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23 Commits

Author SHA1 Message Date
eb5c029414 start statement check, fix some error message 2021-07-27 16:06:13 +08:00
9603aa644a change the symbol resolver back and add some test case 2021-07-27 10:57:25 +08:00
512fc59281 test_case can be used, update symbol_resolver 2021-07-27 10:24:53 +08:00
d14076fe7f fix test_case import bug 2021-07-26 17:38:09 +08:00
e631e4997b add some error message, try to write test using test case 2021-07-26 17:30:48 +08:00
123c5cf903 error_stack added, starting to working on writing error messages 2021-07-26 13:33:48 +08:00
132bc101b0 modified the with_context api and add error_stack 2021-07-26 13:01:47 +08:00
bf675e0863 change wrong spelling of attribute 2021-07-19 17:25:07 +08:00
8f0c335422 directly return after folding the special case of list comprehension 2021-07-19 13:52:53 +08:00
7b93720236 fix some warning from clippy 2021-07-19 13:49:09 +08:00
c7051fcc22 directly impl Fold<()> for InferenceContext 2021-07-19 12:03:13 +08:00
94ffe4dac2 change from prefold to fold_listcomp, and simply the fold_listcomp 2021-07-16 18:13:38 +08:00
b961128367 some more test for tupe constant indexing 2021-07-16 13:12:59 +08:00
de82fbabd8 tuple constant indexing now supported 2021-07-16 13:00:30 +08:00
be512985a7 add wrapper, now can fold from Expr<()> to Expr<Option<Type>>; fix slice; some more testing 2021-07-16 11:28:32 +08:00
f33b3d3482 add some test 2021-07-15 11:49:23 +08:00
7823851fd6 clean up some code, need to test more 2021-07-15 10:47:03 +08:00
c5bef86001 direct impl fold trait on InferenceContext, now code is cleaner, need further test and review 2021-07-14 17:19:03 +08:00
4abe99f6b3 refactor the using of rustpython fold again, now can use with_scope, need further testing 2021-07-14 17:06:00 +08:00
7eb0ab41d4 expression type check, but list comprehension done in a bad way for now... 2021-07-13 16:23:03 +08:00
144b84a612 expr type inference, subscript slice needs to be removed, list comprehension needs to be fixed 2021-07-13 01:25:22 +08:00
3dc448401b refactortherefactor 2021-07-09 13:41:31 +08:00
b161c026bc expression partially done, need review 2021-07-06 12:23:30 +08:00
264 changed files with 2625 additions and 66291 deletions

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BreakConstructorInitializers: AfterColon
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doc-valid-idents = ["CPython", "NumPy", ".."]

2
.gitignore vendored
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__pycache__ __pycache__
/target /target
/nac3standalone/demo/linalg/target
nix/windows/msys2

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# See https://pre-commit.com for more information
# See https://pre-commit.com/hooks.html for more hooks
default_stages: [pre-commit]
repos:
- repo: local
hooks:
- id: nac3-cargo-fmt
name: nac3 cargo format
entry: nix
language: system
types: [file, rust]
pass_filenames: false
description: Runs cargo fmt on the codebase.
args: [develop, -c, cargo, fmt, --all]
- id: nac3-cargo-clippy
name: nac3 cargo clippy
entry: nix
language: system
types: [file, rust]
pass_filenames: false
description: Runs cargo clippy on the codebase.
args: [develop, -c, cargo, clippy, --tests]

1473
Cargo.lock generated

File diff suppressed because it is too large Load Diff

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@ -1,15 +1,6 @@
[workspace] [workspace]
members = [ members = [
"nac3ld",
"nac3ast",
"nac3parser",
"nac3core", "nac3core",
"nac3core/nac3core_derive",
"nac3standalone", "nac3standalone",
"nac3artiq", "nac3embedded",
"runkernel",
] ]
resolver = "2"
[profile.release]
debug = true

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@ -1,62 +1,34 @@
<div align="center"> # nac3 compiler
![icon](https://git.m-labs.hk/M-Labs/nac3/raw/branch/master/nac3.svg)
</div>
# NAC3
NAC3 is a major, backward-incompatible rewrite of the compiler for the [ARTIQ](https://m-labs.hk/artiq) physics experiment control and data acquisition system. It features greatly improved compilation speeds, a much better type system, and more predictable and transparent operation.
NAC3 has a modular design and its applicability reaches beyond ARTIQ. The ``nac3core`` module does not contain anything specific to ARTIQ, and can be used in any project that requires compiling Python to machine code.
**WARNING: NAC3 is currently experimental software and several important features are not implemented yet.**
## Packaging
NAC3 is packaged using the [Nix](https://nixos.org) Flakes system. Install Nix 2.8+ and enable flakes by adding ``experimental-features = nix-command flakes`` to ``nix.conf`` (e.g. ``~/.config/nix/nix.conf``).
## Try NAC3
### Linux
After setting up Nix as above, use ``nix shell git+https://github.com/m-labs/artiq.git?ref=nac3`` to get a shell with the NAC3 version of ARTIQ. See the ``examples`` directory in ARTIQ (``nac3`` Git branch) for some samples of NAC3 kernel code.
### Windows
Install [MSYS2](https://www.msys2.org/), and open "MSYS2 CLANG64". Edit ``/etc/pacman.conf`` to add:
```
[artiq]
SigLevel = Optional TrustAll
Server = https://msys2.m-labs.hk/artiq-nac3
```
Then run the following commands:
```
pacman -Syu
pacman -S mingw-w64-clang-x86_64-artiq
```
## For developers
This repository contains: This repository contains:
- ``nac3ast``: Python abstract syntax tree definition (based on RustPython). - nac3core: Core compiler library, containing type-checking, static analysis (in
- ``nac3parser``: Python parser (based on RustPython). the future) and code generation.
- ``nac3core``: Core compiler library, containing type-checking and code generation. - nac3embedded: Integration with CPython runtime.
- ``nac3standalone``: Standalone compiler tool (core language only). - nac3standalone: Standalone compiler tool.
- ``nac3ld``: Minimalist RISC-V and ARM linker.
- ``nac3artiq``: Integration with ARTIQ and implementation of ARTIQ-specific extensions to the core language.
- ``runkernel``: Simple program that runs compiled ARTIQ kernels on the host and displays RTIO operations. Useful for testing without hardware.
Use ``nix develop`` in this repository to enter a development shell. The core compiler would know nothing about symbol resolution, host variables
If you are using a different shell than bash you can use e.g. ``nix develop --command fish``. etc. The nac3embedded/nac3standalone library would provide (implement) the
symbol resolver to the core compiler for resolving the type and value for
unknown symbols. The core compiler would only type check classes and functions
requested by the nac3embedded/nac3standalone lib (the API should allow the
caller to specify which methods should be compiled). After type checking, the
compiler would analyse the set of functions/classes that are used and perform
code generation.
Build NAC3 with ``cargo build --release``. See the demonstrations in ``nac3artiq`` and ``nac3standalone``. value could be integer values, boolean values, bytes (for memcpy), function ID
(full name + concrete type)
### Pre-Commit Hooks ## Current Plan
Type checking:
- [x] Basic interface for symbol resolver.
- [x] Track location information in context object (for diagnostics).
- [ ] Refactor old expression and statement type inference code. (anto)
- [ ] Error diagnostics utilities. (pca)
- [ ] Move tests to external files, write scripts for testing. (pca)
- [ ] Implement function type checking (instantiate bounded type parameters),
loop unrolling, type inference for lists with virtual objects. (pca)
You are strongly recommended to use the provided pre-commit hooks to automatically reformat files and check for non-optimal Rust practices using Clippy. Run `pre-commit install` to install the hook and `pre-commit` will automatically run `cargo fmt` and `cargo clippy` for you.
Several things to note:
- If `cargo fmt` or `cargo clippy` returns an error, the pre-commit hook will fail. You should fix all errors before trying to commit again.
- If `cargo fmt` reformats some files, the pre-commit hook will also fail. You should review the changes and, if satisfied, try to commit again.

27
flake.lock generated
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@ -1,27 +0,0 @@
{
"nodes": {
"nixpkgs": {
"locked": {
"lastModified": 1735834308,
"narHash": "sha256-dklw3AXr3OGO4/XT1Tu3Xz9n/we8GctZZ75ZWVqAVhk=",
"owner": "NixOS",
"repo": "nixpkgs",
"rev": "6df24922a1400241dae323af55f30e4318a6ca65",
"type": "github"
},
"original": {
"owner": "NixOS",
"ref": "nixos-unstable",
"repo": "nixpkgs",
"type": "github"
}
},
"root": {
"inputs": {
"nixpkgs": "nixpkgs"
}
}
},
"root": "root",
"version": 7
}

212
flake.nix
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@ -1,212 +0,0 @@
{
description = "The third-generation ARTIQ compiler";
inputs.nixpkgs.url = github:NixOS/nixpkgs/nixos-unstable;
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 {};
llvm-tools-irrt = pkgs.runCommandNoCC "llvm-tools-irrt" {}
''
mkdir -p $out/bin
ln -s ${pkgs.llvmPackages_14.clang-unwrapped}/bin/clang $out/bin/clang-irrt
ln -s ${pkgs.llvmPackages_14.llvm.out}/bin/llvm-as $out/bin/llvm-as-irrt
'';
demo-linalg-stub = pkgs.rustPlatform.buildRustPackage {
name = "demo-linalg-stub";
src = ./nac3standalone/demo/linalg;
cargoLock = {
lockFile = ./nac3standalone/demo/linalg/Cargo.lock;
};
doCheck = false;
};
demo-linalg-stub32 = pkgs32.rustPlatform.buildRustPackage {
name = "demo-linalg-stub32";
src = ./nac3standalone/demo/linalg;
cargoLock = {
lockFile = ./nac3standalone/demo/linalg/Cargo.lock;
};
doCheck = false;
};
nac3artiq = pkgs.python3Packages.toPythonModule (
pkgs.rustPlatform.buildRustPackage rec {
name = "nac3artiq";
outputs = [ "out" "runkernel" "standalone" ];
src = self;
cargoLock = {
lockFile = ./Cargo.lock;
};
passthru.cargoLock = cargoLock;
nativeBuildInputs = [ pkgs.python3 (pkgs.wrapClangMulti pkgs.llvmPackages_14.clang) llvm-tools-irrt pkgs.llvmPackages_14.llvm.out llvm-nac3 ];
buildInputs = [ pkgs.python3 llvm-nac3 ];
checkInputs = [ (pkgs.python3.withPackages(ps: [ ps.numpy ps.scipy ])) ];
checkPhase =
''
echo "Checking nac3standalone demos..."
pushd nac3standalone/demo
patchShebangs .
export DEMO_LINALG_STUB=${demo-linalg-stub}/lib/liblinalg.a
export DEMO_LINALG_STUB32=${demo-linalg-stub32}/lib/liblinalg.a
./check_demos.sh -i686
popd
echo "Running Cargo tests..."
cargoCheckHook
'';
installPhase =
''
PYTHON_SITEPACKAGES=$out/${pkgs.python3Packages.python.sitePackages}
mkdir -p $PYTHON_SITEPACKAGES
cp target/x86_64-unknown-linux-gnu/release/libnac3artiq.so $PYTHON_SITEPACKAGES/nac3artiq.so
mkdir -p $runkernel/bin
cp target/x86_64-unknown-linux-gnu/release/runkernel $runkernel/bin
mkdir -p $standalone/bin
cp target/x86_64-unknown-linux-gnu/release/nac3standalone $standalone/bin
'';
}
);
python3-mimalloc = pkgs.python3 // rec {
withMimalloc = pkgs.python3.buildEnv.override({ makeWrapperArgs = [ "--set LD_PRELOAD ${pkgs.mimalloc}/lib/libmimalloc.so" ]; });
withPackages = f: let packages = f pkgs.python3.pkgs; in withMimalloc.override { extraLibs = packages; };
};
# LLVM PGO support
llvm-nac3-instrumented = pkgs.callPackage ./nix/llvm {
stdenv = pkgs.llvmPackages_14.stdenv;
extraCmakeFlags = [ "-DLLVM_BUILD_INSTRUMENTED=IR" ];
};
nac3artiq-instrumented = pkgs.python3Packages.toPythonModule (
pkgs.rustPlatform.buildRustPackage {
name = "nac3artiq-instrumented";
src = self;
inherit (nac3artiq) cargoLock;
nativeBuildInputs = [ pkgs.python3 packages.x86_64-linux.llvm-tools-irrt llvm-nac3-instrumented ];
buildInputs = [ pkgs.python3 llvm-nac3-instrumented ];
cargoBuildFlags = [ "--package" "nac3artiq" "--features" "init-llvm-profile" ];
doCheck = false;
configurePhase =
''
export CARGO_TARGET_X86_64_UNKNOWN_LINUX_GNU_RUSTFLAGS="-C link-arg=-L${pkgs.llvmPackages_14.compiler-rt}/lib/linux -C link-arg=-lclang_rt.profile-x86_64"
'';
installPhase =
''
TARGET_DIR=$out/${pkgs.python3Packages.python.sitePackages}
mkdir -p $TARGET_DIR
cp target/x86_64-unknown-linux-gnu/release/libnac3artiq.so $TARGET_DIR/nac3artiq.so
'';
}
);
nac3artiq-profile = pkgs.stdenvNoCC.mkDerivation {
name = "nac3artiq-profile";
srcs = [
(pkgs.fetchFromGitHub {
owner = "m-labs";
repo = "sipyco";
rev = "094a6cd63ffa980ef63698920170e50dc9ba77fd";
sha256 = "sha256-PPnAyDedUQ7Og/Cby9x5OT9wMkNGTP8GS53V6N/dk4w=";
})
(pkgs.fetchFromGitHub {
owner = "m-labs";
repo = "artiq";
rev = "28c9de3e251daa89a8c9fd79d5ab64a3ec03bac6";
sha256 = "sha256-vAvpbHc5B+1wtG8zqN7j9dQE1ON+i22v+uqA+tw6Gak=";
})
];
buildInputs = [
(python3-mimalloc.withPackages(ps: [ ps.numpy ps.scipy ps.jsonschema ps.lmdb ps.platformdirs nac3artiq-instrumented ]))
pkgs.llvmPackages_14.llvm.out
];
phases = [ "buildPhase" "installPhase" ];
buildPhase =
''
srcs=($srcs)
sipyco=''${srcs[0]}
artiq=''${srcs[1]}
export PYTHONPATH=$sipyco:$artiq
python -m artiq.frontend.artiq_ddb_template $artiq/artiq/examples/nac3devices/nac3devices.json > device_db.py
cp $artiq/artiq/examples/nac3devices/nac3devices.py .
python -m artiq.frontend.artiq_compile nac3devices.py
'';
installPhase =
''
mkdir $out
llvm-profdata merge -o $out/llvm.profdata /build/llvm/build/profiles/*
'';
};
llvm-nac3-pgo = pkgs.callPackage ./nix/llvm {
stdenv = pkgs.llvmPackages_14.stdenv;
extraCmakeFlags = [ "-DLLVM_PROFDATA_FILE=${nac3artiq-profile}/llvm.profdata" ];
};
nac3artiq-pgo = pkgs.python3Packages.toPythonModule (
pkgs.rustPlatform.buildRustPackage {
name = "nac3artiq-pgo";
src = self;
inherit (nac3artiq) cargoLock;
nativeBuildInputs = [ pkgs.python3 packages.x86_64-linux.llvm-tools-irrt llvm-nac3-pgo ];
buildInputs = [ pkgs.python3 llvm-nac3-pgo ];
cargoBuildFlags = [ "--package" "nac3artiq" ];
cargoTestFlags = [ "--package" "nac3ast" "--package" "nac3parser" "--package" "nac3core" "--package" "nac3artiq" ];
installPhase =
''
TARGET_DIR=$out/${pkgs.python3Packages.python.sitePackages}
mkdir -p $TARGET_DIR
cp target/x86_64-unknown-linux-gnu/release/libnac3artiq.so $TARGET_DIR/nac3artiq.so
'';
}
);
};
packages.x86_64-w64-mingw32 = import ./nix/windows { inherit pkgs; };
devShells.x86_64-linux.default = pkgs.mkShell {
name = "nac3-dev-shell";
buildInputs = with pkgs; [
# build dependencies
packages.x86_64-linux.llvm-nac3
(pkgs.wrapClangMulti llvmPackages_14.clang) llvmPackages_14.llvm.out # for running nac3standalone demos
packages.x86_64-linux.llvm-tools-irrt
cargo
rustc
# runtime dependencies
lld_14 # for running kernels on the host
(packages.x86_64-linux.python3-mimalloc.withPackages(ps: [ ps.numpy ps.scipy ]))
# development tools
cargo-insta
clippy
pre-commit
rustfmt
];
shellHook =
''
export DEMO_LINALG_STUB=${packages.x86_64-linux.demo-linalg-stub}/lib/liblinalg.a
export DEMO_LINALG_STUB32=${packages.x86_64-linux.demo-linalg-stub32}/lib/liblinalg.a
'';
};
devShells.x86_64-linux.msys2 = pkgs.mkShell {
name = "nac3-dev-shell-msys2";
buildInputs = with pkgs; [
curl
pacman
fakeroot
packages.x86_64-w64-mingw32.wine-msys2
];
};
hydraJobs = {
inherit (packages.x86_64-linux) llvm-nac3 nac3artiq nac3artiq-pgo;
llvm-nac3-msys2 = packages.x86_64-w64-mingw32.llvm-nac3;
nac3artiq-msys2 = packages.x86_64-w64-mingw32.nac3artiq;
nac3artiq-msys2-pkg = packages.x86_64-w64-mingw32.nac3artiq-pkg;
};
};
nixConfig = {
extra-trusted-public-keys = "nixbld.m-labs.hk-1:5aSRVA5b320xbNvu30tqxVPXpld73bhtOeH6uAjRyHc=";
extra-substituters = "https://nixbld.m-labs.hk";
};
}

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[package]
name = "nac3artiq"
version = "0.1.0"
authors = ["M-Labs"]
edition = "2021"
[lib]
name = "nac3artiq"
crate-type = ["cdylib"]
[dependencies]
itertools = "0.13"
pyo3 = { version = "0.21", features = ["extension-module", "gil-refs"] }
parking_lot = "0.12"
tempfile = "3.13"
nac3core = { path = "../nac3core" }
nac3ld = { path = "../nac3ld" }
[features]
init-llvm-profile = []
no-escape-analysis = ["nac3core/no-escape-analysis"]

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from min_artiq import *
@nac3
class Demo:
core: KernelInvariant[Core]
led0: KernelInvariant[TTLOut]
led1: KernelInvariant[TTLOut]
def __init__(self):
self.core = Core()
self.led0 = TTLOut(self.core, 18)
self.led1 = TTLOut(self.core, 19)
@kernel
def run(self):
self.core.reset()
while True:
with parallel:
self.led0.pulse(100.*ms)
self.led1.pulse(100.*ms)
self.core.delay(100.*ms)
if __name__ == "__main__":
Demo().run()

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@ -1,16 +0,0 @@
# python demo.py
# artiq_run module.elf
device_db = {
"core": {
"type": "local",
"module": "artiq.coredevice.core",
"class": "Core",
"arguments": {
"host": "kc705",
"ref_period": 1e-9,
"ref_multiplier": 8,
"target": "rv32g"
}
},
}

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@ -1,39 +0,0 @@
class EmbeddingMap:
def __init__(self):
self.object_inverse_map = {}
self.object_map = {}
self.string_map = {}
self.string_reverse_map = {}
self.function_map = {}
self.attributes_writeback = []
def store_function(self, key, fun):
self.function_map[key] = fun
return key
def store_object(self, obj):
obj_id = id(obj)
if obj_id in self.object_inverse_map:
return self.object_inverse_map[obj_id]
key = len(self.object_map) + 1
self.object_map[key] = obj
self.object_inverse_map[obj_id] = key
return key
def store_str(self, s):
if s in self.string_reverse_map:
return self.string_reverse_map[s]
key = len(self.string_map)
self.string_map[key] = s
self.string_reverse_map[s] = key
return key
def retrieve_function(self, key):
return self.function_map[key]
def retrieve_object(self, key):
return self.object_map[key]
def retrieve_str(self, key):
return self.string_map[key]

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@ -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()

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@ -1,300 +0,0 @@
from inspect import getfullargspec
from functools import wraps
from types import SimpleNamespace
from numpy import int32, int64
from typing import Generic, TypeVar
from math import floor, ceil
import nac3artiq
from embedding_map import EmbeddingMap
__all__ = [
"Kernel", "KernelInvariant", "virtual", "ConstGeneric",
"Option", "Some", "none", "UnwrapNoneError",
"round64", "floor64", "ceil64",
"extern", "kernel", "portable", "nac3",
"rpc", "ms", "us", "ns",
"print_int32", "print_int64",
"Core", "TTLOut",
"parallel", "sequential"
]
T = TypeVar('T')
class Kernel(Generic[T]):
pass
class KernelInvariant(Generic[T]):
pass
# The virtual class must exist before nac3artiq.NAC3 is created.
class virtual(Generic[T]):
pass
class Option(Generic[T]):
_nac3_option: T
def __init__(self, v: T):
self._nac3_option = v
def is_none(self):
return self._nac3_option is None
def is_some(self):
return not self.is_none()
def unwrap(self):
if self.is_none():
raise UnwrapNoneError()
return self._nac3_option
def __repr__(self) -> str:
if self.is_none():
return "none"
else:
return "Some({})".format(repr(self._nac3_option))
def __str__(self) -> str:
if self.is_none():
return "none"
else:
return "Some({})".format(str(self._nac3_option))
def Some(v: T) -> Option[T]:
return Option(v)
none = Option(None)
class _ConstGenericMarker:
pass
def ConstGeneric(name, constraint):
return TypeVar(name, _ConstGenericMarker, constraint)
def round64(x):
return round(x)
def floor64(x):
return floor(x)
def ceil64(x):
return ceil(x)
import device_db
core_arguments = device_db.device_db["core"]["arguments"]
artiq_builtins = {
"none": none,
"virtual": virtual,
"_ConstGenericMarker": _ConstGenericMarker,
"Option": Option,
}
compiler = nac3artiq.NAC3(core_arguments["target"], artiq_builtins)
allow_registration = True
# Delay NAC3 analysis until all referenced variables are supposed to exist on the CPython side.
registered_functions = set()
registered_classes = set()
def register_function(fun):
assert allow_registration
registered_functions.add(fun)
def register_class(cls):
assert allow_registration
registered_classes.add(cls)
def extern(function):
"""Decorates a function declaration defined by the core device runtime."""
register_function(function)
return function
def rpc(arg=None, flags={}):
"""Decorates a function or method to be executed on the host interpreter."""
if arg is None:
def inner_decorator(function):
return rpc(function, flags)
return inner_decorator
register_function(arg)
return arg
def kernel(function_or_method):
"""Decorates a function or method to be executed on the core device."""
register_function(function_or_method)
argspec = getfullargspec(function_or_method)
if argspec.args and argspec.args[0] == "self":
@wraps(function_or_method)
def run_on_core(self, *args, **kwargs):
fake_method = SimpleNamespace(__self__=self, __name__=function_or_method.__name__)
self.core.run(fake_method, *args, **kwargs)
else:
@wraps(function_or_method)
def run_on_core(*args, **kwargs):
raise RuntimeError("Kernel functions need explicit core.run()")
return run_on_core
def portable(function):
"""Decorates a function or method to be executed on the same device (host/core device) as the caller."""
register_function(function)
return function
def nac3(cls):
"""
Decorates a class to be analyzed by NAC3.
All classes containing kernels or portable methods must use this decorator.
"""
register_class(cls)
return cls
ms = 1e-3
us = 1e-6
ns = 1e-9
@extern
def rtio_init():
raise NotImplementedError("syscall not simulated")
@extern
def rtio_get_counter() -> int64:
raise NotImplementedError("syscall not simulated")
@extern
def rtio_output(target: int32, data: int32):
raise NotImplementedError("syscall not simulated")
@extern
def rtio_input_timestamp(timeout_mu: int64, channel: int32) -> int64:
raise NotImplementedError("syscall not simulated")
@extern
def rtio_input_data(channel: int32) -> int32:
raise NotImplementedError("syscall not simulated")
# These is not part of ARTIQ and only available in runkernel. Defined here for convenience.
@extern
def print_int32(x: int32):
raise NotImplementedError("syscall not simulated")
@extern
def print_int64(x: int64):
raise NotImplementedError("syscall not simulated")
@nac3
class Core:
ref_period: KernelInvariant[float]
def __init__(self):
self.ref_period = core_arguments["ref_period"]
def run(self, method, *args, **kwargs):
global allow_registration
embedding = EmbeddingMap()
if allow_registration:
compiler.analyze(registered_functions, registered_classes, set())
allow_registration = False
if hasattr(method, "__self__"):
obj = method.__self__
name = method.__name__
else:
obj = method
name = ""
compiler.compile_method_to_file(obj, name, args, "module.elf", embedding)
@kernel
def reset(self):
rtio_init()
at_mu(rtio_get_counter() + int64(125000))
@kernel
def break_realtime(self):
min_now = rtio_get_counter() + int64(125000)
if now_mu() < min_now:
at_mu(min_now)
@portable
def seconds_to_mu(self, seconds: float) -> int64:
return int64(round(seconds/self.ref_period))
@portable
def mu_to_seconds(self, mu: int64) -> float:
return float(mu)*self.ref_period
@kernel
def delay(self, dt: float):
delay_mu(self.seconds_to_mu(dt))
@nac3
class TTLOut:
core: KernelInvariant[Core]
channel: KernelInvariant[int32]
target_o: KernelInvariant[int32]
def __init__(self, core: Core, channel: int32):
self.core = core
self.channel = channel
self.target_o = channel << 8
@kernel
def output(self):
pass
@kernel
def set_o(self, o: bool):
rtio_output(self.target_o, 1 if o else 0)
@kernel
def on(self):
self.set_o(True)
@kernel
def off(self):
self.set_o(False)
@kernel
def pulse_mu(self, duration: int64):
self.on()
delay_mu(duration)
self.off()
@kernel
def pulse(self, duration: float):
self.on()
self.core.delay(duration)
self.off()
@nac3
class KernelContextManager:
@kernel
def __enter__(self):
pass
@kernel
def __exit__(self):
pass
@nac3
class UnwrapNoneError(Exception):
"""raised when unwrapping a none value"""
artiq_builtin = True
parallel = KernelContextManager()
sequential = KernelContextManager()

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@ -1 +0,0 @@
../../target/release/libnac3artiq.so

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@ -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()

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@ -1,24 +0,0 @@
from min_artiq import *
from numpy import int32
@nac3
class Demo:
core: KernelInvariant[Core]
attr1: KernelInvariant[str]
attr2: KernelInvariant[int32]
def __init__(self):
self.core = Core()
self.attr2 = 32
self.attr1 = "SAMPLE"
@kernel
def run(self):
print_int32(self.attr2)
self.attr1
if __name__ == "__main__":
Demo().run()

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@ -1,40 +0,0 @@
from min_artiq import *
from numpy import int32
@nac3
class Demo:
attr1: KernelInvariant[int32] = 2
attr2: int32 = 4
attr3: Kernel[int32]
@kernel
def __init__(self):
self.attr3 = 8
@nac3
class NAC3Devices:
core: KernelInvariant[Core]
attr4: KernelInvariant[int32] = 16
def __init__(self):
self.core = Core()
@kernel
def run(self):
Demo.attr1 # Supported
# Demo.attr2 # Field not accessible on Kernel
# Demo.attr3 # Only attributes can be accessed in this way
# Demo.attr1 = 2 # Attributes are immutable
self.attr4 # Attributes can be accessed within class
obj = Demo()
obj.attr1 # Attributes can be accessed by class objects
NAC3Devices.attr4 # Attributes accessible for classes without __init__
if __name__ == "__main__":
NAC3Devices().run()

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@ -1,56 +0,0 @@
/* Force ld to make the ELF header as loadable. */
PHDRS
{
headers PT_LOAD FILEHDR PHDRS ;
text PT_LOAD ;
data PT_LOAD ;
dynamic PT_DYNAMIC ;
eh_frame PT_GNU_EH_FRAME ;
}
SECTIONS
{
/* Push back .text section enough so that ld.lld not complain */
. = SIZEOF_HEADERS;
.text :
{
*(.text .text.*)
} : text
.rodata :
{
*(.rodata .rodata.*)
}
.eh_frame :
{
KEEP(*(.eh_frame))
} : text
.eh_frame_hdr :
{
KEEP(*(.eh_frame_hdr))
} : text : eh_frame
.data :
{
*(.data)
} : data
.dynamic :
{
*(.dynamic)
} : data : dynamic
.bss (NOLOAD) : ALIGN(4)
{
__bss_start = .;
*(.sbss .sbss.* .bss .bss.*);
. = ALIGN(4);
_end = .;
}
. = ALIGN(0x1000);
_sstack_guard = .;
}

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@ -1,324 +0,0 @@
use itertools::Either;
use nac3core::{
codegen::CodeGenContext,
inkwell::{
values::{BasicValueEnum, CallSiteValue},
AddressSpace, AtomicOrdering,
},
};
/// Functions for manipulating the timeline.
pub trait TimeFns {
/// Emits LLVM IR for `now_mu`.
fn emit_now_mu<'ctx>(&self, ctx: &mut CodeGenContext<'ctx, '_>) -> BasicValueEnum<'ctx>;
/// Emits LLVM IR for `at_mu`.
fn emit_at_mu<'ctx>(&self, ctx: &mut CodeGenContext<'ctx, '_>, t: BasicValueEnum<'ctx>);
/// Emits LLVM IR for `delay_mu`.
fn emit_delay_mu<'ctx>(&self, ctx: &mut CodeGenContext<'ctx, '_>, dt: BasicValueEnum<'ctx>);
}
pub struct NowPinningTimeFns64 {}
// For FPGA design reasons, on VexRiscv with 64-bit data bus, the "now" CSR is split into two 32-bit
// values that are each padded to 64-bits.
impl TimeFns for NowPinningTimeFns64 {
fn emit_now_mu<'ctx>(&self, ctx: &mut CodeGenContext<'ctx, '_>) -> BasicValueEnum<'ctx> {
let i64_type = ctx.ctx.i64_type();
let i32_type = ctx.ctx.i32_type();
let now = ctx
.module
.get_global("now")
.unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
let now_hiptr = ctx
.builder
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.map(BasicValueEnum::into_pointer_value)
.unwrap();
let now_loptr = unsafe {
ctx.builder.build_gep(now_hiptr, &[i32_type.const_int(2, false)], "now.lo.addr")
}
.unwrap();
let now_hi = ctx
.builder
.build_load(now_hiptr, "now.hi")
.map(BasicValueEnum::into_int_value)
.unwrap();
let now_lo = ctx
.builder
.build_load(now_loptr, "now.lo")
.map(BasicValueEnum::into_int_value)
.unwrap();
let zext_hi = ctx.builder.build_int_z_extend(now_hi, i64_type, "").unwrap();
let shifted_hi =
ctx.builder.build_left_shift(zext_hi, i64_type.const_int(32, false), "").unwrap();
let zext_lo = ctx.builder.build_int_z_extend(now_lo, i64_type, "").unwrap();
ctx.builder.build_or(shifted_hi, zext_lo, "now_mu").map(Into::into).unwrap()
}
fn emit_at_mu<'ctx>(&self, ctx: &mut CodeGenContext<'ctx, '_>, t: BasicValueEnum<'ctx>) {
let i32_type = ctx.ctx.i32_type();
let i64_type = ctx.ctx.i64_type();
let i64_32 = i64_type.const_int(32, false);
let time = t.into_int_value();
let time_hi = ctx
.builder
.build_int_truncate(
ctx.builder.build_right_shift(time, i64_32, false, "time.hi").unwrap(),
i32_type,
"",
)
.unwrap();
let time_lo = ctx.builder.build_int_truncate(time, i32_type, "time.lo").unwrap();
let now = ctx
.module
.get_global("now")
.unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
let now_hiptr = ctx
.builder
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.map(BasicValueEnum::into_pointer_value)
.unwrap();
let now_loptr = unsafe {
ctx.builder.build_gep(now_hiptr, &[i32_type.const_int(2, false)], "now.lo.addr")
}
.unwrap();
ctx.builder
.build_store(now_hiptr, time_hi)
.unwrap()
.set_atomic_ordering(AtomicOrdering::SequentiallyConsistent)
.unwrap();
ctx.builder
.build_store(now_loptr, time_lo)
.unwrap()
.set_atomic_ordering(AtomicOrdering::SequentiallyConsistent)
.unwrap();
}
fn emit_delay_mu<'ctx>(&self, ctx: &mut CodeGenContext<'ctx, '_>, dt: BasicValueEnum<'ctx>) {
let i64_type = ctx.ctx.i64_type();
let i32_type = ctx.ctx.i32_type();
let now = ctx
.module
.get_global("now")
.unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
let now_hiptr = ctx
.builder
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.map(BasicValueEnum::into_pointer_value)
.unwrap();
let now_loptr = unsafe {
ctx.builder.build_gep(now_hiptr, &[i32_type.const_int(2, false)], "now.lo.addr")
}
.unwrap();
let now_hi = ctx
.builder
.build_load(now_hiptr, "now.hi")
.map(BasicValueEnum::into_int_value)
.unwrap();
let now_lo = ctx
.builder
.build_load(now_loptr, "now.lo")
.map(BasicValueEnum::into_int_value)
.unwrap();
let dt = dt.into_int_value();
let zext_hi = ctx.builder.build_int_z_extend(now_hi, i64_type, "").unwrap();
let shifted_hi =
ctx.builder.build_left_shift(zext_hi, i64_type.const_int(32, false), "").unwrap();
let zext_lo = ctx.builder.build_int_z_extend(now_lo, i64_type, "").unwrap();
let now_val = ctx.builder.build_or(shifted_hi, zext_lo, "now").unwrap();
let time = ctx.builder.build_int_add(now_val, dt, "time").unwrap();
let time_hi = ctx
.builder
.build_int_truncate(
ctx.builder
.build_right_shift(time, i64_type.const_int(32, false), false, "")
.unwrap(),
i32_type,
"time.hi",
)
.unwrap();
let time_lo = ctx.builder.build_int_truncate(time, i32_type, "time.lo").unwrap();
ctx.builder
.build_store(now_hiptr, time_hi)
.unwrap()
.set_atomic_ordering(AtomicOrdering::SequentiallyConsistent)
.unwrap();
ctx.builder
.build_store(now_loptr, time_lo)
.unwrap()
.set_atomic_ordering(AtomicOrdering::SequentiallyConsistent)
.unwrap();
}
}
pub static NOW_PINNING_TIME_FNS_64: NowPinningTimeFns64 = NowPinningTimeFns64 {};
pub struct NowPinningTimeFns {}
impl TimeFns for NowPinningTimeFns {
fn emit_now_mu<'ctx>(&self, ctx: &mut CodeGenContext<'ctx, '_>) -> BasicValueEnum<'ctx> {
let i64_type = ctx.ctx.i64_type();
let now = ctx
.module
.get_global("now")
.unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
let now_raw = ctx
.builder
.build_load(now.as_pointer_value(), "now")
.map(BasicValueEnum::into_int_value)
.unwrap();
let i64_32 = i64_type.const_int(32, false);
let now_lo = ctx.builder.build_left_shift(now_raw, i64_32, "now.lo").unwrap();
let now_hi = ctx.builder.build_right_shift(now_raw, i64_32, false, "now.hi").unwrap();
ctx.builder.build_or(now_lo, now_hi, "now_mu").map(Into::into).unwrap()
}
fn emit_at_mu<'ctx>(&self, ctx: &mut CodeGenContext<'ctx, '_>, t: BasicValueEnum<'ctx>) {
let i32_type = ctx.ctx.i32_type();
let i64_type = ctx.ctx.i64_type();
let i64_32 = i64_type.const_int(32, false);
let time = t.into_int_value();
let time_hi = ctx
.builder
.build_int_truncate(
ctx.builder.build_right_shift(time, i64_32, false, "").unwrap(),
i32_type,
"time.hi",
)
.unwrap();
let time_lo = ctx.builder.build_int_truncate(time, i32_type, "now_trunc").unwrap();
let now = ctx
.module
.get_global("now")
.unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
let now_hiptr = ctx
.builder
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.map(BasicValueEnum::into_pointer_value)
.unwrap();
let now_loptr = unsafe {
ctx.builder.build_gep(now_hiptr, &[i32_type.const_int(1, false)], "now.lo.addr")
}
.unwrap();
ctx.builder
.build_store(now_hiptr, time_hi)
.unwrap()
.set_atomic_ordering(AtomicOrdering::SequentiallyConsistent)
.unwrap();
ctx.builder
.build_store(now_loptr, time_lo)
.unwrap()
.set_atomic_ordering(AtomicOrdering::SequentiallyConsistent)
.unwrap();
}
fn emit_delay_mu<'ctx>(&self, ctx: &mut CodeGenContext<'ctx, '_>, dt: BasicValueEnum<'ctx>) {
let i32_type = ctx.ctx.i32_type();
let i64_type = ctx.ctx.i64_type();
let i64_32 = i64_type.const_int(32, false);
let now = ctx
.module
.get_global("now")
.unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
let now_raw = ctx
.builder
.build_load(now.as_pointer_value(), "")
.map(BasicValueEnum::into_int_value)
.unwrap();
let dt = dt.into_int_value();
let now_lo = ctx.builder.build_left_shift(now_raw, i64_32, "now.lo").unwrap();
let now_hi = ctx.builder.build_right_shift(now_raw, i64_32, false, "now.hi").unwrap();
let now_val = ctx.builder.build_or(now_lo, now_hi, "now_val").unwrap();
let time = ctx.builder.build_int_add(now_val, dt, "time").unwrap();
let time_hi = ctx
.builder
.build_int_truncate(
ctx.builder.build_right_shift(time, i64_32, false, "time.hi").unwrap(),
i32_type,
"now_trunc",
)
.unwrap();
let time_lo = ctx.builder.build_int_truncate(time, i32_type, "time.lo").unwrap();
let now_hiptr = ctx
.builder
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
.map(BasicValueEnum::into_pointer_value)
.unwrap();
let now_loptr = unsafe {
ctx.builder.build_gep(now_hiptr, &[i32_type.const_int(1, false)], "now.lo.addr")
}
.unwrap();
ctx.builder
.build_store(now_hiptr, time_hi)
.unwrap()
.set_atomic_ordering(AtomicOrdering::SequentiallyConsistent)
.unwrap();
ctx.builder
.build_store(now_loptr, time_lo)
.unwrap()
.set_atomic_ordering(AtomicOrdering::SequentiallyConsistent)
.unwrap();
}
}
pub static NOW_PINNING_TIME_FNS: NowPinningTimeFns = NowPinningTimeFns {};
pub struct ExternTimeFns {}
impl TimeFns for ExternTimeFns {
fn emit_now_mu<'ctx>(&self, ctx: &mut CodeGenContext<'ctx, '_>) -> BasicValueEnum<'ctx> {
let now_mu = ctx.module.get_function("now_mu").unwrap_or_else(|| {
ctx.module.add_function("now_mu", ctx.ctx.i64_type().fn_type(&[], false), None)
});
ctx.builder
.build_call(now_mu, &[], "now_mu")
.map(CallSiteValue::try_as_basic_value)
.map(Either::unwrap_left)
.unwrap()
}
fn emit_at_mu<'ctx>(&self, ctx: &mut CodeGenContext<'ctx, '_>, t: BasicValueEnum<'ctx>) {
let at_mu = ctx.module.get_function("at_mu").unwrap_or_else(|| {
ctx.module.add_function(
"at_mu",
ctx.ctx.void_type().fn_type(&[ctx.ctx.i64_type().into()], false),
None,
)
});
ctx.builder.build_call(at_mu, &[t.into()], "at_mu").unwrap();
}
fn emit_delay_mu<'ctx>(&self, ctx: &mut CodeGenContext<'ctx, '_>, dt: BasicValueEnum<'ctx>) {
let delay_mu = ctx.module.get_function("delay_mu").unwrap_or_else(|| {
ctx.module.add_function(
"delay_mu",
ctx.ctx.void_type().fn_type(&[ctx.ctx.i64_type().into()], false),
None,
)
});
ctx.builder.build_call(delay_mu, &[dt.into()], "delay_mu").unwrap();
}
}
pub static EXTERN_TIME_FNS: ExternTimeFns = ExternTimeFns {};

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@ -1,15 +0,0 @@
[package]
name = "nac3ast"
version = "0.1.0"
authors = ["RustPython Team", "M-Labs"]
edition = "2021"
[features]
default = ["constant-optimization", "fold"]
constant-optimization = ["fold"]
fold = []
[dependencies]
parking_lot = "0.12"
string-interner = "0.17"
fxhash = "0.2"

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@ -1,127 +0,0 @@
-- ASDL's 4 builtin types are:
-- identifier, int, string, constant
module Python
{
mod = Module(stmt* body, type_ignore* type_ignores)
| Interactive(stmt* body)
| Expression(expr body)
| FunctionType(expr* argtypes, expr returns)
stmt = FunctionDef(identifier name, arguments args,
stmt* body, expr* decorator_list, expr? returns,
string? type_comment, identifier* config_comment)
| AsyncFunctionDef(identifier name, arguments args,
stmt* body, expr* decorator_list, expr? returns,
string? type_comment, identifier* config_comment)
| ClassDef(identifier name,
expr* bases,
keyword* keywords,
stmt* body,
expr* decorator_list, identifier* config_comment)
| Return(expr? value, identifier* config_comment)
| Delete(expr* targets, identifier* config_comment)
| Assign(expr* targets, expr value, string? type_comment, identifier* config_comment)
| AugAssign(expr target, operator op, expr value, identifier* config_comment)
-- 'simple' indicates that we annotate simple name without parens
| AnnAssign(expr target, expr annotation, expr? value, bool simple, identifier* config_comment)
-- use 'orelse' because else is a keyword in target languages
| For(expr target, expr iter, stmt* body, stmt* orelse, string? type_comment, identifier* config_comment)
| AsyncFor(expr target, expr iter, stmt* body, stmt* orelse, string? type_comment, identifier* config_comment)
| While(expr test, stmt* body, stmt* orelse, identifier* config_comment)
| If(expr test, stmt* body, stmt* orelse, identifier* config_comment)
| With(withitem* items, stmt* body, string? type_comment, identifier* config_comment)
| AsyncWith(withitem* items, stmt* body, string? type_comment, identifier* config_comment)
| Raise(expr? exc, expr? cause, identifier* config_comment)
| Try(stmt* body, excepthandler* handlers, stmt* orelse, stmt* finalbody, identifier* config_comment)
| Assert(expr test, expr? msg, identifier* config_comment)
| Import(alias* names, identifier* config_comment)
| ImportFrom(identifier? module, alias* names, int level, identifier* config_comment)
| Global(identifier* names, identifier* config_comment)
| Nonlocal(identifier* names, identifier* config_comment)
| Expr(expr value, identifier* config_comment)
| Pass(identifier* config_comment)
| Break(identifier* config_comment)
| Continue(identifier* config_comment)
-- col_offset is the byte offset in the utf8 string the parser uses
attributes (int lineno, int col_offset, int? end_lineno, int? end_col_offset)
-- BoolOp() can use left & right?
expr = BoolOp(boolop op, expr* values)
| NamedExpr(expr target, expr value)
| BinOp(expr left, operator op, expr right)
| UnaryOp(unaryop op, expr operand)
| Lambda(arguments args, expr body)
| IfExp(expr test, expr body, expr orelse)
| Dict(expr?* keys, expr* values)
| Set(expr* elts)
| ListComp(expr elt, comprehension* generators)
| SetComp(expr elt, comprehension* generators)
| DictComp(expr key, expr value, comprehension* generators)
| GeneratorExp(expr elt, comprehension* generators)
-- the grammar constrains where yield expressions can occur
| Await(expr value)
| Yield(expr? value)
| YieldFrom(expr value)
-- need sequences for compare to distinguish between
-- x < 4 < 3 and (x < 4) < 3
| Compare(expr left, cmpop* ops, expr* comparators)
| Call(expr func, expr* args, keyword* keywords)
| FormattedValue(expr value, conversion_flag? conversion, expr? format_spec)
| JoinedStr(expr* values)
| Constant(constant value, string? kind)
-- the following expression can appear in assignment context
| Attribute(expr value, identifier attr, expr_context ctx)
| Subscript(expr value, expr slice, expr_context ctx)
| Starred(expr value, expr_context ctx)
| Name(identifier id, expr_context ctx)
| List(expr* elts, expr_context ctx)
| Tuple(expr* elts, expr_context ctx)
-- can appear only in Subscript
| Slice(expr? lower, expr? upper, expr? step)
-- col_offset is the byte offset in the utf8 string the parser uses
attributes (int lineno, int col_offset, int? end_lineno, int? end_col_offset)
expr_context = Load | Store | Del
boolop = And | Or
operator = Add | Sub | Mult | MatMult | Div | Mod | Pow | LShift
| RShift | BitOr | BitXor | BitAnd | FloorDiv
unaryop = Invert | Not | UAdd | USub
cmpop = Eq | NotEq | Lt | LtE | Gt | GtE | Is | IsNot | In | NotIn
comprehension = (expr target, expr iter, expr* ifs, bool is_async)
excepthandler = ExceptHandler(expr? type, identifier? name, stmt* body)
attributes (int lineno, int col_offset, int? end_lineno, int? end_col_offset)
arguments = (arg* posonlyargs, arg* args, arg? vararg, arg* kwonlyargs,
expr?* kw_defaults, arg? kwarg, expr* defaults)
arg = (identifier arg, expr? annotation, string? type_comment)
attributes (int lineno, int col_offset, int? end_lineno, int? end_col_offset)
-- keyword arguments supplied to call (NULL identifier for **kwargs)
keyword = (identifier? arg, expr value)
attributes (int lineno, int col_offset, int? end_lineno, int? end_col_offset)
-- import name with optional 'as' alias.
alias = (identifier name, identifier? asname)
withitem = (expr context_expr, expr? optional_vars)
type_ignore = TypeIgnore(int lineno, string tag)
}

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@ -1,385 +0,0 @@
#-------------------------------------------------------------------------------
# Parser for ASDL [1] definition files. Reads in an ASDL description and parses
# it into an AST that describes it.
#
# The EBNF we're parsing here: Figure 1 of the paper [1]. Extended to support
# modules and attributes after a product. Words starting with Capital letters
# are terminals. Literal tokens are in "double quotes". Others are
# non-terminals. Id is either TokenId or ConstructorId.
#
# module ::= "module" Id "{" [definitions] "}"
# definitions ::= { TypeId "=" type }
# type ::= product | sum
# product ::= fields ["attributes" fields]
# fields ::= "(" { field, "," } field ")"
# field ::= TypeId ["?" | "*"] [Id]
# sum ::= constructor { "|" constructor } ["attributes" fields]
# constructor ::= ConstructorId [fields]
#
# [1] "The Zephyr Abstract Syntax Description Language" by Wang, et. al. See
# http://asdl.sourceforge.net/
#-------------------------------------------------------------------------------
from collections import namedtuple
import re
__all__ = [
'builtin_types', 'parse', 'AST', 'Module', 'Type', 'Constructor',
'Field', 'Sum', 'Product', 'VisitorBase', 'Check', 'check']
# The following classes define nodes into which the ASDL description is parsed.
# Note: this is a "meta-AST". ASDL files (such as Python.asdl) describe the AST
# structure used by a programming language. But ASDL files themselves need to be
# parsed. This module parses ASDL files and uses a simple AST to represent them.
# See the EBNF at the top of the file to understand the logical connection
# between the various node types.
builtin_types = {'identifier', 'string', 'int', 'constant', 'bool', 'conversion_flag'}
class AST:
def __repr__(self):
raise NotImplementedError
class Module(AST):
def __init__(self, name, dfns):
self.name = name
self.dfns = dfns
self.types = {type.name: type.value for type in dfns}
def __repr__(self):
return 'Module({0.name}, {0.dfns})'.format(self)
class Type(AST):
def __init__(self, name, value):
self.name = name
self.value = value
def __repr__(self):
return 'Type({0.name}, {0.value})'.format(self)
class Constructor(AST):
def __init__(self, name, fields=None):
self.name = name
self.fields = fields or []
def __repr__(self):
return 'Constructor({0.name}, {0.fields})'.format(self)
class Field(AST):
def __init__(self, type, name=None, seq=False, opt=False):
self.type = type
self.name = name
self.seq = seq
self.opt = opt
def __str__(self):
if self.seq:
extra = "*"
elif self.opt:
extra = "?"
else:
extra = ""
return "{}{} {}".format(self.type, extra, self.name)
def __repr__(self):
if self.seq:
extra = ", seq=True"
elif self.opt:
extra = ", opt=True"
else:
extra = ""
if self.name is None:
return 'Field({0.type}{1})'.format(self, extra)
else:
return 'Field({0.type}, {0.name}{1})'.format(self, extra)
class Sum(AST):
def __init__(self, types, attributes=None):
self.types = types
self.attributes = attributes or []
def __repr__(self):
if self.attributes:
return 'Sum({0.types}, {0.attributes})'.format(self)
else:
return 'Sum({0.types})'.format(self)
class Product(AST):
def __init__(self, fields, attributes=None):
self.fields = fields
self.attributes = attributes or []
def __repr__(self):
if self.attributes:
return 'Product({0.fields}, {0.attributes})'.format(self)
else:
return 'Product({0.fields})'.format(self)
# A generic visitor for the meta-AST that describes ASDL. This can be used by
# emitters. Note that this visitor does not provide a generic visit method, so a
# subclass needs to define visit methods from visitModule to as deep as the
# interesting node.
# We also define a Check visitor that makes sure the parsed ASDL is well-formed.
class VisitorBase(object):
"""Generic tree visitor for ASTs."""
def __init__(self):
self.cache = {}
def visit(self, obj, *args):
klass = obj.__class__
meth = self.cache.get(klass)
if meth is None:
methname = "visit" + klass.__name__
meth = getattr(self, methname, None)
self.cache[klass] = meth
if meth:
try:
meth(obj, *args)
except Exception as e:
print("Error visiting %r: %s" % (obj, e))
raise
class Check(VisitorBase):
"""A visitor that checks a parsed ASDL tree for correctness.
Errors are printed and accumulated.
"""
def __init__(self):
super(Check, self).__init__()
self.cons = {}
self.errors = 0
self.types = {}
def visitModule(self, mod):
for dfn in mod.dfns:
self.visit(dfn)
def visitType(self, type):
self.visit(type.value, str(type.name))
def visitSum(self, sum, name):
for t in sum.types:
self.visit(t, name)
def visitConstructor(self, cons, name):
key = str(cons.name)
conflict = self.cons.get(key)
if conflict is None:
self.cons[key] = name
else:
print('Redefinition of constructor {}'.format(key))
print('Defined in {} and {}'.format(conflict, name))
self.errors += 1
for f in cons.fields:
self.visit(f, key)
def visitField(self, field, name):
key = str(field.type)
l = self.types.setdefault(key, [])
l.append(name)
def visitProduct(self, prod, name):
for f in prod.fields:
self.visit(f, name)
def check(mod):
"""Check the parsed ASDL tree for correctness.
Return True if success. For failure, the errors are printed out and False
is returned.
"""
v = Check()
v.visit(mod)
for t in v.types:
if t not in mod.types and not t in builtin_types:
v.errors += 1
uses = ", ".join(v.types[t])
print('Undefined type {}, used in {}'.format(t, uses))
return not v.errors
# The ASDL parser itself comes next. The only interesting external interface
# here is the top-level parse function.
def parse(filename):
"""Parse ASDL from the given file and return a Module node describing it."""
with open(filename) as f:
parser = ASDLParser()
return parser.parse(f.read())
# Types for describing tokens in an ASDL specification.
class TokenKind:
"""TokenKind is provides a scope for enumerated token kinds."""
(ConstructorId, TypeId, Equals, Comma, Question, Pipe, Asterisk,
LParen, RParen, LBrace, RBrace) = range(11)
operator_table = {
'=': Equals, ',': Comma, '?': Question, '|': Pipe, '(': LParen,
')': RParen, '*': Asterisk, '{': LBrace, '}': RBrace}
Token = namedtuple('Token', 'kind value lineno')
class ASDLSyntaxError(Exception):
def __init__(self, msg, lineno=None):
self.msg = msg
self.lineno = lineno or '<unknown>'
def __str__(self):
return 'Syntax error on line {0.lineno}: {0.msg}'.format(self)
def tokenize_asdl(buf):
"""Tokenize the given buffer. Yield Token objects."""
for lineno, line in enumerate(buf.splitlines(), 1):
for m in re.finditer(r'\s*(\w+|--.*|.)', line.strip()):
c = m.group(1)
if c[0].isalpha():
# Some kind of identifier
if c[0].isupper():
yield Token(TokenKind.ConstructorId, c, lineno)
else:
yield Token(TokenKind.TypeId, c, lineno)
elif c[:2] == '--':
# Comment
break
else:
# Operators
try:
op_kind = TokenKind.operator_table[c]
except KeyError:
raise ASDLSyntaxError('Invalid operator %s' % c, lineno)
yield Token(op_kind, c, lineno)
class ASDLParser:
"""Parser for ASDL files.
Create, then call the parse method on a buffer containing ASDL.
This is a simple recursive descent parser that uses tokenize_asdl for the
lexing.
"""
def __init__(self):
self._tokenizer = None
self.cur_token = None
def parse(self, buf):
"""Parse the ASDL in the buffer and return an AST with a Module root.
"""
self._tokenizer = tokenize_asdl(buf)
self._advance()
return self._parse_module()
def _parse_module(self):
if self._at_keyword('module'):
self._advance()
else:
raise ASDLSyntaxError(
'Expected "module" (found {})'.format(self.cur_token.value),
self.cur_token.lineno)
name = self._match(self._id_kinds)
self._match(TokenKind.LBrace)
defs = self._parse_definitions()
self._match(TokenKind.RBrace)
return Module(name, defs)
def _parse_definitions(self):
defs = []
while self.cur_token.kind == TokenKind.TypeId:
typename = self._advance()
self._match(TokenKind.Equals)
type = self._parse_type()
defs.append(Type(typename, type))
return defs
def _parse_type(self):
if self.cur_token.kind == TokenKind.LParen:
# If we see a (, it's a product
return self._parse_product()
else:
# Otherwise it's a sum. Look for ConstructorId
sumlist = [Constructor(self._match(TokenKind.ConstructorId),
self._parse_optional_fields())]
while self.cur_token.kind == TokenKind.Pipe:
# More constructors
self._advance()
sumlist.append(Constructor(
self._match(TokenKind.ConstructorId),
self._parse_optional_fields()))
return Sum(sumlist, self._parse_optional_attributes())
def _parse_product(self):
return Product(self._parse_fields(), self._parse_optional_attributes())
def _parse_fields(self):
fields = []
self._match(TokenKind.LParen)
while self.cur_token.kind == TokenKind.TypeId:
typename = self._advance()
is_seq, is_opt = self._parse_optional_field_quantifier()
id = (self._advance() if self.cur_token.kind in self._id_kinds
else None)
fields.append(Field(typename, id, seq=is_seq, opt=is_opt))
if self.cur_token.kind == TokenKind.RParen:
break
elif self.cur_token.kind == TokenKind.Comma:
self._advance()
self._match(TokenKind.RParen)
return fields
def _parse_optional_fields(self):
if self.cur_token.kind == TokenKind.LParen:
return self._parse_fields()
else:
return None
def _parse_optional_attributes(self):
if self._at_keyword('attributes'):
self._advance()
return self._parse_fields()
else:
return None
def _parse_optional_field_quantifier(self):
is_seq, is_opt = False, False
if self.cur_token.kind == TokenKind.Question:
is_opt = True
self._advance()
if self.cur_token.kind == TokenKind.Asterisk:
is_seq = True
self._advance()
return is_seq, is_opt
def _advance(self):
""" Return the value of the current token and read the next one into
self.cur_token.
"""
cur_val = None if self.cur_token is None else self.cur_token.value
try:
self.cur_token = next(self._tokenizer)
except StopIteration:
self.cur_token = None
return cur_val
_id_kinds = (TokenKind.ConstructorId, TokenKind.TypeId)
def _match(self, kind):
"""The 'match' primitive of RD parsers.
* Verifies that the current token is of the given kind (kind can
be a tuple, in which the kind must match one of its members).
* Returns the value of the current token
* Reads in the next token
"""
if (isinstance(kind, tuple) and self.cur_token.kind in kind or
self.cur_token.kind == kind
):
value = self.cur_token.value
self._advance()
return value
else:
raise ASDLSyntaxError(
'Unmatched {} (found {})'.format(kind, self.cur_token.kind),
self.cur_token.lineno)
def _at_keyword(self, keyword):
return (self.cur_token.kind == TokenKind.TypeId and
self.cur_token.value == keyword)

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@ -1,609 +0,0 @@
#! /usr/bin/env python
"""Generate Rust code from an ASDL description."""
import os
import sys
import textwrap
import json
from argparse import ArgumentParser
from pathlib import Path
import asdl
TABSIZE = 4
AUTOGEN_MESSAGE = "// File automatically generated by {}.\n\n"
builtin_type_mapping = {
'identifier': 'Ident',
'string': 'String',
'int': 'usize',
'constant': 'Constant',
'bool': 'bool',
'conversion_flag': 'ConversionFlag',
}
assert builtin_type_mapping.keys() == asdl.builtin_types
def get_rust_type(name):
"""Return a string for the C name of the type.
This function special cases the default types provided by asdl.
"""
if name in asdl.builtin_types:
return builtin_type_mapping[name]
else:
return "".join(part.capitalize() for part in name.split("_"))
def is_simple(sum):
"""Return True if a sum is a simple.
A sum is simple if its types have no fields, e.g.
unaryop = Invert | Not | UAdd | USub
"""
for t in sum.types:
if t.fields:
return False
return True
def asdl_of(name, obj):
if isinstance(obj, asdl.Product) or isinstance(obj, asdl.Constructor):
fields = ", ".join(map(str, obj.fields))
if fields:
fields = "({})".format(fields)
return "{}{}".format(name, fields)
else:
if is_simple(obj):
types = " | ".join(type.name for type in obj.types)
else:
sep = "\n{}| ".format(" " * (len(name) + 1))
types = sep.join(
asdl_of(type.name, type) for type in obj.types
)
return "{} = {}".format(name, types)
class EmitVisitor(asdl.VisitorBase):
"""Visit that emits lines"""
def __init__(self, file):
self.file = file
self.identifiers = set()
super(EmitVisitor, self).__init__()
def emit_identifier(self, name):
name = str(name)
if name in self.identifiers:
return
self.emit("_Py_IDENTIFIER(%s);" % name, 0)
self.identifiers.add(name)
def emit(self, line, depth):
if line:
line = (" " * TABSIZE * depth) + line
self.file.write(line + "\n")
class TypeInfo:
def __init__(self, name):
self.name = name
self.has_userdata = None
self.children = set()
self.boxed = False
def __repr__(self):
return f"<TypeInfo: {self.name}>"
def determine_userdata(self, typeinfo, stack):
if self.name in stack:
return None
stack.add(self.name)
for child, child_seq in self.children:
if child in asdl.builtin_types:
continue
childinfo = typeinfo[child]
child_has_userdata = childinfo.determine_userdata(typeinfo, stack)
if self.has_userdata is None and child_has_userdata is True:
self.has_userdata = True
stack.remove(self.name)
return self.has_userdata
class FindUserdataTypesVisitor(asdl.VisitorBase):
def __init__(self, typeinfo):
self.typeinfo = typeinfo
super().__init__()
def visitModule(self, mod):
for dfn in mod.dfns:
self.visit(dfn)
stack = set()
for info in self.typeinfo.values():
info.determine_userdata(self.typeinfo, stack)
def visitType(self, type):
self.typeinfo[type.name] = TypeInfo(type.name)
self.visit(type.value, type.name)
def visitSum(self, sum, name):
info = self.typeinfo[name]
if is_simple(sum):
info.has_userdata = False
else:
if len(sum.types) > 1:
info.boxed = True
if sum.attributes:
# attributes means Located, which has the `custom: U` field
info.has_userdata = True
for variant in sum.types:
self.add_children(name, variant.fields)
def visitProduct(self, product, name):
info = self.typeinfo[name]
if product.attributes:
# attributes means Located, which has the `custom: U` field
info.has_userdata = True
if len(product.fields) > 2:
info.boxed = True
self.add_children(name, product.fields)
def add_children(self, name, fields):
self.typeinfo[name].children.update((field.type, field.seq) for field in fields)
def rust_field(field_name):
if field_name == 'type':
return 'type_'
else:
return field_name
class TypeInfoEmitVisitor(EmitVisitor):
def __init__(self, file, typeinfo):
self.typeinfo = typeinfo
super().__init__(file)
def has_userdata(self, typ):
return self.typeinfo[typ].has_userdata
def get_generics(self, typ, *generics):
if self.has_userdata(typ):
return [f"<{g}>" for g in generics]
else:
return ["" for g in generics]
class StructVisitor(TypeInfoEmitVisitor):
"""Visitor to generate typedefs for AST."""
def visitModule(self, mod):
for dfn in mod.dfns:
self.visit(dfn)
def visitType(self, type, depth=0):
self.visit(type.value, type.name, depth)
def visitSum(self, sum, name, depth):
if is_simple(sum):
self.simple_sum(sum, name, depth)
else:
self.sum_with_constructors(sum, name, depth)
def emit_attrs(self, depth):
self.emit("#[derive(Clone, Debug, PartialEq)]", depth)
def simple_sum(self, sum, name, depth):
rustname = get_rust_type(name)
self.emit_attrs(depth)
self.emit(f"pub enum {rustname} {{", depth)
for variant in sum.types:
self.emit(f"{variant.name},", depth + 1)
self.emit("}", depth)
self.emit("", depth)
def sum_with_constructors(self, sum, name, depth):
typeinfo = self.typeinfo[name]
generics, generics_applied = self.get_generics(name, "U = ()", "U")
enumname = rustname = get_rust_type(name)
# all the attributes right now are for location, so if it has attrs we
# can just wrap it in Located<>
if sum.attributes:
enumname = rustname + "Kind"
self.emit_attrs(depth)
self.emit(f"pub enum {enumname}{generics} {{", depth)
for t in sum.types:
self.visit(t, typeinfo, depth + 1)
self.emit("}", depth)
if sum.attributes:
self.emit(f"pub type {rustname}<U = ()> = Located<{enumname}{generics_applied}, U>;", depth)
self.emit("", depth)
def visitConstructor(self, cons, parent, depth):
if cons.fields:
self.emit(f"{cons.name} {{", depth)
for f in cons.fields:
self.visit(f, parent, "", depth + 1)
self.emit("},", depth)
else:
self.emit(f"{cons.name},", depth)
def visitField(self, field, parent, vis, depth):
typ = get_rust_type(field.type)
fieldtype = self.typeinfo.get(field.type)
if fieldtype and fieldtype.has_userdata:
typ = f"{typ}<U>"
# don't box if we're doing Vec<T>, but do box if we're doing Vec<Option<Box<T>>>
if fieldtype and fieldtype.boxed and (not field.seq or field.opt):
typ = f"Box<{typ}>"
if field.opt:
typ = f"Option<{typ}>"
if field.seq:
typ = f"Vec<{typ}>"
name = rust_field(field.name)
self.emit(f"{vis}{name}: {typ},", depth)
def visitProduct(self, product, name, depth):
typeinfo = self.typeinfo[name]
generics, generics_applied = self.get_generics(name, "U = ()", "U")
dataname = rustname = get_rust_type(name)
if product.attributes:
dataname = rustname + "Data"
self.emit_attrs(depth)
self.emit(f"pub struct {dataname}{generics} {{", depth)
for f in product.fields:
self.visit(f, typeinfo, "pub ", depth + 1)
self.emit("}", depth)
if product.attributes:
# attributes should just be location info
self.emit(f"pub type {rustname}<U = ()> = Located<{dataname}{generics_applied}, U>;", depth);
self.emit("", depth)
class FoldTraitDefVisitor(TypeInfoEmitVisitor):
def visitModule(self, mod, depth):
self.emit("pub trait Fold<U> {", depth)
self.emit("type TargetU;", depth + 1)
self.emit("type Error;", depth + 1)
self.emit("fn map_user(&mut self, user: U) -> Result<Self::TargetU, Self::Error>;", depth + 2)
for dfn in mod.dfns:
self.visit(dfn, depth + 2)
self.emit("}", depth)
def visitType(self, type, depth):
name = type.name
apply_u, apply_target_u = self.get_generics(name, "U", "Self::TargetU")
enumname = get_rust_type(name)
self.emit(f"fn fold_{name}(&mut self, node: {enumname}{apply_u}) -> Result<{enumname}{apply_target_u}, Self::Error> {{", depth)
self.emit(f"fold_{name}(self, node)", depth + 1)
self.emit("}", depth)
class FoldImplVisitor(TypeInfoEmitVisitor):
def visitModule(self, mod, depth):
self.emit("fn fold_located<U, F: Fold<U> + ?Sized, T, MT>(folder: &mut F, node: Located<T, U>, f: impl FnOnce(&mut F, T) -> Result<MT, F::Error>) -> Result<Located<MT, F::TargetU>, F::Error> {", depth)
self.emit("Ok(Located { custom: folder.map_user(node.custom)?, location: node.location, node: f(folder, node.node)? })", depth + 1)
self.emit("}", depth)
for dfn in mod.dfns:
self.visit(dfn, depth)
def visitType(self, type, depth=0):
self.visit(type.value, type.name, depth)
def visitSum(self, sum, name, depth):
apply_t, apply_u, apply_target_u = self.get_generics(name, "T", "U", "F::TargetU")
enumname = get_rust_type(name)
is_located = bool(sum.attributes)
self.emit(f"impl<T, U> Foldable<T, U> for {enumname}{apply_t} {{", depth)
self.emit(f"type Mapped = {enumname}{apply_u};", depth + 1)
self.emit("fn fold<F: Fold<T, TargetU = U> + ?Sized>(self, folder: &mut F) -> Result<Self::Mapped, F::Error> {", depth + 1)
self.emit(f"folder.fold_{name}(self)", depth + 2)
self.emit("}", depth + 1)
self.emit("}", depth)
self.emit(f"pub fn fold_{name}<U, F: Fold<U> + ?Sized>(#[allow(unused)] folder: &mut F, node: {enumname}{apply_u}) -> Result<{enumname}{apply_target_u}, F::Error> {{", depth)
if is_located:
self.emit("fold_located(folder, node, |folder, node| {", depth)
enumname += "Kind"
self.emit("match node {", depth + 1)
for cons in sum.types:
fields_pattern = self.make_pattern(cons.fields)
self.emit(f"{enumname}::{cons.name} {{ {fields_pattern} }} => {{", depth + 2)
self.gen_construction(f"{enumname}::{cons.name}", cons.fields, depth + 3)
self.emit("}", depth + 2)
self.emit("}", depth + 1)
if is_located:
self.emit("})", depth)
self.emit("}", depth)
def visitProduct(self, product, name, depth):
apply_t, apply_u, apply_target_u = self.get_generics(name, "T", "U", "F::TargetU")
structname = get_rust_type(name)
is_located = bool(product.attributes)
self.emit(f"impl<T, U> Foldable<T, U> for {structname}{apply_t} {{", depth)
self.emit(f"type Mapped = {structname}{apply_u};", depth + 1)
self.emit("fn fold<F: Fold<T, TargetU = U> + ?Sized>(self, folder: &mut F) -> Result<Self::Mapped, F::Error> {", depth + 1)
self.emit(f"folder.fold_{name}(self)", depth + 2)
self.emit("}", depth + 1)
self.emit("}", depth)
self.emit(f"pub fn fold_{name}<U, F: Fold<U> + ?Sized>(#[allow(unused)] folder: &mut F, node: {structname}{apply_u}) -> Result<{structname}{apply_target_u}, F::Error> {{", depth)
if is_located:
self.emit("fold_located(folder, node, |folder, node| {", depth)
structname += "Data"
fields_pattern = self.make_pattern(product.fields)
self.emit(f"let {structname} {{ {fields_pattern} }} = node;", depth + 1)
self.gen_construction(structname, product.fields, depth + 1)
if is_located:
self.emit("})", depth)
self.emit("}", depth)
def make_pattern(self, fields):
return ",".join(rust_field(f.name) for f in fields)
def gen_construction(self, cons_path, fields, depth):
self.emit(f"Ok({cons_path} {{", depth)
for field in fields:
name = rust_field(field.name)
self.emit(f"{name}: Foldable::fold({name}, folder)?,", depth + 1)
self.emit("})", depth)
class FoldModuleVisitor(TypeInfoEmitVisitor):
def visitModule(self, mod):
depth = 0
self.emit('#[cfg(feature = "fold")]', depth)
self.emit("pub mod fold {", depth)
self.emit("use super::*;", depth + 1)
self.emit("use crate::fold_helpers::Foldable;", depth + 1)
FoldTraitDefVisitor(self.file, self.typeinfo).visit(mod, depth + 1)
FoldImplVisitor(self.file, self.typeinfo).visit(mod, depth + 1)
self.emit("}", depth)
class ClassDefVisitor(EmitVisitor):
def visitModule(self, mod):
for dfn in mod.dfns:
self.visit(dfn)
def visitType(self, type, depth=0):
self.visit(type.value, type.name, depth)
def visitSum(self, sum, name, depth):
for cons in sum.types:
self.visit(cons, sum.attributes, depth)
def visitConstructor(self, cons, attrs, depth):
self.gen_classdef(cons.name, cons.fields, attrs, depth)
def visitProduct(self, product, name, depth):
self.gen_classdef(name, product.fields, product.attributes, depth)
def gen_classdef(self, name, fields, attrs, depth):
structname = "Node" + name
self.emit(f'#[pyclass(module = "_ast", name = {json.dumps(name)}, base = "AstNode")]', depth)
self.emit(f"struct {structname};", depth)
self.emit("#[pyimpl(flags(HAS_DICT, BASETYPE))]", depth)
self.emit(f"impl {structname} {{", depth)
self.emit(f"#[extend_class]", depth + 1)
self.emit("fn extend_class_with_fields(ctx: &PyContext, class: &PyTypeRef) {", depth + 1)
fields = ",".join(f"ctx.new_str({json.dumps(f.name)})" for f in fields)
self.emit(f'class.set_str_attr("_fields", ctx.new_list(vec![{fields}]));', depth + 2)
attrs = ",".join(f"ctx.new_str({json.dumps(attr.name)})" for attr in attrs)
self.emit(f'class.set_str_attr("_attributes", ctx.new_list(vec![{attrs}]));', depth + 2)
self.emit("}", depth + 1)
self.emit("}", depth)
class ExtendModuleVisitor(EmitVisitor):
def visitModule(self, mod):
depth = 0
self.emit("pub fn extend_module_nodes(vm: &VirtualMachine, module: &PyObjectRef) {", depth)
self.emit("extend_module!(vm, module, {", depth + 1)
for dfn in mod.dfns:
self.visit(dfn, depth + 2)
self.emit("})", depth + 1)
self.emit("}", depth)
def visitType(self, type, depth):
self.visit(type.value, type.name, depth)
def visitSum(self, sum, name, depth):
for cons in sum.types:
self.visit(cons, depth)
def visitConstructor(self, cons, depth):
self.gen_extension(cons.name, depth)
def visitProduct(self, product, name, depth):
self.gen_extension(name, depth)
def gen_extension(self, name, depth):
self.emit(f"{json.dumps(name)} => Node{name}::make_class(&vm.ctx),", depth)
class TraitImplVisitor(EmitVisitor):
def visitModule(self, mod):
for dfn in mod.dfns:
self.visit(dfn)
def visitType(self, type, depth=0):
self.visit(type.value, type.name, depth)
def visitSum(self, sum, name, depth):
enumname = get_rust_type(name)
if sum.attributes:
enumname += "Kind"
self.emit(f"impl NamedNode for ast::{enumname} {{", depth)
self.emit(f"const NAME: &'static str = {json.dumps(name)};", depth + 1)
self.emit("}", depth)
self.emit(f"impl Node for ast::{enumname} {{", depth)
self.emit("fn ast_to_object(self, _vm: &VirtualMachine) -> PyObjectRef {", depth + 1)
self.emit("match self {", depth + 2)
for variant in sum.types:
self.constructor_to_object(variant, enumname, depth + 3)
self.emit("}", depth + 2)
self.emit("}", depth + 1)
self.emit("fn ast_from_object(_vm: &VirtualMachine, _object: PyObjectRef) -> PyResult<Self> {", depth + 1)
self.gen_sum_fromobj(sum, name, enumname, depth + 2)
self.emit("}", depth + 1)
self.emit("}", depth)
def constructor_to_object(self, cons, enumname, depth):
fields_pattern = self.make_pattern(cons.fields)
self.emit(f"ast::{enumname}::{cons.name} {{ {fields_pattern} }} => {{", depth)
self.make_node(cons.name, cons.fields, depth + 1)
self.emit("}", depth)
def visitProduct(self, product, name, depth):
structname = get_rust_type(name)
if product.attributes:
structname += "Data"
self.emit(f"impl NamedNode for ast::{structname} {{", depth)
self.emit(f"const NAME: &'static str = {json.dumps(name)};", depth + 1)
self.emit("}", depth)
self.emit(f"impl Node for ast::{structname} {{", depth)
self.emit("fn ast_to_object(self, _vm: &VirtualMachine) -> PyObjectRef {", depth + 1)
fields_pattern = self.make_pattern(product.fields)
self.emit(f"let ast::{structname} {{ {fields_pattern} }} = self;", depth + 2)
self.make_node(name, product.fields, depth + 2)
self.emit("}", depth + 1)
self.emit("fn ast_from_object(_vm: &VirtualMachine, _object: PyObjectRef) -> PyResult<Self> {", depth + 1)
self.gen_product_fromobj(product, name, structname, depth + 2)
self.emit("}", depth + 1)
self.emit("}", depth)
def make_node(self, variant, fields, depth):
lines = []
self.emit(f"let _node = AstNode.into_ref_with_type(_vm, Node{variant}::static_type().clone()).unwrap();", depth)
if fields:
self.emit("let _dict = _node.as_object().dict().unwrap();", depth)
for f in fields:
self.emit(f"_dict.set_item({json.dumps(f.name)}, {rust_field(f.name)}.ast_to_object(_vm), _vm).unwrap();", depth)
self.emit("_node.into_object()", depth)
def make_pattern(self, fields):
return ",".join(rust_field(f.name) for f in fields)
def gen_sum_fromobj(self, sum, sumname, enumname, depth):
if sum.attributes:
self.extract_location(sumname, depth)
self.emit("let _cls = _object.class();", depth)
self.emit("Ok(", depth)
for cons in sum.types:
self.emit(f"if _cls.is(Node{cons.name}::static_type()) {{", depth)
self.gen_construction(f"{enumname}::{cons.name}", cons, sumname, depth + 1)
self.emit("} else", depth)
self.emit("{", depth)
msg = f'format!("expected some sort of {sumname}, but got {{}}",_vm.to_repr(&_object)?)'
self.emit(f"return Err(_vm.new_type_error({msg}));", depth + 1)
self.emit("})", depth)
def gen_product_fromobj(self, product, prodname, structname, depth):
if product.attributes:
self.extract_location(prodname, depth)
self.emit("Ok(", depth)
self.gen_construction(structname, product, prodname, depth + 1)
self.emit(")", depth)
def gen_construction(self, cons_path, cons, name, depth):
self.emit(f"ast::{cons_path} {{", depth)
for field in cons.fields:
self.emit(f"{rust_field(field.name)}: {self.decode_field(field, name)},", depth + 1)
self.emit("}", depth)
def extract_location(self, typename, depth):
row = self.decode_field(asdl.Field('int', 'lineno'), typename)
column = self.decode_field(asdl.Field('int', 'col_offset'), typename)
self.emit(f"let _location = ast::Location::new({row}, {column});", depth)
def wrap_located_node(self, depth):
self.emit(f"let node = ast::Located::new(_location, node);", depth)
def decode_field(self, field, typename):
name = json.dumps(field.name)
if field.opt and not field.seq:
return f"get_node_field_opt(_vm, &_object, {name})?.map(|obj| Node::ast_from_object(_vm, obj)).transpose()?"
else:
return f"Node::ast_from_object(_vm, get_node_field(_vm, &_object, {name}, {json.dumps(typename)})?)?"
class ChainOfVisitors:
def __init__(self, *visitors):
self.visitors = visitors
def visit(self, object):
for v in self.visitors:
v.visit(object)
v.emit("", 0)
def write_ast_def(mod, typeinfo, f):
f.write('pub use crate::location::Location;\n')
f.write('pub use crate::constant::*;\n')
f.write('\n')
f.write('type Ident = String;\n')
f.write('\n')
StructVisitor(f, typeinfo).emit_attrs(0)
f.write('pub struct Located<T, U = ()> {\n')
f.write(' pub location: Location,\n')
f.write(' pub custom: U,\n')
f.write(' pub node: T,\n')
f.write('}\n')
f.write('\n')
f.write('impl<T> Located<T> {\n')
f.write(' pub fn new(location: Location, node: T) -> Self {\n')
f.write(' Self { location, custom: (), node }\n')
f.write(' }\n')
f.write('}\n')
f.write('\n')
c = ChainOfVisitors(StructVisitor(f, typeinfo),
FoldModuleVisitor(f, typeinfo))
c.visit(mod)
def write_ast_mod(mod, f):
f.write('use super::*;\n')
f.write('\n')
c = ChainOfVisitors(ClassDefVisitor(f),
TraitImplVisitor(f),
ExtendModuleVisitor(f))
c.visit(mod)
def main(input_filename, ast_mod_filename, ast_def_filename, dump_module=False):
auto_gen_msg = AUTOGEN_MESSAGE.format("/".join(Path(__file__).parts[-2:]))
mod = asdl.parse(input_filename)
if dump_module:
print('Parsed Module:')
print(mod)
if not asdl.check(mod):
sys.exit(1)
typeinfo = {}
FindUserdataTypesVisitor(typeinfo).visit(mod)
with ast_def_filename.open("w") as def_file, \
ast_mod_filename.open("w") as mod_file:
def_file.write(auto_gen_msg)
write_ast_def(mod, typeinfo, def_file)
mod_file.write(auto_gen_msg)
write_ast_mod(mod, mod_file)
print(f"{ast_def_filename}, {ast_mod_filename} regenerated.")
if __name__ == "__main__":
parser = ArgumentParser()
parser.add_argument("input_file", type=Path)
parser.add_argument("-M", "--mod-file", type=Path, required=True)
parser.add_argument("-D", "--def-file", type=Path, required=True)
parser.add_argument("-d", "--dump-module", action="store_true")
args = parser.parse_args()
main(args.input_file, args.mod_file, args.def_file, args.dump_module)

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@ -1,183 +0,0 @@
#[derive(Clone, Debug, PartialEq)]
pub enum Constant {
None,
Bool(bool),
Str(String),
Bytes(Vec<u8>),
Int(i128),
Tuple(Vec<Constant>),
Float(f64),
Complex { real: f64, imag: f64 },
Ellipsis,
}
impl From<String> for Constant {
fn from(s: String) -> Constant {
Self::Str(s)
}
}
impl From<Vec<u8>> for Constant {
fn from(b: Vec<u8>) -> Constant {
Self::Bytes(b)
}
}
impl From<bool> for Constant {
fn from(b: bool) -> Constant {
Self::Bool(b)
}
}
impl From<i32> for Constant {
fn from(i: i32) -> Constant {
Self::Int(i128::from(i))
}
}
impl From<i64> for Constant {
fn from(i: i64) -> Constant {
Self::Int(i128::from(i))
}
}
/// Transforms a value prior to formatting it.
#[derive(Copy, Clone, Debug, PartialEq)]
#[repr(u8)]
pub enum ConversionFlag {
/// Converts by calling `str(<value>)`.
Str = b's',
/// Converts by calling `ascii(<value>)`.
Ascii = b'a',
/// Converts by calling `repr(<value>)`.
Repr = b'r',
}
impl ConversionFlag {
#[must_use]
pub fn try_from_byte(b: u8) -> Option<Self> {
match b {
b's' => Some(Self::Str),
b'a' => Some(Self::Ascii),
b'r' => Some(Self::Repr),
_ => None,
}
}
}
#[cfg(feature = "constant-optimization")]
#[derive(Default)]
pub struct ConstantOptimizer {
_priv: (),
}
#[cfg(feature = "constant-optimization")]
impl ConstantOptimizer {
#[inline]
#[must_use]
pub fn new() -> Self {
Self { _priv: () }
}
}
#[cfg(feature = "constant-optimization")]
impl<U> crate::fold::Fold<U> for ConstantOptimizer {
type TargetU = U;
type Error = std::convert::Infallible;
#[inline]
fn map_user(&mut self, user: U) -> Result<Self::TargetU, Self::Error> {
Ok(user)
}
fn fold_expr(&mut self, node: crate::Expr<U>) -> Result<crate::Expr<U>, Self::Error> {
match node.node {
crate::ExprKind::Tuple { elts, ctx } => {
let elts =
elts.into_iter().map(|x| self.fold_expr(x)).collect::<Result<Vec<_>, _>>()?;
let expr =
if elts.iter().all(|e| matches!(e.node, crate::ExprKind::Constant { .. })) {
let tuple = elts
.into_iter()
.map(|e| match e.node {
crate::ExprKind::Constant { value, .. } => value,
_ => unreachable!(),
})
.collect();
crate::ExprKind::Constant { value: Constant::Tuple(tuple), kind: None }
} else {
crate::ExprKind::Tuple { elts, ctx }
};
Ok(crate::Expr { node: expr, custom: node.custom, location: node.location })
}
_ => crate::fold::fold_expr(self, node),
}
}
}
#[cfg(test)]
mod tests {
#[cfg(feature = "constant-optimization")]
#[test]
fn test_constant_opt() {
use super::*;
use crate::fold::Fold;
use crate::*;
let location = Location::new(0, 0, FileName::default());
let custom = ();
let ast = Located {
location,
custom,
node: ExprKind::Tuple {
ctx: ExprContext::Load,
elts: vec![
Located {
location,
custom,
node: ExprKind::Constant { value: 1.into(), kind: None },
},
Located {
location,
custom,
node: ExprKind::Constant { value: 2.into(), kind: None },
},
Located {
location,
custom,
node: ExprKind::Tuple {
ctx: ExprContext::Load,
elts: vec![
Located {
location,
custom,
node: ExprKind::Constant { value: 3.into(), kind: None },
},
Located {
location,
custom,
node: ExprKind::Constant { value: 4.into(), kind: None },
},
Located {
location,
custom,
node: ExprKind::Constant { value: 5.into(), kind: None },
},
],
},
},
],
},
};
let new_ast = ConstantOptimizer::new().fold_expr(ast).unwrap_or_else(|e| match e {});
assert_eq!(
new_ast,
Located {
location,
custom,
node: ExprKind::Constant {
value: Constant::Tuple(vec![
1.into(),
2.into(),
Constant::Tuple(vec![3.into(), 4.into(), 5.into(),])
]),
kind: None
},
}
);
}
}

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@ -1,67 +0,0 @@
use crate::constant;
use crate::fold::Fold;
use crate::StrRef;
pub(crate) trait Foldable<T, U> {
type Mapped;
fn fold<F: Fold<T, TargetU = U> + ?Sized>(
self,
folder: &mut F,
) -> Result<Self::Mapped, F::Error>;
}
impl<T, U, X> Foldable<T, U> for Vec<X>
where
X: Foldable<T, U>,
{
type Mapped = Vec<X::Mapped>;
fn fold<F: Fold<T, TargetU = U> + ?Sized>(
self,
folder: &mut F,
) -> Result<Self::Mapped, F::Error> {
self.into_iter().map(|x| x.fold(folder)).collect()
}
}
impl<T, U, X> Foldable<T, U> for Option<X>
where
X: Foldable<T, U>,
{
type Mapped = Option<X::Mapped>;
fn fold<F: Fold<T, TargetU = U> + ?Sized>(
self,
folder: &mut F,
) -> Result<Self::Mapped, F::Error> {
self.map(|x| x.fold(folder)).transpose()
}
}
impl<T, U, X> Foldable<T, U> for Box<X>
where
X: Foldable<T, U>,
{
type Mapped = Box<X::Mapped>;
fn fold<F: Fold<T, TargetU = U> + ?Sized>(
self,
folder: &mut F,
) -> Result<Self::Mapped, F::Error> {
(*self).fold(folder).map(Box::new)
}
}
macro_rules! simple_fold {
($($t:ty),+$(,)?) => {
$(impl<T, U> $crate::fold_helpers::Foldable<T, U> for $t {
type Mapped = Self;
#[inline]
fn fold<F: Fold<T, TargetU = U> + ?Sized>(
self,
_folder: &mut F,
) -> Result<Self::Mapped, F::Error> {
Ok(self)
}
})+
};
}
simple_fold!(usize, String, bool, StrRef, constant::Constant, constant::ConversionFlag);

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@ -1,51 +0,0 @@
use crate::{Constant, ExprKind};
impl<U> ExprKind<U> {
/// Returns a short name for the node suitable for use in error messages.
#[must_use]
pub fn name(&self) -> &'static str {
match self {
ExprKind::BoolOp { .. } | ExprKind::BinOp { .. } | ExprKind::UnaryOp { .. } => {
"operator"
}
ExprKind::Subscript { .. } => "subscript",
ExprKind::Await { .. } => "await expression",
ExprKind::Yield { .. } | ExprKind::YieldFrom { .. } => "yield expression",
ExprKind::Compare { .. } => "comparison",
ExprKind::Attribute { .. } => "attribute",
ExprKind::Call { .. } => "function call",
ExprKind::Constant { value, .. } => match value {
Constant::Str(_)
| Constant::Int(_)
| Constant::Float(_)
| Constant::Complex { .. }
| Constant::Bytes(_) => "literal",
Constant::Tuple(_) => "tuple",
Constant::Bool(_) | Constant::None => "keyword",
Constant::Ellipsis => "ellipsis",
},
ExprKind::List { .. } => "list",
ExprKind::Tuple { .. } => "tuple",
ExprKind::Dict { .. } => "dict display",
ExprKind::Set { .. } => "set display",
ExprKind::ListComp { .. } => "list comprehension",
ExprKind::DictComp { .. } => "dict comprehension",
ExprKind::SetComp { .. } => "set comprehension",
ExprKind::GeneratorExp { .. } => "generator expression",
ExprKind::Starred { .. } => "starred",
ExprKind::Slice { .. } => "slice",
ExprKind::JoinedStr { values } => {
if values.iter().any(|e| matches!(e.node, ExprKind::JoinedStr { .. })) {
"f-string expression"
} else {
"literal"
}
}
ExprKind::FormattedValue { .. } => "f-string expression",
ExprKind::Name { .. } => "name",
ExprKind::Lambda { .. } => "lambda",
ExprKind::IfExp { .. } => "conditional expression",
ExprKind::NamedExpr { .. } => "named expression",
}
}
}

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@ -1,21 +0,0 @@
#![deny(future_incompatible, let_underscore, nonstandard_style, clippy::all)]
#![warn(clippy::pedantic)]
#![allow(
clippy::missing_errors_doc,
clippy::missing_panics_doc,
clippy::module_name_repetitions,
clippy::too_many_lines,
clippy::wildcard_imports
)]
mod ast_gen;
mod constant;
#[cfg(feature = "fold")]
mod fold_helpers;
mod impls;
mod location;
pub use ast_gen::*;
pub use location::{FileName, Location};
pub type Suite<U = ()> = Vec<Stmt<U>>;

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@ -1,116 +0,0 @@
//! Datatypes to support source location information.
use crate::ast_gen::StrRef;
use std::cmp::Ordering;
use std::fmt;
#[derive(Clone, Copy, Debug, Eq, PartialEq)]
pub struct FileName(pub StrRef);
impl Default for FileName {
fn default() -> Self {
FileName("unknown".into())
}
}
impl From<String> for FileName {
fn from(s: String) -> Self {
FileName(s.into())
}
}
/// A location somewhere in the sourcecode.
#[derive(Clone, Copy, Debug, Default, Eq, PartialEq)]
pub struct Location {
pub row: usize,
pub column: usize,
pub file: FileName,
}
impl fmt::Display for Location {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
write!(f, "{}:{}:{}", self.file.0, self.row, self.column)
}
}
impl Ord for Location {
fn cmp(&self, other: &Self) -> Ordering {
let file_cmp = self.file.0.to_string().cmp(&other.file.0.to_string());
if file_cmp != Ordering::Equal {
return file_cmp;
}
let row_cmp = self.row.cmp(&other.row);
if row_cmp != Ordering::Equal {
return row_cmp;
}
self.column.cmp(&other.column)
}
}
impl PartialOrd for Location {
fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
Some(self.cmp(other))
}
}
impl Location {
pub fn visualize<'a>(
&self,
line: &'a str,
desc: impl fmt::Display + 'a,
) -> impl fmt::Display + 'a {
struct Visualize<'a, D: fmt::Display> {
loc: Location,
line: &'a str,
desc: D,
}
impl<D: fmt::Display> fmt::Display for Visualize<'_, D> {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
write!(
f,
"{}\n{}\n{arrow:>pad$}",
self.desc,
self.line,
pad = self.loc.column,
arrow = "",
)
}
}
Visualize { loc: *self, line, desc }
}
}
impl Location {
#[must_use]
pub fn new(row: usize, column: usize, file: FileName) -> Self {
Location { row, column, file }
}
#[must_use]
pub fn row(&self) -> usize {
self.row
}
#[must_use]
pub fn column(&self) -> usize {
self.column
}
pub fn reset(&mut self) {
self.row = 1;
self.column = 1;
}
pub fn go_right(&mut self) {
self.column += 1;
}
pub fn go_left(&mut self) {
self.column -= 1;
}
pub fn newline(&mut self) {
self.row += 1;
self.column = 1;
}
}

View File

@ -2,33 +2,15 @@
name = "nac3core" name = "nac3core"
version = "0.1.0" version = "0.1.0"
authors = ["M-Labs"] authors = ["M-Labs"]
edition = "2021" edition = "2018"
[features]
default = ["derive"]
derive = ["dep:nac3core_derive"]
no-escape-analysis = []
[dependencies] [dependencies]
itertools = "0.13" num-bigint = "0.3"
crossbeam = "0.8" num-traits = "0.2"
indexmap = "2.6" inkwell = { git = "https://github.com/TheDan64/inkwell", branch = "master", features = ["llvm10-0"] }
parking_lot = "0.12" rustpython-parser = { git = "https://github.com/RustPython/RustPython", branch = "master" }
rayon = "1.10" indoc = "1.0"
nac3core_derive = { path = "nac3core_derive", optional = true }
nac3parser = { path = "../nac3parser" }
strum = "0.26"
strum_macros = "0.26"
[dependencies.inkwell]
version = "0.5"
default-features = false
features = ["llvm14-0-prefer-dynamic", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]
[dev-dependencies] [dev-dependencies]
test-case = "1.2.0" test-case = "1.2.0"
indoc = "2.0" indoc = "1.0"
insta = "=1.11.0"
[build-dependencies]
regex = "1.10"

View File

@ -1,109 +0,0 @@
use std::{
env,
fs::File,
io::Write,
path::Path,
process::{Command, Stdio},
};
use regex::Regex;
fn main() {
let out_dir = env::var("OUT_DIR").unwrap();
let out_dir = Path::new(&out_dir);
let irrt_dir = Path::new("irrt");
let irrt_cpp_path = irrt_dir.join("irrt.cpp");
/*
* HACK: Sadly, clang doesn't let us emit generic LLVM bitcode.
* Compiling for WASM32 and filtering the output with regex is the closest we can get.
*/
let mut flags: Vec<&str> = vec![
"--target=wasm32",
"-x",
"c++",
"-std=c++20",
"-fno-discard-value-names",
"-fno-exceptions",
"-fno-rtti",
"-emit-llvm",
"-S",
"-Wall",
"-Wextra",
"-o",
"-",
"-I",
irrt_dir.to_str().unwrap(),
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")
.args(flags)
.output()
.inspect(|o| {
assert!(o.status.success(), "{}", std::str::from_utf8(&o.stderr).unwrap());
})
.unwrap();
// https://github.com/rust-lang/regex/issues/244
let output = std::str::from_utf8(&output.stdout).unwrap().replace("\r\n", "\n");
let mut filtered_output = String::with_capacity(output.len());
// Filter out irrelevant IR
//
// Regex:
// - `(?ms:^define.*?\}$)` captures LLVM `define` blocks
// - `(?m:^declare.*?$)` captures LLVM `declare` lines
// - `(?m:^%.+?=\s*type\s*\{.+?\}$)` captures LLVM `type` declarations
// - `(?m:^@.+?=.+$)` captures global constants
let regex_filter = Regex::new(
r"(?ms:^define.*?\}$)|(?m:^declare.*?$)|(?m:^%.+?=\s*type\s*\{.+?\}$)|(?m:^@.+?=.+$)",
)
.unwrap();
for f in regex_filter.captures_iter(&output) {
assert_eq!(f.len(), 1);
filtered_output.push_str(&f[0]);
filtered_output.push('\n');
}
let filtered_output = Regex::new("(#\\d+)|(, *![0-9A-Za-z.]+)|(![0-9A-Za-z.]+)|(!\".*?\")")
.unwrap()
.replace_all(&filtered_output, "");
// For debugging
// Doing `DEBUG_DUMP_IRRT=1 cargo build -p nac3core` dumps the LLVM IR generated
const DEBUG_DUMP_IRRT: &str = "DEBUG_DUMP_IRRT";
println!("cargo:rerun-if-env-changed={DEBUG_DUMP_IRRT}");
if env::var(DEBUG_DUMP_IRRT).is_ok() {
let mut file = File::create(out_dir.join("irrt.ll")).unwrap();
file.write_all(output.as_bytes()).unwrap();
let mut file = File::create(out_dir.join("irrt-filtered.ll")).unwrap();
file.write_all(filtered_output.as_bytes()).unwrap();
}
let mut llvm_as = Command::new("llvm-as-irrt")
.stdin(Stdio::piped())
.arg("-o")
.arg(out_dir.join("irrt.bc"))
.spawn()
.unwrap();
llvm_as.stdin.as_mut().unwrap().write_all(filtered_output.as_bytes()).unwrap();
assert!(llvm_as.wait().unwrap().success());
}

View File

@ -1,15 +0,0 @@
#include "irrt/exception.hpp"
#include "irrt/list.hpp"
#include "irrt/math.hpp"
#include "irrt/range.hpp"
#include "irrt/slice.hpp"
#include "irrt/string.hpp"
#include "irrt/ndarray/basic.hpp"
#include "irrt/ndarray/def.hpp"
#include "irrt/ndarray/iter.hpp"
#include "irrt/ndarray/indexing.hpp"
#include "irrt/ndarray/array.hpp"
#include "irrt/ndarray/reshape.hpp"
#include "irrt/ndarray/broadcast.hpp"
#include "irrt/ndarray/transpose.hpp"
#include "irrt/ndarray/matmul.hpp"

View File

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

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); \
} \
}

View File

@ -1,85 +0,0 @@
#pragma once
#include "irrt/cslice.hpp"
#include "irrt/int_types.hpp"
/**
* @brief The int type of ARTIQ exception IDs.
*/
using ExceptionId = int32_t;
/*
* 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<void*>(const_cast<char*>(filename)),
.len = static_cast<SizeT>(__builtin_strlen(filename))},
.line = line,
.column = 0,
.function = {.base = reinterpret_cast<void*>(const_cast<char*>(function)),
.len = static_cast<SizeT>(__builtin_strlen(function))},
.msg = {.base = reinterpret_cast<void*>(const_cast<char*>(msg)),
.len = static_cast<SizeT>(__builtin_strlen(msg))},
};
e.params[0] = param0;
e.params[1] = param1;
e.params[2] = param2;
__nac3_raise(reinterpret_cast<void*>(&e));
__builtin_unreachable();
}
} // namespace
/**
* @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)

View File

@ -1,25 +0,0 @@
#pragma once
#if __STDC_VERSION__ >= 202000
using int8_t = _BitInt(8);
using uint8_t = unsigned _BitInt(8);
using int32_t = _BitInt(32);
using uint32_t = unsigned _BitInt(32);
using int64_t = _BitInt(64);
using uint64_t = unsigned _BitInt(64);
#else
#pragma clang diagnostic push
#pragma clang diagnostic ignored "-Wdeprecated-type"
using int8_t = _ExtInt(8);
using uint8_t = unsigned _ExtInt(8);
using int32_t = _ExtInt(32);
using uint32_t = unsigned _ExtInt(32);
using int64_t = _ExtInt(64);
using uint64_t = unsigned _ExtInt(64);
#pragma clang diagnostic pop
#endif
// The type of an index or a value describing the length of a range/slice is always `int32_t`.
using SliceIndex = int32_t;

View File

@ -1,96 +0,0 @@
#pragma once
#include "irrt/int_types.hpp"
#include "irrt/math_util.hpp"
#include "irrt/slice.hpp"
namespace {
/**
* @brief A list in NAC3.
*
* The `items` field is opaque. You must rely on external contexts to
* know how to interpret it.
*/
template<typename SizeT>
struct List {
uint8_t* items;
SizeT len;
};
} // namespace
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,
void* dest_arr,
SliceIndex dest_arr_len,
SliceIndex src_start,
SliceIndex src_end,
SliceIndex src_step,
void* 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(static_cast<uint8_t*>(dest_arr) + dest_start * size,
static_cast<uint8_t*>(src_arr) + src_start * size, src_len * size);
}
if (dest_len > 0) {
/* dropping */
__builtin_memmove(static_cast<uint8_t*>(dest_arr) + (dest_start + src_len) * size,
static_cast<uint8_t*>(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) {
void* tmp = __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(static_cast<uint8_t*>(dest_arr) + dest_ind, static_cast<uint8_t*>(src_arr) + src_ind, 1);
} else if (size == 4) {
__builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind * 4,
static_cast<uint8_t*>(src_arr) + src_ind * 4, 4);
} else if (size == 8) {
__builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind * 8,
static_cast<uint8_t*>(src_arr) + src_ind * 8, 8);
} else {
/* memcpy for var size, cannot overlap after previous alloca */
__builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind * size,
static_cast<uint8_t*>(src_arr) + src_ind * size, size);
}
}
/* only dest_step == 1 can we shrink the dest list. */
/* size should be ensured prior to calling this function */
if (dest_step == 1 && dest_end >= dest_start) {
__builtin_memmove(static_cast<uint8_t*>(dest_arr) + dest_ind * size,
static_cast<uint8_t*>(dest_arr) + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size);
return dest_arr_len - (dest_end - dest_ind) - 1;
}
return dest_arr_len;
}
} // extern "C"

View File

@ -1,95 +0,0 @@
#pragma once
#include "irrt/int_types.hpp"
namespace {
// adapted from GNU Scientific Library: https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
// need to make sure `exp >= 0` before calling this function
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);
}
} // namespace

View File

@ -1,13 +0,0 @@
#pragma once
namespace {
template<typename T>
const T& max(const T& a, const T& b) {
return a > b ? a : b;
}
template<typename T>
const T& min(const T& a, const T& b) {
return a > b ? b : a;
}
} // namespace

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@ -1,132 +0,0 @@
#pragma once
#include "irrt/debug.hpp"
#include "irrt/exception.hpp"
#include "irrt/int_types.hpp"
#include "irrt/list.hpp"
#include "irrt/ndarray/basic.hpp"
#include "irrt/ndarray/def.hpp"
namespace {
namespace ndarray::array {
/**
* @brief In the context of `np.array(<list>)`, deduce the ndarray's shape produced by `<list>` and raise
* an exception if there is anything wrong with `<shape>` (e.g., inconsistent dimensions `np.array([[1.0, 2.0],
* [3.0]])`)
*
* If this function finds no issues with `<list>`, the deduced shape is written to `shape`. The caller has the
* responsibility to allocate `[SizeT; ndims]` for `shape`. The caller must also initialize `shape` with `-1`s because
* of implementation details.
*/
template<typename SizeT>
void set_and_validate_list_shape_helper(SizeT axis, List<SizeT>* list, SizeT ndims, SizeT* shape) {
if (shape[axis] == -1) {
// Dimension is unspecified. Set it.
shape[axis] = list->len;
} else {
// Dimension is specified. Check.
if (shape[axis] != list->len) {
// Mismatch, throw an error.
// NOTE: NumPy's error message is more complex and needs more PARAMS to display.
raise_exception(SizeT, EXN_VALUE_ERROR,
"The requested array has an inhomogenous shape "
"after {0} dimension(s).",
axis, shape[axis], list->len);
}
}
if (axis + 1 == ndims) {
// `list` has type `list[ItemType]`
// Do nothing
} else {
// `list` has type `list[list[...]]`
List<SizeT>** lists = (List<SizeT>**)(list->items);
for (SizeT i = 0; i < list->len; i++) {
set_and_validate_list_shape_helper<SizeT>(axis + 1, lists[i], ndims, shape);
}
}
}
/**
* @brief See `set_and_validate_list_shape_helper`.
*/
template<typename SizeT>
void set_and_validate_list_shape(List<SizeT>* list, SizeT ndims, SizeT* shape) {
for (SizeT axis = 0; axis < ndims; axis++) {
shape[axis] = -1; // Sentinel to say this dimension is unspecified.
}
set_and_validate_list_shape_helper<SizeT>(0, list, ndims, shape);
}
/**
* @brief In the context of `np.array(<list>)`, copied the contents stored in `list` to `ndarray`.
*
* `list` is assumed to be "legal". (i.e., no inconsistent dimensions)
*
* # Notes on `ndarray`
* The caller is responsible for allocating space for `ndarray`.
* Here is what this function expects from `ndarray` when called:
* - `ndarray->data` has to be allocated, contiguous, and may contain uninitialized values.
* - `ndarray->itemsize` has to be initialized.
* - `ndarray->ndims` has to be initialized.
* - `ndarray->shape` has to be initialized.
* - `ndarray->strides` is ignored, but note that `ndarray->data` is contiguous.
* When this function call ends:
* - `ndarray->data` is written with contents from `<list>`.
*/
template<typename SizeT>
void write_list_to_array_helper(SizeT axis, SizeT* index, List<SizeT>* list, NDArray<SizeT>* ndarray) {
debug_assert_eq(SizeT, list->len, ndarray->shape[axis]);
if (IRRT_DEBUG_ASSERT_BOOL) {
if (!ndarray::basic::is_c_contiguous(ndarray)) {
raise_debug_assert(SizeT, "ndarray is not C-contiguous", ndarray->strides[0], ndarray->strides[1],
NO_PARAM);
}
}
if (axis + 1 == ndarray->ndims) {
// `list` has type `list[scalar]`
// `ndarray` is contiguous, so we can do this, and this is fast.
uint8_t* dst = static_cast<uint8_t*>(ndarray->data) + (ndarray->itemsize * (*index));
__builtin_memcpy(dst, list->items, ndarray->itemsize * list->len);
*index += list->len;
} else {
// `list` has type `list[list[...]]`
List<SizeT>** lists = (List<SizeT>**)(list->items);
for (SizeT i = 0; i < list->len; i++) {
write_list_to_array_helper<SizeT>(axis + 1, index, lists[i], ndarray);
}
}
}
/**
* @brief See `write_list_to_array_helper`.
*/
template<typename SizeT>
void write_list_to_array(List<SizeT>* list, NDArray<SizeT>* ndarray) {
SizeT index = 0;
write_list_to_array_helper<SizeT>((SizeT)0, &index, list, ndarray);
}
} // namespace ndarray::array
} // namespace
extern "C" {
using namespace ndarray::array;
void __nac3_ndarray_array_set_and_validate_list_shape(List<int32_t>* list, int32_t ndims, int32_t* shape) {
set_and_validate_list_shape(list, ndims, shape);
}
void __nac3_ndarray_array_set_and_validate_list_shape64(List<int64_t>* list, int64_t ndims, int64_t* shape) {
set_and_validate_list_shape(list, ndims, shape);
}
void __nac3_ndarray_array_write_list_to_array(List<int32_t>* list, NDArray<int32_t>* ndarray) {
write_list_to_array(list, ndarray);
}
void __nac3_ndarray_array_write_list_to_array64(List<int64_t>* list, NDArray<int64_t>* ndarray) {
write_list_to_array(list, ndarray);
}
}

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#pragma once
#include "irrt/debug.hpp"
#include "irrt/exception.hpp"
#include "irrt/int_types.hpp"
#include "irrt/ndarray/def.hpp"
namespace {
namespace ndarray::basic {
/**
* @brief Assert that `shape` does not contain negative dimensions.
*
* @param ndims Number of dimensions in `shape`
* @param shape The shape to check on
*/
template<typename SizeT>
void assert_shape_no_negative(SizeT ndims, const SizeT* shape) {
for (SizeT axis = 0; axis < ndims; axis++) {
if (shape[axis] < 0) {
raise_exception(SizeT, EXN_VALUE_ERROR,
"negative dimensions are not allowed; axis {0} "
"has dimension {1}",
axis, shape[axis], NO_PARAM);
}
}
}
/**
* @brief Assert that two shapes are the same in the context of writing output to an ndarray.
*/
template<typename SizeT>
void assert_output_shape_same(SizeT ndarray_ndims,
const SizeT* ndarray_shape,
SizeT output_ndims,
const SizeT* output_shape) {
if (ndarray_ndims != output_ndims) {
// There is no corresponding NumPy error message like this.
raise_exception(SizeT, EXN_VALUE_ERROR, "Cannot write output of ndims {0} to an ndarray with ndims {1}",
output_ndims, ndarray_ndims, NO_PARAM);
}
for (SizeT axis = 0; axis < ndarray_ndims; axis++) {
if (ndarray_shape[axis] != output_shape[axis]) {
// There is no corresponding NumPy error message like this.
raise_exception(SizeT, EXN_VALUE_ERROR,
"Mismatched dimensions on axis {0}, output has "
"dimension {1}, but destination ndarray has dimension {2}.",
axis, output_shape[axis], ndarray_shape[axis]);
}
}
}
/**
* @brief Return the number of elements of an ndarray given its shape.
*
* @param ndims Number of dimensions in `shape`
* @param shape The shape of the ndarray
*/
template<typename SizeT>
SizeT calc_size_from_shape(SizeT ndims, const SizeT* shape) {
SizeT size = 1;
for (SizeT axis = 0; axis < ndims; axis++)
size *= shape[axis];
return size;
}
/**
* @brief Compute the array indices of the `nth` (0-based) element of an ndarray given only its shape.
*
* @param ndims Number of elements in `shape` and `indices`
* @param shape The shape of the ndarray
* @param indices The returned indices indexing the ndarray with shape `shape`.
* @param nth The index of the element of interest.
*/
template<typename SizeT>
void set_indices_by_nth(SizeT ndims, const SizeT* shape, SizeT* indices, SizeT nth) {
for (SizeT i = 0; i < ndims; i++) {
SizeT axis = ndims - i - 1;
SizeT dim = shape[axis];
indices[axis] = nth % dim;
nth /= dim;
}
}
/**
* @brief Return the number of elements of an `ndarray`
*
* This function corresponds to `<an_ndarray>.size`
*/
template<typename SizeT>
SizeT size(const NDArray<SizeT>* ndarray) {
return calc_size_from_shape(ndarray->ndims, ndarray->shape);
}
/**
* @brief Return of the number of its content of an `ndarray`.
*
* This function corresponds to `<an_ndarray>.nbytes`.
*/
template<typename SizeT>
SizeT nbytes(const NDArray<SizeT>* ndarray) {
return size(ndarray) * ndarray->itemsize;
}
/**
* @brief Get the `len()` of an ndarray, and asserts that `ndarray` is a sized object.
*
* This function corresponds to `<an_ndarray>.__len__`.
*
* @param dst_length The length.
*/
template<typename SizeT>
SizeT len(const NDArray<SizeT>* ndarray) {
if (ndarray->ndims != 0) {
return ndarray->shape[0];
}
// numpy prohibits `__len__` on unsized objects
raise_exception(SizeT, EXN_TYPE_ERROR, "len() of unsized object", NO_PARAM, NO_PARAM, NO_PARAM);
__builtin_unreachable();
}
/**
* @brief Return a boolean indicating if `ndarray` is (C-)contiguous.
*
* You may want to see ndarray's rules for C-contiguity:
* https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45
*/
template<typename SizeT>
bool is_c_contiguous(const NDArray<SizeT>* ndarray) {
// References:
// - tinynumpy's implementation:
// https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L102
// - ndarray's flags["C_CONTIGUOUS"]:
// https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html#numpy.ndarray.flags
// - ndarray's rules for C-contiguity:
// https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45
// From
// https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45:
//
// The traditional rule is that for an array to be flagged as C contiguous,
// the following must hold:
//
// strides[-1] == itemsize
// strides[i] == shape[i+1] * strides[i + 1]
// [...]
// According to these rules, a 0- or 1-dimensional array is either both
// C- and F-contiguous, or neither; and an array with 2+ dimensions
// can be C- or F- contiguous, or neither, but not both. Though there
// there are exceptions for arrays with zero or one item, in the first
// case the check is relaxed up to and including the first dimension
// with shape[i] == 0. In the second case `strides == itemsize` will
// can be true for all dimensions and both flags are set.
if (ndarray->ndims == 0) {
return true;
}
if (ndarray->strides[ndarray->ndims - 1] != ndarray->itemsize) {
return false;
}
for (SizeT i = 1; i < ndarray->ndims; i++) {
SizeT axis_i = ndarray->ndims - i - 1;
if (ndarray->strides[axis_i] != ndarray->shape[axis_i + 1] * ndarray->strides[axis_i + 1]) {
return false;
}
}
return true;
}
/**
* @brief Return the pointer to the element indexed by `indices` along the ndarray's axes.
*
* This function does no bound check.
*/
template<typename SizeT>
void* get_pelement_by_indices(const NDArray<SizeT>* ndarray, const SizeT* indices) {
void* element = ndarray->data;
for (SizeT dim_i = 0; dim_i < ndarray->ndims; dim_i++)
element = static_cast<uint8_t*>(element) + indices[dim_i] * ndarray->strides[dim_i];
return element;
}
/**
* @brief Return the pointer to the nth (0-based) element of `ndarray` in flattened view.
*
* This function does no bound check.
*/
template<typename SizeT>
void* get_nth_pelement(const NDArray<SizeT>* ndarray, SizeT nth) {
void* element = ndarray->data;
for (SizeT i = 0; i < ndarray->ndims; i++) {
SizeT axis = ndarray->ndims - i - 1;
SizeT dim = ndarray->shape[axis];
element = static_cast<uint8_t*>(element) + ndarray->strides[axis] * (nth % dim);
nth /= dim;
}
return element;
}
/**
* @brief Update the strides of an ndarray given an ndarray `shape` to be contiguous.
*
* You might want to read https://ajcr.net/stride-guide-part-1/.
*/
template<typename SizeT>
void set_strides_by_shape(NDArray<SizeT>* ndarray) {
SizeT stride_product = 1;
for (SizeT i = 0; i < ndarray->ndims; i++) {
SizeT axis = ndarray->ndims - i - 1;
ndarray->strides[axis] = stride_product * ndarray->itemsize;
stride_product *= ndarray->shape[axis];
}
}
/**
* @brief Set an element in `ndarray`.
*
* @param pelement Pointer to the element in `ndarray` to be set.
* @param pvalue Pointer to the value `pelement` will be set to.
*/
template<typename SizeT>
void set_pelement_value(NDArray<SizeT>* ndarray, void* pelement, const void* pvalue) {
__builtin_memcpy(pelement, pvalue, ndarray->itemsize);
}
/**
* @brief Copy data from one ndarray to another of the exact same size and itemsize.
*
* Both ndarrays will be viewed in their flatten views when copying the elements.
*/
template<typename SizeT>
void copy_data(const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
// TODO: Make this faster with memcpy when we see a contiguous segment.
// TODO: Handle overlapping.
debug_assert_eq(SizeT, src_ndarray->itemsize, dst_ndarray->itemsize);
for (SizeT i = 0; i < size(src_ndarray); i++) {
auto src_element = ndarray::basic::get_nth_pelement(src_ndarray, i);
auto dst_element = ndarray::basic::get_nth_pelement(dst_ndarray, i);
ndarray::basic::set_pelement_value(dst_ndarray, dst_element, src_element);
}
}
} // namespace ndarray::basic
} // namespace
extern "C" {
using namespace ndarray::basic;
void __nac3_ndarray_util_assert_shape_no_negative(int32_t ndims, int32_t* shape) {
assert_shape_no_negative(ndims, shape);
}
void __nac3_ndarray_util_assert_shape_no_negative64(int64_t ndims, int64_t* shape) {
assert_shape_no_negative(ndims, shape);
}
void __nac3_ndarray_util_assert_output_shape_same(int32_t ndarray_ndims,
const int32_t* ndarray_shape,
int32_t output_ndims,
const int32_t* output_shape) {
assert_output_shape_same(ndarray_ndims, ndarray_shape, output_ndims, output_shape);
}
void __nac3_ndarray_util_assert_output_shape_same64(int64_t ndarray_ndims,
const int64_t* ndarray_shape,
int64_t output_ndims,
const int64_t* output_shape) {
assert_output_shape_same(ndarray_ndims, ndarray_shape, output_ndims, output_shape);
}
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);
}
int32_t __nac3_ndarray_len(NDArray<int32_t>* ndarray) {
return len(ndarray);
}
int64_t __nac3_ndarray_len64(NDArray<int64_t>* ndarray) {
return len(ndarray);
}
bool __nac3_ndarray_is_c_contiguous(NDArray<int32_t>* ndarray) {
return is_c_contiguous(ndarray);
}
bool __nac3_ndarray_is_c_contiguous64(NDArray<int64_t>* ndarray) {
return is_c_contiguous(ndarray);
}
void* __nac3_ndarray_get_nth_pelement(const NDArray<int32_t>* ndarray, int32_t nth) {
return get_nth_pelement(ndarray, nth);
}
void* __nac3_ndarray_get_nth_pelement64(const NDArray<int64_t>* ndarray, int64_t nth) {
return get_nth_pelement(ndarray, nth);
}
void* __nac3_ndarray_get_pelement_by_indices(const NDArray<int32_t>* ndarray, int32_t* indices) {
return get_pelement_by_indices(ndarray, indices);
}
void* __nac3_ndarray_get_pelement_by_indices64(const NDArray<int64_t>* ndarray, int64_t* indices) {
return get_pelement_by_indices(ndarray, indices);
}
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);
}
void __nac3_ndarray_copy_data(NDArray<int32_t>* src_ndarray, NDArray<int32_t>* dst_ndarray) {
copy_data(src_ndarray, dst_ndarray);
}
void __nac3_ndarray_copy_data64(NDArray<int64_t>* src_ndarray, NDArray<int64_t>* dst_ndarray) {
copy_data(src_ndarray, dst_ndarray);
}
}

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#pragma once
#include "irrt/int_types.hpp"
#include "irrt/ndarray/def.hpp"
#include "irrt/slice.hpp"
namespace {
template<typename SizeT>
struct ShapeEntry {
SizeT ndims;
SizeT* shape;
};
} // namespace
namespace {
namespace ndarray::broadcast {
/**
* @brief Return true if `src_shape` can broadcast to `dst_shape`.
*
* See https://numpy.org/doc/stable/user/basics.broadcasting.html
*/
template<typename SizeT>
bool can_broadcast_shape_to(SizeT target_ndims, const SizeT* target_shape, SizeT src_ndims, const SizeT* src_shape) {
if (src_ndims > target_ndims) {
return false;
}
for (SizeT i = 0; i < src_ndims; i++) {
SizeT target_dim = target_shape[target_ndims - i - 1];
SizeT src_dim = src_shape[src_ndims - i - 1];
if (!(src_dim == 1 || target_dim == src_dim)) {
return false;
}
}
return true;
}
/**
* @brief Performs `np.broadcast_shapes(<shapes>)`
*
* @param num_shapes Number of entries in `shapes`
* @param shapes The list of shape to do `np.broadcast_shapes` on.
* @param dst_ndims The length of `dst_shape`.
* `dst_ndims` must be `max([shape.ndims for shape in shapes])`, but the caller has to calculate it/provide it.
* for this function since they should already know in order to allocate `dst_shape` in the first place.
* @param dst_shape The resulting shape. Must be pre-allocated by the caller. This function calculate the result
* of `np.broadcast_shapes` and write it here.
*/
template<typename SizeT>
void broadcast_shapes(SizeT num_shapes, const ShapeEntry<SizeT>* shapes, SizeT dst_ndims, SizeT* dst_shape) {
for (SizeT dst_axis = 0; dst_axis < dst_ndims; dst_axis++) {
dst_shape[dst_axis] = 1;
}
#ifdef IRRT_DEBUG_ASSERT
SizeT max_ndims_found = 0;
#endif
for (SizeT i = 0; i < num_shapes; i++) {
ShapeEntry<SizeT> entry = shapes[i];
// Check pre-condition: `dst_ndims` must be `max([shape.ndims for shape in shapes])`
debug_assert(SizeT, entry.ndims <= dst_ndims);
#ifdef IRRT_DEBUG_ASSERT
max_ndims_found = max(max_ndims_found, entry.ndims);
#endif
for (SizeT j = 0; j < entry.ndims; j++) {
SizeT entry_axis = entry.ndims - j - 1;
SizeT dst_axis = dst_ndims - j - 1;
SizeT entry_dim = entry.shape[entry_axis];
SizeT dst_dim = dst_shape[dst_axis];
if (dst_dim == 1) {
dst_shape[dst_axis] = entry_dim;
} else if (entry_dim == 1 || entry_dim == dst_dim) {
// Do nothing
} else {
raise_exception(SizeT, EXN_VALUE_ERROR,
"shape mismatch: objects cannot be broadcast "
"to a single shape.",
NO_PARAM, NO_PARAM, NO_PARAM);
}
}
}
#ifdef IRRT_DEBUG_ASSERT
// Check pre-condition: `dst_ndims` must be `max([shape.ndims for shape in shapes])`
debug_assert_eq(SizeT, max_ndims_found, dst_ndims);
#endif
}
/**
* @brief Perform `np.broadcast_to(<ndarray>, <target_shape>)` and appropriate assertions.
*
* This function attempts to broadcast `src_ndarray` to a new shape defined by `dst_ndarray.shape`,
* and return the result by modifying `dst_ndarray`.
*
* # Notes on `dst_ndarray`
* The caller is responsible for allocating space for the resulting ndarray.
* Here is what this function expects from `dst_ndarray` when called:
* - `dst_ndarray->data` does not have to be initialized.
* - `dst_ndarray->itemsize` does not have to be initialized.
* - `dst_ndarray->ndims` must be initialized, determining the length of `dst_ndarray->shape`
* - `dst_ndarray->shape` must be allocated, and must contain the desired target broadcast shape.
* - `dst_ndarray->strides` must be allocated, through it can contain uninitialized values.
* When this function call ends:
* - `dst_ndarray->data` is set to `src_ndarray->data` (`dst_ndarray` is just a view to `src_ndarray`)
* - `dst_ndarray->itemsize` is set to `src_ndarray->itemsize`
* - `dst_ndarray->ndims` is unchanged.
* - `dst_ndarray->shape` is unchanged.
* - `dst_ndarray->strides` is updated accordingly by how ndarray broadcast_to works.
*/
template<typename SizeT>
void broadcast_to(const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
if (!ndarray::broadcast::can_broadcast_shape_to(dst_ndarray->ndims, dst_ndarray->shape, src_ndarray->ndims,
src_ndarray->shape)) {
raise_exception(SizeT, EXN_VALUE_ERROR, "operands could not be broadcast together", NO_PARAM, NO_PARAM,
NO_PARAM);
}
dst_ndarray->data = src_ndarray->data;
dst_ndarray->itemsize = src_ndarray->itemsize;
for (SizeT i = 0; i < dst_ndarray->ndims; i++) {
SizeT src_axis = src_ndarray->ndims - i - 1;
SizeT dst_axis = dst_ndarray->ndims - i - 1;
if (src_axis < 0 || (src_ndarray->shape[src_axis] == 1 && dst_ndarray->shape[dst_axis] != 1)) {
// Freeze the steps in-place
dst_ndarray->strides[dst_axis] = 0;
} else {
dst_ndarray->strides[dst_axis] = src_ndarray->strides[src_axis];
}
}
}
} // namespace ndarray::broadcast
} // namespace
extern "C" {
using namespace ndarray::broadcast;
void __nac3_ndarray_broadcast_to(NDArray<int32_t>* src_ndarray, NDArray<int32_t>* dst_ndarray) {
broadcast_to(src_ndarray, dst_ndarray);
}
void __nac3_ndarray_broadcast_to64(NDArray<int64_t>* src_ndarray, NDArray<int64_t>* dst_ndarray) {
broadcast_to(src_ndarray, dst_ndarray);
}
void __nac3_ndarray_broadcast_shapes(int32_t num_shapes,
const ShapeEntry<int32_t>* shapes,
int32_t dst_ndims,
int32_t* dst_shape) {
broadcast_shapes(num_shapes, shapes, dst_ndims, dst_shape);
}
void __nac3_ndarray_broadcast_shapes64(int64_t num_shapes,
const ShapeEntry<int64_t>* shapes,
int64_t dst_ndims,
int64_t* dst_shape) {
broadcast_shapes(num_shapes, shapes, dst_ndims, dst_shape);
}
}

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@ -1,51 +0,0 @@
#pragma once
#include "irrt/int_types.hpp"
namespace {
/**
* @brief The NDArray object
*
* Official numpy implementation:
* https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst#pyarrayinterface
*
* Note that this implementation is based on `PyArrayInterface` rather of `PyArrayObject`. The
* difference between `PyArrayInterface` and `PyArrayObject` (relevant to our implementation) is
* that `PyArrayInterface` *has* `itemsize` and uses `void*` for its `data`, whereas `PyArrayObject`
* does not require `itemsize` (probably using `strides[-1]` instead) and uses `char*` for its
* `data`. There are also minor differences in the struct layout.
*/
template<typename SizeT>
struct NDArray {
/**
* @brief The number of bytes of a single element in `data`.
*/
SizeT itemsize;
/**
* @brief The number of dimensions of this shape.
*/
SizeT ndims;
/**
* @brief The NDArray shape, with length equal to `ndims`.
*
* Note that it may contain 0.
*/
SizeT* shape;
/**
* @brief Array strides, with length equal to `ndims`
*
* The stride values are in units of bytes, not number of elements.
*
* Note that `strides` can have negative values or contain 0.
*/
SizeT* strides;
/**
* @brief The underlying data this `ndarray` is pointing to.
*/
void* data;
};
} // namespace

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#pragma once
#include "irrt/exception.hpp"
#include "irrt/int_types.hpp"
#include "irrt/ndarray/basic.hpp"
#include "irrt/ndarray/def.hpp"
#include "irrt/range.hpp"
#include "irrt/slice.hpp"
namespace {
typedef uint8_t NDIndexType;
/**
* @brief A single element index
*
* `data` points to a `int32_t`.
*/
const NDIndexType ND_INDEX_TYPE_SINGLE_ELEMENT = 0;
/**
* @brief A slice index
*
* `data` points to a `Slice<int32_t>`.
*/
const NDIndexType ND_INDEX_TYPE_SLICE = 1;
/**
* @brief `np.newaxis` / `None`
*
* `data` is unused.
*/
const NDIndexType ND_INDEX_TYPE_NEWAXIS = 2;
/**
* @brief `Ellipsis` / `...`
*
* `data` is unused.
*/
const NDIndexType ND_INDEX_TYPE_ELLIPSIS = 3;
/**
* @brief An index used in ndarray indexing
*
* That is:
* ```
* my_ndarray[::-1, 3, ..., np.newaxis]
* ^^^^ ^ ^^^ ^^^^^^^^^^ each of these is represented by an NDIndex.
* ```
*/
struct NDIndex {
/**
* @brief Enum tag to specify the type of index.
*
* Please see the comment of each enum constant.
*/
NDIndexType type;
/**
* @brief The accompanying data associated with `type`.
*
* Please see the comment of each enum constant.
*/
uint8_t* data;
};
} // namespace
namespace {
namespace ndarray::indexing {
/**
* @brief Perform ndarray "basic indexing" (https://numpy.org/doc/stable/user/basics.indexing.html#basic-indexing)
*
* This function is very similar to performing `dst_ndarray = src_ndarray[indices]` in Python.
*
* This function also does proper assertions on `indices` to check for out of bounds access and more.
*
* # Notes on `dst_ndarray`
* The caller is responsible for allocating space for the resulting ndarray.
* Here is what this function expects from `dst_ndarray` when called:
* - `dst_ndarray->data` does not have to be initialized.
* - `dst_ndarray->itemsize` does not have to be initialized.
* - `dst_ndarray->ndims` must be initialized, and it must be equal to the expected `ndims` of the `dst_ndarray` after
* indexing `src_ndarray` with `indices`.
* - `dst_ndarray->shape` must be allocated, through it can contain uninitialized values.
* - `dst_ndarray->strides` must be allocated, through it can contain uninitialized values.
* When this function call ends:
* - `dst_ndarray->data` is set to `src_ndarray->data`.
* - `dst_ndarray->itemsize` is set to `src_ndarray->itemsize`.
* - `dst_ndarray->ndims` is unchanged.
* - `dst_ndarray->shape` is updated according to how `src_ndarray` is indexed.
* - `dst_ndarray->strides` is updated accordingly by how ndarray indexing works.
*
* @param indices indices to index `src_ndarray`, ordered in the same way you would write them in Python.
* @param src_ndarray The NDArray to be indexed.
* @param dst_ndarray The resulting NDArray after indexing. Further details in the comments above,
*/
template<typename SizeT>
void index(SizeT num_indices, const NDIndex* indices, const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
// Validate `indices`.
// Expected value of `dst_ndarray->ndims`.
SizeT expected_dst_ndims = src_ndarray->ndims;
// To check for "too many indices for array: array is ?-dimensional, but ? were indexed"
SizeT num_indexed = 0;
// There may be ellipsis `...` in `indices`. There can only be 0 or 1 ellipsis.
SizeT num_ellipsis = 0;
for (SizeT i = 0; i < num_indices; i++) {
if (indices[i].type == ND_INDEX_TYPE_SINGLE_ELEMENT) {
expected_dst_ndims--;
num_indexed++;
} else if (indices[i].type == ND_INDEX_TYPE_SLICE) {
num_indexed++;
} else if (indices[i].type == ND_INDEX_TYPE_NEWAXIS) {
expected_dst_ndims++;
} else if (indices[i].type == ND_INDEX_TYPE_ELLIPSIS) {
num_ellipsis++;
if (num_ellipsis > 1) {
raise_exception(SizeT, EXN_INDEX_ERROR, "an index can only have a single ellipsis ('...')", NO_PARAM,
NO_PARAM, NO_PARAM);
}
} else {
__builtin_unreachable();
}
}
debug_assert_eq(SizeT, expected_dst_ndims, dst_ndarray->ndims);
if (src_ndarray->ndims - num_indexed < 0) {
raise_exception(SizeT, EXN_INDEX_ERROR,
"too many indices for array: array is {0}-dimensional, "
"but {1} were indexed",
src_ndarray->ndims, num_indices, NO_PARAM);
}
dst_ndarray->data = src_ndarray->data;
dst_ndarray->itemsize = src_ndarray->itemsize;
// Reference code:
// https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L652
SizeT src_axis = 0;
SizeT dst_axis = 0;
for (int32_t i = 0; i < num_indices; i++) {
const NDIndex* index = &indices[i];
if (index->type == ND_INDEX_TYPE_SINGLE_ELEMENT) {
SizeT input = (SizeT) * ((int32_t*)index->data);
SizeT k = slice::resolve_index_in_length(src_ndarray->shape[src_axis], input);
if (k == -1) {
raise_exception(SizeT, EXN_INDEX_ERROR,
"index {0} is out of bounds for axis {1} "
"with size {2}",
input, src_axis, src_ndarray->shape[src_axis]);
}
dst_ndarray->data = static_cast<uint8_t*>(dst_ndarray->data) + k * src_ndarray->strides[src_axis];
src_axis++;
} else if (index->type == ND_INDEX_TYPE_SLICE) {
Slice<int32_t>* slice = (Slice<int32_t>*)index->data;
Range<int32_t> range = slice->indices_checked<SizeT>(src_ndarray->shape[src_axis]);
dst_ndarray->data =
static_cast<uint8_t*>(dst_ndarray->data) + (SizeT)range.start * src_ndarray->strides[src_axis];
dst_ndarray->strides[dst_axis] = ((SizeT)range.step) * src_ndarray->strides[src_axis];
dst_ndarray->shape[dst_axis] = (SizeT)range.len<SizeT>();
dst_axis++;
src_axis++;
} else if (index->type == ND_INDEX_TYPE_NEWAXIS) {
dst_ndarray->strides[dst_axis] = 0;
dst_ndarray->shape[dst_axis] = 1;
dst_axis++;
} else if (index->type == ND_INDEX_TYPE_ELLIPSIS) {
// The number of ':' entries this '...' implies.
SizeT ellipsis_size = src_ndarray->ndims - num_indexed;
for (SizeT j = 0; j < ellipsis_size; j++) {
dst_ndarray->strides[dst_axis] = src_ndarray->strides[src_axis];
dst_ndarray->shape[dst_axis] = src_ndarray->shape[src_axis];
dst_axis++;
src_axis++;
}
} else {
__builtin_unreachable();
}
}
for (; dst_axis < dst_ndarray->ndims; dst_axis++, src_axis++) {
dst_ndarray->shape[dst_axis] = src_ndarray->shape[src_axis];
dst_ndarray->strides[dst_axis] = src_ndarray->strides[src_axis];
}
debug_assert_eq(SizeT, src_ndarray->ndims, src_axis);
debug_assert_eq(SizeT, dst_ndarray->ndims, dst_axis);
}
} // namespace ndarray::indexing
} // namespace
extern "C" {
using namespace ndarray::indexing;
void __nac3_ndarray_index(int32_t num_indices,
NDIndex* indices,
NDArray<int32_t>* src_ndarray,
NDArray<int32_t>* dst_ndarray) {
index(num_indices, indices, src_ndarray, dst_ndarray);
}
void __nac3_ndarray_index64(int64_t num_indices,
NDIndex* indices,
NDArray<int64_t>* src_ndarray,
NDArray<int64_t>* dst_ndarray) {
index(num_indices, indices, src_ndarray, dst_ndarray);
}
}

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#pragma once
#include "irrt/int_types.hpp"
#include "irrt/ndarray/def.hpp"
namespace {
/**
* @brief Helper struct to enumerate through an ndarray *efficiently*.
*
* Example usage (in pseudo-code):
* ```
* // Suppose my_ndarray has been initialized, with shape [2, 3] and dtype `double`
* NDIter nditer;
* nditer.initialize(my_ndarray);
* while (nditer.has_element()) {
* // This body is run 6 (= my_ndarray.size) times.
*
* // [0, 0] -> [0, 1] -> [0, 2] -> [1, 0] -> [1, 1] -> [1, 2] -> end
* print(nditer.indices);
*
* // 0 -> 1 -> 2 -> 3 -> 4 -> 5
* print(nditer.nth);
*
* // <1st element> -> <2nd element> -> ... -> <6th element> -> end
* print(*((double *) nditer.element))
*
* nditer.next(); // Go to next element.
* }
* ```
*
* Interesting cases:
* - If `my_ndarray.ndims` == 0, there is one iteration.
* - If `my_ndarray.shape` contains zeroes, there are no iterations.
*/
template<typename SizeT>
struct NDIter {
// Information about the ndarray being iterated over.
SizeT ndims;
SizeT* shape;
SizeT* strides;
/**
* @brief The current indices.
*
* Must be allocated by the caller.
*/
SizeT* indices;
/**
* @brief The nth (0-based) index of the current indices.
*
* Initially this is 0.
*/
SizeT nth;
/**
* @brief Pointer to the current element.
*
* Initially this points to first element of the ndarray.
*/
void* element;
/**
* @brief Cache for the product of shape.
*
* Could be 0 if `shape` has 0s in it.
*/
SizeT size;
void initialize(SizeT ndims, SizeT* shape, SizeT* strides, void* element, SizeT* indices) {
this->ndims = ndims;
this->shape = shape;
this->strides = strides;
this->indices = indices;
this->element = element;
// Compute size
this->size = 1;
for (SizeT i = 0; i < ndims; i++) {
this->size *= shape[i];
}
// `indices` starts on all 0s.
for (SizeT axis = 0; axis < ndims; axis++)
indices[axis] = 0;
nth = 0;
}
void initialize_by_ndarray(NDArray<SizeT>* ndarray, SizeT* indices) {
// NOTE: ndarray->data is pointing to the first element, and `NDIter`'s `element` should also point to the first
// element as well.
this->initialize(ndarray->ndims, ndarray->shape, ndarray->strides, ndarray->data, indices);
}
// Is the current iteration valid?
// If true, then `element`, `indices` and `nth` contain details about the current element.
bool has_element() { return nth < size; }
// Go to the next element.
void next() {
for (SizeT i = 0; i < ndims; i++) {
SizeT axis = ndims - i - 1;
indices[axis]++;
if (indices[axis] >= shape[axis]) {
indices[axis] = 0;
// TODO: There is something called backstrides to speedup iteration.
// See https://ajcr.net/stride-guide-part-1/, and
// https://docs.scipy.org/doc/numpy-1.13.0/reference/c-api.types-and-structures.html#c.PyArrayIterObject.PyArrayIterObject.backstrides.
element = static_cast<void*>(reinterpret_cast<uint8_t*>(element) - strides[axis] * (shape[axis] - 1));
} else {
element = static_cast<void*>(reinterpret_cast<uint8_t*>(element) + strides[axis]);
break;
}
}
nth++;
}
};
} // namespace
extern "C" {
void __nac3_nditer_initialize(NDIter<int32_t>* iter, NDArray<int32_t>* ndarray, int32_t* indices) {
iter->initialize_by_ndarray(ndarray, indices);
}
void __nac3_nditer_initialize64(NDIter<int64_t>* iter, NDArray<int64_t>* ndarray, int64_t* indices) {
iter->initialize_by_ndarray(ndarray, indices);
}
bool __nac3_nditer_has_element(NDIter<int32_t>* iter) {
return iter->has_element();
}
bool __nac3_nditer_has_element64(NDIter<int64_t>* iter) {
return iter->has_element();
}
void __nac3_nditer_next(NDIter<int32_t>* iter) {
iter->next();
}
void __nac3_nditer_next64(NDIter<int64_t>* iter) {
iter->next();
}
}

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#pragma once
#include "irrt/debug.hpp"
#include "irrt/exception.hpp"
#include "irrt/int_types.hpp"
#include "irrt/ndarray/basic.hpp"
#include "irrt/ndarray/broadcast.hpp"
#include "irrt/ndarray/iter.hpp"
// NOTE: Everything would be much easier and elegant if einsum is implemented.
namespace {
namespace ndarray::matmul {
/**
* @brief Perform the broadcast in `np.einsum("...ij,...jk->...ik", a, b)`.
*
* Example:
* Suppose `a_shape == [1, 97, 4, 2]`
* and `b_shape == [99, 98, 1, 2, 5]`,
*
* ...then `new_a_shape == [99, 98, 97, 4, 2]`,
* `new_b_shape == [99, 98, 97, 2, 5]`,
* and `dst_shape == [99, 98, 97, 4, 5]`.
* ^^^^^^^^^^ ^^^^
* (broadcasted) (4x2 @ 2x5 => 4x5)
*
* @param a_ndims Length of `a_shape`.
* @param a_shape Shape of `a`.
* @param b_ndims Length of `b_shape`.
* @param b_shape Shape of `b`.
* @param final_ndims Should be equal to `max(a_ndims, b_ndims)`. This is the length of `new_a_shape`,
* `new_b_shape`, and `dst_shape` - the number of dimensions after broadcasting.
*/
template<typename SizeT>
void calculate_shapes(SizeT a_ndims,
SizeT* a_shape,
SizeT b_ndims,
SizeT* b_shape,
SizeT final_ndims,
SizeT* new_a_shape,
SizeT* new_b_shape,
SizeT* dst_shape) {
debug_assert(SizeT, a_ndims >= 2);
debug_assert(SizeT, b_ndims >= 2);
debug_assert_eq(SizeT, max(a_ndims, b_ndims), final_ndims);
// Check that a and b are compatible for matmul
if (a_shape[a_ndims - 1] != b_shape[b_ndims - 2]) {
// This is a custom error message. Different from NumPy.
raise_exception(SizeT, EXN_VALUE_ERROR, "Cannot multiply LHS (shape ?x{0}) with RHS (shape {1}x?})",
a_shape[a_ndims - 1], b_shape[b_ndims - 2], NO_PARAM);
}
const SizeT num_entries = 2;
ShapeEntry<SizeT> entries[num_entries] = {{.ndims = a_ndims - 2, .shape = a_shape},
{.ndims = b_ndims - 2, .shape = b_shape}};
// TODO: Optimize this
ndarray::broadcast::broadcast_shapes<SizeT>(num_entries, entries, final_ndims - 2, new_a_shape);
ndarray::broadcast::broadcast_shapes<SizeT>(num_entries, entries, final_ndims - 2, new_b_shape);
ndarray::broadcast::broadcast_shapes<SizeT>(num_entries, entries, final_ndims - 2, dst_shape);
new_a_shape[final_ndims - 2] = a_shape[a_ndims - 2];
new_a_shape[final_ndims - 1] = a_shape[a_ndims - 1];
new_b_shape[final_ndims - 2] = b_shape[b_ndims - 2];
new_b_shape[final_ndims - 1] = b_shape[b_ndims - 1];
dst_shape[final_ndims - 2] = a_shape[a_ndims - 2];
dst_shape[final_ndims - 1] = b_shape[b_ndims - 1];
}
} // namespace ndarray::matmul
} // namespace
extern "C" {
using namespace ndarray::matmul;
void __nac3_ndarray_matmul_calculate_shapes(int32_t a_ndims,
int32_t* a_shape,
int32_t b_ndims,
int32_t* b_shape,
int32_t final_ndims,
int32_t* new_a_shape,
int32_t* new_b_shape,
int32_t* dst_shape) {
calculate_shapes(a_ndims, a_shape, b_ndims, b_shape, final_ndims, new_a_shape, new_b_shape, dst_shape);
}
void __nac3_ndarray_matmul_calculate_shapes64(int64_t a_ndims,
int64_t* a_shape,
int64_t b_ndims,
int64_t* b_shape,
int64_t final_ndims,
int64_t* new_a_shape,
int64_t* new_b_shape,
int64_t* dst_shape) {
calculate_shapes(a_ndims, a_shape, b_ndims, b_shape, final_ndims, new_a_shape, new_b_shape, dst_shape);
}
}

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#pragma once
#include "irrt/exception.hpp"
#include "irrt/int_types.hpp"
#include "irrt/ndarray/def.hpp"
namespace {
namespace ndarray::reshape {
/**
* @brief Perform assertions on and resolve unknown dimensions in `new_shape` in `np.reshape(<ndarray>, new_shape)`
*
* If `new_shape` indeed contains unknown dimensions (specified with `-1`, just like numpy), `new_shape` will be
* modified to contain the resolved dimension.
*
* To perform assertions on and resolve unknown dimensions in `new_shape`, we don't need the actual
* `<ndarray>` object itself, but only the `.size` of the `<ndarray>`.
*
* @param size The `.size` of `<ndarray>`
* @param new_ndims Number of elements in `new_shape`
* @param new_shape Target shape to reshape to
*/
template<typename SizeT>
void resolve_and_check_new_shape(SizeT size, SizeT new_ndims, SizeT* new_shape) {
// Is there a -1 in `new_shape`?
bool neg1_exists = false;
// Location of -1, only initialized if `neg1_exists` is true
SizeT neg1_axis_i;
// The computed ndarray size of `new_shape`
SizeT new_size = 1;
for (SizeT axis_i = 0; axis_i < new_ndims; axis_i++) {
SizeT dim = new_shape[axis_i];
if (dim < 0) {
if (dim == -1) {
if (neg1_exists) {
// Multiple `-1` found. Throw an error.
raise_exception(SizeT, EXN_VALUE_ERROR, "can only specify one unknown dimension", NO_PARAM,
NO_PARAM, NO_PARAM);
} else {
neg1_exists = true;
neg1_axis_i = axis_i;
}
} else {
// TODO: What? In `np.reshape` any negative dimensions is
// treated like its `-1`.
//
// Try running `np.zeros((3, 4)).reshape((-999, 2))`
//
// It is not documented by numpy.
// Throw an error for now...
raise_exception(SizeT, EXN_VALUE_ERROR, "Found non -1 negative dimension {0} on axis {1}", dim, axis_i,
NO_PARAM);
}
} else {
new_size *= dim;
}
}
bool can_reshape;
if (neg1_exists) {
// Let `x` be the unknown dimension
// Solve `x * <new_size> = <size>`
if (new_size == 0 && size == 0) {
// `x` has infinitely many solutions
can_reshape = false;
} else if (new_size == 0 && size != 0) {
// `x` has no solutions
can_reshape = false;
} else if (size % new_size != 0) {
// `x` has no integer solutions
can_reshape = false;
} else {
can_reshape = true;
new_shape[neg1_axis_i] = size / new_size; // Resolve dimension
}
} else {
can_reshape = (new_size == size);
}
if (!can_reshape) {
raise_exception(SizeT, EXN_VALUE_ERROR, "cannot reshape array of size {0} into given shape", size, NO_PARAM,
NO_PARAM);
}
}
} // namespace ndarray::reshape
} // namespace
extern "C" {
void __nac3_ndarray_reshape_resolve_and_check_new_shape(int32_t size, int32_t new_ndims, int32_t* new_shape) {
ndarray::reshape::resolve_and_check_new_shape(size, new_ndims, new_shape);
}
void __nac3_ndarray_reshape_resolve_and_check_new_shape64(int64_t size, int64_t new_ndims, int64_t* new_shape) {
ndarray::reshape::resolve_and_check_new_shape(size, new_ndims, new_shape);
}
}

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#pragma once
#include "irrt/debug.hpp"
#include "irrt/exception.hpp"
#include "irrt/int_types.hpp"
#include "irrt/ndarray/def.hpp"
#include "irrt/slice.hpp"
/*
* Notes on `np.transpose(<array>, <axes>)`
*
* TODO: `axes`, if specified, can actually contain negative indices,
* but it is not documented in numpy.
*
* Supporting it for now.
*/
namespace {
namespace ndarray::transpose {
/**
* @brief Do assertions on `<axes>` in `np.transpose(<array>, <axes>)`.
*
* Note that `np.transpose`'s `<axe>` argument is optional. If the argument
* is specified but the user, use this function to do assertions on it.
*
* @param ndims The number of dimensions of `<array>`
* @param num_axes Number of elements in `<axes>` as specified by the user.
* This should be equal to `ndims`. If not, a "ValueError: axes don't match array" is thrown.
* @param axes The user specified `<axes>`.
*/
template<typename SizeT>
void assert_transpose_axes(SizeT ndims, SizeT num_axes, const SizeT* axes) {
if (ndims != num_axes) {
raise_exception(SizeT, EXN_VALUE_ERROR, "axes don't match array", NO_PARAM, NO_PARAM, NO_PARAM);
}
// TODO: Optimize this
bool* axe_specified = (bool*)__builtin_alloca(sizeof(bool) * ndims);
for (SizeT i = 0; i < ndims; i++)
axe_specified[i] = false;
for (SizeT i = 0; i < ndims; i++) {
SizeT axis = slice::resolve_index_in_length(ndims, axes[i]);
if (axis == -1) {
// TODO: numpy actually throws a `numpy.exceptions.AxisError`
raise_exception(SizeT, EXN_VALUE_ERROR, "axis {0} is out of bounds for array of dimension {1}", axis, ndims,
NO_PARAM);
}
if (axe_specified[axis]) {
raise_exception(SizeT, EXN_VALUE_ERROR, "repeated axis in transpose", NO_PARAM, NO_PARAM, NO_PARAM);
}
axe_specified[axis] = true;
}
}
/**
* @brief Create a transpose view of `src_ndarray` and perform proper assertions.
*
* This function is very similar to doing `dst_ndarray = np.transpose(src_ndarray, <axes>)`.
* If `<axes>` is supposed to be `None`, caller can pass in a `nullptr` to `<axes>`.
*
* The transpose view created is returned by modifying `dst_ndarray`.
*
* The caller is responsible for setting up `dst_ndarray` before calling this function.
* Here is what this function expects from `dst_ndarray` when called:
* - `dst_ndarray->data` does not have to be initialized.
* - `dst_ndarray->itemsize` does not have to be initialized.
* - `dst_ndarray->ndims` must be initialized, must be equal to `src_ndarray->ndims`.
* - `dst_ndarray->shape` must be allocated, through it can contain uninitialized values.
* - `dst_ndarray->strides` must be allocated, through it can contain uninitialized values.
* When this function call ends:
* - `dst_ndarray->data` is set to `src_ndarray->data` (`dst_ndarray` is just a view to `src_ndarray`)
* - `dst_ndarray->itemsize` is set to `src_ndarray->itemsize`
* - `dst_ndarray->ndims` is unchanged
* - `dst_ndarray->shape` is updated according to how `np.transpose` works
* - `dst_ndarray->strides` is updated according to how `np.transpose` works
*
* @param src_ndarray The NDArray to build a transpose view on
* @param dst_ndarray The resulting NDArray after transpose. Further details in the comments above,
* @param num_axes Number of elements in axes. Unused if `axes` is nullptr.
* @param axes Axes permutation. Set it to `nullptr` if `<axes>` is `None`.
*/
template<typename SizeT>
void transpose(const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray, SizeT num_axes, const SizeT* axes) {
debug_assert_eq(SizeT, src_ndarray->ndims, dst_ndarray->ndims);
const auto ndims = src_ndarray->ndims;
if (axes != nullptr)
assert_transpose_axes(ndims, num_axes, axes);
dst_ndarray->data = src_ndarray->data;
dst_ndarray->itemsize = src_ndarray->itemsize;
// Check out https://ajcr.net/stride-guide-part-2/ to see how `np.transpose` works behind the scenes.
if (axes == nullptr) {
// `np.transpose(<array>, axes=None)`
/*
* Minor note: `np.transpose(<array>, axes=None)` is equivalent to
* `np.transpose(<array>, axes=[N-1, N-2, ..., 0])` - basically it
* is reversing the order of strides and shape.
*
* This is a fast implementation to handle this special (but very common) case.
*/
for (SizeT axis = 0; axis < ndims; axis++) {
dst_ndarray->shape[axis] = src_ndarray->shape[ndims - axis - 1];
dst_ndarray->strides[axis] = src_ndarray->strides[ndims - axis - 1];
}
} else {
// `np.transpose(<array>, <axes>)`
// Permute strides and shape according to `axes`, while resolving negative indices in `axes`
for (SizeT axis = 0; axis < ndims; axis++) {
// `i` cannot be OUT_OF_BOUNDS because of assertions
SizeT i = slice::resolve_index_in_length(ndims, axes[axis]);
dst_ndarray->shape[axis] = src_ndarray->shape[i];
dst_ndarray->strides[axis] = src_ndarray->strides[i];
}
}
}
} // namespace ndarray::transpose
} // namespace
extern "C" {
using namespace ndarray::transpose;
void __nac3_ndarray_transpose(const NDArray<int32_t>* src_ndarray,
NDArray<int32_t>* dst_ndarray,
int32_t num_axes,
const int32_t* axes) {
transpose(src_ndarray, dst_ndarray, num_axes, axes);
}
void __nac3_ndarray_transpose64(const NDArray<int64_t>* src_ndarray,
NDArray<int64_t>* dst_ndarray,
int64_t num_axes,
const int64_t* axes) {
transpose(src_ndarray, dst_ndarray, num_axes, axes);
}
}

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#pragma once
#include "irrt/debug.hpp"
#include "irrt/int_types.hpp"
namespace {
namespace range {
template<typename T>
T len(T start, T stop, T step) {
// Reference:
// https://github.com/python/cpython/blob/9dbd12375561a393eaec4b21ee4ac568a407cdb0/Objects/rangeobject.c#L933
if (step > 0 && start < stop)
return 1 + (stop - 1 - start) / step;
else if (step < 0 && start > stop)
return 1 + (start - 1 - stop) / (-step);
else
return 0;
}
} // namespace range
/**
* @brief A Python range.
*/
template<typename T>
struct Range {
T start;
T stop;
T step;
/**
* @brief Calculate the `len()` of this range.
*/
template<typename SizeT>
T len() {
debug_assert(SizeT, step != 0);
return range::len(start, stop, step);
}
};
} // namespace
extern "C" {
using namespace range;
SliceIndex __nac3_range_slice_len(const SliceIndex start, const SliceIndex end, const SliceIndex step) {
return len(start, end, step);
}
}

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#pragma once
#include "irrt/debug.hpp"
#include "irrt/exception.hpp"
#include "irrt/int_types.hpp"
#include "irrt/math_util.hpp"
#include "irrt/range.hpp"
namespace {
namespace slice {
/**
* @brief Resolve a possibly negative index in a list of a known length.
*
* Returns -1 if the resolved index is out of the list's bounds.
*/
template<typename T>
T resolve_index_in_length(T length, T index) {
T resolved = index < 0 ? length + index : index;
if (0 <= resolved && resolved < length) {
return resolved;
} else {
return -1;
}
}
/**
* @brief Resolve a slice as a range.
*
* This is equivalent to `range(*slice(start, stop, step).indices(length))` in Python.
*/
template<typename T>
void indices(bool start_defined,
T start,
bool stop_defined,
T stop,
bool step_defined,
T step,
T length,
T* range_start,
T* range_stop,
T* range_step) {
// Reference: https://github.com/python/cpython/blob/main/Objects/sliceobject.c#L388
*range_step = step_defined ? step : 1;
bool step_is_negative = *range_step < 0;
T lower, upper;
if (step_is_negative) {
lower = -1;
upper = length - 1;
} else {
lower = 0;
upper = length;
}
if (start_defined) {
*range_start = start < 0 ? max(lower, start + length) : min(upper, start);
} else {
*range_start = step_is_negative ? upper : lower;
}
if (stop_defined) {
*range_stop = stop < 0 ? max(lower, stop + length) : min(upper, stop);
} else {
*range_stop = step_is_negative ? lower : upper;
}
}
} // namespace slice
/**
* @brief A Python-like slice with **unresolved** indices.
*/
template<typename T>
struct Slice {
bool start_defined;
T start;
bool stop_defined;
T stop;
bool step_defined;
T step;
Slice() { this->reset(); }
void reset() {
this->start_defined = false;
this->stop_defined = false;
this->step_defined = false;
}
void set_start(T start) {
this->start_defined = true;
this->start = start;
}
void set_stop(T stop) {
this->stop_defined = true;
this->stop = stop;
}
void set_step(T step) {
this->step_defined = true;
this->step = step;
}
/**
* @brief Resolve this slice as a range.
*
* In Python, this would be `range(*slice(start, stop, step).indices(length))`.
*/
template<typename SizeT>
Range<T> indices(T length) {
// Reference:
// https://github.com/python/cpython/blob/main/Objects/sliceobject.c#L388
debug_assert(SizeT, length >= 0);
Range<T> result;
slice::indices(start_defined, start, stop_defined, stop, step_defined, step, length, &result.start,
&result.stop, &result.step);
return result;
}
/**
* @brief Like `.indices()` but with assertions.
*/
template<typename SizeT>
Range<T> indices_checked(T length) {
// TODO: Switch to `SizeT length`
if (length < 0) {
raise_exception(SizeT, EXN_VALUE_ERROR, "length should not be negative, got {0}", length, NO_PARAM,
NO_PARAM);
}
if (this->step_defined && this->step == 0) {
raise_exception(SizeT, EXN_VALUE_ERROR, "slice step cannot be zero", NO_PARAM, NO_PARAM, NO_PARAM);
}
return this->indices<SizeT>(length);
}
};
} // namespace
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;
}
}

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

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

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

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

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

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

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

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

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

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

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@ -1,325 +0,0 @@
use std::collections::HashMap;
use indexmap::IndexMap;
use nac3parser::ast::StrRef;
use crate::{
symbol_resolver::SymbolValue,
toplevel::DefinitionId,
typecheck::{
type_inferencer::PrimitiveStore,
typedef::{
into_var_map, FunSignature, FuncArg, Type, TypeEnum, TypeVar, TypeVarId, Unifier,
},
},
};
pub struct ConcreteTypeStore {
store: Vec<ConcreteTypeEnum>,
}
#[derive(Copy, Clone, Eq, PartialEq, Hash, Debug)]
pub struct ConcreteType(usize);
#[derive(Clone, Debug)]
pub struct ConcreteFuncArg {
pub name: StrRef,
pub ty: ConcreteType,
pub default_value: Option<SymbolValue>,
pub is_vararg: bool,
}
#[derive(Clone, Debug)]
pub enum Primitive {
Int32,
Int64,
UInt32,
UInt64,
Float,
Bool,
None,
Range,
Str,
Exception,
}
#[derive(Debug)]
pub enum ConcreteTypeEnum {
TPrimitive(Primitive),
TTuple {
ty: Vec<ConcreteType>,
is_vararg_ctx: bool,
},
TObj {
obj_id: DefinitionId,
fields: HashMap<StrRef, (ConcreteType, bool)>,
params: IndexMap<TypeVarId, ConcreteType>,
},
TVirtual {
ty: ConcreteType,
},
TFunc {
args: Vec<ConcreteFuncArg>,
ret: ConcreteType,
vars: HashMap<TypeVarId, ConcreteType>,
},
TLiteral {
values: Vec<SymbolValue>,
},
}
impl ConcreteTypeStore {
#[must_use]
pub fn new() -> ConcreteTypeStore {
ConcreteTypeStore {
store: vec![
ConcreteTypeEnum::TPrimitive(Primitive::Int32),
ConcreteTypeEnum::TPrimitive(Primitive::Int64),
ConcreteTypeEnum::TPrimitive(Primitive::Float),
ConcreteTypeEnum::TPrimitive(Primitive::Bool),
ConcreteTypeEnum::TPrimitive(Primitive::None),
ConcreteTypeEnum::TPrimitive(Primitive::Range),
ConcreteTypeEnum::TPrimitive(Primitive::Str),
ConcreteTypeEnum::TPrimitive(Primitive::Exception),
ConcreteTypeEnum::TPrimitive(Primitive::UInt32),
ConcreteTypeEnum::TPrimitive(Primitive::UInt64),
],
}
}
#[must_use]
pub fn get(&self, cty: ConcreteType) -> &ConcreteTypeEnum {
&self.store[cty.0]
}
pub fn from_signature(
&mut self,
unifier: &mut Unifier,
primitives: &PrimitiveStore,
signature: &FunSignature,
cache: &mut HashMap<Type, Option<ConcreteType>>,
) -> ConcreteTypeEnum {
ConcreteTypeEnum::TFunc {
args: signature
.args
.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)
},
default_value: arg.default_value.clone(),
is_vararg: arg.is_vararg,
})
.collect(),
ret: self.from_unifier_type(unifier, primitives, signature.ret, cache),
vars: signature
.vars
.iter()
.map(|(id, ty)| (*id, self.from_unifier_type(unifier, primitives, *ty, cache)))
.collect(),
}
}
pub fn from_unifier_type(
&mut self,
unifier: &mut Unifier,
primitives: &PrimitiveStore,
ty: Type,
cache: &mut HashMap<Type, Option<ConcreteType>>,
) -> ConcreteType {
let ty = unifier.get_representative(ty);
if unifier.unioned(ty, primitives.int32) {
ConcreteType(0)
} else if unifier.unioned(ty, primitives.int64) {
ConcreteType(1)
} else if unifier.unioned(ty, primitives.float) {
ConcreteType(2)
} else if unifier.unioned(ty, primitives.bool) {
ConcreteType(3)
} else if unifier.unioned(ty, primitives.none) {
ConcreteType(4)
} else if unifier.unioned(ty, primitives.range) {
ConcreteType(5)
} else if unifier.unioned(ty, primitives.str) {
ConcreteType(6)
} else if unifier.unioned(ty, primitives.exception) {
ConcreteType(7)
} else if unifier.unioned(ty, primitives.uint32) {
ConcreteType(8)
} else if unifier.unioned(ty, primitives.uint64) {
ConcreteType(9)
} else if let Some(cty) = cache.get(&ty) {
if let Some(cty) = cty {
*cty
} else {
let index = self.store.len();
// placeholder
self.store.push(ConcreteTypeEnum::TPrimitive(Primitive::Int32));
let result = ConcreteType(index);
cache.insert(ty, Some(result));
result
}
} else {
cache.insert(ty, None);
let ty_enum = unifier.get_ty(ty);
let result = match &*ty_enum {
TypeEnum::TTuple { ty, is_vararg_ctx } => 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,
fields: fields
.iter()
.filter_map(|(name, ty)| {
// here we should not have type vars, but some partial instantiated
// class methods can still have uninstantiated type vars, so
// filter out all the methods, as this will not affect codegen
if let TypeEnum::TFunc(..) = &*unifier.get_ty(ty.0) {
None
} else {
Some((
*name,
(
self.from_unifier_type(unifier, primitives, ty.0, cache),
ty.1,
),
))
}
})
.collect(),
params: params
.iter()
.map(|(id, ty)| {
(*id, self.from_unifier_type(unifier, primitives, *ty, cache))
})
.collect(),
},
TypeEnum::TVirtual { ty } => ConcreteTypeEnum::TVirtual {
ty: self.from_unifier_type(unifier, primitives, *ty, cache),
},
TypeEnum::TFunc(signature) => {
self.from_signature(unifier, primitives, signature, cache)
}
TypeEnum::TLiteral { values, .. } => {
ConcreteTypeEnum::TLiteral { values: values.clone() }
}
_ => unreachable!("{:?}", ty_enum.get_type_name()),
};
let index = if let Some(ConcreteType(index)) = cache.get(&ty).unwrap() {
self.store[*index] = result;
*index
} else {
self.store.push(result);
self.store.len() - 1
};
cache.insert(ty, Some(ConcreteType(index)));
ConcreteType(index)
}
}
pub fn to_unifier_type(
&self,
unifier: &mut Unifier,
primitives: &PrimitiveStore,
cty: ConcreteType,
cache: &mut HashMap<ConcreteType, Option<Type>>,
) -> Type {
if let Some(ty) = cache.get_mut(&cty) {
return if let Some(ty) = ty {
*ty
} else {
*ty = Some(unifier.get_dummy_var().ty);
ty.unwrap()
};
}
cache.insert(cty, None);
let result = match &self.store[cty.0] {
ConcreteTypeEnum::TPrimitive(primitive) => {
let ty = match primitive {
Primitive::Int32 => primitives.int32,
Primitive::Int64 => primitives.int64,
Primitive::UInt32 => primitives.uint32,
Primitive::UInt64 => primitives.uint64,
Primitive::Float => primitives.float,
Primitive::Bool => primitives.bool,
Primitive::None => primitives.none,
Primitive::Range => primitives.range,
Primitive::Str => primitives.str,
Primitive::Exception => primitives.exception,
};
*cache.get_mut(&cty).unwrap() = Some(ty);
return ty;
}
ConcreteTypeEnum::TTuple { ty, is_vararg_ctx } => 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) }
}
ConcreteTypeEnum::TObj { obj_id, fields, params } => TypeEnum::TObj {
obj_id: *obj_id,
fields: fields
.iter()
.map(|(name, cty)| {
(*name, (self.to_unifier_type(unifier, primitives, cty.0, cache), cty.1))
})
.collect::<HashMap<_, _>>(),
params: into_var_map(params.iter().map(|(&id, cty)| {
let ty = self.to_unifier_type(unifier, primitives, *cty, cache);
TypeVar { id, ty }
})),
},
ConcreteTypeEnum::TFunc { args, ret, vars } => TypeEnum::TFunc(FunSignature {
args: args
.iter()
.map(|arg| FuncArg {
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),
vars: into_var_map(vars.iter().map(|(&id, cty)| {
let ty = self.to_unifier_type(unifier, primitives, *cty, cache);
TypeVar { id, ty }
})),
}),
ConcreteTypeEnum::TLiteral { values, .. } => {
TypeEnum::TLiteral { values: values.clone(), loc: None }
}
};
let result = unifier.add_ty(result);
if let Some(ty) = cache.get(&cty).unwrap() {
unifier.unify(*ty, result).unwrap();
}
cache.insert(cty, Some(result));
result
}
pub fn add_cty(&mut self, cty: ConcreteTypeEnum) -> ConcreteType {
self.store.push(cty);
ConcreteType(self.store.len() - 1)
}
}
impl Default for ConcreteTypeStore {
fn default() -> Self {
Self::new()
}
}

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@ -1,193 +0,0 @@
use inkwell::{
attributes::{Attribute, AttributeLoc},
values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue},
};
use itertools::Either;
use super::CodeGenContext;
/// Macro to generate extern function
/// Both function return type and function parameter type are `FloatValue`
///
/// Arguments:
/// * `unary/binary`: Whether the extern function requires one (unary) or two (binary) operands
/// * `$fn_name:ident`: The identifier of the rust function to be generated
/// * `$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
/// * `$(,$args:ident)*`: Operands of the extern function
/// The data type of these operands will be set to `FloatValue`
///
macro_rules! generate_extern_fn {
("unary", $fn_name:ident, $extern_fn:literal) => {
generate_extern_fn!($fn_name, $extern_fn, arg, "mustprogress", "nofree", "nounwind", "willreturn", "writeonly");
};
("unary", $fn_name:ident, $extern_fn:literal $(,$attributes:literal)*) => {
generate_extern_fn!($fn_name, $extern_fn, arg $(,$attributes)*);
};
("binary", $fn_name:ident, $extern_fn:literal) => {
generate_extern_fn!($fn_name, $extern_fn, arg1, arg2, "mustprogress", "nofree", "nounwind", "willreturn", "writeonly");
};
("binary", $fn_name:ident, $extern_fn:literal $(,$attributes:literal)*) => {
generate_extern_fn!($fn_name, $extern_fn, arg1, arg2 $(,$attributes)*);
};
($fn_name:ident, $extern_fn:literal $(,$args:ident)* $(,$attributes:literal)*) => {
#[doc = concat!("Invokes the [`", stringify!($extern_fn), "`](https://en.cppreference.com/w/c/numeric/math/", stringify!($llvm_name), ") function." )]
pub fn $fn_name<'ctx>(
ctx: &CodeGenContext<'ctx, '_>
$(,$args: FloatValue<'ctx>)*,
name: Option<&str>,
) -> FloatValue<'ctx> {
const FN_NAME: &str = $extern_fn;
let llvm_f64 = ctx.ctx.f64_type();
$(debug_assert_eq!($args.get_type(), llvm_f64);)*
let extern_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
let fn_type = llvm_f64.fn_type(&[$($args.get_type().into()),*], false);
let func = ctx.module.add_function(FN_NAME, fn_type, None);
for attr in [$($attributes),*] {
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, &[$($args.into()),*], name.unwrap_or_default())
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_float_value))
.map(Either::unwrap_left)
.unwrap()
}
};
}
generate_extern_fn!("unary", call_tan, "tan");
generate_extern_fn!("unary", call_asin, "asin");
generate_extern_fn!("unary", call_acos, "acos");
generate_extern_fn!("unary", call_atan, "atan");
generate_extern_fn!("unary", call_sinh, "sinh");
generate_extern_fn!("unary", call_cosh, "cosh");
generate_extern_fn!("unary", call_tanh, "tanh");
generate_extern_fn!("unary", call_asinh, "asinh");
generate_extern_fn!("unary", call_acosh, "acosh");
generate_extern_fn!("unary", call_atanh, "atanh");
generate_extern_fn!("unary", call_expm1, "expm1");
generate_extern_fn!(
"unary",
call_cbrt,
"cbrt",
"mustprogress",
"nofree",
"nosync",
"nounwind",
"readonly",
"willreturn"
);
generate_extern_fn!("unary", call_erf, "erf", "nounwind");
generate_extern_fn!("unary", call_erfc, "erfc", "nounwind");
generate_extern_fn!("unary", call_j1, "j1", "nounwind");
generate_extern_fn!("binary", call_atan2, "atan2");
generate_extern_fn!("binary", call_hypot, "hypot", "nounwind");
generate_extern_fn!("binary", call_nextafter, "nextafter", "nounwind");
/// Invokes the [`ldexp`](https://en.cppreference.com/w/c/numeric/math/ldexp) function.
pub fn call_ldexp<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
arg: FloatValue<'ctx>,
exp: IntValue<'ctx>,
name: Option<&str>,
) -> FloatValue<'ctx> {
const FN_NAME: &str = "ldexp";
let llvm_f64 = ctx.ctx.f64_type();
let llvm_i32 = ctx.ctx.i32_type();
debug_assert_eq!(arg.get_type(), llvm_f64);
debug_assert_eq!(exp.get_type(), llvm_i32);
let extern_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
let fn_type = llvm_f64.fn_type(&[llvm_f64.into(), llvm_i32.into()], false);
let func = ctx.module.add_function(FN_NAME, fn_type, None);
for attr in ["mustprogress", "nofree", "nounwind", "willreturn"] {
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, &[arg.into(), exp.into()], name.unwrap_or_default())
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_float_value))
.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);

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@ -1,295 +0,0 @@
use inkwell::{
context::Context,
types::{BasicTypeEnum, IntType},
values::{BasicValueEnum, IntValue, PointerValue},
};
use nac3parser::ast::{Expr, Stmt, StrRef};
use super::{bool_to_i1, bool_to_i8, expr::*, stmt::*, values::ArraySliceValue, CodeGenContext};
use crate::{
symbol_resolver::ValueEnum,
toplevel::{DefinitionId, TopLevelDef},
typecheck::typedef::{FunSignature, Type},
};
pub trait CodeGenerator {
/// Return the module name for the code generator.
fn get_name(&self) -> &str;
/// Return an instance of [`IntType`] corresponding to the type of `size_t` for this instance.
fn get_size_type<'ctx>(&self, ctx: &'ctx Context) -> IntType<'ctx>;
/// Generate function call and returns the function return value.
/// - obj: Optional object for method call.
/// - fun: Function signature and definition ID.
/// - params: Function parameters. Note that this does not include the object even if the
/// function is a class method.
fn gen_call<'ctx>(
&mut self,
ctx: &mut CodeGenContext<'ctx, '_>,
obj: Option<(Type, ValueEnum<'ctx>)>,
fun: (&FunSignature, DefinitionId),
params: Vec<(Option<StrRef>, ValueEnum<'ctx>)>,
) -> Result<Option<BasicValueEnum<'ctx>>, String>
where
Self: Sized,
{
gen_call(self, ctx, obj, fun, params)
}
/// Generate object constructor and returns the constructed object.
/// - signature: Function signature of the constructor.
/// - def: Class definition for the constructor class.
/// - params: Function parameters.
fn gen_constructor<'ctx>(
&mut self,
ctx: &mut CodeGenContext<'ctx, '_>,
signature: &FunSignature,
def: &TopLevelDef,
params: Vec<(Option<StrRef>, ValueEnum<'ctx>)>,
) -> Result<BasicValueEnum<'ctx>, String>
where
Self: Sized,
{
gen_constructor(self, ctx, signature, def, params)
}
/// Generate a function instance.
/// - obj: Optional object for method call.
/// - 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>(
&mut self,
ctx: &mut CodeGenContext<'ctx, '_>,
obj: Option<(Type, ValueEnum<'ctx>)>,
fun: (&FunSignature, &mut TopLevelDef, String),
id: usize,
) -> Result<String, String> {
gen_func_instance(ctx, &obj, fun, id)
}
/// Generate the code for an expression.
fn gen_expr<'ctx>(
&mut self,
ctx: &mut CodeGenContext<'ctx, '_>,
expr: &Expr<Option<Type>>,
) -> Result<Option<ValueEnum<'ctx>>, String>
where
Self: Sized,
{
gen_expr(self, ctx, expr)
}
/// Allocate memory for a variable and return a pointer pointing to it.
/// The default implementation places the allocations at the start of the function.
fn gen_var_alloc<'ctx>(
&mut self,
ctx: &mut CodeGenContext<'ctx, '_>,
ty: BasicTypeEnum<'ctx>,
name: Option<&str>,
) -> Result<PointerValue<'ctx>, String> {
gen_var(ctx, ty, name)
}
/// Allocate memory for a variable and return a pointer pointing to it.
/// The default implementation places the allocations at the start of the function.
fn gen_array_var_alloc<'ctx>(
&mut self,
ctx: &mut CodeGenContext<'ctx, '_>,
ty: BasicTypeEnum<'ctx>,
size: IntValue<'ctx>,
name: Option<&'ctx str>,
) -> Result<ArraySliceValue<'ctx>, String> {
gen_array_var(ctx, ty, size, name)
}
/// Return a pointer pointing to the target of the expression.
fn gen_store_target<'ctx>(
&mut self,
ctx: &mut CodeGenContext<'ctx, '_>,
pattern: &Expr<Option<Type>>,
name: Option<&str>,
) -> Result<Option<PointerValue<'ctx>>, String>
where
Self: Sized,
{
gen_store_target(self, ctx, pattern, name)
}
/// Generate code for an assignment expression.
fn gen_assign<'ctx>(
&mut self,
ctx: &mut CodeGenContext<'ctx, '_>,
target: &Expr<Option<Type>>,
value: ValueEnum<'ctx>,
value_ty: Type,
) -> Result<(), String>
where
Self: Sized,
{
gen_assign(self, ctx, target, value, value_ty)
}
/// Generate code for an assignment expression where LHS is a `"target_list"`.
///
/// See <https://docs.python.org/3/reference/simple_stmts.html#assignment-statements>.
fn gen_assign_target_list<'ctx>(
&mut self,
ctx: &mut CodeGenContext<'ctx, '_>,
targets: &Vec<Expr<Option<Type>>>,
value: ValueEnum<'ctx>,
value_ty: Type,
) -> Result<(), String>
where
Self: Sized,
{
gen_assign_target_list(self, ctx, targets, value, value_ty)
}
/// Generate code for an item assignment.
///
/// i.e., `target[key] = value`
fn gen_setitem<'ctx>(
&mut self,
ctx: &mut CodeGenContext<'ctx, '_>,
target: &Expr<Option<Type>>,
key: &Expr<Option<Type>>,
value: ValueEnum<'ctx>,
value_ty: Type,
) -> Result<(), String>
where
Self: Sized,
{
gen_setitem(self, ctx, target, key, value, value_ty)
}
/// Generate code for a while expression.
/// Return true if the while loop must early return
fn gen_while(
&mut self,
ctx: &mut CodeGenContext<'_, '_>,
stmt: &Stmt<Option<Type>>,
) -> Result<(), String>
where
Self: Sized,
{
gen_while(self, ctx, stmt)
}
/// Generate code for a for expression.
/// Return true if the for loop must early return
fn gen_for(
&mut self,
ctx: &mut CodeGenContext<'_, '_>,
stmt: &Stmt<Option<Type>>,
) -> Result<(), String>
where
Self: Sized,
{
gen_for(self, ctx, stmt)
}
/// Generate code for an if expression.
/// Return true if the statement must early return
fn gen_if(
&mut self,
ctx: &mut CodeGenContext<'_, '_>,
stmt: &Stmt<Option<Type>>,
) -> Result<(), String>
where
Self: Sized,
{
gen_if(self, ctx, stmt)
}
fn gen_with(
&mut self,
ctx: &mut CodeGenContext<'_, '_>,
stmt: &Stmt<Option<Type>>,
) -> Result<(), String>
where
Self: Sized,
{
gen_with(self, ctx, stmt)
}
/// Generate code for a statement
///
/// Return true if the statement must early return
fn gen_stmt(
&mut self,
ctx: &mut CodeGenContext<'_, '_>,
stmt: &Stmt<Option<Type>>,
) -> Result<(), String>
where
Self: Sized,
{
gen_stmt(self, ctx, stmt)
}
/// Generates code for a block statement.
fn gen_block<'a, I: Iterator<Item = &'a Stmt<Option<Type>>>>(
&mut self,
ctx: &mut CodeGenContext<'_, '_>,
stmts: I,
) -> Result<(), String>
where
Self: Sized,
{
gen_block(self, ctx, stmts)
}
/// See [`bool_to_i1`].
fn bool_to_i1<'ctx>(
&self,
ctx: &CodeGenContext<'ctx, '_>,
bool_value: IntValue<'ctx>,
) -> IntValue<'ctx> {
bool_to_i1(&ctx.builder, bool_value)
}
/// See [`bool_to_i8`].
fn bool_to_i8<'ctx>(
&self,
ctx: &CodeGenContext<'ctx, '_>,
bool_value: IntValue<'ctx>,
) -> IntValue<'ctx> {
bool_to_i8(&ctx.builder, ctx.ctx, bool_value)
}
}
pub struct DefaultCodeGenerator {
name: String,
size_t: u32,
}
impl DefaultCodeGenerator {
#[must_use]
pub fn new(name: String, size_t: u32) -> DefaultCodeGenerator {
assert!(matches!(size_t, 32 | 64));
DefaultCodeGenerator { name, size_t }
}
}
impl CodeGenerator for DefaultCodeGenerator {
/// Returns the name for this [`CodeGenerator`].
fn get_name(&self) -> &str {
&self.name
}
/// Returns an LLVM integer type representing `size_t`.
fn get_size_type<'ctx>(&self, ctx: &'ctx Context) -> IntType<'ctx> {
// it should be unsigned, but we don't really need unsigned and this could save us from
// having to do a bit cast...
if self.size_t == 32 {
ctx.i32_type()
} else {
ctx.i64_type()
}
}
}

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

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

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@ -1,252 +0,0 @@
use inkwell::{
attributes::{Attribute, AttributeLoc},
context::Context,
memory_buffer::MemoryBuffer,
module::Module,
values::{BasicValue, BasicValueEnum, IntValue},
IntPredicate,
};
use nac3parser::ast::Expr;
use super::{CodeGenContext, CodeGenerator};
use crate::{symbol_resolver::SymbolResolver, typecheck::typedef::Type};
pub use list::*;
pub use math::*;
pub use range::*;
pub use slice::*;
pub use string::*;
mod list;
mod math;
pub mod ndarray;
mod range;
mod slice;
mod string;
#[must_use]
pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver) -> Module<'ctx> {
let bitcode_buf = MemoryBuffer::create_from_memory_range(
include_bytes!(concat!(env!("OUT_DIR"), "/irrt.bc")),
"irrt_bitcode_buffer",
);
let irrt_mod = Module::parse_bitcode_from_buffer(&bitcode_buf, ctx).unwrap();
let inline_attr = Attribute::get_named_enum_kind_id("alwaysinline");
for symbol in &[
"__nac3_int_exp_int32_t",
"__nac3_int_exp_int64_t",
"__nac3_range_slice_len",
"__nac3_slice_index_bound",
] {
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
}
/// Returns the name of a function which contains variants for 32-bit and 64-bit `size_t`.
///
/// - When [`TypeContext::size_type`] is 32-bits, the function name is `fn_name}`.
/// - When [`TypeContext::size_type`] is 64-bits, the function name is `{fn_name}64`.
#[must_use]
pub fn get_usize_dependent_function_name<G: CodeGenerator + ?Sized>(
generator: &G,
ctx: &CodeGenContext<'_, '_>,
name: &str,
) -> String {
let mut name = name.to_owned();
match generator.get_size_type(ctx.ctx).get_bit_width() {
32 => {}
64 => name.push_str("64"),
bit_width => {
panic!("Unsupported int type bit width {bit_width}, must be either 32-bits or 64-bits")
}
}
name
}
/// NOTE: the output value of the end index of this function should be compared ***inclusively***,
/// because python allows `a[2::-1]`, whose semantic is `[a[2], a[1], a[0]]`, which is equivalent to
/// NO numeric slice in python.
///
/// equivalent code:
/// ```pseudo_code
/// match (start, end, step):
/// case (s, e, None | Some(step)) if step > 0:
/// return (
/// match s:
/// case None:
/// 0
/// case Some(s):
/// handle_in_bound(s)
/// ,match e:
/// case None:
/// length - 1
/// case Some(e):
/// handle_in_bound(e) - 1
/// ,step == None ? 1 : step
/// )
/// case (s, e, Some(step)) if step < 0:
/// return (
/// match s:
/// case None:
/// length - 1
/// case Some(s):
/// s = handle_in_bound(s)
/// if s == length:
/// s - 1
/// else:
/// s
/// ,match e:
/// case None:
/// 0
/// case Some(e):
/// handle_in_bound(e) + 1
/// ,step
/// )
/// ```
pub fn handle_slice_indices<'ctx, G: CodeGenerator>(
start: &Option<Box<Expr<Option<Type>>>>,
end: &Option<Box<Expr<Option<Type>>>>,
step: &Option<Box<Expr<Option<Type>>>>,
ctx: &mut CodeGenContext<'ctx, '_>,
generator: &mut G,
length: IntValue<'ctx>,
) -> Result<Option<(IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>)>, String> {
let llvm_i32 = ctx.ctx.i32_type();
let zero = llvm_i32.const_zero();
let one = llvm_i32.const_int(1, false);
let length = ctx.builder.build_int_truncate_or_bit_cast(length, llvm_i32, "leni32").unwrap();
Ok(Some(match (start, end, step) {
(s, e, None) => (
if let Some(s) = s.as_ref() {
match handle_slice_index_bound(s, ctx, generator, length)? {
Some(v) => v,
None => return Ok(None),
}
} else {
llvm_i32.const_zero()
},
{
let e = if let Some(s) = e.as_ref() {
match handle_slice_index_bound(s, ctx, generator, length)? {
Some(v) => v,
None => return Ok(None),
}
} else {
length
};
ctx.builder.build_int_sub(e, one, "final_end").unwrap()
},
one,
),
(s, e, Some(step)) => {
let step = if let Some(v) = generator.gen_expr(ctx, step)? {
v.to_basic_value_enum(ctx, generator, ctx.primitives.int32)?.into_int_value()
} else {
return Ok(None);
};
// assert step != 0, throw exception if not
let not_zero = ctx
.builder
.build_int_compare(
IntPredicate::NE,
step,
step.get_type().const_zero(),
"range_step_ne",
)
.unwrap();
ctx.make_assert(
generator,
not_zero,
"0:ValueError",
"slice step cannot be zero",
[None, None, None],
ctx.current_loc,
);
let len_id = ctx.builder.build_int_sub(length, one, "lenmin1").unwrap();
let neg = ctx
.builder
.build_int_compare(IntPredicate::SLT, step, zero, "step_is_neg")
.unwrap();
(
match s {
Some(s) => {
let Some(s) = handle_slice_index_bound(s, ctx, generator, length)? else {
return Ok(None);
};
ctx.builder
.build_select(
ctx.builder
.build_and(
ctx.builder
.build_int_compare(
IntPredicate::EQ,
s,
length,
"s_eq_len",
)
.unwrap(),
neg,
"should_minus_one",
)
.unwrap(),
ctx.builder.build_int_sub(s, one, "s_min").unwrap(),
s,
"final_start",
)
.map(BasicValueEnum::into_int_value)
.unwrap()
}
None => ctx
.builder
.build_select(neg, len_id, zero, "stt")
.map(BasicValueEnum::into_int_value)
.unwrap(),
},
match e {
Some(e) => {
let Some(e) = handle_slice_index_bound(e, ctx, generator, length)? else {
return Ok(None);
};
ctx.builder
.build_select(
neg,
ctx.builder.build_int_add(e, one, "end_add_one").unwrap(),
ctx.builder.build_int_sub(e, one, "end_sub_one").unwrap(),
"final_end",
)
.map(BasicValueEnum::into_int_value)
.unwrap()
}
None => ctx
.builder
.build_select(neg, zero, len_id, "end")
.map(BasicValueEnum::into_int_value)
.unwrap(),
},
step,
)
}
}))
}

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

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

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

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

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

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

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

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

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

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

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

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

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@ -1,381 +0,0 @@
use inkwell::{
intrinsics::Intrinsic,
types::AnyTypeEnum::IntType,
values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue, PointerValue},
AddressSpace,
};
use itertools::Either;
use super::CodeGenContext;
/// Invokes the [`llvm.va_start`](https://llvm.org/docs/LangRef.html#llvm-va-start-intrinsic)
/// intrinsic.
pub fn call_va_start<'ctx>(ctx: &CodeGenContext<'ctx, '_>, arglist: PointerValue<'ctx>) {
const FN_NAME: &str = "llvm.va_start";
let intrinsic_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
let llvm_void = ctx.ctx.void_type();
let llvm_i8 = ctx.ctx.i8_type();
let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
let fn_type = llvm_void.fn_type(&[llvm_p0i8.into()], false);
ctx.module.add_function(FN_NAME, fn_type, None)
});
ctx.builder.build_call(intrinsic_fn, &[arglist.into()], "").unwrap();
}
/// Invokes the [`llvm.va_end`](https://llvm.org/docs/LangRef.html#llvm-va-end-intrinsic)
/// intrinsic.
pub fn call_va_end<'ctx>(ctx: &CodeGenContext<'ctx, '_>, arglist: PointerValue<'ctx>) {
const FN_NAME: &str = "llvm.va_end";
let intrinsic_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
let llvm_void = ctx.ctx.void_type();
let llvm_i8 = ctx.ctx.i8_type();
let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
let fn_type = llvm_void.fn_type(&[llvm_p0i8.into()], false);
ctx.module.add_function(FN_NAME, fn_type, None)
});
ctx.builder.build_call(intrinsic_fn, &[arglist.into()], "").unwrap();
}
/// Invokes the [`llvm.stacksave`](https://llvm.org/docs/LangRef.html#llvm-stacksave-intrinsic)
/// intrinsic.
pub fn call_stacksave<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
name: Option<&str>,
) -> PointerValue<'ctx> {
const FN_NAME: &str = "llvm.stacksave";
let intrinsic_fn = Intrinsic::find(FN_NAME)
.and_then(|intrinsic| intrinsic.get_declaration(&ctx.module, &[]))
.unwrap();
ctx.builder
.build_call(intrinsic_fn, &[], name.unwrap_or_default())
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_pointer_value))
.map(Either::unwrap_left)
.unwrap()
}
/// Invokes the
/// [`llvm.stackrestore`](https://llvm.org/docs/LangRef.html#llvm-stackrestore-intrinsic) intrinsic.
///
/// - `ptr`: The pointer storing the address to restore the stack to.
pub fn call_stackrestore<'ctx>(ctx: &CodeGenContext<'ctx, '_>, ptr: PointerValue<'ctx>) {
const FN_NAME: &str = "llvm.stackrestore";
/*
SEE https://github.com/TheDan64/inkwell/issues/496
We want `llvm.stackrestore`, but the following would generate `llvm.stackrestore.p0i8`.
```ignore
let intrinsic_fn = Intrinsic::find(FN_NAME)
.and_then(|intrinsic| intrinsic.get_declaration(&ctx.module, &[llvm_p0i8.into()]))
.unwrap();
```
Temp workaround by manually declaring the intrinsic with the correct function name instead.
*/
let intrinsic_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
let llvm_void = ctx.ctx.void_type();
let llvm_i8 = ctx.ctx.i8_type();
let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
let fn_type = llvm_void.fn_type(&[llvm_p0i8.into()], false);
ctx.module.add_function(FN_NAME, fn_type, None)
});
ctx.builder.build_call(intrinsic_fn, &[ptr.into()], "").unwrap();
}
/// Invokes the [`llvm.memcpy`](https://llvm.org/docs/LangRef.html#llvm-memcpy-intrinsic) intrinsic.
///
/// * `dest` - The pointer to the destination. Must be a pointer to an integer type.
/// * `src` - The pointer to the source. Must be a pointer to an integer type.
/// * `len` - The number of bytes to copy.
/// * `is_volatile` - Whether the `memcpy` operation should be `volatile`.
pub fn call_memcpy<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
dest: PointerValue<'ctx>,
src: PointerValue<'ctx>,
len: IntValue<'ctx>,
is_volatile: IntValue<'ctx>,
) {
const FN_NAME: &str = "llvm.memcpy";
debug_assert!(dest.get_type().get_element_type().is_int_type());
debug_assert!(src.get_type().get_element_type().is_int_type());
debug_assert_eq!(
dest.get_type().get_element_type().into_int_type().get_bit_width(),
src.get_type().get_element_type().into_int_type().get_bit_width(),
);
debug_assert!(matches!(len.get_type().get_bit_width(), 32 | 64));
debug_assert_eq!(is_volatile.get_type().get_bit_width(), 1);
let llvm_dest_t = dest.get_type();
let llvm_src_t = src.get_type();
let llvm_len_t = len.get_type();
let intrinsic_fn = Intrinsic::find(FN_NAME)
.and_then(|intrinsic| {
intrinsic.get_declaration(
&ctx.module,
&[llvm_dest_t.into(), llvm_src_t.into(), llvm_len_t.into()],
)
})
.unwrap();
ctx.builder
.build_call(intrinsic_fn, &[dest.into(), src.into(), len.into(), is_volatile.into()], "")
.unwrap();
}
/// Invokes the `llvm.memcpy` intrinsic.
///
/// Unlike [`call_memcpy`], this function accepts any type of pointer value. If `dest` or `src` is
/// not a pointer to an integer, the pointer(s) will be cast to `i8*` before invoking `memcpy`.
pub fn call_memcpy_generic<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
dest: PointerValue<'ctx>,
src: PointerValue<'ctx>,
len: IntValue<'ctx>,
is_volatile: IntValue<'ctx>,
) {
let llvm_i8 = ctx.ctx.i8_type();
let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
let dest_elem_t = dest.get_type().get_element_type();
let src_elem_t = src.get_type().get_element_type();
let dest = if matches!(dest_elem_t, IntType(t) if t.get_bit_width() == 8) {
dest
} else {
ctx.builder
.build_bit_cast(dest, llvm_p0i8, "")
.map(BasicValueEnum::into_pointer_value)
.unwrap()
};
let src = if matches!(src_elem_t, IntType(t) if t.get_bit_width() == 8) {
src
} else {
ctx.builder
.build_bit_cast(src, llvm_p0i8, "")
.map(BasicValueEnum::into_pointer_value)
.unwrap()
};
call_memcpy(ctx, dest, src, len, is_volatile);
}
/// Invokes the `llvm.memcpy` intrinsic.
///
/// Unlike [`call_memcpy`], this function accepts any type of pointer value. If `dest` or `src` is
/// not a pointer to an integer, the pointer(s) will be cast to `i8*` before invoking `memcpy`.
/// Moreover, `len` now refers to the number of elements to copy (rather than number of bytes to
/// copy).
pub fn call_memcpy_generic_array<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
dest: PointerValue<'ctx>,
src: PointerValue<'ctx>,
len: IntValue<'ctx>,
is_volatile: IntValue<'ctx>,
) {
let llvm_i8 = ctx.ctx.i8_type();
let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
let llvm_sizeof_expr_t = llvm_i8.size_of().get_type();
let dest_elem_t = dest.get_type().get_element_type();
let src_elem_t = src.get_type().get_element_type();
let dest = if matches!(dest_elem_t, IntType(t) if t.get_bit_width() == 8) {
dest
} else {
ctx.builder
.build_bit_cast(dest, llvm_p0i8, "")
.map(BasicValueEnum::into_pointer_value)
.unwrap()
};
let src = if matches!(src_elem_t, IntType(t) if t.get_bit_width() == 8) {
src
} else {
ctx.builder
.build_bit_cast(src, llvm_p0i8, "")
.map(BasicValueEnum::into_pointer_value)
.unwrap()
};
let len = ctx.builder.build_int_z_extend_or_bit_cast(len, llvm_sizeof_expr_t, "").unwrap();
let len = ctx.builder.build_int_mul(len, src_elem_t.size_of().unwrap(), "").unwrap();
call_memcpy(ctx, dest, src, len, is_volatile);
}
/// Macro to find and generate build call for llvm intrinsic (body of llvm intrinsic function)
///
/// Arguments:
/// * `$ctx:ident`: Reference to the current Code Generation Context
/// * `$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
/// * `$llvm_ty:ident`: Type of first operand
/// * `,($val:ident)*`: Comma separated list of operands
macro_rules! generate_llvm_intrinsic_fn_body {
($ctx:ident, $name:ident, $llvm_name:literal, $map_fn:expr, $llvm_ty:ident $(,$val:ident)*) => {{
const FN_NAME: &str = concat!("llvm.", $llvm_name);
let intrinsic_fn = Intrinsic::find(FN_NAME).and_then(|intrinsic| intrinsic.get_declaration(&$ctx.module, &[$llvm_ty.into()])).unwrap();
$ctx.builder.build_call(intrinsic_fn, &[$($val.into()),*], $name.unwrap_or_default()).map(CallSiteValue::try_as_basic_value).map(|v| v.map_left($map_fn)).map(Either::unwrap_left).unwrap()
}};
}
/// Macro to generate the llvm intrinsic function using [`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"
/// * `$val:ident`: The operand for unary operations
/// * `$val1:ident`, `$val2:ident`: The operands for binary operations
macro_rules! generate_llvm_intrinsic_fn {
("float", $fn_name:ident, $llvm_name:literal, $val:ident) => {
#[doc = concat!("Invokes the [`", stringify!($llvm_name), "`](https://llvm.org/docs/LangRef.html#llvm-", stringify!($llvm_name), "-intrinsic) intrinsic." )]
pub fn $fn_name<'ctx> (
ctx: &CodeGenContext<'ctx, '_>,
$val: FloatValue<'ctx>,
name: Option<&str>,
) -> FloatValue<'ctx> {
let llvm_ty = $val.get_type();
generate_llvm_intrinsic_fn_body!(ctx, name, $llvm_name, BasicValueEnum::into_float_value, llvm_ty, $val)
}
};
("float", $fn_name:ident, $llvm_name:literal, $val1:ident, $val2:ident) => {
#[doc = concat!("Invokes the [`", stringify!($llvm_name), "`](https://llvm.org/docs/LangRef.html#llvm-", stringify!($llvm_name), "-intrinsic) intrinsic." )]
pub fn $fn_name<'ctx> (
ctx: &CodeGenContext<'ctx, '_>,
$val1: FloatValue<'ctx>,
$val2: FloatValue<'ctx>,
name: Option<&str>,
) -> FloatValue<'ctx> {
debug_assert_eq!($val1.get_type(), $val2.get_type());
let llvm_ty = $val1.get_type();
generate_llvm_intrinsic_fn_body!(ctx, name, $llvm_name, BasicValueEnum::into_float_value, llvm_ty, $val1, $val2)
}
};
("int", $fn_name:ident, $llvm_name:literal, $val1:ident, $val2:ident) => {
#[doc = concat!("Invokes the [`", stringify!($llvm_name), "`](https://llvm.org/docs/LangRef.html#llvm-", stringify!($llvm_name), "-intrinsic) intrinsic." )]
pub fn $fn_name<'ctx> (
ctx: &CodeGenContext<'ctx, '_>,
$val1: IntValue<'ctx>,
$val2: IntValue<'ctx>,
name: Option<&str>,
) -> IntValue<'ctx> {
debug_assert_eq!($val1.get_type().get_bit_width(), $val2.get_type().get_bit_width());
let llvm_ty = $val1.get_type();
generate_llvm_intrinsic_fn_body!(ctx, name, $llvm_name, BasicValueEnum::into_int_value, llvm_ty, $val1, $val2)
}
};
}
/// Invokes the [`llvm.abs`](https://llvm.org/docs/LangRef.html#llvm-abs-intrinsic) intrinsic.
///
/// * `src` - The value for which the absolute value is to be returned.
/// * `is_int_min_poison` - Whether `poison` is to be returned if `src` is `INT_MIN`.
pub fn call_int_abs<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
src: IntValue<'ctx>,
is_int_min_poison: IntValue<'ctx>,
name: Option<&str>,
) -> IntValue<'ctx> {
debug_assert_eq!(is_int_min_poison.get_type().get_bit_width(), 1);
debug_assert!(is_int_min_poison.is_const());
let src_type = src.get_type();
generate_llvm_intrinsic_fn_body!(
ctx,
name,
"abs",
BasicValueEnum::into_int_value,
src_type,
src,
is_int_min_poison
)
}
generate_llvm_intrinsic_fn!("int", call_int_smax, "smax", a, b);
generate_llvm_intrinsic_fn!("int", call_int_smin, "smin", a, b);
generate_llvm_intrinsic_fn!("int", call_int_umax, "umax", a, b);
generate_llvm_intrinsic_fn!("int", call_int_umin, "umin", a, b);
generate_llvm_intrinsic_fn!("int", call_expect, "expect", val, expected_val);
generate_llvm_intrinsic_fn!("float", call_float_sqrt, "sqrt", val);
generate_llvm_intrinsic_fn!("float", call_float_sin, "sin", val);
generate_llvm_intrinsic_fn!("float", call_float_cos, "cos", val);
generate_llvm_intrinsic_fn!("float", call_float_pow, "pow", val, power);
generate_llvm_intrinsic_fn!("float", call_float_exp, "exp", val);
generate_llvm_intrinsic_fn!("float", call_float_exp2, "exp2", val);
generate_llvm_intrinsic_fn!("float", call_float_log, "log", val);
generate_llvm_intrinsic_fn!("float", call_float_log10, "log10", val);
generate_llvm_intrinsic_fn!("float", call_float_log2, "log2", val);
generate_llvm_intrinsic_fn!("float", call_float_fabs, "fabs", src);
generate_llvm_intrinsic_fn!("float", call_float_minnum, "minnum", val, power);
generate_llvm_intrinsic_fn!("float", call_float_maxnum, "maxnum", val, power);
generate_llvm_intrinsic_fn!("float", call_float_copysign, "copysign", mag, sgn);
generate_llvm_intrinsic_fn!("float", call_float_floor, "floor", val);
generate_llvm_intrinsic_fn!("float", call_float_ceil, "ceil", val);
generate_llvm_intrinsic_fn!("float", call_float_round, "round", val);
generate_llvm_intrinsic_fn!("float", call_float_rint, "rint", val);
/// Invokes the [`llvm.powi`](https://llvm.org/docs/LangRef.html#llvm-powi-intrinsic) intrinsic.
pub fn call_float_powi<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
val: FloatValue<'ctx>,
power: IntValue<'ctx>,
name: Option<&str>,
) -> FloatValue<'ctx> {
const FN_NAME: &str = "llvm.powi";
let llvm_val_t = val.get_type();
let llvm_power_t = power.get_type();
let intrinsic_fn = Intrinsic::find(FN_NAME)
.and_then(|intrinsic| {
intrinsic.get_declaration(&ctx.module, &[llvm_val_t.into(), llvm_power_t.into()])
})
.unwrap();
ctx.builder
.build_call(intrinsic_fn, &[val.into(), power.into()], name.unwrap_or_default())
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_float_value))
.map(Either::unwrap_left)
.unwrap()
}
/// Invokes the [`llvm.ctpop`](https://llvm.org/docs/LangRef.html#llvm-ctpop-intrinsic) intrinsic.
pub fn call_int_ctpop<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
src: IntValue<'ctx>,
name: Option<&str>,
) -> IntValue<'ctx> {
const FN_NAME: &str = "llvm.ctpop";
let llvm_src_t = src.get_type();
let intrinsic_fn = Intrinsic::find(FN_NAME)
.and_then(|intrinsic| intrinsic.get_declaration(&ctx.module, &[llvm_src_t.into()]))
.unwrap();
ctx.builder
.build_call(intrinsic_fn, &[src.into()], name.unwrap_or_default())
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap()
}

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@ -1,413 +0,0 @@
use inkwell::{
values::{BasicValue, BasicValueEnum, PointerValue},
IntPredicate,
};
use nac3parser::ast::StrRef;
use super::{
macros::codegen_unreachable,
stmt::gen_for_callback,
types::ndarray::{NDArrayType, NDIterType},
values::{ndarray::shape::parse_numpy_int_sequence, ProxyValue},
CodeGenContext, CodeGenerator,
};
use crate::{
symbol_resolver::ValueEnum,
toplevel::{
helper::{arraylike_flatten_element_type, extract_ndims},
numpy::unpack_ndarray_var_tys,
DefinitionId,
},
typecheck::typedef::{FunSignature, Type},
};
/// Generates LLVM IR for `ndarray.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);
let shape_ty = fun.0.args[0].ty;
let shape_arg = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
let (dtype, ndims) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
let llvm_dtype = context.get_llvm_type(generator, dtype);
let ndims = extract_ndims(&context.unifier, ndims);
let shape = parse_numpy_int_sequence(generator, context, (shape_ty, shape_arg));
let ndarray = NDArrayType::new(generator, context.ctx, llvm_dtype, ndims)
.construct_numpy_empty(generator, context, &shape, None);
Ok(ndarray.as_base_value())
}
/// Generates LLVM IR for `ndarray.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);
let shape_ty = fun.0.args[0].ty;
let shape_arg = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
let (dtype, ndims) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
let llvm_dtype = context.get_llvm_type(generator, dtype);
let ndims = extract_ndims(&context.unifier, ndims);
let shape = parse_numpy_int_sequence(generator, context, (shape_ty, shape_arg));
let ndarray = NDArrayType::new(generator, context.ctx, llvm_dtype, ndims)
.construct_numpy_zeros(generator, context, dtype, &shape, None);
Ok(ndarray.as_base_value())
}
/// Generates LLVM IR for `ndarray.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);
let shape_ty = fun.0.args[0].ty;
let shape_arg = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
let (dtype, ndims) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
let llvm_dtype = context.get_llvm_type(generator, dtype);
let ndims = extract_ndims(&context.unifier, ndims);
let shape = parse_numpy_int_sequence(generator, context, (shape_ty, shape_arg));
let ndarray = NDArrayType::new(generator, context.ctx, llvm_dtype, ndims)
.construct_numpy_ones(generator, context, dtype, &shape, None);
Ok(ndarray.as_base_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);
let shape_ty = fun.0.args[0].ty;
let shape_arg = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
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)?;
let (dtype, ndims) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
let llvm_dtype = context.get_llvm_type(generator, dtype);
let ndims = extract_ndims(&context.unifier, ndims);
let shape = parse_numpy_int_sequence(generator, context, (shape_ty, shape_arg));
let ndarray = NDArrayType::new(generator, context.ctx, llvm_dtype, ndims).construct_numpy_full(
generator,
context,
&shape,
fill_value_arg,
None,
);
Ok(ndarray.as_base_value())
}
pub fn gen_ndarray_array<'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!(matches!(args.len(), 1..=3));
let obj_ty = fun.0.args[0].ty;
let obj_arg = args[0].1.clone().to_basic_value_enum(context, generator, obj_ty)?;
let copy_arg = if let Some(arg) =
args.iter().find(|arg| arg.0.is_some_and(|name| name == fun.0.args[1].name))
{
let copy_ty = fun.0.args[1].ty;
arg.1.clone().to_basic_value_enum(context, generator, copy_ty)?
} else {
context.gen_symbol_val(
generator,
fun.0.args[1].default_value.as_ref().unwrap(),
fun.0.args[1].ty,
)
};
// The ndmin argument is ignored. We can simply force the ndarray's number of dimensions to be
// the `ndims` of the function return type.
let (_, ndims) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
let ndims = extract_ndims(&context.unifier, ndims);
let copy = generator.bool_to_i1(context, copy_arg.into_int_value());
let ndarray = NDArrayType::from_unifier_type(generator, context, fun.0.ret)
.construct_numpy_array(generator, context, (obj_ty, obj_arg), copy, None)
.atleast_nd(generator, context, ndims);
Ok(ndarray.as_base_value())
}
/// Generates LLVM IR for `ndarray.eye`.
pub fn gen_ndarray_eye<'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!(matches!(args.len(), 1..=3));
let nrows_ty = fun.0.args[0].ty;
let nrows_arg = args[0].1.clone().to_basic_value_enum(context, generator, nrows_ty)?;
let ncols_ty = fun.0.args[1].ty;
let ncols_arg = if let Some(arg) =
args.iter().find(|arg| arg.0.is_some_and(|name| name == fun.0.args[1].name))
{
arg.1.clone().to_basic_value_enum(context, generator, ncols_ty)
} else {
args[0].1.clone().to_basic_value_enum(context, generator, nrows_ty)
}?;
let offset_ty = fun.0.args[2].ty;
let offset_arg = if let Some(arg) =
args.iter().find(|arg| arg.0.is_some_and(|name| name == fun.0.args[2].name))
{
arg.1.clone().to_basic_value_enum(context, generator, offset_ty)
} else {
Ok(context.gen_symbol_val(
generator,
fun.0.args[2].default_value.as_ref().unwrap(),
offset_ty,
))
}?;
let (dtype, _) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
let llvm_usize = generator.get_size_type(context.ctx);
let llvm_dtype = context.get_llvm_type(generator, dtype);
let nrows = context
.builder
.build_int_s_extend_or_bit_cast(nrows_arg.into_int_value(), llvm_usize, "")
.unwrap();
let ncols = context
.builder
.build_int_s_extend_or_bit_cast(ncols_arg.into_int_value(), llvm_usize, "")
.unwrap();
let offset = context
.builder
.build_int_s_extend_or_bit_cast(offset_arg.into_int_value(), llvm_usize, "")
.unwrap();
let ndarray = NDArrayType::new(generator, context.ctx, llvm_dtype, 2)
.construct_numpy_eye(generator, context, dtype, nrows, ncols, offset, None);
Ok(ndarray.as_base_value())
}
/// Generates LLVM IR for `ndarray.identity`.
pub fn gen_ndarray_identity<'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);
let n_ty = fun.0.args[0].ty;
let n_arg = args[0].1.clone().to_basic_value_enum(context, generator, n_ty)?;
let (dtype, _) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
let llvm_usize = generator.get_size_type(context.ctx);
let llvm_dtype = context.get_llvm_type(generator, dtype);
let n = context
.builder
.build_int_s_extend_or_bit_cast(n_arg.into_int_value(), llvm_usize, "")
.unwrap();
let ndarray = NDArrayType::new(generator, context.ctx, llvm_dtype, 2)
.construct_numpy_identity(generator, context, dtype, n, None);
Ok(ndarray.as_base_value())
}
/// Generates LLVM IR for `ndarray.copy`.
pub fn gen_ndarray_copy<'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_some());
assert!(args.is_empty());
let this_ty = obj.as_ref().unwrap().0;
let this_arg =
obj.as_ref().unwrap().1.clone().to_basic_value_enum(context, generator, this_ty)?;
let this = NDArrayType::from_unifier_type(generator, context, this_ty)
.map_value(this_arg.into_pointer_value(), None);
let ndarray = this.make_copy(generator, context);
Ok(ndarray.as_base_value())
}
/// Generates LLVM IR for `ndarray.fill`.
pub fn gen_ndarray_fill<'ctx>(
context: &mut CodeGenContext<'ctx, '_>,
obj: &Option<(Type, ValueEnum<'ctx>)>,
fun: (&FunSignature, DefinitionId),
args: &[(Option<StrRef>, ValueEnum<'ctx>)],
generator: &mut dyn CodeGenerator,
) -> Result<(), String> {
assert!(obj.is_some());
assert_eq!(args.len(), 1);
let this_ty = obj.as_ref().unwrap().0;
let this_arg =
obj.as_ref().unwrap().1.clone().to_basic_value_enum(context, generator, this_ty)?;
let value_ty = fun.0.args[0].ty;
let value_arg = args[0].1.clone().to_basic_value_enum(context, generator, value_ty)?;
let this = NDArrayType::from_unifier_type(generator, context, this_ty)
.map_value(this_arg.into_pointer_value(), None);
this.fill(generator, context, value_arg);
Ok(())
}
/// 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_ty, x1): (Type, BasicValueEnum<'ctx>),
(x2_ty, x2): (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "ndarray_dot";
match (x1, x2) {
(BasicValueEnum::PointerValue(n1), BasicValueEnum::PointerValue(n2)) => {
let a = NDArrayType::from_unifier_type(generator, ctx, x1_ty).map_value(n1, None);
let b = NDArrayType::from_unifier_type(generator, ctx, x2_ty).map_value(n2, None);
// TODO: General `np.dot()` https://numpy.org/doc/stable/reference/generated/numpy.dot.html.
assert_eq!(a.get_type().ndims(), 1);
assert_eq!(b.get_type().ndims(), 1);
let common_dtype = arraylike_flatten_element_type(&mut ctx.unifier, x1_ty);
// Check shapes.
let a_size = a.size(generator, ctx);
let b_size = b.size(generator, ctx);
let same_shape =
ctx.builder.build_int_compare(IntPredicate::EQ, a_size, b_size, "").unwrap();
ctx.make_assert(
generator,
same_shape,
"0:ValueError",
"shapes ({0},) and ({1},) not aligned: {0} (dim 0) != {1} (dim 1)",
[Some(a_size), Some(b_size), None],
ctx.current_loc,
);
let dtype_llvm = ctx.get_llvm_type(generator, common_dtype);
let result = ctx.builder.build_alloca(dtype_llvm, "np_dot_result").unwrap();
ctx.builder.build_store(result, dtype_llvm.const_zero()).unwrap();
// Do dot product.
gen_for_callback(
generator,
ctx,
Some("np_dot"),
|generator, ctx| {
let a_iter = NDIterType::new(generator, ctx.ctx).construct(generator, ctx, a);
let b_iter = NDIterType::new(generator, ctx.ctx).construct(generator, ctx, b);
Ok((a_iter, b_iter))
},
|generator, ctx, (a_iter, _b_iter)| {
// Only a_iter drives the condition, b_iter should have the same status.
Ok(a_iter.has_element(generator, ctx))
},
|_, ctx, _hooks, (a_iter, b_iter)| {
let a_scalar = a_iter.get_scalar(ctx);
let b_scalar = b_iter.get_scalar(ctx);
let old_result = ctx.builder.build_load(result, "").unwrap();
let new_result: BasicValueEnum<'ctx> = match old_result {
BasicValueEnum::IntValue(old_result) => {
let a_scalar = a_scalar.into_int_value();
let b_scalar = b_scalar.into_int_value();
let x = ctx.builder.build_int_mul(a_scalar, b_scalar, "").unwrap();
ctx.builder.build_int_add(old_result, x, "").unwrap().into()
}
BasicValueEnum::FloatValue(old_result) => {
let a_scalar = a_scalar.into_float_value();
let b_scalar = b_scalar.into_float_value();
let x = ctx.builder.build_float_mul(a_scalar, b_scalar, "").unwrap();
ctx.builder.build_float_add(old_result, x, "").unwrap().into()
}
_ => {
panic!("Unrecognized dtype: {}", ctx.unifier.stringify(common_dtype));
}
};
ctx.builder.build_store(result, new_result).unwrap();
Ok(())
},
|generator, ctx, (a_iter, b_iter)| {
a_iter.next(generator, ctx);
b_iter.next(generator, ctx);
Ok(())
},
)
.unwrap();
Ok(ctx.builder.build_load(result, "").unwrap())
}
(BasicValueEnum::IntValue(e1), BasicValueEnum::IntValue(e2)) => {
Ok(ctx.builder.build_int_mul(e1, e2, "").unwrap().as_basic_value_enum())
}
(BasicValueEnum::FloatValue(e1), BasicValueEnum::FloatValue(e2)) => {
Ok(ctx.builder.build_float_mul(e1, e2, "").unwrap().as_basic_value_enum())
}
_ => codegen_unreachable!(
ctx,
"{FN_NAME}() not supported for '{}'",
format!("'{}'", ctx.unifier.stringify(x1_ty))
),
}
}

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@ -1,469 +0,0 @@
use std::{
collections::{HashMap, HashSet},
sync::Arc,
};
use indexmap::IndexMap;
use indoc::indoc;
use inkwell::{
targets::{InitializationConfig, Target},
OptimizationLevel,
};
use nac3parser::{
ast::{fold::Fold, FileName, StrRef},
parser::parse_program,
};
use parking_lot::RwLock;
use super::{
concrete_type::ConcreteTypeStore,
types::{ndarray::NDArrayType, ListType, ProxyType, RangeType},
CodeGenContext, CodeGenLLVMOptions, CodeGenTargetMachineOptions, CodeGenTask, CodeGenerator,
DefaultCodeGenerator, WithCall, WorkerRegistry,
};
use crate::{
symbol_resolver::{SymbolResolver, ValueEnum},
toplevel::{
composer::{ComposerConfig, TopLevelComposer},
DefinitionId, FunInstance, TopLevelContext, TopLevelDef,
},
typecheck::{
type_inferencer::{FunctionData, IdentifierInfo, Inferencer, PrimitiveStore},
typedef::{FunSignature, FuncArg, Type, TypeEnum, Unifier, VarMap},
},
};
struct Resolver {
id_to_type: HashMap<StrRef, Type>,
id_to_def: RwLock<HashMap<StrRef, DefinitionId>>,
}
impl Resolver {
pub fn add_id_def(&self, id: StrRef, def: DefinitionId) {
self.id_to_def.write().insert(id, def);
}
}
impl SymbolResolver for Resolver {
fn get_default_param_value(
&self,
_: &nac3parser::ast::Expr,
) -> Option<crate::symbol_resolver::SymbolValue> {
unimplemented!()
}
fn get_symbol_type(
&self,
_: &mut Unifier,
_: &[Arc<RwLock<TopLevelDef>>],
_: &PrimitiveStore,
str: StrRef,
) -> Result<Type, String> {
self.id_to_type.get(&str).copied().ok_or_else(|| format!("cannot find symbol `{str}`"))
}
fn get_symbol_value<'ctx>(
&self,
_: StrRef,
_: &mut CodeGenContext<'ctx, '_>,
_: &mut dyn CodeGenerator,
) -> Option<ValueEnum<'ctx>> {
unimplemented!()
}
fn get_identifier_def(&self, id: StrRef) -> Result<DefinitionId, HashSet<String>> {
self.id_to_def
.read()
.get(&id)
.copied()
.ok_or_else(|| HashSet::from([format!("cannot find symbol `{id}`")]))
}
fn get_string_id(&self, _: &str) -> i32 {
unimplemented!()
}
fn get_exception_id(&self, _tyid: usize) -> usize {
unimplemented!()
}
}
#[test]
fn test_primitives() {
let source = indoc! { "
c = a + b
d = a if c == 1 else 0
return d
"};
let statements = parse_program(source, FileName::default()).unwrap();
let composer = TopLevelComposer::new(Vec::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 resolver =
Arc::new(Resolver { id_to_type: HashMap::new(), id_to_def: RwLock::new(HashMap::new()) })
as Arc<dyn SymbolResolver + Send + Sync>;
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,
},
],
ret: primitives.int32,
vars: VarMap::new(),
};
let mut store = ConcreteTypeStore::new();
let mut cache = HashMap::new();
let signature = store.from_signature(&mut unifier, &primitives, &signature, &mut cache);
let signature = store.add_cty(signature);
let mut function_data = FunctionData {
resolver: resolver.clone(),
bound_variables: Vec::new(),
return_type: Some(primitives.int32),
};
let mut virtual_checks = Vec::new();
let mut calls = HashMap::new();
let mut identifiers: HashMap<_, _> =
["a".into(), "b".into()].map(|id| (id, IdentifierInfo::default())).into();
let mut inferencer = Inferencer {
top_level: &top_level,
function_data: &mut function_data,
unifier: &mut unifier,
variable_mapping: HashMap::default(),
primitives: &primitives,
virtual_checks: &mut virtual_checks,
calls: &mut calls,
defined_identifiers: identifiers.clone(),
in_handler: false,
};
inferencer.variable_mapping.insert("a".into(), inferencer.primitives.int32);
inferencer.variable_mapping.insert("b".into(), inferencer.primitives.int32);
let statements = statements
.into_iter()
.map(|v| inferencer.fold_stmt(v))
.collect::<Result<Vec<_>, _>>()
.unwrap();
inferencer.check_block(&statements, &mut identifiers).unwrap();
let top_level = Arc::new(TopLevelContext {
definitions: Arc::new(RwLock::new(std::mem::take(&mut *top_level.definitions.write()))),
unifiers: Arc::new(RwLock::new(vec![(unifier.get_shared_unifier(), primitives)])),
personality_symbol: None,
});
let task = CodeGenTask {
subst: Vec::default(),
symbol_name: "testing".into(),
body: Arc::new(statements),
unifier_index: 0,
calls: Arc::new(calls),
resolver,
store,
signature,
id: 0,
};
let f = Arc::new(WithCall::new(Box::new(|module| {
// the following IR is equivalent to
// ```
// ; ModuleID = 'test.ll'
// source_filename = "test"
//
// ; Function Attrs: norecurse nounwind readnone
// define i32 @testing(i32 %0, i32 %1) local_unnamed_addr #0 {
// init:
// %add = add i32 %1, %0
// %cmp = icmp eq i32 %add, 1
// %ifexpr = select i1 %cmp, i32 %0, i32 0
// ret i32 %ifexpr
// }
//
// attributes #0 = { norecurse nounwind readnone }
// ```
// after O2 optimization
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 {
init:
%add = add i32 %1, %0, !dbg !9
%cmp = icmp eq i32 %add, 1, !dbg !10
%. = select i1 %cmp, i32 %0, i32 0, !dbg !11
ret i32 %., !dbg !12
}
attributes #0 = { mustprogress nofree norecurse nosync nounwind readnone willreturn }
!llvm.module.flags = !{!0, !1}
!llvm.dbg.cu = !{!2}
!0 = !{i32 2, !\"Debug Info Version\", i32 3}
!1 = !{i32 2, !\"Dwarf Version\", i32 4}
!2 = distinct !DICompileUnit(language: DW_LANG_Python, file: !3, producer: \"NAC3\", isOptimized: true, runtimeVersion: 0, emissionKind: FullDebug)
!3 = !DIFile(filename: \"unknown\", directory: \"\")
!4 = distinct !DISubprogram(name: \"testing\", linkageName: \"testing\", scope: null, file: !3, line: 1, type: !5, scopeLine: 1, flags: DIFlagPublic, spFlags: DISPFlagDefinition | DISPFlagOptimized, unit: !2, retainedNodes: !8)
!5 = !DISubroutineType(flags: DIFlagPublic, types: !6)
!6 = !{!7}
!7 = !DIBasicType(name: \"_\", flags: DIFlagPublic)
!8 = !{}
!9 = !DILocation(line: 1, column: 9, scope: !4)
!10 = !DILocation(line: 2, column: 15, scope: !4)
!11 = !DILocation(line: 0, scope: !4)
!12 = !DILocation(line: 3, column: 8, scope: !4)
"}
.trim();
assert_eq!(expected, module.print_to_string().to_str().unwrap().trim());
})));
Target::initialize_all(&InitializationConfig::default());
let llvm_options = CodeGenLLVMOptions {
opt_level: OptimizationLevel::Default,
target: CodeGenTargetMachineOptions::from_host_triple(),
};
let (registry, handles) = WorkerRegistry::create_workers(threads, top_level, &llvm_options, &f);
registry.add_task(task);
registry.wait_tasks_complete(handles);
}
#[test]
fn test_simple_call() {
let source_1 = indoc! { "
a = foo(a)
return a * 2
"};
let statements_1 = parse_program(source_1, FileName::default()).unwrap();
let source_2 = indoc! { "
return a + 1
"};
let statements_2 = parse_program(source_2, FileName::default()).unwrap();
let composer = TopLevelComposer::new(Vec::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,
}],
ret: primitives.int32,
vars: VarMap::new(),
};
let fun_ty = unifier.add_ty(TypeEnum::TFunc(signature.clone()));
let mut store = ConcreteTypeStore::new();
let mut cache = HashMap::new();
let signature = store.from_signature(&mut unifier, &primitives, &signature, &mut cache);
let signature = store.add_cty(signature);
let foo_id = top_level.definitions.read().len();
top_level.definitions.write().push(Arc::new(RwLock::new(TopLevelDef::Function {
name: "foo".to_string(),
simple_name: "foo".into(),
signature: fun_ty,
var_id: vec![],
instance_to_stmt: HashMap::new(),
instance_to_symbol: HashMap::new(),
resolver: None,
codegen_callback: None,
loc: None,
})));
let resolver = Resolver { id_to_type: HashMap::new(), id_to_def: RwLock::new(HashMap::new()) };
resolver.add_id_def("foo".into(), DefinitionId(foo_id));
let resolver = Arc::new(resolver) as Arc<dyn SymbolResolver + Send + Sync>;
if let TopLevelDef::Function { resolver: r, .. } =
&mut *top_level.definitions.read()[foo_id].write()
{
*r = Some(resolver.clone());
} else {
unreachable!()
}
let threads = vec![DefaultCodeGenerator::new("test".into(), 32).into()];
let mut function_data = FunctionData {
resolver: resolver.clone(),
bound_variables: Vec::new(),
return_type: Some(primitives.int32),
};
let mut virtual_checks = Vec::new();
let mut calls = HashMap::new();
let mut identifiers: HashMap<_, _> =
["a".into(), "foo".into()].map(|id| (id, IdentifierInfo::default())).into();
let mut inferencer = Inferencer {
top_level: &top_level,
function_data: &mut function_data,
unifier: &mut unifier,
variable_mapping: HashMap::default(),
primitives: &primitives,
virtual_checks: &mut virtual_checks,
calls: &mut calls,
defined_identifiers: identifiers.clone(),
in_handler: false,
};
inferencer.variable_mapping.insert("a".into(), inferencer.primitives.int32);
inferencer.variable_mapping.insert("foo".into(), fun_ty);
let statements_1 = statements_1
.into_iter()
.map(|v| inferencer.fold_stmt(v))
.collect::<Result<Vec<_>, _>>()
.unwrap();
let calls1 = inferencer.calls.clone();
inferencer.calls.clear();
let statements_2 = statements_2
.into_iter()
.map(|v| inferencer.fold_stmt(v))
.collect::<Result<Vec<_>, _>>()
.unwrap();
if let TopLevelDef::Function { instance_to_stmt, .. } =
&mut *top_level.definitions.read()[foo_id].write()
{
instance_to_stmt.insert(
String::new(),
FunInstance {
body: Arc::new(statements_2),
calls: Arc::new(inferencer.calls.clone()),
subst: IndexMap::default(),
unifier_id: 0,
},
);
} else {
unreachable!()
}
inferencer.check_block(&statements_1, &mut identifiers).unwrap();
let top_level = Arc::new(TopLevelContext {
definitions: Arc::new(RwLock::new(std::mem::take(&mut *top_level.definitions.write()))),
unifiers: Arc::new(RwLock::new(vec![(unifier.get_shared_unifier(), primitives)])),
personality_symbol: None,
});
let task = CodeGenTask {
subst: Vec::default(),
symbol_name: "testing".to_string(),
body: Arc::new(statements_1),
calls: Arc::new(calls1),
unifier_index: 0,
resolver,
signature,
store,
id: 0,
};
let f = Arc::new(WithCall::new(Box::new(|module| {
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 {
init:
%add.i = shl i32 %0, 1, !dbg !10
%mul = add i32 %add.i, 2, !dbg !10
ret i32 %mul, !dbg !10
}
; Function Attrs: mustprogress nofree norecurse nosync nounwind readnone willreturn
define i32 @foo.0(i32 %0) local_unnamed_addr #0 !dbg !11 {
init:
%add = add i32 %0, 1, !dbg !12
ret i32 %add, !dbg !12
}
attributes #0 = { mustprogress nofree norecurse nosync nounwind readnone willreturn }
!llvm.module.flags = !{!0, !1}
!llvm.dbg.cu = !{!2, !4}
!0 = !{i32 2, !\"Debug Info Version\", i32 3}
!1 = !{i32 2, !\"Dwarf Version\", i32 4}
!2 = distinct !DICompileUnit(language: DW_LANG_Python, file: !3, producer: \"NAC3\", isOptimized: true, runtimeVersion: 0, emissionKind: FullDebug)
!3 = !DIFile(filename: \"unknown\", directory: \"\")
!4 = distinct !DICompileUnit(language: DW_LANG_Python, file: !3, producer: \"NAC3\", isOptimized: true, runtimeVersion: 0, emissionKind: FullDebug)
!5 = distinct !DISubprogram(name: \"testing\", linkageName: \"testing\", scope: null, file: !3, line: 1, type: !6, scopeLine: 1, flags: DIFlagPublic, spFlags: DISPFlagDefinition | DISPFlagOptimized, unit: !2, retainedNodes: !9)
!6 = !DISubroutineType(flags: DIFlagPublic, types: !7)
!7 = !{!8}
!8 = !DIBasicType(name: \"_\", flags: DIFlagPublic)
!9 = !{}
!10 = !DILocation(line: 2, column: 12, scope: !5)
!11 = distinct !DISubprogram(name: \"foo.0\", linkageName: \"foo.0\", scope: null, file: !3, line: 1, type: !6, scopeLine: 1, flags: DIFlagPublic, spFlags: DISPFlagDefinition | DISPFlagOptimized, unit: !4, retainedNodes: !9)
!12 = !DILocation(line: 1, column: 12, scope: !11)
"}
.trim();
assert_eq!(expected, module.print_to_string().to_str().unwrap().trim());
})));
Target::initialize_all(&InitializationConfig::default());
let llvm_options = CodeGenLLVMOptions {
opt_level: OptimizationLevel::Default,
target: CodeGenTargetMachineOptions::from_host_triple(),
};
let (registry, handles) = WorkerRegistry::create_workers(threads, top_level, &llvm_options, &f);
registry.add_task(task);
registry.wait_tasks_complete(handles);
}
#[test]
fn test_classes_list_type_new() {
let ctx = inkwell::context::Context::create();
let generator = DefaultCodeGenerator::new(String::new(), 64);
let llvm_i32 = ctx.i32_type();
let llvm_usize = generator.get_size_type(&ctx);
let llvm_list = ListType::new(&generator, &ctx, llvm_i32.into());
assert!(ListType::is_representable(llvm_list.as_base_type(), llvm_usize).is_ok());
}
#[test]
fn test_classes_range_type_new() {
let ctx = inkwell::context::Context::create();
let llvm_range = RangeType::new(&ctx);
assert!(RangeType::is_representable(llvm_range.as_base_type()).is_ok());
}
#[test]
fn test_classes_ndarray_type_new() {
let ctx = inkwell::context::Context::create();
let generator = DefaultCodeGenerator::new(String::new(), 64);
let llvm_i32 = ctx.i32_type();
let llvm_usize = generator.get_size_type(&ctx);
let llvm_ndarray = NDArrayType::new(&generator, &ctx, llvm_i32.into(), 2);
assert!(NDArrayType::is_representable(llvm_ndarray.as_base_type(), llvm_usize).is_ok());
}

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

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

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

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

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

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

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

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

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

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