator + ?Sized,
{
let sizet = IntModel(generator.get_size_type(ctx.ctx));
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 ints; e.g., `np.empty([600, 800, 3])`
// A list has to be a PointerValue
let shape_list = ListValue::from_ptr_val(shape.into_pointer_value(), sizet.0, None);
// Create `Producer`
let ndims = Int(shape_list.load_size(ctx, Some("count")));
Producer {
count: ndims,
write_to_array: Box::new(move |ctx, generator, dst_array| {
// Basically iterate through the list and write to `dst_slice` accordingly
let init_val = sizet.constant(0).0;
let max_val = (ndims.0, false);
let incr_val = sizet.constant(1).0;
gen_for_callback_incrementing(
ctx,
generator,
init_val,
max_val,
|generator, ctx, _hooks, axis| {
let axis = Int(axis);
// Get the dimension at `axis`
let dim = shape_list
.data()
.get(ctx, generator, &axis.0, None)
.into_int_value();
// Cast `dim` to SizeT
let dim = ctx
.builder
.build_int_s_extend_or_bit_cast(dim, sizet.0, "dim_casted")
.unwrap();
// Write
dst_array.ix(generator, ctx, axis, "dim").store(ctx, Int(dim));
Ok(())
},
incr_val,
)
}),
}
}
TypeEnum::TTuple { ty: tuple_types } => {
// 2. A tuple of ints; e.g., `np.empty((600, 800, 3))`
// Get the length/size of the tuple, which also happens to be the value of `ndims`.
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_tuple = shape.into_struct_value();
Producer {
count: sizet.constant(ndims as u64),
write_to_array: Box::new(move |generator, ctx, dst_array| {
for axis in 0..ndims {
// Get the dimension at `axis`
let dim = ctx
.builder
.build_extract_value(
shape_tuple,
axis as u32,
format!("dim{axis}").as_str(),
)
.unwrap()
.into_int_value();
// Cast `dim` to SizeT
let dim = ctx
.builder
.build_int_s_extend_or_bit_cast(dim, sizet.0, "dim_casted")
.unwrap();
// Write
dst_array
.ix(generator, ctx, sizet.constant(axis as u64), "dim")
.store(ctx, Int(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();
Producer {
count: sizet.constant(1),
write_to_array: Box::new(move |generator, ctx, dst_array| {
// Cast `shape_int` to SizeT
let dim = ctx
.builder
.build_int_s_extend_or_bit_cast(shape_int, sizet.0, "dim_casted")
.unwrap();
// Set shape[0] = shape_int
dst_array.ix(generator, ctx, sizet.constant(0), "dim").store(ctx, Int(dim));
Ok(())
}),
}
}
_ => panic!("parse_input_shape_arg encountered unknown type"),
}
}

86
nac3core/src/codegen/irrt/numpy/slice.rs Normal file
View File

@ -0,0 +1,86 @@
use crate::codegen::{model::*, CodeGenContext};
// nac3core's slicing index/length values are always int32_t
pub type SliceIndexInt = Int32;
pub type SliceIndexModel = FixedIntModel<SliceIndexInt>;
pub type SliceIndex<'ctx> = FixedInt<'ctx, SliceIndexInt>;
#[derive(Debug, Clone)]
pub struct UserSliceFields {
pub start_defined: Field<BoolModel>,
pub start: Field<SliceIndexModel>,
pub stop_defined: Field<BoolModel>,
pub stop: Field<SliceIndexModel>,
pub step_defined: Field<BoolModel>,
pub step: Field<SliceIndexModel>,
}
#[derive(Debug, Clone, Copy, Default)]
pub struct UserSlice;
impl<'ctx> IsStruct<'ctx> for UserSlice {
type Fields = UserSliceFields;
fn struct_name(&self) -> &'static str {
"UserSlice"
}
fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields {
Self::Fields {
start_defined: builder.add_field_auto("start_defined"),
start: builder.add_field_auto("start"),
stop_defined: builder.add_field_auto("stop_defined"),
stop: builder.add_field_auto("stop"),
step_defined: builder.add_field_auto("step_defined"),
step: builder.add_field_auto("step"),
}
}
}
#[derive(Debug, Clone)]
pub struct RustUserSlice<'ctx> {
pub start: Option<SliceIndex<'ctx>>,
pub stop: Option<SliceIndex<'ctx>>,
pub step: Option<SliceIndex<'ctx>>,
}
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,
ctx: &CodeGenContext<'ctx, '_>,
dst_slice_ptr: Pointer<'ctx, StructModel<UserSlice>>,
) {
// TODO: make this neater, with a helper lambda?
let bool_model = BoolModel::default();
let false_ = bool_model.constant(ctx.ctx, 0);
let true_ = bool_model.constant(ctx.ctx, 1);
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_),
}
}
}

181
nac3core/src/codegen/irrt/numpy/subscript.rs Normal file
View File

@ -0,0 +1,181 @@
use crate::codegen::{
irrt::{
error_context::{check_error_context, prepare_error_context, ErrorContext},
util::{get_sized_dependent_function_name, FunctionBuilder},
},
model::*,
CodeGenContext, CodeGenerator,
};
use super::{
ndarray::NpArray,
slice::{RustUserSlice, SliceIndex, SliceIndexModel, UserSlice},
};
#[derive(Debug, Clone, Copy)]
pub struct NDSubscriptFields {
pub type_: Field<ByteModel>, // Defined to be uint8_t in IRRT
pub data: Field<PointerModel<ByteModel>>,
}
#[derive(Debug, Clone, Copy, Default)]
pub struct NDSubscript;
impl<'ctx> IsStruct<'ctx> for NDSubscript {
type Fields = NDSubscriptFields;
fn struct_name(&self) -> &'static str {
"NDSubscript"
}
fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields {
Self::Fields { type_: builder.add_field_auto("type"), data: builder.add_field_auto("data") }
}
}
// An enum variant to store the content
// and type of an NDSubscript in high level.
#[derive(Debug, Clone)]
pub enum RustNDSubscript<'ctx> {
Index(SliceIndex<'ctx>),
Slice(RustUserSlice<'ctx>),
}
impl<'ctx> RustNDSubscript<'ctx> {
fn irrt_subscript_id(&self) -> u64 {
// Defined in IRRT
match self {
RustNDSubscript::Index(_) => 0,
RustNDSubscript::Slice(_) => 1,
}
}
fn write_to_ndsubscript(
&self,
ctx: &CodeGenContext<'ctx, '_>,
dst_ndsubscript_ptr: Pointer<'ctx, StructModel<NDSubscript>>,
) {
let byte_model = ByteModel::default();
let slice_index_model = SliceIndexModel::default();
let user_slice_model = StructModel(UserSlice);
// Set `dst_ndsubscript_ptr->type`
dst_ndsubscript_ptr
.gep(ctx, |f| f.type_)
.store(ctx, byte_model.constant(ctx.ctx, self.irrt_subscript_id()));
// Set `dst_ndsubscript_ptr->data`
let data = match self {
RustNDSubscript::Index(in_index) => {
let index_ptr = slice_index_model.alloca(ctx, "index");
index_ptr.store(ctx, *in_index);
index_ptr.cast_to(ctx, FixedIntModel(Byte), "")
}
RustNDSubscript::Slice(in_rust_slice) => {
let user_slice_ptr = user_slice_model.alloca(ctx, "user_slice");
in_rust_slice.write_to_user_slice(ctx, user_slice_ptr);
user_slice_ptr.cast_to(ctx, FixedIntModel(Byte), "")
}
};
dst_ndsubscript_ptr.gep(ctx, |f| f.data).store(ctx, data);
}
// Allocate an array of subscripts onto the stack and return its stack pointer
pub fn alloca_subscripts(
ctx: &CodeGenContext<'ctx, '_>,
subscripts: &[RustNDSubscript<'ctx>],
) -> ArraySlice<'ctx, StructModel<NDSubscript>> {
let index_model = Int32Model::default();
let ndsubscript_model = StructModel(NDSubscript);
let ndsubscript_array = ndsubscript_model.array_alloca(
ctx,
index_model.constant(ctx.ctx, subscripts.len() as u64).to_int(),
"ndsubscripts",
);
for (i, rust_ndsubscript) in subscripts.iter().enumerate() {
let ndsubscript_ptr = ndsubscript_array.ix_unchecked(
ctx,
index_model.constant(ctx.ctx, i as u64).to_int(),
"",
);
rust_ndsubscript.write_to_ndsubscript(ctx, ndsubscript_ptr);
}
ndsubscript_array
}
#[must_use]
pub fn deduce_ndims_after_slicing(slices: &[RustNDSubscript], original_ndims: i32) -> i32 {
let mut final_ndims: i32 = original_ndims;
for slice in slices {
match slice {
RustNDSubscript::Index(_) => {
// Index subscripts demotes the rank by 1
final_ndims -= 1;
}
RustNDSubscript::Slice(_) => {
// Nothing
}
}
}
final_ndims
}
}
pub fn call_nac3_ndarray_subscript_deduce_ndims_after_slicing<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
sizet: IntModel<'ctx>,
ndims: Int<'ctx>,
num_ndsubscripts: Int<'ctx>,
ndsubscripts: Pointer<'ctx, StructModel<NDSubscript>>,
) -> Int<'ctx> {
let result = sizet.alloca(ctx, "result");
let errctx_ptr = prepare_error_context(ctx);
FunctionBuilder::begin(
ctx,
&get_sized_dependent_function_name(
sizet,
"__nac3_ndarray_subscript_deduce_ndims_after_slicing",
),
)
.arg("errctx", PointerModel(StructModel(ErrorContext)), errctx_ptr)
.arg("result", PointerModel(sizet), result)
.arg("ndims", sizet, ndims)
.arg("num_ndsubscripts", sizet, num_ndsubscripts)
.arg("ndsubscripts", PointerModel(StructModel(NDSubscript)), ndsubscripts)
.returning_void();
check_error_context(generator, ctx, errctx_ptr);
result.load(ctx, "final_ndims")
}
pub fn call_nac3_ndarray_subscript<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
num_subscripts: SliceIndex<'ctx>,
subscripts: Pointer<'ctx, StructModel<NDSubscript>>,
src_ndarray: Pointer<'ctx, StructModel<NpArray<'ctx>>>,
dst_ndarray: Pointer<'ctx, StructModel<NpArray<'ctx>>>,
) {
let sizet = src_ndarray.element.0.sizet;
assert!(sizet.same_as(dst_ndarray.element.0.sizet)); // SizeT of src_ndarray and dst_ndarray must match
let errctx_ptr = prepare_error_context(ctx);
FunctionBuilder::begin(
ctx,
&get_sized_dependent_function_name(sizet, "__nac3_ndarray_subscript"),
)
.arg("errctx", PointerModel(StructModel(ErrorContext)), errctx_ptr)
.arg("num_subscripts", SliceIndexModel::default(), num_subscripts)
.arg("subscripts", PointerModel(StructModel(NDSubscript)), subscripts)
.arg("src_ndarray", PointerModel(StructModel(NpArray { sizet })), src_ndarray)
.arg("dst_ndarray", PointerModel(StructModel(NpArray { sizet })), dst_ndarray)
.returning_void();
check_error_context(generator, ctx, errctx_ptr);
}

26
nac3core/src/codegen/irrt/test.rs Normal file
View File

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

79
nac3core/src/codegen/irrt/util.rs Normal file
View File

@ -0,0 +1,79 @@
use inkwell::{
types::{BasicMetadataTypeEnum, BasicType, IntType},
values::{AnyValue, BasicMetadataValueEnum},
};
use crate::{
codegen::{model::*, CodeGenContext},
util::SizeVariant,
};
fn get_size_variant(ty: IntType) -> SizeVariant {
match ty.get_bit_width() {
32 => SizeVariant::Bits32,
64 => SizeVariant::Bits64,
_ => unreachable!("Unsupported int type bit width {}", ty.get_bit_width()),
}
}
#[must_use]
pub fn get_sized_dependent_function_name(ty: IntModel, fn_name: &str) -> String {
let mut fn_name = fn_name.to_owned();
match get_size_variant(ty.0) {
SizeVariant::Bits32 => {
// Do nothing, `fn_name` already has the correct name
}
SizeVariant::Bits64 => {
// Append "64", this is the naming convention
fn_name.push_str("64");
}
}
fn_name
}
// TODO: Variadic argument?
pub struct FunctionBuilder<'ctx, 'a> {
ctx: &'a CodeGenContext<'ctx, 'a>,
fn_name: &'a str,
arguments: Vec<(BasicMetadataTypeEnum<'ctx>, BasicMetadataValueEnum<'ctx>)>,
}
impl<'ctx, 'a> FunctionBuilder<'ctx, 'a> {
pub fn begin(ctx: &'a CodeGenContext<'ctx, 'a>, fn_name: &'a str) -> Self {
FunctionBuilder { ctx, fn_name, arguments: Vec::new() }
}
// The name is for self-documentation
#[must_use]
pub fn arg<M: Model<'ctx>>(mut self, _name: &'static str, model: M, value: M::Value) -> Self {
self.arguments
.push((model.get_llvm_type(self.ctx.ctx).into(), value.get_llvm_value().into()));
self
}
pub fn returning<M: Model<'ctx>>(self, name: &'static str, return_model: M) -> M::Value {
let (param_tys, param_vals): (Vec<_>, Vec<_>) = self.arguments.into_iter().unzip();
let function = self.ctx.module.get_function(self.fn_name).unwrap_or_else(|| {
let return_type = return_model.get_llvm_type(self.ctx.ctx);
let fn_type = return_type.fn_type(&param_tys, false);
self.ctx.module.add_function(self.fn_name, fn_type, None)
});
let ret = self.ctx.builder.build_call(function, &param_vals, name).unwrap();
return_model.review(self.ctx.ctx, ret.as_any_value_enum())
}
// TODO: Code duplication, but otherwise returning<S: Optic<'ctx>> cannot resolve S if return_optic = None
pub fn returning_void(self) {
let (param_tys, param_vals): (Vec<_>, Vec<_>) = self.arguments.into_iter().unzip();
let function = self.ctx.module.get_function(self.fn_name).unwrap_or_else(|| {
let return_type = self.ctx.ctx.void_type();
let fn_type = return_type.fn_type(&param_tys, false);
self.ctx.module.add_function(self.fn_name, fn_type, None)
});
self.ctx.builder.build_call(function, &param_vals, "").unwrap();
}
}

55
nac3core/src/codegen/llvm_intrinsics.rs
View File

@ -35,38 +35,52 @@ 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)
/// Invokes the [`llvm.lifetime.start`](https://releases.llvm.org/14.0.0/docs/LangRef.html#llvm-lifetime-start-intrinsic)
/// intrinsic.
pub fn call_va_start<'ctx>(ctx: &CodeGenContext<'ctx, '_>, arglist: PointerValue<'ctx>) {
const FN_NAME: &str = "llvm.va_start";
pub fn call_lifetime_start<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
size: IntValue<'ctx>,
ptr: PointerValue<'ctx>,
) {
const FN_NAME: &str = "llvm.lifetime.start";
// NOTE: inkwell temporary workaround, see [`call_stackrestore`] for details
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);
let llvm_i64 = ctx.ctx.i64_type();
let llvm_p0i8 = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
let fn_type = llvm_void.fn_type(&[llvm_i64.into(), llvm_p0i8.into()], false);
ctx.module.add_function(FN_NAME, fn_type, None)
});
ctx.builder.build_call(intrinsic_fn, &[arglist.into()], "").unwrap();
ctx.builder
.build_call(intrinsic_fn, &[size.into(), ptr.into()], "")
.map(CallSiteValue::try_as_basic_value)
.unwrap();
}
/// Invokes the [`llvm.va_start`](https://llvm.org/docs/LangRef.html#llvm-va-start-intrinsic)
/// Invokes the [`llvm.lifetime.end`](https://releases.llvm.org/14.0.0/docs/LangRef.html#llvm-lifetime-end-intrinsic)
/// intrinsic.
pub fn call_va_end<'ctx>(ctx: &CodeGenContext<'ctx, '_>, arglist: PointerValue<'ctx>) {
const FN_NAME: &str = "llvm.va_end";
pub fn call_lifetime_end<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
size: IntValue<'ctx>,
ptr: PointerValue<'ctx>,
) {
const FN_NAME: &str = "llvm.lifetime.end";
// NOTE: inkwell temporary workaround, see [`call_stackrestore`] for details
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);
let llvm_i64 = ctx.ctx.i64_type();
let llvm_p0i8 = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
let fn_type = llvm_void.fn_type(&[llvm_i64.into(), llvm_p0i8.into()], false);
ctx.module.add_function(FN_NAME, fn_type, None)
});
ctx.builder.build_call(intrinsic_fn, &[arglist.into()], "").unwrap();
ctx.builder
.build_call(intrinsic_fn, &[size.into(), ptr.into()], "")
.map(CallSiteValue::try_as_basic_value)
.unwrap();
}
/// Invokes the [`llvm.stacksave`](https://llvm.org/docs/LangRef.html#llvm-stacksave-intrinsic)
@ -205,9 +219,8 @@ 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
/// * `,($val:ident)*`: Comma separated list of operands
macro_rules! generate_llvm_intrinsic_fn_body {
@ -223,8 +236,8 @@ macro_rules! generate_llvm_intrinsic_fn_body {
/// Arguments:
/// * `float/int`: Indicates the return and argument type of the function
/// * `$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 {

140
nac3core/src/codegen/mod.rs
View File

@ -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},
@ -23,7 +23,9 @@ use inkwell::{
values::{BasicValueEnum, FunctionValue, IntValue, PhiValue, PointerValue},
AddressSpace, IntPredicate, OptimizationLevel,
};
use irrt::{error_context::Str, numpy::ndarray::NpArray};
use itertools::Itertools;
use model::*;
use nac3parser::ast::{Location, Stmt, StrRef};
use parking_lot::{Condvar, Mutex};
use std::collections::{HashMap, HashSet};
@ -41,7 +43,9 @@ 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;
#[cfg(test)]
@ -50,22 +54,6 @@ 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>,
@ -84,16 +72,6 @@ pub struct CodeGenLLVMOptions {
pub target: CodeGenTargetMachineOptions,
}
impl CodeGenLLVMOptions {
/// Creates a [`TargetMachine`] using the target options specified by this struct.
///
/// See [`Target::create_target_machine`].
#[must_use]
pub fn create_target_machine(&self) -> Option<TargetMachine> {
self.target.create_target_machine(self.opt_level)
}
}
/// Additional options for code generation for the target machine.
#[derive(Clone, Debug, Eq, PartialEq)]
pub struct CodeGenTargetMachineOptions {
@ -364,10 +342,6 @@ impl WorkerRegistry {
let mut builder = context.create_builder();
let mut module = context.create_module(generator.get_name());
let target_machine = self.llvm_options.create_target_machine().unwrap();
module.set_data_layout(&target_machine.get_target_data().get_data_layout());
module.set_triple(&target_machine.get_triple());
module.add_basic_value_flag(
"Debug Info Version",
inkwell::module::FlagBehavior::Warning,
@ -391,10 +365,6 @@ impl WorkerRegistry {
errors.insert(e);
// create a new empty module just to continue codegen and collect errors
module = context.create_module(&format!("{}_recover", generator.get_name()));
let target_machine = self.llvm_options.create_target_machine().unwrap();
module.set_data_layout(&target_machine.get_target_data().get_data_layout());
module.set_triple(&target_machine.get_triple());
}
}
*self.task_count.lock() -= 1;
@ -460,7 +430,7 @@ 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 +475,8 @@ 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 sizet = IntModel(generator.get_size_type(ctx));
PointerModel(StructModel(NpArray { sizet })).get_llvm_type(ctx)
}
_ => unreachable!(
@ -554,10 +520,8 @@ 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 +551,7 @@ 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 +560,11 @@ 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 +589,6 @@ 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,
@ -716,7 +646,7 @@ pub fn gen_func_impl<
..primitives
};
let mut type_cache: HashMap<_, _> = [
let mut type_cache: HashMap<_, BasicTypeEnum<'_>> = [
(primitives.int32, context.i32_type().into()),
(primitives.int64, context.i64_type().into()),
(primitives.uint32, context.i32_type().into()),
@ -724,19 +654,8 @@ pub fn gen_func_impl<
(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(),
}
let sizet = IntModel(generator.get_size_type(context));
StructModel(Str { sizet }).get_llvm_type(context)
}),
(primitives.range, RangeType::new(context).as_base_type().into()),
(primitives.exception, {
@ -744,10 +663,12 @@ pub fn gen_func_impl<
if let Some(t) = module.get_struct_type(name) {
t.ptr_type(AddressSpace::default()).as_basic_type_enum()
} else {
let sizet = IntModel(generator.get_size_type(context));
let str_ty = StructModel(Str { sizet }).get_llvm_type(context);
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()
@ -770,7 +691,6 @@ 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 +713,7 @@ 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 +732,9 @@ pub fn gen_func_impl<
params.insert(0, ret_type.unwrap().ptr_type(AddressSpace::default()).into());
}
debug_assert!(matches!(args.iter().filter(|arg| arg.is_vararg).count(), 0..=1));
let vararg_arg = args.iter().find(|arg| arg.is_vararg);
let fn_type = match ret_type {
Some(ret_type) if !has_sret => ret_type.fn_type(&params, vararg_arg.is_some()),
_ => context.void_type().fn_type(&params, vararg_arg.is_some()),
Some(ret_type) if !has_sret => ret_type.fn_type(&params, false),
_ => context.void_type().fn_type(&params, false),
};
let symbol = &task.symbol_name;
@ -850,9 +764,7 @@ 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 +797,6 @@ 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 +1019,3 @@ 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()
}

70
nac3core/src/codegen/model/core.rs Normal file
View File

@ -0,0 +1,70 @@
use inkwell::{
context::Context,
types::{AnyTypeEnum, BasicTypeEnum},
values::{AnyValueEnum, BasicValueEnum},
};
use crate::codegen::CodeGenContext;
use super::{slice::ArraySlice, Int, Pointer};
pub trait ModelValue<'ctx>: Clone + Copy {
fn get_llvm_value(&self) -> BasicValueEnum<'ctx>;
}
// Should have been within [`Model<'ctx>`],
// but rust object safety requirements made it necessary to
// split this interface out
pub trait CanCheckLLVMType<'ctx> {
/// Check if `scrutinee` matches the same LLVM type of this [`Model<'ctx>`].
///
/// If they don't not match, a human-readable error message is returned.
fn check_llvm_type(
&self,
ctx: &'ctx Context,
scrutinee: AnyTypeEnum<'ctx>,
) -> Result<(), String>;
}
/// A [`Model`] is a type-safe concrete representation of a complex LLVM type.
pub trait Model<'ctx>: Clone + Copy + CanCheckLLVMType<'ctx> + Sized {
/// The values that inhabit this [`Model<'ctx>`].
///
/// ...that is the type of wrapper that wraps the LLVM values that inhabit [`Model<'ctx>::get_llvm_type()`].
type Value: ModelValue<'ctx>;
/// Get the [`BasicTypeEnum<'ctx>`] this [`Model<'ctx>`] is representing.
fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx>;
/// Cast an [`AnyValueEnum<'ctx>`] into a [`Self::Value`].
///
/// Panics if `value` cannot pass [`CanCheckLLVMType::check_llvm_type()`].
fn review(&self, ctx: &'ctx Context, value: AnyValueEnum<'ctx>) -> Self::Value;
/// Build an instruction to allocate a value of [`Model::get_llvm_type`].
fn alloca(&self, ctx: &CodeGenContext<'ctx, '_>, name: &str) -> Pointer<'ctx, Self> {
Pointer {
element: *self,
value: ctx.builder.build_alloca(self.get_llvm_type(ctx.ctx), name).unwrap(),
}
}
/// Build an instruction to allocate an array of [`Model::get_llvm_type`].
fn array_alloca(
&self,
ctx: &CodeGenContext<'ctx, '_>,
count: Int<'ctx>,
name: &str,
) -> ArraySlice<'ctx, Self> {
ArraySlice {
num_elements: count,
pointer: Pointer {
element: *self,
value: ctx
.builder
.build_array_alloca(self.get_llvm_type(ctx.ctx), count.0, name)
.unwrap(),
},
}
}
}

220
nac3core/src/codegen/model/gep.rs Normal file
View File

@ -0,0 +1,220 @@
use inkwell::{
context::Context,
types::{AnyType, AnyTypeEnum, BasicType, BasicTypeEnum, StructType},
values::{AnyValueEnum, BasicValue, BasicValueEnum, StructValue},
};
use itertools::{izip, Itertools};
use crate::codegen::CodeGenContext;
use super::{core::CanCheckLLVMType, Model, ModelValue, Pointer};
#[derive(Debug, Clone, Copy)]
pub struct Field<E> {
pub gep_index: u64,
pub name: &'static str,
pub element: E,
}
// Like [`Field<E>`] but element must be [`BasicTypeEnum<'ctx>`]
struct FieldLLVM<'ctx> {
gep_index: u64,
name: &'ctx str,
llvm_type: BasicTypeEnum<'ctx>,
// Only CanCheckLLVMType is needed, dont put in the whole `Model<'ctx>`
llvm_type_model: Box<dyn CanCheckLLVMType<'ctx> + 'ctx>,
}
pub struct FieldBuilder<'ctx> {
pub ctx: &'ctx Context,
gep_index_counter: u64,
struct_name: &'ctx str,
fields: Vec<FieldLLVM<'ctx>>,
}
impl<'ctx> FieldBuilder<'ctx> {
#[must_use]
pub fn new(ctx: &'ctx Context, struct_name: &'ctx str) -> Self {
FieldBuilder { ctx, gep_index_counter: 0, struct_name, fields: Vec::new() }
}
fn next_gep_index(&mut self) -> u64 {
let index = self.gep_index_counter;
self.gep_index_counter += 1;
index
}
pub fn add_field<E: Model<'ctx> + 'ctx>(&mut self, name: &'static str, element: E) -> Field<E> {
let gep_index = self.next_gep_index();
self.fields.push(FieldLLVM {
gep_index,
name,
llvm_type: element.get_llvm_type(self.ctx),
llvm_type_model: Box::new(element),
});
Field { gep_index, name, element }
}
pub fn add_field_auto<E: Model<'ctx> + Default + 'ctx>(
&mut self,
name: &'static str,
) -> Field<E> {
self.add_field(name, E::default())
}
}
/// A marker trait to mark singleton struct that describes a particular LLVM structure.
pub trait IsStruct<'ctx>: Clone + Copy {
/// The type of the Rust `struct` that holds all the fields of this LLVM struct.
type Fields;
/// A cosmetic name for this struct.
/// TODO: Currently unused. To be used in error reporting.
fn struct_name(&self) -> &'static str;
fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields;
fn get_fields(&self, ctx: &'ctx Context) -> Self::Fields {
let mut builder = FieldBuilder::new(ctx, self.struct_name());
self.build_fields(&mut builder)
}
/// Get the LLVM struct type this [`IsStruct<'ctx>`] is representing.
fn get_struct_type(&self, ctx: &'ctx Context) -> StructType<'ctx> {
let mut builder = FieldBuilder::new(ctx, self.struct_name());
self.build_fields(&mut builder); // Self::Fields is discarded
let field_types = builder.fields.iter().map(|f| f.llvm_type).collect_vec();
ctx.struct_type(&field_types, false)
}
/// Check if `scrutinee` matches the [`StructType<'ctx>`] this [`IsStruct<'ctx>`] is representing.
fn check_struct_type(
&self,
ctx: &'ctx Context,
scrutinee: StructType<'ctx>,
) -> Result<(), String> {
// Details about scrutinee
let scrutinee_field_types = scrutinee.get_field_types();
// Details about the defined specifications of this struct
// We will access them through builder
let mut builder = FieldBuilder::new(ctx, self.struct_name());
self.build_fields(&mut builder);
// Check # of fields
if builder.fields.len() != scrutinee_field_types.len() {
return Err(format!(
"Expecting struct to have {} field(s), but scrutinee has {} field(s)",
builder.fields.len(),
scrutinee_field_types.len()
));
}
// Check the types of each field
// TODO: Traceback?
for (f, scrutinee_field_type) in izip!(builder.fields, scrutinee_field_types) {
f.llvm_type_model.check_llvm_type(ctx, scrutinee_field_type.as_any_type_enum())?;
}
Ok(())
}
}
/// A [`Model<'ctx>`] that represents an LLVM struct.
///
/// `self.0` contains a [`IsStruct<'ctx>`] that gives the details of the LLVM struct.
#[derive(Debug, Clone, Copy)]
pub struct StructModel<S>(pub S);
impl<'ctx, S: IsStruct<'ctx>> CanCheckLLVMType<'ctx> for StructModel<S> {
fn check_llvm_type(
&self,
ctx: &'ctx Context,
scrutinee: AnyTypeEnum<'ctx>,
) -> Result<(), String> {
// Check if scrutinee is even a struct type
let AnyTypeEnum::StructType(scrutinee) = scrutinee else {
return Err(format!("Expecting a struct type, but got {scrutinee:?}"));
};
// Ok. now check the struct type *thoroughly*
self.0.check_struct_type(ctx, scrutinee)
}
}
impl<'ctx, S: IsStruct<'ctx>> Model<'ctx> for StructModel<S> {
type Value = Struct<'ctx, S>; // TODO: enrich it
fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
self.0.get_struct_type(ctx).as_basic_type_enum()
}
fn review(&self, ctx: &'ctx Context, value: AnyValueEnum<'ctx>) -> Self::Value {
// Check that `value` is not some bogus values or an incorrect StructValue
self.check_llvm_type(ctx, value.get_type()).unwrap();
Struct { structure: self.0, value: value.into_struct_value() }
}
}
#[derive(Debug, Clone, Copy)]
pub struct Struct<'ctx, S> {
pub structure: S,
pub value: StructValue<'ctx>,
}
impl<'ctx, S: IsStruct<'ctx>> ModelValue<'ctx> for Struct<'ctx, S> {
fn get_llvm_value(&self) -> BasicValueEnum<'ctx> {
self.value.as_basic_value_enum()
}
}
impl<'ctx, S: IsStruct<'ctx>> Pointer<'ctx, StructModel<S>> {
/// Build an instruction that does `getelementptr` on an LLVM structure referenced by this pointer.
///
/// This provides a nice syntax to chain up `getelementptr` in an intuitive and type-safe way:
///
/// ```ignore
/// let ctx: &CodeGenContext<'ctx, '_>;
/// let ndarray: Pointer<'ctx, StructModel<NpArray<'ctx>>>;
/// ndarray.gep(ctx, |f| f.ndims).store();
/// ```
///
/// You might even write chains `gep`, i.e.,
/// ```ignore
/// my_struct
/// .gep(ctx, |f| f.thing1)
/// .gep(ctx, |f| f.value)
/// .store(ctx, my_value) // Equivalent to `my_struct.thing1.value = my_value`
/// ```
pub fn gep<E, GetFieldFn>(
&self,
ctx: &CodeGenContext<'ctx, '_>,
get_field: GetFieldFn,
) -> Pointer<'ctx, E>
where
E: Model<'ctx>,
GetFieldFn: FnOnce(S::Fields) -> Field<E>,
{
let fields = self.element.0.get_fields(ctx.ctx);
let field = get_field(fields);
let llvm_i32 = ctx.ctx.i32_type(); // TODO: I think I'm not supposed to *just* use i32 for GEP like that
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()
};
Pointer { element: field.element, value: ptr }
}
}

279
nac3core/src/codegen/model/int.rs Normal file
View File

@ -0,0 +1,279 @@
use inkwell::{
context::Context,
types::{AnyType, AnyTypeEnum, BasicType, BasicTypeEnum, IntType},
values::{AnyValueEnum, BasicValue, BasicValueEnum, IntValue},
};
use crate::codegen::CodeGenContext;
use super::core::*;
/// Helper function to check if `scrutinee` is the same as `expected_int_type`
fn check_int_llvm_type<'ctx>(
scrutinee: AnyTypeEnum<'ctx>,
expected_int_type: IntType<'ctx>,
) -> Result<(), String> {
// Check if llvm_type is int type
let AnyTypeEnum::IntType(scrutinee) = scrutinee else {
return Err(format!("Expecting an int type but got {scrutinee:?}"));
};
// Check bit width
if scrutinee.get_bit_width() != expected_int_type.get_bit_width() {
return Err(format!(
"Expecting an int type of {}-bit(s) but got int type {}-bit(s)",
expected_int_type.get_bit_width(),
scrutinee.get_bit_width()
));
}
Ok(())
}
/// Helper function to cast `scrutinee` is into an [`IntValue<'ctx>`].
/// The LLVM type of `scrutinee` will be checked with [`check_int_llvm_type`].
fn review_int_llvm_value<'ctx>(
value: AnyValueEnum<'ctx>,
expected_int_type: IntType<'ctx>,
) -> Result<IntValue<'ctx>, String> {
// Check if value is of int type, error if that is anything else
check_int_llvm_type(value.get_type().as_any_type_enum(), expected_int_type)?;
// Ok, it is must be an int
Ok(value.into_int_value())
}
/// A model representing an [`IntType<'ctx>`].
///
/// Also see [`FixedIntModel`], which is more constrained than [`IntModel`]
/// but provides more type-safe mechanisms and even auto-derivation of [`BasicTypeEnum<'ctx>`]
/// for creating LLVM structures.
#[derive(Debug, Clone, Copy)]
pub struct IntModel<'ctx>(pub IntType<'ctx>);
/// An inhabitant of an [`IntModel<'ctx>`]
#[derive(Debug, Clone, Copy)]
pub struct Int<'ctx>(pub IntValue<'ctx>);
impl<'ctx> CanCheckLLVMType<'ctx> for IntModel<'ctx> {
fn check_llvm_type(
&self,
_ctx: &'ctx Context,
scrutinee: AnyTypeEnum<'ctx>,
) -> Result<(), String> {
check_int_llvm_type(scrutinee, self.0)
}
}
impl<'ctx> Model<'ctx> for IntModel<'ctx> {
type Value = Int<'ctx>;
fn get_llvm_type(&self, _ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
self.0.as_basic_type_enum()
}
fn review(&self, ctx: &'ctx Context, value: AnyValueEnum<'ctx>) -> Self::Value {
let int = value.into_int_value();
self.check_llvm_type(ctx, int.get_type().as_any_type_enum()).unwrap();
Int(int)
}
}
impl<'ctx> ModelValue<'ctx> for Int<'ctx> {
fn get_llvm_value(&self) -> BasicValueEnum<'ctx> {
self.0.as_basic_value_enum()
}
}
// Extra utilities for [`Int<'ctx>`]
impl<'ctx> Int<'ctx> {
#[must_use]
pub fn signed_cast_to_int(
self,
ctx: &CodeGenContext<'ctx, '_>,
target_int: IntModel<'ctx>,
name: &str,
) -> Int<'ctx> {
Int(ctx.builder.build_int_s_extend_or_bit_cast(self.0, target_int.0, name).unwrap())
}
#[must_use]
pub fn signed_cast_to_fixed<T: IsFixedInt>(
self,
ctx: &CodeGenContext<'ctx, '_>,
target_fixed: T,
name: &str,
) -> FixedInt<'ctx, T> {
FixedInt {
int: target_fixed,
value: ctx
.builder
.build_int_s_extend_or_bit_cast(self.0, T::get_int_type(ctx.ctx), name)
.unwrap(),
}
}
}
// Extra utilities for [`IntModel<'ctx>`]
impl<'ctx> IntModel<'ctx> {
/// Create a constant value that inhabits this [`IntModel<'ctx>`].
#[must_use]
pub fn constant(&self, value: u64) -> Int<'ctx> {
Int(self.0.const_int(value, false))
}
/// Check if `other` is fully compatible with this [`IntModel<'ctx>`].
///
/// This simply checks if the underlying [`IntType<'ctx>`] has
/// the same number of bits.
#[must_use]
pub fn same_as(&self, other: IntModel<'ctx>) -> bool {
// TODO: or `self.0 == other.0` would also work?
self.0.get_bit_width() == other.0.get_bit_width()
}
}
/// A model representing a compile-time known [`IntType<'ctx>`].
///
/// Also see [`IntModel`], which is less constrained than [`FixedIntModel`],
/// but enables one to handle [`IntType<'ctx>`] that could be dynamic
#[derive(Debug, Clone, Copy, Default)]
pub struct FixedIntModel<T>(pub T);
impl<T: IsFixedInt> FixedIntModel<T> {
pub fn to_int_model(self, ctx: &Context) -> IntModel<'_> {
IntModel(T::get_int_type(ctx))
}
}
impl<'ctx, T: IsFixedInt> CanCheckLLVMType<'ctx> for FixedIntModel<T> {
fn check_llvm_type(
&self,
ctx: &'ctx Context,
scrutinee: AnyTypeEnum<'ctx>,
) -> Result<(), String> {
check_int_llvm_type(scrutinee, T::get_int_type(ctx))
}
}
impl<'ctx, T: IsFixedInt> Model<'ctx> for FixedIntModel<T> {
type Value = FixedInt<'ctx, T>;
fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
T::get_int_type(ctx).as_basic_type_enum()
}
fn review(&self, ctx: &'ctx Context, value: AnyValueEnum<'ctx>) -> Self::Value {
let value = review_int_llvm_value(value, T::get_int_type(ctx)).unwrap();
FixedInt { int: self.0, value }
}
}
impl<'ctx, T: IsFixedInt> FixedIntModel<T> {
pub fn constant(&self, ctx: &'ctx Context, value: u64) -> FixedInt<'ctx, T> {
FixedInt { int: self.0, value: T::get_int_type(ctx).const_int(value, false) }
}
}
/// An inhabitant of [`FixedIntModel<'ctx>`]
#[derive(Debug, Clone, Copy)]
pub struct FixedInt<'ctx, T: IsFixedInt> {
pub int: T,
pub value: IntValue<'ctx>,
}
/// A marker trait to mark singleton struct that describes a particular fixed integer type.
/// See [`Bool`], [`Byte`], [`Int32`], etc.
///
/// The [`Default`] trait is to enable auto-derivations for utilities like
/// [`FieldBuilder::add_field_auto`]
pub trait IsFixedInt: Clone + Copy + Default {
fn get_int_type(ctx: &Context) -> IntType<'_>;
fn get_bit_width() -> u32; // This is required, instead of only relying on get_int_type
}
impl<'ctx, T: IsFixedInt> ModelValue<'ctx> for FixedInt<'ctx, T> {
fn get_llvm_value(&self) -> BasicValueEnum<'ctx> {
self.value.as_basic_value_enum()
}
}
// Extra utilities for [`FixedInt<'ctx, T>`]
impl<'ctx, T: IsFixedInt> FixedInt<'ctx, T> {
pub fn to_int(self) -> Int<'ctx> {
Int(self.value)
}
pub fn signed_cast_to_fixed<R: IsFixedInt>(
self,
ctx: &CodeGenContext<'ctx, '_>,
target_fixed_int: R,
name: &str,
) -> FixedInt<'ctx, R> {
FixedInt {
int: target_fixed_int,
value: ctx
.builder
.build_int_s_extend_or_bit_cast(self.value, R::get_int_type(ctx.ctx), name)
.unwrap(),
}
}
}
// Some pre-defined fixed integers
#[derive(Debug, Clone, Copy, Default)]
pub struct Bool;
pub type BoolModel = FixedIntModel<Bool>;
impl IsFixedInt for Bool {
fn get_int_type(ctx: &Context) -> IntType<'_> {
ctx.bool_type()
}
fn get_bit_width() -> u32 {
1
}
}
#[derive(Debug, Clone, Copy, Default)]
pub struct Byte;
pub type ByteModel = FixedIntModel<Byte>;
impl IsFixedInt for Byte {
fn get_int_type(ctx: &Context) -> IntType<'_> {
ctx.i8_type()
}
fn get_bit_width() -> u32 {
8
}
}
#[derive(Debug, Clone, Copy, Default)]
pub struct Int32;
pub type Int32Model = FixedIntModel<Int32>;
impl IsFixedInt for Int32 {
fn get_int_type(ctx: &Context) -> IntType<'_> {
ctx.i32_type()
}
fn get_bit_width() -> u32 {
32
}
}
#[derive(Debug, Clone, Copy, Default)]
pub struct Int64;
pub type Int64Model = FixedIntModel<Int64>;
impl IsFixedInt for Int64 {
fn get_int_type(ctx: &Context) -> IntType<'_> {
ctx.i64_type()
}
fn get_bit_width() -> u32 {
64
}
}

11
nac3core/src/codegen/model/mod.rs Normal file
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@ -0,0 +1,11 @@
pub mod core;
pub mod gep;
pub mod int;
pub mod pointer;
pub mod slice;
pub use core::*;
pub use gep::*;
pub use int::*;
pub use pointer::*;
pub use slice::*;

184
nac3core/src/codegen/model/pointer.rs Normal file
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@ -0,0 +1,184 @@
use inkwell::{
context::Context,
types::{AnyTypeEnum, BasicType, BasicTypeEnum},
values::{AnyValue, AnyValueEnum, BasicValue, BasicValueEnum, PointerValue},
AddressSpace,
};
use crate::codegen::CodeGenContext;
use super::core::*;
/// An inhabitant of [`PointerModel<E>`]
#[derive(Debug, Clone, Copy)]
pub struct Pointer<'ctx, E: Model<'ctx>> {
pub element: E,
pub value: PointerValue<'ctx>,
}
/// A [`Model<'ctx>`] representing an LLVM [`PointerType<'ctx>`]
/// with *full* information on the element u
///
/// [`self.0`] contains [`Model<'ctx>`] that represents the
/// LLVM type of element of the [`PointerType<'ctx>`] is pointing at
/// (like `PointerType<'ctx>::get_element_type()`, but abstracted as a [`Model<'ctx>`]).
#[derive(Debug, Clone, Copy, Default)]
pub struct PointerModel<E>(pub E);
impl<'ctx, E: Model<'ctx>> ModelValue<'ctx> for Pointer<'ctx, E> {
fn get_llvm_value(&self) -> BasicValueEnum<'ctx> {
self.value.as_basic_value_enum()
}
}
impl<'ctx, E: Model<'ctx>> Pointer<'ctx, E> {
/// Build an instruction to store a value into this pointer
pub fn store(&self, ctx: &CodeGenContext<'ctx, '_>, val: E::Value) {
ctx.builder.build_store(self.value, val.get_llvm_value()).unwrap();
}
/// Build an instruction to load a value from this pointer
pub fn load(&self, ctx: &CodeGenContext<'ctx, '_>, name: &str) -> E::Value {
let val = ctx.builder.build_load(self.value, name).unwrap();
self.element.review(ctx.ctx, val.as_any_value_enum())
}
pub fn to_opaque(self) -> OpaquePointer<'ctx> {
OpaquePointer(self.value)
}
pub fn cast_opaque_to(
&self,
ctx: &CodeGenContext<'ctx, '_>,
element_type: BasicTypeEnum<'ctx>,
name: &str,
) -> OpaquePointer<'ctx> {
self.to_opaque().cast_opaque_to(ctx, element_type, name)
}
pub fn cast_to<R: Model<'ctx>>(
self,
ctx: &CodeGenContext<'ctx, '_>,
element_model: R,
name: &str,
) -> Pointer<'ctx, R> {
let casted_ptr =
self.to_opaque().cast_opaque_to(ctx, element_model.get_llvm_type(ctx.ctx), name).0;
Pointer { element: element_model, value: casted_ptr }
}
}
impl<'ctx, E: Model<'ctx>> CanCheckLLVMType<'ctx> for PointerModel<E> {
fn check_llvm_type(
&self,
ctx: &'ctx Context,
scrutinee: AnyTypeEnum<'ctx>,
) -> Result<(), String> {
// Check if scrutinee is even a PointerValue
let AnyTypeEnum::PointerType(scrutinee) = scrutinee else {
return Err(format!("Expecting a pointer value, but got {scrutinee:?}"));
};
// Check the type of what the pointer is pointing at
// TODO: This will be deprecated by inkwell > llvm14 because `get_element_type()` will be gone
self.0.check_llvm_type(ctx, scrutinee.get_element_type())?; // TODO: Include backtrace?
Ok(())
}
}
impl<'ctx, E: Model<'ctx>> Model<'ctx> for PointerModel<E> {
type Value = Pointer<'ctx, E>;
fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
self.0.get_llvm_type(ctx).ptr_type(AddressSpace::default()).as_basic_type_enum()
}
fn review(&self, ctx: &'ctx Context, value: AnyValueEnum<'ctx>) -> Self::Value {
self.check_llvm_type(ctx, value.get_type()).unwrap();
// TODO: Check get_element_type()? for LLVM 14 at least...
Pointer { element: self.0, value: value.into_pointer_value() }
}
}
// A pointer of which the element's model is unknown.
#[derive(Debug, Clone, Copy)]
pub struct OpaquePointer<'ctx>(pub PointerValue<'ctx>);
#[derive(Debug, Clone, Copy, Default)]
pub struct OpaquePointerModel;
impl<'ctx> ModelValue<'ctx> for OpaquePointer<'ctx> {
fn get_llvm_value(&self) -> BasicValueEnum<'ctx> {
self.0.as_basic_value_enum()
}
}
impl<'ctx> CanCheckLLVMType<'ctx> for OpaquePointerModel {
fn check_llvm_type(
&self,
_ctx: &'ctx Context,
scrutinee: AnyTypeEnum<'ctx>,
) -> Result<(), String> {
// OpaquePointerModel only cares that it is a pointer,
// but not what the pointer is pointing at
match scrutinee {
AnyTypeEnum::PointerType(_) => Ok(()),
_ => Err(format!("Expecting a pointer type, but got {scrutinee:?}")),
}
}
}
impl<'ctx> Model<'ctx> for OpaquePointerModel {
type Value = OpaquePointer<'ctx>;
fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
ctx.i8_type().ptr_type(AddressSpace::default()).as_basic_type_enum()
}
fn review(&self, ctx: &'ctx Context, value: AnyValueEnum<'ctx>) -> Self::Value {
// Check if value is even of a pointer type
self.check_llvm_type(ctx, value.get_type()).unwrap();
OpaquePointer(value.into_pointer_value())
}
}
impl<'ctx> OpaquePointer<'ctx> {
pub fn load_opaque(&self, ctx: &CodeGenContext<'ctx, '_>, name: &str) -> BasicValueEnum<'ctx> {
ctx.builder.build_load(self.0, name).unwrap()
}
pub fn store_opaque(&self, ctx: &CodeGenContext<'ctx, '_>, value: BasicValueEnum<'ctx>) {
ctx.builder.build_store(self.0, value).unwrap();
}
#[must_use]
pub fn cast_opaque_to(
self,
ctx: &CodeGenContext<'ctx, '_>,
element_llvm_type: BasicTypeEnum<'ctx>,
name: &str,
) -> OpaquePointer<'ctx> {
OpaquePointer(
ctx.builder
.build_pointer_cast(
self.0,
element_llvm_type.ptr_type(AddressSpace::default()),
name,
)
.unwrap(),
)
}
pub fn cast_to<E: Model<'ctx>>(
self,
ctx: &CodeGenContext<'ctx, '_>,
element_model: E,
name: &str,
) -> Pointer<'ctx, E> {
let ptr = self.cast_opaque_to(ctx, element_model.get_llvm_type(ctx.ctx), name).0;
Pointer { element: element_model, value: ptr }
}
}

73
nac3core/src/codegen/model/slice.rs Normal file
View File

@ -0,0 +1,73 @@
use crate::codegen::{CodeGenContext, CodeGenerator};
use super::{Int, Model, Pointer};
pub struct ArraySlice<'ctx, E: Model<'ctx>> {
pub num_elements: Int<'ctx>,
pub pointer: Pointer<'ctx, E>,
}
impl<'ctx, E: Model<'ctx>> ArraySlice<'ctx, E> {
pub fn ix_unchecked(
&self,
ctx: &CodeGenContext<'ctx, '_>,
idx: Int<'ctx>,
name: &str,
) -> Pointer<'ctx, E> {
let element_addr =
unsafe { ctx.builder.build_in_bounds_gep(self.pointer.value, &[idx.0], name).unwrap() };
Pointer { value: element_addr, element: self.pointer.element }
}
pub fn ix<G: CodeGenerator + ?Sized>(
&self,
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
idx: Int<'ctx>,
name: &str,
) -> Pointer<'ctx, E> {
let int_type = self.num_elements.0.get_type(); // NOTE: Weird get_type(), see comment under `trait Ixed`
assert_eq!(int_type.get_bit_width(), idx.0.get_type().get_bit_width()); // Might as well check bit width to catch bugs
// TODO: SGE or UGE? or make it defined by the implementee?
// Check `0 <= index`
let lower_bounded = ctx
.builder
.build_int_compare(
inkwell::IntPredicate::SLE,
int_type.const_zero(),
idx.0,
"lower_bounded",
)
.unwrap();
// Check `index < num_elements`
let upper_bounded = ctx
.builder
.build_int_compare(
inkwell::IntPredicate::SLT,
idx.0,
self.num_elements.0,
"upper_bounded",
)
.unwrap();
// Compute `0 <= index && index < num_elements`
let bounded = ctx.builder.build_and(lower_bounded, upper_bounded, "bounded").unwrap();
// Assert `bounded`
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.0), Some(self.num_elements.0), None],
ctx.current_loc
);
// ...and finally do indexing
self.ix_unchecked(ctx, idx, name)
}
}

554
nac3core/src/codegen/numpy.rs
View File

@ -9,10 +9,9 @@ use crate::{
irrt::{
calculate_len_for_slice_range, call_ndarray_calc_broadcast,
call_ndarray_calc_broadcast_index, call_ndarray_calc_nd_indices,
call_ndarray_calc_size,
call_ndarray_calc_size, error_context::call_nac3_dummy_raise,
},
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.
@ -90,7 +86,6 @@ where
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(shape_len, false),
|generator, ctx, _, i| {
@ -136,7 +131,6 @@ where
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(shape_len, false),
|generator, ctx, _, i| {
@ -163,7 +157,7 @@ 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 +252,9 @@ 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, "")
} else {
codegen_unreachable!(ctx)
unreachable!()
}
}
@ -286,9 +280,9 @@ 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")
} else {
codegen_unreachable!(ctx)
unreachable!()
}
}
@ -356,7 +350,7 @@ fn call_ndarray_empty_impl<'ctx, G: CodeGenerator + ?Sized>(
create_ndarray_const_shape(generator, ctx, elem_ty, &[shape_int])
}
_ => codegen_unreachable!(ctx),
_ => unreachable!(),
}
}
@ -388,7 +382,6 @@ where
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(ndarray_num_elems, false),
|generator, ctx, _, i| {
@ -545,6 +538,8 @@ fn call_ndarray_zeros_impl<'ctx, G: CodeGenerator + ?Sized>(
elem_ty: Type,
shape: BasicValueEnum<'ctx>,
) -> Result<NDArrayValue<'ctx>, String> {
call_nac3_dummy_raise(generator, ctx);
let supported_types = [
ctx.primitives.int32,
ctx.primitives.int64,
@ -627,7 +622,7 @@ 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)
@ -710,12 +705,11 @@ fn ndarray_from_ndlist_impl<'ctx, G: CodeGenerator + ?Sized>(
gen_for_range_callback(
generator,
ctx,
None,
true,
|_, _| Ok(llvm_usize.const_zero()),
(|_, ctx| Ok(src_lst.load_size(ctx, None)), false),
|_, _| Ok(llvm_usize.const_int(1, false)),
|generator, ctx, _, i| {
|generator, ctx, i| {
let offset = ctx.builder.build_int_mul(stride, i, "").unwrap();
let dst_ptr =
@ -951,12 +945,11 @@ fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
gen_for_range_callback(
generator,
ctx,
None,
true,
|_, _| Ok(llvm_usize.const_zero()),
(|_, _| Ok(stop), false),
|_, _| Ok(llvm_usize.const_int(1, false)),
|generator, ctx, _, _| {
|generator, ctx, _| {
let plist_plist_i8 = make_llvm_list(llvm_plist_i8.into())
.ptr_type(AddressSpace::default());
@ -1072,15 +1065,15 @@ 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, '_>,
@ -1095,17 +1088,13 @@ fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
// If there are no (remaining) slice expressions, memcpy the entire dimension
if slices.is_empty() {
let sizeof_elem = ctx.get_llvm_type(generator, elem_ty).size_of().unwrap();
let stride = call_ndarray_calc_size(
generator,
ctx,
&src_arr.dim_sizes(),
(Some(llvm_usize.const_int(dim, false)), None),
);
let stride =
ctx.builder.build_int_z_extend_or_bit_cast(stride, sizeof_elem.get_type(), "").unwrap();
let sizeof_elem = ctx.get_llvm_type(generator, elem_ty).size_of().unwrap();
let cpy_len = ctx.builder.build_int_mul(stride, sizeof_elem, "").unwrap();
call_memcpy_generic(ctx, dst_slice_ptr, src_slice_ptr, cpy_len, llvm_i1.const_zero());
@ -1139,12 +1128,11 @@ fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
gen_for_range_callback(
generator,
ctx,
None,
false,
|_, _| Ok(start),
(|_, _| Ok(stop), true),
|_, _| Ok(step),
|generator, ctx, _, src_i| {
|generator, ctx, src_i| {
// Calculate the offset of the active slice
let src_data_offset = ctx.builder.build_int_mul(src_stride, src_i, "").unwrap();
let dst_i =
@ -1185,7 +1173,7 @@ 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, '_>,
@ -1257,7 +1245,6 @@ pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_int(slices.len() as u64, false),
(this.load_ndims(ctx), false),
|generator, ctx, _, idx| {
@ -1350,7 +1337,7 @@ 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
@ -1437,7 +1424,7 @@ 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, '_>,
@ -1662,7 +1649,6 @@ pub fn ndarray_matmul_2d<'ctx, G: CodeGenerator>(
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_i32.const_zero(),
(common_dim, false),
|generator, ctx, _, i| {
@ -2021,7 +2007,7 @@ 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)
@ -2030,497 +2016,3 @@ 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))
),
}
}

195
nac3core/src/codegen/numpy_new.rs Normal file
View File

@ -0,0 +1,195 @@
use inkwell::values::{BasicValue, BasicValueEnum, PointerValue};
use nac3parser::ast::StrRef;
use crate::{
symbol_resolver::ValueEnum,
toplevel::DefinitionId,
typecheck::typedef::{FunSignature, Type},
};
use super::{
irrt::numpy::{
ndarray::{
alloca_ndarray_and_init, call_nac3_ndarray_fill_generic, NDArrayInitMode, NpArray,
},
shape::parse_input_shape_arg,
},
model::*,
CodeGenContext, CodeGenerator,
};
/// LLVM-typed implementation for generating the implementation for constructing an empty `NDArray`.
fn call_ndarray_empty_impl<'ctx, G>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
elem_ty: Type,
shape: BasicValueEnum<'ctx>,
shape_ty: Type,
name: &str,
) -> Result<Pointer<'ctx, StructModel<NpArray<'ctx>>>, String>
where
G: CodeGenerator + ?Sized,
{
let elem_type = ctx.get_llvm_type(generator, elem_ty);
let shape = parse_input_shape_arg(generator, ctx, shape, shape_ty);
let ndarray_ptr = alloca_ndarray_and_init(
generator,
ctx,
elem_type,
NDArrayInitMode::ShapeAndAllocaData { shape },
name,
)?;
Ok(ndarray_ptr)
}
fn call_ndarray_full_impl<'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<Pointer<'ctx, StructModel<NpArray<'ctx>>>, String>
where
G: CodeGenerator + ?Sized,
{
let ndarray_ptr = call_ndarray_empty_impl(generator, ctx, elem_ty, shape, shape_ty, name)?;
// NOTE: fill_value's type is not checked!! so be careful with logics
// Allocate fill_value on the stack and give the corresponding stack pointer
// to call_nac3_ndarray_fill_generic
let fill_value_ptr = ctx.builder.build_alloca(fill_value.get_type(), "fill_value_ptr").unwrap();
let fill_value_ptr = OpaquePointer(fill_value_ptr);
fill_value_ptr.store_opaque(ctx, fill_value);
let fill_value_ptr = fill_value_ptr.cast_to(ctx, FixedIntModel(Byte), "");
call_nac3_ndarray_fill_generic(ctx, ndarray_ptr, fill_value_ptr);
Ok(ndarray_ptr)
}
/// 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 = call_ndarray_empty_impl(
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 = call_ndarray_full_impl(
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 = call_ndarray_full_impl(
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 `ndarray.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 = call_ndarray_full_impl(
generator,
context,
fill_value_ty,
shape_arg,
shape_ty,
fill_value_arg,
"ndarray",
)?;
Ok(ndarray_ptr.value)
}

696
nac3core/src/codegen/stmt.rs
View File

@ -1,14 +1,16 @@
use super::{
classes::{ArrayLikeIndexer, ArraySliceValue, ListValue, RangeValue},
expr::{destructure_range, gen_binop_expr},
gen_in_range_check,
super::symbol_resolver::ValueEnum,
expr::destructure_range,
irrt::{handle_slice_indices, list_slice_assignment},
macros::codegen_unreachable,
CodeGenContext, CodeGenerator,
};
use crate::{
symbol_resolver::ValueEnum,
toplevel::{DefinitionId, TopLevelDef},
codegen::{
classes::{ArrayLikeIndexer, ArraySliceValue, ListValue, RangeValue},
expr::gen_binop_expr,
gen_in_range_check,
},
toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId, TopLevelDef},
typecheck::{
magic_methods::Binop,
typedef::{iter_type_vars, FunSignature, Type, TypeEnum},
@ -21,10 +23,10 @@ use inkwell::{
values::{BasicValue, BasicValueEnum, FunctionValue, IntValue, PointerValue},
IntPredicate,
};
use itertools::{izip, Itertools};
use nac3parser::ast::{
Constant, ExcepthandlerKind, Expr, ExprKind, Location, Stmt, StmtKind, StrRef,
};
use std::convert::TryFrom;
/// See [`CodeGenerator::gen_var_alloc`].
pub fn gen_var<'ctx>(
@ -95,6 +97,8 @@ pub fn gen_store_target<'ctx, G: CodeGenerator>(
pattern: &Expr<Option<Type>>,
name: Option<&str>,
) -> Result<Option<PointerValue<'ctx>>, String> {
let llvm_usize = generator.get_size_type(ctx.ctx);
// very similar to gen_expr, but we don't do an extra load at the end
// and we flatten nested tuples
Ok(Some(match &pattern.node {
@ -119,7 +123,7 @@ pub fn gen_store_target<'ctx, G: CodeGenerator>(
return Ok(None);
};
let BasicValueEnum::PointerValue(ptr) = val else {
codegen_unreachable!(ctx);
unreachable!();
};
unsafe {
ctx.builder.build_in_bounds_gep(
@ -133,7 +137,62 @@ pub fn gen_store_target<'ctx, G: CodeGenerator>(
}
.unwrap()
}
_ => codegen_unreachable!(ctx),
ExprKind::Subscript { value, slice, .. } => {
match ctx.unifier.get_ty_immutable(value.custom.unwrap()).as_ref() {
TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::List.id() => {
let v = generator
.gen_expr(ctx, value)?
.unwrap()
.to_basic_value_enum(ctx, generator, value.custom.unwrap())?
.into_pointer_value();
let v = ListValue::from_ptr_val(v, llvm_usize, None);
let len = v.load_size(ctx, Some("len"));
let raw_index = generator
.gen_expr(ctx, slice)?
.unwrap()
.to_basic_value_enum(ctx, generator, slice.custom.unwrap())?
.into_int_value();
let raw_index = ctx
.builder
.build_int_s_extend(raw_index, generator.get_size_type(ctx.ctx), "sext")
.unwrap();
// handle negative index
let is_negative = ctx
.builder
.build_int_compare(
IntPredicate::SLT,
raw_index,
generator.get_size_type(ctx.ctx).const_zero(),
"is_neg",
)
.unwrap();
let adjusted = ctx.builder.build_int_add(raw_index, len, "adjusted").unwrap();
let index = ctx
.builder
.build_select(is_negative, adjusted, raw_index, "index")
.map(BasicValueEnum::into_int_value)
.unwrap();
// unsigned less than is enough, because negative index after adjustment is
// bigger than the length (for unsigned cmp)
let bound_check = ctx
.builder
.build_int_compare(IntPredicate::ULT, index, len, "inbound")
.unwrap();
ctx.make_assert(
generator,
bound_check,
"0:IndexError",
"index {0} out of bounds 0:{1}",
[Some(raw_index), Some(len), None],
slice.location,
);
v.data().ptr_offset(ctx, generator, &index, name)
}
_ => unreachable!(),
}
}
_ => unreachable!(),
}))
}
@ -145,193 +204,93 @@ pub fn gen_assign<'ctx, G: CodeGenerator>(
value: ValueEnum<'ctx>,
value_ty: Type,
) -> Result<(), String> {
// See https://docs.python.org/3/reference/simple_stmts.html#assignment-statements.
match &target.node {
ExprKind::Subscript { value: target, slice: key, .. } => {
// Handle "slicing" or "subscription"
generator.gen_setitem(ctx, target, key, value, value_ty)?;
/*
To handle assignment statements `target = value`, with
special care taken for targets `gen_store_target` cannot handle, these are:
- Case 1. target is a Tuple
- e.g., `(x, y, z, w) = value`
- Case 2. *Sliced* list assignment `list.__setitem__`
- e.g., `my_list[1:3] = [100, 101]`, BUT NOT `my_list[0] = 99` (gen_store_target knows how to handle these),
- Case 3. Indexed ndarray assignment `ndarray.__setitem__`
- e.g., `my_ndarray[::-1, :] = 3`, `my_ndarray[:, 3::-1] = their_ndarray[10::2]`
- NOTE: Technically speaking, if `target` is sliced in such as way that it is referencing a
single element/scalar, we *could* implement gen_store_target for this special case
(to point to the raw address of that scalar in the ndarray); but it is much,
*much* simpler to generalize all indexed ndarray assignment without
special handling on that edgecase.
- Otherwise, use `gen_store_target`
*/
let llvm_usize = generator.get_size_type(ctx.ctx);
if let ExprKind::Tuple { elts, .. } = &target.node {
// Handle Case 1. target is a Tuple
let BasicValueEnum::StructValue(v) =
value.to_basic_value_enum(ctx, generator, target.custom.unwrap())?
else {
unreachable!()
};
for (i, elt) in elts.iter().enumerate() {
let elem_ty = elt.custom.unwrap();
let v = ctx
.builder
.build_extract_value(v, u32::try_from(i).unwrap(), "struct_elem")
.unwrap();
generator.gen_assign(ctx, elt, v.into(), elem_ty)?;
}
ExprKind::Tuple { elts, .. } | ExprKind::List { elts, .. } => {
// Fold on `"[" [target_list] "]"` and `"(" [target_list] ")"`
generator.gen_assign_target_list(ctx, elts, value, value_ty)?;
}
_ => {
// Handle attribute and direct variable assignments.
let name = if let ExprKind::Name { id, .. } = &target.node {
format!("{id}.addr")
} else {
String::from("target.addr")
};
let Some(ptr) = generator.gen_store_target(ctx, target, Some(name.as_str()))? else {
return Ok(());
};
if let ExprKind::Name { id, .. } = &target.node {
let (_, static_value, counter) = ctx.var_assignment.get_mut(id).unwrap();
*counter += 1;
if let ValueEnum::Static(s) = &value {
*static_value = Some(s.clone());
}
}
let val = value.to_basic_value_enum(ctx, generator, target.custom.unwrap())?;
// Perform i1 <-> i8 conversion as needed
let val = if ctx.unifier.unioned(target.custom.unwrap(), ctx.primitives.bool) {
generator.bool_to_i8(ctx, val.into_int_value()).into()
} else {
val
};
ctx.builder.build_store(ptr, val).unwrap();
}
};
Ok(())
}
/// See [`CodeGenerator::gen_assign_target_list`].
pub fn gen_assign_target_list<'ctx, G: CodeGenerator>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
targets: &Vec<Expr<Option<Type>>>,
value: ValueEnum<'ctx>,
value_ty: Type,
) -> Result<(), String> {
// Deconstruct the tuple `value`
let BasicValueEnum::StructValue(tuple) = value.to_basic_value_enum(ctx, generator, value_ty)?
else {
codegen_unreachable!(ctx)
};
// NOTE: Currently, RHS's type is forced to be a Tuple by the type inferencer.
let TypeEnum::TTuple { ty: tuple_tys, .. } = &*ctx.unifier.get_ty(value_ty) else {
codegen_unreachable!(ctx);
};
assert_eq!(tuple.get_type().count_fields() as usize, tuple_tys.len());
let tuple = (0..tuple.get_type().count_fields())
.map(|i| ctx.builder.build_extract_value(tuple, i, "item").unwrap())
.collect_vec();
// Find the starred target if it exists.
let mut starred_target_index: Option<usize> = None; // Index of the "starred" target. If it exists, there may only be one.
for (i, target) in targets.iter().enumerate() {
if matches!(target.node, ExprKind::Starred { .. }) {
assert!(starred_target_index.is_none()); // The typechecker ensures this
starred_target_index = Some(i);
}
return Ok(()); // Terminate
}
if let Some(starred_target_index) = starred_target_index {
assert!(tuple_tys.len() >= targets.len() - 1); // The typechecker ensures this
// Else, try checking if it's Case 2 or 3, and they *ONLY*
// happen if `target.node` is a `ExprKind::Subscript`, so do a special check
if let ExprKind::Subscript { value: target_without_slice, slice, .. } = &target.node {
// Get the type of target
let target_ty = target.custom.unwrap();
let target_ty_enum = &*ctx.unifier.get_ty(target_ty);
let a = starred_target_index; // Number of RHS values before the starred target
let b = tuple_tys.len() - (targets.len() - 1 - starred_target_index); // Number of RHS values after the starred target
// Thus `tuple[a..b]` is assigned to the starred target.
// Pattern match on this pair.
// This is done like this because of Case 2 - slice.node has to be in a specific pattern
match (target_ty_enum, &slice.node) {
(TypeEnum::TObj { obj_id, .. }, ExprKind::Slice { lower, upper, step })
if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
{
// Case 2. *Sliced* list assignment
// Handle assignment before the starred target
for (target, val, val_ty) in
izip!(&targets[..starred_target_index], &tuple[..a], &tuple_tys[..a])
{
generator.gen_assign(ctx, target, ValueEnum::Dynamic(*val), *val_ty)?;
}
// Handle assignment to the starred target
if let ExprKind::Starred { value: target, .. } = &targets[starred_target_index].node {
let vals = &tuple[a..b];
let val_tys = &tuple_tys[a..b];
// Create a sub-tuple from `value` for the starred target.
let sub_tuple_ty = ctx
.ctx
.struct_type(&vals.iter().map(BasicValueEnum::get_type).collect_vec(), false);
let psub_tuple_val =
ctx.builder.build_alloca(sub_tuple_ty, "starred_target_value_ptr").unwrap();
for (i, val) in vals.iter().enumerate() {
let pitem = ctx
.builder
.build_struct_gep(psub_tuple_val, i as u32, "starred_target_value_item")
.unwrap();
ctx.builder.build_store(pitem, *val).unwrap();
}
let sub_tuple_val =
ctx.builder.build_load(psub_tuple_val, "starred_target_value").unwrap();
// Create the typechecker type of the sub-tuple
let sub_tuple_ty =
ctx.unifier.add_ty(TypeEnum::TTuple { ty: val_tys.to_vec(), is_vararg_ctx: false });
// Now assign with that sub-tuple to the starred target.
generator.gen_assign(ctx, target, ValueEnum::Dynamic(sub_tuple_val), sub_tuple_ty)?;
} else {
codegen_unreachable!(ctx) // The typechecker ensures this
}
// Handle assignment after the starred target
for (target, val, val_ty) in
izip!(&targets[starred_target_index + 1..], &tuple[b..], &tuple_tys[b..])
{
generator.gen_assign(ctx, target, ValueEnum::Dynamic(*val), *val_ty)?;
}
} else {
assert_eq!(tuple_tys.len(), targets.len()); // The typechecker ensures this
for (target, val, val_ty) in izip!(targets, tuple, tuple_tys) {
generator.gen_assign(ctx, target, ValueEnum::Dynamic(val), *val_ty)?;
}
}
Ok(())
}
/// See [`CodeGenerator::gen_setitem`].
pub fn gen_setitem<'ctx, G: CodeGenerator>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
target: &Expr<Option<Type>>,
key: &Expr<Option<Type>>,
value: ValueEnum<'ctx>,
value_ty: Type,
) -> Result<(), String> {
let target_ty = target.custom.unwrap();
let key_ty = key.custom.unwrap();
match &*ctx.unifier.get_ty(target_ty) {
TypeEnum::TObj { obj_id, params: list_params, .. }
if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
{
// Handle list item assignment
let llvm_usize = generator.get_size_type(ctx.ctx);
let target_item_ty = iter_type_vars(list_params).next().unwrap().ty;
let target = generator
.gen_expr(ctx, target)?
.unwrap()
.to_basic_value_enum(ctx, generator, target_ty)?
.into_pointer_value();
let target = ListValue::from_ptr_val(target, llvm_usize, None);
if let ExprKind::Slice { .. } = &key.node {
// Handle assigning to a slice
let ExprKind::Slice { lower, upper, step } = &key.node else {
codegen_unreachable!(ctx)
};
let ls = generator
.gen_expr(ctx, target_without_slice)?
.unwrap()
.to_basic_value_enum(ctx, generator, target_without_slice.custom.unwrap())?
.into_pointer_value();
let ls = ListValue::from_ptr_val(ls, llvm_usize, None);
let Some((start, end, step)) = handle_slice_indices(
lower,
upper,
step,
ctx,
generator,
target.load_size(ctx, None),
ls.load_size(ctx, None),
)?
else {
return Ok(());
};
let value =
value.to_basic_value_enum(ctx, generator, value_ty)?.into_pointer_value();
let value = value
.to_basic_value_enum(ctx, generator, target.custom.unwrap())?
.into_pointer_value();
let value = ListValue::from_ptr_val(value, llvm_usize, None);
let ty = match &*ctx.unifier.get_ty_immutable(target.custom.unwrap()) {
TypeEnum::TObj { obj_id, params, .. } if *obj_id == PrimDef::List.id() => {
*params.iter().next().unwrap().1
}
TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
unpack_ndarray_var_tys(&mut ctx.unifier, target.custom.unwrap()).0
}
_ => unreachable!(),
};
let target_item_ty = ctx.get_llvm_type(generator, target_item_ty);
let ty = ctx.get_llvm_type(generator, ty);
let Some(src_ind) = handle_slice_indices(
&None,
&None,
@ -343,78 +302,68 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
else {
return Ok(());
};
list_slice_assignment(
generator,
list_slice_assignment(generator, ctx, ty, ls, (start, end, step), value, src_ind);
return Ok(()); // Terminate
}
(TypeEnum::TObj { obj_id, .. }, _)
if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
{
// Case 3. Indexed ndarray assignment
let target = generator.gen_expr(ctx, target)?.unwrap().to_basic_value_enum(
ctx,
target_item_ty,
target,
(start, end, step),
value,
src_ind,
);
} else {
// Handle assigning to an index
let len = target.load_size(ctx, Some("len"));
let index = generator
.gen_expr(ctx, key)?
.unwrap()
.to_basic_value_enum(ctx, generator, key_ty)?
.into_int_value();
let index = ctx
.builder
.build_int_s_extend(index, generator.get_size_type(ctx.ctx), "sext")
.unwrap();
// handle negative index
let is_negative = ctx
.builder
.build_int_compare(
IntPredicate::SLT,
index,
generator.get_size_type(ctx.ctx).const_zero(),
"is_neg",
)
.unwrap();
let adjusted = ctx.builder.build_int_add(index, len, "adjusted").unwrap();
let index = ctx
.builder
.build_select(is_negative, adjusted, index, "index")
.map(BasicValueEnum::into_int_value)
.unwrap();
// unsigned less than is enough, because negative index after adjustment is
// bigger than the length (for unsigned cmp)
let bound_check = ctx
.builder
.build_int_compare(IntPredicate::ULT, index, len, "inbound")
.unwrap();
ctx.make_assert(
generator,
bound_check,
"0:IndexError",
"index {0} out of bounds 0:{1}",
[Some(index), Some(len), None],
key.location,
);
target.custom.unwrap(),
)?;
// Write value to index on list
let item_ptr =
target.data().ptr_offset(ctx, generator, &index, Some("list_item_ptr"));
let value = value.to_basic_value_enum(ctx, generator, value_ty)?;
ctx.builder.build_store(item_ptr, value).unwrap();
match &*ctx.unifier.get_ty(value_ty) {
TypeEnum::TObj { obj_id, .. }
if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
{
// `value` is an `ndarray[dtype, ndims]`
todo!()
}
_ => {
// TODO: Inferencer's assignment forces `target` and `value` to have the same type
// NOTE: gen_assign() has already been extended, I will keep it in place
// in participation for when this is extended to be no longer the case.
todo!("support scalar assignment")
// panic!(
// "Unsupported ndarray assignment value: {}",
// ctx.unifier.stringify(value_ty)
// );
}
}
return Ok(()); // Terminate
}
_ => {
// Fallthrough
}
}
TypeEnum::TObj { obj_id, .. }
if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
{
// Handle NDArray item assignment
todo!("ndarray subscript assignment is not yet implemented");
}
_ => {
panic!("encountered unknown target type: {}", ctx.unifier.stringify(target_ty));
}
// The assignment expression matches none of the special cases.
// We should actually use `gen_store_target`.
let name = if let ExprKind::Name { id, .. } = &target.node {
format!("{id}.addr")
} else {
String::from("target.addr")
};
let Some(ptr) = generator.gen_store_target(ctx, target, Some(name.as_str()))? else {
return Ok(());
};
if let ExprKind::Name { id, .. } = &target.node {
let (_, static_value, counter) = ctx.var_assignment.get_mut(id).unwrap();
*counter += 1;
if let ValueEnum::Static(s) = &value {
*static_value = Some(s.clone());
}
}
let val = value.to_basic_value_enum(ctx, generator, target.custom.unwrap())?;
ctx.builder.build_store(ptr, val).unwrap();
Ok(())
}
@ -424,9 +373,7 @@ pub fn gen_for<G: CodeGenerator>(
ctx: &mut CodeGenContext<'_, '_>,
stmt: &Stmt<Option<Type>>,
) -> Result<(), String> {
let StmtKind::For { iter, target, body, orelse, .. } = &stmt.node else {
codegen_unreachable!(ctx)
};
let StmtKind::For { iter, target, body, orelse, .. } = &stmt.node else { unreachable!() };
// var_assignment static values may be changed in another branch
// if so, remove the static value as it may not be correct in this branch
@ -450,17 +397,70 @@ pub fn gen_for<G: CodeGenerator>(
// store loop bb information and restore it later
let loop_bb = ctx.loop_target.replace((incr_bb, cont_bb));
let iter_ty = iter.custom.unwrap();
let iter_val = if let Some(v) = generator.gen_expr(ctx, iter)? {
v.to_basic_value_enum(ctx, generator, iter_ty)?
v.to_basic_value_enum(ctx, generator, iter.custom.unwrap())?
} else {
return Ok(());
};
// The implementation of the for loop logic depends on
// the typechecker type of `iter`.
let iter_ty = iter.custom.unwrap();
match &*ctx.unifier.get_ty(iter_ty) {
TypeEnum::TObj { obj_id, params, .. }
if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
{
// `iter` is a `List[T]`, and `T` is the element type
// Get the `T` out of `List[T]` - it is defined to be the 1st param.
let list_elem_ty = iter_type_vars(params).nth(0).unwrap().ty;
// Implementation
let index_addr = generator.gen_var_alloc(ctx, size_t.into(), Some("for.index.addr"))?;
ctx.builder.build_store(index_addr, size_t.const_zero()).unwrap();
let len = ctx
.build_gep_and_load(
iter_val.into_pointer_value(),
&[zero, int32.const_int(1, false)],
Some("len"),
)
.into_int_value();
ctx.builder.build_unconditional_branch(cond_bb).unwrap();
ctx.builder.position_at_end(cond_bb);
let index = ctx
.builder
.build_load(index_addr, "for.index")
.map(BasicValueEnum::into_int_value)
.unwrap();
let cmp = ctx.builder.build_int_compare(IntPredicate::SLT, index, len, "cond").unwrap();
ctx.builder.build_conditional_branch(cmp, body_bb, orelse_bb).unwrap();
ctx.builder.position_at_end(incr_bb);
let index =
ctx.builder.build_load(index_addr, "").map(BasicValueEnum::into_int_value).unwrap();
let inc = ctx.builder.build_int_add(index, size_t.const_int(1, true), "inc").unwrap();
ctx.builder.build_store(index_addr, inc).unwrap();
ctx.builder.build_unconditional_branch(cond_bb).unwrap();
ctx.builder.position_at_end(body_bb);
let arr_ptr = ctx
.build_gep_and_load(iter_val.into_pointer_value(), &[zero, zero], Some("arr.addr"))
.into_pointer_value();
let index = ctx
.builder
.build_load(index_addr, "for.index")
.map(BasicValueEnum::into_int_value)
.unwrap();
let val = ctx.build_gep_and_load(arr_ptr, &[index], Some("val"));
generator.gen_assign(ctx, target, val.into(), list_elem_ty)?;
generator.gen_block(ctx, body.iter())?;
}
TypeEnum::TObj { obj_id, .. }
if *obj_id == ctx.primitives.range.obj_id(&ctx.unifier).unwrap() =>
{
// `iter` is a `range(start, stop, step)`, and `int32` is the element type
let iter_val = RangeValue::from_ptr_val(iter_val.into_pointer_value(), Some("range"));
// Internal variable for loop; Cannot be assigned
let i = generator.gen_var_alloc(ctx, int32.into(), Some("for.i.addr"))?;
@ -468,7 +468,7 @@ pub fn gen_for<G: CodeGenerator>(
let Some(target_i) =
generator.gen_store_target(ctx, target, Some("for.target.addr"))?
else {
codegen_unreachable!(ctx)
unreachable!()
};
let (start, stop, step) = destructure_range(ctx, iter_val);
@ -529,52 +529,8 @@ pub fn gen_for<G: CodeGenerator>(
.unwrap();
generator.gen_block(ctx, body.iter())?;
}
TypeEnum::TObj { obj_id, params: list_params, .. }
if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
{
let index_addr = generator.gen_var_alloc(ctx, size_t.into(), Some("for.index.addr"))?;
ctx.builder.build_store(index_addr, size_t.const_zero()).unwrap();
let len = ctx
.build_gep_and_load(
iter_val.into_pointer_value(),
&[zero, int32.const_int(1, false)],
Some("len"),
)
.into_int_value();
ctx.builder.build_unconditional_branch(cond_bb).unwrap();
ctx.builder.position_at_end(cond_bb);
let index = ctx
.builder
.build_load(index_addr, "for.index")
.map(BasicValueEnum::into_int_value)
.unwrap();
let cmp = ctx.builder.build_int_compare(IntPredicate::SLT, index, len, "cond").unwrap();
ctx.builder.build_conditional_branch(cmp, body_bb, orelse_bb).unwrap();
ctx.builder.position_at_end(incr_bb);
let index =
ctx.builder.build_load(index_addr, "").map(BasicValueEnum::into_int_value).unwrap();
let inc = ctx.builder.build_int_add(index, size_t.const_int(1, true), "inc").unwrap();
ctx.builder.build_store(index_addr, inc).unwrap();
ctx.builder.build_unconditional_branch(cond_bb).unwrap();
ctx.builder.position_at_end(body_bb);
let arr_ptr = ctx
.build_gep_and_load(iter_val.into_pointer_value(), &[zero, zero], Some("arr.addr"))
.into_pointer_value();
let index = ctx
.builder
.build_load(index_addr, "for.index")
.map(BasicValueEnum::into_int_value)
.unwrap();
let val = ctx.build_gep_and_load(arr_ptr, &[index], Some("val"));
let val_ty = iter_type_vars(list_params).next().unwrap().ty;
generator.gen_assign(ctx, target, val.into(), val_ty)?;
generator.gen_block(ctx, body.iter())?;
}
_ => {
panic!("unsupported for loop iterator type: {}", ctx.unifier.stringify(iter_ty));
panic!("unsupported iterator type in for loop: {}", ctx.unifier.stringify(iter_ty))
}
}
@ -629,15 +585,14 @@ pub struct BreakContinueHooks<'ctx> {
/// ```
///
/// * `init` - A lambda containing IR statements declaring and initializing loop variables. The
/// return value is a [Clone] value which will be passed to the other lambdas.
/// return value is a [Clone] value which will be passed to the other lambdas.
/// * `cond` - A lambda containing IR statements checking whether the loop should continue
/// executing. The result value must be an `i1` indicating if the loop should continue.
/// executing. The result value must be an `i1` indicating if the loop should continue.
/// * `body` - A lambda containing IR statements within the loop body.
/// * `update` - A lambda containing IR statements updating loop variables.
pub fn gen_for_callback<'ctx, 'a, G, I, InitFn, CondFn, BodyFn, UpdateFn>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, 'a>,
label: Option<&str>,
init: InitFn,
cond: CondFn,
body: BodyFn,
@ -648,24 +603,18 @@ where
I: Clone,
InitFn: FnOnce(&mut G, &mut CodeGenContext<'ctx, 'a>) -> Result<I, String>,
CondFn: FnOnce(&mut G, &mut CodeGenContext<'ctx, 'a>, I) -> Result<IntValue<'ctx>, String>,
BodyFn: FnOnce(
&mut G,
&mut CodeGenContext<'ctx, 'a>,
BreakContinueHooks<'ctx>,
I,
) -> Result<(), String>,
BodyFn:
FnOnce(&mut G, &mut CodeGenContext<'ctx, 'a>, BreakContinueHooks, I) -> Result<(), String>,
UpdateFn: FnOnce(&mut G, &mut CodeGenContext<'ctx, 'a>, I) -> Result<(), String>,
{
let label = label.unwrap_or("for");
let current_bb = ctx.builder.get_insert_block().unwrap();
let init_bb = ctx.ctx.insert_basic_block_after(current_bb, &format!("{label}.init"));
let init_bb = ctx.ctx.insert_basic_block_after(current_bb, "for.init");
// The BB containing the loop condition check
let cond_bb = ctx.ctx.insert_basic_block_after(init_bb, &format!("{label}.cond"));
let body_bb = ctx.ctx.insert_basic_block_after(cond_bb, &format!("{label}.body"));
let cond_bb = ctx.ctx.insert_basic_block_after(init_bb, "for.cond");
let body_bb = ctx.ctx.insert_basic_block_after(cond_bb, "for.body");
// The BB containing the increment expression
let update_bb = ctx.ctx.insert_basic_block_after(body_bb, &format!("{label}.update"));
let cont_bb = ctx.ctx.insert_basic_block_after(update_bb, &format!("{label}.end"));
let update_bb = ctx.ctx.insert_basic_block_after(body_bb, "for.update");
let cont_bb = ctx.ctx.insert_basic_block_after(update_bb, "for.end");
// store loop bb information and restore it later
let loop_bb = ctx.loop_target.replace((update_bb, cont_bb));
@ -714,15 +663,14 @@ where
/// ```
///
/// * `init_val` - The initial value of the loop variable. The type of this value will also be used
/// as the type of the loop variable.
/// as the type of the loop variable.
/// * `max_val` - A tuple containing the maximum value of the loop variable, and whether the maximum
/// value should be treated as inclusive (as opposed to exclusive).
/// value should be treated as inclusive (as opposed to exclusive).
/// * `body` - A lambda containing IR statements within the loop body.
/// * `incr_val` - The value to increment the loop variable on each iteration.
pub fn gen_for_callback_incrementing<'ctx, 'a, G, BodyFn>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, 'a>,
label: Option<&str>,
init_val: IntValue<'ctx>,
max_val: (IntValue<'ctx>, bool),
body: BodyFn,
@ -733,7 +681,7 @@ where
BodyFn: FnOnce(
&mut G,
&mut CodeGenContext<'ctx, 'a>,
BreakContinueHooks<'ctx>,
BreakContinueHooks,
IntValue<'ctx>,
) -> Result<(), String>,
{
@ -742,7 +690,6 @@ where
gen_for_callback(
generator,
ctx,
label,
|generator, ctx| {
let i_addr = generator.gen_var_alloc(ctx, init_val_t.into(), None)?;
ctx.builder.build_store(i_addr, init_val).unwrap();
@ -787,18 +734,16 @@ where
///
/// - `is_unsigned`: Whether to treat the values of the `range` as unsigned.
/// - `start_fn`: A lambda of IR statements that retrieves the `start` value of the `range`-like
/// iterable.
/// iterable.
/// - `stop_fn`: A lambda of IR statements that retrieves the `stop` value of the `range`-like
/// iterable. This value will be extended to the size of `start`.
/// iterable. This value will be extended to the size of `start`.
/// - `stop_inclusive`: Whether the stop value should be treated as inclusive.
/// - `step_fn`: A lambda of IR statements that retrieves the `step` value of the `range`-like
/// iterable. This value will be extended to the size of `start`.
/// iterable. This value will be extended to the size of `start`.
/// - `body_fn`: A lambda of IR statements within the loop body.
#[allow(clippy::too_many_arguments)]
pub fn gen_for_range_callback<'ctx, 'a, G, StartFn, StopFn, StepFn, BodyFn>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, 'a>,
label: Option<&str>,
is_unsigned: bool,
start_fn: StartFn,
(stop_fn, stop_inclusive): (StopFn, bool),
@ -810,19 +755,13 @@ where
StartFn: Fn(&mut G, &mut CodeGenContext<'ctx, 'a>) -> Result<IntValue<'ctx>, String>,
StopFn: Fn(&mut G, &mut CodeGenContext<'ctx, 'a>) -> Result<IntValue<'ctx>, String>,
StepFn: Fn(&mut G, &mut CodeGenContext<'ctx, 'a>) -> Result<IntValue<'ctx>, String>,
BodyFn: FnOnce(
&mut G,
&mut CodeGenContext<'ctx, 'a>,
BreakContinueHooks<'ctx>,
IntValue<'ctx>,
) -> Result<(), String>,
BodyFn: FnOnce(&mut G, &mut CodeGenContext<'ctx, 'a>, IntValue<'ctx>) -> Result<(), String>,
{
let init_val_t = start_fn(generator, ctx).map(IntValue::get_type).unwrap();
gen_for_callback(
generator,
ctx,
label,
|generator, ctx| {
let i_addr = generator.gen_var_alloc(ctx, init_val_t.into(), None)?;
@ -880,10 +819,10 @@ where
Ok(cond)
},
|generator, ctx, hooks, (i_addr, _)| {
|generator, ctx, _, (i_addr, _)| {
let i = ctx.builder.build_load(i_addr, "").map(BasicValueEnum::into_int_value).unwrap();
body_fn(generator, ctx, hooks, i)
body_fn(generator, ctx, i)
},
|generator, ctx, (i_addr, _)| {
let i = ctx.builder.build_load(i_addr, "").map(BasicValueEnum::into_int_value).unwrap();
@ -911,7 +850,7 @@ pub fn gen_while<G: CodeGenerator>(
ctx: &mut CodeGenContext<'_, '_>,
stmt: &Stmt<Option<Type>>,
) -> Result<(), String> {
let StmtKind::While { test, body, orelse, .. } = &stmt.node else { codegen_unreachable!(ctx) };
let StmtKind::While { test, body, orelse, .. } = &stmt.node else { unreachable!() };
// var_assignment static values may be changed in another branch
// if so, remove the static value as it may not be correct in this branch
@ -941,7 +880,7 @@ pub fn gen_while<G: CodeGenerator>(
return Ok(());
};
let BasicValueEnum::IntValue(test) = test else { codegen_unreachable!(ctx) };
let BasicValueEnum::IntValue(test) = test else { unreachable!() };
ctx.builder
.build_conditional_branch(generator.bool_to_i1(ctx, test), body_bb, orelse_bb)
@ -1089,7 +1028,7 @@ pub fn gen_if<G: CodeGenerator>(
ctx: &mut CodeGenContext<'_, '_>,
stmt: &Stmt<Option<Type>>,
) -> Result<(), String> {
let StmtKind::If { test, body, orelse, .. } = &stmt.node else { codegen_unreachable!(ctx) };
let StmtKind::If { test, body, orelse, .. } = &stmt.node else { unreachable!() };
// var_assignment static values may be changed in another branch
// if so, remove the static value as it may not be correct in this branch
@ -1212,11 +1151,11 @@ pub fn exn_constructor<'ctx>(
let zelf_id = if let TypeEnum::TObj { obj_id, .. } = &*ctx.unifier.get_ty(zelf_ty) {
obj_id.0
} else {
codegen_unreachable!(ctx)
unreachable!()
};
let defs = ctx.top_level.definitions.read();
let def = defs[zelf_id].read();
let TopLevelDef::Class { name: zelf_name, .. } = &*def else { codegen_unreachable!(ctx) };
let TopLevelDef::Class { name: zelf_name, .. } = &*def else { unreachable!() };
let exception_name = format!("{}:{}", ctx.resolver.get_exception_id(zelf_id), zelf_name);
unsafe {
let id_ptr = ctx.builder.build_in_bounds_gep(zelf, &[zero, zero], "exn.id").unwrap();
@ -1324,7 +1263,7 @@ pub fn gen_try<'ctx, 'a, G: CodeGenerator>(
target: &Stmt<Option<Type>>,
) -> Result<(), String> {
let StmtKind::Try { body, handlers, orelse, finalbody, .. } = &target.node else {
codegen_unreachable!(ctx)
unreachable!()
};
// if we need to generate anything related to exception, we must have personality defined
@ -1401,7 +1340,7 @@ pub fn gen_try<'ctx, 'a, G: CodeGenerator>(
if let TypeEnum::TObj { obj_id, .. } = &*ctx.unifier.get_ty(type_.custom.unwrap()) {
*obj_id
} else {
codegen_unreachable!(ctx)
unreachable!()
};
let exception_name = format!("{}:{}", ctx.resolver.get_exception_id(obj_id.0), exn_name);
let exn_id = ctx.resolver.get_string_id(&exception_name);
@ -1673,23 +1612,6 @@ pub fn gen_return<G: CodeGenerator>(
} else {
None
};
// Remap boolean return type into i1
let value = value.map(|ret_val| {
// The "return type" of a sret function is in the first parameter
let expected_ty = if ctx.need_sret {
func.get_type().get_param_types()[0]
} else {
func.get_type().get_return_type().unwrap()
};
if matches!(expected_ty, BasicTypeEnum::IntType(ty) if ty.get_bit_width() == 1) {
generator.bool_to_i1(ctx, ret_val.into_int_value()).into()
} else {
ret_val
}
});
if let Some(return_target) = ctx.return_target {
if let Some(value) = value {
ctx.builder.build_store(ctx.return_buffer.unwrap(), value).unwrap();
@ -1700,6 +1622,25 @@ pub fn gen_return<G: CodeGenerator>(
ctx.builder.build_store(ctx.return_buffer.unwrap(), value.unwrap()).unwrap();
ctx.builder.build_return(None).unwrap();
} else {
// Remap boolean return type into i1
let value = value.map(|v| {
let expected_ty = func.get_type().get_return_type().unwrap();
let ret_val = v.as_basic_value_enum();
if expected_ty.is_int_type() && ret_val.is_int_value() {
let ret_type = expected_ty.into_int_type();
let ret_val = ret_val.into_int_value();
if ret_type.get_bit_width() == 1 && ret_val.get_type().get_bit_width() != 1 {
generator.bool_to_i1(ctx, ret_val)
} else {
ret_val
}
.into()
} else {
ret_val
}
});
let value = value.as_ref().map(|v| v as &dyn BasicValue);
ctx.builder.build_return(value).unwrap();
}
@ -1733,14 +1674,18 @@ pub fn gen_stmt<G: CodeGenerator>(
}
StmtKind::AnnAssign { target, value, .. } => {
if let Some(value) = value {
let Some(value_enum) = generator.gen_expr(ctx, value)? else { return Ok(()) };
generator.gen_assign(ctx, target, value_enum, value.custom.unwrap())?;
let value_ty = value.custom.unwrap();
let Some(value) = generator.gen_expr(ctx, value)? else { return Ok(()) };
generator.gen_assign(ctx, target, value, value_ty)?;
}
}
StmtKind::Assign { targets, value, .. } => {
let Some(value_enum) = generator.gen_expr(ctx, value)? else { return Ok(()) };
// TODO: Is the implementation wrong? It looks very strange.
let value_ty = value.custom.unwrap();
let Some(value) = generator.gen_expr(ctx, value)? else { return Ok(()) };
for target in targets {
generator.gen_assign(ctx, target, value_enum.clone(), value.custom.unwrap())?;
generator.gen_assign(ctx, target, value.clone(), value_ty)?;
}
}
StmtKind::Continue { .. } => {
@ -1754,44 +1699,21 @@ pub fn gen_stmt<G: CodeGenerator>(
StmtKind::For { .. } => generator.gen_for(ctx, stmt)?,
StmtKind::With { .. } => generator.gen_with(ctx, stmt)?,
StmtKind::AugAssign { target, op, value, .. } => {
let value_enum = gen_binop_expr(
let value_ty = value.custom.unwrap();
let value = gen_binop_expr(
generator,
ctx,
target,
Binop::aug_assign(*op),
value,
stmt.location,
)?
.unwrap();
generator.gen_assign(ctx, target, value_enum, value.custom.unwrap())?;
)?;
generator.gen_assign(ctx, target, value.unwrap(), value_ty)?;
}
StmtKind::Try { .. } => gen_try(generator, ctx, stmt)?,
StmtKind::Raise { exc, .. } => {
if let Some(exc) = exc {
let exn = if let ExprKind::Name { id, .. } = &exc.node {
// Handle "raise Exception" short form
let def_id = ctx.resolver.get_identifier_def(*id).map_err(|e| {
format!("{} (at {})", e.iter().next().unwrap(), exc.location)
})?;
let def = ctx.top_level.definitions.read();
let TopLevelDef::Class { constructor, .. } = *def[def_id.0].read() else {
return Err(format!("Failed to resolve symbol {id} (at {})", exc.location));
};
let TypeEnum::TFunc(signature) =
ctx.unifier.get_ty(constructor.unwrap()).as_ref().clone()
else {
return Err(format!("Failed to resolve symbol {id} (at {})", exc.location));
};
generator
.gen_call(ctx, None, (&signature, def_id), Vec::default())?
.map(Into::into)
} else {
generator.gen_expr(ctx, exc)?
};
let exc = if let Some(v) = exn {
let exc = if let Some(v) = generator.gen_expr(ctx, exc)? {
v.to_basic_value_enum(ctx, generator, exc.custom.unwrap())?
} else {
return Ok(());
@ -1815,11 +1737,11 @@ pub fn gen_stmt<G: CodeGenerator>(
return Ok(());
}
}
None => ctx.gen_string(generator, "").into(),
None => ctx.gen_string(generator, ""),
};
ctx.make_assert_impl(
generator,
generator.bool_to_i1(ctx, test.into_int_value()),
test.into_int_value(),
"0:AssertionError",
err_msg,
[None, None, None],

29
nac3core/src/codegen/test.rs
View File

@ -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(),
@ -199,8 +189,6 @@ fn test_primitives() {
let expected = indoc! {"
; ModuleID = 'test'
source_filename = \"test\"
target datalayout = \"e-m:e-p270:32:32-p271:32:32-p272:64:64-i64:64-f80:128-n8:16:32:64-S128\"
target triple = \"x86_64-unknown-linux-gnu\"
; Function Attrs: mustprogress nofree norecurse nosync nounwind readnone willreturn
define i32 @testing(i32 %0, i32 %1) local_unnamed_addr #0 !dbg !4 {
@ -258,19 +246,14 @@ fn test_simple_call() {
"};
let statements_2 = parse_program(source_2, FileName::default()).unwrap();
let composer = TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 32).0;
let composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 32).0;
let mut unifier = composer.unifier.clone();
let primitives = composer.primitives_ty;
let top_level = Arc::new(composer.make_top_level_context());
unifier.top_level = Some(top_level.clone());
let signature = FunSignature {
args: vec![FuncArg {
name: "a".into(),
ty: primitives.int32,
default_value: None,
is_vararg: false,
}],
args: vec![FuncArg { name: "a".into(), ty: primitives.int32, default_value: None }],
ret: primitives.int32,
vars: VarMap::new(),
};
@ -385,8 +368,6 @@ fn test_simple_call() {
let expected = indoc! {"
; ModuleID = 'test'
source_filename = \"test\"
target datalayout = \"e-m:e-p270:32:32-p271:32:32-p272:64:64-i64:64-f80:128-n8:16:32:64-S128\"
target triple = \"x86_64-unknown-linux-gnu\"
; Function Attrs: mustprogress nofree norecurse nosync nounwind readnone willreturn
define i32 @testing(i32 %0) local_unnamed_addr #0 !dbg !5 {

1
nac3core/src/lib.rs
View File

@ -23,3 +23,4 @@ pub mod codegen;
pub mod symbol_resolver;
pub mod toplevel;
pub mod typecheck;
pub(crate) mod util;

8
nac3core/src/symbol_resolver.rs
View File

@ -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()]))
}

491
nac3core/src/toplevel/builtins.rs
View File

@ -5,7 +5,7 @@ use indexmap::IndexMap;
use inkwell::{
attributes::{Attribute, AttributeLoc},
types::{BasicMetadataTypeEnum, BasicType},
values::{BasicMetadataValueEnum, BasicValue, CallSiteValue},
values::{AnyValue, BasicMetadataValueEnum, BasicValue, CallSiteValue},
IntPredicate,
};
use itertools::Either;
@ -15,12 +15,23 @@ use crate::{
codegen::{
builtin_fns,
classes::{ProxyValue, RangeValue},
numpy::*,
expr::destructure_range,
irrt::{
calculate_len_for_slice_range,
numpy::ndarray::{call_nac3_ndarray_len, NpArray},
},
model::*,
numpy::{
gen_ndarray_array, gen_ndarray_copy, gen_ndarray_eye, gen_ndarray_fill,
gen_ndarray_identity,
},
numpy_new,
stmt::exn_constructor,
},
symbol_resolver::SymbolValue,
toplevel::{helper::PrimDef, numpy::make_ndarray_ty},
typecheck::typedef::{into_var_map, iter_type_vars, TypeVar, VarMap},
util::SizeVariant,
};
use super::*;
@ -43,26 +54,10 @@ 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 +107,7 @@ 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 +123,7 @@ 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 +142,7 @@ 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 +204,10 @@ 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,
@ -297,19 +287,10 @@ pub fn get_builtins(unifier: &mut Unifier, primitives: &PrimitiveStore) -> Built
.collect()
}
/// A helper enum used by [`BuiltinBuilder`]
#[derive(Clone, Copy)]
enum SizeVariant {
Bits32,
Bits64,
}
impl SizeVariant {
fn of_int(self, primitives: &PrimitiveStore) -> Type {
match self {
SizeVariant::Bits32 => primitives.int32,
SizeVariant::Bits64 => primitives.int64,
}
fn get_size_variant_of_int(size_variant: SizeVariant, primitives: &PrimitiveStore) -> Type {
match size_variant {
SizeVariant::Bits32 => primitives.int32,
SizeVariant::Bits64 => primitives.int64,
}
}
@ -365,8 +346,8 @@ impl<'a> BuiltinBuilder<'a> {
let (is_some_ty, unwrap_ty, option_tvar) =
if let TypeEnum::TObj { fields, params, .. } = unifier.get_ty(option).as_ref() {
(
*fields.get(&PrimDef::FunOptionIsSome.simple_name().into()).unwrap(),
*fields.get(&PrimDef::FunOptionUnwrap.simple_name().into()).unwrap(),
*fields.get(&PrimDef::OptionIsSome.simple_name().into()).unwrap(),
*fields.get(&PrimDef::OptionUnwrap.simple_name().into()).unwrap(),
iter_type_vars(params).next().unwrap(),
)
} else {
@ -381,9 +362,9 @@ impl<'a> BuiltinBuilder<'a> {
let ndarray_dtype_tvar = iter_type_vars(ndarray_params).next().unwrap();
let ndarray_ndims_tvar = iter_type_vars(ndarray_params).nth(1).unwrap();
let ndarray_copy_ty =
*ndarray_fields.get(&PrimDef::FunNDArrayCopy.simple_name().into()).unwrap();
*ndarray_fields.get(&PrimDef::NDArrayCopy.simple_name().into()).unwrap();
let ndarray_fill_ty =
*ndarray_fields.get(&PrimDef::FunNDArrayFill.simple_name().into()).unwrap();
*ndarray_fields.get(&PrimDef::NDArrayFill.simple_name().into()).unwrap();
let num_ty = unifier.get_fresh_var_with_range(
&[int32, int64, float, boolean, uint32, uint64],
@ -483,14 +464,14 @@ impl<'a> BuiltinBuilder<'a> {
PrimDef::Exception => self.build_exception_class_related(prim),
PrimDef::Option
| PrimDef::FunOptionIsSome
| PrimDef::FunOptionIsNone
| PrimDef::FunOptionUnwrap
| PrimDef::OptionIsSome
| PrimDef::OptionIsNone
| PrimDef::OptionUnwrap
| PrimDef::FunSome => self.build_option_class_related(prim),
PrimDef::List => self.build_list_class_related(prim),
PrimDef::NDArray | PrimDef::FunNDArrayCopy | PrimDef::FunNDArrayFill => {
PrimDef::NDArray | PrimDef::NDArrayCopy | PrimDef::NDArrayFill => {
self.build_ndarray_class_related(prim)
}
@ -575,22 +556,6 @@ 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) {
@ -599,7 +564,7 @@ impl<'a> BuiltinBuilder<'a> {
match (&tld, prim.details()) {
(
TopLevelDef::Class { name, object_id, .. },
PrimDefDetails::PrimClass { name: exp_name, .. },
PrimDefDetails::PrimClass { name: exp_name },
) => {
let exp_object_id = prim.id();
assert_eq!(name, &exp_name.into());
@ -648,24 +613,17 @@ 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,
@ -836,9 +794,9 @@ impl<'a> BuiltinBuilder<'a> {
prim,
&[
PrimDef::Option,
PrimDef::FunOptionIsSome,
PrimDef::FunOptionIsNone,
PrimDef::FunOptionUnwrap,
PrimDef::OptionIsSome,
PrimDef::OptionIsNone,
PrimDef::OptionUnwrap,
PrimDef::FunSome,
],
);
@ -851,9 +809,9 @@ impl<'a> BuiltinBuilder<'a> {
fields: Vec::default(),
attributes: Vec::default(),
methods: vec![
Self::create_method(PrimDef::FunOptionIsSome, self.is_some_ty.0),
Self::create_method(PrimDef::FunOptionIsNone, self.is_some_ty.0),
Self::create_method(PrimDef::FunOptionUnwrap, self.unwrap_ty.0),
Self::create_method(PrimDef::OptionIsSome, self.is_some_ty.0),
Self::create_method(PrimDef::OptionIsNone, self.is_some_ty.0),
Self::create_method(PrimDef::OptionUnwrap, self.unwrap_ty.0),
],
ancestors: vec![TypeAnnotation::CustomClass {
id: prim.id(),
@ -864,7 +822,7 @@ impl<'a> BuiltinBuilder<'a> {
loc: None,
},
PrimDef::FunOptionUnwrap => TopLevelDef::Function {
PrimDef::OptionUnwrap => TopLevelDef::Function {
name: prim.name().into(),
simple_name: prim.simple_name().into(),
signature: self.unwrap_ty.0,
@ -878,7 +836,7 @@ impl<'a> BuiltinBuilder<'a> {
loc: None,
},
PrimDef::FunOptionIsNone | PrimDef::FunOptionIsSome => TopLevelDef::Function {
PrimDef::OptionIsNone | PrimDef::OptionIsSome => TopLevelDef::Function {
name: prim.name().to_string(),
simple_name: prim.simple_name().into(),
signature: self.is_some_ty.0,
@ -899,10 +857,10 @@ impl<'a> BuiltinBuilder<'a> {
};
let returned_int = match prim {
PrimDef::FunOptionIsNone => {
PrimDef::OptionIsNone => {
ctx.builder.build_is_null(ptr, prim.simple_name())
}
PrimDef::FunOptionIsSome => {
PrimDef::OptionIsSome => {
ctx.builder.build_is_not_null(ptr, prim.simple_name())
}
_ => unreachable!(),
@ -921,7 +879,6 @@ 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]),
@ -976,7 +933,7 @@ impl<'a> BuiltinBuilder<'a> {
fn build_ndarray_class_related(&self, prim: PrimDef) -> TopLevelDef {
debug_assert_prim_is_allowed(
prim,
&[PrimDef::NDArray, PrimDef::FunNDArrayCopy, PrimDef::FunNDArrayFill],
&[PrimDef::NDArray, PrimDef::NDArrayCopy, PrimDef::NDArrayFill],
);
match prim {
@ -987,8 +944,8 @@ impl<'a> BuiltinBuilder<'a> {
fields: Vec::default(),
attributes: Vec::default(),
methods: vec![
Self::create_method(PrimDef::FunNDArrayCopy, self.ndarray_copy_ty.0),
Self::create_method(PrimDef::FunNDArrayFill, self.ndarray_fill_ty.0),
Self::create_method(PrimDef::NDArrayCopy, self.ndarray_copy_ty.0),
Self::create_method(PrimDef::NDArrayFill, self.ndarray_fill_ty.0),
],
ancestors: Vec::default(),
constructor: None,
@ -996,7 +953,7 @@ impl<'a> BuiltinBuilder<'a> {
loc: None,
},
PrimDef::FunNDArrayCopy => TopLevelDef::Function {
PrimDef::NDArrayCopy => TopLevelDef::Function {
name: prim.name().into(),
simple_name: prim.simple_name().into(),
signature: self.ndarray_copy_ty.0,
@ -1013,7 +970,7 @@ impl<'a> BuiltinBuilder<'a> {
loc: None,
},
PrimDef::FunNDArrayFill => TopLevelDef::Function {
PrimDef::NDArrayFill => TopLevelDef::Function {
name: prim.name().into(),
simple_name: prim.simple_name().into(),
signature: self.ndarray_fill_ty.0,
@ -1056,7 +1013,6 @@ 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(),
@ -1105,7 +1061,7 @@ impl<'a> BuiltinBuilder<'a> {
);
// The size variant of the function determines the size of the returned int.
let int_sized = size_variant.of_int(self.primitives);
let int_sized = get_size_variant_of_int(size_variant, self.primitives);
let ndarray_int_sized =
make_ndarray_ty(self.unifier, self.primitives, Some(int_sized), Some(common_ndim.ty));
@ -1130,7 +1086,7 @@ impl<'a> BuiltinBuilder<'a> {
let arg_ty = fun.0.args[0].ty;
let arg = args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
let ret_elem_ty = size_variant.of_int(&ctx.primitives);
let ret_elem_ty = get_size_variant_of_int(size_variant, &ctx.primitives);
Ok(Some(builtin_fns::call_round(generator, ctx, (arg_ty, arg), ret_elem_ty)?))
}),
)
@ -1171,7 +1127,7 @@ impl<'a> BuiltinBuilder<'a> {
make_ndarray_ty(self.unifier, self.primitives, Some(float), Some(common_ndim.ty));
// The size variant of the function determines the type of int returned
let int_sized = size_variant.of_int(self.primitives);
let int_sized = get_size_variant_of_int(size_variant, self.primitives);
let ndarray_int_sized =
make_ndarray_ty(self.unifier, self.primitives, Some(int_sized), Some(common_ndim.ty));
@ -1194,7 +1150,7 @@ impl<'a> BuiltinBuilder<'a> {
let arg_ty = fun.0.args[0].ty;
let arg = args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
let ret_elem_ty = size_variant.of_int(&ctx.primitives);
let ret_elem_ty = get_size_variant_of_int(size_variant, &ctx.primitives);
let func = match kind {
Kind::Ceil => builtin_fns::call_ceil,
Kind::Floor => builtin_fns::call_floor,
@ -1246,9 +1202,9 @@ 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::gen_ndarray_empty,
PrimDef::FunNpZeros => numpy_new::gen_ndarray_zeros,
PrimDef::FunNpOnes => numpy_new::gen_ndarray_ones,
_ => unreachable!(),
};
func(ctx, &obj, fun, &args, generator).map(|val| Some(val.as_basic_value_enum()))
@ -1276,23 +1232,16 @@ 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 +1272,7 @@ 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::gen_ndarray_full(ctx, &obj, fun, &args, generator)
.map(|val| Some(val.as_basic_value_enum()))
}),
)
@ -1334,24 +1283,17 @@ 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,
@ -1395,12 +1337,7 @@ 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 +1401,31 @@ 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 +1433,54 @@ 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() => {
// Parse `arg`
let sizet = IntModel(generator.get_size_type(ctx.ctx));
builtin_fns::call_len(generator, ctx, (arg_ty, arg)).map(|ret| Some(ret.into()))
let ndarray_ptr_model =
PointerModel(StructModel(NpArray { sizet }));
let ndarray_ptr =
ndarray_ptr_model.review(ctx.ctx, arg.as_any_value_enum());
// Calculate len
// NOTE: Unsized object is asserted in IRRT
let len = call_nac3_ndarray_len(generator, ctx, ndarray_ptr);
let len = len.signed_cast_to_fixed(ctx, Int32, "len_i32");
Some(len.value.as_basic_value_enum())
}
_ => unreachable!(),
}
})
},
)))),
loc: None,
@ -1505,18 +1496,8 @@ 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 +1579,7 @@ 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 +1620,6 @@ 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 +1808,7 @@ 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 +1842,6 @@ 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())
}

127
nac3core/src/toplevel/composer.rs
View File

@ -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()));
@ -787,7 +766,6 @@ impl TopLevelComposer {
let target_ty = get_type_from_type_annotation_kinds(
&temp_def_list,
unifier,
primitives,
&def,
&mut subst_list,
)?;
@ -881,73 +859,7 @@ 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 {
@ -1024,7 +936,6 @@ impl TopLevelComposer {
let ty = get_type_from_type_annotation_kinds(
temp_def_list.as_ref(),
unifier,
primitives_store,
&type_annotation,
&mut None,
)?;
@ -1048,18 +959,11 @@ 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 = {
@ -1098,7 +1002,6 @@ impl TopLevelComposer {
get_type_from_type_annotation_kinds(
&temp_def_list,
unifier,
primitives_store,
&return_ty_annotation,
&mut None,
)?
@ -1311,7 +1214,6 @@ impl TopLevelComposer {
})
}
},
is_vararg: false,
};
// push the dummy type and the type annotation
// into the list for later unification
@ -1720,7 +1622,6 @@ impl TopLevelComposer {
let self_type = get_type_from_type_annotation_kinds(
&def_list,
unifier,
primitives_ty,
&make_self_type_annotation(type_vars, *object_id),
&mut None,
)?;
@ -1737,25 +1638,21 @@ 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 +1719,7 @@ 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([
@ -1911,11 +1803,7 @@ impl TopLevelComposer {
let ty_ann = make_self_type_annotation(type_vars, *class_id);
let self_ty = get_type_from_type_annotation_kinds(
&def_list,
unifier,
primitives_ty,
&ty_ann,
&mut None,
&def_list, unifier, &ty_ann, &mut None,
)?;
vars.extend(type_vars.iter().map(|ty| {
let TypeEnum::TVar { id, .. } = &*unifier.get_ty(*ty) else {
@ -1970,7 +1858,6 @@ 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()
};

348
nac3core/src/toplevel/helper.rs
View File

@ -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;
@ -28,22 +27,17 @@ pub enum PrimDef {
List,
NDArray,
// Option methods
FunOptionIsSome,
FunOptionIsNone,
FunOptionUnwrap,
// Option-related functions
FunSome,
// NDArray methods
FunNDArrayCopy,
FunNDArrayFill,
// Range methods
FunRangeInit,
// NumPy factory functions
// Member Functions
OptionIsSome,
OptionIsNone,
OptionUnwrap,
NDArrayCopy,
NDArrayFill,
FunInt32,
FunInt64,
FunUInt32,
FunUInt64,
FunFloat,
FunNpNDArray,
FunNpEmpty,
FunNpZeros,
@ -52,17 +46,28 @@ pub enum PrimDef {
FunNpArray,
FunNpEye,
FunNpIdentity,
// Miscellaneous NumPy & SciPy functions
FunRound,
FunRound64,
FunNpRound,
FunRangeInit,
FunStr,
FunBool,
FunFloor,
FunFloor64,
FunNpFloor,
FunCeil,
FunCeil64,
FunNpCeil,
FunLen,
FunMin,
FunNpMin,
FunNpMinimum,
FunNpArgmin,
FunMax,
FunNpMax,
FunNpMaximum,
FunNpArgmax,
FunAbs,
FunNpIsNan,
FunNpIsInf,
FunNpSin,
@ -100,46 +105,15 @@ pub enum PrimDef {
FunNpLdExp,
FunNpHypot,
FunNpNextAfter,
FunNpTranspose,
FunNpReshape,
// Linalg functions
FunNpDot,
FunNpLinalgCholesky,
FunNpLinalgQr,
FunNpLinalgSvd,
FunNpLinalgInv,
FunNpLinalgPinv,
FunNpLinalgMatrixPower,
FunNpLinalgDet,
FunSpLinalgLu,
FunSpLinalgSchur,
FunSpLinalgHessenberg,
// Miscellaneous Python & NAC3 functions
FunInt32,
FunInt64,
FunUInt32,
FunUInt64,
FunFloat,
FunRound,
FunRound64,
FunStr,
FunBool,
FunFloor,
FunFloor64,
FunCeil,
FunCeil64,
FunLen,
FunMin,
FunMax,
FunAbs,
// Top-Level Functions
FunSome,
}
/// Associated details of a [`PrimDef`]
pub enum PrimDefDetails {
PrimFunction { name: &'static str, simple_name: &'static str },
PrimClass { name: &'static str, get_ty_fn: fn(&PrimitiveStore) -> Type },
PrimClass { name: &'static str },
}
impl PrimDef {
@ -181,17 +155,15 @@ impl PrimDef {
#[must_use]
pub fn name(&self) -> &'static str {
match self.details() {
PrimDefDetails::PrimFunction { name, .. } | PrimDefDetails::PrimClass { name, .. } => {
name
}
PrimDefDetails::PrimFunction { name, .. } | PrimDefDetails::PrimClass { name } => name,
}
}
/// Get the associated details of this [`PrimDef`]
#[must_use]
pub fn details(self) -> PrimDefDetails {
fn class(name: &'static str, get_ty_fn: fn(&PrimitiveStore) -> Type) -> PrimDefDetails {
PrimDefDetails::PrimClass { name, get_ty_fn }
fn class(name: &'static str) -> PrimDefDetails {
PrimDefDetails::PrimClass { name }
}
fn fun(name: &'static str, simple_name: Option<&'static str>) -> PrimDefDetails {
@ -199,37 +171,29 @@ impl PrimDef {
}
match self {
// Classes
PrimDef::Int32 => class("int32", |primitives| primitives.int32),
PrimDef::Int64 => class("int64", |primitives| primitives.int64),
PrimDef::Float => class("float", |primitives| primitives.float),
PrimDef::Bool => class("bool", |primitives| primitives.bool),
PrimDef::None => class("none", |primitives| primitives.none),
PrimDef::Range => class("range", |primitives| primitives.range),
PrimDef::Str => class("str", |primitives| primitives.str),
PrimDef::Exception => class("Exception", |primitives| primitives.exception),
PrimDef::UInt32 => class("uint32", |primitives| primitives.uint32),
PrimDef::UInt64 => class("uint64", |primitives| primitives.uint64),
PrimDef::Option => class("Option", |primitives| primitives.option),
PrimDef::List => class("list", |primitives| primitives.list),
PrimDef::NDArray => class("ndarray", |primitives| primitives.ndarray),
// Option methods
PrimDef::FunOptionIsSome => fun("Option.is_some", Some("is_some")),
PrimDef::FunOptionIsNone => fun("Option.is_none", Some("is_none")),
PrimDef::FunOptionUnwrap => fun("Option.unwrap", Some("unwrap")),
// Option-related functions
PrimDef::FunSome => fun("Some", None),
// NDArray methods
PrimDef::FunNDArrayCopy => fun("ndarray.copy", Some("copy")),
PrimDef::FunNDArrayFill => fun("ndarray.fill", Some("fill")),
// Range methods
PrimDef::FunRangeInit => fun("range.__init__", Some("__init__")),
// NumPy factory functions
PrimDef::Int32 => class("int32"),
PrimDef::Int64 => class("int64"),
PrimDef::Float => class("float"),
PrimDef::Bool => class("bool"),
PrimDef::None => class("none"),
PrimDef::Range => class("range"),
PrimDef::Str => class("str"),
PrimDef::Exception => class("Exception"),
PrimDef::UInt32 => class("uint32"),
PrimDef::UInt64 => class("uint64"),
PrimDef::Option => class("Option"),
PrimDef::OptionIsSome => fun("Option.is_some", Some("is_some")),
PrimDef::OptionIsNone => fun("Option.is_none", Some("is_none")),
PrimDef::OptionUnwrap => fun("Option.unwrap", Some("unwrap")),
PrimDef::List => class("list"),
PrimDef::NDArray => class("ndarray"),
PrimDef::NDArrayCopy => fun("ndarray.copy", Some("copy")),
PrimDef::NDArrayFill => fun("ndarray.fill", Some("fill")),
PrimDef::FunInt32 => fun("int32", None),
PrimDef::FunInt64 => fun("int64", None),
PrimDef::FunUInt32 => fun("uint32", None),
PrimDef::FunUInt64 => fun("uint64", None),
PrimDef::FunFloat => fun("float", None),
PrimDef::FunNpNDArray => fun("np_ndarray", None),
PrimDef::FunNpEmpty => fun("np_empty", None),
PrimDef::FunNpZeros => fun("np_zeros", None),
@ -238,17 +202,28 @@ impl PrimDef {
PrimDef::FunNpArray => fun("np_array", None),
PrimDef::FunNpEye => fun("np_eye", None),
PrimDef::FunNpIdentity => fun("np_identity", None),
// Miscellaneous NumPy & SciPy functions
PrimDef::FunRound => fun("round", None),
PrimDef::FunRound64 => fun("round64", None),
PrimDef::FunNpRound => fun("np_round", None),
PrimDef::FunRangeInit => fun("range.__init__", Some("__init__")),
PrimDef::FunStr => fun("str", None),
PrimDef::FunBool => fun("bool", None),
PrimDef::FunFloor => fun("floor", None),
PrimDef::FunFloor64 => fun("floor64", None),
PrimDef::FunNpFloor => fun("np_floor", None),
PrimDef::FunCeil => fun("ceil", None),
PrimDef::FunCeil64 => fun("ceil64", None),
PrimDef::FunNpCeil => fun("np_ceil", None),
PrimDef::FunLen => fun("len", None),
PrimDef::FunMin => fun("min", None),
PrimDef::FunNpMin => fun("np_min", None),
PrimDef::FunNpMinimum => fun("np_minimum", None),
PrimDef::FunNpArgmin => fun("np_argmin", None),
PrimDef::FunMax => fun("max", None),
PrimDef::FunNpMax => fun("np_max", None),
PrimDef::FunNpMaximum => fun("np_maximum", None),
PrimDef::FunNpArgmax => fun("np_argmax", None),
PrimDef::FunAbs => fun("abs", None),
PrimDef::FunNpIsNan => fun("np_isnan", None),
PrimDef::FunNpIsInf => fun("np_isinf", None),
PrimDef::FunNpSin => fun("np_sin", None),
@ -286,40 +261,7 @@ impl PrimDef {
PrimDef::FunNpLdExp => fun("np_ldexp", None),
PrimDef::FunNpHypot => fun("np_hypot", None),
PrimDef::FunNpNextAfter => fun("np_nextafter", None),
PrimDef::FunNpTranspose => fun("np_transpose", None),
PrimDef::FunNpReshape => fun("np_reshape", None),
// Linalg functions
PrimDef::FunNpDot => fun("np_dot", None),
PrimDef::FunNpLinalgCholesky => fun("np_linalg_cholesky", None),
PrimDef::FunNpLinalgQr => fun("np_linalg_qr", None),
PrimDef::FunNpLinalgSvd => fun("np_linalg_svd", None),
PrimDef::FunNpLinalgInv => fun("np_linalg_inv", None),
PrimDef::FunNpLinalgPinv => fun("np_linalg_pinv", None),
PrimDef::FunNpLinalgMatrixPower => fun("np_linalg_matrix_power", None),
PrimDef::FunNpLinalgDet => fun("np_linalg_det", None),
PrimDef::FunSpLinalgLu => fun("sp_linalg_lu", None),
PrimDef::FunSpLinalgSchur => fun("sp_linalg_schur", None),
PrimDef::FunSpLinalgHessenberg => fun("sp_linalg_hessenberg", None),
// Miscellaneous Python & NAC3 functions
PrimDef::FunInt32 => fun("int32", None),
PrimDef::FunInt64 => fun("int64", None),
PrimDef::FunUInt32 => fun("uint32", None),
PrimDef::FunUInt64 => fun("uint64", None),
PrimDef::FunFloat => fun("float", None),
PrimDef::FunRound => fun("round", None),
PrimDef::FunRound64 => fun("round64", None),
PrimDef::FunStr => fun("str", None),
PrimDef::FunBool => fun("bool", None),
PrimDef::FunFloor => fun("floor", None),
PrimDef::FunFloor64 => fun("floor64", None),
PrimDef::FunCeil => fun("ceil", None),
PrimDef::FunCeil64 => fun("ceil64", None),
PrimDef::FunLen => fun("len", None),
PrimDef::FunMin => fun("min", None),
PrimDef::FunMax => fun("max", None),
PrimDef::FunAbs => fun("abs", None),
PrimDef::FunSome => fun("Some", None),
}
}
}
@ -470,9 +412,9 @@ impl TopLevelComposer {
let option = unifier.add_ty(TypeEnum::TObj {
obj_id: PrimDef::Option.id(),
fields: vec![
(PrimDef::FunOptionIsSome.simple_name().into(), (is_some_type_fun_ty, true)),
(PrimDef::FunOptionIsNone.simple_name().into(), (is_some_type_fun_ty, true)),
(PrimDef::FunOptionUnwrap.simple_name().into(), (unwrap_fun_ty, true)),
(PrimDef::OptionIsSome.simple_name().into(), (is_some_type_fun_ty, true)),
(PrimDef::OptionIsNone.simple_name().into(), (is_some_type_fun_ty, true)),
(PrimDef::OptionUnwrap.simple_name().into(), (unwrap_fun_ty, true)),
]
.into_iter()
.collect::<HashMap<_, _>>(),
@ -506,7 +448,6 @@ 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]),
@ -514,8 +455,8 @@ impl TopLevelComposer {
let ndarray = unifier.add_ty(TypeEnum::TObj {
obj_id: PrimDef::NDArray.id(),
fields: Mapping::from([
(PrimDef::FunNDArrayCopy.simple_name().into(), (ndarray_copy_fun_ty, true)),
(PrimDef::FunNDArrayFill.simple_name().into(), (ndarray_fill_fun_ty, true)),
(PrimDef::NDArrayCopy.simple_name().into(), (ndarray_copy_fun_ty, true)),
(PrimDef::NDArrayFill.simple_name().into(), (ndarray_fill_fun_ty, true)),
]),
params: into_var_map([ndarray_dtype_tvar, ndarray_ndims_tvar]),
});
@ -734,16 +675,7 @@ 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 +711,30 @@ 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!()

6
nac3core/src/toplevel/mod.rs
View File

@ -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>,

8
nac3core/src/toplevel/numpy.rs
View File

@ -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,

2
nac3core/src/toplevel/snapshots/nac3core__toplevel__test__test_analyze__generic_class.snap
View File

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

2
nac3core/src/toplevel/snapshots/nac3core__toplevel__test__test_analyze__inheritance_override.snap
View File

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

4
nac3core/src/toplevel/snapshots/nac3core__toplevel__test__test_analyze__list_tuple_generic.snap
View File

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

2
nac3core/src/toplevel/snapshots/nac3core__toplevel__test__test_analyze__self1.snap
View File

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

4
nac3core/src/toplevel/snapshots/nac3core__toplevel__test__test_analyze__simple_class_compose.snap
View File

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

15
nac3core/src/toplevel/test.rs
View File

@ -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![

228
nac3core/src/toplevel/type_annotation.rs
View File

@ -1,9 +1,8 @@
use super::*;
use crate::symbol_resolver::SymbolValue;
use crate::toplevel::helper::{PrimDef, PrimDefDetails};
use crate::toplevel::helper::PrimDef;
use crate::typecheck::typedef::VarMap;
use nac3parser::ast::Constant;
use strum::IntoEnumIterator;
#[derive(Clone, Debug)]
pub enum TypeAnnotation {
@ -64,9 +63,9 @@ impl TypeAnnotation {
/// Parses an AST expression `expr` into a [`TypeAnnotation`].
///
/// * `locked` - A [`HashMap`] containing the IDs of known definitions, mapped to a [`Vec`] of all
/// generic variables associated with the definition.
/// generic variables associated with the definition.
/// * `type_var` - The type variable associated with the type argument currently being parsed. Pass
/// [`None`] when this function is invoked externally.
/// [`None`] when this function is invoked externally.
pub fn parse_ast_to_type_annotation_kinds<T, S: std::hash::BuildHasher + Clone>(
resolver: &(dyn SymbolResolver + Send + Sync),
top_level_defs: &[Arc<RwLock<TopLevelDef>>],
@ -358,7 +357,6 @@ pub fn parse_ast_to_type_annotation_kinds<T, S: std::hash::BuildHasher + Clone>(
pub fn get_type_from_type_annotation_kinds(
top_level_defs: &[Arc<RwLock<TopLevelDef>>],
unifier: &mut Unifier,
primitives: &PrimitiveStore,
ann: &TypeAnnotation,
subst_list: &mut Option<Vec<Type>>,
) -> Result<Type, HashSet<String>> {
@ -381,141 +379,100 @@ pub fn get_type_from_type_annotation_kinds(
let param_ty = params
.iter()
.map(|x| {
get_type_from_type_annotation_kinds(
top_level_defs,
unifier,
primitives,
x,
subst_list,
)
get_type_from_type_annotation_kinds(top_level_defs, unifier, x, subst_list)
})
.collect::<Result<Vec<_>, _>>()?;
let ty = if let Some(prim_def) = PrimDef::iter().find(|prim| prim.id() == *obj_id) {
// Primitive TopLevelDefs do not contain all fields that are present in their Type
// counterparts, so directly perform subst on the Type instead.
let PrimDefDetails::PrimClass { get_ty_fn, .. } = prim_def.details() else {
unreachable!()
};
let base_ty = get_ty_fn(primitives);
let params =
if let TypeEnum::TObj { params, .. } = &*unifier.get_ty_immutable(base_ty) {
params.clone()
} else {
unreachable!()
};
unifier
.subst(
get_ty_fn(primitives),
&params
.iter()
.zip(param_ty)
.map(|(obj_tv, param)| (*obj_tv.0, param))
.collect(),
)
.unwrap_or(base_ty)
} else {
let subst = {
// check for compatible range
// TODO: if allow type var to be applied(now this disallowed in the parse_to_type_annotation), need more check
let mut result = VarMap::new();
for (tvar, p) in type_vars.iter().zip(param_ty) {
match unifier.get_ty(*tvar).as_ref() {
TypeEnum::TVar {
id,
range,
fields: None,
name,
loc,
is_const_generic: false,
} => {
let ok: bool = {
// create a temp type var and unify to check compatibility
p == *tvar || {
let temp = unifier.get_fresh_var_with_range(
range.as_slice(),
*name,
*loc,
);
unifier.unify(temp.ty, p).is_ok()
}
};
if ok {
result.insert(*id, p);
} else {
return Err(HashSet::from([format!(
"cannot apply type {} to type variable with id {:?}",
unifier.internal_stringify(
p,
&mut |id| format!("class{id}"),
&mut |id| format!("typevar{id}"),
&mut None
),
*id
)]));
let subst = {
// check for compatible range
// TODO: if allow type var to be applied(now this disallowed in the parse_to_type_annotation), need more check
let mut result = VarMap::new();
for (tvar, p) in type_vars.iter().zip(param_ty) {
match unifier.get_ty(*tvar).as_ref() {
TypeEnum::TVar {
id,
range,
fields: None,
name,
loc,
is_const_generic: false,
} => {
let ok: bool = {
// create a temp type var and unify to check compatibility
p == *tvar || {
let temp = unifier.get_fresh_var_with_range(
range.as_slice(),
*name,
*loc,
);
unifier.unify(temp.ty, p).is_ok()
}
};
if ok {
result.insert(*id, p);
} else {
return Err(HashSet::from([format!(
"cannot apply type {} to type variable with id {:?}",
unifier.internal_stringify(
p,
&mut |id| format!("class{id}"),
&mut |id| format!("typevar{id}"),
&mut None
),
*id
)]));
}
TypeEnum::TVar {
id, range, name, loc, is_const_generic: true, ..
} => {
let ty = range[0];
let ok: bool = {
// create a temp type var and unify to check compatibility
p == *tvar || {
let temp =
unifier.get_fresh_const_generic_var(ty, *name, *loc);
unifier.unify(temp.ty, p).is_ok()
}
};
if ok {
result.insert(*id, p);
} else {
return Err(HashSet::from([format!(
"cannot apply type {} to type variable {}",
unifier.stringify(p),
name.unwrap_or_else(|| format!("typevar{id}").into()),
)]));
}
}
_ => unreachable!("must be generic type var"),
}
}
result
};
// Class Attributes keep a copy with Class Definition and are not added to objects
let mut tobj_fields = methods
.iter()
.map(|(name, ty, _)| {
let subst_ty = unifier.subst(*ty, &subst).unwrap_or(*ty);
// methods are immutable
(*name, (subst_ty, false))
})
.collect::<HashMap<_, _>>();
tobj_fields.extend(fields.iter().map(|(name, ty, mutability)| {
let subst_ty = unifier.subst(*ty, &subst).unwrap_or(*ty);
(*name, (subst_ty, *mutability))
}));
let need_subst = !subst.is_empty();
let ty = unifier.add_ty(TypeEnum::TObj {
obj_id: *obj_id,
fields: tobj_fields,
params: subst,
});
if need_subst {
if let Some(wl) = subst_list.as_mut() {
wl.push(ty);
TypeEnum::TVar { id, range, name, loc, is_const_generic: true, .. } => {
let ty = range[0];
let ok: bool = {
// create a temp type var and unify to check compatibility
p == *tvar || {
let temp = unifier.get_fresh_const_generic_var(ty, *name, *loc);
unifier.unify(temp.ty, p).is_ok()
}
};
if ok {
result.insert(*id, p);
} else {
return Err(HashSet::from([format!(
"cannot apply type {} to type variable {}",
unifier.stringify(p),
name.unwrap_or_else(|| format!("typevar{id}").into()),
)]));
}
}
_ => unreachable!("must be generic type var"),
}
}
ty
result
};
// Class Attributes keep a copy with Class Definition and are not added to objects
let mut tobj_fields = methods
.iter()
.map(|(name, ty, _)| {
let subst_ty = unifier.subst(*ty, &subst).unwrap_or(*ty);
// methods are immutable
(*name, (subst_ty, false))
})
.collect::<HashMap<_, _>>();
tobj_fields.extend(fields.iter().map(|(name, ty, mutability)| {
let subst_ty = unifier.subst(*ty, &subst).unwrap_or(*ty);
(*name, (subst_ty, *mutability))
}));
let need_subst = !subst.is_empty();
let ty = unifier.add_ty(TypeEnum::TObj {
obj_id: *obj_id,
fields: tobj_fields,
params: subst,
});
if need_subst {
if let Some(wl) = subst_list.as_mut() {
wl.push(ty);
}
}
Ok(ty)
}
TypeAnnotation::Primitive(ty) | TypeAnnotation::TypeVar(ty) => Ok(*ty),
@ -533,7 +490,6 @@ pub fn get_type_from_type_annotation_kinds(
let ty = get_type_from_type_annotation_kinds(
top_level_defs,
unifier,
primitives,
ty.as_ref(),
subst_list,
)?;
@ -543,16 +499,10 @@ pub fn get_type_from_type_annotation_kinds(
let tys = tys
.iter()
.map(|x| {
get_type_from_type_annotation_kinds(
top_level_defs,
unifier,
primitives,
x,
subst_list,
)
get_type_from_type_annotation_kinds(top_level_defs, unifier, x, subst_list)
})
.collect::<Result<Vec<_>, _>>()?;
Ok(unifier.add_ty(TypeEnum::TTuple { ty: tys, is_vararg_ctx: false }))
Ok(unifier.add_ty(TypeEnum::TTuple { ty: tys }))
}
}
}

37
nac3core/src/typecheck/function_check.rs
View File

@ -34,18 +34,13 @@ impl<'a> Inferencer<'a> {
self.should_have_value(pattern)?;
Ok(())
}
ExprKind::List { elts, .. } | ExprKind::Tuple { elts, .. } => {
ExprKind::Tuple { elts, .. } => {
for elt in elts {
self.check_pattern(elt, defined_identifiers)?;
self.should_have_value(elt)?;
}
Ok(())
}
ExprKind::Starred { value, .. } => {
self.check_pattern(value, defined_identifiers)?;
self.should_have_value(value)?;
Ok(())
}
ExprKind::Subscript { value, slice, .. } => {
self.check_expr(value, defined_identifiers)?;
self.should_have_value(value)?;
@ -212,23 +207,19 @@ impl<'a> Inferencer<'a> {
/// This is a workaround preventing the caller from using a variable `alloca`-ed in the body, which
/// is freed when the function returns.
fn check_return_value_ty(&mut self, ret_ty: Type) -> bool {
if cfg!(feature = "no-escape-analysis") {
true
} else {
match &*self.unifier.get_ty_immutable(ret_ty) {
TypeEnum::TObj { .. } => [
self.primitives.int32,
self.primitives.int64,
self.primitives.uint32,
self.primitives.uint64,
self.primitives.float,
self.primitives.bool,
]
.iter()
.any(|allowed_ty| self.unifier.unioned(ret_ty, *allowed_ty)),
TypeEnum::TTuple { ty, .. } => ty.iter().all(|t| self.check_return_value_ty(*t)),
_ => false,
}
match &*self.unifier.get_ty_immutable(ret_ty) {
TypeEnum::TObj { .. } => [
self.primitives.int32,
self.primitives.int64,
self.primitives.uint32,
self.primitives.uint64,
self.primitives.float,
self.primitives.bool,
]
.iter()
.any(|allowed_ty| self.unifier.unioned(ret_ty, *allowed_ty)),
TypeEnum::TTuple { ty } => ty.iter().all(|t| self.check_return_value_ty(*t)),
_ => false,
}
}

23
nac3core/src/typecheck/magic_methods.rs
View File

@ -197,7 +197,6 @@ pub fn impl_binop(
ty: other_ty,
default_value: None,
name: "other".into(),
is_vararg: false,
}],
})),
false,
@ -262,7 +261,6 @@ pub fn impl_cmpop(
ty: other_ty,
default_value: None,
name: "other".into(),
is_vararg: false,
}],
})),
false,
@ -520,23 +518,6 @@ pub fn typeof_binop(
}
Operator::MatMult => {
// NOTE: NumPy matmul's LHS and RHS must both be ndarrays. Scalars are not allowed.
match (&*unifier.get_ty(lhs), &*unifier.get_ty(rhs)) {
(
TypeEnum::TObj { obj_id: lhs_obj_id, .. },
TypeEnum::TObj { obj_id: rhs_obj_id, .. },
) if *lhs_obj_id == primitives.ndarray.obj_id(unifier).unwrap()
&& *rhs_obj_id == primitives.ndarray.obj_id(unifier).unwrap() =>
{
// LHS and RHS have valid types
}
_ => {
let lhs_str = unifier.stringify(lhs);
let rhs_str = unifier.stringify(rhs);
return Err(format!("ndarray.__matmul__ only accepts ndarray operands, but left operand has type {lhs_str}, and right operand has type {rhs_str}"));
}
}
let (_, lhs_ndims) = unpack_ndarray_var_tys(unifier, lhs);
let lhs_ndims = match &*unifier.get_ty_immutable(lhs_ndims) {
TypeEnum::TLiteral { values, .. } => {
@ -697,7 +678,6 @@ pub fn set_primitives_magic_methods(store: &PrimitiveStore, unifier: &mut Unifie
bool: bool_t,
uint32: uint32_t,
uint64: uint64_t,
str: str_t,
list: list_t,
ndarray: ndarray_t,
..
@ -743,9 +723,6 @@ pub fn set_primitives_magic_methods(store: &PrimitiveStore, unifier: &mut Unifie
impl_sign(unifier, store, bool_t, Some(int32_t));
impl_eq(unifier, store, bool_t, &[bool_t, ndarray_bool_t], None);
/* str ========= */
impl_cmpop(unifier, store, str_t, &[str_t], &[Cmpop::Eq, Cmpop::NotEq], Some(bool_t));
/* list ======== */
impl_binop(unifier, store, list_t, &[list_t], Some(list_t), &[Operator::Add]);
impl_binop(unifier, store, list_t, &[int32_t, int64_t], Some(list_t), &[Operator::Mult]);

7
nac3core/src/typecheck/type_error.rs
View File

@ -183,10 +183,9 @@ impl<'a> Display for DisplayTypeError<'a> {
}
result
}
(
TypeEnum::TTuple { ty: ty1, is_vararg_ctx: is_vararg1 },
TypeEnum::TTuple { ty: ty2, is_vararg_ctx: is_vararg2 },
) if !is_vararg1 && !is_vararg2 && ty1.len() != ty2.len() => {
(TypeEnum::TTuple { ty: ty1 }, TypeEnum::TTuple { ty: ty2 })
if ty1.len() != ty2.len() =>
{
let t1 = self.unifier.stringify_with_notes(*t1, &mut notes);
let t2 = self.unifier.stringify_with_notes(*t2, &mut notes);
write!(f, "Tuple length mismatch: got {t1} and {t2}")

1106
nac3core/src/typecheck/type_inferencer/mod.rs
View File

File diff suppressed because it is too large Load Diff

14
nac3core/src/typecheck/type_inferencer/test.rs
View File

@ -83,12 +83,7 @@ impl TestEnvironment {
});
with_fields(&mut unifier, int32, |unifier, fields| {
let add_ty = unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![FuncArg {
name: "other".into(),
ty: int32,
default_value: None,
is_vararg: false,
}],
args: vec![FuncArg { name: "other".into(), ty: int32, default_value: None }],
ret: int32,
vars: VarMap::new(),
}));
@ -229,12 +224,7 @@ impl TestEnvironment {
});
with_fields(&mut unifier, int32, |unifier, fields| {
let add_ty = unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![FuncArg {
name: "other".into(),
ty: int32,
default_value: None,
is_vararg: false,
}],
args: vec![FuncArg { name: "other".into(), ty: int32, default_value: None }],
ret: int32,
vars: VarMap::new(),
}));

197
nac3core/src/typecheck/typedef/mod.rs
View File

@ -1,4 +1,16 @@
use super::magic_methods::{Binop, HasOpInfo};
use indexmap::IndexMap;
use itertools::Itertools;
use std::cell::RefCell;
use std::collections::HashMap;
use std::fmt::{self, Display};
use std::iter::zip;
use std::rc::Rc;
use std::sync::{Arc, Mutex};
use std::{borrow::Cow, collections::HashSet};
use nac3parser::ast::{Cmpop, Location, StrRef, Unaryop};
use super::magic_methods::Binop;
use super::type_error::{TypeError, TypeErrorKind};
use super::unification_table::{UnificationKey, UnificationTable};
use crate::symbol_resolver::SymbolValue;
@ -6,16 +18,6 @@ use crate::toplevel::helper::PrimDef;
use crate::toplevel::{DefinitionId, TopLevelContext, TopLevelDef};
use crate::typecheck::magic_methods::OpInfo;
use crate::typecheck::type_inferencer::PrimitiveStore;
use indexmap::IndexMap;
use itertools::{repeat_n, Itertools};
use nac3parser::ast::{Cmpop, Location, StrRef, Unaryop};
use std::cell::RefCell;
use std::collections::HashMap;
use std::fmt::{self, Display};
use std::iter::{repeat, zip};
use std::rc::Rc;
use std::sync::{Arc, Mutex};
use std::{borrow::Cow, collections::HashSet};
#[cfg(test)]
mod test;
@ -113,7 +115,6 @@ pub struct FuncArg {
pub name: StrRef,
pub ty: Type,
pub default_value: Option<SymbolValue>,
pub is_vararg: bool,
}
impl FuncArg {
@ -232,12 +233,6 @@ pub enum TypeEnum {
TTuple {
/// The types of elements present in this tuple.
ty: Vec<Type>,
/// Whether this tuple is used in a vararg context.
///
/// If `true`, `ty` must only contain one type, and the tuple is assumed to contain any
/// number of `ty`-typed values.
is_vararg_ctx: bool,
},
/// An object type.
@ -532,7 +527,7 @@ impl Unifier {
TypeEnum::TVirtual { ty } => self.get_instantiations(*ty).map(|ty| {
ty.iter().map(|&ty| self.add_ty(TypeEnum::TVirtual { ty })).collect_vec()
}),
TypeEnum::TTuple { ty, is_vararg_ctx } => {
TypeEnum::TTuple { ty } => {
let tuples = ty
.iter()
.map(|ty| self.get_instantiations(*ty).unwrap_or_else(|| vec![*ty]))
@ -542,12 +537,7 @@ impl Unifier {
None
} else {
Some(
tuples
.into_iter()
.map(|ty| {
self.add_ty(TypeEnum::TTuple { ty, is_vararg_ctx: *is_vararg_ctx })
})
.collect(),
tuples.into_iter().map(|ty| self.add_ty(TypeEnum::TTuple { ty })).collect(),
)
}
}
@ -591,7 +581,7 @@ impl Unifier {
TVar { .. } => allowed_typevars.iter().any(|b| self.unification_table.unioned(a, *b)),
TCall { .. } => false,
TVirtual { ty } => self.is_concrete(*ty, allowed_typevars),
TTuple { ty, .. } => ty.iter().all(|ty| self.is_concrete(*ty, allowed_typevars)),
TTuple { ty } => ty.iter().all(|ty| self.is_concrete(*ty, allowed_typevars)),
TObj { params: vars, .. } => {
vars.values().all(|ty| self.is_concrete(*ty, allowed_typevars))
}
@ -659,7 +649,6 @@ impl Unifier {
// Get details about the function signature/parameters.
let num_params = signature.args.len();
let is_vararg = signature.args.iter().any(|arg| arg.is_vararg);
// Force the type vars in `b` and `signature' to be up-to-date.
let b = self.instantiate_fun(b, signature);
@ -748,7 +737,7 @@ impl Unifier {
};
// Check for "too many arguments"
if !is_vararg && num_params < posargs.len() {
if num_params < posargs.len() {
let expected_min_count =
signature.args.iter().filter(|param| param.is_required()).count();
let expected_max_count = num_params;
@ -781,19 +770,6 @@ impl Unifier {
type_check_arg(param.name, param.ty, arg_ty)?;
}
if is_vararg {
debug_assert!(!signature.args.is_empty());
let vararg_args = posargs.iter().skip(signature.args.len());
let vararg_param = signature.args.last().unwrap();
for (&arg_ty, param) in zip(vararg_args, repeat(vararg_param)) {
// `param_info` for this argument would've already been marked as supplied
// during non-vararg posarg typecheck
type_check_arg(param.name, param.ty, arg_ty)?;
}
}
// Now consume all keyword arguments and typecheck them.
for (&param_name, &arg_ty) in kwargs {
// We will also use this opportunity to check if this keyword argument is "legal".
@ -983,10 +959,7 @@ impl Unifier {
self.unify_impl(x, b, false)?;
self.set_a_to_b(a, x);
}
(
TVar { fields: Some(fields), range, is_const_generic: false, .. },
TTuple { ty, .. },
) => {
(TVar { fields: Some(fields), range, is_const_generic: false, .. }, TTuple { ty }) => {
let len = i32::try_from(ty.len()).unwrap();
for (k, v) in fields {
match *k {
@ -1007,18 +980,8 @@ impl Unifier {
self.unify_impl(v.ty, ty[ind as usize], false)
.map_err(|e| e.at(v.loc))?;
}
RecordKey::Str(s) => {
let tuple_fns = [
Cmpop::Eq.op_info().method_name,
Cmpop::NotEq.op_info().method_name,
];
if !tuple_fns.into_iter().any(|op| s.to_string() == op) {
return Err(TypeError::new(
TypeErrorKind::NoSuchField(*k, b),
v.loc,
));
}
RecordKey::Str(_) => {
return Err(TypeError::new(TypeErrorKind::NoSuchField(*k, b), v.loc))
}
}
}
@ -1093,47 +1056,15 @@ impl Unifier {
self.set_a_to_b(a, b);
}
(
TTuple { ty: ty1, is_vararg_ctx: is_vararg1 },
TTuple { ty: ty2, is_vararg_ctx: is_vararg2 },
) => {
// Rules for Tuples:
// - ty1: is_vararg && ty2: is_vararg -> ty1[0] == ty2[0]
// - ty1: is_vararg && ty2: !is_vararg -> type error (not enough info to infer the correct number of arguments)
// - ty1: !is_vararg && ty2: is_vararg -> ty1[..] == ty2[0]
// - ty1: !is_vararg && ty2: !is_vararg -> ty1.len() == ty2.len() && ty1[i] == ty2[i]
debug_assert!(!is_vararg1 || ty1.len() == 1);
debug_assert!(!is_vararg2 || ty2.len() == 1);
match (*is_vararg1, *is_vararg2) {
(true, true) => {
if self.unify_impl(ty1[0], ty2[0], false).is_err() {
return Self::incompatible_types(a, b);
}
}
(true, false) => return Self::incompatible_types(a, b),
(false, true) => {
for y in ty2 {
if self.unify_impl(ty1[0], *y, false).is_err() {
return Self::incompatible_types(a, b);
}
}
}
(false, false) => {
if ty1.len() != ty2.len() {
return Self::incompatible_types(a, b);
}
for (x, y) in ty1.iter().zip(ty2.iter()) {
if self.unify_impl(*x, *y, false).is_err() {
return Self::incompatible_types(a, b);
}
}
(TTuple { ty: ty1 }, TTuple { ty: ty2 }) => {
if ty1.len() != ty2.len() {
return Err(TypeError::new(TypeErrorKind::IncompatibleTypes(a, b), None));
}
for (x, y) in ty1.iter().zip(ty2.iter()) {
if self.unify_impl(*x, *y, false).is_err() {
return Err(TypeError::new(TypeErrorKind::IncompatibleTypes(a, b), None));
}
}
self.set_a_to_b(a, b);
}
(TVar { fields: Some(map), range, .. }, TObj { obj_id, fields, params }) => {
@ -1376,22 +1307,10 @@ impl Unifier {
TypeEnum::TLiteral { values, .. } => {
format!("const({})", values.iter().map(|v| format!("{v:?}")).join(", "))
}
TypeEnum::TTuple { ty, is_vararg_ctx } => {
if *is_vararg_ctx {
debug_assert_eq!(ty.len(), 1);
let field = self.internal_stringify(
*ty.iter().next().unwrap(),
obj_to_name,
var_to_name,
notes,
);
format!("tuple[*{field}]")
} else {
let mut fields = ty
.iter()
.map(|v| self.internal_stringify(*v, obj_to_name, var_to_name, notes));
format!("tuple[{}]", fields.join(", "))
}
TypeEnum::TTuple { ty } => {
let mut fields =
ty.iter().map(|v| self.internal_stringify(*v, obj_to_name, var_to_name, notes));
format!("tuple[{}]", fields.join(", "))
}
TypeEnum::TVirtual { ty } => {
format!(
@ -1416,21 +1335,17 @@ impl Unifier {
.args
.iter()
.map(|arg| {
let vararg_prefix = if arg.is_vararg { "*" } else { "" };
if let Some(dv) = &arg.default_value {
format!(
"{}:{}{}={}",
"{}:{}={}",
arg.name,
vararg_prefix,
self.internal_stringify(arg.ty, obj_to_name, var_to_name, notes),
dv
)
} else {
format!(
"{}:{}{}",
"{}:{}",
arg.name,
vararg_prefix,
self.internal_stringify(arg.ty, obj_to_name, var_to_name, notes)
)
}
@ -1516,7 +1431,7 @@ impl Unifier {
match &*ty {
TypeEnum::TRigidVar { .. } | TypeEnum::TLiteral { .. } => None,
TypeEnum::TVar { id, .. } => mapping.get(id).copied(),
TypeEnum::TTuple { ty, is_vararg_ctx } => {
TypeEnum::TTuple { ty } => {
let mut new_ty = Cow::from(ty);
for (i, t) in ty.iter().enumerate() {
if let Some(t1) = self.subst_impl(*t, mapping, cache) {
@ -1524,10 +1439,7 @@ impl Unifier {
}
}
if matches!(new_ty, Cow::Owned(_)) {
Some(self.add_ty(TypeEnum::TTuple {
ty: new_ty.into_owned(),
is_vararg_ctx: *is_vararg_ctx,
}))
Some(self.add_ty(TypeEnum::TTuple { ty: new_ty.into_owned() }))
} else {
None
}
@ -1687,37 +1599,16 @@ impl Unifier {
}
}
(TVar { range, .. }, _) => self.check_var_compatibility(b, range).or(Err(())),
(
TTuple { ty: ty1, is_vararg_ctx: is_vararg1 },
TTuple { ty: ty2, is_vararg_ctx: is_vararg2 },
) => {
if *is_vararg1 && *is_vararg2 {
let isect_ty = self.get_intersection(ty1[0], ty2[0])?;
Ok(isect_ty.map(|ty| self.add_ty(TTuple { ty: vec![ty], is_vararg_ctx: true })))
(TTuple { ty: ty1 }, TTuple { ty: ty2 }) if ty1.len() == ty2.len() => {
let ty: Vec<_> = zip(ty1.iter(), ty2.iter())
.map(|(a, b)| self.get_intersection(*a, *b))
.try_collect()?;
if ty.iter().any(Option::is_some) {
Ok(Some(self.add_ty(TTuple {
ty: zip(ty, ty1.iter()).map(|(a, b)| a.unwrap_or(*b)).collect(),
})))
} else {
let zip_iter: Box<dyn Iterator<Item = (&Type, &Type)>> =
match (*is_vararg1, *is_vararg2) {
(true, _) => Box::new(repeat_n(&ty1[0], ty2.len()).zip(ty2.iter())),
(_, false) => Box::new(ty1.iter().zip(repeat_n(&ty2[0], ty1.len()))),
_ => {
if ty1.len() != ty2.len() {
return Err(());
}
Box::new(ty1.iter().zip(ty2.iter()))
}
};
let ty: Vec<_> =
zip_iter.map(|(a, b)| self.get_intersection(*a, *b)).try_collect()?;
Ok(if ty.iter().any(Option::is_some) {
Some(self.add_ty(TTuple {
ty: zip(ty, ty1.iter()).map(|(a, b)| a.unwrap_or(*b)).collect(),
is_vararg_ctx: false,
}))
} else {
None
})
Ok(None)
}
}
// TODO(Derppening): #444

9
nac3core/src/typecheck/typedef/test.rs
View File

@ -28,10 +28,7 @@ impl Unifier {
TypeEnum::TVar { fields: Some(map1), .. },
TypeEnum::TVar { fields: Some(map2), .. },
) => self.map_eq2(map1, map2),
(
TypeEnum::TTuple { ty: ty1, is_vararg_ctx: false },
TypeEnum::TTuple { ty: ty2, is_vararg_ctx: false },
) => {
(TypeEnum::TTuple { ty: ty1 }, TypeEnum::TTuple { ty: ty2 }) => {
ty1.len() == ty2.len()
&& ty1.iter().zip(ty2.iter()).all(|(t1, t2)| self.eq(*t1, *t2))
}
@ -181,7 +178,7 @@ impl TestEnvironment {
ty.push(result.0);
s = result.1;
}
(self.unifier.add_ty(TypeEnum::TTuple { ty, is_vararg_ctx: false }), &s[1..])
(self.unifier.add_ty(TypeEnum::TTuple { ty }), &s[1..])
}
"Record" => {
let mut s = &typ[end..];
@ -611,7 +608,7 @@ fn test_instantiation() {
let v1 = env.unifier.get_fresh_var_with_range(&[list_v, int], None, None).ty;
let v2 = env.unifier.get_fresh_var_with_range(&[list_int, float], None, None).ty;
let t = env.unifier.get_dummy_var().ty;
let tuple = env.unifier.add_ty(TypeEnum::TTuple { ty: vec![v, v1, v2], is_vararg_ctx: false });
let tuple = env.unifier.add_ty(TypeEnum::TTuple { ty: vec![v, v1, v2] });
let v3 = env.unifier.get_fresh_var_with_range(&[tuple, t], None, None).ty;
// t = TypeVar('t')
// v = TypeVar('v', int, bool)

6
nac3core/src/util.rs Normal file
View File

@ -0,0 +1,6 @@
/// A helper enum used by [`BuiltinBuilder`]
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum SizeVariant {
Bits32,
Bits64,
}

2
nac3ld/src/dwarf.rs
View File

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

3
nac3standalone/Cargo.toml
View File

@ -4,9 +4,6 @@ version = "0.1.0"
authors = ["M-Labs"]
edition = "2021"
[features]
no-escape-analysis = ["nac3core/no-escape-analysis"]
[dependencies]
parking_lot = "0.12"
nac3parser = { path = "../nac3parser" }

61
nac3standalone/demo/check_demo.sh
View File

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

5
nac3standalone/demo/check_demos.sh
View File

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

62
nac3standalone/demo/demo.c
View File

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

28
nac3standalone/demo/interpret_demo.py
View File

@ -6,7 +6,6 @@ import importlib.machinery
import math
import numpy as np
import numpy.typing as npt
import scipy as sp
import pathlib
from numpy import int32, int64, uint32, uint64
@ -168,7 +167,7 @@ def patch(module):
module.ceil64 = _ceil
module.np_ceil = np.ceil
# NumPy NDArray factory functions
# NumPy ndarray functions
module.ndarray = NDArray
module.np_ndarray = np.ndarray
module.np_empty = np.empty
@ -218,10 +217,8 @@ def patch(module):
module.np_ldexp = np.ldexp
module.np_hypot = np.hypot
module.np_nextafter = np.nextafter
module.np_transpose = np.transpose
module.np_reshape = np.reshape
# SciPy Math functions
# SciPy Math Functions
module.sp_spec_erf = special.erf
module.sp_spec_erfc = special.erfc
module.sp_spec_gamma = special.gamma
@ -229,19 +226,14 @@ def patch(module):
module.sp_spec_j0 = special.j0
module.sp_spec_j1 = special.j1
# Linalg functions
module.np_dot = np.dot
module.np_linalg_cholesky = np.linalg.cholesky
module.np_linalg_qr = np.linalg.qr
module.np_linalg_svd = np.linalg.svd
module.np_linalg_inv = np.linalg.inv
module.np_linalg_pinv = np.linalg.pinv
module.np_linalg_matrix_power = np.linalg.matrix_power
module.np_linalg_det = np.linalg.det
module.sp_linalg_lu = lambda x: sp.linalg.lu(x, True)
module.sp_linalg_schur = sp.linalg.schur
module.sp_linalg_hessenberg = lambda x: sp.linalg.hessenberg(x, True)
# NumPy NDArray Functions
module.np_ndarray = np.ndarray
module.np_empty = np.empty
module.np_zeros = np.zeros
module.np_ones = np.ones
module.np_full = np.full
module.np_eye = np.eye
module.np_identity = np.identity
def file_import(filename, prefix="file_import_"):
filename = pathlib.Path(filename)

114
nac3standalone/demo/linalg/Cargo.lock generated
View File

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

13
nac3standalone/demo/linalg/Cargo.toml
View File

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

406
nac3standalone/demo/linalg/src/lib.rs
View File

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

48
nac3standalone/demo/run_demo.sh
View File

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

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