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d397b9ceaa |
.pre-commit-config.yamlCargo.lockCargo.tomlflake.lockflake.nix
nac3artiq
nac3ast
nac3core
Cargo.tomlbuild.rs
irrt
irrt.cpp
irrt
nac3core_derive
src/codegen
@ -1,24 +1,24 @@
|
||||
# See https://pre-commit.com for more information
|
||||
# See https://pre-commit.com/hooks.html for more hooks
|
||||
|
||||
default_stages: [pre-commit]
|
||||
default_stages: [commit]
|
||||
|
||||
repos:
|
||||
- repo: local
|
||||
hooks:
|
||||
- id: nac3-cargo-fmt
|
||||
name: nac3 cargo format
|
||||
entry: nix
|
||||
entry: cargo
|
||||
language: system
|
||||
types: [file, rust]
|
||||
pass_filenames: false
|
||||
description: Runs cargo fmt on the codebase.
|
||||
args: [develop, -c, cargo, fmt, --all]
|
||||
args: [fmt]
|
||||
- id: nac3-cargo-clippy
|
||||
name: nac3 cargo clippy
|
||||
entry: nix
|
||||
entry: cargo
|
||||
language: system
|
||||
types: [file, rust]
|
||||
pass_filenames: false
|
||||
description: Runs cargo clippy on the codebase.
|
||||
args: [develop, -c, cargo, clippy, --tests]
|
||||
args: [clippy, --tests]
|
||||
|
523
Cargo.lock
generated
523
Cargo.lock
generated
File diff suppressed because it is too large
Load Diff
@ -4,7 +4,6 @@ members = [
|
||||
"nac3ast",
|
||||
"nac3parser",
|
||||
"nac3core",
|
||||
"nac3core/nac3core_derive",
|
||||
"nac3standalone",
|
||||
"nac3artiq",
|
||||
"runkernel",
|
||||
|
6
flake.lock
generated
6
flake.lock
generated
@ -2,11 +2,11 @@
|
||||
"nodes": {
|
||||
"nixpkgs": {
|
||||
"locked": {
|
||||
"lastModified": 1733940404,
|
||||
"narHash": "sha256-Pj39hSoUA86ZePPF/UXiYHHM7hMIkios8TYG29kQT4g=",
|
||||
"lastModified": 1723637854,
|
||||
"narHash": "sha256-med8+5DSWa2UnOqtdICndjDAEjxr5D7zaIiK4pn0Q7c=",
|
||||
"owner": "NixOS",
|
||||
"repo": "nixpkgs",
|
||||
"rev": "5d67ea6b4b63378b9c13be21e2ec9d1afc921713",
|
||||
"rev": "c3aa7b8938b17aebd2deecf7be0636000d62a2b9",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
|
10
flake.nix
10
flake.nix
@ -107,18 +107,18 @@
|
||||
(pkgs.fetchFromGitHub {
|
||||
owner = "m-labs";
|
||||
repo = "sipyco";
|
||||
rev = "094a6cd63ffa980ef63698920170e50dc9ba77fd";
|
||||
sha256 = "sha256-PPnAyDedUQ7Og/Cby9x5OT9wMkNGTP8GS53V6N/dk4w=";
|
||||
rev = "939f84f9b5eef7efbf7423c735d1834783b6140e";
|
||||
sha256 = "sha256-15Nun4EY35j+6SPZkjzZtyH/ncxLS60KuGJjFh5kSTc=";
|
||||
})
|
||||
(pkgs.fetchFromGitHub {
|
||||
owner = "m-labs";
|
||||
repo = "artiq";
|
||||
rev = "28c9de3e251daa89a8c9fd79d5ab64a3ec03bac6";
|
||||
sha256 = "sha256-vAvpbHc5B+1wtG8zqN7j9dQE1ON+i22v+uqA+tw6Gak=";
|
||||
rev = "923ca3377d42c815f979983134ec549dc39d3ca0";
|
||||
sha256 = "sha256-oJoEeNEeNFSUyh6jXG8Tzp6qHVikeHS0CzfE+mODPgw=";
|
||||
})
|
||||
];
|
||||
buildInputs = [
|
||||
(python3-mimalloc.withPackages(ps: [ ps.numpy ps.scipy ps.jsonschema ps.lmdb ps.platformdirs nac3artiq-instrumented ]))
|
||||
(python3-mimalloc.withPackages(ps: [ ps.numpy ps.scipy ps.jsonschema ps.lmdb nac3artiq-instrumented ]))
|
||||
pkgs.llvmPackages_14.llvm.out
|
||||
];
|
||||
phases = [ "buildPhase" "installPhase" ];
|
||||
|
@ -12,10 +12,16 @@ crate-type = ["cdylib"]
|
||||
itertools = "0.13"
|
||||
pyo3 = { version = "0.21", features = ["extension-module", "gil-refs"] }
|
||||
parking_lot = "0.12"
|
||||
tempfile = "3.13"
|
||||
tempfile = "3.10"
|
||||
nac3parser = { path = "../nac3parser" }
|
||||
nac3core = { path = "../nac3core" }
|
||||
nac3ld = { path = "../nac3ld" }
|
||||
|
||||
[dependencies.inkwell]
|
||||
version = "0.4"
|
||||
default-features = false
|
||||
features = ["llvm14-0", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]
|
||||
|
||||
[features]
|
||||
init-llvm-profile = []
|
||||
no-escape-analysis = ["nac3core/no-escape-analysis"]
|
||||
|
@ -7,6 +7,33 @@ class EmbeddingMap:
|
||||
self.function_map = {}
|
||||
self.attributes_writeback = []
|
||||
|
||||
# preallocate exception names
|
||||
self.preallocate_runtime_exception_names(["RuntimeError",
|
||||
"RTIOUnderflow",
|
||||
"RTIOOverflow",
|
||||
"RTIODestinationUnreachable",
|
||||
"DMAError",
|
||||
"I2CError",
|
||||
"CacheError",
|
||||
"SPIError",
|
||||
"0:ZeroDivisionError",
|
||||
"0:IndexError",
|
||||
"0:ValueError",
|
||||
"0:RuntimeError",
|
||||
"0:AssertionError",
|
||||
"0:KeyError",
|
||||
"0:NotImplementedError",
|
||||
"0:OverflowError",
|
||||
"0:IOError",
|
||||
"0:UnwrapNoneError"])
|
||||
|
||||
def preallocate_runtime_exception_names(self, names):
|
||||
for i, name in enumerate(names):
|
||||
if ":" not in name:
|
||||
name = "0:artiq.coredevice.exceptions." + name
|
||||
exn_id = self.store_str(name)
|
||||
assert exn_id == i
|
||||
|
||||
def store_function(self, key, fun):
|
||||
self.function_map[key] = fun
|
||||
return key
|
||||
|
@ -112,15 +112,10 @@ def extern(function):
|
||||
register_function(function)
|
||||
return function
|
||||
|
||||
|
||||
def rpc(arg=None, flags={}):
|
||||
"""Decorates a function or method to be executed on the host interpreter."""
|
||||
if arg is None:
|
||||
def inner_decorator(function):
|
||||
return rpc(function, flags)
|
||||
return inner_decorator
|
||||
register_function(arg)
|
||||
return arg
|
||||
def rpc(function):
|
||||
"""Decorates a function declaration defined by the core device runtime."""
|
||||
register_function(function)
|
||||
return function
|
||||
|
||||
def kernel(function_or_method):
|
||||
"""Decorates a function or method to be executed on the core device."""
|
||||
@ -206,7 +201,7 @@ class Core:
|
||||
embedding = EmbeddingMap()
|
||||
|
||||
if allow_registration:
|
||||
compiler.analyze(registered_functions, registered_classes, set())
|
||||
compiler.analyze(registered_functions, registered_classes)
|
||||
allow_registration = False
|
||||
|
||||
if hasattr(method, "__self__"):
|
||||
|
@ -1,3 +1,39 @@
|
||||
use nac3core::{
|
||||
codegen::{
|
||||
classes::{
|
||||
ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayType,
|
||||
NDArrayValue, ProxyType, ProxyValue, RangeValue, UntypedArrayLikeAccessor,
|
||||
},
|
||||
expr::{destructure_range, gen_call},
|
||||
irrt::call_ndarray_calc_size,
|
||||
llvm_intrinsics::{call_int_smax, call_memcpy_generic, call_stackrestore, call_stacksave},
|
||||
stmt::{gen_block, gen_for_callback_incrementing, gen_if_callback, gen_with},
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
symbol_resolver::ValueEnum,
|
||||
toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId, GenCall},
|
||||
typecheck::typedef::{iter_type_vars, FunSignature, FuncArg, Type, TypeEnum, VarMap},
|
||||
};
|
||||
|
||||
use nac3parser::ast::{Expr, ExprKind, Located, Stmt, StmtKind, StrRef};
|
||||
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
module::Linkage,
|
||||
types::{BasicType, IntType},
|
||||
values::{BasicValueEnum, PointerValue, StructValue},
|
||||
AddressSpace, IntPredicate, OptimizationLevel,
|
||||
};
|
||||
|
||||
use pyo3::{
|
||||
types::{PyDict, PyList},
|
||||
PyObject, PyResult, Python,
|
||||
};
|
||||
|
||||
use crate::{symbol_resolver::InnerResolver, timeline::TimeFns};
|
||||
|
||||
use inkwell::values::IntValue;
|
||||
use itertools::Itertools;
|
||||
use std::{
|
||||
collections::{hash_map::DefaultHasher, HashMap},
|
||||
hash::{Hash, Hasher},
|
||||
@ -6,43 +42,6 @@ use std::{
|
||||
sync::Arc,
|
||||
};
|
||||
|
||||
use itertools::Itertools;
|
||||
use pyo3::{
|
||||
types::{PyDict, PyList},
|
||||
PyObject, PyResult, Python,
|
||||
};
|
||||
|
||||
use super::{symbol_resolver::InnerResolver, timeline::TimeFns};
|
||||
use nac3core::{
|
||||
codegen::{
|
||||
expr::{destructure_range, gen_call},
|
||||
llvm_intrinsics::{call_int_smax, call_memcpy, call_stackrestore, call_stacksave},
|
||||
stmt::{gen_block, gen_for_callback_incrementing, gen_if_callback, gen_with},
|
||||
type_aligned_alloca,
|
||||
types::ndarray::NDArrayType,
|
||||
values::{
|
||||
ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, ProxyValue, RangeValue,
|
||||
UntypedArrayLikeAccessor,
|
||||
},
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
inkwell::{
|
||||
context::Context,
|
||||
module::Linkage,
|
||||
types::{BasicType, IntType},
|
||||
values::{BasicValueEnum, IntValue, PointerValue, StructValue},
|
||||
AddressSpace, IntPredicate, OptimizationLevel,
|
||||
},
|
||||
nac3parser::ast::{Expr, ExprKind, Located, Stmt, StmtKind, StrRef},
|
||||
symbol_resolver::ValueEnum,
|
||||
toplevel::{
|
||||
helper::{extract_ndims, PrimDef},
|
||||
numpy::unpack_ndarray_var_tys,
|
||||
DefinitionId, GenCall,
|
||||
},
|
||||
typecheck::typedef::{iter_type_vars, FunSignature, FuncArg, Type, TypeEnum, VarMap},
|
||||
};
|
||||
|
||||
/// The parallelism mode within a block.
|
||||
#[derive(Copy, Clone, Eq, PartialEq)]
|
||||
enum ParallelMode {
|
||||
@ -461,49 +460,52 @@ fn format_rpc_arg<'ctx>(
|
||||
let llvm_i1 = ctx.ctx.bool_type();
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
let (elem_ty, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, arg_ty);
|
||||
let ndims = extract_ndims(&ctx.unifier, ndims);
|
||||
let dtype = ctx.get_llvm_type(generator, elem_ty);
|
||||
let ndarray = NDArrayType::new(generator, ctx.ctx, dtype, Some(ndims))
|
||||
.map_value(arg.into_pointer_value(), None);
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, arg_ty);
|
||||
let llvm_arg_ty =
|
||||
NDArrayType::new(generator, ctx.ctx, ctx.get_llvm_type(generator, elem_ty));
|
||||
let llvm_arg = NDArrayValue::from_ptr_val(arg.into_pointer_value(), llvm_usize, None);
|
||||
|
||||
let ndims = llvm_usize.const_int(ndims, false);
|
||||
let llvm_usize_sizeof = ctx
|
||||
.builder
|
||||
.build_int_truncate_or_bit_cast(llvm_arg_ty.size_type().size_of(), llvm_usize, "")
|
||||
.unwrap();
|
||||
let llvm_pdata_sizeof = ctx
|
||||
.builder
|
||||
.build_int_truncate_or_bit_cast(
|
||||
llvm_arg_ty.element_type().ptr_type(AddressSpace::default()).size_of(),
|
||||
llvm_usize,
|
||||
"",
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
// `ndarray.data` is possibly not contiguous, and we need it to be contiguous for
|
||||
// the reader.
|
||||
// Turning it into a ContiguousNDArray to get a `data` that is contiguous.
|
||||
let carray = ndarray.make_contiguous_ndarray(generator, ctx);
|
||||
let dims_buf_sz =
|
||||
ctx.builder.build_int_mul(llvm_arg.load_ndims(ctx), llvm_usize_sizeof, "").unwrap();
|
||||
|
||||
let sizeof_usize = llvm_usize.size_of();
|
||||
let sizeof_usize =
|
||||
ctx.builder.build_int_z_extend_or_bit_cast(sizeof_usize, llvm_usize, "").unwrap();
|
||||
let buffer_size =
|
||||
ctx.builder.build_int_add(dims_buf_sz, llvm_pdata_sizeof, "").unwrap();
|
||||
|
||||
let sizeof_pdata = dtype.ptr_type(AddressSpace::default()).size_of();
|
||||
let sizeof_pdata =
|
||||
ctx.builder.build_int_z_extend_or_bit_cast(sizeof_pdata, llvm_usize, "").unwrap();
|
||||
let buffer = ctx.builder.build_array_alloca(llvm_i8, buffer_size, "rpc.arg").unwrap();
|
||||
let buffer = ArraySliceValue::from_ptr_val(buffer, buffer_size, Some("rpc.arg"));
|
||||
|
||||
let sizeof_buf_shape = ctx.builder.build_int_mul(sizeof_usize, ndims, "").unwrap();
|
||||
let sizeof_buf = ctx.builder.build_int_add(sizeof_buf_shape, sizeof_pdata, "").unwrap();
|
||||
call_memcpy_generic(
|
||||
ctx,
|
||||
buffer.base_ptr(ctx, generator),
|
||||
llvm_arg.ptr_to_data(ctx),
|
||||
llvm_pdata_sizeof,
|
||||
llvm_i1.const_zero(),
|
||||
);
|
||||
|
||||
// buf = { data: void*, shape: [size_t; ndims]; }
|
||||
let buf = ctx.builder.build_array_alloca(llvm_i8, sizeof_buf, "rpc.arg").unwrap();
|
||||
let buf = ArraySliceValue::from_ptr_val(buf, sizeof_buf, Some("rpc.arg"));
|
||||
let buf_data = buf.base_ptr(ctx, generator);
|
||||
let buf_shape =
|
||||
unsafe { buf.ptr_offset_unchecked(ctx, generator, &sizeof_pdata, None) };
|
||||
let pbuffer_dims_begin =
|
||||
unsafe { buffer.ptr_offset_unchecked(ctx, generator, &llvm_pdata_sizeof, None) };
|
||||
call_memcpy_generic(
|
||||
ctx,
|
||||
pbuffer_dims_begin,
|
||||
llvm_arg.dim_sizes().base_ptr(ctx, generator),
|
||||
dims_buf_sz,
|
||||
llvm_i1.const_zero(),
|
||||
);
|
||||
|
||||
// Write to `buf->data`
|
||||
let carray_data = carray.load_data(ctx);
|
||||
let carray_data = ctx.builder.build_pointer_cast(carray_data, llvm_pi8, "").unwrap();
|
||||
call_memcpy(ctx, buf_data, carray_data, sizeof_pdata, llvm_i1.const_zero());
|
||||
|
||||
// Write to `buf->shape`
|
||||
let carray_shape = ndarray.shape().base_ptr(ctx, generator);
|
||||
let carray_shape_i8 =
|
||||
ctx.builder.build_pointer_cast(carray_shape, llvm_pi8, "").unwrap();
|
||||
call_memcpy(ctx, buf_shape, carray_shape_i8, sizeof_buf_shape, llvm_i1.const_zero());
|
||||
|
||||
buf.base_ptr(ctx, generator)
|
||||
buffer.base_ptr(ctx, generator)
|
||||
}
|
||||
|
||||
_ => {
|
||||
@ -513,7 +515,7 @@ fn format_rpc_arg<'ctx>(
|
||||
ctx.builder.build_store(arg_slot, arg).unwrap();
|
||||
|
||||
ctx.builder
|
||||
.build_bit_cast(arg_slot, llvm_pi8, "rpc.arg")
|
||||
.build_bitcast(arg_slot, llvm_pi8, "rpc.arg")
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap()
|
||||
}
|
||||
@ -544,8 +546,6 @@ fn format_rpc_ret<'ctx>(
|
||||
let llvm_i32 = ctx.ctx.i32_type();
|
||||
let llvm_i8_8 = ctx.ctx.struct_type(&[llvm_i8.array_type(8).into()], false);
|
||||
let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
|
||||
|
||||
let rpc_recv = ctx.module.get_function("rpc_recv").unwrap_or_else(|| {
|
||||
ctx.module.add_function("rpc_recv", llvm_i32.fn_type(&[llvm_pi8.into()], false), None)
|
||||
@ -566,7 +566,8 @@ fn format_rpc_ret<'ctx>(
|
||||
|
||||
let result = match &*ctx.unifier.get_ty_immutable(ret_ty) {
|
||||
TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
|
||||
let num_0 = llvm_usize.const_zero();
|
||||
let llvm_i1 = ctx.ctx.bool_type();
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
// Round `val` up to its modulo `power_of_two`
|
||||
let round_up = |ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
@ -592,49 +593,79 @@ fn format_rpc_ret<'ctx>(
|
||||
.unwrap()
|
||||
};
|
||||
|
||||
// Setup types
|
||||
let (elem_ty, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, ret_ty);
|
||||
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
let llvm_ret_ty = NDArrayType::new(generator, ctx.ctx, llvm_elem_ty);
|
||||
|
||||
// Allocate the resulting ndarray
|
||||
// A condition after format_rpc_ret ensures this will not be popped this off.
|
||||
let (dtype, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, ret_ty);
|
||||
let dtype_llvm = ctx.get_llvm_type(generator, dtype);
|
||||
let ndims = extract_ndims(&ctx.unifier, ndims);
|
||||
let ndarray = NDArrayType::new(generator, ctx.ctx, dtype_llvm, Some(ndims))
|
||||
.construct_uninitialized(generator, ctx, None);
|
||||
let ndarray = llvm_ret_ty.new_value(generator, ctx, Some("rpc.result"));
|
||||
|
||||
// NOTE: Current content of `ndarray`:
|
||||
// - * `data` - **NOT YET** allocated.
|
||||
// - * `itemsize` - initialized to be size_of(dtype).
|
||||
// - * `ndims` - initialized.
|
||||
// - * `shape` - allocated; has uninitialized values.
|
||||
// - * `strides` - allocated; has uninitialized values.
|
||||
// Setup ndims
|
||||
let ndims =
|
||||
if let TypeEnum::TLiteral { values, .. } = &*ctx.unifier.get_ty_immutable(ndims) {
|
||||
assert_eq!(values.len(), 1);
|
||||
|
||||
let itemsize = ndarray.load_itemsize(ctx); // Same as doing a `ctx.get_llvm_type` on `dtype` and get its `size_of()`.
|
||||
u64::try_from(values[0].clone()).unwrap()
|
||||
} else {
|
||||
unreachable!();
|
||||
};
|
||||
// Set `ndarray.ndims`
|
||||
ndarray.store_ndims(ctx, generator, llvm_usize.const_int(ndims, false));
|
||||
// Allocate `ndarray.shape` [size_t; ndims]
|
||||
ndarray.create_dim_sizes(ctx, llvm_usize, ndarray.load_ndims(ctx));
|
||||
|
||||
/*
|
||||
ndarray now:
|
||||
- .ndims: initialized
|
||||
- .shape: allocated but uninitialized .shape
|
||||
- .data: uninitialized
|
||||
*/
|
||||
|
||||
let llvm_usize_sizeof = ctx
|
||||
.builder
|
||||
.build_int_truncate_or_bit_cast(llvm_usize.size_of(), llvm_usize, "")
|
||||
.unwrap();
|
||||
let llvm_pdata_sizeof = ctx
|
||||
.builder
|
||||
.build_int_truncate_or_bit_cast(
|
||||
llvm_ret_ty.element_type().size_of().unwrap(),
|
||||
llvm_usize,
|
||||
"",
|
||||
)
|
||||
.unwrap();
|
||||
let llvm_elem_sizeof = ctx
|
||||
.builder
|
||||
.build_int_truncate_or_bit_cast(llvm_elem_ty.size_of().unwrap(), llvm_usize, "")
|
||||
.unwrap();
|
||||
|
||||
// Allocates a buffer for the initial RPC'ed object, which is guaranteed to be
|
||||
// (4 + 4 * ndims) bytes with 8-byte alignment
|
||||
let sizeof_usize = llvm_usize.size_of();
|
||||
let sizeof_usize =
|
||||
ctx.builder.build_int_truncate_or_bit_cast(sizeof_usize, llvm_usize, "").unwrap();
|
||||
|
||||
let sizeof_ptr = llvm_i8.ptr_type(AddressSpace::default()).size_of();
|
||||
let sizeof_ptr =
|
||||
ctx.builder.build_int_z_extend_or_bit_cast(sizeof_ptr, llvm_usize, "").unwrap();
|
||||
|
||||
let sizeof_shape =
|
||||
ctx.builder.build_int_mul(ndarray.load_ndims(ctx), sizeof_usize, "").unwrap();
|
||||
|
||||
// Size of the buffer for the initial `rpc_recv()`.
|
||||
let sizeof_dims =
|
||||
ctx.builder.build_int_mul(ndarray.load_ndims(ctx), llvm_usize_sizeof, "").unwrap();
|
||||
let unaligned_buffer_size =
|
||||
ctx.builder.build_int_add(sizeof_ptr, sizeof_shape, "").unwrap();
|
||||
ctx.builder.build_int_add(sizeof_dims, llvm_pdata_sizeof, "").unwrap();
|
||||
let buffer_size = round_up(ctx, unaligned_buffer_size, llvm_usize.const_int(8, false));
|
||||
|
||||
let stackptr = call_stacksave(ctx, None);
|
||||
let buffer = type_aligned_alloca(
|
||||
generator,
|
||||
ctx,
|
||||
llvm_i8_8,
|
||||
unaligned_buffer_size,
|
||||
Some("rpc.buffer"),
|
||||
);
|
||||
let buffer = ArraySliceValue::from_ptr_val(buffer, unaligned_buffer_size, None);
|
||||
// Just to be absolutely sure, alloca in [i8 x 8] slices to force 8-byte alignment
|
||||
let buffer = ctx
|
||||
.builder
|
||||
.build_array_alloca(
|
||||
llvm_i8_8,
|
||||
ctx.builder
|
||||
.build_int_unsigned_div(buffer_size, llvm_usize.const_int(8, false), "")
|
||||
.unwrap(),
|
||||
"rpc.buffer",
|
||||
)
|
||||
.unwrap();
|
||||
let buffer = ctx
|
||||
.builder
|
||||
.build_bitcast(buffer, llvm_pi8, "")
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap();
|
||||
let buffer = ArraySliceValue::from_ptr_val(buffer, buffer_size, None);
|
||||
|
||||
// The first call to `rpc_recv` reads the top-level ndarray object: [pdata, shape]
|
||||
//
|
||||
@ -642,7 +673,7 @@ fn format_rpc_ret<'ctx>(
|
||||
let ndarray_nbytes = ctx
|
||||
.build_call_or_invoke(
|
||||
rpc_recv,
|
||||
&[buffer.base_ptr(ctx, generator).into()], // Reads [usize; ndims]
|
||||
&[buffer.base_ptr(ctx, generator).into()], // Reads [usize; ndims]. NOTE: We are allocated [size_t; ndims].
|
||||
"rpc.size.next",
|
||||
)
|
||||
.map(BasicValueEnum::into_int_value)
|
||||
@ -650,14 +681,16 @@ fn format_rpc_ret<'ctx>(
|
||||
|
||||
// debug_assert(ndarray_nbytes > 0)
|
||||
if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
|
||||
let cmp = ctx
|
||||
.builder
|
||||
.build_int_compare(IntPredicate::UGT, ndarray_nbytes, num_0, "")
|
||||
.unwrap();
|
||||
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
cmp,
|
||||
ctx.builder
|
||||
.build_int_compare(
|
||||
IntPredicate::UGT,
|
||||
ndarray_nbytes,
|
||||
ndarray_nbytes.get_type().const_zero(),
|
||||
"",
|
||||
)
|
||||
.unwrap(),
|
||||
"0:AssertionError",
|
||||
"Unexpected RPC termination for ndarray - Expected data buffer next",
|
||||
[None, None, None],
|
||||
@ -666,50 +699,49 @@ fn format_rpc_ret<'ctx>(
|
||||
}
|
||||
|
||||
// Copy shape from the buffer to `ndarray.shape`.
|
||||
// We need to skip the first `sizeof(uint8_t*)` bytes to skip the `pdata` in `[pdata, shape]`.
|
||||
let pbuffer_shape =
|
||||
unsafe { buffer.ptr_offset_unchecked(ctx, generator, &sizeof_ptr, None) };
|
||||
let pbuffer_shape =
|
||||
ctx.builder.build_pointer_cast(pbuffer_shape, llvm_pusize, "").unwrap();
|
||||
|
||||
// Copy shape from buffer to `ndarray.shape`
|
||||
ndarray.copy_shape_from_array(generator, ctx, pbuffer_shape);
|
||||
let pbuffer_dims =
|
||||
unsafe { buffer.ptr_offset_unchecked(ctx, generator, &llvm_pdata_sizeof, None) };
|
||||
|
||||
call_memcpy_generic(
|
||||
ctx,
|
||||
ndarray.dim_sizes().base_ptr(ctx, generator),
|
||||
pbuffer_dims,
|
||||
sizeof_dims,
|
||||
llvm_i1.const_zero(),
|
||||
);
|
||||
// Restore stack from before allocation of buffer
|
||||
call_stackrestore(ctx, stackptr);
|
||||
|
||||
// Allocate `ndarray.data`.
|
||||
// `ndarray.shape` must be initialized beforehand in this implementation
|
||||
// (for ndarray.create_data() to know how many elements to allocate)
|
||||
unsafe { ndarray.create_data(generator, ctx) }; // NOTE: the strides of `ndarray` has also been set to contiguous in `create_data`.
|
||||
let num_elements =
|
||||
call_ndarray_calc_size(generator, ctx, &ndarray.dim_sizes(), (None, None));
|
||||
|
||||
// debug_assert(nelems * sizeof(T) >= ndarray_nbytes)
|
||||
if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
|
||||
let num_elements = ndarray.size(generator, ctx);
|
||||
|
||||
let expected_ndarray_nbytes =
|
||||
ctx.builder.build_int_mul(num_elements, itemsize, "").unwrap();
|
||||
let cmp = ctx
|
||||
.builder
|
||||
.build_int_compare(
|
||||
IntPredicate::UGE,
|
||||
expected_ndarray_nbytes,
|
||||
ndarray_nbytes,
|
||||
"",
|
||||
)
|
||||
.unwrap();
|
||||
let sizeof_data =
|
||||
ctx.builder.build_int_mul(num_elements, llvm_elem_sizeof, "").unwrap();
|
||||
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
cmp,
|
||||
ctx.builder.build_int_compare(IntPredicate::UGE,
|
||||
sizeof_data,
|
||||
ndarray_nbytes,
|
||||
"",
|
||||
).unwrap(),
|
||||
"0:AssertionError",
|
||||
"Unexpected allocation size request for ndarray data - Expected up to {0} bytes, got {1} bytes",
|
||||
[Some(expected_ndarray_nbytes), Some(ndarray_nbytes), None],
|
||||
[Some(sizeof_data), Some(ndarray_nbytes), None],
|
||||
ctx.current_loc,
|
||||
);
|
||||
}
|
||||
|
||||
ndarray.create_data(ctx, llvm_elem_ty, num_elements);
|
||||
|
||||
let ndarray_data = ndarray.data().base_ptr(ctx, generator);
|
||||
let ndarray_data_i8 =
|
||||
ctx.builder.build_pointer_cast(ndarray_data, llvm_pi8, "").unwrap();
|
||||
|
||||
// NOTE: Currently on `prehead_bb`
|
||||
ctx.builder.build_unconditional_branch(head_bb).unwrap();
|
||||
@ -718,7 +750,7 @@ fn format_rpc_ret<'ctx>(
|
||||
ctx.builder.position_at_end(head_bb);
|
||||
|
||||
let phi = ctx.builder.build_phi(llvm_pi8, "rpc.ptr").unwrap();
|
||||
phi.add_incoming(&[(&ndarray_data, prehead_bb)]);
|
||||
phi.add_incoming(&[(&ndarray_data_i8, prehead_bb)]);
|
||||
|
||||
let alloc_size = ctx
|
||||
.build_call_or_invoke(rpc_recv, &[phi.as_basic_value()], "rpc.size.next")
|
||||
@ -733,13 +765,12 @@ fn format_rpc_ret<'ctx>(
|
||||
|
||||
ctx.builder.position_at_end(alloc_bb);
|
||||
// Align the allocation to sizeof(T)
|
||||
let alloc_size = round_up(ctx, alloc_size, itemsize);
|
||||
// TODO(Derppening): Candidate for refactor into type_aligned_alloca
|
||||
let alloc_size = round_up(ctx, alloc_size, llvm_elem_sizeof);
|
||||
let alloc_ptr = ctx
|
||||
.builder
|
||||
.build_array_alloca(
|
||||
dtype_llvm,
|
||||
ctx.builder.build_int_unsigned_div(alloc_size, itemsize, "").unwrap(),
|
||||
llvm_elem_ty,
|
||||
ctx.builder.build_int_unsigned_div(alloc_size, llvm_elem_sizeof, "").unwrap(),
|
||||
"rpc.alloc",
|
||||
)
|
||||
.unwrap();
|
||||
@ -754,7 +785,7 @@ fn format_rpc_ret<'ctx>(
|
||||
|
||||
_ => {
|
||||
let slot = ctx.builder.build_alloca(llvm_ret_ty, "rpc.ret.slot").unwrap();
|
||||
let slotgen = ctx.builder.build_bit_cast(slot, llvm_pi8, "rpc.ret.ptr").unwrap();
|
||||
let slotgen = ctx.builder.build_bitcast(slot, llvm_pi8, "rpc.ret.ptr").unwrap();
|
||||
ctx.builder.build_unconditional_branch(head_bb).unwrap();
|
||||
ctx.builder.position_at_end(head_bb);
|
||||
|
||||
@ -775,7 +806,7 @@ fn format_rpc_ret<'ctx>(
|
||||
let alloc_ptr =
|
||||
ctx.builder.build_array_alloca(llvm_pi8, alloc_size, "rpc.alloc").unwrap();
|
||||
let alloc_ptr =
|
||||
ctx.builder.build_bit_cast(alloc_ptr, llvm_pi8, "rpc.alloc.ptr").unwrap();
|
||||
ctx.builder.build_bitcast(alloc_ptr, llvm_pi8, "rpc.alloc.ptr").unwrap();
|
||||
phi.add_incoming(&[(&alloc_ptr, alloc_bb)]);
|
||||
ctx.builder.build_unconditional_branch(head_bb).unwrap();
|
||||
|
||||
@ -793,7 +824,6 @@ fn rpc_codegen_callback_fn<'ctx>(
|
||||
fun: (&FunSignature, DefinitionId),
|
||||
args: Vec<(Option<StrRef>, ValueEnum<'ctx>)>,
|
||||
generator: &mut dyn CodeGenerator,
|
||||
is_async: bool,
|
||||
) -> Result<Option<BasicValueEnum<'ctx>>, String> {
|
||||
let int8 = ctx.ctx.i8_type();
|
||||
let int32 = ctx.ctx.i32_type();
|
||||
@ -902,72 +932,42 @@ fn rpc_codegen_callback_fn<'ctx>(
|
||||
}
|
||||
|
||||
// call
|
||||
if is_async {
|
||||
let rpc_send_async = ctx.module.get_function("rpc_send_async").unwrap_or_else(|| {
|
||||
ctx.module.add_function(
|
||||
"rpc_send_async",
|
||||
ctx.ctx.void_type().fn_type(
|
||||
&[
|
||||
int32.into(),
|
||||
tag_ptr_type.ptr_type(AddressSpace::default()).into(),
|
||||
ptr_type.ptr_type(AddressSpace::default()).into(),
|
||||
],
|
||||
false,
|
||||
),
|
||||
None,
|
||||
)
|
||||
});
|
||||
ctx.builder
|
||||
.build_call(
|
||||
rpc_send_async,
|
||||
&[service_id.into(), tag_ptr.into(), args_ptr.into()],
|
||||
"rpc.send",
|
||||
)
|
||||
.unwrap();
|
||||
} else {
|
||||
let rpc_send = ctx.module.get_function("rpc_send").unwrap_or_else(|| {
|
||||
ctx.module.add_function(
|
||||
"rpc_send",
|
||||
ctx.ctx.void_type().fn_type(
|
||||
&[
|
||||
int32.into(),
|
||||
tag_ptr_type.ptr_type(AddressSpace::default()).into(),
|
||||
ptr_type.ptr_type(AddressSpace::default()).into(),
|
||||
],
|
||||
false,
|
||||
),
|
||||
None,
|
||||
)
|
||||
});
|
||||
ctx.builder
|
||||
.build_call(rpc_send, &[service_id.into(), tag_ptr.into(), args_ptr.into()], "rpc.send")
|
||||
.unwrap();
|
||||
}
|
||||
let rpc_send = ctx.module.get_function("rpc_send").unwrap_or_else(|| {
|
||||
ctx.module.add_function(
|
||||
"rpc_send",
|
||||
ctx.ctx.void_type().fn_type(
|
||||
&[
|
||||
int32.into(),
|
||||
tag_ptr_type.ptr_type(AddressSpace::default()).into(),
|
||||
ptr_type.ptr_type(AddressSpace::default()).into(),
|
||||
],
|
||||
false,
|
||||
),
|
||||
None,
|
||||
)
|
||||
});
|
||||
ctx.builder
|
||||
.build_call(rpc_send, &[service_id.into(), tag_ptr.into(), args_ptr.into()], "rpc.send")
|
||||
.unwrap();
|
||||
|
||||
// reclaim stack space used by arguments
|
||||
call_stackrestore(ctx, stackptr);
|
||||
|
||||
if is_async {
|
||||
// async RPCs do not return any values
|
||||
Ok(None)
|
||||
} else {
|
||||
let result = format_rpc_ret(generator, ctx, fun.0.ret);
|
||||
let result = format_rpc_ret(generator, ctx, fun.0.ret);
|
||||
|
||||
if !result.is_some_and(|res| res.get_type().is_pointer_type()) {
|
||||
// An RPC returning an NDArray would not touch here.
|
||||
call_stackrestore(ctx, stackptr);
|
||||
}
|
||||
|
||||
Ok(result)
|
||||
if !result.is_some_and(|res| res.get_type().is_pointer_type()) {
|
||||
// An RPC returning an NDArray would not touch here.
|
||||
call_stackrestore(ctx, stackptr);
|
||||
}
|
||||
|
||||
Ok(result)
|
||||
}
|
||||
|
||||
pub fn attributes_writeback<'ctx>(
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
pub fn attributes_writeback(
|
||||
ctx: &mut CodeGenContext<'_, '_>,
|
||||
generator: &mut dyn CodeGenerator,
|
||||
inner_resolver: &InnerResolver,
|
||||
host_attributes: &PyObject,
|
||||
return_obj: Option<(Type, ValueEnum<'ctx>)>,
|
||||
) -> Result<(), String> {
|
||||
Python::with_gil(|py| -> PyResult<Result<(), String>> {
|
||||
let host_attributes: &PyList = host_attributes.downcast(py)?;
|
||||
@ -977,11 +977,6 @@ pub fn attributes_writeback<'ctx>(
|
||||
let zero = int32.const_zero();
|
||||
let mut values = Vec::new();
|
||||
let mut scratch_buffer = Vec::new();
|
||||
|
||||
if let Some((ty, obj)) = return_obj {
|
||||
values.push((ty, obj.to_basic_value_enum(ctx, generator, ty).unwrap()));
|
||||
}
|
||||
|
||||
for val in (*globals).values() {
|
||||
let val = val.as_ref(py);
|
||||
let ty = inner_resolver.get_obj_type(
|
||||
@ -1060,7 +1055,7 @@ pub fn attributes_writeback<'ctx>(
|
||||
let args: Vec<_> =
|
||||
values.into_iter().map(|(_, val)| (None, ValueEnum::Dynamic(val))).collect();
|
||||
if let Err(e) =
|
||||
rpc_codegen_callback_fn(ctx, None, (&fun, PrimDef::Int32.id()), args, generator, true)
|
||||
rpc_codegen_callback_fn(ctx, None, (&fun, PrimDef::Int32.id()), args, generator)
|
||||
{
|
||||
return Ok(Err(e));
|
||||
}
|
||||
@ -1070,9 +1065,9 @@ pub fn attributes_writeback<'ctx>(
|
||||
Ok(())
|
||||
}
|
||||
|
||||
pub fn rpc_codegen_callback(is_async: bool) -> Arc<GenCall> {
|
||||
Arc::new(GenCall::new(Box::new(move |ctx, obj, fun, args, generator| {
|
||||
rpc_codegen_callback_fn(ctx, obj, fun, args, generator, is_async)
|
||||
pub fn rpc_codegen_callback() -> Arc<GenCall> {
|
||||
Arc::new(GenCall::new(Box::new(|ctx, obj, fun, args, generator| {
|
||||
rpc_codegen_callback_fn(ctx, obj, fun, args, generator)
|
||||
})))
|
||||
}
|
||||
|
||||
@ -1286,8 +1281,7 @@ fn polymorphic_print<'ctx>(
|
||||
fmt.push('[');
|
||||
flush(ctx, generator, &mut fmt, &mut args);
|
||||
|
||||
let val =
|
||||
ListValue::from_pointer_value(value.into_pointer_value(), llvm_usize, None);
|
||||
let val = ListValue::from_ptr_val(value.into_pointer_value(), llvm_usize, None);
|
||||
let len = val.load_size(ctx, None);
|
||||
let last =
|
||||
ctx.builder.build_int_sub(len, llvm_usize.const_int(1, false), "").unwrap();
|
||||
@ -1338,50 +1332,56 @@ fn polymorphic_print<'ctx>(
|
||||
}
|
||||
|
||||
TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
|
||||
|
||||
fmt.push_str("array([");
|
||||
flush(ctx, generator, &mut fmt, &mut args);
|
||||
|
||||
let (dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
|
||||
let ndarray = NDArrayType::from_unifier_type(generator, ctx, ty)
|
||||
.map_value(value.into_pointer_value(), None);
|
||||
let val = NDArrayValue::from_ptr_val(value.into_pointer_value(), llvm_usize, None);
|
||||
let len = call_ndarray_calc_size(generator, ctx, &val.dim_sizes(), (None, None));
|
||||
let last =
|
||||
ctx.builder.build_int_sub(len, llvm_usize.const_int(1, false), "").unwrap();
|
||||
|
||||
let num_0 = llvm_usize.const_zero();
|
||||
gen_for_callback_incrementing(
|
||||
generator,
|
||||
ctx,
|
||||
None,
|
||||
llvm_usize.const_zero(),
|
||||
(len, false),
|
||||
|generator, ctx, _, i| {
|
||||
let elem = unsafe { val.data().get_unchecked(ctx, generator, &i, None) };
|
||||
|
||||
// Print `ndarray` as a flat list delimited by interspersed with ", \0"
|
||||
ndarray.foreach(generator, ctx, |generator, ctx, _, hdl| {
|
||||
let i = hdl.get_index(ctx);
|
||||
let scalar = hdl.get_scalar(ctx);
|
||||
polymorphic_print(
|
||||
ctx,
|
||||
generator,
|
||||
&[(elem_ty, elem.into())],
|
||||
"",
|
||||
None,
|
||||
true,
|
||||
as_rtio,
|
||||
)?;
|
||||
|
||||
// if (i != 0) puts(", ");
|
||||
gen_if_callback(
|
||||
generator,
|
||||
ctx,
|
||||
|_, ctx| {
|
||||
let not_first = ctx
|
||||
.builder
|
||||
.build_int_compare(IntPredicate::NE, i, num_0, "")
|
||||
.unwrap();
|
||||
Ok(not_first)
|
||||
},
|
||||
|generator, ctx| {
|
||||
printf(ctx, generator, ", \0".into(), Vec::default());
|
||||
Ok(())
|
||||
},
|
||||
|_, _| Ok(()),
|
||||
)?;
|
||||
gen_if_callback(
|
||||
generator,
|
||||
ctx,
|
||||
|_, ctx| {
|
||||
Ok(ctx
|
||||
.builder
|
||||
.build_int_compare(IntPredicate::ULT, i, last, "")
|
||||
.unwrap())
|
||||
},
|
||||
|generator, ctx| {
|
||||
printf(ctx, generator, ", \0".into(), Vec::default());
|
||||
|
||||
// Print element
|
||||
polymorphic_print(
|
||||
ctx,
|
||||
generator,
|
||||
&[(dtype, scalar.into())],
|
||||
"",
|
||||
None,
|
||||
true,
|
||||
as_rtio,
|
||||
)?;
|
||||
Ok(())
|
||||
})?;
|
||||
Ok(())
|
||||
},
|
||||
|_, _| Ok(()),
|
||||
)?;
|
||||
|
||||
Ok(())
|
||||
},
|
||||
llvm_usize.const_int(1, false),
|
||||
)?;
|
||||
|
||||
fmt.push_str(")]");
|
||||
flush(ctx, generator, &mut fmt, &mut args);
|
||||
@ -1391,7 +1391,7 @@ fn polymorphic_print<'ctx>(
|
||||
fmt.push_str("range(");
|
||||
flush(ctx, generator, &mut fmt, &mut args);
|
||||
|
||||
let val = RangeValue::from_pointer_value(value.into_pointer_value(), None);
|
||||
let val = RangeValue::from_ptr_val(value.into_pointer_value(), None);
|
||||
|
||||
let (start, stop, step) = destructure_range(ctx, val);
|
||||
|
||||
|
@ -1,4 +1,10 @@
|
||||
#![deny(future_incompatible, let_underscore, nonstandard_style, clippy::all)]
|
||||
#![deny(
|
||||
future_incompatible,
|
||||
let_underscore,
|
||||
nonstandard_style,
|
||||
rust_2024_compatibility,
|
||||
clippy::all
|
||||
)]
|
||||
#![warn(clippy::pedantic)]
|
||||
#![allow(
|
||||
unsafe_op_in_unsafe_fn,
|
||||
@ -10,65 +16,64 @@
|
||||
clippy::wildcard_imports
|
||||
)]
|
||||
|
||||
use std::{
|
||||
collections::{HashMap, HashSet},
|
||||
fs,
|
||||
io::Write,
|
||||
process::Command,
|
||||
rc::Rc,
|
||||
sync::Arc,
|
||||
};
|
||||
use std::collections::{HashMap, HashSet};
|
||||
use std::fs;
|
||||
use std::io::Write;
|
||||
use std::process::Command;
|
||||
use std::rc::Rc;
|
||||
use std::sync::Arc;
|
||||
|
||||
use itertools::Itertools;
|
||||
use parking_lot::{Mutex, RwLock};
|
||||
use pyo3::{
|
||||
create_exception, exceptions,
|
||||
prelude::*,
|
||||
types::{PyBytes, PyDict, PyNone, PySet},
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
memory_buffer::MemoryBuffer,
|
||||
module::{Linkage, Module},
|
||||
passes::PassBuilderOptions,
|
||||
support::is_multithreaded,
|
||||
targets::*,
|
||||
OptimizationLevel,
|
||||
};
|
||||
use tempfile::{self, TempDir};
|
||||
use itertools::Itertools;
|
||||
use nac3core::codegen::{gen_func_impl, CodeGenLLVMOptions, CodeGenTargetMachineOptions};
|
||||
use nac3core::toplevel::builtins::get_exn_constructor;
|
||||
use nac3core::typecheck::typedef::{into_var_map, TypeEnum, Unifier, VarMap};
|
||||
use nac3parser::{
|
||||
ast::{ExprKind, Stmt, StmtKind, StrRef},
|
||||
parser::parse_program,
|
||||
};
|
||||
use pyo3::create_exception;
|
||||
use pyo3::prelude::*;
|
||||
use pyo3::{exceptions, types::PyBytes, types::PyDict, types::PySet};
|
||||
|
||||
use parking_lot::{Mutex, RwLock};
|
||||
|
||||
use nac3core::{
|
||||
codegen::{
|
||||
concrete_type::ConcreteTypeStore, gen_func_impl, irrt::load_irrt, CodeGenLLVMOptions,
|
||||
CodeGenTargetMachineOptions, CodeGenTask, CodeGenerator, WithCall, WorkerRegistry,
|
||||
},
|
||||
inkwell::{
|
||||
context::Context,
|
||||
memory_buffer::MemoryBuffer,
|
||||
module::{FlagBehavior, Linkage, Module},
|
||||
passes::PassBuilderOptions,
|
||||
support::is_multithreaded,
|
||||
targets::*,
|
||||
OptimizationLevel,
|
||||
},
|
||||
nac3parser::{
|
||||
ast::{Constant, ExprKind, Located, Stmt, StmtKind, StrRef},
|
||||
parser::parse_program,
|
||||
},
|
||||
codegen::irrt::load_irrt,
|
||||
codegen::{concrete_type::ConcreteTypeStore, CodeGenTask, WithCall, WorkerRegistry},
|
||||
symbol_resolver::SymbolResolver,
|
||||
toplevel::{
|
||||
builtins::get_exn_constructor,
|
||||
composer::{BuiltinFuncCreator, BuiltinFuncSpec, ComposerConfig, TopLevelComposer},
|
||||
DefinitionId, GenCall, TopLevelDef,
|
||||
},
|
||||
typecheck::{
|
||||
type_inferencer::PrimitiveStore,
|
||||
typedef::{into_var_map, FunSignature, FuncArg, Type, TypeEnum, Unifier, VarMap},
|
||||
},
|
||||
typecheck::typedef::{FunSignature, FuncArg},
|
||||
typecheck::{type_inferencer::PrimitiveStore, typedef::Type},
|
||||
};
|
||||
|
||||
use nac3ld::Linker;
|
||||
|
||||
use codegen::{
|
||||
attributes_writeback, gen_core_log, gen_rtio_log, rpc_codegen_callback, ArtiqCodeGenerator,
|
||||
use crate::{
|
||||
codegen::{
|
||||
attributes_writeback, gen_core_log, gen_rtio_log, rpc_codegen_callback, ArtiqCodeGenerator,
|
||||
},
|
||||
symbol_resolver::{DeferredEvaluationStore, InnerResolver, PythonHelper, Resolver},
|
||||
};
|
||||
use symbol_resolver::{DeferredEvaluationStore, InnerResolver, PythonHelper, Resolver};
|
||||
use timeline::TimeFns;
|
||||
use tempfile::{self, TempDir};
|
||||
|
||||
mod codegen;
|
||||
mod symbol_resolver;
|
||||
mod timeline;
|
||||
|
||||
use timeline::TimeFns;
|
||||
|
||||
#[derive(PartialEq, Clone, Copy)]
|
||||
enum Isa {
|
||||
Host,
|
||||
@ -142,32 +147,14 @@ impl Nac3 {
|
||||
module: &PyObject,
|
||||
registered_class_ids: &HashSet<u64>,
|
||||
) -> PyResult<()> {
|
||||
let (module_name, source_file, source) =
|
||||
Python::with_gil(|py| -> PyResult<(String, String, String)> {
|
||||
let module: &PyAny = module.extract(py)?;
|
||||
let source_file = module.getattr("__file__");
|
||||
let (source_file, source) = if let Ok(source_file) = source_file {
|
||||
let source_file = source_file.extract()?;
|
||||
(
|
||||
source_file,
|
||||
fs::read_to_string(source_file).map_err(|e| {
|
||||
exceptions::PyIOError::new_err(format!(
|
||||
"failed to read input file: {e}"
|
||||
))
|
||||
})?,
|
||||
)
|
||||
} else {
|
||||
// kernels submitted by content have no file
|
||||
// but still can provide source by StringLoader
|
||||
let get_src_fn = module
|
||||
.getattr("__loader__")?
|
||||
.extract::<PyObject>()?
|
||||
.getattr(py, "get_source")?;
|
||||
("<expcontent>", get_src_fn.call1(py, (PyNone::get(py),))?.extract(py)?)
|
||||
};
|
||||
Ok((module.getattr("__name__")?.extract()?, source_file.to_string(), source))
|
||||
})?;
|
||||
let (module_name, source_file) = Python::with_gil(|py| -> PyResult<(String, String)> {
|
||||
let module: &PyAny = module.extract(py)?;
|
||||
Ok((module.getattr("__name__")?.extract()?, module.getattr("__file__")?.extract()?))
|
||||
})?;
|
||||
|
||||
let source = fs::read_to_string(&source_file).map_err(|e| {
|
||||
exceptions::PyIOError::new_err(format!("failed to read input file: {e}"))
|
||||
})?;
|
||||
let parser_result = parse_program(&source, source_file.into())
|
||||
.map_err(|e| exceptions::PySyntaxError::new_err(format!("parse error: {e}")))?;
|
||||
|
||||
@ -207,8 +194,10 @@ impl Nac3 {
|
||||
body.retain(|stmt| {
|
||||
if let StmtKind::FunctionDef { ref decorator_list, .. } = stmt.node {
|
||||
decorator_list.iter().any(|decorator| {
|
||||
if let Some(id) = decorator_id_string(decorator) {
|
||||
id == "kernel" || id == "portable" || id == "rpc"
|
||||
if let ExprKind::Name { id, .. } = decorator.node {
|
||||
id.to_string() == "kernel"
|
||||
|| id.to_string() == "portable"
|
||||
|| id.to_string() == "rpc"
|
||||
} else {
|
||||
false
|
||||
}
|
||||
@ -221,8 +210,9 @@ impl Nac3 {
|
||||
}
|
||||
StmtKind::FunctionDef { ref decorator_list, .. } => {
|
||||
decorator_list.iter().any(|decorator| {
|
||||
if let Some(id) = decorator_id_string(decorator) {
|
||||
id == "extern" || id == "kernel" || id == "portable" || id == "rpc"
|
||||
if let ExprKind::Name { id, .. } = decorator.node {
|
||||
let id = id.to_string();
|
||||
id == "extern" || id == "portable" || id == "kernel" || id == "rpc"
|
||||
} else {
|
||||
false
|
||||
}
|
||||
@ -488,25 +478,9 @@ impl Nac3 {
|
||||
|
||||
match &stmt.node {
|
||||
StmtKind::FunctionDef { decorator_list, .. } => {
|
||||
if decorator_list
|
||||
.iter()
|
||||
.any(|decorator| decorator_id_string(decorator) == Some("rpc".to_string()))
|
||||
{
|
||||
store_fun
|
||||
.call1(
|
||||
py,
|
||||
(
|
||||
def_id.0.into_py(py),
|
||||
module.getattr(py, name.to_string().as_str()).unwrap(),
|
||||
),
|
||||
)
|
||||
.unwrap();
|
||||
let is_async = decorator_list.iter().any(|decorator| {
|
||||
decorator_get_flags(decorator)
|
||||
.iter()
|
||||
.any(|constant| *constant == Constant::Str("async".into()))
|
||||
});
|
||||
rpc_ids.push((None, def_id, is_async));
|
||||
if decorator_list.iter().any(|decorator| matches!(decorator.node, ExprKind::Name { id, .. } if id == "rpc".into())) {
|
||||
store_fun.call1(py, (def_id.0.into_py(py), module.getattr(py, name.to_string().as_str()).unwrap())).unwrap();
|
||||
rpc_ids.push((None, def_id));
|
||||
}
|
||||
}
|
||||
StmtKind::ClassDef { name, body, .. } => {
|
||||
@ -514,26 +488,19 @@ impl Nac3 {
|
||||
let class_obj = module.getattr(py, class_name.as_str()).unwrap();
|
||||
for stmt in body {
|
||||
if let StmtKind::FunctionDef { name, decorator_list, .. } = &stmt.node {
|
||||
if decorator_list.iter().any(|decorator| {
|
||||
decorator_id_string(decorator) == Some("rpc".to_string())
|
||||
}) {
|
||||
let is_async = decorator_list.iter().any(|decorator| {
|
||||
decorator_get_flags(decorator)
|
||||
.iter()
|
||||
.any(|constant| *constant == Constant::Str("async".into()))
|
||||
});
|
||||
if decorator_list.iter().any(|decorator| matches!(decorator.node, ExprKind::Name { id, .. } if id == "rpc".into())) {
|
||||
if name == &"__init__".into() {
|
||||
return Err(CompileError::new_err(format!(
|
||||
"compilation failed\n----------\nThe constructor of class {} should not be decorated with rpc decorator (at {})",
|
||||
class_name, stmt.location
|
||||
)));
|
||||
}
|
||||
rpc_ids.push((Some((class_obj.clone(), *name)), def_id, is_async));
|
||||
rpc_ids.push((Some((class_obj.clone(), *name)), def_id));
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
_ => (),
|
||||
_ => ()
|
||||
}
|
||||
|
||||
let id = *name_to_pyid.get(&name).unwrap();
|
||||
@ -577,7 +544,7 @@ impl Nac3 {
|
||||
field_to_val: RwLock::default(),
|
||||
name_to_pyid,
|
||||
module: module.to_object(py),
|
||||
helper: helper.clone(),
|
||||
helper,
|
||||
string_store: self.string_store.clone(),
|
||||
exception_ids: self.exception_ids.clone(),
|
||||
deferred_eval_store: self.deferred_eval_store.clone(),
|
||||
@ -589,7 +556,7 @@ impl Nac3 {
|
||||
.unwrap();
|
||||
|
||||
// Process IRRT
|
||||
let context = Context::create();
|
||||
let context = inkwell::context::Context::create();
|
||||
let irrt = load_irrt(&context, resolver.as_ref());
|
||||
|
||||
let fun_signature =
|
||||
@ -629,12 +596,13 @@ impl Nac3 {
|
||||
let top_level = Arc::new(composer.make_top_level_context());
|
||||
|
||||
{
|
||||
let rpc_codegen = rpc_codegen_callback();
|
||||
let defs = top_level.definitions.read();
|
||||
for (class_data, id, is_async) in &rpc_ids {
|
||||
for (class_data, id) in &rpc_ids {
|
||||
let mut def = defs[id.0].write();
|
||||
match &mut *def {
|
||||
TopLevelDef::Function { codegen_callback, .. } => {
|
||||
*codegen_callback = Some(rpc_codegen_callback(*is_async));
|
||||
*codegen_callback = Some(rpc_codegen.clone());
|
||||
}
|
||||
TopLevelDef::Class { methods, .. } => {
|
||||
let (class_def, method_name) = class_data.as_ref().unwrap();
|
||||
@ -645,7 +613,7 @@ impl Nac3 {
|
||||
if let TopLevelDef::Function { codegen_callback, .. } =
|
||||
&mut *defs[id.0].write()
|
||||
{
|
||||
*codegen_callback = Some(rpc_codegen_callback(*is_async));
|
||||
*codegen_callback = Some(rpc_codegen.clone());
|
||||
store_fun
|
||||
.call1(
|
||||
py,
|
||||
@ -660,11 +628,6 @@ impl Nac3 {
|
||||
}
|
||||
}
|
||||
}
|
||||
TopLevelDef::Variable { .. } => {
|
||||
return Err(CompileError::new_err(String::from(
|
||||
"Unsupported @rpc annotation on global variable",
|
||||
)))
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -685,12 +648,33 @@ impl Nac3 {
|
||||
let task = CodeGenTask {
|
||||
subst: Vec::default(),
|
||||
symbol_name: "__modinit__".to_string(),
|
||||
body: instance.body,
|
||||
signature,
|
||||
resolver: resolver.clone(),
|
||||
store,
|
||||
unifier_index: instance.unifier_id,
|
||||
calls: instance.calls,
|
||||
id: 0,
|
||||
};
|
||||
|
||||
let mut store = ConcreteTypeStore::new();
|
||||
let mut cache = HashMap::new();
|
||||
let signature = store.from_signature(
|
||||
&mut composer.unifier,
|
||||
&self.primitive,
|
||||
&fun_signature,
|
||||
&mut cache,
|
||||
);
|
||||
let signature = store.add_cty(signature);
|
||||
let attributes_writeback_task = CodeGenTask {
|
||||
subst: Vec::default(),
|
||||
symbol_name: "attributes_writeback".to_string(),
|
||||
body: Arc::new(Vec::default()),
|
||||
signature,
|
||||
resolver,
|
||||
store,
|
||||
unifier_index: instance.unifier_id,
|
||||
calls: instance.calls,
|
||||
calls: Arc::new(HashMap::default()),
|
||||
id: 0,
|
||||
};
|
||||
|
||||
@ -703,7 +687,7 @@ impl Nac3 {
|
||||
let buffer = buffer.as_slice().into();
|
||||
membuffer.lock().push(buffer);
|
||||
})));
|
||||
let size_t = context
|
||||
let size_t = Context::create()
|
||||
.ptr_sized_int_type(&self.get_llvm_target_machine().get_target_data(), None)
|
||||
.get_bit_width();
|
||||
let num_threads = if is_multithreaded() { 4 } else { 1 };
|
||||
@ -714,27 +698,19 @@ impl Nac3 {
|
||||
.collect();
|
||||
|
||||
let membuffer = membuffers.clone();
|
||||
let mut has_return = false;
|
||||
py.allow_threads(|| {
|
||||
let (registry, handles) =
|
||||
WorkerRegistry::create_workers(threads, top_level.clone(), &self.llvm_options, &f);
|
||||
registry.add_task(task);
|
||||
registry.wait_tasks_complete(handles);
|
||||
|
||||
let mut generator = ArtiqCodeGenerator::new("main".to_string(), size_t, self.time_fns);
|
||||
let context = Context::create();
|
||||
let module = context.create_module("main");
|
||||
let mut generator =
|
||||
ArtiqCodeGenerator::new("attributes_writeback".to_string(), size_t, self.time_fns);
|
||||
let context = inkwell::context::Context::create();
|
||||
let module = context.create_module("attributes_writeback");
|
||||
let target_machine = self.llvm_options.create_target_machine().unwrap();
|
||||
module.set_data_layout(&target_machine.get_target_data().get_data_layout());
|
||||
module.set_triple(&target_machine.get_triple());
|
||||
module.add_basic_value_flag(
|
||||
"Debug Info Version",
|
||||
FlagBehavior::Warning,
|
||||
context.i32_type().const_int(3, false),
|
||||
);
|
||||
module.add_basic_value_flag(
|
||||
"Dwarf Version",
|
||||
FlagBehavior::Warning,
|
||||
context.i32_type().const_int(4, false),
|
||||
);
|
||||
let builder = context.create_builder();
|
||||
let (_, module, _) = gen_func_impl(
|
||||
&context,
|
||||
@ -742,27 +718,9 @@ impl Nac3 {
|
||||
®istry,
|
||||
builder,
|
||||
module,
|
||||
task,
|
||||
attributes_writeback_task,
|
||||
|generator, ctx| {
|
||||
assert_eq!(instance.body.len(), 1, "toplevel module should have 1 statement");
|
||||
let StmtKind::Expr { value: ref expr, .. } = instance.body[0].node else {
|
||||
unreachable!("toplevel statement must be an expression")
|
||||
};
|
||||
let ExprKind::Call { .. } = expr.node else {
|
||||
unreachable!("toplevel expression must be a function call")
|
||||
};
|
||||
|
||||
let return_obj =
|
||||
generator.gen_expr(ctx, expr)?.map(|value| (expr.custom.unwrap(), value));
|
||||
has_return = return_obj.is_some();
|
||||
registry.wait_tasks_complete(handles);
|
||||
attributes_writeback(
|
||||
ctx,
|
||||
generator,
|
||||
inner_resolver.as_ref(),
|
||||
&host_attributes,
|
||||
return_obj,
|
||||
)
|
||||
attributes_writeback(ctx, generator, inner_resolver.as_ref(), &host_attributes)
|
||||
},
|
||||
)
|
||||
.unwrap();
|
||||
@ -771,23 +729,35 @@ impl Nac3 {
|
||||
membuffer.lock().push(buffer);
|
||||
});
|
||||
|
||||
embedding_map.setattr("expects_return", has_return).unwrap();
|
||||
|
||||
// Link all modules into `main`.
|
||||
let buffers = membuffers.lock();
|
||||
let main = context
|
||||
.create_module_from_ir(MemoryBuffer::create_from_memory_range(
|
||||
buffers.last().unwrap(),
|
||||
"main",
|
||||
))
|
||||
.create_module_from_ir(MemoryBuffer::create_from_memory_range(&buffers[0], "main"))
|
||||
.unwrap();
|
||||
for buffer in buffers.iter().rev().skip(1) {
|
||||
for buffer in buffers.iter().skip(1) {
|
||||
let other = context
|
||||
.create_module_from_ir(MemoryBuffer::create_from_memory_range(buffer, "main"))
|
||||
.unwrap();
|
||||
|
||||
main.link_in_module(other).map_err(|err| CompileError::new_err(err.to_string()))?;
|
||||
}
|
||||
let builder = context.create_builder();
|
||||
let modinit_return = main
|
||||
.get_function("__modinit__")
|
||||
.unwrap()
|
||||
.get_last_basic_block()
|
||||
.unwrap()
|
||||
.get_terminator()
|
||||
.unwrap();
|
||||
builder.position_before(&modinit_return);
|
||||
builder
|
||||
.build_call(
|
||||
main.get_function("attributes_writeback").unwrap(),
|
||||
&[],
|
||||
"attributes_writeback",
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
main.link_in_module(irrt).map_err(|err| CompileError::new_err(err.to_string()))?;
|
||||
|
||||
let mut function_iter = main.get_first_function();
|
||||
@ -822,20 +792,6 @@ impl Nac3 {
|
||||
panic!("Failed to run optimization for module `main`: {}", err.to_string());
|
||||
}
|
||||
|
||||
Python::with_gil(|py| {
|
||||
let string_store = self.string_store.read();
|
||||
let mut string_store_vec = string_store.iter().collect::<Vec<_>>();
|
||||
string_store_vec.sort_by(|(_s1, key1), (_s2, key2)| key1.cmp(key2));
|
||||
for (s, key) in string_store_vec {
|
||||
let embed_key: i32 = helper.store_str.call1(py, (s,)).unwrap().extract(py).unwrap();
|
||||
assert_eq!(
|
||||
embed_key, *key,
|
||||
"string {s} is out of sync between embedding map (key={embed_key}) and \
|
||||
the internal string store (key={key})"
|
||||
);
|
||||
}
|
||||
});
|
||||
|
||||
link_fn(&main)
|
||||
}
|
||||
|
||||
@ -888,41 +844,6 @@ impl Nac3 {
|
||||
}
|
||||
}
|
||||
|
||||
/// Retrieves the Name.id from a decorator, supports decorators with arguments.
|
||||
fn decorator_id_string(decorator: &Located<ExprKind>) -> Option<String> {
|
||||
if let ExprKind::Name { id, .. } = decorator.node {
|
||||
// Bare decorator
|
||||
return Some(id.to_string());
|
||||
} else if let ExprKind::Call { func, .. } = &decorator.node {
|
||||
// Decorators that are calls (e.g. "@rpc()") have Call for the node,
|
||||
// need to extract the id from within.
|
||||
if let ExprKind::Name { id, .. } = func.node {
|
||||
return Some(id.to_string());
|
||||
}
|
||||
}
|
||||
None
|
||||
}
|
||||
|
||||
/// Retrieves flags from a decorator, if any.
|
||||
fn decorator_get_flags(decorator: &Located<ExprKind>) -> Vec<Constant> {
|
||||
let mut flags = vec![];
|
||||
if let ExprKind::Call { keywords, .. } = &decorator.node {
|
||||
for keyword in keywords {
|
||||
if keyword.node.arg != Some("flags".into()) {
|
||||
continue;
|
||||
}
|
||||
if let ExprKind::Set { elts } = &keyword.node.value.node {
|
||||
for elt in elts {
|
||||
if let ExprKind::Constant { value, .. } = &elt.node {
|
||||
flags.push(value.clone());
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
flags
|
||||
}
|
||||
|
||||
fn link_with_lld(elf_filename: String, obj_filename: String) -> PyResult<()> {
|
||||
let linker_args = vec![
|
||||
"-shared".to_string(),
|
||||
@ -1085,48 +1006,6 @@ impl Nac3 {
|
||||
let working_directory = tempfile::Builder::new().prefix("nac3-").tempdir().unwrap();
|
||||
fs::write(working_directory.path().join("kernel.ld"), include_bytes!("kernel.ld")).unwrap();
|
||||
|
||||
let mut string_store: HashMap<String, i32> = HashMap::default();
|
||||
|
||||
// Keep this list of exceptions in sync with `EXCEPTION_ID_LOOKUP` in `artiq::firmware::ksupport::eh_artiq`
|
||||
// The exceptions declared here must be defined in `artiq.coredevice.exceptions`
|
||||
// Verify synchronization by running the test cases in `artiq.test.coredevice.test_exceptions`
|
||||
let runtime_exception_names = [
|
||||
"RTIOUnderflow",
|
||||
"RTIOOverflow",
|
||||
"RTIODestinationUnreachable",
|
||||
"DMAError",
|
||||
"I2CError",
|
||||
"CacheError",
|
||||
"SPIError",
|
||||
"SubkernelError",
|
||||
"0:AssertionError",
|
||||
"0:AttributeError",
|
||||
"0:IndexError",
|
||||
"0:IOError",
|
||||
"0:KeyError",
|
||||
"0:NotImplementedError",
|
||||
"0:OverflowError",
|
||||
"0:RuntimeError",
|
||||
"0:TimeoutError",
|
||||
"0:TypeError",
|
||||
"0:ValueError",
|
||||
"0:ZeroDivisionError",
|
||||
"0:LinAlgError",
|
||||
"UnwrapNoneError",
|
||||
];
|
||||
|
||||
// Preallocate runtime exception names
|
||||
for (i, name) in runtime_exception_names.iter().enumerate() {
|
||||
let exn_name = if name.find(':').is_none() {
|
||||
format!("0:artiq.coredevice.exceptions.{name}")
|
||||
} else {
|
||||
(*name).to_string()
|
||||
};
|
||||
|
||||
let id = i32::try_from(i).unwrap();
|
||||
string_store.insert(exn_name, id);
|
||||
}
|
||||
|
||||
Ok(Nac3 {
|
||||
isa,
|
||||
time_fns,
|
||||
@ -1136,7 +1015,7 @@ impl Nac3 {
|
||||
top_levels: Vec::default(),
|
||||
pyid_to_def: Arc::default(),
|
||||
working_directory,
|
||||
string_store: Arc::new(string_store.into()),
|
||||
string_store: Arc::default(),
|
||||
exception_ids: Arc::default(),
|
||||
deferred_eval_store: DeferredEvaluationStore::new(),
|
||||
llvm_options: CodeGenLLVMOptions {
|
||||
@ -1146,12 +1025,7 @@ impl Nac3 {
|
||||
})
|
||||
}
|
||||
|
||||
fn analyze(
|
||||
&mut self,
|
||||
functions: &PySet,
|
||||
classes: &PySet,
|
||||
content_modules: &PySet,
|
||||
) -> PyResult<()> {
|
||||
fn analyze(&mut self, functions: &PySet, classes: &PySet) -> PyResult<()> {
|
||||
let (modules, class_ids) =
|
||||
Python::with_gil(|py| -> PyResult<(HashMap<u64, PyObject>, HashSet<u64>)> {
|
||||
let mut modules: HashMap<u64, PyObject> = HashMap::new();
|
||||
@ -1161,21 +1035,13 @@ impl Nac3 {
|
||||
let getmodule_fn = PyModule::import(py, "inspect")?.getattr("getmodule")?;
|
||||
|
||||
for function in functions {
|
||||
let module: PyObject = getmodule_fn.call1((function,))?.extract()?;
|
||||
if !module.is_none(py) {
|
||||
modules.insert(id_fn.call1((&module,))?.extract()?, module);
|
||||
}
|
||||
let module = getmodule_fn.call1((function,))?.extract()?;
|
||||
modules.insert(id_fn.call1((&module,))?.extract()?, module);
|
||||
}
|
||||
for class in classes {
|
||||
let module: PyObject = getmodule_fn.call1((class,))?.extract()?;
|
||||
if !module.is_none(py) {
|
||||
modules.insert(id_fn.call1((&module,))?.extract()?, module);
|
||||
}
|
||||
class_ids.insert(id_fn.call1((class,))?.extract()?);
|
||||
}
|
||||
for module in content_modules {
|
||||
let module: PyObject = module.extract()?;
|
||||
let module = getmodule_fn.call1((class,))?.extract()?;
|
||||
modules.insert(id_fn.call1((&module,))?.extract()?, module);
|
||||
class_ids.insert(id_fn.call1((class,))?.extract()?);
|
||||
}
|
||||
Ok((modules, class_ids))
|
||||
})?;
|
||||
|
@ -1,32 +1,16 @@
|
||||
use std::{
|
||||
collections::{HashMap, HashSet},
|
||||
sync::{
|
||||
atomic::{AtomicBool, Ordering::Relaxed},
|
||||
Arc,
|
||||
},
|
||||
use crate::PrimitivePythonId;
|
||||
use inkwell::{
|
||||
module::Linkage,
|
||||
types::{BasicType, BasicTypeEnum},
|
||||
values::BasicValueEnum,
|
||||
AddressSpace,
|
||||
};
|
||||
|
||||
use itertools::Itertools;
|
||||
use parking_lot::RwLock;
|
||||
use pyo3::{
|
||||
types::{PyDict, PyTuple},
|
||||
PyAny, PyErr, PyObject, PyResult, Python,
|
||||
};
|
||||
|
||||
use super::PrimitivePythonId;
|
||||
use nac3core::{
|
||||
codegen::{
|
||||
types::{ndarray::NDArrayType, ProxyType},
|
||||
values::ndarray::make_contiguous_strides,
|
||||
classes::{NDArrayType, ProxyType},
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
inkwell::{
|
||||
module::Linkage,
|
||||
types::{BasicType, BasicTypeEnum},
|
||||
values::BasicValueEnum,
|
||||
AddressSpace,
|
||||
},
|
||||
nac3parser::ast::{self, StrRef},
|
||||
symbol_resolver::{StaticValue, SymbolResolver, SymbolValue, ValueEnum},
|
||||
toplevel::{
|
||||
helper::PrimDef,
|
||||
@ -38,6 +22,19 @@ use nac3core::{
|
||||
typedef::{into_var_map, iter_type_vars, Type, TypeEnum, TypeVar, Unifier, VarMap},
|
||||
},
|
||||
};
|
||||
use nac3parser::ast::{self, StrRef};
|
||||
use parking_lot::RwLock;
|
||||
use pyo3::{
|
||||
types::{PyDict, PyTuple},
|
||||
PyAny, PyObject, PyResult, Python,
|
||||
};
|
||||
use std::{
|
||||
collections::{HashMap, HashSet},
|
||||
sync::{
|
||||
atomic::{AtomicBool, Ordering::Relaxed},
|
||||
Arc,
|
||||
},
|
||||
};
|
||||
|
||||
pub enum PrimitiveValue {
|
||||
I32(i32),
|
||||
@ -1085,19 +1082,18 @@ impl InnerResolver {
|
||||
} else {
|
||||
unreachable!("must be ndarray")
|
||||
};
|
||||
let (ndarray_dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ndarray_ty);
|
||||
let (ndarray_dtype, ndarray_ndims) =
|
||||
unpack_ndarray_var_tys(&mut ctx.unifier, ndarray_ty);
|
||||
|
||||
let llvm_i8 = ctx.ctx.i8_type();
|
||||
let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
let llvm_ndarray = NDArrayType::from_unifier_type(generator, ctx, ndarray_ty);
|
||||
let dtype = llvm_ndarray.element_type();
|
||||
let ndarray_dtype_llvm_ty = ctx.get_llvm_type(generator, ndarray_dtype);
|
||||
let ndarray_llvm_ty = NDArrayType::new(generator, ctx.ctx, ndarray_dtype_llvm_ty);
|
||||
|
||||
{
|
||||
if self.global_value_ids.read().contains_key(&id) {
|
||||
let global = ctx.module.get_global(&id_str).unwrap_or_else(|| {
|
||||
ctx.module.add_global(
|
||||
llvm_ndarray.as_base_type().get_element_type().into_struct_type(),
|
||||
ndarray_llvm_ty.as_underlying_type(),
|
||||
Some(AddressSpace::default()),
|
||||
&id_str,
|
||||
)
|
||||
@ -1107,41 +1103,40 @@ impl InnerResolver {
|
||||
self.global_value_ids.write().insert(id, obj.into());
|
||||
}
|
||||
|
||||
let ndims = llvm_ndarray.ndims().unwrap();
|
||||
let TypeEnum::TLiteral { values, .. } = &*ctx.unifier.get_ty_immutable(ndarray_ndims)
|
||||
else {
|
||||
unreachable!("Expected Literal for ndarray_ndims")
|
||||
};
|
||||
|
||||
let ndarray_ndims = if values.len() == 1 {
|
||||
values[0].clone()
|
||||
} else {
|
||||
todo!("Unpacking literal of more than one element unimplemented")
|
||||
};
|
||||
let Ok(ndarray_ndims) = u64::try_from(ndarray_ndims) else {
|
||||
unreachable!("Expected u64 value for ndarray_ndims")
|
||||
};
|
||||
|
||||
// Obtain the shape of the ndarray
|
||||
let shape_tuple: &PyTuple = obj.getattr("shape")?.downcast()?;
|
||||
assert_eq!(shape_tuple.len(), ndims as usize);
|
||||
|
||||
// The Rust type inferencer cannot figure this out
|
||||
let shape_values = shape_tuple
|
||||
assert_eq!(shape_tuple.len(), ndarray_ndims as usize);
|
||||
let shape_values: Result<Option<Vec<_>>, _> = shape_tuple
|
||||
.iter()
|
||||
.enumerate()
|
||||
.map(|(i, elem)| {
|
||||
let value = self
|
||||
.get_obj_value(py, elem, ctx, generator, ctx.primitives.usize())
|
||||
.map_err(|e| {
|
||||
super::CompileError::new_err(format!("Error getting element {i}: {e}"))
|
||||
})?
|
||||
.unwrap();
|
||||
let value = value.into_int_value();
|
||||
Ok(value)
|
||||
self.get_obj_value(py, elem, ctx, generator, ctx.primitives.usize()).map_err(
|
||||
|e| super::CompileError::new_err(format!("Error getting element {i}: {e}")),
|
||||
)
|
||||
})
|
||||
.collect::<Result<Vec<_>, PyErr>>()?;
|
||||
|
||||
// Also use this opportunity to get the constant values of `shape_values` for calculating strides.
|
||||
let shape_u64s = shape_values
|
||||
.iter()
|
||||
.map(|dim| {
|
||||
assert!(dim.is_const());
|
||||
dim.get_zero_extended_constant().unwrap()
|
||||
})
|
||||
.collect_vec();
|
||||
let shape_values = llvm_usize.const_array(&shape_values);
|
||||
.collect();
|
||||
let shape_values = shape_values?.unwrap();
|
||||
let shape_values = llvm_usize.const_array(
|
||||
&shape_values.into_iter().map(BasicValueEnum::into_int_value).collect_vec(),
|
||||
);
|
||||
|
||||
// create a global for ndarray.shape and initialize it using the shape
|
||||
let shape_global = ctx.module.add_global(
|
||||
llvm_usize.array_type(ndims as u32),
|
||||
llvm_usize.array_type(ndarray_ndims as u32),
|
||||
Some(AddressSpace::default()),
|
||||
&(id_str.clone() + ".shape"),
|
||||
);
|
||||
@ -1149,25 +1144,17 @@ impl InnerResolver {
|
||||
|
||||
// Obtain the (flattened) elements of the ndarray
|
||||
let sz: usize = obj.getattr("size")?.extract()?;
|
||||
let data: Vec<_> = (0..sz)
|
||||
let data: Result<Option<Vec<_>>, _> = (0..sz)
|
||||
.map(|i| {
|
||||
obj.getattr("flat")?.get_item(i).and_then(|elem| {
|
||||
let value = self
|
||||
.get_obj_value(py, elem, ctx, generator, ndarray_dtype)
|
||||
.map_err(|e| {
|
||||
super::CompileError::new_err(format!(
|
||||
"Error getting element {i}: {e}"
|
||||
))
|
||||
})?
|
||||
.unwrap();
|
||||
|
||||
assert_eq!(value.get_type(), dtype);
|
||||
Ok(value)
|
||||
self.get_obj_value(py, elem, ctx, generator, ndarray_dtype).map_err(|e| {
|
||||
super::CompileError::new_err(format!("Error getting element {i}: {e}"))
|
||||
})
|
||||
})
|
||||
})
|
||||
.try_collect()?;
|
||||
let data = data.into_iter();
|
||||
let data = match dtype {
|
||||
.collect();
|
||||
let data = data?.unwrap().into_iter();
|
||||
let data = match ndarray_dtype_llvm_ty {
|
||||
BasicTypeEnum::ArrayType(ty) => {
|
||||
ty.const_array(&data.map(BasicValueEnum::into_array_value).collect_vec())
|
||||
}
|
||||
@ -1192,68 +1179,34 @@ impl InnerResolver {
|
||||
};
|
||||
|
||||
// create a global for ndarray.data and initialize it using the elements
|
||||
//
|
||||
// NOTE: NDArray's `data` is `u8*`. Here, `data_global` is an array of `dtype`.
|
||||
// We will have to cast it to an `u8*` later.
|
||||
let data_global = ctx.module.add_global(
|
||||
dtype.array_type(sz as u32),
|
||||
ndarray_dtype_llvm_ty.array_type(sz as u32),
|
||||
Some(AddressSpace::default()),
|
||||
&(id_str.clone() + ".data"),
|
||||
);
|
||||
data_global.set_initializer(&data);
|
||||
|
||||
// Get the constant itemsize.
|
||||
let itemsize = dtype.size_of().unwrap();
|
||||
let itemsize = itemsize.get_zero_extended_constant().unwrap();
|
||||
|
||||
// Create the strides needed for ndarray.strides
|
||||
let strides = make_contiguous_strides(itemsize, ndims, &shape_u64s);
|
||||
let strides =
|
||||
strides.into_iter().map(|stride| llvm_usize.const_int(stride, false)).collect_vec();
|
||||
let strides = llvm_usize.const_array(&strides);
|
||||
|
||||
// create a global for ndarray.strides and initialize it
|
||||
let strides_global = ctx.module.add_global(
|
||||
llvm_i8.array_type(ndims as u32),
|
||||
Some(AddressSpace::default()),
|
||||
&format!("${id_str}.strides"),
|
||||
);
|
||||
strides_global.set_initializer(&strides);
|
||||
|
||||
// create a global for the ndarray object and initialize it
|
||||
let value = ndarray_llvm_ty.as_underlying_type().const_named_struct(&[
|
||||
llvm_usize.const_int(ndarray_ndims, false).into(),
|
||||
shape_global
|
||||
.as_pointer_value()
|
||||
.const_cast(llvm_usize.ptr_type(AddressSpace::default()))
|
||||
.into(),
|
||||
data_global
|
||||
.as_pointer_value()
|
||||
.const_cast(ndarray_dtype_llvm_ty.ptr_type(AddressSpace::default()))
|
||||
.into(),
|
||||
]);
|
||||
|
||||
// NOTE: data_global is an array of dtype, we want a `u8*`.
|
||||
let ndarray_data = data_global.as_pointer_value();
|
||||
let ndarray_data = ctx.builder.build_pointer_cast(ndarray_data, llvm_pi8, "").unwrap();
|
||||
|
||||
let ndarray_itemsize = llvm_usize.const_int(itemsize, false);
|
||||
|
||||
let ndarray_ndims = llvm_usize.const_int(ndims, false);
|
||||
|
||||
let ndarray_shape = shape_global.as_pointer_value();
|
||||
|
||||
let ndarray_strides = strides_global.as_pointer_value();
|
||||
|
||||
let ndarray = llvm_ndarray
|
||||
.as_base_type()
|
||||
.get_element_type()
|
||||
.into_struct_type()
|
||||
.const_named_struct(&[
|
||||
ndarray_itemsize.into(),
|
||||
ndarray_ndims.into(),
|
||||
ndarray_shape.into(),
|
||||
ndarray_strides.into(),
|
||||
ndarray_data.into(),
|
||||
]);
|
||||
|
||||
let ndarray_global = ctx.module.add_global(
|
||||
llvm_ndarray.as_base_type().get_element_type().into_struct_type(),
|
||||
let ndarray = ctx.module.add_global(
|
||||
ndarray_llvm_ty.as_underlying_type(),
|
||||
Some(AddressSpace::default()),
|
||||
&id_str,
|
||||
);
|
||||
ndarray_global.set_initializer(&ndarray);
|
||||
ndarray.set_initializer(&value);
|
||||
|
||||
Ok(Some(ndarray_global.as_pointer_value().into()))
|
||||
Ok(Some(ndarray.as_pointer_value().into()))
|
||||
} else if ty_id == self.primitive_ids.tuple {
|
||||
let expected_ty_enum = ctx.unifier.get_ty_immutable(expected_ty);
|
||||
let TypeEnum::TTuple { ty, is_vararg_ctx: false } = expected_ty_enum.as_ref() else {
|
||||
@ -1514,7 +1467,6 @@ impl SymbolResolver for Resolver {
|
||||
&self,
|
||||
id: StrRef,
|
||||
_: &mut CodeGenContext<'ctx, '_>,
|
||||
_: &mut dyn CodeGenerator,
|
||||
) -> Option<ValueEnum<'ctx>> {
|
||||
let sym_value = {
|
||||
let id_to_val = self.0.id_to_pyval.read();
|
||||
@ -1576,7 +1528,10 @@ impl SymbolResolver for Resolver {
|
||||
if let Some(id) = string_store.get(s) {
|
||||
*id
|
||||
} else {
|
||||
let id = i32::try_from(string_store.len()).unwrap();
|
||||
let id = Python::with_gil(|py| -> PyResult<i32> {
|
||||
self.0.helper.store_str.call1(py, (s,))?.extract(py)
|
||||
})
|
||||
.unwrap();
|
||||
string_store.insert(s.into(), id);
|
||||
id
|
||||
}
|
||||
|
@ -1,12 +1,9 @@
|
||||
use itertools::Either;
|
||||
|
||||
use nac3core::{
|
||||
codegen::CodeGenContext,
|
||||
inkwell::{
|
||||
values::{BasicValueEnum, CallSiteValue},
|
||||
AddressSpace, AtomicOrdering,
|
||||
},
|
||||
use inkwell::{
|
||||
values::{BasicValueEnum, CallSiteValue},
|
||||
AddressSpace, AtomicOrdering,
|
||||
};
|
||||
use itertools::Either;
|
||||
use nac3core::codegen::CodeGenContext;
|
||||
|
||||
/// Functions for manipulating the timeline.
|
||||
pub trait TimeFns {
|
||||
@ -34,7 +31,7 @@ impl TimeFns for NowPinningTimeFns64 {
|
||||
.unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
|
||||
let now_hiptr = ctx
|
||||
.builder
|
||||
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
|
||||
.build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap();
|
||||
|
||||
@ -83,7 +80,7 @@ impl TimeFns for NowPinningTimeFns64 {
|
||||
.unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
|
||||
let now_hiptr = ctx
|
||||
.builder
|
||||
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
|
||||
.build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap();
|
||||
|
||||
@ -112,7 +109,7 @@ impl TimeFns for NowPinningTimeFns64 {
|
||||
.unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
|
||||
let now_hiptr = ctx
|
||||
.builder
|
||||
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
|
||||
.build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap();
|
||||
|
||||
@ -210,7 +207,7 @@ impl TimeFns for NowPinningTimeFns {
|
||||
.unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
|
||||
let now_hiptr = ctx
|
||||
.builder
|
||||
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
|
||||
.build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap();
|
||||
|
||||
@ -261,7 +258,7 @@ impl TimeFns for NowPinningTimeFns {
|
||||
let time_lo = ctx.builder.build_int_truncate(time, i32_type, "time.lo").unwrap();
|
||||
let now_hiptr = ctx
|
||||
.builder
|
||||
.build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
|
||||
.build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap();
|
||||
|
||||
|
@ -10,6 +10,7 @@ constant-optimization = ["fold"]
|
||||
fold = []
|
||||
|
||||
[dependencies]
|
||||
lazy_static = "1.5"
|
||||
parking_lot = "0.12"
|
||||
string-interner = "0.17"
|
||||
fxhash = "0.2"
|
||||
|
@ -5,12 +5,14 @@ pub use crate::location::Location;
|
||||
|
||||
use fxhash::FxBuildHasher;
|
||||
use parking_lot::{Mutex, MutexGuard};
|
||||
use std::{cell::RefCell, collections::HashMap, fmt, sync::LazyLock};
|
||||
use std::{cell::RefCell, collections::HashMap, fmt};
|
||||
use string_interner::{symbol::SymbolU32, DefaultBackend, StringInterner};
|
||||
|
||||
pub type Interner = StringInterner<DefaultBackend, FxBuildHasher>;
|
||||
static INTERNER: LazyLock<Mutex<Interner>> =
|
||||
LazyLock::new(|| Mutex::new(StringInterner::with_hasher(FxBuildHasher::default())));
|
||||
lazy_static! {
|
||||
static ref INTERNER: Mutex<Interner> =
|
||||
Mutex::new(StringInterner::with_hasher(FxBuildHasher::default()));
|
||||
}
|
||||
|
||||
thread_local! {
|
||||
static LOCAL_INTERNER: RefCell<HashMap<String, StrRef>> = RefCell::default();
|
||||
|
@ -1,4 +1,10 @@
|
||||
#![deny(future_incompatible, let_underscore, nonstandard_style, clippy::all)]
|
||||
#![deny(
|
||||
future_incompatible,
|
||||
let_underscore,
|
||||
nonstandard_style,
|
||||
rust_2024_compatibility,
|
||||
clippy::all
|
||||
)]
|
||||
#![warn(clippy::pedantic)]
|
||||
#![allow(
|
||||
clippy::missing_errors_doc,
|
||||
@ -8,6 +14,9 @@
|
||||
clippy::wildcard_imports
|
||||
)]
|
||||
|
||||
#[macro_use]
|
||||
extern crate lazy_static;
|
||||
|
||||
mod ast_gen;
|
||||
mod constant;
|
||||
#[cfg(feature = "fold")]
|
||||
|
@ -5,25 +5,22 @@ authors = ["M-Labs"]
|
||||
edition = "2021"
|
||||
|
||||
[features]
|
||||
default = ["derive"]
|
||||
derive = ["dep:nac3core_derive"]
|
||||
no-escape-analysis = []
|
||||
|
||||
[dependencies]
|
||||
itertools = "0.13"
|
||||
crossbeam = "0.8"
|
||||
indexmap = "2.6"
|
||||
indexmap = "2.2"
|
||||
parking_lot = "0.12"
|
||||
rayon = "1.10"
|
||||
nac3core_derive = { path = "nac3core_derive", optional = true }
|
||||
rayon = "1.8"
|
||||
nac3parser = { path = "../nac3parser" }
|
||||
strum = "0.26"
|
||||
strum_macros = "0.26"
|
||||
|
||||
[dependencies.inkwell]
|
||||
version = "0.5"
|
||||
version = "0.4"
|
||||
default-features = false
|
||||
features = ["llvm14-0-prefer-dynamic", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]
|
||||
features = ["llvm14-0", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]
|
||||
|
||||
[dev-dependencies]
|
||||
test-case = "1.2.0"
|
||||
|
@ -1,3 +1,4 @@
|
||||
use regex::Regex;
|
||||
use std::{
|
||||
env,
|
||||
fs::File,
|
||||
@ -6,8 +7,6 @@ use std::{
|
||||
process::{Command, Stdio},
|
||||
};
|
||||
|
||||
use regex::Regex;
|
||||
|
||||
fn main() {
|
||||
let out_dir = env::var("OUT_DIR").unwrap();
|
||||
let out_dir = Path::new(&out_dir);
|
||||
@ -56,8 +55,9 @@ fn main() {
|
||||
let output = Command::new("clang-irrt")
|
||||
.args(flags)
|
||||
.output()
|
||||
.inspect(|o| {
|
||||
.map(|o| {
|
||||
assert!(o.status.success(), "{}", std::str::from_utf8(&o.stderr).unwrap());
|
||||
o
|
||||
})
|
||||
.unwrap();
|
||||
|
||||
|
@ -1,4 +1,5 @@
|
||||
#include "irrt/exception.hpp"
|
||||
#include "irrt/int_types.hpp"
|
||||
#include "irrt/list.hpp"
|
||||
#include "irrt/math.hpp"
|
||||
#include "irrt/ndarray.hpp"
|
||||
@ -8,3 +9,8 @@
|
||||
#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"
|
@ -4,6 +4,6 @@
|
||||
|
||||
template<typename SizeT>
|
||||
struct CSlice {
|
||||
void* base;
|
||||
uint8_t* base;
|
||||
SizeT len;
|
||||
};
|
@ -6,7 +6,7 @@
|
||||
/**
|
||||
* @brief The int type of ARTIQ exception IDs.
|
||||
*/
|
||||
using ExceptionId = int32_t;
|
||||
typedef int32_t ExceptionId;
|
||||
|
||||
/*
|
||||
* Set of exceptions C++ IRRT can use.
|
||||
@ -55,14 +55,14 @@ void _raise_exception_helper(ExceptionId id,
|
||||
int64_t param2) {
|
||||
Exception<SizeT> e = {
|
||||
.id = id,
|
||||
.filename = {.base = reinterpret_cast<void*>(const_cast<char*>(filename)),
|
||||
.len = static_cast<SizeT>(__builtin_strlen(filename))},
|
||||
.filename = {.base = reinterpret_cast<uint8_t*>(const_cast<char*>(filename)),
|
||||
.len = static_cast<int32_t>(__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))},
|
||||
.function = {.base = reinterpret_cast<uint8_t*>(const_cast<char*>(function)),
|
||||
.len = static_cast<int32_t>(__builtin_strlen(function))},
|
||||
.msg = {.base = reinterpret_cast<uint8_t*>(const_cast<char*>(msg)),
|
||||
.len = static_cast<int32_t>(__builtin_strlen(msg))},
|
||||
};
|
||||
e.params[0] = param0;
|
||||
e.params[1] = param1;
|
||||
@ -70,7 +70,6 @@ void _raise_exception_helper(ExceptionId id,
|
||||
__nac3_raise(reinterpret_cast<void*>(&e));
|
||||
__builtin_unreachable();
|
||||
}
|
||||
} // namespace
|
||||
|
||||
/**
|
||||
* @brief Raise an exception with location details (location in the IRRT source files).
|
||||
@ -83,3 +82,4 @@ void _raise_exception_helper(ExceptionId id,
|
||||
*/
|
||||
#define raise_exception(SizeT, id, msg, param0, param1, param2) \
|
||||
_raise_exception_helper<SizeT>(id, __FILE__, __LINE__, __FUNCTION__, msg, param0, param1, param2)
|
||||
} // namespace
|
@ -1,25 +1,11 @@
|
||||
#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
|
||||
|
||||
// NDArray indices are always `uint32_t`.
|
||||
using NDIndexInt = uint32_t;
|
||||
|
@ -2,6 +2,21 @@
|
||||
|
||||
#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
|
||||
@ -13,12 +28,12 @@ extern "C" {
|
||||
SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
|
||||
SliceIndex dest_end,
|
||||
SliceIndex dest_step,
|
||||
void* dest_arr,
|
||||
uint8_t* dest_arr,
|
||||
SliceIndex dest_arr_len,
|
||||
SliceIndex src_start,
|
||||
SliceIndex src_end,
|
||||
SliceIndex src_step,
|
||||
void* src_arr,
|
||||
uint8_t* src_arr,
|
||||
SliceIndex src_arr_len,
|
||||
const SliceIndex size) {
|
||||
/* if dest_arr_len == 0, do nothing since we do not support extending list */
|
||||
@ -29,13 +44,11 @@ SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
|
||||
const SliceIndex src_len = (src_end >= src_start) ? (src_end - src_start + 1) : 0;
|
||||
const SliceIndex dest_len = (dest_end >= dest_start) ? (dest_end - dest_start + 1) : 0;
|
||||
if (src_len > 0) {
|
||||
__builtin_memmove(static_cast<uint8_t*>(dest_arr) + dest_start * size,
|
||||
static_cast<uint8_t*>(src_arr) + src_start * size, src_len * size);
|
||||
__builtin_memmove(dest_arr + dest_start * size, 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,
|
||||
__builtin_memmove(dest_arr + (dest_start + src_len) * size, dest_arr + (dest_end + 1) * size,
|
||||
(dest_arr_len - dest_end - 1) * size);
|
||||
}
|
||||
/* shrink size */
|
||||
@ -46,7 +59,7 @@ SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
|
||||
&& !(max(dest_start, dest_end) < min(src_start, src_end)
|
||||
|| max(src_start, src_end) < min(dest_start, dest_end));
|
||||
if (need_alloca) {
|
||||
void* tmp = __builtin_alloca(src_arr_len * size);
|
||||
uint8_t* tmp = reinterpret_cast<uint8_t*>(__builtin_alloca(src_arr_len * size));
|
||||
__builtin_memcpy(tmp, src_arr, src_arr_len * size);
|
||||
src_arr = tmp;
|
||||
}
|
||||
@ -55,24 +68,20 @@ SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
|
||||
for (; (src_step > 0) ? (src_ind <= src_end) : (src_ind >= src_end); src_ind += src_step, dest_ind += dest_step) {
|
||||
/* for constant optimization */
|
||||
if (size == 1) {
|
||||
__builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind, static_cast<uint8_t*>(src_arr) + src_ind, 1);
|
||||
__builtin_memcpy(dest_arr + dest_ind, src_arr + src_ind, 1);
|
||||
} else if (size == 4) {
|
||||
__builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind * 4,
|
||||
static_cast<uint8_t*>(src_arr) + src_ind * 4, 4);
|
||||
__builtin_memcpy(dest_arr + dest_ind * 4, 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);
|
||||
__builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
|
||||
} else {
|
||||
/* memcpy for var size, cannot overlap after previous alloca */
|
||||
__builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind * size,
|
||||
static_cast<uint8_t*>(src_arr) + src_ind * size, size);
|
||||
__builtin_memcpy(dest_arr + dest_ind * size, src_arr + src_ind * size, size);
|
||||
}
|
||||
}
|
||||
/* only dest_step == 1 can we shrink the dest list. */
|
||||
/* size should be ensured prior to calling this function */
|
||||
if (dest_step == 1 && dest_end >= dest_start) {
|
||||
__builtin_memmove(static_cast<uint8_t*>(dest_arr) + dest_ind * size,
|
||||
static_cast<uint8_t*>(dest_arr) + (dest_end + 1) * size,
|
||||
__builtin_memmove(dest_arr + dest_ind * size, dest_arr + (dest_end + 1) * size,
|
||||
(dest_arr_len - dest_end - 1) * size);
|
||||
return dest_arr_len - (dest_end - dest_ind) - 1;
|
||||
}
|
||||
|
@ -90,4 +90,4 @@ double __nac3_j0(double x) {
|
||||
|
||||
return j0(x);
|
||||
}
|
||||
} // namespace
|
||||
}
|
@ -148,4 +148,4 @@ void __nac3_ndarray_calc_broadcast_idx64(const uint64_t* src_dims,
|
||||
NDIndexInt* out_idx) {
|
||||
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
|
||||
}
|
||||
} // namespace
|
||||
}
|
134
nac3core/irrt/irrt/ndarray/array.hpp
Normal file
134
nac3core/irrt/irrt/ndarray/array.hpp
Normal file
@ -0,0 +1,134 @@
|
||||
#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 {
|
||||
namespace array {
|
||||
/**
|
||||
* @brief In the context of `np.array(<list>)`, deduce the ndarray's shape produced by `<list>` and raise
|
||||
* an exception if there is anything wrong with `<shape>` (e.g., inconsistent dimensions `np.array([[1.0, 2.0],
|
||||
* [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 = 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 array
|
||||
} // namespace ndarray
|
||||
} // 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);
|
||||
}
|
||||
}
|
@ -113,13 +113,12 @@ SizeT nbytes(const NDArray<SizeT>* ndarray) {
|
||||
*/
|
||||
template<typename SizeT>
|
||||
SizeT len(const NDArray<SizeT>* ndarray) {
|
||||
if (ndarray->ndims != 0) {
|
||||
// numpy prohibits `__len__` on unsized objects
|
||||
if (ndarray->ndims == 0) {
|
||||
raise_exception(SizeT, EXN_TYPE_ERROR, "len() of unsized object", NO_PARAM, NO_PARAM, NO_PARAM);
|
||||
} else {
|
||||
return ndarray->shape[0];
|
||||
}
|
||||
|
||||
// numpy prohibits `__len__` on unsized objects
|
||||
raise_exception(SizeT, EXN_TYPE_ERROR, "len() of unsized object", NO_PARAM, NO_PARAM, NO_PARAM);
|
||||
__builtin_unreachable();
|
||||
}
|
||||
|
||||
/**
|
||||
@ -179,10 +178,10 @@ bool is_c_contiguous(const NDArray<SizeT>* ndarray) {
|
||||
* This function does no bound check.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
void* get_pelement_by_indices(const NDArray<SizeT>* ndarray, const SizeT* indices) {
|
||||
void* element = ndarray->data;
|
||||
uint8_t* get_pelement_by_indices(const NDArray<SizeT>* ndarray, const SizeT* indices) {
|
||||
uint8_t* element = ndarray->data;
|
||||
for (SizeT dim_i = 0; dim_i < ndarray->ndims; dim_i++)
|
||||
element = static_cast<uint8_t*>(element) + indices[dim_i] * ndarray->strides[dim_i];
|
||||
element += indices[dim_i] * ndarray->strides[dim_i];
|
||||
return element;
|
||||
}
|
||||
|
||||
@ -192,12 +191,12 @@ void* get_pelement_by_indices(const NDArray<SizeT>* ndarray, const SizeT* indice
|
||||
* This function does no bound check.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
void* get_nth_pelement(const NDArray<SizeT>* ndarray, SizeT nth) {
|
||||
void* element = ndarray->data;
|
||||
uint8_t* get_nth_pelement(const NDArray<SizeT>* ndarray, SizeT nth) {
|
||||
uint8_t* element = ndarray->data;
|
||||
for (SizeT i = 0; i < ndarray->ndims; i++) {
|
||||
SizeT axis = ndarray->ndims - i - 1;
|
||||
SizeT dim = ndarray->shape[axis];
|
||||
element = static_cast<uint8_t*>(element) + ndarray->strides[axis] * (nth % dim);
|
||||
element += ndarray->strides[axis] * (nth % dim);
|
||||
nth /= dim;
|
||||
}
|
||||
return element;
|
||||
@ -225,7 +224,7 @@ void set_strides_by_shape(NDArray<SizeT>* ndarray) {
|
||||
* @param pvalue Pointer to the value `pelement` will be set to.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
void set_pelement_value(NDArray<SizeT>* ndarray, void* pelement, const void* pvalue) {
|
||||
void set_pelement_value(NDArray<SizeT>* ndarray, uint8_t* pelement, const uint8_t* pvalue) {
|
||||
__builtin_memcpy(pelement, pvalue, ndarray->itemsize);
|
||||
}
|
||||
|
||||
@ -308,19 +307,19 @@ bool __nac3_ndarray_is_c_contiguous64(NDArray<int64_t>* ndarray) {
|
||||
return is_c_contiguous(ndarray);
|
||||
}
|
||||
|
||||
void* __nac3_ndarray_get_nth_pelement(const NDArray<int32_t>* ndarray, int32_t nth) {
|
||||
uint8_t* __nac3_ndarray_get_nth_pelement(const NDArray<int32_t>* ndarray, int32_t nth) {
|
||||
return get_nth_pelement(ndarray, nth);
|
||||
}
|
||||
|
||||
void* __nac3_ndarray_get_nth_pelement64(const NDArray<int64_t>* ndarray, int64_t nth) {
|
||||
uint8_t* __nac3_ndarray_get_nth_pelement64(const NDArray<int64_t>* ndarray, int64_t nth) {
|
||||
return get_nth_pelement(ndarray, nth);
|
||||
}
|
||||
|
||||
void* __nac3_ndarray_get_pelement_by_indices(const NDArray<int32_t>* ndarray, int32_t* indices) {
|
||||
uint8_t* __nac3_ndarray_get_pelement_by_indices(const NDArray<int32_t>* ndarray, int32_t* indices) {
|
||||
return get_pelement_by_indices(ndarray, indices);
|
||||
}
|
||||
|
||||
void* __nac3_ndarray_get_pelement_by_indices64(const NDArray<int64_t>* ndarray, int64_t* indices) {
|
||||
uint8_t* __nac3_ndarray_get_pelement_by_indices64(const NDArray<int64_t>* ndarray, int64_t* indices) {
|
||||
return get_pelement_by_indices(ndarray, indices);
|
||||
}
|
||||
|
||||
|
165
nac3core/irrt/irrt/ndarray/broadcast.hpp
Normal file
165
nac3core/irrt/irrt/ndarray/broadcast.hpp
Normal file
@ -0,0 +1,165 @@
|
||||
#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 {
|
||||
namespace 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);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Check pre-condition: `dst_ndims` must be `max([shape.ndims for shape in shapes])`
|
||||
debug_assert_eq(SizeT, max_ndims_found, dst_ndims);
|
||||
}
|
||||
|
||||
/**
|
||||
* @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 broadcast
|
||||
} // namespace ndarray
|
||||
} // 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);
|
||||
}
|
||||
}
|
@ -7,16 +7,15 @@ namespace {
|
||||
* @brief The NDArray object
|
||||
*
|
||||
* Official numpy implementation:
|
||||
* https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst#pyarrayinterface
|
||||
*
|
||||
* 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.
|
||||
* https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst
|
||||
*/
|
||||
template<typename SizeT>
|
||||
struct NDArray {
|
||||
/**
|
||||
* @brief The underlying data this `ndarray` is pointing to.
|
||||
*/
|
||||
uint8_t* data;
|
||||
|
||||
/**
|
||||
* @brief The number of bytes of a single element in `data`.
|
||||
*/
|
||||
@ -42,10 +41,5 @@ struct NDArray {
|
||||
* Note that `strides` can have negative values or contain 0.
|
||||
*/
|
||||
SizeT* strides;
|
||||
|
||||
/**
|
||||
* @brief The underlying data this `ndarray` is pointing to.
|
||||
*/
|
||||
void* data;
|
||||
};
|
||||
} // namespace
|
@ -154,7 +154,7 @@ void index(SizeT num_indices, const NDIndex* indices, const NDArray<SizeT>* src_
|
||||
input, src_axis, src_ndarray->shape[src_axis]);
|
||||
}
|
||||
|
||||
dst_ndarray->data = static_cast<uint8_t*>(dst_ndarray->data) + k * src_ndarray->strides[src_axis];
|
||||
dst_ndarray->data += k * src_ndarray->strides[src_axis];
|
||||
|
||||
src_axis++;
|
||||
} else if (index->type == ND_INDEX_TYPE_SLICE) {
|
||||
@ -162,7 +162,7 @@ void index(SizeT num_indices, const NDIndex* indices, const NDArray<SizeT>* src_
|
||||
|
||||
Range<int32_t> range = slice->indices_checked<SizeT>(src_ndarray->shape[src_axis]);
|
||||
|
||||
dst_ndarray->data = static_cast<uint8_t*>(dst_ndarray->data) + (SizeT)range.start * src_ndarray->strides[src_axis];
|
||||
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>();
|
||||
|
||||
|
@ -58,7 +58,7 @@ struct NDIter {
|
||||
*
|
||||
* Initially this points to first element of the ndarray.
|
||||
*/
|
||||
void* element;
|
||||
uint8_t* element;
|
||||
|
||||
/**
|
||||
* @brief Cache for the product of shape.
|
||||
@ -67,7 +67,7 @@ struct NDIter {
|
||||
*/
|
||||
SizeT size;
|
||||
|
||||
void initialize(SizeT ndims, SizeT* shape, SizeT* strides, void* element, SizeT* indices) {
|
||||
void initialize(SizeT ndims, SizeT* shape, SizeT* strides, uint8_t* element, SizeT* indices) {
|
||||
this->ndims = ndims;
|
||||
this->shape = shape;
|
||||
this->strides = strides;
|
||||
@ -108,9 +108,9 @@ struct NDIter {
|
||||
// TODO: There is something called backstrides to speedup iteration.
|
||||
// See https://ajcr.net/stride-guide-part-1/, and
|
||||
// https://docs.scipy.org/doc/numpy-1.13.0/reference/c-api.types-and-structures.html#c.PyArrayIterObject.PyArrayIterObject.backstrides.
|
||||
element = static_cast<void*>(reinterpret_cast<uint8_t*>(element) - strides[axis] * (shape[axis] - 1));
|
||||
element -= strides[axis] * (shape[axis] - 1);
|
||||
} else {
|
||||
element = static_cast<void*>(reinterpret_cast<uint8_t*>(element) + strides[axis]);
|
||||
element += strides[axis];
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
100
nac3core/irrt/irrt/ndarray/matmul.hpp
Normal file
100
nac3core/irrt/irrt/ndarray/matmul.hpp
Normal file
@ -0,0 +1,100 @@
|
||||
#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 {
|
||||
namespace 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 matmul
|
||||
} // namespace ndarray
|
||||
} // 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);
|
||||
}
|
||||
}
|
99
nac3core/irrt/irrt/ndarray/reshape.hpp
Normal file
99
nac3core/irrt/irrt/ndarray/reshape.hpp
Normal file
@ -0,0 +1,99 @@
|
||||
#pragma once
|
||||
|
||||
#include "irrt/exception.hpp"
|
||||
#include "irrt/int_types.hpp"
|
||||
#include "irrt/ndarray/def.hpp"
|
||||
|
||||
namespace {
|
||||
namespace ndarray {
|
||||
namespace 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 reshape
|
||||
} // namespace ndarray
|
||||
} // 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);
|
||||
}
|
||||
}
|
145
nac3core/irrt/irrt/ndarray/transpose.hpp
Normal file
145
nac3core/irrt/irrt/ndarray/transpose.hpp
Normal file
@ -0,0 +1,145 @@
|
||||
#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 {
|
||||
namespace 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 transpose
|
||||
} // namespace ndarray
|
||||
} // 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);
|
||||
}
|
||||
}
|
@ -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"
|
@ -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()
|
||||
}
|
@ -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() {}
|
@ -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() {}
|
@ -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() {}
|
@ -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() {}
|
@ -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() {}
|
@ -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() {}
|
@ -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");
|
||||
}
|
File diff suppressed because it is too large
Load Diff
1764
nac3core/src/codegen/classes.rs
Normal file
1764
nac3core/src/codegen/classes.rs
Normal file
File diff suppressed because it is too large
Load Diff
@ -1,9 +1,3 @@
|
||||
use std::collections::HashMap;
|
||||
|
||||
use indexmap::IndexMap;
|
||||
|
||||
use nac3parser::ast::StrRef;
|
||||
|
||||
use crate::{
|
||||
symbol_resolver::SymbolValue,
|
||||
toplevel::DefinitionId,
|
||||
@ -15,6 +9,10 @@ use crate::{
|
||||
},
|
||||
};
|
||||
|
||||
use indexmap::IndexMap;
|
||||
use nac3parser::ast::StrRef;
|
||||
use std::collections::HashMap;
|
||||
|
||||
pub struct ConcreteTypeStore {
|
||||
store: Vec<ConcreteTypeEnum>,
|
||||
}
|
||||
|
File diff suppressed because it is too large
Load Diff
@ -1,10 +1,8 @@
|
||||
use inkwell::{
|
||||
attributes::{Attribute, AttributeLoc},
|
||||
values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue},
|
||||
};
|
||||
use inkwell::attributes::{Attribute, AttributeLoc};
|
||||
use inkwell::values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue};
|
||||
use itertools::Either;
|
||||
|
||||
use super::CodeGenContext;
|
||||
use crate::codegen::CodeGenContext;
|
||||
|
||||
/// Macro to generate extern function
|
||||
/// Both function return type and function parameter type are `FloatValue`
|
||||
|
@ -1,18 +1,16 @@
|
||||
use crate::{
|
||||
codegen::{bool_to_i1, bool_to_i8, classes::ArraySliceValue, expr::*, stmt::*, CodeGenContext},
|
||||
symbol_resolver::ValueEnum,
|
||||
toplevel::{DefinitionId, TopLevelDef},
|
||||
typecheck::typedef::{FunSignature, Type},
|
||||
};
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
types::{BasicTypeEnum, IntType},
|
||||
values::{BasicValueEnum, IntValue, PointerValue},
|
||||
};
|
||||
|
||||
use nac3parser::ast::{Expr, Stmt, StrRef};
|
||||
|
||||
use super::{bool_to_i1, bool_to_i8, 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;
|
||||
|
@ -1,162 +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 size_ty = generator.get_size_type(ctx.ctx);
|
||||
let int8_ptr = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
|
||||
let int32 = ctx.ctx.i32_type();
|
||||
let (fun_symbol, elem_ptr_type) = ("__nac3_list_slice_assign_var_size", int8_ptr);
|
||||
let slice_assign_fun = {
|
||||
let ty_vec = vec![
|
||||
int32.into(), // dest start idx
|
||||
int32.into(), // dest end idx
|
||||
int32.into(), // dest step
|
||||
elem_ptr_type.into(), // dest arr ptr
|
||||
int32.into(), // dest arr len
|
||||
int32.into(), // src start idx
|
||||
int32.into(), // src end idx
|
||||
int32.into(), // src step
|
||||
elem_ptr_type.into(), // src arr ptr
|
||||
int32.into(), // src arr len
|
||||
int32.into(), // size
|
||||
];
|
||||
ctx.module.get_function(fun_symbol).unwrap_or_else(|| {
|
||||
let fn_t = int32.fn_type(ty_vec.as_slice(), false);
|
||||
ctx.module.add_function(fun_symbol, fn_t, None)
|
||||
})
|
||||
};
|
||||
|
||||
let zero = int32.const_zero();
|
||||
let one = int32.const_int(1, false);
|
||||
let dest_arr_ptr = dest_arr.data().base_ptr(ctx, generator);
|
||||
let dest_arr_ptr =
|
||||
ctx.builder.build_pointer_cast(dest_arr_ptr, elem_ptr_type, "dest_arr_ptr_cast").unwrap();
|
||||
let dest_len = dest_arr.load_size(ctx, Some("dest.len"));
|
||||
let dest_len = ctx.builder.build_int_truncate_or_bit_cast(dest_len, int32, "srclen32").unwrap();
|
||||
let src_arr_ptr = src_arr.data().base_ptr(ctx, generator);
|
||||
let src_arr_ptr =
|
||||
ctx.builder.build_pointer_cast(src_arr_ptr, elem_ptr_type, "src_arr_ptr_cast").unwrap();
|
||||
let src_len = src_arr.load_size(ctx, Some("src.len"));
|
||||
let src_len = ctx.builder.build_int_truncate_or_bit_cast(src_len, int32, "srclen32").unwrap();
|
||||
|
||||
// index in bound and positive should be done
|
||||
// assert if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest), and
|
||||
// throw exception if not satisfied
|
||||
let src_end = ctx
|
||||
.builder
|
||||
.build_select(
|
||||
ctx.builder.build_int_compare(IntPredicate::SLT, src_idx.2, zero, "is_neg").unwrap(),
|
||||
ctx.builder.build_int_sub(src_idx.1, one, "e_min_one").unwrap(),
|
||||
ctx.builder.build_int_add(src_idx.1, one, "e_add_one").unwrap(),
|
||||
"final_e",
|
||||
)
|
||||
.map(BasicValueEnum::into_int_value)
|
||||
.unwrap();
|
||||
let dest_end = ctx
|
||||
.builder
|
||||
.build_select(
|
||||
ctx.builder.build_int_compare(IntPredicate::SLT, dest_idx.2, zero, "is_neg").unwrap(),
|
||||
ctx.builder.build_int_sub(dest_idx.1, one, "e_min_one").unwrap(),
|
||||
ctx.builder.build_int_add(dest_idx.1, one, "e_add_one").unwrap(),
|
||||
"final_e",
|
||||
)
|
||||
.map(BasicValueEnum::into_int_value)
|
||||
.unwrap();
|
||||
let src_slice_len =
|
||||
calculate_len_for_slice_range(generator, ctx, src_idx.0, src_end, src_idx.2);
|
||||
let dest_slice_len =
|
||||
calculate_len_for_slice_range(generator, ctx, dest_idx.0, dest_end, dest_idx.2);
|
||||
let src_eq_dest = ctx
|
||||
.builder
|
||||
.build_int_compare(IntPredicate::EQ, src_slice_len, dest_slice_len, "slice_src_eq_dest")
|
||||
.unwrap();
|
||||
let src_slt_dest = ctx
|
||||
.builder
|
||||
.build_int_compare(IntPredicate::SLT, src_slice_len, dest_slice_len, "slice_src_slt_dest")
|
||||
.unwrap();
|
||||
let dest_step_eq_one = ctx
|
||||
.builder
|
||||
.build_int_compare(
|
||||
IntPredicate::EQ,
|
||||
dest_idx.2,
|
||||
dest_idx.2.get_type().const_int(1, false),
|
||||
"slice_dest_step_eq_one",
|
||||
)
|
||||
.unwrap();
|
||||
let cond_1 = ctx.builder.build_and(dest_step_eq_one, src_slt_dest, "slice_cond_1").unwrap();
|
||||
let cond = ctx.builder.build_or(src_eq_dest, cond_1, "slice_cond").unwrap();
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
cond,
|
||||
"0:ValueError",
|
||||
"attempt to assign sequence of size {0} to slice of size {1} with step size {2}",
|
||||
[Some(src_slice_len), Some(dest_slice_len), Some(dest_idx.2)],
|
||||
ctx.current_loc,
|
||||
);
|
||||
|
||||
let new_len = {
|
||||
let args = vec![
|
||||
dest_idx.0.into(), // dest start idx
|
||||
dest_idx.1.into(), // dest end idx
|
||||
dest_idx.2.into(), // dest step
|
||||
dest_arr_ptr.into(), // dest arr ptr
|
||||
dest_len.into(), // dest arr len
|
||||
src_idx.0.into(), // src start idx
|
||||
src_idx.1.into(), // src end idx
|
||||
src_idx.2.into(), // src step
|
||||
src_arr_ptr.into(), // src arr ptr
|
||||
src_len.into(), // src arr len
|
||||
{
|
||||
let s = match ty {
|
||||
BasicTypeEnum::FloatType(t) => t.size_of(),
|
||||
BasicTypeEnum::IntType(t) => t.size_of(),
|
||||
BasicTypeEnum::PointerType(t) => t.size_of(),
|
||||
BasicTypeEnum::StructType(t) => t.size_of().unwrap(),
|
||||
_ => codegen_unreachable!(ctx),
|
||||
};
|
||||
ctx.builder.build_int_truncate_or_bit_cast(s, int32, "size").unwrap()
|
||||
}
|
||||
.into(),
|
||||
];
|
||||
ctx.builder
|
||||
.build_call(slice_assign_fun, args.as_slice(), "slice_assign")
|
||||
.map(CallSiteValue::try_as_basic_value)
|
||||
.map(|v| v.map_left(BasicValueEnum::into_int_value))
|
||||
.map(Either::unwrap_left)
|
||||
.unwrap()
|
||||
};
|
||||
// update length
|
||||
let need_update =
|
||||
ctx.builder.build_int_compare(IntPredicate::NE, new_len, dest_len, "need_update").unwrap();
|
||||
let current = ctx.builder.get_insert_block().unwrap().get_parent().unwrap();
|
||||
let update_bb = ctx.ctx.append_basic_block(current, "update");
|
||||
let cont_bb = ctx.ctx.append_basic_block(current, "cont");
|
||||
ctx.builder.build_conditional_branch(need_update, update_bb, cont_bb).unwrap();
|
||||
ctx.builder.position_at_end(update_bb);
|
||||
let new_len = ctx.builder.build_int_z_extend_or_bit_cast(new_len, size_ty, "new_len").unwrap();
|
||||
dest_arr.store_size(ctx, generator, new_len);
|
||||
ctx.builder.build_unconditional_branch(cont_bb).unwrap();
|
||||
ctx.builder.position_at_end(cont_bb);
|
||||
}
|
@ -1,152 +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 intrinsic_fn = ctx.module.get_function("__nac3_isinf").unwrap_or_else(|| {
|
||||
let fn_type = ctx.ctx.i32_type().fn_type(&[ctx.ctx.f64_type().into()], false);
|
||||
ctx.module.add_function("__nac3_isinf", fn_type, None)
|
||||
});
|
||||
|
||||
let ret = ctx
|
||||
.builder
|
||||
.build_call(intrinsic_fn, &[v.into()], "isinf")
|
||||
.map(CallSiteValue::try_as_basic_value)
|
||||
.map(|v| v.map_left(BasicValueEnum::into_int_value))
|
||||
.map(Either::unwrap_left)
|
||||
.unwrap();
|
||||
|
||||
generator.bool_to_i1(ctx, ret)
|
||||
}
|
||||
|
||||
/// Generates a call to `isnan` in IR. Returns an `i1` representing the result.
|
||||
pub fn call_isnan<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
v: FloatValue<'ctx>,
|
||||
) -> IntValue<'ctx> {
|
||||
let intrinsic_fn = ctx.module.get_function("__nac3_isnan").unwrap_or_else(|| {
|
||||
let fn_type = ctx.ctx.i32_type().fn_type(&[ctx.ctx.f64_type().into()], false);
|
||||
ctx.module.add_function("__nac3_isnan", fn_type, None)
|
||||
});
|
||||
|
||||
let ret = ctx
|
||||
.builder
|
||||
.build_call(intrinsic_fn, &[v.into()], "isnan")
|
||||
.map(CallSiteValue::try_as_basic_value)
|
||||
.map(|v| v.map_left(BasicValueEnum::into_int_value))
|
||||
.map(Either::unwrap_left)
|
||||
.unwrap();
|
||||
|
||||
generator.bool_to_i1(ctx, ret)
|
||||
}
|
||||
|
||||
/// Generates a call to `gamma` in IR. Returns an `f64` representing the result.
|
||||
pub fn call_gamma<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
|
||||
let llvm_f64 = ctx.ctx.f64_type();
|
||||
|
||||
let intrinsic_fn = ctx.module.get_function("__nac3_gamma").unwrap_or_else(|| {
|
||||
let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
|
||||
ctx.module.add_function("__nac3_gamma", fn_type, None)
|
||||
});
|
||||
|
||||
ctx.builder
|
||||
.build_call(intrinsic_fn, &[v.into()], "gamma")
|
||||
.map(CallSiteValue::try_as_basic_value)
|
||||
.map(|v| v.map_left(BasicValueEnum::into_float_value))
|
||||
.map(Either::unwrap_left)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Generates a call to `gammaln` in IR. Returns an `f64` representing the result.
|
||||
pub fn call_gammaln<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
|
||||
let llvm_f64 = ctx.ctx.f64_type();
|
||||
|
||||
let intrinsic_fn = ctx.module.get_function("__nac3_gammaln").unwrap_or_else(|| {
|
||||
let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
|
||||
ctx.module.add_function("__nac3_gammaln", fn_type, None)
|
||||
});
|
||||
|
||||
ctx.builder
|
||||
.build_call(intrinsic_fn, &[v.into()], "gammaln")
|
||||
.map(CallSiteValue::try_as_basic_value)
|
||||
.map(|v| v.map_left(BasicValueEnum::into_float_value))
|
||||
.map(Either::unwrap_left)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Generates a call to `j0` in IR. Returns an `f64` representing the result.
|
||||
pub fn call_j0<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
|
||||
let llvm_f64 = ctx.ctx.f64_type();
|
||||
|
||||
let intrinsic_fn = ctx.module.get_function("__nac3_j0").unwrap_or_else(|| {
|
||||
let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
|
||||
ctx.module.add_function("__nac3_j0", fn_type, None)
|
||||
});
|
||||
|
||||
ctx.builder
|
||||
.build_call(intrinsic_fn, &[v.into()], "j0")
|
||||
.map(CallSiteValue::try_as_basic_value)
|
||||
.map(|v| v.map_left(BasicValueEnum::into_float_value))
|
||||
.map(Either::unwrap_left)
|
||||
.unwrap()
|
||||
}
|
File diff suppressed because it is too large
Load Diff
@ -1,250 +0,0 @@
|
||||
use inkwell::{
|
||||
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},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
pub fn call_nac3_ndarray_util_assert_shape_no_negative<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
ndims: IntValue<'ctx>,
|
||||
shape: PointerValue<'ctx>,
|
||||
) {
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
|
||||
|
||||
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(), ndims.into()), (llvm_pusize.into(), shape.into())],
|
||||
None,
|
||||
None,
|
||||
);
|
||||
}
|
||||
|
||||
pub fn call_nac3_ndarray_util_assert_output_shape_same<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
ndarray_ndims: IntValue<'ctx>,
|
||||
ndarray_shape: PointerValue<'ctx>,
|
||||
output_ndims: IntValue<'ctx>,
|
||||
output_shape: IntValue<'ctx>,
|
||||
) {
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
|
||||
|
||||
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_ndims.into()),
|
||||
(llvm_pusize.into(), ndarray_shape.into()),
|
||||
(llvm_usize.into(), output_ndims.into()),
|
||||
(llvm_pusize.into(), output_shape.into()),
|
||||
],
|
||||
None,
|
||||
None,
|
||||
);
|
||||
}
|
||||
|
||||
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()
|
||||
}
|
||||
|
||||
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()
|
||||
}
|
||||
|
||||
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()
|
||||
}
|
||||
|
||||
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()
|
||||
}
|
||||
|
||||
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();
|
||||
|
||||
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()
|
||||
}
|
||||
|
||||
pub fn call_nac3_ndarray_get_pelement_by_indices<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
ndarray: NDArrayValue<'ctx>,
|
||||
indices: PointerValue<'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();
|
||||
|
||||
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.into()),
|
||||
],
|
||||
Some("pelement"),
|
||||
None,
|
||||
)
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
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,
|
||||
);
|
||||
}
|
||||
|
||||
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,
|
||||
);
|
||||
}
|
@ -1,29 +0,0 @@
|
||||
use crate::codegen::{
|
||||
expr::infer_and_call_function,
|
||||
irrt::get_usize_dependent_function_name,
|
||||
values::{ndarray::NDArrayValue, ArrayLikeValue, ArraySliceValue, ProxyValue},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
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,
|
||||
);
|
||||
}
|
@ -1,70 +0,0 @@
|
||||
use inkwell::{
|
||||
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},
|
||||
ArrayLikeValue, ArraySliceValue, ProxyValue,
|
||||
},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
pub fn call_nac3_nditer_initialize<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
iter: NDIterValue<'ctx>,
|
||||
ndarray: NDArrayValue<'ctx>,
|
||||
indices: ArraySliceValue<'ctx>,
|
||||
) {
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
|
||||
|
||||
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,
|
||||
);
|
||||
}
|
||||
|
||||
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()
|
||||
}
|
||||
|
||||
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);
|
||||
}
|
@ -1,391 +0,0 @@
|
||||
use inkwell::{
|
||||
types::IntType,
|
||||
values::{BasicValueEnum, CallSiteValue, IntValue},
|
||||
AddressSpace, IntPredicate,
|
||||
};
|
||||
use itertools::Either;
|
||||
|
||||
use crate::codegen::{
|
||||
llvm_intrinsics,
|
||||
macros::codegen_unreachable,
|
||||
stmt::gen_for_callback_incrementing,
|
||||
values::{
|
||||
ndarray::NDArrayValue, ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue,
|
||||
TypedArrayLikeAccessor, TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
|
||||
},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
pub use basic::*;
|
||||
pub use indexing::*;
|
||||
pub use iter::*;
|
||||
|
||||
mod basic;
|
||||
mod indexing;
|
||||
mod iter;
|
||||
|
||||
/// Generates a call to `__nac3_ndarray_calc_size`. Returns an [`IntValue`] representing the
|
||||
/// calculated total size.
|
||||
///
|
||||
/// * `dims` - An [`ArrayLikeIndexer`] containing the size of each dimension.
|
||||
/// * `range` - The dimension index to begin and end (exclusively) calculating the dimensions for,
|
||||
/// or [`None`] if starting from the first dimension and ending at the last dimension
|
||||
/// respectively.
|
||||
pub fn call_ndarray_calc_size<'ctx, G, Dims>(
|
||||
generator: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
dims: &Dims,
|
||||
(begin, end): (Option<IntValue<'ctx>>, Option<IntValue<'ctx>>),
|
||||
) -> IntValue<'ctx>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
Dims: ArrayLikeIndexer<'ctx>,
|
||||
{
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
|
||||
|
||||
let ndarray_calc_size_fn_name = match llvm_usize.get_bit_width() {
|
||||
32 => "__nac3_ndarray_calc_size",
|
||||
64 => "__nac3_ndarray_calc_size64",
|
||||
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
|
||||
};
|
||||
let ndarray_calc_size_fn_t = llvm_usize.fn_type(
|
||||
&[llvm_pusize.into(), llvm_usize.into(), llvm_usize.into(), llvm_usize.into()],
|
||||
false,
|
||||
);
|
||||
let ndarray_calc_size_fn =
|
||||
ctx.module.get_function(ndarray_calc_size_fn_name).unwrap_or_else(|| {
|
||||
ctx.module.add_function(ndarray_calc_size_fn_name, ndarray_calc_size_fn_t, None)
|
||||
});
|
||||
|
||||
let begin = begin.unwrap_or_else(|| llvm_usize.const_zero());
|
||||
let end = end.unwrap_or_else(|| dims.size(ctx, generator));
|
||||
ctx.builder
|
||||
.build_call(
|
||||
ndarray_calc_size_fn,
|
||||
&[
|
||||
dims.base_ptr(ctx, generator).into(),
|
||||
dims.size(ctx, generator).into(),
|
||||
begin.into(),
|
||||
end.into(),
|
||||
],
|
||||
"",
|
||||
)
|
||||
.map(CallSiteValue::try_as_basic_value)
|
||||
.map(|v| v.map_left(BasicValueEnum::into_int_value))
|
||||
.map(Either::unwrap_left)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Generates a call to `__nac3_ndarray_calc_nd_indices`. Returns a [`TypeArrayLikeAdpater`]
|
||||
/// containing `i32` indices of the flattened index.
|
||||
///
|
||||
/// * `index` - The index to compute the multidimensional index for.
|
||||
/// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
|
||||
/// `NDArray`.
|
||||
pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
index: IntValue<'ctx>,
|
||||
ndarray: NDArrayValue<'ctx>,
|
||||
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
|
||||
let llvm_void = ctx.ctx.void_type();
|
||||
let llvm_i32 = ctx.ctx.i32_type();
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
|
||||
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
|
||||
|
||||
let ndarray_calc_nd_indices_fn_name = match llvm_usize.get_bit_width() {
|
||||
32 => "__nac3_ndarray_calc_nd_indices",
|
||||
64 => "__nac3_ndarray_calc_nd_indices64",
|
||||
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
|
||||
};
|
||||
let ndarray_calc_nd_indices_fn =
|
||||
ctx.module.get_function(ndarray_calc_nd_indices_fn_name).unwrap_or_else(|| {
|
||||
let fn_type = llvm_void.fn_type(
|
||||
&[llvm_usize.into(), llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into()],
|
||||
false,
|
||||
);
|
||||
|
||||
ctx.module.add_function(ndarray_calc_nd_indices_fn_name, fn_type, None)
|
||||
});
|
||||
|
||||
let ndarray_num_dims = ndarray.load_ndims(ctx);
|
||||
let ndarray_dims = ndarray.shape();
|
||||
|
||||
let indices = ctx.builder.build_array_alloca(llvm_i32, ndarray_num_dims, "").unwrap();
|
||||
|
||||
ctx.builder
|
||||
.build_call(
|
||||
ndarray_calc_nd_indices_fn,
|
||||
&[
|
||||
index.into(),
|
||||
ndarray_dims.base_ptr(ctx, generator).into(),
|
||||
ndarray_num_dims.into(),
|
||||
indices.into(),
|
||||
],
|
||||
"",
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
TypedArrayLikeAdapter::from(
|
||||
ArraySliceValue::from_ptr_val(indices, ndarray_num_dims, None),
|
||||
Box::new(|_, v| v.into_int_value()),
|
||||
Box::new(|_, v| v.into()),
|
||||
)
|
||||
}
|
||||
|
||||
fn call_ndarray_flatten_index_impl<'ctx, G, Indices>(
|
||||
generator: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
ndarray: NDArrayValue<'ctx>,
|
||||
indices: &Indices,
|
||||
) -> IntValue<'ctx>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
Indices: ArrayLikeIndexer<'ctx>,
|
||||
{
|
||||
let llvm_i32 = ctx.ctx.i32_type();
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
|
||||
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
|
||||
|
||||
debug_assert_eq!(
|
||||
IntType::try_from(indices.element_type(ctx, generator))
|
||||
.map(IntType::get_bit_width)
|
||||
.unwrap_or_default(),
|
||||
llvm_i32.get_bit_width(),
|
||||
"Expected i32 value for argument `indices` to `call_ndarray_flatten_index_impl`"
|
||||
);
|
||||
debug_assert_eq!(
|
||||
indices.size(ctx, generator).get_type().get_bit_width(),
|
||||
llvm_usize.get_bit_width(),
|
||||
"Expected usize integer value for argument `indices_size` to `call_ndarray_flatten_index_impl`"
|
||||
);
|
||||
|
||||
let ndarray_flatten_index_fn_name = match llvm_usize.get_bit_width() {
|
||||
32 => "__nac3_ndarray_flatten_index",
|
||||
64 => "__nac3_ndarray_flatten_index64",
|
||||
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
|
||||
};
|
||||
let ndarray_flatten_index_fn =
|
||||
ctx.module.get_function(ndarray_flatten_index_fn_name).unwrap_or_else(|| {
|
||||
let fn_type = llvm_usize.fn_type(
|
||||
&[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_usize.into()],
|
||||
false,
|
||||
);
|
||||
|
||||
ctx.module.add_function(ndarray_flatten_index_fn_name, fn_type, None)
|
||||
});
|
||||
|
||||
let ndarray_num_dims = ndarray.load_ndims(ctx);
|
||||
let ndarray_dims = ndarray.shape();
|
||||
|
||||
let index = ctx
|
||||
.builder
|
||||
.build_call(
|
||||
ndarray_flatten_index_fn,
|
||||
&[
|
||||
ndarray_dims.base_ptr(ctx, generator).into(),
|
||||
ndarray_num_dims.into(),
|
||||
indices.base_ptr(ctx, generator).into(),
|
||||
indices.size(ctx, generator).into(),
|
||||
],
|
||||
"",
|
||||
)
|
||||
.map(CallSiteValue::try_as_basic_value)
|
||||
.map(|v| v.map_left(BasicValueEnum::into_int_value))
|
||||
.map(Either::unwrap_left)
|
||||
.unwrap();
|
||||
|
||||
index
|
||||
}
|
||||
|
||||
/// Generates a call to `__nac3_ndarray_flatten_index`. Returns the flattened index for the
|
||||
/// multidimensional index.
|
||||
///
|
||||
/// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
|
||||
/// `NDArray`.
|
||||
/// * `indices` - The multidimensional index to compute the flattened index for.
|
||||
pub fn call_ndarray_flatten_index<'ctx, G, Index>(
|
||||
generator: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
ndarray: NDArrayValue<'ctx>,
|
||||
indices: &Index,
|
||||
) -> IntValue<'ctx>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
Index: ArrayLikeIndexer<'ctx>,
|
||||
{
|
||||
call_ndarray_flatten_index_impl(generator, ctx, ndarray, indices)
|
||||
}
|
||||
|
||||
/// Generates a call to `__nac3_ndarray_calc_broadcast`. Returns a tuple containing the number of
|
||||
/// dimension and size of each dimension of the resultant `ndarray`.
|
||||
pub fn call_ndarray_calc_broadcast<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
lhs: NDArrayValue<'ctx>,
|
||||
rhs: NDArrayValue<'ctx>,
|
||||
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
|
||||
|
||||
let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
|
||||
32 => "__nac3_ndarray_calc_broadcast",
|
||||
64 => "__nac3_ndarray_calc_broadcast64",
|
||||
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
|
||||
};
|
||||
let ndarray_calc_broadcast_fn =
|
||||
ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
|
||||
let fn_type = llvm_usize.fn_type(
|
||||
&[
|
||||
llvm_pusize.into(),
|
||||
llvm_usize.into(),
|
||||
llvm_pusize.into(),
|
||||
llvm_usize.into(),
|
||||
llvm_pusize.into(),
|
||||
],
|
||||
false,
|
||||
);
|
||||
|
||||
ctx.module.add_function(ndarray_calc_broadcast_fn_name, fn_type, None)
|
||||
});
|
||||
|
||||
let lhs_ndims = lhs.load_ndims(ctx);
|
||||
let rhs_ndims = rhs.load_ndims(ctx);
|
||||
let min_ndims = llvm_intrinsics::call_int_umin(ctx, lhs_ndims, rhs_ndims, None);
|
||||
|
||||
gen_for_callback_incrementing(
|
||||
generator,
|
||||
ctx,
|
||||
None,
|
||||
llvm_usize.const_zero(),
|
||||
(min_ndims, false),
|
||||
|generator, ctx, _, idx| {
|
||||
let idx = ctx.builder.build_int_sub(min_ndims, idx, "").unwrap();
|
||||
let (lhs_dim_sz, rhs_dim_sz) = unsafe {
|
||||
(
|
||||
lhs.shape().get_typed_unchecked(ctx, generator, &idx, None),
|
||||
rhs.shape().get_typed_unchecked(ctx, generator, &idx, None),
|
||||
)
|
||||
};
|
||||
|
||||
let llvm_usize_const_one = llvm_usize.const_int(1, false);
|
||||
let lhs_eqz = ctx
|
||||
.builder
|
||||
.build_int_compare(IntPredicate::EQ, lhs_dim_sz, llvm_usize_const_one, "")
|
||||
.unwrap();
|
||||
let rhs_eqz = ctx
|
||||
.builder
|
||||
.build_int_compare(IntPredicate::EQ, rhs_dim_sz, llvm_usize_const_one, "")
|
||||
.unwrap();
|
||||
let lhs_or_rhs_eqz = ctx.builder.build_or(lhs_eqz, rhs_eqz, "").unwrap();
|
||||
|
||||
let lhs_eq_rhs = ctx
|
||||
.builder
|
||||
.build_int_compare(IntPredicate::EQ, lhs_dim_sz, rhs_dim_sz, "")
|
||||
.unwrap();
|
||||
|
||||
let is_compatible = ctx.builder.build_or(lhs_or_rhs_eqz, lhs_eq_rhs, "").unwrap();
|
||||
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
is_compatible,
|
||||
"0:ValueError",
|
||||
"operands could not be broadcast together",
|
||||
[None, None, None],
|
||||
ctx.current_loc,
|
||||
);
|
||||
|
||||
Ok(())
|
||||
},
|
||||
llvm_usize.const_int(1, false),
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let max_ndims = llvm_intrinsics::call_int_umax(ctx, lhs_ndims, rhs_ndims, None);
|
||||
let lhs_dims = lhs.shape().base_ptr(ctx, generator);
|
||||
let lhs_ndims = lhs.load_ndims(ctx);
|
||||
let rhs_dims = rhs.shape().base_ptr(ctx, generator);
|
||||
let rhs_ndims = rhs.load_ndims(ctx);
|
||||
let out_dims = ctx.builder.build_array_alloca(llvm_usize, max_ndims, "").unwrap();
|
||||
let out_dims = ArraySliceValue::from_ptr_val(out_dims, max_ndims, None);
|
||||
|
||||
ctx.builder
|
||||
.build_call(
|
||||
ndarray_calc_broadcast_fn,
|
||||
&[
|
||||
lhs_dims.into(),
|
||||
lhs_ndims.into(),
|
||||
rhs_dims.into(),
|
||||
rhs_ndims.into(),
|
||||
out_dims.base_ptr(ctx, generator).into(),
|
||||
],
|
||||
"",
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
TypedArrayLikeAdapter::from(
|
||||
out_dims,
|
||||
Box::new(|_, v| v.into_int_value()),
|
||||
Box::new(|_, v| v.into()),
|
||||
)
|
||||
}
|
||||
|
||||
/// Generates a call to `__nac3_ndarray_calc_broadcast_idx`. Returns an [`ArrayAllocaValue`]
|
||||
/// containing the indices used for accessing `array` corresponding to the index of the broadcasted
|
||||
/// array `broadcast_idx`.
|
||||
pub fn call_ndarray_calc_broadcast_index<
|
||||
'ctx,
|
||||
G: CodeGenerator + ?Sized,
|
||||
BroadcastIdx: UntypedArrayLikeAccessor<'ctx>,
|
||||
>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
array: NDArrayValue<'ctx>,
|
||||
broadcast_idx: &BroadcastIdx,
|
||||
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
|
||||
let llvm_i32 = ctx.ctx.i32_type();
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
|
||||
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
|
||||
|
||||
let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
|
||||
32 => "__nac3_ndarray_calc_broadcast_idx",
|
||||
64 => "__nac3_ndarray_calc_broadcast_idx64",
|
||||
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
|
||||
};
|
||||
let ndarray_calc_broadcast_fn =
|
||||
ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
|
||||
let fn_type = llvm_usize.fn_type(
|
||||
&[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_pi32.into()],
|
||||
false,
|
||||
);
|
||||
|
||||
ctx.module.add_function(ndarray_calc_broadcast_fn_name, fn_type, None)
|
||||
});
|
||||
|
||||
let broadcast_size = broadcast_idx.size(ctx, generator);
|
||||
let out_idx = ctx.builder.build_array_alloca(llvm_i32, broadcast_size, "").unwrap();
|
||||
|
||||
let array_dims = array.shape().base_ptr(ctx, generator);
|
||||
let array_ndims = array.load_ndims(ctx);
|
||||
let broadcast_idx_ptr = unsafe {
|
||||
broadcast_idx.ptr_offset_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
|
||||
};
|
||||
|
||||
ctx.builder
|
||||
.build_call(
|
||||
ndarray_calc_broadcast_fn,
|
||||
&[array_dims.into(), array_ndims.into(), broadcast_idx_ptr.into(), out_idx.into()],
|
||||
"",
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
TypedArrayLikeAdapter::from(
|
||||
ArraySliceValue::from_ptr_val(out_idx, broadcast_size, None),
|
||||
Box::new(|_, v| v.into_int_value()),
|
||||
Box::new(|_, v| v.into()),
|
||||
)
|
||||
}
|
@ -1,42 +0,0 @@
|
||||
use inkwell::{
|
||||
values::{BasicValueEnum, CallSiteValue, IntValue},
|
||||
IntPredicate,
|
||||
};
|
||||
use itertools::Either;
|
||||
|
||||
use crate::codegen::{CodeGenContext, CodeGenerator};
|
||||
|
||||
pub fn calculate_len_for_slice_range<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
start: IntValue<'ctx>,
|
||||
end: IntValue<'ctx>,
|
||||
step: IntValue<'ctx>,
|
||||
) -> IntValue<'ctx> {
|
||||
const SYMBOL: &str = "__nac3_range_slice_len";
|
||||
let len_func = ctx.module.get_function(SYMBOL).unwrap_or_else(|| {
|
||||
let i32_t = ctx.ctx.i32_type();
|
||||
let fn_t = i32_t.fn_type(&[i32_t.into(), i32_t.into(), i32_t.into()], false);
|
||||
ctx.module.add_function(SYMBOL, fn_t, None)
|
||||
});
|
||||
|
||||
// assert step != 0, throw exception if not
|
||||
let not_zero = ctx
|
||||
.builder
|
||||
.build_int_compare(IntPredicate::NE, step, step.get_type().const_zero(), "range_step_ne")
|
||||
.unwrap();
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
not_zero,
|
||||
"0:ValueError",
|
||||
"step must not be zero",
|
||||
[None, None, None],
|
||||
ctx.current_loc,
|
||||
);
|
||||
ctx.builder
|
||||
.build_call(len_func, &[start.into(), end.into(), step.into()], "calc_len")
|
||||
.map(CallSiteValue::try_as_basic_value)
|
||||
.map(|v| v.map_left(BasicValueEnum::into_int_value))
|
||||
.map(Either::unwrap_left)
|
||||
.unwrap()
|
||||
}
|
@ -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(),
|
||||
))
|
||||
}
|
@ -1,14 +1,12 @@
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
intrinsics::Intrinsic,
|
||||
types::{AnyTypeEnum::IntType, FloatType},
|
||||
values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue, PointerValue},
|
||||
AddressSpace,
|
||||
};
|
||||
use crate::codegen::CodeGenContext;
|
||||
use inkwell::context::Context;
|
||||
use inkwell::intrinsics::Intrinsic;
|
||||
use inkwell::types::AnyTypeEnum::IntType;
|
||||
use inkwell::types::FloatType;
|
||||
use inkwell::values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue, PointerValue};
|
||||
use inkwell::AddressSpace;
|
||||
use itertools::Either;
|
||||
|
||||
use super::CodeGenContext;
|
||||
|
||||
/// Returns the string representation for the floating-point type `ft` when used in intrinsic
|
||||
/// functions.
|
||||
fn get_float_intrinsic_repr(ctx: &Context, ft: FloatType) -> &'static str {
|
||||
@ -185,7 +183,7 @@ pub fn call_memcpy_generic<'ctx>(
|
||||
dest
|
||||
} else {
|
||||
ctx.builder
|
||||
.build_bit_cast(dest, llvm_p0i8, "")
|
||||
.build_bitcast(dest, llvm_p0i8, "")
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap()
|
||||
};
|
||||
@ -193,7 +191,7 @@ pub fn call_memcpy_generic<'ctx>(
|
||||
src
|
||||
} else {
|
||||
ctx.builder
|
||||
.build_bit_cast(src, llvm_p0i8, "")
|
||||
.build_bitcast(src, llvm_p0i8, "")
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap()
|
||||
};
|
||||
@ -201,49 +199,6 @@ pub fn call_memcpy_generic<'ctx>(
|
||||
call_memcpy(ctx, dest, src, len, is_volatile);
|
||||
}
|
||||
|
||||
/// Invokes the `llvm.memcpy` intrinsic.
|
||||
///
|
||||
/// Unlike [`call_memcpy`], this function accepts any type of pointer value. If `dest` or `src` is
|
||||
/// not a pointer to an integer, the pointer(s) will be cast to `i8*` before invoking `memcpy`.
|
||||
/// Moreover, `len` now refers to the number of elements to copy (rather than number of bytes to
|
||||
/// copy).
|
||||
pub fn call_memcpy_generic_array<'ctx>(
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
dest: PointerValue<'ctx>,
|
||||
src: PointerValue<'ctx>,
|
||||
len: IntValue<'ctx>,
|
||||
is_volatile: IntValue<'ctx>,
|
||||
) {
|
||||
let llvm_i8 = ctx.ctx.i8_type();
|
||||
let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
|
||||
let llvm_sizeof_expr_t = llvm_i8.size_of().get_type();
|
||||
|
||||
let dest_elem_t = dest.get_type().get_element_type();
|
||||
let src_elem_t = src.get_type().get_element_type();
|
||||
|
||||
let dest = if matches!(dest_elem_t, IntType(t) if t.get_bit_width() == 8) {
|
||||
dest
|
||||
} else {
|
||||
ctx.builder
|
||||
.build_bit_cast(dest, llvm_p0i8, "")
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap()
|
||||
};
|
||||
let src = if matches!(src_elem_t, IntType(t) if t.get_bit_width() == 8) {
|
||||
src
|
||||
} else {
|
||||
ctx.builder
|
||||
.build_bit_cast(src, llvm_p0i8, "")
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap()
|
||||
};
|
||||
|
||||
let len = ctx.builder.build_int_z_extend_or_bit_cast(len, llvm_sizeof_expr_t, "").unwrap();
|
||||
let len = ctx.builder.build_int_mul(len, src_elem_t.size_of().unwrap(), "").unwrap();
|
||||
|
||||
call_memcpy(ctx, dest, src, len, is_volatile);
|
||||
}
|
||||
|
||||
/// Macro to find and generate build call for llvm intrinsic (body of llvm intrinsic function)
|
||||
///
|
||||
/// Arguments:
|
||||
@ -386,25 +341,3 @@ pub fn call_float_powi<'ctx>(
|
||||
.map(Either::unwrap_left)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Invokes the [`llvm.ctpop`](https://llvm.org/docs/LangRef.html#llvm-ctpop-intrinsic) intrinsic.
|
||||
pub fn call_int_ctpop<'ctx>(
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
src: IntValue<'ctx>,
|
||||
name: Option<&str>,
|
||||
) -> IntValue<'ctx> {
|
||||
const FN_NAME: &str = "llvm.ctpop";
|
||||
|
||||
let llvm_src_t = src.get_type();
|
||||
|
||||
let intrinsic_fn = Intrinsic::find(FN_NAME)
|
||||
.and_then(|intrinsic| intrinsic.get_declaration(&ctx.module, &[llvm_src_t.into()]))
|
||||
.unwrap();
|
||||
|
||||
ctx.builder
|
||||
.build_call(intrinsic_fn, &[src.into()], name.unwrap_or_default())
|
||||
.map(CallSiteValue::try_as_basic_value)
|
||||
.map(|v| v.map_left(BasicValueEnum::into_int_value))
|
||||
.map(Either::unwrap_left)
|
||||
.unwrap()
|
||||
}
|
||||
|
@ -1,12 +1,12 @@
|
||||
use std::{
|
||||
collections::{HashMap, HashSet},
|
||||
sync::{
|
||||
atomic::{AtomicBool, Ordering},
|
||||
Arc,
|
||||
use crate::{
|
||||
codegen::classes::{ListType, ProxyType, RangeType},
|
||||
symbol_resolver::{StaticValue, SymbolResolver},
|
||||
toplevel::{helper::PrimDef, TopLevelContext, TopLevelDef},
|
||||
typecheck::{
|
||||
type_inferencer::{CodeLocation, PrimitiveStore},
|
||||
typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
|
||||
},
|
||||
thread,
|
||||
};
|
||||
|
||||
use crossbeam::channel::{unbounded, Receiver, Sender};
|
||||
use inkwell::{
|
||||
attributes::{Attribute, AttributeLoc},
|
||||
@ -24,41 +24,36 @@ use inkwell::{
|
||||
AddressSpace, IntPredicate, OptimizationLevel,
|
||||
};
|
||||
use itertools::Itertools;
|
||||
use parking_lot::{Condvar, Mutex};
|
||||
|
||||
use model::*;
|
||||
use nac3parser::ast::{Location, Stmt, StrRef};
|
||||
|
||||
use crate::{
|
||||
symbol_resolver::{StaticValue, SymbolResolver},
|
||||
toplevel::{
|
||||
helper::{extract_ndims, PrimDef},
|
||||
numpy::unpack_ndarray_var_tys,
|
||||
TopLevelContext, TopLevelDef,
|
||||
},
|
||||
typecheck::{
|
||||
type_inferencer::{CodeLocation, PrimitiveStore},
|
||||
typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
|
||||
},
|
||||
use object::ndarray::NDArray;
|
||||
use parking_lot::{Condvar, Mutex};
|
||||
use std::collections::{HashMap, HashSet};
|
||||
use std::sync::{
|
||||
atomic::{AtomicBool, Ordering},
|
||||
Arc,
|
||||
};
|
||||
use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
|
||||
pub use generator::{CodeGenerator, DefaultCodeGenerator};
|
||||
use types::{ndarray::NDArrayType, ListType, ProxyType, RangeType};
|
||||
use std::thread;
|
||||
|
||||
pub mod builtin_fns;
|
||||
pub mod classes;
|
||||
pub mod concrete_type;
|
||||
pub mod expr;
|
||||
pub mod extern_fns;
|
||||
mod generator;
|
||||
pub mod irrt;
|
||||
pub mod llvm_intrinsics;
|
||||
pub mod model;
|
||||
pub mod numpy;
|
||||
pub mod object;
|
||||
pub mod stmt;
|
||||
pub mod types;
|
||||
pub mod values;
|
||||
|
||||
#[cfg(test)]
|
||||
mod test;
|
||||
|
||||
use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
|
||||
pub use generator::{CodeGenerator, DefaultCodeGenerator};
|
||||
|
||||
mod macros {
|
||||
/// Codegen-variant of [`std::unreachable`] which accepts an instance of [`CodeGenContext`] as
|
||||
/// its first argument to provide Python source information to indicate the codegen location
|
||||
@ -514,13 +509,7 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
|
||||
}
|
||||
|
||||
TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
|
||||
let (dtype, ndims) = unpack_ndarray_var_tys(unifier, ty);
|
||||
let ndims = extract_ndims(unifier, ndims);
|
||||
let element_type = get_llvm_type(
|
||||
ctx, module, generator, unifier, top_level, type_cache, dtype,
|
||||
);
|
||||
|
||||
NDArrayType::new(generator, ctx, element_type, Some(ndims)).as_base_type().into()
|
||||
Ptr(Struct(NDArray)).llvm_type(generator, ctx).as_basic_type_enum()
|
||||
}
|
||||
|
||||
_ => unreachable!(
|
||||
@ -858,9 +847,10 @@ pub fn gen_func_impl<
|
||||
builder.position_at_end(init_bb);
|
||||
let body_bb = context.append_basic_block(fn_val, "body");
|
||||
|
||||
// Store non-vararg argument values into local variables
|
||||
let mut var_assignment = HashMap::new();
|
||||
let offset = u32::from(has_sret);
|
||||
|
||||
// Store non-vararg argument values into local variables
|
||||
for (n, arg) in args.iter().enumerate().filter(|(_, arg)| !arg.is_vararg) {
|
||||
let param = fn_val.get_nth_param((n as u32) + offset).unwrap();
|
||||
let local_type = get_llvm_type(
|
||||
@ -1124,106 +1114,3 @@ fn gen_in_range_check<'ctx>(
|
||||
fn get_va_count_arg_name(arg_name: StrRef) -> StrRef {
|
||||
format!("__{}_va_count", &arg_name).into()
|
||||
}
|
||||
|
||||
/// Returns the alignment of the type.
|
||||
///
|
||||
/// This is necessary as `get_alignment` is not implemented as part of [`BasicType`].
|
||||
pub fn get_type_alignment<'ctx>(ty: impl Into<BasicTypeEnum<'ctx>>) -> IntValue<'ctx> {
|
||||
match ty.into() {
|
||||
BasicTypeEnum::ArrayType(ty) => ty.get_alignment(),
|
||||
BasicTypeEnum::FloatType(ty) => ty.get_alignment(),
|
||||
BasicTypeEnum::IntType(ty) => ty.get_alignment(),
|
||||
BasicTypeEnum::PointerType(ty) => ty.get_alignment(),
|
||||
BasicTypeEnum::StructType(ty) => ty.get_alignment(),
|
||||
BasicTypeEnum::VectorType(ty) => ty.get_alignment(),
|
||||
}
|
||||
}
|
||||
|
||||
/// Inserts an `alloca` instruction with allocation `size` given in bytes and the alignment of the
|
||||
/// given type.
|
||||
///
|
||||
/// The returned [`PointerValue`] will have a type of `i8*`, a size of at least `size`, and will be
|
||||
/// aligned with the alignment of `align_ty`.
|
||||
pub fn type_aligned_alloca<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
align_ty: impl Into<BasicTypeEnum<'ctx>>,
|
||||
size: IntValue<'ctx>,
|
||||
name: Option<&str>,
|
||||
) -> PointerValue<'ctx> {
|
||||
/// Round `val` up to its modulo `power_of_two`.
|
||||
fn round_up<'ctx>(
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
val: IntValue<'ctx>,
|
||||
power_of_two: IntValue<'ctx>,
|
||||
) -> IntValue<'ctx> {
|
||||
debug_assert_eq!(
|
||||
val.get_type().get_bit_width(),
|
||||
power_of_two.get_type().get_bit_width(),
|
||||
"`val` ({}) and `power_of_two` ({}) must be the same type",
|
||||
val.get_type(),
|
||||
power_of_two.get_type(),
|
||||
);
|
||||
|
||||
let llvm_val_t = val.get_type();
|
||||
|
||||
let max_rem =
|
||||
ctx.builder.build_int_sub(power_of_two, llvm_val_t.const_int(1, false), "").unwrap();
|
||||
ctx.builder
|
||||
.build_and(
|
||||
ctx.builder.build_int_add(val, max_rem, "").unwrap(),
|
||||
ctx.builder.build_not(max_rem, "").unwrap(),
|
||||
"",
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
let llvm_i8 = ctx.ctx.i8_type();
|
||||
let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
let align_ty = align_ty.into();
|
||||
|
||||
let size = ctx.builder.build_int_truncate_or_bit_cast(size, llvm_usize, "").unwrap();
|
||||
|
||||
debug_assert_eq!(
|
||||
size.get_type().get_bit_width(),
|
||||
llvm_usize.get_bit_width(),
|
||||
"Expected size_t ({}) for parameter `size` of `aligned_alloca`, got {}",
|
||||
llvm_usize,
|
||||
size.get_type(),
|
||||
);
|
||||
|
||||
let alignment = get_type_alignment(align_ty);
|
||||
let alignment = ctx.builder.build_int_truncate_or_bit_cast(alignment, llvm_usize, "").unwrap();
|
||||
|
||||
if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
|
||||
let alignment_bitcount = llvm_intrinsics::call_int_ctpop(ctx, alignment, None);
|
||||
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
ctx.builder
|
||||
.build_int_compare(
|
||||
IntPredicate::EQ,
|
||||
alignment_bitcount,
|
||||
alignment_bitcount.get_type().const_int(1, false),
|
||||
"",
|
||||
)
|
||||
.unwrap(),
|
||||
"0:AssertionError",
|
||||
"Expected power-of-two alignment for aligned_alloca, got {0}",
|
||||
[Some(alignment), None, None],
|
||||
ctx.current_loc,
|
||||
);
|
||||
}
|
||||
|
||||
let buffer_size = round_up(ctx, size, alignment);
|
||||
let aligned_slices = ctx.builder.build_int_unsigned_div(buffer_size, alignment, "").unwrap();
|
||||
|
||||
// Just to be absolutely sure, alloca in [i8 x alignment] slices
|
||||
let buffer = ctx.builder.build_array_alloca(align_ty, aligned_slices, "").unwrap();
|
||||
|
||||
ctx.builder
|
||||
.build_bit_cast(buffer, llvm_pi8, name.unwrap_or_default())
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap()
|
||||
}
|
||||
|
42
nac3core/src/codegen/model/any.rs
Normal file
42
nac3core/src/codegen/model/any.rs
Normal file
@ -0,0 +1,42 @@
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
types::{BasicType, BasicTypeEnum},
|
||||
values::BasicValueEnum,
|
||||
};
|
||||
|
||||
use crate::codegen::CodeGenerator;
|
||||
|
||||
use super::*;
|
||||
|
||||
/// A [`Model`] of any [`BasicTypeEnum`].
|
||||
///
|
||||
/// Use this when it is infeasible to use model abstractions.
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct Any<'ctx>(pub BasicTypeEnum<'ctx>);
|
||||
|
||||
impl<'ctx> Model<'ctx> for Any<'ctx> {
|
||||
type Value = BasicValueEnum<'ctx>;
|
||||
type Type = BasicTypeEnum<'ctx>;
|
||||
|
||||
fn llvm_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
_generator: &G,
|
||||
_ctx: &'ctx Context,
|
||||
) -> Self::Type {
|
||||
self.0
|
||||
}
|
||||
|
||||
fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
_generator: &mut G,
|
||||
_ctx: &'ctx Context,
|
||||
ty: T,
|
||||
) -> Result<(), ModelError> {
|
||||
let ty = ty.as_basic_type_enum();
|
||||
if ty == self.0 {
|
||||
Ok(())
|
||||
} else {
|
||||
Err(ModelError(format!("Expecting {}, but got {}", self.0, ty)))
|
||||
}
|
||||
}
|
||||
}
|
147
nac3core/src/codegen/model/array.rs
Normal file
147
nac3core/src/codegen/model/array.rs
Normal file
@ -0,0 +1,147 @@
|
||||
use std::fmt;
|
||||
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
types::{ArrayType, BasicType, BasicTypeEnum},
|
||||
values::{ArrayValue, IntValue},
|
||||
};
|
||||
|
||||
use crate::codegen::{CodeGenContext, CodeGenerator};
|
||||
|
||||
use super::*;
|
||||
|
||||
/// Trait for Rust structs identifying length values for [`Array`].
|
||||
pub trait ArrayLen: fmt::Debug + Clone + Copy {
|
||||
fn length(&self) -> u32;
|
||||
}
|
||||
|
||||
/// A statically known length.
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Len<const N: u32>;
|
||||
|
||||
/// A dynamically known length.
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct AnyLen(pub u32);
|
||||
|
||||
impl<const N: u32> ArrayLen for Len<N> {
|
||||
fn length(&self) -> u32 {
|
||||
N
|
||||
}
|
||||
}
|
||||
|
||||
impl ArrayLen for AnyLen {
|
||||
fn length(&self) -> u32 {
|
||||
self.0
|
||||
}
|
||||
}
|
||||
|
||||
/// A Model for an [`ArrayType`].
|
||||
///
|
||||
/// `Len` should be of a [`LenKind`] and `Item` should be a of [`Model`].
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Array<Len, Item> {
|
||||
/// Length of this array.
|
||||
pub len: Len,
|
||||
/// [`Model`] of the array items.
|
||||
pub item: Item,
|
||||
}
|
||||
|
||||
impl<'ctx, Len: ArrayLen, Item: Model<'ctx>> Model<'ctx> for Array<Len, Item> {
|
||||
type Value = ArrayValue<'ctx>;
|
||||
type Type = ArrayType<'ctx>;
|
||||
|
||||
fn llvm_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> Self::Type {
|
||||
self.item.llvm_type(generator, ctx).array_type(self.len.length())
|
||||
}
|
||||
|
||||
fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
ty: T,
|
||||
) -> Result<(), ModelError> {
|
||||
let ty = ty.as_basic_type_enum();
|
||||
let BasicTypeEnum::ArrayType(ty) = ty else {
|
||||
return Err(ModelError(format!("Expecting ArrayType, but got {ty:?}")));
|
||||
};
|
||||
|
||||
if ty.len() != self.len.length() {
|
||||
return Err(ModelError(format!(
|
||||
"Expecting ArrayType with size {}, but got an ArrayType with size {}",
|
||||
ty.len(),
|
||||
self.len.length()
|
||||
)));
|
||||
}
|
||||
|
||||
self.item
|
||||
.check_type(generator, ctx, ty.get_element_type())
|
||||
.map_err(|err| err.under_context("an ArrayType"))?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, Len: ArrayLen, Item: Model<'ctx>> Instance<'ctx, Ptr<Array<Len, Item>>> {
|
||||
/// Get the pointer to the `i`-th (0-based) array element.
|
||||
pub fn gep(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
i: IntValue<'ctx>,
|
||||
) -> Instance<'ctx, Ptr<Item>> {
|
||||
let zero = ctx.ctx.i32_type().const_zero();
|
||||
let ptr = unsafe { ctx.builder.build_in_bounds_gep(self.value, &[zero, i], "").unwrap() };
|
||||
|
||||
unsafe { Ptr(self.model.0.item).believe_value(ptr) }
|
||||
}
|
||||
|
||||
/// Like `gep` but `i` is a constant.
|
||||
pub fn gep_const(&self, ctx: &CodeGenContext<'ctx, '_>, i: u64) -> Instance<'ctx, Ptr<Item>> {
|
||||
assert!(
|
||||
i < u64::from(self.model.0.len.length()),
|
||||
"Index {i} is out of bounds. Array length = {}",
|
||||
self.model.0.len.length()
|
||||
);
|
||||
|
||||
let i = ctx.ctx.i32_type().const_int(i, false);
|
||||
self.gep(ctx, i)
|
||||
}
|
||||
|
||||
/// Convenience function equivalent to `.gep(...).load(...)`.
|
||||
pub fn get<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
i: IntValue<'ctx>,
|
||||
) -> Instance<'ctx, Item> {
|
||||
self.gep(ctx, i).load(generator, ctx)
|
||||
}
|
||||
|
||||
/// Like `get` but `i` is a constant.
|
||||
pub fn get_const<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
i: u64,
|
||||
) -> Instance<'ctx, Item> {
|
||||
self.gep_const(ctx, i).load(generator, ctx)
|
||||
}
|
||||
|
||||
/// Convenience function equivalent to `.gep(...).store(...)`.
|
||||
pub fn set(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
i: IntValue<'ctx>,
|
||||
value: Instance<'ctx, Item>,
|
||||
) {
|
||||
self.gep(ctx, i).store(ctx, value);
|
||||
}
|
||||
|
||||
/// Like `set` but `i` is a constant.
|
||||
pub fn set_const(&self, ctx: &CodeGenContext<'ctx, '_>, i: u64, value: Instance<'ctx, Item>) {
|
||||
self.gep_const(ctx, i).store(ctx, value);
|
||||
}
|
||||
}
|
207
nac3core/src/codegen/model/core.rs
Normal file
207
nac3core/src/codegen/model/core.rs
Normal file
@ -0,0 +1,207 @@
|
||||
use std::fmt;
|
||||
|
||||
use inkwell::{context::Context, types::*, values::*};
|
||||
use itertools::Itertools;
|
||||
|
||||
use super::*;
|
||||
use crate::codegen::{CodeGenContext, CodeGenerator};
|
||||
|
||||
/// A error type for reporting any [`Model`]-related error (e.g., a [`BasicType`] mismatch).
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct ModelError(pub String);
|
||||
|
||||
impl ModelError {
|
||||
/// Append a context message to the error.
|
||||
pub(super) fn under_context(mut self, context: &str) -> Self {
|
||||
self.0.push_str(" ... in ");
|
||||
self.0.push_str(context);
|
||||
self
|
||||
}
|
||||
}
|
||||
|
||||
/// Trait for Rust structs identifying [`BasicType`]s in the context of a known [`CodeGenerator`] and [`CodeGenContext`].
|
||||
///
|
||||
/// For instance,
|
||||
/// - [`Int<Int32>`] identifies an [`IntType`] with 32-bits.
|
||||
/// - [`Int<SizeT>`] identifies an [`IntType`] with bit-width [`CodeGenerator::get_size_type`].
|
||||
/// - [`Ptr<Int<SizeT>>`] identifies a [`PointerType`] that points to an [`IntType`] with bit-width [`CodeGenerator::get_size_type`].
|
||||
/// - [`Int<AnyInt>`] identifies an [`IntType`] with bit-width of whatever is set in the [`AnyInt`] object.
|
||||
/// - [`Any`] identifies a [`BasicType`] set in the [`Any`] object itself.
|
||||
///
|
||||
/// You can get the [`BasicType`] out of a model with [`Model::get_type`].
|
||||
///
|
||||
/// Furthermore, [`Instance<'ctx, M>`] is a simple structure that carries a [`BasicValue`] with [`BasicType`] identified by model `M`.
|
||||
///
|
||||
/// The main purpose of this abstraction is to have a more Rust type-safe way to use Inkwell and give type-hints for programmers.
|
||||
///
|
||||
/// ### Notes on `Default` trait
|
||||
///
|
||||
/// For some models like [`Int<Int32>`] or [`Int<SizeT>`], they have a [`Default`] trait since just by looking at their types, it is possible
|
||||
/// to tell the [`BasicType`]s they are identifying.
|
||||
///
|
||||
/// This can be used to create strongly-typed interfaces accepting only values of a specific [`BasicType`] without having to worry about
|
||||
/// writing debug assertions to check, for example, if the programmer has passed in an [`IntValue`] with the wrong bit-width.
|
||||
/// ```ignore
|
||||
/// fn give_me_i32_and_get_a_size_t_back<'ctx>(i32: Instance<'ctx, Int<Int32>>) -> Instance<'ctx, Int<SizeT>> {
|
||||
/// // code...
|
||||
/// }
|
||||
/// ```
|
||||
///
|
||||
/// ### Notes on converting between Inkwell and model/ge.
|
||||
///
|
||||
/// Suppose you have an [`IntValue`], and you want to pass it into a function that takes a [`Instance<'ctx, Int<Int32>>`]. You can do use
|
||||
/// [`Model::check_value`] or [`Model::believe_value`].
|
||||
/// ```ignore
|
||||
/// let my_value: IntValue<'ctx>;
|
||||
///
|
||||
/// let my_value = Int(Int32).check_value(my_value).unwrap(); // Panics if `my_value` is not 32-bit with a descriptive error message.
|
||||
///
|
||||
/// // or, if you are absolutely certain that `my_value` is 32-bit and doing extra checks is a waste of time:
|
||||
/// let my_value = Int(Int32).believe_value(my_value);
|
||||
/// ```
|
||||
pub trait Model<'ctx>: fmt::Debug + Clone + Copy {
|
||||
/// The [`BasicType`] *variant* this model is identifying.
|
||||
type Type: BasicType<'ctx>;
|
||||
|
||||
/// The [`BasicValue`] type of the [`BasicType`] of this model.
|
||||
type Value: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>>;
|
||||
|
||||
/// Return the [`BasicType`] of this model.
|
||||
#[must_use]
|
||||
fn llvm_type<G: CodeGenerator + ?Sized>(&self, generator: &G, ctx: &'ctx Context)
|
||||
-> Self::Type;
|
||||
|
||||
/// Get the number of bytes of the [`BasicType`] of this model.
|
||||
fn size_of<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
) -> IntValue<'ctx> {
|
||||
self.llvm_type(generator, ctx).size_of().unwrap()
|
||||
}
|
||||
|
||||
/// Check if a [`BasicType`] matches the [`BasicType`] of this model.
|
||||
fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
ty: T,
|
||||
) -> Result<(), ModelError>;
|
||||
|
||||
/// Create an instance from a value.
|
||||
///
|
||||
/// # Safety
|
||||
///
|
||||
/// Caller must make sure the type of `value` and the type of this `model` are equivalent.
|
||||
#[must_use]
|
||||
unsafe fn believe_value(&self, value: Self::Value) -> Instance<'ctx, Self> {
|
||||
Instance { model: *self, value }
|
||||
}
|
||||
|
||||
/// Check if a [`BasicValue`]'s type is equivalent to the type of this model.
|
||||
/// Wrap the [`BasicValue`] into an [`Instance`] if it is.
|
||||
fn check_value<V: BasicValue<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
value: V,
|
||||
) -> Result<Instance<'ctx, Self>, ModelError> {
|
||||
let value = value.as_basic_value_enum();
|
||||
self.check_type(generator, ctx, value.get_type())
|
||||
.map_err(|err| err.under_context(format!("the value {value:?}").as_str()))?;
|
||||
|
||||
let Ok(value) = Self::Value::try_from(value) else {
|
||||
unreachable!("check_type() has bad implementation")
|
||||
};
|
||||
unsafe { Ok(self.believe_value(value)) }
|
||||
}
|
||||
|
||||
// Allocate a value on the stack and return its pointer.
|
||||
fn alloca<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
) -> Instance<'ctx, Ptr<Self>> {
|
||||
let p = ctx.builder.build_alloca(self.llvm_type(generator, ctx.ctx), "").unwrap();
|
||||
unsafe { Ptr(*self).believe_value(p) }
|
||||
}
|
||||
|
||||
// Allocate an array on the stack and return its pointer.
|
||||
fn array_alloca<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
len: IntValue<'ctx>,
|
||||
) -> Instance<'ctx, Ptr<Self>> {
|
||||
let p =
|
||||
ctx.builder.build_array_alloca(self.llvm_type(generator, ctx.ctx), len, "").unwrap();
|
||||
unsafe { Ptr(*self).believe_value(p) }
|
||||
}
|
||||
|
||||
fn var_alloca<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
name: Option<&str>,
|
||||
) -> Result<Instance<'ctx, Ptr<Self>>, String> {
|
||||
let ty = self.llvm_type(generator, ctx.ctx).as_basic_type_enum();
|
||||
let p = generator.gen_var_alloc(ctx, ty, name)?;
|
||||
unsafe { Ok(Ptr(*self).believe_value(p)) }
|
||||
}
|
||||
|
||||
fn array_var_alloca<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
len: IntValue<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> Result<Instance<'ctx, Ptr<Self>>, String> {
|
||||
// TODO: Remove ArraySliceValue
|
||||
let ty = self.llvm_type(generator, ctx.ctx).as_basic_type_enum();
|
||||
let p = generator.gen_array_var_alloc(ctx, ty, len, name)?;
|
||||
unsafe { Ok(Ptr(*self).believe_value(PointerValue::from(p))) }
|
||||
}
|
||||
|
||||
/// Allocate a constant array.
|
||||
fn const_array<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
values: &[Instance<'ctx, Self>],
|
||||
) -> Instance<'ctx, Array<AnyLen, Self>> {
|
||||
macro_rules! make {
|
||||
($t:expr, $into_value:expr) => {
|
||||
$t.const_array(
|
||||
&values
|
||||
.iter()
|
||||
.map(|x| $into_value(x.value.as_basic_value_enum()))
|
||||
.collect_vec(),
|
||||
)
|
||||
};
|
||||
}
|
||||
|
||||
let value = match self.llvm_type(generator, ctx).as_basic_type_enum() {
|
||||
BasicTypeEnum::ArrayType(t) => make!(t, BasicValueEnum::into_array_value),
|
||||
BasicTypeEnum::IntType(t) => make!(t, BasicValueEnum::into_int_value),
|
||||
BasicTypeEnum::FloatType(t) => make!(t, BasicValueEnum::into_float_value),
|
||||
BasicTypeEnum::PointerType(t) => make!(t, BasicValueEnum::into_pointer_value),
|
||||
BasicTypeEnum::StructType(t) => make!(t, BasicValueEnum::into_struct_value),
|
||||
BasicTypeEnum::VectorType(t) => make!(t, BasicValueEnum::into_vector_value),
|
||||
};
|
||||
|
||||
Array { len: AnyLen(values.len() as u32), item: *self }
|
||||
.check_value(generator, ctx, value)
|
||||
.unwrap()
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct Instance<'ctx, M: Model<'ctx>> {
|
||||
/// The model of this instance.
|
||||
pub model: M,
|
||||
|
||||
/// The value of this instance.
|
||||
///
|
||||
/// It is guaranteed the [`BasicType`] of `value` is consistent with that of `model`.
|
||||
pub value: M::Value,
|
||||
}
|
94
nac3core/src/codegen/model/float.rs
Normal file
94
nac3core/src/codegen/model/float.rs
Normal file
@ -0,0 +1,94 @@
|
||||
use std::fmt;
|
||||
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
types::{BasicType, FloatType},
|
||||
values::FloatValue,
|
||||
};
|
||||
|
||||
use crate::codegen::CodeGenerator;
|
||||
|
||||
use super::*;
|
||||
|
||||
pub trait FloatKind<'ctx>: fmt::Debug + Clone + Copy {
|
||||
fn get_float_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> FloatType<'ctx>;
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Float32;
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Float64;
|
||||
|
||||
impl<'ctx> FloatKind<'ctx> for Float32 {
|
||||
fn get_float_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
_generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> FloatType<'ctx> {
|
||||
ctx.f32_type()
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> FloatKind<'ctx> for Float64 {
|
||||
fn get_float_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
_generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> FloatType<'ctx> {
|
||||
ctx.f64_type()
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct AnyFloat<'ctx>(FloatType<'ctx>);
|
||||
|
||||
impl<'ctx> FloatKind<'ctx> for AnyFloat<'ctx> {
|
||||
fn get_float_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
_generator: &G,
|
||||
_ctx: &'ctx Context,
|
||||
) -> FloatType<'ctx> {
|
||||
self.0
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Float<N>(pub N);
|
||||
|
||||
impl<'ctx, N: FloatKind<'ctx>> Model<'ctx> for Float<N> {
|
||||
type Value = FloatValue<'ctx>;
|
||||
type Type = FloatType<'ctx>;
|
||||
|
||||
fn llvm_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> Self::Type {
|
||||
self.0.get_float_type(generator, ctx)
|
||||
}
|
||||
|
||||
fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
ty: T,
|
||||
) -> Result<(), ModelError> {
|
||||
let ty = ty.as_basic_type_enum();
|
||||
let Ok(ty) = FloatType::try_from(ty) else {
|
||||
return Err(ModelError(format!("Expecting FloatType, but got {ty:?}")));
|
||||
};
|
||||
|
||||
let exp_ty = self.0.get_float_type(generator, ctx);
|
||||
|
||||
// TODO: Inkwell does not have get_bit_width for FloatType?
|
||||
if ty != exp_ty {
|
||||
return Err(ModelError(format!("Expecting {exp_ty:?}, but got {ty:?}")));
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
}
|
122
nac3core/src/codegen/model/function.rs
Normal file
122
nac3core/src/codegen/model/function.rs
Normal file
@ -0,0 +1,122 @@
|
||||
use inkwell::{
|
||||
attributes::{Attribute, AttributeLoc},
|
||||
types::{BasicMetadataTypeEnum, BasicType, FunctionType},
|
||||
values::{AnyValue, BasicMetadataValueEnum, BasicValue, BasicValueEnum, CallSiteValue},
|
||||
};
|
||||
use itertools::Itertools;
|
||||
|
||||
use crate::codegen::{CodeGenContext, CodeGenerator};
|
||||
|
||||
use super::*;
|
||||
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
struct Arg<'ctx> {
|
||||
ty: BasicMetadataTypeEnum<'ctx>,
|
||||
val: BasicMetadataValueEnum<'ctx>,
|
||||
}
|
||||
|
||||
/// A convenience structure to construct & call an LLVM function.
|
||||
///
|
||||
/// ### Usage
|
||||
///
|
||||
/// The syntax is like this:
|
||||
/// ```ignore
|
||||
/// let result = CallFunction::begin("my_function_name")
|
||||
/// .attrs(...)
|
||||
/// .arg(arg1)
|
||||
/// .arg(arg2)
|
||||
/// .arg(arg3)
|
||||
/// .returning("my_function_result", Int32);
|
||||
/// ```
|
||||
///
|
||||
/// The function `my_function_name` is called when `.returning()` (or its variants) is called, returning
|
||||
/// the result as an `Instance<'ctx, Int<Int32>>`.
|
||||
///
|
||||
/// If `my_function_name` has not been declared in `ctx.module`, once `.returning()` is called, a function
|
||||
/// declaration of `my_function_name` is added to `ctx.module`, where the [`FunctionType`] is deduced from
|
||||
/// the argument types and returning type.
|
||||
pub struct FnCall<'ctx, 'a, 'b, 'c, 'd, G: CodeGenerator + ?Sized> {
|
||||
generator: &'d mut G,
|
||||
ctx: &'b CodeGenContext<'ctx, 'a>,
|
||||
/// Function name
|
||||
name: &'c str,
|
||||
/// Call arguments
|
||||
args: Vec<Arg<'ctx>>,
|
||||
/// LLVM function Attributes
|
||||
attrs: Vec<&'static str>,
|
||||
}
|
||||
|
||||
impl<'ctx, 'a, 'b, 'c, 'd, G: CodeGenerator + ?Sized> FnCall<'ctx, 'a, 'b, 'c, 'd, G> {
|
||||
pub fn builder(generator: &'d mut G, ctx: &'b CodeGenContext<'ctx, 'a>, name: &'c str) -> Self {
|
||||
FnCall { generator, ctx, name, args: Vec::new(), attrs: Vec::new() }
|
||||
}
|
||||
|
||||
/// Push a list of LLVM function attributes to the function declaration.
|
||||
#[must_use]
|
||||
pub fn attrs(mut self, attrs: Vec<&'static str>) -> Self {
|
||||
self.attrs = attrs;
|
||||
self
|
||||
}
|
||||
|
||||
/// Push a call argument to the function call.
|
||||
#[allow(clippy::needless_pass_by_value)]
|
||||
#[must_use]
|
||||
pub fn arg<M: Model<'ctx>>(mut self, arg: Instance<'ctx, M>) -> Self {
|
||||
let arg = Arg {
|
||||
ty: arg.model.llvm_type(self.generator, self.ctx.ctx).as_basic_type_enum().into(),
|
||||
val: arg.value.as_basic_value_enum().into(),
|
||||
};
|
||||
self.args.push(arg);
|
||||
self
|
||||
}
|
||||
|
||||
/// Call the function and expect the function to return a value of type of `return_model`.
|
||||
#[must_use]
|
||||
pub fn returning<M: Model<'ctx>>(self, name: &str, return_model: M) -> Instance<'ctx, M> {
|
||||
let ret_ty = return_model.llvm_type(self.generator, self.ctx.ctx);
|
||||
|
||||
let ret = self.call(|tys| ret_ty.fn_type(tys, false), name);
|
||||
let ret = BasicValueEnum::try_from(ret.as_any_value_enum()).unwrap(); // Must work
|
||||
let ret = return_model.check_value(self.generator, self.ctx.ctx, ret).unwrap(); // Must work
|
||||
ret
|
||||
}
|
||||
|
||||
/// Like [`CallFunction::returning_`] but `return_model` is automatically inferred.
|
||||
#[must_use]
|
||||
pub fn returning_auto<M: Model<'ctx> + Default>(self, name: &str) -> Instance<'ctx, M> {
|
||||
self.returning(name, M::default())
|
||||
}
|
||||
|
||||
/// Call the function and expect the function to return a void-type.
|
||||
pub fn returning_void(self) {
|
||||
let ret_ty = self.ctx.ctx.void_type();
|
||||
|
||||
let _ = self.call(|tys| ret_ty.fn_type(tys, false), "");
|
||||
}
|
||||
|
||||
fn call<F>(&self, make_fn_type: F, return_value_name: &str) -> CallSiteValue<'ctx>
|
||||
where
|
||||
F: FnOnce(&[BasicMetadataTypeEnum<'ctx>]) -> FunctionType<'ctx>,
|
||||
{
|
||||
// Get the LLVM function.
|
||||
let func = self.ctx.module.get_function(self.name).unwrap_or_else(|| {
|
||||
// Declare the function if it doesn't exist.
|
||||
let tys = self.args.iter().map(|arg| arg.ty).collect_vec();
|
||||
|
||||
let func_type = make_fn_type(&tys);
|
||||
let func = self.ctx.module.add_function(self.name, func_type, None);
|
||||
|
||||
for attr in &self.attrs {
|
||||
func.add_attribute(
|
||||
AttributeLoc::Function,
|
||||
self.ctx.ctx.create_enum_attribute(Attribute::get_named_enum_kind_id(attr), 0),
|
||||
);
|
||||
}
|
||||
|
||||
func
|
||||
});
|
||||
|
||||
let vals = self.args.iter().map(|arg| arg.val).collect_vec();
|
||||
self.ctx.builder.build_call(func, &vals, return_value_name).unwrap()
|
||||
}
|
||||
}
|
422
nac3core/src/codegen/model/int.rs
Normal file
422
nac3core/src/codegen/model/int.rs
Normal file
@ -0,0 +1,422 @@
|
||||
use std::{cmp::Ordering, fmt};
|
||||
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
types::{BasicType, IntType},
|
||||
values::IntValue,
|
||||
IntPredicate,
|
||||
};
|
||||
|
||||
use crate::codegen::{CodeGenContext, CodeGenerator};
|
||||
|
||||
use super::*;
|
||||
|
||||
pub trait IntKind<'ctx>: fmt::Debug + Clone + Copy {
|
||||
fn get_int_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> IntType<'ctx>;
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Bool;
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Byte;
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Int32;
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Int64;
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct SizeT;
|
||||
|
||||
impl<'ctx> IntKind<'ctx> for Bool {
|
||||
fn get_int_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
_generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> IntType<'ctx> {
|
||||
ctx.bool_type()
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> IntKind<'ctx> for Byte {
|
||||
fn get_int_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
_generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> IntType<'ctx> {
|
||||
ctx.i8_type()
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> IntKind<'ctx> for Int32 {
|
||||
fn get_int_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
_generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> IntType<'ctx> {
|
||||
ctx.i32_type()
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> IntKind<'ctx> for Int64 {
|
||||
fn get_int_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
_generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> IntType<'ctx> {
|
||||
ctx.i64_type()
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> IntKind<'ctx> for SizeT {
|
||||
fn get_int_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> IntType<'ctx> {
|
||||
generator.get_size_type(ctx)
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct AnyInt<'ctx>(pub IntType<'ctx>);
|
||||
|
||||
impl<'ctx> IntKind<'ctx> for AnyInt<'ctx> {
|
||||
fn get_int_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
_generator: &G,
|
||||
_ctx: &'ctx Context,
|
||||
) -> IntType<'ctx> {
|
||||
self.0
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Int<N>(pub N);
|
||||
|
||||
impl<'ctx, N: IntKind<'ctx>> Model<'ctx> for Int<N> {
|
||||
type Value = IntValue<'ctx>;
|
||||
type Type = IntType<'ctx>;
|
||||
|
||||
fn llvm_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> Self::Type {
|
||||
self.0.get_int_type(generator, ctx)
|
||||
}
|
||||
|
||||
fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
ty: T,
|
||||
) -> Result<(), ModelError> {
|
||||
let ty = ty.as_basic_type_enum();
|
||||
let Ok(ty) = IntType::try_from(ty) else {
|
||||
return Err(ModelError(format!("Expecting IntType, but got {ty:?}")));
|
||||
};
|
||||
|
||||
let exp_ty = self.0.get_int_type(generator, ctx);
|
||||
if ty.get_bit_width() != exp_ty.get_bit_width() {
|
||||
return Err(ModelError(format!(
|
||||
"Expecting IntType to have {} bit(s), but got {} bit(s)",
|
||||
exp_ty.get_bit_width(),
|
||||
ty.get_bit_width()
|
||||
)));
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, N: IntKind<'ctx>> Int<N> {
|
||||
pub fn const_int<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
value: u64,
|
||||
sign_extend: bool,
|
||||
) -> Instance<'ctx, Self> {
|
||||
let value = self.llvm_type(generator, ctx).const_int(value, sign_extend);
|
||||
unsafe { self.believe_value(value) }
|
||||
}
|
||||
|
||||
pub fn const_0<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
) -> Instance<'ctx, Self> {
|
||||
let value = self.llvm_type(generator, ctx).const_zero();
|
||||
unsafe { self.believe_value(value) }
|
||||
}
|
||||
|
||||
pub fn const_1<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
) -> Instance<'ctx, Self> {
|
||||
self.const_int(generator, ctx, 1, false)
|
||||
}
|
||||
|
||||
pub fn const_all_ones<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
) -> Instance<'ctx, Self> {
|
||||
let value = self.llvm_type(generator, ctx).const_all_ones();
|
||||
unsafe { self.believe_value(value) }
|
||||
}
|
||||
|
||||
pub fn s_extend_or_bit_cast<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
value: IntValue<'ctx>,
|
||||
) -> Instance<'ctx, Self> {
|
||||
assert!(
|
||||
value.get_type().get_bit_width()
|
||||
<= self.0.get_int_type(generator, ctx.ctx).get_bit_width()
|
||||
);
|
||||
let value = ctx
|
||||
.builder
|
||||
.build_int_s_extend_or_bit_cast(value, self.llvm_type(generator, ctx.ctx), "")
|
||||
.unwrap();
|
||||
unsafe { self.believe_value(value) }
|
||||
}
|
||||
|
||||
pub fn s_extend<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
value: IntValue<'ctx>,
|
||||
) -> Instance<'ctx, Self> {
|
||||
assert!(
|
||||
value.get_type().get_bit_width()
|
||||
< self.0.get_int_type(generator, ctx.ctx).get_bit_width()
|
||||
);
|
||||
let value =
|
||||
ctx.builder.build_int_s_extend(value, self.llvm_type(generator, ctx.ctx), "").unwrap();
|
||||
unsafe { self.believe_value(value) }
|
||||
}
|
||||
|
||||
pub fn z_extend_or_bit_cast<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
value: IntValue<'ctx>,
|
||||
) -> Instance<'ctx, Self> {
|
||||
assert!(
|
||||
value.get_type().get_bit_width()
|
||||
<= self.0.get_int_type(generator, ctx.ctx).get_bit_width()
|
||||
);
|
||||
let value = ctx
|
||||
.builder
|
||||
.build_int_z_extend_or_bit_cast(value, self.llvm_type(generator, ctx.ctx), "")
|
||||
.unwrap();
|
||||
unsafe { self.believe_value(value) }
|
||||
}
|
||||
|
||||
pub fn z_extend<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
value: IntValue<'ctx>,
|
||||
) -> Instance<'ctx, Self> {
|
||||
assert!(
|
||||
value.get_type().get_bit_width()
|
||||
< self.0.get_int_type(generator, ctx.ctx).get_bit_width()
|
||||
);
|
||||
let value =
|
||||
ctx.builder.build_int_z_extend(value, self.llvm_type(generator, ctx.ctx), "").unwrap();
|
||||
unsafe { self.believe_value(value) }
|
||||
}
|
||||
|
||||
pub fn truncate_or_bit_cast<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
value: IntValue<'ctx>,
|
||||
) -> Instance<'ctx, Self> {
|
||||
assert!(
|
||||
value.get_type().get_bit_width()
|
||||
>= self.0.get_int_type(generator, ctx.ctx).get_bit_width()
|
||||
);
|
||||
let value = ctx
|
||||
.builder
|
||||
.build_int_truncate_or_bit_cast(value, self.llvm_type(generator, ctx.ctx), "")
|
||||
.unwrap();
|
||||
unsafe { self.believe_value(value) }
|
||||
}
|
||||
|
||||
pub fn truncate<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
value: IntValue<'ctx>,
|
||||
) -> Instance<'ctx, Self> {
|
||||
assert!(
|
||||
value.get_type().get_bit_width()
|
||||
> self.0.get_int_type(generator, ctx.ctx).get_bit_width()
|
||||
);
|
||||
let value =
|
||||
ctx.builder.build_int_truncate(value, self.llvm_type(generator, ctx.ctx), "").unwrap();
|
||||
unsafe { self.believe_value(value) }
|
||||
}
|
||||
|
||||
/// `sext` or `trunc` an int to this model's int type. Does nothing if equal bit-widths.
|
||||
pub fn s_extend_or_truncate<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
value: IntValue<'ctx>,
|
||||
) -> Instance<'ctx, Self> {
|
||||
let their_width = value.get_type().get_bit_width();
|
||||
let our_width = self.0.get_int_type(generator, ctx.ctx).get_bit_width();
|
||||
match their_width.cmp(&our_width) {
|
||||
Ordering::Less => self.s_extend(generator, ctx, value),
|
||||
Ordering::Equal => unsafe { self.believe_value(value) },
|
||||
Ordering::Greater => self.truncate(generator, ctx, value),
|
||||
}
|
||||
}
|
||||
|
||||
/// `zext` or `trunc` an int to this model's int type. Does nothing if equal bit-widths.
|
||||
pub fn z_extend_or_truncate<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
value: IntValue<'ctx>,
|
||||
) -> Instance<'ctx, Self> {
|
||||
let their_width = value.get_type().get_bit_width();
|
||||
let our_width = self.0.get_int_type(generator, ctx.ctx).get_bit_width();
|
||||
match their_width.cmp(&our_width) {
|
||||
Ordering::Less => self.z_extend(generator, ctx, value),
|
||||
Ordering::Equal => unsafe { self.believe_value(value) },
|
||||
Ordering::Greater => self.truncate(generator, ctx, value),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl Int<Bool> {
|
||||
#[must_use]
|
||||
pub fn const_false<'ctx, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
) -> Instance<'ctx, Self> {
|
||||
self.const_int(generator, ctx, 0, false)
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn const_true<'ctx, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
) -> Instance<'ctx, Self> {
|
||||
self.const_int(generator, ctx, 1, false)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, N: IntKind<'ctx>> Instance<'ctx, Int<N>> {
|
||||
pub fn s_extend_or_bit_cast<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
to_int_kind: NewN,
|
||||
) -> Instance<'ctx, Int<NewN>> {
|
||||
Int(to_int_kind).s_extend_or_bit_cast(generator, ctx, self.value)
|
||||
}
|
||||
|
||||
pub fn s_extend<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
to_int_kind: NewN,
|
||||
) -> Instance<'ctx, Int<NewN>> {
|
||||
Int(to_int_kind).s_extend(generator, ctx, self.value)
|
||||
}
|
||||
|
||||
pub fn z_extend_or_bit_cast<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
to_int_kind: NewN,
|
||||
) -> Instance<'ctx, Int<NewN>> {
|
||||
Int(to_int_kind).z_extend_or_bit_cast(generator, ctx, self.value)
|
||||
}
|
||||
|
||||
pub fn z_extend<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
to_int_kind: NewN,
|
||||
) -> Instance<'ctx, Int<NewN>> {
|
||||
Int(to_int_kind).z_extend(generator, ctx, self.value)
|
||||
}
|
||||
|
||||
pub fn truncate_or_bit_cast<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
to_int_kind: NewN,
|
||||
) -> Instance<'ctx, Int<NewN>> {
|
||||
Int(to_int_kind).truncate_or_bit_cast(generator, ctx, self.value)
|
||||
}
|
||||
|
||||
pub fn truncate<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
to_int_kind: NewN,
|
||||
) -> Instance<'ctx, Int<NewN>> {
|
||||
Int(to_int_kind).truncate(generator, ctx, self.value)
|
||||
}
|
||||
|
||||
pub fn s_extend_or_truncate<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
to_int_kind: NewN,
|
||||
) -> Instance<'ctx, Int<NewN>> {
|
||||
Int(to_int_kind).s_extend_or_truncate(generator, ctx, self.value)
|
||||
}
|
||||
|
||||
pub fn z_extend_or_truncate<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
to_int_kind: NewN,
|
||||
) -> Instance<'ctx, Int<NewN>> {
|
||||
Int(to_int_kind).z_extend_or_truncate(generator, ctx, self.value)
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn add(&self, ctx: &CodeGenContext<'ctx, '_>, other: Self) -> Self {
|
||||
let value = ctx.builder.build_int_add(self.value, other.value, "").unwrap();
|
||||
unsafe { self.model.believe_value(value) }
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn sub(&self, ctx: &CodeGenContext<'ctx, '_>, other: Self) -> Self {
|
||||
let value = ctx.builder.build_int_sub(self.value, other.value, "").unwrap();
|
||||
unsafe { self.model.believe_value(value) }
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn mul(&self, ctx: &CodeGenContext<'ctx, '_>, other: Self) -> Self {
|
||||
let value = ctx.builder.build_int_mul(self.value, other.value, "").unwrap();
|
||||
unsafe { self.model.believe_value(value) }
|
||||
}
|
||||
|
||||
pub fn compare(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
op: IntPredicate,
|
||||
other: Self,
|
||||
) -> Instance<'ctx, Int<Bool>> {
|
||||
let value = ctx.builder.build_int_compare(op, self.value, other.value, "").unwrap();
|
||||
unsafe { Int(Bool).believe_value(value) }
|
||||
}
|
||||
}
|
17
nac3core/src/codegen/model/mod.rs
Normal file
17
nac3core/src/codegen/model/mod.rs
Normal file
@ -0,0 +1,17 @@
|
||||
mod any;
|
||||
mod array;
|
||||
mod core;
|
||||
mod float;
|
||||
pub mod function;
|
||||
mod int;
|
||||
mod ptr;
|
||||
mod structure;
|
||||
pub mod util;
|
||||
|
||||
pub use any::*;
|
||||
pub use array::*;
|
||||
pub use core::*;
|
||||
pub use float::*;
|
||||
pub use int::*;
|
||||
pub use ptr::*;
|
||||
pub use structure::*;
|
223
nac3core/src/codegen/model/ptr.rs
Normal file
223
nac3core/src/codegen/model/ptr.rs
Normal file
@ -0,0 +1,223 @@
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
types::{BasicType, BasicTypeEnum, PointerType},
|
||||
values::{IntValue, PointerValue},
|
||||
AddressSpace,
|
||||
};
|
||||
|
||||
use crate::codegen::{llvm_intrinsics::call_memcpy_generic, CodeGenContext, CodeGenerator};
|
||||
|
||||
use super::*;
|
||||
|
||||
/// A model for [`PointerType`].
|
||||
///
|
||||
/// `Item` is the element type this pointer is pointing to, and should be of a [`Model`].
|
||||
///
|
||||
// TODO: LLVM 15: `Item` is a Rust type-hint for the LLVM type of value the `.store()/.load()` family
|
||||
// of functions return. If a truly opaque pointer is needed, tell the programmer to use `OpaquePtr`.
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Ptr<Item>(pub Item);
|
||||
|
||||
/// An opaque pointer. Like [`Ptr`] but without any Rust type-hints about its element type.
|
||||
///
|
||||
/// `.load()/.store()` is not available for [`Instance`]s of opaque pointers.
|
||||
pub type OpaquePtr = Ptr<()>;
|
||||
|
||||
// TODO: LLVM 15: `Item: Model<'ctx>` don't even need to be a model anymore. It will only be
|
||||
// a type-hint for the `.load()/.store()` functions for the `pointee_ty`.
|
||||
//
|
||||
// See https://thedan64.github.io/inkwell/inkwell/builder/struct.Builder.html#method.build_load.
|
||||
impl<'ctx, Item: Model<'ctx>> Model<'ctx> for Ptr<Item> {
|
||||
type Value = PointerValue<'ctx>;
|
||||
type Type = PointerType<'ctx>;
|
||||
|
||||
fn llvm_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> Self::Type {
|
||||
// TODO: LLVM 15: ctx.ptr_type(AddressSpace::default())
|
||||
self.0.llvm_type(generator, ctx).ptr_type(AddressSpace::default())
|
||||
}
|
||||
|
||||
fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
ty: T,
|
||||
) -> Result<(), ModelError> {
|
||||
let ty = ty.as_basic_type_enum();
|
||||
let Ok(ty) = PointerType::try_from(ty) else {
|
||||
return Err(ModelError(format!("Expecting PointerType, but got {ty:?}")));
|
||||
};
|
||||
|
||||
let elem_ty = ty.get_element_type();
|
||||
let Ok(elem_ty) = BasicTypeEnum::try_from(elem_ty) else {
|
||||
return Err(ModelError(format!(
|
||||
"Expecting pointer element type to be a BasicTypeEnum, but got {elem_ty:?}"
|
||||
)));
|
||||
};
|
||||
|
||||
// TODO: inkwell `get_element_type()` will be deprecated.
|
||||
// Remove the check for `get_element_type()` when the time comes.
|
||||
self.0
|
||||
.check_type(generator, ctx, elem_ty)
|
||||
.map_err(|err| err.under_context("a PointerType"))?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, Item: Model<'ctx>> Ptr<Item> {
|
||||
/// Return a ***constant*** nullptr.
|
||||
pub fn nullptr<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
) -> Instance<'ctx, Ptr<Item>> {
|
||||
let ptr = self.llvm_type(generator, ctx).const_null();
|
||||
unsafe { self.believe_value(ptr) }
|
||||
}
|
||||
|
||||
/// Cast a pointer into this model with [`inkwell::builder::Builder::build_pointer_cast`]
|
||||
pub fn pointer_cast<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
ptr: PointerValue<'ctx>,
|
||||
) -> Instance<'ctx, Ptr<Item>> {
|
||||
// TODO: LLVM 15: Write in an impl where `Item` does not have to be `Model<'ctx>`.
|
||||
// TODO: LLVM 15: This function will only have to be:
|
||||
// ```
|
||||
// return self.believe_value(ptr);
|
||||
// ```
|
||||
let t = self.llvm_type(generator, ctx.ctx);
|
||||
let ptr = ctx.builder.build_pointer_cast(ptr, t, "").unwrap();
|
||||
unsafe { self.believe_value(ptr) }
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, Item: Model<'ctx>> Instance<'ctx, Ptr<Item>> {
|
||||
/// Offset the pointer by [`inkwell::builder::Builder::build_in_bounds_gep`].
|
||||
#[must_use]
|
||||
pub fn offset(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
offset: IntValue<'ctx>,
|
||||
) -> Instance<'ctx, Ptr<Item>> {
|
||||
let p = unsafe { ctx.builder.build_in_bounds_gep(self.value, &[offset], "").unwrap() };
|
||||
unsafe { self.model.believe_value(p) }
|
||||
}
|
||||
|
||||
/// Offset the pointer by [`inkwell::builder::Builder::build_in_bounds_gep`] by a constant offset.
|
||||
#[must_use]
|
||||
pub fn offset_const(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
offset: i64,
|
||||
) -> Instance<'ctx, Ptr<Item>> {
|
||||
let offset = ctx.ctx.i32_type().const_int(offset as u64, true);
|
||||
self.offset(ctx, offset)
|
||||
}
|
||||
|
||||
pub fn set_index(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
index: IntValue<'ctx>,
|
||||
value: Instance<'ctx, Item>,
|
||||
) {
|
||||
self.offset(ctx, index).store(ctx, value);
|
||||
}
|
||||
|
||||
pub fn set_index_const(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
index: i64,
|
||||
value: Instance<'ctx, Item>,
|
||||
) {
|
||||
self.offset_const(ctx, index).store(ctx, value);
|
||||
}
|
||||
|
||||
pub fn get_index<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
index: IntValue<'ctx>,
|
||||
) -> Instance<'ctx, Item> {
|
||||
self.offset(ctx, index).load(generator, ctx)
|
||||
}
|
||||
|
||||
pub fn get_index_const<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
index: i64,
|
||||
) -> Instance<'ctx, Item> {
|
||||
self.offset_const(ctx, index).load(generator, ctx)
|
||||
}
|
||||
|
||||
/// Load the value with [`inkwell::builder::Builder::build_load`].
|
||||
pub fn load<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
) -> Instance<'ctx, Item> {
|
||||
let value = ctx.builder.build_load(self.value, "").unwrap();
|
||||
self.model.0.check_value(generator, ctx.ctx, value).unwrap() // If unwrap() panics, there is a logic error.
|
||||
}
|
||||
|
||||
/// Store a value with [`inkwell::builder::Builder::build_store`].
|
||||
pub fn store(&self, ctx: &CodeGenContext<'ctx, '_>, value: Instance<'ctx, Item>) {
|
||||
ctx.builder.build_store(self.value, value.value).unwrap();
|
||||
}
|
||||
|
||||
/// Return a casted pointer of element type `NewElement` with [`inkwell::builder::Builder::build_pointer_cast`].
|
||||
pub fn pointer_cast<NewItem: Model<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
new_item: NewItem,
|
||||
) -> Instance<'ctx, Ptr<NewItem>> {
|
||||
// TODO: LLVM 15: Write in an impl where `Item` does not have to be `Model<'ctx>`.
|
||||
Ptr(new_item).pointer_cast(generator, ctx, self.value)
|
||||
}
|
||||
|
||||
/// Cast this pointer to `uint8_t*`
|
||||
pub fn cast_to_pi8<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
) -> Instance<'ctx, Ptr<Int<Byte>>> {
|
||||
Ptr(Int(Byte)).pointer_cast(generator, ctx, self.value)
|
||||
}
|
||||
|
||||
/// Check if the pointer is null with [`inkwell::builder::Builder::build_is_null`].
|
||||
pub fn is_null(&self, ctx: &CodeGenContext<'ctx, '_>) -> Instance<'ctx, Int<Bool>> {
|
||||
let value = ctx.builder.build_is_null(self.value, "").unwrap();
|
||||
unsafe { Int(Bool).believe_value(value) }
|
||||
}
|
||||
|
||||
/// Check if the pointer is not null with [`inkwell::builder::Builder::build_is_not_null`].
|
||||
pub fn is_not_null(&self, ctx: &CodeGenContext<'ctx, '_>) -> Instance<'ctx, Int<Bool>> {
|
||||
let value = ctx.builder.build_is_not_null(self.value, "").unwrap();
|
||||
unsafe { Int(Bool).believe_value(value) }
|
||||
}
|
||||
|
||||
/// `memcpy` from another pointer.
|
||||
pub fn copy_from<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
source: Self,
|
||||
num_items: IntValue<'ctx>,
|
||||
) {
|
||||
// Force extend `num_items` and `itemsize` to `i64` so their types would match.
|
||||
let itemsize = self.model.size_of(generator, ctx.ctx);
|
||||
let itemsize = Int(SizeT).z_extend_or_truncate(generator, ctx, itemsize);
|
||||
let num_items = Int(SizeT).z_extend_or_truncate(generator, ctx, num_items);
|
||||
let totalsize = itemsize.mul(ctx, num_items);
|
||||
|
||||
let is_volatile = ctx.ctx.bool_type().const_zero(); // is_volatile = false
|
||||
call_memcpy_generic(ctx, self.value, source.value, totalsize.value, is_volatile);
|
||||
}
|
||||
}
|
364
nac3core/src/codegen/model/structure.rs
Normal file
364
nac3core/src/codegen/model/structure.rs
Normal file
@ -0,0 +1,364 @@
|
||||
use std::fmt;
|
||||
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
types::{BasicType, BasicTypeEnum, StructType},
|
||||
values::{BasicValueEnum, StructValue},
|
||||
};
|
||||
|
||||
use crate::codegen::{CodeGenContext, CodeGenerator};
|
||||
|
||||
use super::*;
|
||||
|
||||
/// A traveral that traverses a Rust `struct` that is used to declare an LLVM's struct's field types.
|
||||
pub trait FieldTraversal<'ctx> {
|
||||
/// Output type of [`FieldTraversal::add`].
|
||||
type Output<M>;
|
||||
|
||||
/// Traverse through the type of a declared field and do something with it.
|
||||
///
|
||||
/// * `name` - The cosmetic name of the LLVM field. Used for debugging.
|
||||
/// * `model` - The [`Model`] representing the LLVM type of this field.
|
||||
fn add<M: Model<'ctx>>(&mut self, name: &'static str, model: M) -> Self::Output<M>;
|
||||
|
||||
/// Like [`FieldTraversal::add`] but [`Model`] is automatically inferred from its [`Default`] trait.
|
||||
fn add_auto<M: Model<'ctx> + Default>(&mut self, name: &'static str) -> Self::Output<M> {
|
||||
self.add(name, M::default())
|
||||
}
|
||||
}
|
||||
|
||||
/// Descriptor of an LLVM struct field.
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct GepField<M> {
|
||||
/// The GEP index of this field. This is the index to use with `build_gep`.
|
||||
pub gep_index: u32,
|
||||
/// The cosmetic name of this field.
|
||||
pub name: &'static str,
|
||||
/// The [`Model`] of this field's type.
|
||||
pub model: M,
|
||||
}
|
||||
|
||||
/// A traversal to calculate the GEP index of fields.
|
||||
pub struct GepFieldTraversal {
|
||||
/// The current GEP index.
|
||||
gep_index_counter: u32,
|
||||
}
|
||||
|
||||
impl<'ctx> FieldTraversal<'ctx> for GepFieldTraversal {
|
||||
type Output<M> = GepField<M>;
|
||||
|
||||
fn add<M: Model<'ctx>>(&mut self, name: &'static str, model: M) -> Self::Output<M> {
|
||||
let gep_index = self.gep_index_counter;
|
||||
self.gep_index_counter += 1;
|
||||
Self::Output { gep_index, name, model }
|
||||
}
|
||||
}
|
||||
|
||||
/// A traversal to collect the field types of a struct.
|
||||
///
|
||||
/// This is used to collect field types and construct the LLVM struct type with [`Context::struct_type`].
|
||||
struct TypeFieldTraversal<'ctx, 'a, G: CodeGenerator + ?Sized> {
|
||||
generator: &'a G,
|
||||
ctx: &'ctx Context,
|
||||
/// The collected field types so far in exact order.
|
||||
field_types: Vec<BasicTypeEnum<'ctx>>,
|
||||
}
|
||||
|
||||
impl<'ctx, 'a, G: CodeGenerator + ?Sized> FieldTraversal<'ctx> for TypeFieldTraversal<'ctx, 'a, G> {
|
||||
type Output<M> = (); // Checking types return nothing.
|
||||
|
||||
fn add<M: Model<'ctx>>(&mut self, _name: &'static str, model: M) -> Self::Output<M> {
|
||||
let t = model.llvm_type(self.generator, self.ctx).as_basic_type_enum();
|
||||
self.field_types.push(t);
|
||||
}
|
||||
}
|
||||
|
||||
/// A traversal to check the types of fields.
|
||||
struct CheckTypeFieldTraversal<'ctx, 'a, G: CodeGenerator + ?Sized> {
|
||||
generator: &'a mut G,
|
||||
ctx: &'ctx Context,
|
||||
/// The current GEP index, so we can tell the index of the field we are checking
|
||||
/// and report the GEP index.
|
||||
gep_index_counter: u32,
|
||||
/// The [`StructType`] to check.
|
||||
scrutinee: StructType<'ctx>,
|
||||
/// The list of collected errors so far.
|
||||
errors: Vec<ModelError>,
|
||||
}
|
||||
|
||||
impl<'ctx, 'a, G: CodeGenerator + ?Sized> FieldTraversal<'ctx>
|
||||
for CheckTypeFieldTraversal<'ctx, 'a, G>
|
||||
{
|
||||
type Output<M> = (); // Checking types return nothing.
|
||||
|
||||
fn add<M: Model<'ctx>>(&mut self, name: &'static str, model: M) -> Self::Output<M> {
|
||||
let gep_index = self.gep_index_counter;
|
||||
self.gep_index_counter += 1;
|
||||
|
||||
if let Some(t) = self.scrutinee.get_field_type_at_index(gep_index) {
|
||||
if let Err(err) = model.check_type(self.generator, self.ctx, t) {
|
||||
self.errors
|
||||
.push(err.under_context(format!("field #{gep_index} '{name}'").as_str()));
|
||||
}
|
||||
}
|
||||
// Otherwise, it will be caught by Struct's `check_type`.
|
||||
}
|
||||
}
|
||||
|
||||
/// A trait for Rust structs identifying LLVM structures.
|
||||
///
|
||||
/// ### Example
|
||||
///
|
||||
/// Suppose you want to define this structure:
|
||||
/// ```c
|
||||
/// template <typename T>
|
||||
/// struct ContiguousNDArray {
|
||||
/// size_t ndims;
|
||||
/// size_t* shape;
|
||||
/// T* data;
|
||||
/// }
|
||||
/// ```
|
||||
///
|
||||
/// This is how it should be done:
|
||||
/// ```ignore
|
||||
/// pub struct ContiguousNDArrayFields<'ctx, F: FieldTraversal<'ctx>, Item: Model<'ctx>> {
|
||||
/// pub ndims: F::Out<Int<SizeT>>,
|
||||
/// pub shape: F::Out<Ptr<Int<SizeT>>>,
|
||||
/// pub data: F::Out<Ptr<Item>>,
|
||||
/// }
|
||||
///
|
||||
/// /// An ndarray without strides and non-opaque `data` field in NAC3.
|
||||
/// #[derive(Debug, Clone, Copy)]
|
||||
/// pub struct ContiguousNDArray<M> {
|
||||
/// /// [`Model`] of the items.
|
||||
/// pub item: M,
|
||||
/// }
|
||||
///
|
||||
/// impl<'ctx, Item: Model<'ctx>> StructKind<'ctx> for ContiguousNDArray<Item> {
|
||||
/// type Fields<F: FieldTraversal<'ctx>> = ContiguousNDArrayFields<'ctx, F, Item>;
|
||||
///
|
||||
/// fn traverse_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
|
||||
/// // The order of `traversal.add*` is important
|
||||
/// Self::Fields {
|
||||
/// ndims: traversal.add_auto("ndims"),
|
||||
/// shape: traversal.add_auto("shape"),
|
||||
/// data: traversal.add("data", Ptr(self.item)),
|
||||
/// }
|
||||
/// }
|
||||
/// }
|
||||
/// ```
|
||||
///
|
||||
/// The [`FieldTraversal`] here is a mechanism to allow the fields of `ContiguousNDArrayFields` to be
|
||||
/// traversed to do useful work such as:
|
||||
///
|
||||
/// - To create the [`StructType`] of `ContiguousNDArray` by collecting [`BasicType`]s of the fields.
|
||||
/// - To enable the `.gep(ctx, |f| f.ndims).store(ctx, ...)` syntax.
|
||||
///
|
||||
/// Suppose now that you have defined `ContiguousNDArray` and you want to allocate a `ContiguousNDArray`
|
||||
/// with dtype `float64` in LLVM, this is how you do it:
|
||||
/// ```ignore
|
||||
/// type F64NDArray = Struct<ContiguousNDArray<Float<Float64>>>; // Type alias for leaner documentation
|
||||
/// let model: F64NDArray = Struct(ContigousNDArray { item: Float(Float64) });
|
||||
/// let ndarray: Instance<'ctx, Ptr<F64NDArray>> = model.alloca(generator, ctx);
|
||||
/// ```
|
||||
///
|
||||
/// ...and here is how you may manipulate/access `ndarray`:
|
||||
///
|
||||
/// (NOTE: some arguments have been omitted)
|
||||
///
|
||||
/// ```ignore
|
||||
/// // Get `&ndarray->data`
|
||||
/// ndarray.gep(|f| f.data); // type: Instance<'ctx, Ptr<Float<Float64>>>
|
||||
///
|
||||
/// // Get `ndarray->ndims`
|
||||
/// ndarray.get(|f| f.ndims); // type: Instance<'ctx, Int<SizeT>>
|
||||
///
|
||||
/// // Get `&ndarray->ndims`
|
||||
/// ndarray.gep(|f| f.ndims); // type: Instance<'ctx, Ptr<Int<SizeT>>>
|
||||
///
|
||||
/// // Get `ndarray->shape[0]`
|
||||
/// ndarray.get(|f| f.shape).get_index_const(0); // Instance<'ctx, Int<SizeT>>
|
||||
///
|
||||
/// // Get `&ndarray->shape[2]`
|
||||
/// ndarray.get(|f| f.shape).offset_const(2); // Instance<'ctx, Ptr<Int<SizeT>>>
|
||||
///
|
||||
/// // Do `ndarray->ndims = 3;`
|
||||
/// let num_3 = Int(SizeT).const_int(3);
|
||||
/// ndarray.set(|f| f.ndims, num_3);
|
||||
/// ```
|
||||
pub trait StructKind<'ctx>: fmt::Debug + Clone + Copy {
|
||||
/// The associated fields of this struct.
|
||||
type Fields<F: FieldTraversal<'ctx>>;
|
||||
|
||||
/// Traverse through all fields of this [`StructKind`].
|
||||
///
|
||||
/// Only used internally in this module for implementing other components.
|
||||
fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F>;
|
||||
|
||||
/// Get a convenience structure to get a struct field's GEP index through its corresponding Rust field.
|
||||
///
|
||||
/// Only used internally in this module for implementing other components.
|
||||
fn fields(&self) -> Self::Fields<GepFieldTraversal> {
|
||||
self.iter_fields(&mut GepFieldTraversal { gep_index_counter: 0 })
|
||||
}
|
||||
|
||||
/// Get the LLVM [`StructType`] of this [`StructKind`].
|
||||
fn get_struct_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> StructType<'ctx> {
|
||||
let mut traversal = TypeFieldTraversal { generator, ctx, field_types: Vec::new() };
|
||||
self.iter_fields(&mut traversal);
|
||||
|
||||
ctx.struct_type(&traversal.field_types, false)
|
||||
}
|
||||
}
|
||||
|
||||
/// A model for LLVM struct.
|
||||
///
|
||||
/// `S` should be of a [`StructKind`].
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct Struct<S>(pub S);
|
||||
|
||||
impl<'ctx, S: StructKind<'ctx>> Struct<S> {
|
||||
/// Create a constant struct value from its fields.
|
||||
///
|
||||
/// This function also validates `fields` and panic when there is something wrong.
|
||||
pub fn const_struct<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
fields: &[BasicValueEnum<'ctx>],
|
||||
) -> Instance<'ctx, Self> {
|
||||
// NOTE: There *could* have been a functor `F<M> = Instance<'ctx, M>` for `S::Fields<F>`
|
||||
// to create a more user-friendly interface, but Rust's type system is not sophisticated enough
|
||||
// and if you try doing that Rust would force you put lifetimes everywhere.
|
||||
let val = ctx.const_struct(fields, false);
|
||||
self.check_value(generator, ctx, val).unwrap()
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, S: StructKind<'ctx>> Model<'ctx> for Struct<S> {
|
||||
type Value = StructValue<'ctx>;
|
||||
type Type = StructType<'ctx>;
|
||||
|
||||
fn llvm_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &G,
|
||||
ctx: &'ctx Context,
|
||||
) -> Self::Type {
|
||||
self.0.get_struct_type(generator, ctx)
|
||||
}
|
||||
|
||||
fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
ty: T,
|
||||
) -> Result<(), ModelError> {
|
||||
let ty = ty.as_basic_type_enum();
|
||||
let Ok(ty) = StructType::try_from(ty) else {
|
||||
return Err(ModelError(format!("Expecting StructType, but got {ty:?}")));
|
||||
};
|
||||
|
||||
// Check each field individually.
|
||||
let mut traversal = CheckTypeFieldTraversal {
|
||||
generator,
|
||||
ctx,
|
||||
gep_index_counter: 0,
|
||||
errors: Vec::new(),
|
||||
scrutinee: ty,
|
||||
};
|
||||
self.0.iter_fields(&mut traversal);
|
||||
|
||||
// Check the number of fields.
|
||||
let exp_num_fields = traversal.gep_index_counter;
|
||||
let got_num_fields = u32::try_from(ty.get_field_types().len()).unwrap();
|
||||
if exp_num_fields != got_num_fields {
|
||||
return Err(ModelError(format!(
|
||||
"Expecting StructType with {exp_num_fields} field(s), but got {got_num_fields}"
|
||||
)));
|
||||
}
|
||||
|
||||
if !traversal.errors.is_empty() {
|
||||
// Currently, only the first error is reported.
|
||||
return Err(traversal.errors[0].clone());
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, S: StructKind<'ctx>> Instance<'ctx, Struct<S>> {
|
||||
/// Get a field with [`StructValue::get_field_at_index`].
|
||||
pub fn get_field<G: CodeGenerator + ?Sized, M, GetField>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
get_field: GetField,
|
||||
) -> Instance<'ctx, M>
|
||||
where
|
||||
M: Model<'ctx>,
|
||||
GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
|
||||
{
|
||||
let field = get_field(self.model.0.fields());
|
||||
let val = self.value.get_field_at_index(field.gep_index).unwrap();
|
||||
field.model.check_value(generator, ctx, val).unwrap()
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, S: StructKind<'ctx>> Instance<'ctx, Ptr<Struct<S>>> {
|
||||
/// Get a pointer to a field with [`Builder::build_in_bounds_gep`].
|
||||
pub fn gep<M, GetField>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
get_field: GetField,
|
||||
) -> Instance<'ctx, Ptr<M>>
|
||||
where
|
||||
M: Model<'ctx>,
|
||||
GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
|
||||
{
|
||||
let field = get_field(self.model.0 .0.fields());
|
||||
let llvm_i32 = ctx.ctx.i32_type();
|
||||
|
||||
let ptr = unsafe {
|
||||
ctx.builder
|
||||
.build_in_bounds_gep(
|
||||
self.value,
|
||||
&[llvm_i32.const_zero(), llvm_i32.const_int(u64::from(field.gep_index), false)],
|
||||
field.name,
|
||||
)
|
||||
.unwrap()
|
||||
};
|
||||
|
||||
unsafe { Ptr(field.model).believe_value(ptr) }
|
||||
}
|
||||
|
||||
/// Convenience function equivalent to `.gep(...).load(...)`.
|
||||
pub fn get<M, GetField, G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
get_field: GetField,
|
||||
) -> Instance<'ctx, M>
|
||||
where
|
||||
M: Model<'ctx>,
|
||||
GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
|
||||
{
|
||||
self.gep(ctx, get_field).load(generator, ctx)
|
||||
}
|
||||
|
||||
/// Convenience function equivalent to `.gep(...).store(...)`.
|
||||
pub fn set<M, GetField>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
get_field: GetField,
|
||||
value: Instance<'ctx, M>,
|
||||
) where
|
||||
M: Model<'ctx>,
|
||||
GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
|
||||
{
|
||||
self.gep(ctx, get_field).store(ctx, value);
|
||||
}
|
||||
}
|
42
nac3core/src/codegen/model/util.rs
Normal file
42
nac3core/src/codegen/model/util.rs
Normal file
@ -0,0 +1,42 @@
|
||||
use crate::codegen::{
|
||||
stmt::{gen_for_callback_incrementing, BreakContinueHooks},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
use super::*;
|
||||
|
||||
/// Like [`gen_for_callback_incrementing`] with [`Model`] abstractions.
|
||||
///
|
||||
/// `stop` is not included.
|
||||
pub fn gen_for_model<'ctx, 'a, G, F, N>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, 'a>,
|
||||
start: Instance<'ctx, Int<N>>,
|
||||
stop: Instance<'ctx, Int<N>>,
|
||||
step: Instance<'ctx, Int<N>>,
|
||||
body: F,
|
||||
) -> Result<(), String>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
F: FnOnce(
|
||||
&mut G,
|
||||
&mut CodeGenContext<'ctx, 'a>,
|
||||
BreakContinueHooks<'ctx>,
|
||||
Instance<'ctx, Int<N>>,
|
||||
) -> Result<(), String>,
|
||||
N: IntKind<'ctx> + Default,
|
||||
{
|
||||
let int_model = Int(N::default());
|
||||
gen_for_callback_incrementing(
|
||||
generator,
|
||||
ctx,
|
||||
None,
|
||||
start.value,
|
||||
(stop.value, false),
|
||||
|g, ctx, hooks, i| {
|
||||
let i = unsafe { int_model.believe_value(i) };
|
||||
body(g, ctx, hooks, i)
|
||||
},
|
||||
step.value,
|
||||
)
|
||||
}
|
File diff suppressed because it is too large
Load Diff
12
nac3core/src/codegen/object/any.rs
Normal file
12
nac3core/src/codegen/object/any.rs
Normal file
@ -0,0 +1,12 @@
|
||||
use inkwell::values::BasicValueEnum;
|
||||
|
||||
use crate::typecheck::typedef::Type;
|
||||
|
||||
/// A NAC3 LLVM Python object of any type.
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct AnyObject<'ctx> {
|
||||
/// Typechecker type of the object.
|
||||
pub ty: Type,
|
||||
/// LLVM value of the object.
|
||||
pub value: BasicValueEnum<'ctx>,
|
||||
}
|
87
nac3core/src/codegen/object/list.rs
Normal file
87
nac3core/src/codegen/object/list.rs
Normal file
@ -0,0 +1,87 @@
|
||||
use crate::{
|
||||
codegen::{model::*, CodeGenContext, CodeGenerator},
|
||||
typecheck::typedef::{iter_type_vars, Type, TypeEnum},
|
||||
};
|
||||
|
||||
use super::any::AnyObject;
|
||||
|
||||
/// Fields of [`List`]
|
||||
pub struct ListFields<'ctx, F: FieldTraversal<'ctx>, Item: Model<'ctx>> {
|
||||
/// Array pointer to content
|
||||
pub items: F::Output<Ptr<Item>>,
|
||||
/// Number of items in the array
|
||||
pub len: F::Output<Int<SizeT>>,
|
||||
}
|
||||
|
||||
/// A list in NAC3.
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct List<Item> {
|
||||
/// Model of the list items
|
||||
pub item: Item,
|
||||
}
|
||||
|
||||
impl<'ctx, Item: Model<'ctx>> StructKind<'ctx> for List<Item> {
|
||||
type Fields<F: FieldTraversal<'ctx>> = ListFields<'ctx, F, Item>;
|
||||
|
||||
fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields {
|
||||
items: traversal.add("items", Ptr(self.item)),
|
||||
len: traversal.add_auto("len"),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, Item: Model<'ctx>> Instance<'ctx, Ptr<Struct<List<Item>>>> {
|
||||
/// Cast the items pointer to `uint8_t*`.
|
||||
pub fn with_pi8_items<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> Instance<'ctx, Ptr<Struct<List<Int<Byte>>>>> {
|
||||
self.pointer_cast(generator, ctx, Struct(List { item: Int(Byte) }))
|
||||
}
|
||||
}
|
||||
|
||||
/// A NAC3 Python List object.
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct ListObject<'ctx> {
|
||||
/// Typechecker type of the list items
|
||||
pub item_type: Type,
|
||||
pub instance: Instance<'ctx, Ptr<Struct<List<Any<'ctx>>>>>,
|
||||
}
|
||||
|
||||
impl<'ctx> ListObject<'ctx> {
|
||||
/// Create a [`ListObject`] from an LLVM value and its typechecker [`Type`].
|
||||
pub fn from_object<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
object: AnyObject<'ctx>,
|
||||
) -> Self {
|
||||
// Check typechecker type and extract `item_type`
|
||||
let item_type = match &*ctx.unifier.get_ty(object.ty) {
|
||||
TypeEnum::TObj { obj_id, params, .. }
|
||||
if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
|
||||
{
|
||||
iter_type_vars(params).next().unwrap().ty // Extract `item_type`
|
||||
}
|
||||
_ => {
|
||||
panic!("Expecting type to be a list, but got {}", ctx.unifier.stringify(object.ty))
|
||||
}
|
||||
};
|
||||
|
||||
let plist = Ptr(Struct(List { item: Any(ctx.get_llvm_type(generator, item_type)) }));
|
||||
|
||||
// Create object
|
||||
let value = plist.check_value(generator, ctx.ctx, object.value).unwrap();
|
||||
ListObject { item_type, instance: value }
|
||||
}
|
||||
|
||||
/// Get the `len()` of this list.
|
||||
pub fn len<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> Instance<'ctx, Int<SizeT>> {
|
||||
self.instance.get(generator, ctx, |f| f.len)
|
||||
}
|
||||
}
|
5
nac3core/src/codegen/object/mod.rs
Normal file
5
nac3core/src/codegen/object/mod.rs
Normal file
@ -0,0 +1,5 @@
|
||||
pub mod any;
|
||||
pub mod list;
|
||||
pub mod ndarray;
|
||||
pub mod tuple;
|
||||
pub mod utils;
|
184
nac3core/src/codegen/object/ndarray/array.rs
Normal file
184
nac3core/src/codegen/object/ndarray/array.rs
Normal file
@ -0,0 +1,184 @@
|
||||
use super::NDArrayObject;
|
||||
use crate::{
|
||||
codegen::{
|
||||
irrt::{
|
||||
call_nac3_ndarray_array_set_and_validate_list_shape,
|
||||
call_nac3_ndarray_array_write_list_to_array,
|
||||
},
|
||||
model::*,
|
||||
object::{any::AnyObject, list::ListObject},
|
||||
stmt::gen_if_else_expr_callback,
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
toplevel::helper::{arraylike_flatten_element_type, arraylike_get_ndims},
|
||||
typecheck::typedef::{Type, TypeEnum},
|
||||
};
|
||||
|
||||
/// Get the expected `dtype` and `ndims` of the ndarray returned by `np_array(list)`.
|
||||
fn get_list_object_dtype_and_ndims<'ctx>(
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
list: ListObject<'ctx>,
|
||||
) -> (Type, u64) {
|
||||
let dtype = arraylike_flatten_element_type(&mut ctx.unifier, list.item_type);
|
||||
|
||||
let ndims = arraylike_get_ndims(&mut ctx.unifier, list.item_type);
|
||||
let ndims = ndims + 1; // To count `list` itself.
|
||||
|
||||
(dtype, ndims)
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
/// Implementation of `np_array(<list>, copy=True)`
|
||||
fn make_np_array_list_copy_true_impl<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
list: ListObject<'ctx>,
|
||||
) -> Self {
|
||||
let (dtype, ndims_int) = get_list_object_dtype_and_ndims(ctx, list);
|
||||
let list_value = list.instance.with_pi8_items(generator, ctx);
|
||||
|
||||
// Validate `list` has a consistent shape.
|
||||
// Raise an exception if `list` is something abnormal like `[[1, 2], [3]]`.
|
||||
// If `list` has a consistent shape, deduce the shape and write it to `shape`.
|
||||
let ndims = Int(SizeT).const_int(generator, ctx.ctx, ndims_int, false);
|
||||
let shape = Int(SizeT).array_alloca(generator, ctx, ndims.value);
|
||||
call_nac3_ndarray_array_set_and_validate_list_shape(
|
||||
generator, ctx, list_value, ndims, shape,
|
||||
);
|
||||
|
||||
let ndarray = NDArrayObject::alloca(generator, ctx, dtype, ndims_int);
|
||||
ndarray.copy_shape_from_array(generator, ctx, shape);
|
||||
ndarray.create_data(generator, ctx);
|
||||
|
||||
// Copy all contents from the list.
|
||||
call_nac3_ndarray_array_write_list_to_array(generator, ctx, list_value, ndarray.instance);
|
||||
|
||||
ndarray
|
||||
}
|
||||
|
||||
/// Implementation of `np_array(<list>, copy=None)`
|
||||
fn make_np_array_list_copy_none_impl<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
list: ListObject<'ctx>,
|
||||
) -> Self {
|
||||
// np_array without copying is only possible `list` is not nested.
|
||||
//
|
||||
// If `list` is `list[T]`, we can create an ndarray with `data` set
|
||||
// to the array pointer of `list`.
|
||||
//
|
||||
// If `list` is `list[list[T]]` or worse, copy.
|
||||
|
||||
let (dtype, ndims) = get_list_object_dtype_and_ndims(ctx, list);
|
||||
if ndims == 1 {
|
||||
// `list` is not nested
|
||||
let ndarray = NDArrayObject::alloca(generator, ctx, dtype, 1);
|
||||
|
||||
// Set data
|
||||
let data = list.instance.get(generator, ctx, |f| f.items).cast_to_pi8(generator, ctx);
|
||||
ndarray.instance.set(ctx, |f| f.data, data);
|
||||
|
||||
// ndarray->shape[0] = list->len;
|
||||
let shape = ndarray.instance.get(generator, ctx, |f| f.shape);
|
||||
let list_len = list.instance.get(generator, ctx, |f| f.len);
|
||||
shape.set_index_const(ctx, 0, list_len);
|
||||
|
||||
// Set strides, the `data` is contiguous
|
||||
ndarray.set_strides_contiguous(generator, ctx);
|
||||
|
||||
ndarray
|
||||
} else {
|
||||
// `list` is nested, copy
|
||||
NDArrayObject::make_np_array_list_copy_true_impl(generator, ctx, list)
|
||||
}
|
||||
}
|
||||
|
||||
/// Implementation of `np_array(<list>, copy=copy)`
|
||||
fn make_np_array_list_impl<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
list: ListObject<'ctx>,
|
||||
copy: Instance<'ctx, Int<Bool>>,
|
||||
) -> Self {
|
||||
let (dtype, ndims) = get_list_object_dtype_and_ndims(ctx, list);
|
||||
|
||||
let ndarray = gen_if_else_expr_callback(
|
||||
generator,
|
||||
ctx,
|
||||
|_generator, _ctx| Ok(copy.value),
|
||||
|generator, ctx| {
|
||||
let ndarray =
|
||||
NDArrayObject::make_np_array_list_copy_true_impl(generator, ctx, list);
|
||||
Ok(Some(ndarray.instance.value))
|
||||
},
|
||||
|generator, ctx| {
|
||||
let ndarray =
|
||||
NDArrayObject::make_np_array_list_copy_none_impl(generator, ctx, list);
|
||||
Ok(Some(ndarray.instance.value))
|
||||
},
|
||||
)
|
||||
.unwrap()
|
||||
.unwrap();
|
||||
|
||||
NDArrayObject::from_value_and_unpacked_types(generator, ctx, ndarray, dtype, ndims)
|
||||
}
|
||||
|
||||
/// Implementation of `np_array(<ndarray>, copy=copy)`.
|
||||
pub fn make_np_array_ndarray_impl<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndarray: NDArrayObject<'ctx>,
|
||||
copy: Instance<'ctx, Int<Bool>>,
|
||||
) -> Self {
|
||||
let ndarray_val = gen_if_else_expr_callback(
|
||||
generator,
|
||||
ctx,
|
||||
|_generator, _ctx| Ok(copy.value),
|
||||
|generator, ctx| {
|
||||
let ndarray = ndarray.make_copy(generator, ctx); // Force copy
|
||||
Ok(Some(ndarray.instance.value))
|
||||
},
|
||||
|_generator, _ctx| {
|
||||
// No need to copy. Return `ndarray` itself.
|
||||
Ok(Some(ndarray.instance.value))
|
||||
},
|
||||
)
|
||||
.unwrap()
|
||||
.unwrap();
|
||||
|
||||
NDArrayObject::from_value_and_unpacked_types(
|
||||
generator,
|
||||
ctx,
|
||||
ndarray_val,
|
||||
ndarray.dtype,
|
||||
ndarray.ndims,
|
||||
)
|
||||
}
|
||||
|
||||
/// Create a new ndarray like `np.array()`.
|
||||
///
|
||||
/// NOTE: The `ndmin` argument is not here. You may want to
|
||||
/// do [`NDArrayObject::atleast_nd`] to achieve that.
|
||||
pub fn make_np_array<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
object: AnyObject<'ctx>,
|
||||
copy: Instance<'ctx, Int<Bool>>,
|
||||
) -> Self {
|
||||
match &*ctx.unifier.get_ty(object.ty) {
|
||||
TypeEnum::TObj { obj_id, .. }
|
||||
if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
|
||||
{
|
||||
let list = ListObject::from_object(generator, ctx, object);
|
||||
NDArrayObject::make_np_array_list_impl(generator, ctx, list, copy)
|
||||
}
|
||||
TypeEnum::TObj { obj_id, .. }
|
||||
if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
|
||||
{
|
||||
let ndarray = NDArrayObject::from_object(generator, ctx, object);
|
||||
NDArrayObject::make_np_array_ndarray_impl(generator, ctx, ndarray, copy)
|
||||
}
|
||||
_ => panic!("Unrecognized object type: {}", ctx.unifier.stringify(object.ty)), // Typechecker ensures this
|
||||
}
|
||||
}
|
||||
}
|
139
nac3core/src/codegen/object/ndarray/broadcast.rs
Normal file
139
nac3core/src/codegen/object/ndarray/broadcast.rs
Normal file
@ -0,0 +1,139 @@
|
||||
use itertools::Itertools;
|
||||
|
||||
use crate::codegen::{
|
||||
irrt::{call_nac3_ndarray_broadcast_shapes, call_nac3_ndarray_broadcast_to},
|
||||
model::*,
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
use super::NDArrayObject;
|
||||
|
||||
/// Fields of [`ShapeEntry`]
|
||||
pub struct ShapeEntryFields<'ctx, F: FieldTraversal<'ctx>> {
|
||||
pub ndims: F::Output<Int<SizeT>>,
|
||||
pub shape: F::Output<Ptr<Int<SizeT>>>,
|
||||
}
|
||||
|
||||
/// An IRRT structure used in broadcasting.
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct ShapeEntry;
|
||||
|
||||
impl<'ctx> StructKind<'ctx> for ShapeEntry {
|
||||
type Fields<F: FieldTraversal<'ctx>> = ShapeEntryFields<'ctx, F>;
|
||||
|
||||
fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields { ndims: traversal.add_auto("ndims"), shape: traversal.add_auto("shape") }
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
/// Create a broadcast view on this ndarray with a target shape.
|
||||
///
|
||||
/// The input shape will be checked to make sure that it contains no negative values.
|
||||
///
|
||||
/// * `target_ndims` - The ndims type after broadcasting to the given shape.
|
||||
/// The caller has to figure this out for this function.
|
||||
/// * `target_shape` - An array pointer pointing to the target shape.
|
||||
#[must_use]
|
||||
pub fn broadcast_to<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
target_ndims: u64,
|
||||
target_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
|
||||
) -> Self {
|
||||
let broadcast_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, target_ndims);
|
||||
broadcast_ndarray.copy_shape_from_array(generator, ctx, target_shape);
|
||||
|
||||
call_nac3_ndarray_broadcast_to(generator, ctx, self.instance, broadcast_ndarray.instance);
|
||||
broadcast_ndarray
|
||||
}
|
||||
}
|
||||
/// A result produced by [`broadcast_all_ndarrays`]
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct BroadcastAllResult<'ctx> {
|
||||
/// The statically known `ndims` of the broadcast result.
|
||||
pub ndims: u64,
|
||||
/// The broadcasting shape.
|
||||
pub shape: Instance<'ctx, Ptr<Int<SizeT>>>,
|
||||
/// Broadcasted views on the inputs.
|
||||
///
|
||||
/// All of them will have `shape` [`BroadcastAllResult::shape`] and
|
||||
/// `ndims` [`BroadcastAllResult::ndims`]. The length of the vector
|
||||
/// is the same as the input.
|
||||
pub ndarrays: Vec<NDArrayObject<'ctx>>,
|
||||
}
|
||||
|
||||
/// Helper function to call `call_nac3_ndarray_broadcast_shapes`
|
||||
fn broadcast_shapes<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
in_shape_entries: &[(Instance<'ctx, Ptr<Int<SizeT>>>, u64)], // (shape, shape's length/ndims)
|
||||
broadcast_ndims: u64,
|
||||
broadcast_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
|
||||
) {
|
||||
// Prepare input shape entries to be passed to `call_nac3_ndarray_broadcast_shapes`.
|
||||
let num_shape_entries = Int(SizeT).const_int(
|
||||
generator,
|
||||
ctx.ctx,
|
||||
u64::try_from(in_shape_entries.len()).unwrap(),
|
||||
false,
|
||||
);
|
||||
let shape_entries = Struct(ShapeEntry).array_alloca(generator, ctx, num_shape_entries.value);
|
||||
for (i, (in_shape, in_ndims)) in in_shape_entries.iter().enumerate() {
|
||||
let pshape_entry = shape_entries.offset_const(ctx, i64::try_from(i).unwrap());
|
||||
|
||||
let in_ndims = Int(SizeT).const_int(generator, ctx.ctx, *in_ndims, false);
|
||||
pshape_entry.set(ctx, |f| f.ndims, in_ndims);
|
||||
|
||||
pshape_entry.set(ctx, |f| f.shape, *in_shape);
|
||||
}
|
||||
|
||||
let broadcast_ndims = Int(SizeT).const_int(generator, ctx.ctx, broadcast_ndims, false);
|
||||
call_nac3_ndarray_broadcast_shapes(
|
||||
generator,
|
||||
ctx,
|
||||
num_shape_entries,
|
||||
shape_entries,
|
||||
broadcast_ndims,
|
||||
broadcast_shape,
|
||||
);
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
/// Broadcast all ndarrays according to `np.broadcast()` and return a [`BroadcastAllResult`]
|
||||
/// containing all the information of the result of the broadcast operation.
|
||||
pub fn broadcast<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndarrays: &[Self],
|
||||
) -> BroadcastAllResult<'ctx> {
|
||||
assert!(!ndarrays.is_empty());
|
||||
|
||||
// Infer the broadcast output ndims.
|
||||
let broadcast_ndims_int = ndarrays.iter().map(|ndarray| ndarray.ndims).max().unwrap();
|
||||
|
||||
let broadcast_ndims = Int(SizeT).const_int(generator, ctx.ctx, broadcast_ndims_int, false);
|
||||
let broadcast_shape = Int(SizeT).array_alloca(generator, ctx, broadcast_ndims.value);
|
||||
|
||||
let shape_entries = ndarrays
|
||||
.iter()
|
||||
.map(|ndarray| (ndarray.instance.get(generator, ctx, |f| f.shape), ndarray.ndims))
|
||||
.collect_vec();
|
||||
broadcast_shapes(generator, ctx, &shape_entries, broadcast_ndims_int, broadcast_shape);
|
||||
|
||||
// Broadcast all the inputs to shape `dst_shape`.
|
||||
let broadcast_ndarrays: Vec<_> = ndarrays
|
||||
.iter()
|
||||
.map(|ndarray| {
|
||||
ndarray.broadcast_to(generator, ctx, broadcast_ndims_int, broadcast_shape)
|
||||
})
|
||||
.collect_vec();
|
||||
|
||||
BroadcastAllResult {
|
||||
ndims: broadcast_ndims_int,
|
||||
shape: broadcast_shape,
|
||||
ndarrays: broadcast_ndarrays,
|
||||
}
|
||||
}
|
||||
}
|
134
nac3core/src/codegen/object/ndarray/contiguous.rs
Normal file
134
nac3core/src/codegen/object/ndarray/contiguous.rs
Normal file
@ -0,0 +1,134 @@
|
||||
use crate::{
|
||||
codegen::{model::*, CodeGenContext, CodeGenerator},
|
||||
typecheck::typedef::Type,
|
||||
};
|
||||
|
||||
use super::NDArrayObject;
|
||||
|
||||
/// Fields of [`ContiguousNDArray`]
|
||||
pub struct ContiguousNDArrayFields<'ctx, F: FieldTraversal<'ctx>, Item: Model<'ctx>> {
|
||||
pub ndims: F::Output<Int<SizeT>>,
|
||||
pub shape: F::Output<Ptr<Int<SizeT>>>,
|
||||
pub data: F::Output<Ptr<Item>>,
|
||||
}
|
||||
|
||||
/// An ndarray without strides and non-opaque `data` field in NAC3.
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct ContiguousNDArray<M> {
|
||||
/// [`Model`] of the items.
|
||||
pub item: M,
|
||||
}
|
||||
|
||||
impl<'ctx, Item: Model<'ctx>> StructKind<'ctx> for ContiguousNDArray<Item> {
|
||||
type Fields<F: FieldTraversal<'ctx>> = ContiguousNDArrayFields<'ctx, F, Item>;
|
||||
|
||||
fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields {
|
||||
ndims: traversal.add_auto("ndims"),
|
||||
shape: traversal.add_auto("shape"),
|
||||
data: traversal.add("data", Ptr(self.item)),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
/// Create a [`ContiguousNDArray`] from the contents of this ndarray.
|
||||
///
|
||||
/// This function may or may not be expensive depending on if this ndarray has contiguous data.
|
||||
///
|
||||
/// If this ndarray is not C-contiguous, this function will allocate memory on the stack for the `data` field of
|
||||
/// the returned [`ContiguousNDArray`] and copy contents of this ndarray to there.
|
||||
///
|
||||
/// If this ndarray is C-contiguous, contents of this ndarray will not be copied. The created [`ContiguousNDArray`]
|
||||
/// will share memory with this ndarray.
|
||||
///
|
||||
/// The `item_model` sets the [`Model`] of the returned [`ContiguousNDArray`]'s `Item` model for type-safety, and
|
||||
/// should match the `ctx.get_llvm_type()` of this ndarray's `dtype`. Otherwise this function panics. Use model [`Any`]
|
||||
/// if you don't care/cannot know the [`Model`] in advance.
|
||||
pub fn make_contiguous_ndarray<G: CodeGenerator + ?Sized, Item: Model<'ctx>>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
item_model: Item,
|
||||
) -> Instance<'ctx, Ptr<Struct<ContiguousNDArray<Item>>>> {
|
||||
// Sanity check on `self.dtype` and `item_model`.
|
||||
let dtype_llvm = ctx.get_llvm_type(generator, self.dtype);
|
||||
item_model.check_type(generator, ctx.ctx, dtype_llvm).unwrap();
|
||||
|
||||
let cdarray_model = Struct(ContiguousNDArray { item: item_model });
|
||||
|
||||
let current_bb = ctx.builder.get_insert_block().unwrap();
|
||||
let then_bb = ctx.ctx.insert_basic_block_after(current_bb, "then_bb");
|
||||
let else_bb = ctx.ctx.insert_basic_block_after(then_bb, "else_bb");
|
||||
let end_bb = ctx.ctx.insert_basic_block_after(else_bb, "end_bb");
|
||||
|
||||
// Allocate and setup the resulting [`ContiguousNDArray`].
|
||||
let result = cdarray_model.alloca(generator, ctx);
|
||||
|
||||
// Set ndims and shape.
|
||||
let ndims = self.ndims_llvm(generator, ctx.ctx);
|
||||
result.set(ctx, |f| f.ndims, ndims);
|
||||
|
||||
let shape = self.instance.get(generator, ctx, |f| f.shape);
|
||||
result.set(ctx, |f| f.shape, shape);
|
||||
|
||||
let is_contiguous = self.is_c_contiguous(generator, ctx);
|
||||
ctx.builder.build_conditional_branch(is_contiguous.value, then_bb, else_bb).unwrap();
|
||||
|
||||
// Inserting into then_bb; This ndarray is contiguous.
|
||||
ctx.builder.position_at_end(then_bb);
|
||||
let data = self.instance.get(generator, ctx, |f| f.data);
|
||||
let data = data.pointer_cast(generator, ctx, item_model);
|
||||
result.set(ctx, |f| f.data, data);
|
||||
ctx.builder.build_unconditional_branch(end_bb).unwrap();
|
||||
|
||||
// Inserting into else_bb; This ndarray is not contiguous. Do a full-copy on `data`.
|
||||
// `make_copy` produces an ndarray with contiguous `data`.
|
||||
ctx.builder.position_at_end(else_bb);
|
||||
let copied_ndarray = self.make_copy(generator, ctx);
|
||||
let data = copied_ndarray.instance.get(generator, ctx, |f| f.data);
|
||||
let data = data.pointer_cast(generator, ctx, item_model);
|
||||
result.set(ctx, |f| f.data, data);
|
||||
ctx.builder.build_unconditional_branch(end_bb).unwrap();
|
||||
|
||||
// Reposition to end_bb for continuation
|
||||
ctx.builder.position_at_end(end_bb);
|
||||
|
||||
result
|
||||
}
|
||||
|
||||
/// Create an [`NDArrayObject`] from a [`ContiguousNDArray`].
|
||||
///
|
||||
/// The operation is super cheap. The newly created [`NDArrayObject`] will share the
|
||||
/// same memory as the [`ContiguousNDArray`].
|
||||
///
|
||||
/// `ndims` has to be provided as [`NDArrayObject`] requires a statically known `ndims` value, despite
|
||||
/// the fact that the information should be contained within the [`ContiguousNDArray`].
|
||||
pub fn from_contiguous_ndarray<G: CodeGenerator + ?Sized, Item: Model<'ctx>>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
carray: Instance<'ctx, Ptr<Struct<ContiguousNDArray<Item>>>>,
|
||||
dtype: Type,
|
||||
ndims: u64,
|
||||
) -> Self {
|
||||
// Sanity check on `dtype` and `contiguous_array`'s `Item` model.
|
||||
let dtype_llvm = ctx.get_llvm_type(generator, dtype);
|
||||
carray.model.0 .0.item.check_type(generator, ctx.ctx, dtype_llvm).unwrap();
|
||||
|
||||
// TODO: Debug assert `ndims == carray.ndims` to catch bugs.
|
||||
|
||||
// Allocate the resulting ndarray.
|
||||
let ndarray = NDArrayObject::alloca(generator, ctx, dtype, ndims);
|
||||
|
||||
// Copy shape and update strides
|
||||
let shape = carray.get(generator, ctx, |f| f.shape);
|
||||
ndarray.copy_shape_from_array(generator, ctx, shape);
|
||||
ndarray.set_strides_contiguous(generator, ctx);
|
||||
|
||||
// Share data
|
||||
let data = carray.get(generator, ctx, |f| f.data).pointer_cast(generator, ctx, Int(Byte));
|
||||
ndarray.instance.set(ctx, |f| f.data, data);
|
||||
|
||||
ndarray
|
||||
}
|
||||
}
|
176
nac3core/src/codegen/object/ndarray/factory.rs
Normal file
176
nac3core/src/codegen/object/ndarray/factory.rs
Normal file
@ -0,0 +1,176 @@
|
||||
use inkwell::{values::BasicValueEnum, IntPredicate};
|
||||
|
||||
use crate::{
|
||||
codegen::{
|
||||
irrt::call_nac3_ndarray_util_assert_shape_no_negative, model::*, CodeGenContext,
|
||||
CodeGenerator,
|
||||
},
|
||||
typecheck::typedef::Type,
|
||||
};
|
||||
|
||||
use super::NDArrayObject;
|
||||
|
||||
/// Get the zero value in `np.zeros()` of a `dtype`.
|
||||
fn ndarray_zero_value<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
dtype: Type,
|
||||
) -> BasicValueEnum<'ctx> {
|
||||
if [ctx.primitives.int32, ctx.primitives.uint32]
|
||||
.iter()
|
||||
.any(|ty| ctx.unifier.unioned(dtype, *ty))
|
||||
{
|
||||
ctx.ctx.i32_type().const_zero().into()
|
||||
} else if [ctx.primitives.int64, ctx.primitives.uint64]
|
||||
.iter()
|
||||
.any(|ty| ctx.unifier.unioned(dtype, *ty))
|
||||
{
|
||||
ctx.ctx.i64_type().const_zero().into()
|
||||
} else if ctx.unifier.unioned(dtype, ctx.primitives.float) {
|
||||
ctx.ctx.f64_type().const_zero().into()
|
||||
} else if ctx.unifier.unioned(dtype, ctx.primitives.bool) {
|
||||
ctx.ctx.bool_type().const_zero().into()
|
||||
} else if ctx.unifier.unioned(dtype, ctx.primitives.str) {
|
||||
ctx.gen_string(generator, "").into()
|
||||
} else {
|
||||
panic!("unrecognized dtype: {}", ctx.unifier.stringify(dtype));
|
||||
}
|
||||
}
|
||||
|
||||
/// Get the one value in `np.ones()` of a `dtype`.
|
||||
fn ndarray_one_value<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
dtype: Type,
|
||||
) -> BasicValueEnum<'ctx> {
|
||||
if [ctx.primitives.int32, ctx.primitives.uint32]
|
||||
.iter()
|
||||
.any(|ty| ctx.unifier.unioned(dtype, *ty))
|
||||
{
|
||||
let is_signed = ctx.unifier.unioned(dtype, ctx.primitives.int32);
|
||||
ctx.ctx.i32_type().const_int(1, is_signed).into()
|
||||
} else if [ctx.primitives.int64, ctx.primitives.uint64]
|
||||
.iter()
|
||||
.any(|ty| ctx.unifier.unioned(dtype, *ty))
|
||||
{
|
||||
let is_signed = ctx.unifier.unioned(dtype, ctx.primitives.int64);
|
||||
ctx.ctx.i64_type().const_int(1, is_signed).into()
|
||||
} else if ctx.unifier.unioned(dtype, ctx.primitives.float) {
|
||||
ctx.ctx.f64_type().const_float(1.0).into()
|
||||
} else if ctx.unifier.unioned(dtype, ctx.primitives.bool) {
|
||||
ctx.ctx.bool_type().const_int(1, false).into()
|
||||
} else if ctx.unifier.unioned(dtype, ctx.primitives.str) {
|
||||
ctx.gen_string(generator, "1").into()
|
||||
} else {
|
||||
panic!("unrecognized dtype: {}", ctx.unifier.stringify(dtype));
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
/// Create an ndarray like `np.empty`.
|
||||
pub fn make_np_empty<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
dtype: Type,
|
||||
ndims: u64,
|
||||
shape: Instance<'ctx, Ptr<Int<SizeT>>>,
|
||||
) -> Self {
|
||||
// Validate `shape`
|
||||
let ndims_llvm = Int(SizeT).const_int(generator, ctx.ctx, ndims, false);
|
||||
call_nac3_ndarray_util_assert_shape_no_negative(generator, ctx, ndims_llvm, shape);
|
||||
|
||||
let ndarray = NDArrayObject::alloca(generator, ctx, dtype, ndims);
|
||||
ndarray.copy_shape_from_array(generator, ctx, shape);
|
||||
ndarray.create_data(generator, ctx);
|
||||
|
||||
ndarray
|
||||
}
|
||||
|
||||
/// Create an ndarray like `np.full`.
|
||||
pub fn make_np_full<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
dtype: Type,
|
||||
ndims: u64,
|
||||
shape: Instance<'ctx, Ptr<Int<SizeT>>>,
|
||||
fill_value: BasicValueEnum<'ctx>,
|
||||
) -> Self {
|
||||
let ndarray = NDArrayObject::make_np_empty(generator, ctx, dtype, ndims, shape);
|
||||
ndarray.fill(generator, ctx, fill_value);
|
||||
ndarray
|
||||
}
|
||||
|
||||
/// Create an ndarray like `np.zero`.
|
||||
pub fn make_np_zeros<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
dtype: Type,
|
||||
ndims: u64,
|
||||
shape: Instance<'ctx, Ptr<Int<SizeT>>>,
|
||||
) -> Self {
|
||||
let fill_value = ndarray_zero_value(generator, ctx, dtype);
|
||||
NDArrayObject::make_np_full(generator, ctx, dtype, ndims, shape, fill_value)
|
||||
}
|
||||
|
||||
/// Create an ndarray like `np.ones`.
|
||||
pub fn make_np_ones<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
dtype: Type,
|
||||
ndims: u64,
|
||||
shape: Instance<'ctx, Ptr<Int<SizeT>>>,
|
||||
) -> Self {
|
||||
let fill_value = ndarray_one_value(generator, ctx, dtype);
|
||||
NDArrayObject::make_np_full(generator, ctx, dtype, ndims, shape, fill_value)
|
||||
}
|
||||
|
||||
/// Create an ndarray like `np.eye`.
|
||||
pub fn make_np_eye<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
dtype: Type,
|
||||
nrows: Instance<'ctx, Int<SizeT>>,
|
||||
ncols: Instance<'ctx, Int<SizeT>>,
|
||||
offset: Instance<'ctx, Int<SizeT>>,
|
||||
) -> Self {
|
||||
let ndzero = ndarray_zero_value(generator, ctx, dtype);
|
||||
let ndone = ndarray_one_value(generator, ctx, dtype);
|
||||
|
||||
let ndarray = NDArrayObject::alloca_dynamic_shape(generator, ctx, dtype, &[nrows, ncols]);
|
||||
|
||||
// Create data and make the matrix like look np.eye()
|
||||
ndarray.create_data(generator, ctx);
|
||||
ndarray
|
||||
.foreach(generator, ctx, |generator, ctx, _hooks, nditer| {
|
||||
// NOTE: rows and cols can never be zero here, since this ndarray's `np.size` would be zero
|
||||
// and this loop would not execute.
|
||||
|
||||
// Load up `row_i` and `col_i` from indices.
|
||||
let row_i = nditer.get_indices().get_index_const(generator, ctx, 0);
|
||||
let col_i = nditer.get_indices().get_index_const(generator, ctx, 1);
|
||||
|
||||
let be_one = row_i.add(ctx, offset).compare(ctx, IntPredicate::EQ, col_i);
|
||||
let value = ctx.builder.build_select(be_one.value, ndone, ndzero, "value").unwrap();
|
||||
|
||||
let p = nditer.get_pointer(generator, ctx);
|
||||
ctx.builder.build_store(p, value).unwrap();
|
||||
|
||||
Ok(())
|
||||
})
|
||||
.unwrap();
|
||||
|
||||
ndarray
|
||||
}
|
||||
|
||||
/// Create an ndarray like `np.identity`.
|
||||
pub fn make_np_identity<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
dtype: Type,
|
||||
size: Instance<'ctx, Int<SizeT>>,
|
||||
) -> Self {
|
||||
// Convenient implementation
|
||||
let offset = Int(SizeT).const_0(generator, ctx.ctx);
|
||||
NDArrayObject::make_np_eye(generator, ctx, dtype, size, size, offset)
|
||||
}
|
||||
}
|
227
nac3core/src/codegen/object/ndarray/indexing.rs
Normal file
227
nac3core/src/codegen/object/ndarray/indexing.rs
Normal file
@ -0,0 +1,227 @@
|
||||
use crate::codegen::{
|
||||
irrt::call_nac3_ndarray_index,
|
||||
model::*,
|
||||
object::utils::slice::{RustSlice, Slice},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
use super::NDArrayObject;
|
||||
|
||||
pub type NDIndexType = Byte;
|
||||
|
||||
/// Fields of [`NDIndex`]
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct NDIndexFields<'ctx, F: FieldTraversal<'ctx>> {
|
||||
pub type_: F::Output<Int<NDIndexType>>,
|
||||
pub data: F::Output<Ptr<Int<Byte>>>,
|
||||
}
|
||||
|
||||
/// An IRRT representation of an ndarray subscript index.
|
||||
#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
|
||||
pub struct NDIndex;
|
||||
|
||||
impl<'ctx> StructKind<'ctx> for NDIndex {
|
||||
type Fields<F: FieldTraversal<'ctx>> = NDIndexFields<'ctx, F>;
|
||||
|
||||
fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields { type_: traversal.add_auto("type"), data: traversal.add_auto("data") }
|
||||
}
|
||||
}
|
||||
|
||||
// A convenience enum representing a [`NDIndex`].
|
||||
#[derive(Debug, Clone)]
|
||||
pub enum RustNDIndex<'ctx> {
|
||||
SingleElement(Instance<'ctx, Int<Int32>>),
|
||||
Slice(RustSlice<'ctx, Int32>),
|
||||
NewAxis,
|
||||
Ellipsis,
|
||||
}
|
||||
|
||||
impl<'ctx> RustNDIndex<'ctx> {
|
||||
/// Get the value to set `NDIndex::type` for this variant.
|
||||
fn get_type_id(&self) -> u64 {
|
||||
// Defined in IRRT, must be in sync
|
||||
match self {
|
||||
RustNDIndex::SingleElement(_) => 0,
|
||||
RustNDIndex::Slice(_) => 1,
|
||||
RustNDIndex::NewAxis => 2,
|
||||
RustNDIndex::Ellipsis => 3,
|
||||
}
|
||||
}
|
||||
|
||||
/// Serialize this [`RustNDIndex`] by writing it into an LLVM [`NDIndex`].
|
||||
fn write_to_ndindex<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
dst_ndindex_ptr: Instance<'ctx, Ptr<Struct<NDIndex>>>,
|
||||
) {
|
||||
// Set `dst_ndindex_ptr->type`
|
||||
dst_ndindex_ptr.gep(ctx, |f| f.type_).store(
|
||||
ctx,
|
||||
Int(NDIndexType::default()).const_int(generator, ctx.ctx, self.get_type_id(), false),
|
||||
);
|
||||
|
||||
// Set `dst_ndindex_ptr->data`
|
||||
match self {
|
||||
RustNDIndex::SingleElement(in_index) => {
|
||||
let index_ptr = Int(Int32).alloca(generator, ctx);
|
||||
index_ptr.store(ctx, *in_index);
|
||||
|
||||
dst_ndindex_ptr
|
||||
.gep(ctx, |f| f.data)
|
||||
.store(ctx, index_ptr.pointer_cast(generator, ctx, Int(Byte)));
|
||||
}
|
||||
RustNDIndex::Slice(in_rust_slice) => {
|
||||
let user_slice_ptr = Struct(Slice(Int32)).alloca(generator, ctx);
|
||||
in_rust_slice.write_to_slice(generator, ctx, user_slice_ptr);
|
||||
|
||||
dst_ndindex_ptr
|
||||
.gep(ctx, |f| f.data)
|
||||
.store(ctx, user_slice_ptr.pointer_cast(generator, ctx, Int(Byte)));
|
||||
}
|
||||
RustNDIndex::NewAxis | RustNDIndex::Ellipsis => {}
|
||||
}
|
||||
}
|
||||
|
||||
/// Serialize a list of `RustNDIndex` as a newly allocated LLVM array of `NDIndex`.
|
||||
pub fn make_ndindices<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
in_ndindices: &[RustNDIndex<'ctx>],
|
||||
) -> (Instance<'ctx, Int<SizeT>>, Instance<'ctx, Ptr<Struct<NDIndex>>>) {
|
||||
let ndindex_model = Struct(NDIndex);
|
||||
|
||||
// Allocate the LLVM ndindices.
|
||||
let num_ndindices =
|
||||
Int(SizeT).const_int(generator, ctx.ctx, in_ndindices.len() as u64, false);
|
||||
let ndindices = ndindex_model.array_alloca(generator, ctx, num_ndindices.value);
|
||||
|
||||
// Initialize all of them.
|
||||
for (i, in_ndindex) in in_ndindices.iter().enumerate() {
|
||||
let pndindex = ndindices.offset_const(ctx, i64::try_from(i).unwrap());
|
||||
in_ndindex.write_to_ndindex(generator, ctx, pndindex);
|
||||
}
|
||||
|
||||
(num_ndindices, ndindices)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
/// Get the expected `ndims` after indexing with `indices`.
|
||||
#[must_use]
|
||||
fn deduce_ndims_after_indexing_with(&self, indices: &[RustNDIndex<'ctx>]) -> u64 {
|
||||
let mut ndims = self.ndims;
|
||||
for index in indices {
|
||||
match index {
|
||||
RustNDIndex::SingleElement(_) => {
|
||||
ndims -= 1; // Single elements decrements ndims
|
||||
}
|
||||
RustNDIndex::NewAxis => {
|
||||
ndims += 1; // `np.newaxis` / `none` adds a new axis
|
||||
}
|
||||
RustNDIndex::Ellipsis | RustNDIndex::Slice(_) => {}
|
||||
}
|
||||
}
|
||||
ndims
|
||||
}
|
||||
|
||||
/// Index into the ndarray, and return a newly-allocated view on this ndarray.
|
||||
///
|
||||
/// This function behaves like NumPy's ndarray indexing, but if the indices index
|
||||
/// into a single element, an unsized ndarray is returned.
|
||||
#[must_use]
|
||||
pub fn index<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
indices: &[RustNDIndex<'ctx>],
|
||||
) -> Self {
|
||||
let dst_ndims = self.deduce_ndims_after_indexing_with(indices);
|
||||
let dst_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, dst_ndims);
|
||||
|
||||
let (num_indices, indices) = RustNDIndex::make_ndindices(generator, ctx, indices);
|
||||
call_nac3_ndarray_index(
|
||||
generator,
|
||||
ctx,
|
||||
num_indices,
|
||||
indices,
|
||||
self.instance,
|
||||
dst_ndarray.instance,
|
||||
);
|
||||
|
||||
dst_ndarray
|
||||
}
|
||||
}
|
||||
|
||||
pub mod util {
|
||||
use itertools::Itertools;
|
||||
use nac3parser::ast::{Expr, ExprKind};
|
||||
|
||||
use crate::{
|
||||
codegen::{model::*, object::utils::slice::util::gen_slice, CodeGenContext, CodeGenerator},
|
||||
typecheck::typedef::Type,
|
||||
};
|
||||
|
||||
use super::RustNDIndex;
|
||||
|
||||
/// Generate LLVM code to transform an ndarray subscript expression to
|
||||
/// its list of [`RustNDIndex`]
|
||||
///
|
||||
/// i.e.,
|
||||
/// ```python
|
||||
/// my_ndarray[::3, 1, :2:]
|
||||
/// ^^^^^^^^^^^ Then these into a three `RustNDIndex`es
|
||||
/// ```
|
||||
pub fn gen_ndarray_subscript_ndindices<'ctx, G: CodeGenerator>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
subscript: &Expr<Option<Type>>,
|
||||
) -> Result<Vec<RustNDIndex<'ctx>>, String> {
|
||||
// TODO: Support https://numpy.org/doc/stable/user/basics.indexing.html#dimensional-indexing-tools
|
||||
|
||||
// Annoying notes about `slice`
|
||||
// - `my_array[5]`
|
||||
// - slice is a `Constant`
|
||||
// - `my_array[:5]`
|
||||
// - slice is a `Slice`
|
||||
// - `my_array[:]`
|
||||
// - slice is a `Slice`, but lower upper step would all be `Option::None`
|
||||
// - `my_array[:, :]`
|
||||
// - slice is now a `Tuple` of two `Slice`-s
|
||||
//
|
||||
// In summary:
|
||||
// - when there is a comma "," within [], `slice` will be a `Tuple` of the entries.
|
||||
// - when there is not comma "," within [] (i.e., just a single entry), `slice` will be that entry itself.
|
||||
//
|
||||
// So we first "flatten" out the slice expression
|
||||
let index_exprs = match &subscript.node {
|
||||
ExprKind::Tuple { elts, .. } => elts.iter().collect_vec(),
|
||||
_ => vec![subscript],
|
||||
};
|
||||
|
||||
// Process all index expressions
|
||||
let mut rust_ndindices: Vec<RustNDIndex> = Vec::with_capacity(index_exprs.len()); // Not using iterators here because `?` is used here.
|
||||
for index_expr in index_exprs {
|
||||
// NOTE: Currently nac3core's slices do not have an object representation,
|
||||
// so the code/implementation looks awkward - we have to do pattern matching on the expression
|
||||
let ndindex = if let ExprKind::Slice { lower, upper, step } = &index_expr.node {
|
||||
// Handle slices
|
||||
let slice = gen_slice(generator, ctx, lower, upper, step)?;
|
||||
RustNDIndex::Slice(slice)
|
||||
} else {
|
||||
// Treat and handle everything else as a single element index.
|
||||
let index = generator.gen_expr(ctx, index_expr)?.unwrap().to_basic_value_enum(
|
||||
ctx,
|
||||
generator,
|
||||
ctx.primitives.int32, // Must be int32, this checks for illegal values
|
||||
)?;
|
||||
let index = Int(Int32).check_value(generator, ctx.ctx, index).unwrap();
|
||||
|
||||
RustNDIndex::SingleElement(index)
|
||||
};
|
||||
rust_ndindices.push(ndindex);
|
||||
}
|
||||
Ok(rust_ndindices)
|
||||
}
|
||||
}
|
219
nac3core/src/codegen/object/ndarray/map.rs
Normal file
219
nac3core/src/codegen/object/ndarray/map.rs
Normal file
@ -0,0 +1,219 @@
|
||||
use inkwell::values::BasicValueEnum;
|
||||
use itertools::Itertools;
|
||||
|
||||
use crate::{
|
||||
codegen::{
|
||||
object::ndarray::{AnyObject, NDArrayObject},
|
||||
stmt::gen_for_callback,
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
typecheck::typedef::Type,
|
||||
};
|
||||
|
||||
use super::{nditer::NDIterHandle, NDArrayOut, ScalarOrNDArray};
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
/// Generate LLVM IR to broadcast `ndarray`s together, and starmap through them with `mapping` elementwise.
|
||||
///
|
||||
/// `mapping` is an LLVM IR generator. The input of `mapping` is the list of elements when iterating through
|
||||
/// the input `ndarrays` after broadcasting. The output of `mapping` is the result of the elementwise operation.
|
||||
///
|
||||
/// `out` specifies whether the result should be a new ndarray or to be written an existing ndarray.
|
||||
pub fn broadcast_starmap<'a, G, MappingFn>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, 'a>,
|
||||
ndarrays: &[Self],
|
||||
out: NDArrayOut<'ctx>,
|
||||
mapping: MappingFn,
|
||||
) -> Result<Self, String>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
MappingFn: FnOnce(
|
||||
&mut G,
|
||||
&mut CodeGenContext<'ctx, 'a>,
|
||||
&[BasicValueEnum<'ctx>],
|
||||
) -> Result<BasicValueEnum<'ctx>, String>,
|
||||
{
|
||||
// Broadcast inputs
|
||||
let broadcast_result = NDArrayObject::broadcast(generator, ctx, ndarrays);
|
||||
|
||||
let out_ndarray = match out {
|
||||
NDArrayOut::NewNDArray { dtype } => {
|
||||
// Create a new ndarray based on the broadcast shape.
|
||||
let result_ndarray =
|
||||
NDArrayObject::alloca(generator, ctx, dtype, broadcast_result.ndims);
|
||||
result_ndarray.copy_shape_from_array(generator, ctx, broadcast_result.shape);
|
||||
result_ndarray.create_data(generator, ctx);
|
||||
result_ndarray
|
||||
}
|
||||
NDArrayOut::WriteToNDArray { ndarray: result_ndarray } => {
|
||||
// Use an existing ndarray.
|
||||
|
||||
// Check that its shape is compatible with the broadcast shape.
|
||||
result_ndarray.assert_can_be_written_by_out(
|
||||
generator,
|
||||
ctx,
|
||||
broadcast_result.ndims,
|
||||
broadcast_result.shape,
|
||||
);
|
||||
result_ndarray
|
||||
}
|
||||
};
|
||||
|
||||
// Map element-wise and store results into `mapped_ndarray`.
|
||||
let nditer = NDIterHandle::new(generator, ctx, out_ndarray);
|
||||
gen_for_callback(
|
||||
generator,
|
||||
ctx,
|
||||
Some("broadcast_starmap"),
|
||||
|generator, ctx| {
|
||||
// Create NDIters for all broadcasted input ndarrays.
|
||||
let other_nditers = broadcast_result
|
||||
.ndarrays
|
||||
.iter()
|
||||
.map(|ndarray| NDIterHandle::new(generator, ctx, *ndarray))
|
||||
.collect_vec();
|
||||
Ok((nditer, other_nditers))
|
||||
},
|
||||
|generator, ctx, (out_nditer, _in_nditers)| {
|
||||
// We can simply use `out_nditer`'s `has_element()`.
|
||||
// `in_nditers`' `has_element()`s should return the same value.
|
||||
Ok(out_nditer.has_element(generator, ctx).value)
|
||||
},
|
||||
|generator, ctx, _hooks, (out_nditer, in_nditers)| {
|
||||
// Get all the scalars from the broadcasted input ndarrays, pass them to `mapping`,
|
||||
// and write to `out_ndarray`.
|
||||
let in_scalars = in_nditers
|
||||
.iter()
|
||||
.map(|nditer| nditer.get_scalar(generator, ctx).value)
|
||||
.collect_vec();
|
||||
|
||||
let result = mapping(generator, ctx, &in_scalars)?;
|
||||
|
||||
let p = out_nditer.get_pointer(generator, ctx);
|
||||
ctx.builder.build_store(p, result).unwrap();
|
||||
|
||||
Ok(())
|
||||
},
|
||||
|generator, ctx, (out_nditer, in_nditers)| {
|
||||
// Advance all iterators
|
||||
out_nditer.next(generator, ctx);
|
||||
in_nditers.iter().for_each(|nditer| nditer.next(generator, ctx));
|
||||
Ok(())
|
||||
},
|
||||
)?;
|
||||
|
||||
Ok(out_ndarray)
|
||||
}
|
||||
|
||||
/// Map through this ndarray with an elementwise function.
|
||||
pub fn map<'a, G, Mapping>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, 'a>,
|
||||
out: NDArrayOut<'ctx>,
|
||||
mapping: Mapping,
|
||||
) -> Result<Self, String>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
Mapping: FnOnce(
|
||||
&mut G,
|
||||
&mut CodeGenContext<'ctx, 'a>,
|
||||
BasicValueEnum<'ctx>,
|
||||
) -> Result<BasicValueEnum<'ctx>, String>,
|
||||
{
|
||||
NDArrayObject::broadcast_starmap(
|
||||
generator,
|
||||
ctx,
|
||||
&[*self],
|
||||
out,
|
||||
|generator, ctx, scalars| mapping(generator, ctx, scalars[0]),
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> ScalarOrNDArray<'ctx> {
|
||||
/// Starmap through a list of inputs using `mapping`, where an input could be an ndarray, a scalar.
|
||||
///
|
||||
/// This function is very helpful when implementing NumPy functions that takes on either scalars or ndarrays or a mix of them
|
||||
/// as their inputs and produces either an ndarray with broadcast, or a scalar if all its inputs are all scalars.
|
||||
///
|
||||
/// For example ,this function can be used to implement `np.add`, which has the following behaviors:
|
||||
/// - `np.add(3, 4) = 7` # (scalar, scalar) -> scalar
|
||||
/// - `np.add(3, np.array([4, 5, 6]))` # (scalar, ndarray) -> ndarray; the first `scalar` is converted into an ndarray and broadcasted.
|
||||
/// - `np.add(np.array([[1], [2], [3]]), np.array([[4, 5, 6]]))` # (ndarray, ndarray) -> ndarray; there is broadcasting.
|
||||
///
|
||||
/// ## Details:
|
||||
///
|
||||
/// If `inputs` are all [`ScalarOrNDArray::Scalar`], the output will be a [`ScalarOrNDArray::Scalar`] with type `ret_dtype`.
|
||||
///
|
||||
/// Otherwise (if there are any [`ScalarOrNDArray::NDArray`] in `inputs`), all inputs will be 'as-ndarray'-ed into ndarrays,
|
||||
/// then all inputs (now all ndarrays) will be passed to [`NDArrayObject::broadcasting_starmap`] and **create** a new ndarray
|
||||
/// with dtype `ret_dtype`.
|
||||
pub fn broadcasting_starmap<'a, G, MappingFn>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, 'a>,
|
||||
inputs: &[ScalarOrNDArray<'ctx>],
|
||||
ret_dtype: Type,
|
||||
mapping: MappingFn,
|
||||
) -> Result<ScalarOrNDArray<'ctx>, String>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
MappingFn: FnOnce(
|
||||
&mut G,
|
||||
&mut CodeGenContext<'ctx, 'a>,
|
||||
&[BasicValueEnum<'ctx>],
|
||||
) -> Result<BasicValueEnum<'ctx>, String>,
|
||||
{
|
||||
// Check if all inputs are Scalars
|
||||
let all_scalars: Option<Vec<_>> = inputs.iter().map(AnyObject::try_from).try_collect().ok();
|
||||
|
||||
if let Some(scalars) = all_scalars {
|
||||
let scalars = scalars.iter().map(|scalar| scalar.value).collect_vec();
|
||||
let value = mapping(generator, ctx, &scalars)?;
|
||||
|
||||
Ok(ScalarOrNDArray::Scalar(AnyObject { ty: ret_dtype, value }))
|
||||
} else {
|
||||
// Promote all input to ndarrays and map through them.
|
||||
let inputs = inputs.iter().map(|input| input.to_ndarray(generator, ctx)).collect_vec();
|
||||
let ndarray = NDArrayObject::broadcast_starmap(
|
||||
generator,
|
||||
ctx,
|
||||
&inputs,
|
||||
NDArrayOut::NewNDArray { dtype: ret_dtype },
|
||||
mapping,
|
||||
)?;
|
||||
Ok(ScalarOrNDArray::NDArray(ndarray))
|
||||
}
|
||||
}
|
||||
|
||||
/// Map through this [`ScalarOrNDArray`] with an elementwise function.
|
||||
///
|
||||
/// If this is a scalar, `mapping` will directly act on the scalar. This function will return a [`ScalarOrNDArray::Scalar`] of that result.
|
||||
///
|
||||
/// If this is an ndarray, `mapping` will be applied to the elements of the ndarray. A new ndarray of the results will be created and
|
||||
/// returned as a [`ScalarOrNDArray::NDArray`].
|
||||
pub fn map<'a, G, Mapping>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, 'a>,
|
||||
ret_dtype: Type,
|
||||
mapping: Mapping,
|
||||
) -> Result<ScalarOrNDArray<'ctx>, String>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
Mapping: FnOnce(
|
||||
&mut G,
|
||||
&mut CodeGenContext<'ctx, 'a>,
|
||||
BasicValueEnum<'ctx>,
|
||||
) -> Result<BasicValueEnum<'ctx>, String>,
|
||||
{
|
||||
ScalarOrNDArray::broadcasting_starmap(
|
||||
generator,
|
||||
ctx,
|
||||
&[*self],
|
||||
ret_dtype,
|
||||
|generator, ctx, scalars| mapping(generator, ctx, scalars[0]),
|
||||
)
|
||||
}
|
||||
}
|
218
nac3core/src/codegen/object/ndarray/matmul.rs
Normal file
218
nac3core/src/codegen/object/ndarray/matmul.rs
Normal file
@ -0,0 +1,218 @@
|
||||
use std::cmp::max;
|
||||
|
||||
use nac3parser::ast::Operator;
|
||||
use util::gen_for_model;
|
||||
|
||||
use crate::{
|
||||
codegen::{
|
||||
expr::gen_binop_expr_with_values, irrt::call_nac3_ndarray_matmul_calculate_shapes,
|
||||
model::*, object::ndarray::indexing::RustNDIndex, CodeGenContext, CodeGenerator,
|
||||
},
|
||||
typecheck::{magic_methods::Binop, typedef::Type},
|
||||
};
|
||||
|
||||
use super::{NDArrayObject, NDArrayOut};
|
||||
|
||||
/// Perform `np.einsum("...ij,...jk->...ik", in_a, in_b)`.
|
||||
///
|
||||
/// `dst_dtype` defines the dtype of the returned ndarray.
|
||||
fn matmul_at_least_2d<'ctx, G: CodeGenerator>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
dst_dtype: Type,
|
||||
in_a: NDArrayObject<'ctx>,
|
||||
in_b: NDArrayObject<'ctx>,
|
||||
) -> NDArrayObject<'ctx> {
|
||||
assert!(in_a.ndims >= 2);
|
||||
assert!(in_b.ndims >= 2);
|
||||
|
||||
// Deduce ndims of the result of matmul.
|
||||
let ndims_int = max(in_a.ndims, in_b.ndims);
|
||||
let ndims = Int(SizeT).const_int(generator, ctx.ctx, ndims_int, false);
|
||||
|
||||
// Broadcasts `in_a.shape[:-2]` and `in_b.shape[:-2]` together and allocate the
|
||||
// destination ndarray to store the result of matmul.
|
||||
let (lhs, rhs, dst) = {
|
||||
let in_lhs_ndims = in_a.ndims_llvm(generator, ctx.ctx);
|
||||
let in_lhs_shape = in_a.instance.get(generator, ctx, |f| f.shape);
|
||||
let in_rhs_ndims = in_b.ndims_llvm(generator, ctx.ctx);
|
||||
let in_rhs_shape = in_b.instance.get(generator, ctx, |f| f.shape);
|
||||
let lhs_shape = Int(SizeT).array_alloca(generator, ctx, ndims.value);
|
||||
let rhs_shape = Int(SizeT).array_alloca(generator, ctx, ndims.value);
|
||||
let dst_shape = Int(SizeT).array_alloca(generator, ctx, ndims.value);
|
||||
|
||||
// Matmul dimension compatibility is checked here.
|
||||
call_nac3_ndarray_matmul_calculate_shapes(
|
||||
generator,
|
||||
ctx,
|
||||
in_lhs_ndims,
|
||||
in_lhs_shape,
|
||||
in_rhs_ndims,
|
||||
in_rhs_shape,
|
||||
ndims,
|
||||
lhs_shape,
|
||||
rhs_shape,
|
||||
dst_shape,
|
||||
);
|
||||
|
||||
let lhs = in_a.broadcast_to(generator, ctx, ndims_int, lhs_shape);
|
||||
let rhs = in_b.broadcast_to(generator, ctx, ndims_int, rhs_shape);
|
||||
|
||||
let dst = NDArrayObject::alloca(generator, ctx, dst_dtype, ndims_int);
|
||||
dst.copy_shape_from_array(generator, ctx, dst_shape);
|
||||
dst.create_data(generator, ctx);
|
||||
|
||||
(lhs, rhs, dst)
|
||||
};
|
||||
|
||||
let len = lhs.instance.get(generator, ctx, |f| f.shape).get_index_const(
|
||||
generator,
|
||||
ctx,
|
||||
i64::try_from(ndims_int - 1).unwrap(),
|
||||
);
|
||||
|
||||
let at_row = i64::try_from(ndims_int - 2).unwrap();
|
||||
let at_col = i64::try_from(ndims_int - 1).unwrap();
|
||||
|
||||
let dst_dtype_llvm = ctx.get_llvm_type(generator, dst_dtype);
|
||||
let dst_zero = dst_dtype_llvm.const_zero();
|
||||
|
||||
dst.foreach(generator, ctx, |generator, ctx, _, hdl| {
|
||||
let pdst_ij = hdl.get_pointer(generator, ctx);
|
||||
|
||||
ctx.builder.build_store(pdst_ij, dst_zero).unwrap();
|
||||
|
||||
let indices = hdl.get_indices();
|
||||
let i = indices.get_index_const(generator, ctx, at_row);
|
||||
let j = indices.get_index_const(generator, ctx, at_col);
|
||||
|
||||
let num_0 = Int(SizeT).const_int(generator, ctx.ctx, 0, false);
|
||||
let num_1 = Int(SizeT).const_int(generator, ctx.ctx, 1, false);
|
||||
|
||||
gen_for_model(generator, ctx, num_0, len, num_1, |generator, ctx, _, k| {
|
||||
// `indices` is modified to index into `a` and `b`, and restored.
|
||||
indices.set_index_const(ctx, at_row, i);
|
||||
indices.set_index_const(ctx, at_col, k);
|
||||
let a_ik = lhs.get_scalar_by_indices(generator, ctx, indices);
|
||||
|
||||
indices.set_index_const(ctx, at_row, k);
|
||||
indices.set_index_const(ctx, at_col, j);
|
||||
let b_kj = rhs.get_scalar_by_indices(generator, ctx, indices);
|
||||
|
||||
// Restore `indices`.
|
||||
indices.set_index_const(ctx, at_row, i);
|
||||
indices.set_index_const(ctx, at_col, j);
|
||||
|
||||
// x = a_[...]ik * b_[...]kj
|
||||
let x = gen_binop_expr_with_values(
|
||||
generator,
|
||||
ctx,
|
||||
(&Some(lhs.dtype), a_ik.value),
|
||||
Binop::normal(Operator::Mult),
|
||||
(&Some(rhs.dtype), b_kj.value),
|
||||
ctx.current_loc,
|
||||
)?
|
||||
.unwrap()
|
||||
.to_basic_value_enum(ctx, generator, dst_dtype)?;
|
||||
|
||||
// dst_[...]ij += x
|
||||
let dst_ij = ctx.builder.build_load(pdst_ij, "").unwrap();
|
||||
let dst_ij = gen_binop_expr_with_values(
|
||||
generator,
|
||||
ctx,
|
||||
(&Some(dst_dtype), dst_ij),
|
||||
Binop::normal(Operator::Add),
|
||||
(&Some(dst_dtype), x),
|
||||
ctx.current_loc,
|
||||
)?
|
||||
.unwrap()
|
||||
.to_basic_value_enum(ctx, generator, dst_dtype)?;
|
||||
ctx.builder.build_store(pdst_ij, dst_ij).unwrap();
|
||||
|
||||
Ok(())
|
||||
})
|
||||
})
|
||||
.unwrap();
|
||||
|
||||
dst
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
/// Perform `np.matmul` according to the rules in
|
||||
/// <https://numpy.org/doc/stable/reference/generated/numpy.matmul.html>.
|
||||
///
|
||||
/// This function always return an [`NDArrayObject`]. You may want to use [`NDArrayObject::split_unsized`]
|
||||
/// to handle when the output could be a scalar.
|
||||
///
|
||||
/// `dst_dtype` defines the dtype of the returned ndarray.
|
||||
pub fn matmul<G: CodeGenerator>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
a: Self,
|
||||
b: Self,
|
||||
out: NDArrayOut<'ctx>,
|
||||
) -> Self {
|
||||
// Sanity check, but type inference should prevent this.
|
||||
assert!(a.ndims > 0 && b.ndims > 0, "np.matmul disallows scalar input");
|
||||
|
||||
/*
|
||||
If both arguments are 2-D they are multiplied like conventional matrices.
|
||||
If either argument is N-D, N > 2, it is treated as a stack of matrices residing in the last two indices and broadcast accordingly.
|
||||
If the first argument is 1-D, it is promoted to a matrix by prepending a 1 to its dimensions. After matrix multiplication the prepended 1 is removed.
|
||||
If the second argument is 1-D, it is promoted to a matrix by appending a 1 to its dimensions. After matrix multiplication the appended 1 is removed.
|
||||
*/
|
||||
|
||||
let new_a = if a.ndims == 1 {
|
||||
// Prepend 1 to its dimensions
|
||||
a.index(generator, ctx, &[RustNDIndex::NewAxis, RustNDIndex::Ellipsis])
|
||||
} else {
|
||||
a
|
||||
};
|
||||
|
||||
let new_b = if b.ndims == 1 {
|
||||
// Append 1 to its dimensions
|
||||
b.index(generator, ctx, &[RustNDIndex::Ellipsis, RustNDIndex::NewAxis])
|
||||
} else {
|
||||
b
|
||||
};
|
||||
|
||||
// NOTE: `result` will always be a newly allocated ndarray.
|
||||
// Current implementation cannot do in-place matrix muliplication.
|
||||
let mut result = matmul_at_least_2d(generator, ctx, out.get_dtype(), new_a, new_b);
|
||||
|
||||
// Postprocessing on the result to remove prepended/appended axes.
|
||||
let mut postindices = vec![];
|
||||
let zero = Int(Int32).const_0(generator, ctx.ctx);
|
||||
|
||||
if a.ndims == 1 {
|
||||
// Remove the prepended 1
|
||||
postindices.push(RustNDIndex::SingleElement(zero));
|
||||
}
|
||||
|
||||
if b.ndims == 1 {
|
||||
// Remove the appended 1
|
||||
postindices.push(RustNDIndex::Ellipsis);
|
||||
postindices.push(RustNDIndex::SingleElement(zero));
|
||||
}
|
||||
|
||||
if !postindices.is_empty() {
|
||||
result = result.index(generator, ctx, &postindices);
|
||||
}
|
||||
|
||||
match out {
|
||||
NDArrayOut::NewNDArray { .. } => result,
|
||||
NDArrayOut::WriteToNDArray { ndarray: out_ndarray } => {
|
||||
let result_shape = result.instance.get(generator, ctx, |f| f.shape);
|
||||
out_ndarray.assert_can_be_written_by_out(
|
||||
generator,
|
||||
ctx,
|
||||
result.ndims,
|
||||
result_shape,
|
||||
);
|
||||
|
||||
out_ndarray.copy_data_from(generator, ctx, result);
|
||||
out_ndarray
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
655
nac3core/src/codegen/object/ndarray/mod.rs
Normal file
655
nac3core/src/codegen/object/ndarray/mod.rs
Normal file
@ -0,0 +1,655 @@
|
||||
pub mod array;
|
||||
pub mod broadcast;
|
||||
pub mod contiguous;
|
||||
pub mod factory;
|
||||
pub mod indexing;
|
||||
pub mod map;
|
||||
pub mod matmul;
|
||||
pub mod nditer;
|
||||
pub mod shape_util;
|
||||
pub mod view;
|
||||
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
types::BasicType,
|
||||
values::{BasicValue, BasicValueEnum, PointerValue},
|
||||
AddressSpace,
|
||||
};
|
||||
|
||||
use crate::{
|
||||
codegen::{
|
||||
irrt::{
|
||||
call_nac3_ndarray_copy_data, call_nac3_ndarray_get_nth_pelement,
|
||||
call_nac3_ndarray_get_pelement_by_indices, call_nac3_ndarray_is_c_contiguous,
|
||||
call_nac3_ndarray_len, call_nac3_ndarray_nbytes,
|
||||
call_nac3_ndarray_set_strides_by_shape, call_nac3_ndarray_size,
|
||||
call_nac3_ndarray_util_assert_output_shape_same,
|
||||
},
|
||||
model::*,
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
toplevel::{
|
||||
helper::{create_ndims, extract_ndims},
|
||||
numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
|
||||
},
|
||||
typecheck::typedef::{Type, TypeEnum},
|
||||
};
|
||||
|
||||
use super::{any::AnyObject, tuple::TupleObject};
|
||||
|
||||
/// Fields of [`NDArray`]
|
||||
pub struct NDArrayFields<'ctx, F: FieldTraversal<'ctx>> {
|
||||
pub data: F::Output<Ptr<Int<Byte>>>,
|
||||
pub itemsize: F::Output<Int<SizeT>>,
|
||||
pub ndims: F::Output<Int<SizeT>>,
|
||||
pub shape: F::Output<Ptr<Int<SizeT>>>,
|
||||
pub strides: F::Output<Ptr<Int<SizeT>>>,
|
||||
}
|
||||
|
||||
/// A strided ndarray in NAC3.
|
||||
///
|
||||
/// See IRRT implementation for details about its fields.
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct NDArray;
|
||||
|
||||
impl<'ctx> StructKind<'ctx> for NDArray {
|
||||
type Fields<F: FieldTraversal<'ctx>> = NDArrayFields<'ctx, F>;
|
||||
|
||||
fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields {
|
||||
data: traversal.add_auto("data"),
|
||||
itemsize: traversal.add_auto("itemsize"),
|
||||
ndims: traversal.add_auto("ndims"),
|
||||
shape: traversal.add_auto("shape"),
|
||||
strides: traversal.add_auto("strides"),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// A NAC3 Python ndarray object.
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct NDArrayObject<'ctx> {
|
||||
pub dtype: Type,
|
||||
pub ndims: u64,
|
||||
pub instance: Instance<'ctx, Ptr<Struct<NDArray>>>,
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
/// Attempt to convert an [`AnyObject`] into an [`NDArrayObject`].
|
||||
pub fn from_object<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
object: AnyObject<'ctx>,
|
||||
) -> NDArrayObject<'ctx> {
|
||||
let (dtype, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, object.ty);
|
||||
let ndims = extract_ndims(&ctx.unifier, ndims);
|
||||
Self::from_value_and_unpacked_types(generator, ctx, object.value, dtype, ndims)
|
||||
}
|
||||
|
||||
/// Like [`NDArrayObject::from_object`] but you directly supply the ndarray's
|
||||
/// `dtype` and `ndims`.
|
||||
pub fn from_value_and_unpacked_types<V: BasicValue<'ctx>, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
value: V,
|
||||
dtype: Type,
|
||||
ndims: u64,
|
||||
) -> Self {
|
||||
let value = Ptr(Struct(NDArray)).check_value(generator, ctx.ctx, value).unwrap();
|
||||
NDArrayObject { dtype, ndims, instance: value }
|
||||
}
|
||||
|
||||
/// Get this ndarray's `ndims` as an LLVM constant.
|
||||
pub fn ndims_llvm<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &'ctx Context,
|
||||
) -> Instance<'ctx, Int<SizeT>> {
|
||||
Int(SizeT).const_int(generator, ctx, self.ndims, false)
|
||||
}
|
||||
|
||||
/// Get the typechecker ndarray type of this [`NDArrayObject`].
|
||||
pub fn get_type(&self, ctx: &mut CodeGenContext<'ctx, '_>) -> Type {
|
||||
let ndims = create_ndims(&mut ctx.unifier, self.ndims);
|
||||
make_ndarray_ty(&mut ctx.unifier, &ctx.primitives, Some(self.dtype), Some(ndims))
|
||||
}
|
||||
|
||||
/// Forget that this is an ndarray and convert into an [`AnyObject`].
|
||||
pub fn to_any(&self, ctx: &mut CodeGenContext<'ctx, '_>) -> AnyObject<'ctx> {
|
||||
let ty = self.get_type(ctx);
|
||||
AnyObject { value: self.instance.value.as_basic_value_enum(), ty }
|
||||
}
|
||||
|
||||
/// Allocate an ndarray on the stack given its `ndims` and `dtype`.
|
||||
///
|
||||
/// `shape` and `strides` will be automatically allocated onto the stack.
|
||||
///
|
||||
/// The returned ndarray's content will be:
|
||||
/// - `data`: uninitialized.
|
||||
/// - `itemsize`: set to the `sizeof()` of `dtype`.
|
||||
/// - `ndims`: set to the value of `ndims`.
|
||||
/// - `shape`: allocated with an array of length `ndims` with uninitialized values.
|
||||
/// - `strides`: allocated with an array of length `ndims` with uninitialized values.
|
||||
pub fn alloca<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
dtype: Type,
|
||||
ndims: u64,
|
||||
) -> Self {
|
||||
let ndarray = Struct(NDArray).alloca(generator, ctx);
|
||||
|
||||
let itemsize = ctx.get_llvm_type(generator, dtype).size_of().unwrap();
|
||||
let itemsize = Int(SizeT).z_extend_or_truncate(generator, ctx, itemsize);
|
||||
ndarray.set(ctx, |f| f.itemsize, itemsize);
|
||||
|
||||
let ndims_val = Int(SizeT).const_int(generator, ctx.ctx, ndims, false);
|
||||
ndarray.set(ctx, |f| f.ndims, ndims_val);
|
||||
|
||||
let shape = Int(SizeT).array_alloca(generator, ctx, ndims_val.value);
|
||||
ndarray.set(ctx, |f| f.shape, shape);
|
||||
|
||||
let strides = Int(SizeT).array_alloca(generator, ctx, ndims_val.value);
|
||||
ndarray.set(ctx, |f| f.strides, strides);
|
||||
|
||||
NDArrayObject { dtype, ndims, instance: ndarray }
|
||||
}
|
||||
|
||||
/// Convenience function. Allocate an [`NDArrayObject`] with a statically known shape.
|
||||
///
|
||||
/// The returned [`NDArrayObject`]'s `data` and `strides` are uninitialized.
|
||||
pub fn alloca_constant_shape<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
dtype: Type,
|
||||
shape: &[u64],
|
||||
) -> Self {
|
||||
let ndarray = NDArrayObject::alloca(generator, ctx, dtype, shape.len() as u64);
|
||||
|
||||
// Write shape
|
||||
let dst_shape = ndarray.instance.get(generator, ctx, |f| f.shape);
|
||||
for (i, dim) in shape.iter().enumerate() {
|
||||
let dim = Int(SizeT).const_int(generator, ctx.ctx, *dim, false);
|
||||
dst_shape.offset_const(ctx, i64::try_from(i).unwrap()).store(ctx, dim);
|
||||
}
|
||||
|
||||
ndarray
|
||||
}
|
||||
|
||||
/// Convenience function. Allocate an [`NDArrayObject`] with a dynamically known shape.
|
||||
///
|
||||
/// The returned [`NDArrayObject`]'s `data` and `strides` are uninitialized.
|
||||
pub fn alloca_dynamic_shape<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
dtype: Type,
|
||||
shape: &[Instance<'ctx, Int<SizeT>>],
|
||||
) -> Self {
|
||||
let ndarray = NDArrayObject::alloca(generator, ctx, dtype, shape.len() as u64);
|
||||
|
||||
// Write shape
|
||||
let dst_shape = ndarray.instance.get(generator, ctx, |f| f.shape);
|
||||
for (i, dim) in shape.iter().enumerate() {
|
||||
dst_shape.offset_const(ctx, i64::try_from(i).unwrap()).store(ctx, *dim);
|
||||
}
|
||||
|
||||
ndarray
|
||||
}
|
||||
|
||||
/// Initialize an ndarray's `data` by allocating a buffer on the stack.
|
||||
/// The allocated data buffer is considered to be *owned* by the ndarray.
|
||||
///
|
||||
/// `strides` of the ndarray will also be updated with `set_strides_by_shape`.
|
||||
///
|
||||
/// `shape` and `itemsize` of the ndarray ***must*** be initialized first.
|
||||
pub fn create_data<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) {
|
||||
let nbytes = self.nbytes(generator, ctx);
|
||||
|
||||
let data = Int(Byte).array_alloca(generator, ctx, nbytes.value);
|
||||
self.instance.set(ctx, |f| f.data, data);
|
||||
|
||||
self.set_strides_contiguous(generator, ctx);
|
||||
}
|
||||
|
||||
/// Copy shape dimensions from an array.
|
||||
pub fn copy_shape_from_array<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
shape: Instance<'ctx, Ptr<Int<SizeT>>>,
|
||||
) {
|
||||
let num_items = self.ndims_llvm(generator, ctx.ctx).value;
|
||||
self.instance.get(generator, ctx, |f| f.shape).copy_from(generator, ctx, shape, num_items);
|
||||
}
|
||||
|
||||
/// Copy shape dimensions from an ndarray.
|
||||
/// Panics if `ndims` mismatches.
|
||||
pub fn copy_shape_from_ndarray<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
src_ndarray: NDArrayObject<'ctx>,
|
||||
) {
|
||||
assert_eq!(self.ndims, src_ndarray.ndims);
|
||||
let src_shape = src_ndarray.instance.get(generator, ctx, |f| f.shape);
|
||||
self.copy_shape_from_array(generator, ctx, src_shape);
|
||||
}
|
||||
|
||||
/// Copy strides dimensions from an array.
|
||||
pub fn copy_strides_from_array<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
strides: Instance<'ctx, Ptr<Int<SizeT>>>,
|
||||
) {
|
||||
let num_items = self.ndims_llvm(generator, ctx.ctx).value;
|
||||
self.instance
|
||||
.get(generator, ctx, |f| f.strides)
|
||||
.copy_from(generator, ctx, strides, num_items);
|
||||
}
|
||||
|
||||
/// Copy strides dimensions from an ndarray.
|
||||
/// Panics if `ndims` mismatches.
|
||||
pub fn copy_strides_from_ndarray<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
src_ndarray: NDArrayObject<'ctx>,
|
||||
) {
|
||||
assert_eq!(self.ndims, src_ndarray.ndims);
|
||||
let src_strides = src_ndarray.instance.get(generator, ctx, |f| f.strides);
|
||||
self.copy_strides_from_array(generator, ctx, src_strides);
|
||||
}
|
||||
|
||||
/// Get the `np.size()` of this ndarray.
|
||||
pub fn size<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> Instance<'ctx, Int<SizeT>> {
|
||||
call_nac3_ndarray_size(generator, ctx, self.instance)
|
||||
}
|
||||
|
||||
/// Get the `ndarray.nbytes` of this ndarray.
|
||||
pub fn nbytes<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> Instance<'ctx, Int<SizeT>> {
|
||||
call_nac3_ndarray_nbytes(generator, ctx, self.instance)
|
||||
}
|
||||
|
||||
/// Get the `len()` of this ndarray.
|
||||
pub fn len<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> Instance<'ctx, Int<SizeT>> {
|
||||
call_nac3_ndarray_len(generator, ctx, self.instance)
|
||||
}
|
||||
|
||||
/// Check if this ndarray is C-contiguous.
|
||||
///
|
||||
/// See NumPy's `flags["C_CONTIGUOUS"]`: <https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html#numpy.ndarray.flags>
|
||||
pub fn is_c_contiguous<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> Instance<'ctx, Int<Bool>> {
|
||||
call_nac3_ndarray_is_c_contiguous(generator, ctx, self.instance)
|
||||
}
|
||||
|
||||
/// Get the pointer to the n-th (0-based) element.
|
||||
///
|
||||
/// The returned pointer has the element type of the LLVM type of this ndarray's `dtype`.
|
||||
pub fn get_nth_pelement<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
nth: Instance<'ctx, Int<SizeT>>,
|
||||
) -> PointerValue<'ctx> {
|
||||
let elem_ty = ctx.get_llvm_type(generator, self.dtype);
|
||||
|
||||
let p = call_nac3_ndarray_get_nth_pelement(generator, ctx, self.instance, nth);
|
||||
ctx.builder
|
||||
.build_pointer_cast(p.value, elem_ty.ptr_type(AddressSpace::default()), "")
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Get the n-th (0-based) scalar.
|
||||
pub fn get_nth_scalar<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
nth: Instance<'ctx, Int<SizeT>>,
|
||||
) -> AnyObject<'ctx> {
|
||||
let ptr = self.get_nth_pelement(generator, ctx, nth);
|
||||
let value = ctx.builder.build_load(ptr, "").unwrap();
|
||||
AnyObject { ty: self.dtype, value }
|
||||
}
|
||||
|
||||
/// Get the pointer to the element indexed by `indices`.
|
||||
///
|
||||
/// The returned pointer has the element type of the LLVM type of this ndarray's `dtype`.
|
||||
pub fn get_pelement_by_indices<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
indices: Instance<'ctx, Ptr<Int<SizeT>>>,
|
||||
) -> PointerValue<'ctx> {
|
||||
let elem_ty = ctx.get_llvm_type(generator, self.dtype);
|
||||
|
||||
let p = call_nac3_ndarray_get_pelement_by_indices(generator, ctx, self.instance, indices);
|
||||
ctx.builder
|
||||
.build_pointer_cast(p.value, elem_ty.ptr_type(AddressSpace::default()), "")
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Get the scalar indexed by `indices`.
|
||||
pub fn get_scalar_by_indices<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
indices: Instance<'ctx, Ptr<Int<SizeT>>>,
|
||||
) -> AnyObject<'ctx> {
|
||||
let ptr = self.get_pelement_by_indices(generator, ctx, indices);
|
||||
let value = ctx.builder.build_load(ptr, "").unwrap();
|
||||
AnyObject { ty: self.dtype, value }
|
||||
}
|
||||
|
||||
/// Call [`call_nac3_ndarray_set_strides_by_shape`] on this ndarray to update `strides`.
|
||||
///
|
||||
/// Update the ndarray's strides to make the ndarray contiguous.
|
||||
pub fn set_strides_contiguous<G: CodeGenerator + ?Sized>(
|
||||
self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) {
|
||||
call_nac3_ndarray_set_strides_by_shape(generator, ctx, self.instance);
|
||||
}
|
||||
|
||||
/// Clone/Copy this ndarray - Allocate a new ndarray with the same shape as this ndarray and copy the contents over.
|
||||
///
|
||||
/// The new ndarray will own its data and will be C-contiguous.
|
||||
#[must_use]
|
||||
pub fn make_copy<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> Self {
|
||||
let clone = NDArrayObject::alloca(generator, ctx, self.dtype, self.ndims);
|
||||
|
||||
let shape = self.instance.gep(ctx, |f| f.shape).load(generator, ctx);
|
||||
clone.copy_shape_from_array(generator, ctx, shape);
|
||||
clone.create_data(generator, ctx);
|
||||
clone.copy_data_from(generator, ctx, *self);
|
||||
clone
|
||||
}
|
||||
|
||||
/// Copy data from another ndarray.
|
||||
///
|
||||
/// This ndarray and `src` is that their `np.size()` should be the same. Their shapes
|
||||
/// do not matter. The copying order is determined by how their flattened views look.
|
||||
///
|
||||
/// Panics if the `dtype`s of ndarrays are different.
|
||||
pub fn copy_data_from<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
src: NDArrayObject<'ctx>,
|
||||
) {
|
||||
assert!(ctx.unifier.unioned(self.dtype, src.dtype), "self and src dtype should match");
|
||||
call_nac3_ndarray_copy_data(generator, ctx, src.instance, self.instance);
|
||||
}
|
||||
|
||||
/// Returns true if this ndarray is unsized - `ndims == 0` and only contains a scalar.
|
||||
#[must_use]
|
||||
pub fn is_unsized(&self) -> bool {
|
||||
self.ndims == 0
|
||||
}
|
||||
|
||||
/// If this ndarray is unsized, return its sole value as an [`AnyObject`].
|
||||
/// Otherwise, do nothing and return the ndarray itself.
|
||||
pub fn split_unsized<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> ScalarOrNDArray<'ctx> {
|
||||
if self.is_unsized() {
|
||||
// NOTE: `np.size(self) == 0` here is never possible.
|
||||
let zero = Int(SizeT).const_0(generator, ctx.ctx);
|
||||
let value = self.get_nth_scalar(generator, ctx, zero).value;
|
||||
|
||||
ScalarOrNDArray::Scalar(AnyObject { ty: self.dtype, value })
|
||||
} else {
|
||||
ScalarOrNDArray::NDArray(*self)
|
||||
}
|
||||
}
|
||||
|
||||
/// Fill the ndarray with a scalar.
|
||||
///
|
||||
/// `fill_value` must have the same LLVM type as the `dtype` of this ndarray.
|
||||
pub fn fill<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
value: BasicValueEnum<'ctx>,
|
||||
) {
|
||||
// TODO: It is possible to optimize this by exploiting contiguous strides with memset.
|
||||
// Probably best to implement in IRRT.
|
||||
self.foreach(generator, ctx, |generator, ctx, _hooks, nditer| {
|
||||
let p = nditer.get_pointer(generator, ctx);
|
||||
ctx.builder.build_store(p, value).unwrap();
|
||||
Ok(())
|
||||
})
|
||||
.unwrap();
|
||||
}
|
||||
|
||||
/// Create the shape tuple of this ndarray like `np.shape(<ndarray>)`.
|
||||
///
|
||||
/// The returned integers in the tuple are in int32.
|
||||
pub fn make_shape_tuple<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> TupleObject<'ctx> {
|
||||
// TODO: Return a tuple of SizeT
|
||||
|
||||
let mut objects = Vec::with_capacity(self.ndims as usize);
|
||||
|
||||
for i in 0..self.ndims {
|
||||
let dim = self
|
||||
.instance
|
||||
.get(generator, ctx, |f| f.shape)
|
||||
.get_index_const(generator, ctx, i64::try_from(i).unwrap())
|
||||
.truncate_or_bit_cast(generator, ctx, Int32);
|
||||
|
||||
objects.push(AnyObject {
|
||||
ty: ctx.primitives.int32,
|
||||
value: dim.value.as_basic_value_enum(),
|
||||
});
|
||||
}
|
||||
|
||||
TupleObject::from_objects(generator, ctx, objects)
|
||||
}
|
||||
|
||||
/// Create the strides tuple of this ndarray like `<ndarray>.strides`.
|
||||
///
|
||||
/// The returned integers in the tuple are in int32.
|
||||
pub fn make_strides_tuple<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> TupleObject<'ctx> {
|
||||
// TODO: Return a tuple of SizeT.
|
||||
|
||||
let mut objects = Vec::with_capacity(self.ndims as usize);
|
||||
|
||||
for i in 0..self.ndims {
|
||||
let dim = self
|
||||
.instance
|
||||
.get(generator, ctx, |f| f.strides)
|
||||
.get_index_const(generator, ctx, i64::try_from(i).unwrap())
|
||||
.truncate_or_bit_cast(generator, ctx, Int32);
|
||||
|
||||
objects.push(AnyObject {
|
||||
ty: ctx.primitives.int32,
|
||||
value: dim.value.as_basic_value_enum(),
|
||||
});
|
||||
}
|
||||
|
||||
TupleObject::from_objects(generator, ctx, objects)
|
||||
}
|
||||
|
||||
/// Create an unsized ndarray to contain `object`.
|
||||
pub fn make_unsized<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
object: AnyObject<'ctx>,
|
||||
) -> NDArrayObject<'ctx> {
|
||||
// We have to put the value on the stack to get a data pointer.
|
||||
let data = ctx.builder.build_alloca(object.value.get_type(), "make_unsized").unwrap();
|
||||
ctx.builder.build_store(data, object.value).unwrap();
|
||||
let data = Ptr(Int(Byte)).pointer_cast(generator, ctx, data);
|
||||
|
||||
let ndarray = NDArrayObject::alloca(generator, ctx, object.ty, 0);
|
||||
ndarray.instance.set(ctx, |f| f.data, data);
|
||||
ndarray
|
||||
}
|
||||
/// Check if this `NDArray` can be used as an `out` ndarray for an operation.
|
||||
///
|
||||
/// Raise an exception if the shapes do not match.
|
||||
pub fn assert_can_be_written_by_out<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
out_ndims: u64,
|
||||
out_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
|
||||
) {
|
||||
let ndarray_ndims = self.ndims_llvm(generator, ctx.ctx);
|
||||
let ndarray_shape = self.instance.get(generator, ctx, |f| f.shape);
|
||||
|
||||
let output_ndims = Int(SizeT).const_int(generator, ctx.ctx, out_ndims, false);
|
||||
let output_shape = out_shape;
|
||||
|
||||
call_nac3_ndarray_util_assert_output_shape_same(
|
||||
generator,
|
||||
ctx,
|
||||
ndarray_ndims,
|
||||
ndarray_shape,
|
||||
output_ndims,
|
||||
output_shape,
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
/// A convenience enum for implementing functions that acts on scalars or ndarrays or both.
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub enum ScalarOrNDArray<'ctx> {
|
||||
Scalar(AnyObject<'ctx>),
|
||||
NDArray(NDArrayObject<'ctx>),
|
||||
}
|
||||
|
||||
impl<'ctx> TryFrom<&ScalarOrNDArray<'ctx>> for AnyObject<'ctx> {
|
||||
type Error = ();
|
||||
|
||||
fn try_from(value: &ScalarOrNDArray<'ctx>) -> Result<Self, Self::Error> {
|
||||
match value {
|
||||
ScalarOrNDArray::Scalar(scalar) => Ok(*scalar),
|
||||
ScalarOrNDArray::NDArray(_ndarray) => Err(()),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> TryFrom<&ScalarOrNDArray<'ctx>> for NDArrayObject<'ctx> {
|
||||
type Error = ();
|
||||
|
||||
fn try_from(value: &ScalarOrNDArray<'ctx>) -> Result<Self, Self::Error> {
|
||||
match value {
|
||||
ScalarOrNDArray::Scalar(_scalar) => Err(()),
|
||||
ScalarOrNDArray::NDArray(ndarray) => Ok(*ndarray),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> ScalarOrNDArray<'ctx> {
|
||||
/// Split on `object` either into a scalar or an ndarray.
|
||||
///
|
||||
/// If `object` is an ndarray, [`ScalarOrNDArray::NDArray`].
|
||||
///
|
||||
/// For everything else, it is wrapped with [`ScalarOrNDArray::Scalar`].
|
||||
pub fn split_object<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
object: AnyObject<'ctx>,
|
||||
) -> ScalarOrNDArray<'ctx> {
|
||||
match &*ctx.unifier.get_ty(object.ty) {
|
||||
TypeEnum::TObj { obj_id, .. }
|
||||
if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
|
||||
{
|
||||
let ndarray = NDArrayObject::from_object(generator, ctx, object);
|
||||
ScalarOrNDArray::NDArray(ndarray)
|
||||
}
|
||||
_ => ScalarOrNDArray::Scalar(object),
|
||||
}
|
||||
}
|
||||
|
||||
/// Get the underlying [`BasicValueEnum<'ctx>`] of this [`ScalarOrNDArray`].
|
||||
#[must_use]
|
||||
pub fn to_basic_value_enum(self) -> BasicValueEnum<'ctx> {
|
||||
match self {
|
||||
ScalarOrNDArray::Scalar(scalar) => scalar.value,
|
||||
ScalarOrNDArray::NDArray(ndarray) => ndarray.instance.value.as_basic_value_enum(),
|
||||
}
|
||||
}
|
||||
|
||||
/// Convert this [`ScalarOrNDArray`] to an ndarray - behaves like `np.asarray`.
|
||||
/// - If this is an ndarray, the ndarray is returned.
|
||||
/// - If this is a scalar, this function returns new ndarray created with [`NDArrayObject::make_unsized`].
|
||||
pub fn to_ndarray<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> NDArrayObject<'ctx> {
|
||||
match self {
|
||||
ScalarOrNDArray::NDArray(ndarray) => *ndarray,
|
||||
ScalarOrNDArray::Scalar(scalar) => NDArrayObject::make_unsized(generator, ctx, *scalar),
|
||||
}
|
||||
}
|
||||
|
||||
/// Get the dtype of the ndarray created if this were called with [`ScalarOrNDArray::to_ndarray`].
|
||||
#[must_use]
|
||||
pub fn get_dtype(&self) -> Type {
|
||||
match self {
|
||||
ScalarOrNDArray::NDArray(ndarray) => ndarray.dtype,
|
||||
ScalarOrNDArray::Scalar(scalar) => scalar.ty,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// An helper enum specifying how a function should produce its output.
|
||||
///
|
||||
/// Many functions in NumPy has an optional `out` parameter (e.g., `matmul`). If `out` is specified
|
||||
/// with an ndarray, the result of a function will be written to `out`. If `out` is not specified, a function will
|
||||
/// create a new ndarray and store the result in it.
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub enum NDArrayOut<'ctx> {
|
||||
/// Tell a function should create a new ndarray with the expected element type `dtype`.
|
||||
NewNDArray { dtype: Type },
|
||||
/// Tell a function to write the result to `ndarray`.
|
||||
WriteToNDArray { ndarray: NDArrayObject<'ctx> },
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayOut<'ctx> {
|
||||
/// Get the dtype of this output.
|
||||
#[must_use]
|
||||
pub fn get_dtype(&self) -> Type {
|
||||
match self {
|
||||
NDArrayOut::NewNDArray { dtype } => *dtype,
|
||||
NDArrayOut::WriteToNDArray { ndarray } => ndarray.dtype,
|
||||
}
|
||||
}
|
||||
}
|
179
nac3core/src/codegen/object/ndarray/nditer.rs
Normal file
179
nac3core/src/codegen/object/ndarray/nditer.rs
Normal file
@ -0,0 +1,179 @@
|
||||
use inkwell::{types::BasicType, values::PointerValue, AddressSpace};
|
||||
|
||||
use crate::codegen::{
|
||||
irrt::{call_nac3_nditer_has_element, call_nac3_nditer_initialize, call_nac3_nditer_next},
|
||||
model::*,
|
||||
object::any::AnyObject,
|
||||
stmt::{gen_for_callback, BreakContinueHooks},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
use super::NDArrayObject;
|
||||
|
||||
/// Fields of [`NDIter`]
|
||||
pub struct NDIterFields<'ctx, F: FieldTraversal<'ctx>> {
|
||||
pub ndims: F::Output<Int<SizeT>>,
|
||||
pub shape: F::Output<Ptr<Int<SizeT>>>,
|
||||
pub strides: F::Output<Ptr<Int<SizeT>>>,
|
||||
|
||||
pub indices: F::Output<Ptr<Int<SizeT>>>,
|
||||
pub nth: F::Output<Int<SizeT>>,
|
||||
pub element: F::Output<Ptr<Int<Byte>>>,
|
||||
|
||||
pub size: F::Output<Int<SizeT>>,
|
||||
}
|
||||
|
||||
/// An IRRT helper structure used to iterate through an ndarray.
|
||||
#[derive(Debug, Clone, Copy, Default)]
|
||||
pub struct NDIter;
|
||||
|
||||
impl<'ctx> StructKind<'ctx> for NDIter {
|
||||
type Fields<F: FieldTraversal<'ctx>> = NDIterFields<'ctx, F>;
|
||||
|
||||
fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields {
|
||||
ndims: traversal.add_auto("ndims"),
|
||||
shape: traversal.add_auto("shape"),
|
||||
strides: traversal.add_auto("strides"),
|
||||
|
||||
indices: traversal.add_auto("indices"),
|
||||
nth: traversal.add_auto("nth"),
|
||||
element: traversal.add_auto("element"),
|
||||
|
||||
size: traversal.add_auto("size"),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// A helper structure with a convenient interface to interact with [`NDIter`].
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct NDIterHandle<'ctx> {
|
||||
instance: Instance<'ctx, Ptr<Struct<NDIter>>>,
|
||||
/// The ndarray this [`NDIter`] to iterating over.
|
||||
ndarray: NDArrayObject<'ctx>,
|
||||
/// The current indices of [`NDIter`].
|
||||
indices: Instance<'ctx, Ptr<Int<SizeT>>>,
|
||||
}
|
||||
|
||||
impl<'ctx> NDIterHandle<'ctx> {
|
||||
/// Allocate an [`NDIter`] that iterates through an ndarray.
|
||||
pub fn new<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndarray: NDArrayObject<'ctx>,
|
||||
) -> Self {
|
||||
let nditer = Struct(NDIter).alloca(generator, ctx);
|
||||
let ndims = ndarray.ndims_llvm(generator, ctx.ctx);
|
||||
|
||||
// The caller has the responsibility to allocate 'indices' for `NDIter`.
|
||||
let indices = Int(SizeT).array_alloca(generator, ctx, ndims.value);
|
||||
call_nac3_nditer_initialize(generator, ctx, nditer, ndarray.instance, indices);
|
||||
|
||||
NDIterHandle { ndarray, instance: nditer, indices }
|
||||
}
|
||||
|
||||
/// Is the current iteration valid?
|
||||
///
|
||||
/// If true, then `element`, `indices` and `nth` contain details about the current element.
|
||||
///
|
||||
/// If `ndarray` is unsized, this returns true only for the first iteration.
|
||||
/// If `ndarray` is 0-sized, this always returns false.
|
||||
#[must_use]
|
||||
pub fn has_element<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> Instance<'ctx, Int<Bool>> {
|
||||
call_nac3_nditer_has_element(generator, ctx, self.instance)
|
||||
}
|
||||
|
||||
/// Go to the next element. If `has_element()` is false, then this has undefined behavior.
|
||||
///
|
||||
/// If `ndarray` is unsized, this can only be called once.
|
||||
/// If `ndarray` is 0-sized, this can never be called.
|
||||
pub fn next<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) {
|
||||
call_nac3_nditer_next(generator, ctx, self.instance);
|
||||
}
|
||||
|
||||
/// Get pointer to the current element.
|
||||
#[must_use]
|
||||
pub fn get_pointer<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> PointerValue<'ctx> {
|
||||
let elem_ty = ctx.get_llvm_type(generator, self.ndarray.dtype);
|
||||
|
||||
let p = self.instance.get(generator, ctx, |f| f.element);
|
||||
ctx.builder
|
||||
.build_pointer_cast(p.value, elem_ty.ptr_type(AddressSpace::default()), "element")
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Get the value of the current element.
|
||||
#[must_use]
|
||||
pub fn get_scalar<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> AnyObject<'ctx> {
|
||||
let p = self.get_pointer(generator, ctx);
|
||||
let value = ctx.builder.build_load(p, "value").unwrap();
|
||||
AnyObject { ty: self.ndarray.dtype, value }
|
||||
}
|
||||
|
||||
/// Get the index of the current element if this ndarray were a flat ndarray.
|
||||
#[must_use]
|
||||
pub fn get_index<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> Instance<'ctx, Int<SizeT>> {
|
||||
self.instance.get(generator, ctx, |f| f.nth)
|
||||
}
|
||||
|
||||
/// Get the indices of the current element.
|
||||
#[must_use]
|
||||
pub fn get_indices(&self) -> Instance<'ctx, Ptr<Int<SizeT>>> {
|
||||
self.indices
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
/// Iterate through every element in the ndarray.
|
||||
///
|
||||
/// `body` has access to [`BreakContinueHooks`] to short-circuit and [`NDIterHandle`] to
|
||||
/// get properties of the current iteration (e.g., the current element, indices, etc.)
|
||||
pub fn foreach<'a, G, F>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, 'a>,
|
||||
body: F,
|
||||
) -> Result<(), String>
|
||||
where
|
||||
G: CodeGenerator + ?Sized,
|
||||
F: FnOnce(
|
||||
&mut G,
|
||||
&mut CodeGenContext<'ctx, 'a>,
|
||||
BreakContinueHooks<'ctx>,
|
||||
NDIterHandle<'ctx>,
|
||||
) -> Result<(), String>,
|
||||
{
|
||||
gen_for_callback(
|
||||
generator,
|
||||
ctx,
|
||||
Some("ndarray_foreach"),
|
||||
|generator, ctx| Ok(NDIterHandle::new(generator, ctx, *self)),
|
||||
|generator, ctx, nditer| Ok(nditer.has_element(generator, ctx).value),
|
||||
|generator, ctx, hooks, nditer| body(generator, ctx, hooks, nditer),
|
||||
|generator, ctx, nditer| {
|
||||
nditer.next(generator, ctx);
|
||||
Ok(())
|
||||
},
|
||||
)
|
||||
}
|
||||
}
|
105
nac3core/src/codegen/object/ndarray/shape_util.rs
Normal file
105
nac3core/src/codegen/object/ndarray/shape_util.rs
Normal file
@ -0,0 +1,105 @@
|
||||
use util::gen_for_model;
|
||||
|
||||
use crate::{
|
||||
codegen::{
|
||||
model::*,
|
||||
object::{any::AnyObject, list::ListObject, tuple::TupleObject},
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
typecheck::typedef::TypeEnum,
|
||||
};
|
||||
|
||||
/// Parse a NumPy-like "int sequence" input and return the int sequence as an array and its length.
|
||||
///
|
||||
/// * `sequence` - The `sequence` parameter.
|
||||
/// * `sequence_ty` - The typechecker type of `sequence`
|
||||
///
|
||||
/// The `sequence` argument type may only be one of the following:
|
||||
/// 1. A list of `int32`; e.g., `np.empty([600, 800, 3])`
|
||||
/// 2. A tuple of `int32`; e.g., `np.empty((600, 800, 3))`
|
||||
/// 3. A scalar `int32`; e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
|
||||
///
|
||||
/// All `int32` values will be sign-extended to `SizeT`.
|
||||
pub fn parse_numpy_int_sequence<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
input_sequence: AnyObject<'ctx>,
|
||||
) -> (Instance<'ctx, Int<SizeT>>, Instance<'ctx, Ptr<Int<SizeT>>>) {
|
||||
let zero = Int(SizeT).const_0(generator, ctx.ctx);
|
||||
let one = Int(SizeT).const_1(generator, ctx.ctx);
|
||||
|
||||
// The result `list` to return.
|
||||
match &*ctx.unifier.get_ty(input_sequence.ty) {
|
||||
TypeEnum::TObj { obj_id, .. }
|
||||
if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
|
||||
{
|
||||
// 1. A list of `int32`; e.g., `np.empty([600, 800, 3])`
|
||||
|
||||
// Check `input_sequence`
|
||||
let input_sequence = ListObject::from_object(generator, ctx, input_sequence);
|
||||
|
||||
let len = input_sequence.instance.get(generator, ctx, |f| f.len);
|
||||
let result = Int(SizeT).array_alloca(generator, ctx, len.value);
|
||||
|
||||
// Load all the `int32`s from the input_sequence, cast them to `SizeT`, and store them into `result`
|
||||
gen_for_model(generator, ctx, zero, len, one, |generator, ctx, _hooks, i| {
|
||||
// Load the i-th int32 in the input sequence
|
||||
let int = input_sequence
|
||||
.instance
|
||||
.get(generator, ctx, |f| f.items)
|
||||
.get_index(generator, ctx, i.value)
|
||||
.value
|
||||
.into_int_value();
|
||||
|
||||
// Cast to SizeT
|
||||
let int = Int(SizeT).s_extend_or_bit_cast(generator, ctx, int);
|
||||
|
||||
// Store
|
||||
result.set_index(ctx, i.value, int);
|
||||
|
||||
Ok(())
|
||||
})
|
||||
.unwrap();
|
||||
|
||||
(len, result)
|
||||
}
|
||||
TypeEnum::TTuple { .. } => {
|
||||
// 2. A tuple of ints; e.g., `np.empty((600, 800, 3))`
|
||||
|
||||
let input_sequence = TupleObject::from_object(ctx, input_sequence);
|
||||
|
||||
let len = input_sequence.len(generator, ctx);
|
||||
|
||||
let result = Int(SizeT).array_alloca(generator, ctx, len.value);
|
||||
|
||||
for i in 0..input_sequence.num_elements() {
|
||||
// Get the i-th element off of the tuple and load it into `result`.
|
||||
let int = input_sequence.index(ctx, i).value.into_int_value();
|
||||
let int = Int(SizeT).s_extend_or_bit_cast(generator, ctx, int);
|
||||
|
||||
result.set_index_const(ctx, i64::try_from(i).unwrap(), int);
|
||||
}
|
||||
|
||||
(len, result)
|
||||
}
|
||||
TypeEnum::TObj { obj_id, .. }
|
||||
if *obj_id == ctx.primitives.int32.obj_id(&ctx.unifier).unwrap() =>
|
||||
{
|
||||
// 3. A scalar int; e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
|
||||
let input_int = input_sequence.value.into_int_value();
|
||||
|
||||
let len = Int(SizeT).const_1(generator, ctx.ctx);
|
||||
let result = Int(SizeT).array_alloca(generator, ctx, len.value);
|
||||
let int = Int(SizeT).s_extend_or_bit_cast(generator, ctx, input_int);
|
||||
|
||||
// Storing into result[0]
|
||||
result.store(ctx, int);
|
||||
|
||||
(len, result)
|
||||
}
|
||||
_ => panic!(
|
||||
"encountered unknown sequence type: {}",
|
||||
ctx.unifier.stringify(input_sequence.ty)
|
||||
),
|
||||
}
|
||||
}
|
119
nac3core/src/codegen/object/ndarray/view.rs
Normal file
119
nac3core/src/codegen/object/ndarray/view.rs
Normal file
@ -0,0 +1,119 @@
|
||||
use crate::codegen::{
|
||||
irrt::{call_nac3_ndarray_reshape_resolve_and_check_new_shape, call_nac3_ndarray_transpose},
|
||||
model::*,
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
use super::{indexing::RustNDIndex, NDArrayObject};
|
||||
|
||||
impl<'ctx> NDArrayObject<'ctx> {
|
||||
/// Make sure the ndarray is at least `ndmin`-dimensional.
|
||||
///
|
||||
/// If this ndarray's `ndims` is less than `ndmin`, a view is created on this with 1s prepended to the shape.
|
||||
/// If this ndarray's `ndims` is not less than `ndmin`, this function does nothing and return this ndarray.
|
||||
#[must_use]
|
||||
pub fn atleast_nd<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndmin: u64,
|
||||
) -> Self {
|
||||
if self.ndims < ndmin {
|
||||
// Extend the dimensions with np.newaxis.
|
||||
let mut indices = vec![];
|
||||
for _ in self.ndims..ndmin {
|
||||
indices.push(RustNDIndex::NewAxis);
|
||||
}
|
||||
indices.push(RustNDIndex::Ellipsis);
|
||||
self.index(generator, ctx, &indices)
|
||||
} else {
|
||||
*self
|
||||
}
|
||||
}
|
||||
|
||||
/// Create a reshaped view on this ndarray like `np.reshape()`.
|
||||
///
|
||||
/// If there is a `-1` in `new_shape`, it will be resolved; `new_shape` would **NOT** be modified as a result.
|
||||
///
|
||||
/// If reshape without copying is impossible, this function will allocate a new ndarray and copy contents.
|
||||
///
|
||||
/// * `new_ndims` - The number of dimensions of `new_shape` as a [`Type`].
|
||||
/// * `new_shape` - The target shape to do `np.reshape()`.
|
||||
#[must_use]
|
||||
pub fn reshape_or_copy<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
new_ndims: u64,
|
||||
new_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
|
||||
) -> Self {
|
||||
// TODO: The current criterion for whether to do a full copy or not is by checking `is_c_contiguous`,
|
||||
// but this is not optimal - there are cases when the ndarray is not contiguous but could be reshaped
|
||||
// without copying data. Look into how numpy does it.
|
||||
|
||||
let current_bb = ctx.builder.get_insert_block().unwrap();
|
||||
let then_bb = ctx.ctx.insert_basic_block_after(current_bb, "then_bb");
|
||||
let else_bb = ctx.ctx.insert_basic_block_after(then_bb, "else_bb");
|
||||
let end_bb = ctx.ctx.insert_basic_block_after(else_bb, "end_bb");
|
||||
|
||||
let dst_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, new_ndims);
|
||||
dst_ndarray.copy_shape_from_array(generator, ctx, new_shape);
|
||||
|
||||
// Reolsve negative indices
|
||||
let size = self.size(generator, ctx);
|
||||
let dst_ndims = dst_ndarray.ndims_llvm(generator, ctx.ctx);
|
||||
let dst_shape = dst_ndarray.instance.get(generator, ctx, |f| f.shape);
|
||||
call_nac3_ndarray_reshape_resolve_and_check_new_shape(
|
||||
generator, ctx, size, dst_ndims, dst_shape,
|
||||
);
|
||||
|
||||
let is_c_contiguous = self.is_c_contiguous(generator, ctx);
|
||||
ctx.builder.build_conditional_branch(is_c_contiguous.value, then_bb, else_bb).unwrap();
|
||||
|
||||
// Inserting into then_bb: reshape is possible without copying
|
||||
ctx.builder.position_at_end(then_bb);
|
||||
dst_ndarray.set_strides_contiguous(generator, ctx);
|
||||
dst_ndarray.instance.set(ctx, |f| f.data, self.instance.get(generator, ctx, |f| f.data));
|
||||
ctx.builder.build_unconditional_branch(end_bb).unwrap();
|
||||
|
||||
// Inserting into else_bb: reshape is impossible without copying
|
||||
ctx.builder.position_at_end(else_bb);
|
||||
dst_ndarray.create_data(generator, ctx);
|
||||
dst_ndarray.copy_data_from(generator, ctx, *self);
|
||||
ctx.builder.build_unconditional_branch(end_bb).unwrap();
|
||||
|
||||
// Reposition for continuation
|
||||
ctx.builder.position_at_end(end_bb);
|
||||
|
||||
dst_ndarray
|
||||
}
|
||||
|
||||
/// Create a transposed view on this ndarray like `np.transpose(<ndarray>, <axes> = None)`.
|
||||
/// * `axes` - If specified, should be an array of the permutation (negative indices are **allowed**).
|
||||
#[must_use]
|
||||
pub fn transpose<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
axes: Option<Instance<'ctx, Ptr<Int<SizeT>>>>,
|
||||
) -> Self {
|
||||
// Define models
|
||||
let transposed_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, self.ndims);
|
||||
|
||||
let num_axes = self.ndims_llvm(generator, ctx.ctx);
|
||||
|
||||
// `axes = nullptr` if `axes` is unspecified.
|
||||
let axes = axes.unwrap_or_else(|| Ptr(Int(SizeT)).nullptr(generator, ctx.ctx));
|
||||
|
||||
call_nac3_ndarray_transpose(
|
||||
generator,
|
||||
ctx,
|
||||
self.instance,
|
||||
transposed_ndarray.instance,
|
||||
num_axes,
|
||||
axes,
|
||||
);
|
||||
|
||||
transposed_ndarray
|
||||
}
|
||||
}
|
99
nac3core/src/codegen/object/tuple.rs
Normal file
99
nac3core/src/codegen/object/tuple.rs
Normal file
@ -0,0 +1,99 @@
|
||||
use inkwell::values::StructValue;
|
||||
use itertools::Itertools;
|
||||
|
||||
use crate::{
|
||||
codegen::{model::*, CodeGenContext, CodeGenerator},
|
||||
typecheck::typedef::{Type, TypeEnum},
|
||||
};
|
||||
|
||||
use super::any::AnyObject;
|
||||
|
||||
/// A NAC3 tuple object.
|
||||
///
|
||||
/// NOTE: This struct has no copy trait.
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct TupleObject<'ctx> {
|
||||
/// The type of the tuple.
|
||||
pub tys: Vec<Type>,
|
||||
/// The underlying LLVM struct value of this tuple.
|
||||
pub value: StructValue<'ctx>,
|
||||
}
|
||||
|
||||
impl<'ctx> TupleObject<'ctx> {
|
||||
pub fn from_object(ctx: &mut CodeGenContext<'ctx, '_>, object: AnyObject<'ctx>) -> Self {
|
||||
// TODO: Keep `is_vararg_ctx` from TTuple?
|
||||
|
||||
// Sanity check on object type.
|
||||
let TypeEnum::TTuple { ty: tys, .. } = &*ctx.unifier.get_ty(object.ty) else {
|
||||
panic!(
|
||||
"Expected type to be a TypeEnum::TTuple, got {}",
|
||||
ctx.unifier.stringify(object.ty)
|
||||
);
|
||||
};
|
||||
|
||||
// Check number of fields
|
||||
let value = object.value.into_struct_value();
|
||||
let value_num_fields = value.get_type().count_fields() as usize;
|
||||
assert!(
|
||||
value_num_fields == tys.len(),
|
||||
"Tuple type has {} item(s), but the LLVM struct value has {} field(s)",
|
||||
tys.len(),
|
||||
value_num_fields
|
||||
);
|
||||
|
||||
TupleObject { tys: tys.clone(), value }
|
||||
}
|
||||
|
||||
/// Convenience function. Create a [`TupleObject`] from an iterator of objects.
|
||||
pub fn from_objects<I, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
objects: I,
|
||||
) -> Self
|
||||
where
|
||||
I: IntoIterator<Item = AnyObject<'ctx>>,
|
||||
{
|
||||
let (values, tys): (Vec<_>, Vec<_>) =
|
||||
objects.into_iter().map(|object| (object.value, object.ty)).unzip();
|
||||
|
||||
let llvm_tys = tys.iter().map(|ty| ctx.get_llvm_type(generator, *ty)).collect_vec();
|
||||
let llvm_tuple_ty = ctx.ctx.struct_type(&llvm_tys, false);
|
||||
|
||||
let pllvm_tuple = ctx.builder.build_alloca(llvm_tuple_ty, "tuple").unwrap();
|
||||
for (i, val) in values.into_iter().enumerate() {
|
||||
let pval = ctx.builder.build_struct_gep(pllvm_tuple, i as u32, "value").unwrap();
|
||||
ctx.builder.build_store(pval, val).unwrap();
|
||||
}
|
||||
|
||||
let value = ctx.builder.build_load(pllvm_tuple, "").unwrap().into_struct_value();
|
||||
TupleObject { tys, value }
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn num_elements(&self) -> usize {
|
||||
self.tys.len()
|
||||
}
|
||||
|
||||
/// Get the `len()` of this tuple.
|
||||
#[must_use]
|
||||
pub fn len<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> Instance<'ctx, Int<SizeT>> {
|
||||
Int(SizeT).const_int(generator, ctx.ctx, self.num_elements() as u64, false)
|
||||
}
|
||||
|
||||
/// Get the `i`-th (0-based) object in this tuple.
|
||||
pub fn index(&self, ctx: &mut CodeGenContext<'ctx, '_>, i: usize) -> AnyObject<'ctx> {
|
||||
assert!(
|
||||
i < self.num_elements(),
|
||||
"Tuple object with length {} have index {i}",
|
||||
self.num_elements()
|
||||
);
|
||||
|
||||
let value = ctx.builder.build_extract_value(self.value, i as u32, "tuple[{i}]").unwrap();
|
||||
let ty = self.tys[i];
|
||||
AnyObject { ty, value }
|
||||
}
|
||||
}
|
1
nac3core/src/codegen/object/utils/mod.rs
Normal file
1
nac3core/src/codegen/object/utils/mod.rs
Normal file
@ -0,0 +1 @@
|
||||
pub mod slice;
|
125
nac3core/src/codegen/object/utils/slice.rs
Normal file
125
nac3core/src/codegen/object/utils/slice.rs
Normal file
@ -0,0 +1,125 @@
|
||||
use crate::codegen::{model::*, CodeGenContext, CodeGenerator};
|
||||
|
||||
/// Fields of [`Slice`]
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct SliceFields<'ctx, F: FieldTraversal<'ctx>, N: IntKind<'ctx>> {
|
||||
pub start_defined: F::Output<Int<Bool>>,
|
||||
pub start: F::Output<Int<N>>,
|
||||
pub stop_defined: F::Output<Int<Bool>>,
|
||||
pub stop: F::Output<Int<N>>,
|
||||
pub step_defined: F::Output<Int<Bool>>,
|
||||
pub step: F::Output<Int<N>>,
|
||||
}
|
||||
|
||||
/// An IRRT representation of an (unresolved) slice.
|
||||
#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
|
||||
pub struct Slice<N>(pub N);
|
||||
|
||||
impl<'ctx, N: IntKind<'ctx>> StructKind<'ctx> for Slice<N> {
|
||||
type Fields<F: FieldTraversal<'ctx>> = SliceFields<'ctx, F, N>;
|
||||
|
||||
fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
|
||||
Self::Fields {
|
||||
start_defined: traversal.add_auto("start_defined"),
|
||||
start: traversal.add("start", Int(self.0)),
|
||||
stop_defined: traversal.add_auto("stop_defined"),
|
||||
stop: traversal.add("stop", Int(self.0)),
|
||||
step_defined: traversal.add_auto("step_defined"),
|
||||
step: traversal.add("step", Int(self.0)),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// A Rust structure that has [`Slice`] utilities and looks like a [`Slice`] but
|
||||
/// `start`, `stop` and `step` are held by LLVM registers only and possibly
|
||||
/// [`Option::None`] if unspecified.
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct RustSlice<'ctx, N: IntKind<'ctx>> {
|
||||
// It is possible that `start`, `stop`, and `step` are all `None`.
|
||||
// We need to know the `int_kind` even when that is the case.
|
||||
pub int_kind: N,
|
||||
pub start: Option<Instance<'ctx, Int<N>>>,
|
||||
pub stop: Option<Instance<'ctx, Int<N>>>,
|
||||
pub step: Option<Instance<'ctx, Int<N>>>,
|
||||
}
|
||||
|
||||
impl<'ctx, N: IntKind<'ctx>> RustSlice<'ctx, N> {
|
||||
/// Write the contents to an LLVM [`Slice`].
|
||||
pub fn write_to_slice<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
dst_slice_ptr: Instance<'ctx, Ptr<Struct<Slice<N>>>>,
|
||||
) {
|
||||
let false_ = Int(Bool).const_false(generator, ctx.ctx);
|
||||
let true_ = Int(Bool).const_true(generator, ctx.ctx);
|
||||
|
||||
match self.start {
|
||||
Some(start) => {
|
||||
dst_slice_ptr.gep(ctx, |f| f.start_defined).store(ctx, true_);
|
||||
dst_slice_ptr.gep(ctx, |f| f.start).store(ctx, start);
|
||||
}
|
||||
None => dst_slice_ptr.gep(ctx, |f| f.start_defined).store(ctx, false_),
|
||||
}
|
||||
|
||||
match self.stop {
|
||||
Some(stop) => {
|
||||
dst_slice_ptr.gep(ctx, |f| f.stop_defined).store(ctx, true_);
|
||||
dst_slice_ptr.gep(ctx, |f| f.stop).store(ctx, stop);
|
||||
}
|
||||
None => dst_slice_ptr.gep(ctx, |f| f.stop_defined).store(ctx, false_),
|
||||
}
|
||||
|
||||
match self.step {
|
||||
Some(step) => {
|
||||
dst_slice_ptr.gep(ctx, |f| f.step_defined).store(ctx, true_);
|
||||
dst_slice_ptr.gep(ctx, |f| f.step).store(ctx, step);
|
||||
}
|
||||
None => dst_slice_ptr.gep(ctx, |f| f.step_defined).store(ctx, false_),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub mod util {
|
||||
use nac3parser::ast::Expr;
|
||||
|
||||
use crate::{
|
||||
codegen::{model::*, CodeGenContext, CodeGenerator},
|
||||
typecheck::typedef::Type,
|
||||
};
|
||||
|
||||
use super::RustSlice;
|
||||
|
||||
/// Generate LLVM IR for an [`ExprKind::Slice`] and convert it into a [`RustSlice`].
|
||||
#[allow(clippy::type_complexity)]
|
||||
pub fn gen_slice<'ctx, G: CodeGenerator>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
lower: &Option<Box<Expr<Option<Type>>>>,
|
||||
upper: &Option<Box<Expr<Option<Type>>>>,
|
||||
step: &Option<Box<Expr<Option<Type>>>>,
|
||||
) -> Result<RustSlice<'ctx, Int32>, String> {
|
||||
let mut help = |value_expr: &Option<Box<Expr<Option<Type>>>>| -> Result<_, String> {
|
||||
Ok(match value_expr {
|
||||
None => None,
|
||||
Some(value_expr) => {
|
||||
let value_expr = generator
|
||||
.gen_expr(ctx, value_expr)?
|
||||
.unwrap()
|
||||
.to_basic_value_enum(ctx, generator, ctx.primitives.int32)?;
|
||||
|
||||
let value_expr =
|
||||
Int(Int32).check_value(generator, ctx.ctx, value_expr).unwrap();
|
||||
|
||||
Some(value_expr)
|
||||
}
|
||||
})
|
||||
};
|
||||
|
||||
let start = help(lower)?;
|
||||
let stop = help(upper)?;
|
||||
let step = help(step)?;
|
||||
|
||||
Ok(RustSlice { int_kind: Int32, start, stop, step })
|
||||
}
|
||||
}
|
@ -1,22 +1,15 @@
|
||||
use inkwell::{
|
||||
attributes::{Attribute, AttributeLoc},
|
||||
basic_block::BasicBlock,
|
||||
types::{BasicType, BasicTypeEnum},
|
||||
values::{BasicValue, BasicValueEnum, FunctionValue, IntValue, PointerValue},
|
||||
IntPredicate,
|
||||
};
|
||||
use itertools::{izip, Itertools};
|
||||
|
||||
use nac3parser::ast::{
|
||||
Constant, ExcepthandlerKind, Expr, ExprKind, Location, Stmt, StmtKind, StrRef,
|
||||
};
|
||||
|
||||
use super::{
|
||||
classes::{ArrayLikeIndexer, ArraySliceValue, ListValue, RangeValue},
|
||||
expr::{destructure_range, gen_binop_expr},
|
||||
gen_in_range_check,
|
||||
irrt::{handle_slice_indices, list_slice_assignment},
|
||||
macros::codegen_unreachable,
|
||||
values::{ArrayLikeIndexer, ArraySliceValue, ListValue, RangeValue},
|
||||
object::{
|
||||
any::AnyObject,
|
||||
ndarray::{
|
||||
indexing::util::gen_ndarray_subscript_ndindices, NDArrayObject, ScalarOrNDArray,
|
||||
},
|
||||
},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
use crate::{
|
||||
@ -27,6 +20,17 @@ use crate::{
|
||||
typedef::{iter_type_vars, FunSignature, Type, TypeEnum},
|
||||
},
|
||||
};
|
||||
use inkwell::{
|
||||
attributes::{Attribute, AttributeLoc},
|
||||
basic_block::BasicBlock,
|
||||
types::{BasicType, BasicTypeEnum},
|
||||
values::{BasicValue, BasicValueEnum, FunctionValue, IntValue, PointerValue},
|
||||
IntPredicate,
|
||||
};
|
||||
use itertools::{izip, Itertools};
|
||||
use nac3parser::ast::{
|
||||
Constant, ExcepthandlerKind, Expr, ExprKind, Location, Stmt, StmtKind, StrRef,
|
||||
};
|
||||
|
||||
/// See [`CodeGenerator::gen_var_alloc`].
|
||||
pub fn gen_var<'ctx>(
|
||||
@ -310,7 +314,7 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
|
||||
.unwrap()
|
||||
.to_basic_value_enum(ctx, generator, target_ty)?
|
||||
.into_pointer_value();
|
||||
let target = ListValue::from_pointer_value(target, llvm_usize, None);
|
||||
let target = ListValue::from_ptr_val(target, llvm_usize, None);
|
||||
|
||||
if let ExprKind::Slice { .. } = &key.node {
|
||||
// Handle assigning to a slice
|
||||
@ -331,7 +335,7 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
|
||||
|
||||
let value =
|
||||
value.to_basic_value_enum(ctx, generator, value_ty)?.into_pointer_value();
|
||||
let value = ListValue::from_pointer_value(value, llvm_usize, None);
|
||||
let value = ListValue::from_ptr_val(value, llvm_usize, None);
|
||||
|
||||
let target_item_ty = ctx.get_llvm_type(generator, target_item_ty);
|
||||
let Some(src_ind) = handle_slice_indices(
|
||||
@ -411,7 +415,47 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
|
||||
if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
|
||||
{
|
||||
// Handle NDArray item assignment
|
||||
todo!("ndarray subscript assignment is not yet implemented");
|
||||
// Process target
|
||||
let target = generator
|
||||
.gen_expr(ctx, target)?
|
||||
.unwrap()
|
||||
.to_basic_value_enum(ctx, generator, target_ty)?;
|
||||
let target = AnyObject { value: target, ty: target_ty };
|
||||
|
||||
// Process key
|
||||
let key = gen_ndarray_subscript_ndindices(generator, ctx, key)?;
|
||||
|
||||
// Process value
|
||||
let value = value.to_basic_value_enum(ctx, generator, value_ty)?;
|
||||
let value = AnyObject { value, ty: value_ty };
|
||||
|
||||
/*
|
||||
Reference code:
|
||||
```python
|
||||
target = target[key]
|
||||
value = np.asarray(value)
|
||||
|
||||
shape = np.broadcast_shape((target, value))
|
||||
|
||||
target = np.broadcast_to(target, shape)
|
||||
value = np.broadcast_to(value, shape)
|
||||
|
||||
...and finally copy 1-1 from value to target.
|
||||
```
|
||||
*/
|
||||
|
||||
let target = NDArrayObject::from_object(generator, ctx, target);
|
||||
let target = target.index(generator, ctx, &key);
|
||||
|
||||
let value =
|
||||
ScalarOrNDArray::split_object(generator, ctx, value).to_ndarray(generator, ctx);
|
||||
|
||||
let broadcast_result = NDArrayObject::broadcast(generator, ctx, &[target, value]);
|
||||
|
||||
let target = broadcast_result.ndarrays[0];
|
||||
let value = broadcast_result.ndarrays[1];
|
||||
|
||||
target.copy_data_from(generator, ctx, value);
|
||||
}
|
||||
_ => {
|
||||
panic!("encountered unknown target type: {}", ctx.unifier.stringify(target_ty));
|
||||
@ -463,8 +507,7 @@ pub fn gen_for<G: CodeGenerator>(
|
||||
TypeEnum::TObj { obj_id, .. }
|
||||
if *obj_id == ctx.primitives.range.obj_id(&ctx.unifier).unwrap() =>
|
||||
{
|
||||
let iter_val =
|
||||
RangeValue::from_pointer_value(iter_val.into_pointer_value(), Some("range"));
|
||||
let iter_val = RangeValue::from_ptr_val(iter_val.into_pointer_value(), Some("range"));
|
||||
// Internal variable for loop; Cannot be assigned
|
||||
let i = generator.gen_var_alloc(ctx, int32.into(), Some("for.i.addr"))?;
|
||||
// Variable declared in "target" expression of the loop; Can be reassigned *or* shadowed
|
||||
@ -1829,37 +1872,6 @@ pub fn gen_stmt<G: CodeGenerator>(
|
||||
stmt.location,
|
||||
);
|
||||
}
|
||||
StmtKind::Global { names, .. } => {
|
||||
let registered_globals = ctx
|
||||
.top_level
|
||||
.definitions
|
||||
.read()
|
||||
.iter()
|
||||
.filter_map(|def| {
|
||||
if let TopLevelDef::Variable { simple_name, ty, .. } = &*def.read() {
|
||||
Some((*simple_name, *ty))
|
||||
} else {
|
||||
None
|
||||
}
|
||||
})
|
||||
.collect_vec();
|
||||
|
||||
for id in names {
|
||||
let Some((_, ty)) = registered_globals.iter().find(|(name, _)| name == id) else {
|
||||
return Err(format!("{id} is not a global at {}", stmt.location));
|
||||
};
|
||||
|
||||
let resolver = ctx.resolver.clone();
|
||||
let ptr = resolver
|
||||
.get_symbol_value(*id, ctx, generator)
|
||||
.map(|val| val.to_basic_value_enum(ctx, generator, *ty))
|
||||
.transpose()?
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap();
|
||||
|
||||
ctx.var_assignment.insert(*id, (ptr, None, 0));
|
||||
}
|
||||
}
|
||||
_ => unimplemented!(),
|
||||
};
|
||||
Ok(())
|
||||
|
@ -1,37 +1,34 @@
|
||||
use std::{
|
||||
collections::{HashMap, HashSet},
|
||||
sync::Arc,
|
||||
};
|
||||
|
||||
use indexmap::IndexMap;
|
||||
use indoc::indoc;
|
||||
use inkwell::{
|
||||
targets::{InitializationConfig, Target},
|
||||
OptimizationLevel,
|
||||
};
|
||||
use nac3parser::{
|
||||
ast::{fold::Fold, FileName, StrRef},
|
||||
parser::parse_program,
|
||||
};
|
||||
use parking_lot::RwLock;
|
||||
|
||||
use super::{
|
||||
concrete_type::ConcreteTypeStore,
|
||||
types::{ndarray::NDArrayType, ListType, ProxyType, RangeType},
|
||||
CodeGenContext, CodeGenLLVMOptions, CodeGenTargetMachineOptions, CodeGenTask, CodeGenerator,
|
||||
DefaultCodeGenerator, WithCall, WorkerRegistry,
|
||||
};
|
||||
use crate::{
|
||||
codegen::{
|
||||
classes::{ListType, NDArrayType, ProxyType, RangeType},
|
||||
concrete_type::ConcreteTypeStore,
|
||||
CodeGenContext, CodeGenLLVMOptions, CodeGenTargetMachineOptions, CodeGenTask,
|
||||
CodeGenerator, DefaultCodeGenerator, WithCall, WorkerRegistry,
|
||||
},
|
||||
symbol_resolver::{SymbolResolver, ValueEnum},
|
||||
toplevel::{
|
||||
composer::{ComposerConfig, TopLevelComposer},
|
||||
DefinitionId, FunInstance, TopLevelContext, TopLevelDef,
|
||||
},
|
||||
typecheck::{
|
||||
type_inferencer::{FunctionData, IdentifierInfo, Inferencer, PrimitiveStore},
|
||||
type_inferencer::{FunctionData, Inferencer, PrimitiveStore},
|
||||
typedef::{FunSignature, FuncArg, Type, TypeEnum, Unifier, VarMap},
|
||||
},
|
||||
};
|
||||
use indexmap::IndexMap;
|
||||
use indoc::indoc;
|
||||
use inkwell::{
|
||||
targets::{InitializationConfig, Target},
|
||||
OptimizationLevel,
|
||||
};
|
||||
use nac3parser::ast::FileName;
|
||||
use nac3parser::{
|
||||
ast::{fold::Fold, StrRef},
|
||||
parser::parse_program,
|
||||
};
|
||||
use parking_lot::RwLock;
|
||||
use std::collections::{HashMap, HashSet};
|
||||
use std::sync::Arc;
|
||||
|
||||
struct Resolver {
|
||||
id_to_type: HashMap<StrRef, Type>,
|
||||
@ -67,7 +64,6 @@ impl SymbolResolver for Resolver {
|
||||
&self,
|
||||
_: StrRef,
|
||||
_: &mut CodeGenContext<'ctx, '_>,
|
||||
_: &mut dyn CodeGenerator,
|
||||
) -> Option<ValueEnum<'ctx>> {
|
||||
unimplemented!()
|
||||
}
|
||||
@ -142,8 +138,7 @@ fn test_primitives() {
|
||||
};
|
||||
let mut virtual_checks = Vec::new();
|
||||
let mut calls = HashMap::new();
|
||||
let mut identifiers: HashMap<_, _> =
|
||||
["a".into(), "b".into()].map(|id| (id, IdentifierInfo::default())).into();
|
||||
let mut identifiers: HashSet<_> = ["a".into(), "b".into()].into();
|
||||
let mut inferencer = Inferencer {
|
||||
top_level: &top_level,
|
||||
function_data: &mut function_data,
|
||||
@ -322,8 +317,7 @@ fn test_simple_call() {
|
||||
};
|
||||
let mut virtual_checks = Vec::new();
|
||||
let mut calls = HashMap::new();
|
||||
let mut identifiers: HashMap<_, _> =
|
||||
["a".into(), "foo".into()].map(|id| (id, IdentifierInfo::default())).into();
|
||||
let mut identifiers: HashSet<_> = ["a".into(), "foo".into()].into();
|
||||
let mut inferencer = Inferencer {
|
||||
top_level: &top_level,
|
||||
function_data: &mut function_data,
|
||||
@ -452,7 +446,7 @@ fn test_classes_list_type_new() {
|
||||
let llvm_usize = generator.get_size_type(&ctx);
|
||||
|
||||
let llvm_list = ListType::new(&generator, &ctx, llvm_i32.into());
|
||||
assert!(ListType::is_representable(llvm_list.as_base_type(), llvm_usize).is_ok());
|
||||
assert!(ListType::is_type(llvm_list.as_base_type(), llvm_usize).is_ok());
|
||||
}
|
||||
|
||||
#[test]
|
||||
@ -460,7 +454,7 @@ fn test_classes_range_type_new() {
|
||||
let ctx = inkwell::context::Context::create();
|
||||
|
||||
let llvm_range = RangeType::new(&ctx);
|
||||
assert!(RangeType::is_representable(llvm_range.as_base_type()).is_ok());
|
||||
assert!(RangeType::is_type(llvm_range.as_base_type()).is_ok());
|
||||
}
|
||||
|
||||
#[test]
|
||||
@ -471,6 +465,6 @@ fn test_classes_ndarray_type_new() {
|
||||
let llvm_i32 = ctx.i32_type();
|
||||
let llvm_usize = generator.get_size_type(&ctx);
|
||||
|
||||
let llvm_ndarray = NDArrayType::new(&generator, &ctx, llvm_i32.into(), None);
|
||||
assert!(NDArrayType::is_representable(llvm_ndarray.as_base_type(), llvm_usize).is_ok());
|
||||
let llvm_ndarray = NDArrayType::new(&generator, &ctx, llvm_i32.into());
|
||||
assert!(NDArrayType::is_type(llvm_ndarray.as_base_type(), llvm_usize).is_ok());
|
||||
}
|
||||
|
@ -1,206 +0,0 @@
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
|
||||
values::IntValue,
|
||||
AddressSpace,
|
||||
};
|
||||
|
||||
use super::ProxyType;
|
||||
use crate::codegen::{
|
||||
values::{ArraySliceValue, ListValue, ProxyValue},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
/// Proxy type for a `list` type in LLVM.
|
||||
#[derive(Debug, PartialEq, Eq, Clone, Copy)]
|
||||
pub struct ListType<'ctx> {
|
||||
ty: PointerType<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
}
|
||||
|
||||
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 llvm_list_ty = llvm_ty.get_element_type();
|
||||
let AnyTypeEnum::StructType(llvm_list_ty) = llvm_list_ty else {
|
||||
return Err(format!("Expected struct type for `list` type, got {llvm_list_ty}"));
|
||||
};
|
||||
if llvm_list_ty.count_fields() != 2 {
|
||||
return Err(format!(
|
||||
"Expected 2 fields in `list`, got {}",
|
||||
llvm_list_ty.count_fields()
|
||||
));
|
||||
}
|
||||
|
||||
let list_size_ty = llvm_list_ty.get_field_type_at_index(0).unwrap();
|
||||
let Ok(_) = PointerType::try_from(list_size_ty) else {
|
||||
return Err(format!("Expected pointer type for `list.0`, got {list_size_ty}"));
|
||||
};
|
||||
|
||||
let list_data_ty = llvm_list_ty.get_field_type_at_index(1).unwrap();
|
||||
let Ok(list_data_ty) = IntType::try_from(list_data_ty) else {
|
||||
return Err(format!("Expected int type for `list.1`, got {list_data_ty}"));
|
||||
};
|
||||
if list_data_ty.get_bit_width() != llvm_usize.get_bit_width() {
|
||||
return Err(format!(
|
||||
"Expected {}-bit int type for `list.1`, got {}-bit int",
|
||||
llvm_usize.get_bit_width(),
|
||||
list_data_ty.get_bit_width()
|
||||
));
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// Creates an LLVM type corresponding to the expected structure of a `List`.
|
||||
#[must_use]
|
||||
fn llvm_type(
|
||||
ctx: &'ctx Context,
|
||||
element_type: BasicTypeEnum<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
) -> PointerType<'ctx> {
|
||||
// struct List { data: T*, size: size_t }
|
||||
let field_tys = [element_type.ptr_type(AddressSpace::default()).into(), llvm_usize.into()];
|
||||
|
||||
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, element_type, llvm_usize);
|
||||
|
||||
ListType::from_type(llvm_list, 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());
|
||||
|
||||
ListType { ty: ptr_ty, llvm_usize }
|
||||
}
|
||||
|
||||
/// Returns the type of the `size` field of this `list` type.
|
||||
#[must_use]
|
||||
pub fn size_type(&self) -> IntType<'ctx> {
|
||||
self.as_base_type()
|
||||
.get_element_type()
|
||||
.into_struct_type()
|
||||
.get_field_type_at_index(1)
|
||||
.map(BasicTypeEnum::into_int_type)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Returns the element type of this `list` type.
|
||||
#[must_use]
|
||||
pub fn element_type(&self) -> AnyTypeEnum<'ctx> {
|
||||
self.as_base_type()
|
||||
.get_element_type()
|
||||
.into_struct_type()
|
||||
.get_field_type_at_index(0)
|
||||
.map(BasicTypeEnum::into_pointer_type)
|
||||
.map(PointerType::get_element_type)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Allocates an instance of [`ListValue`] as if by calling `alloca` on the base type.
|
||||
#[must_use]
|
||||
pub fn alloca<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(generator, ctx, name),
|
||||
self.llvm_usize,
|
||||
name,
|
||||
)
|
||||
}
|
||||
|
||||
/// 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 raw_alloca<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> <Self::Value as ProxyValue<'ctx>>::Base {
|
||||
generator
|
||||
.gen_var_alloc(
|
||||
ctx,
|
||||
self.as_base_type().get_element_type().into_struct_type().into(),
|
||||
name,
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
fn array_alloca<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.as_base_type().get_element_type().into_struct_type().into(),
|
||||
size,
|
||||
name,
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
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()
|
||||
}
|
||||
}
|
@ -1,76 +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};
|
||||
|
||||
use super::{
|
||||
values::{ArraySliceValue, ProxyValue},
|
||||
{CodeGenContext, CodeGenerator},
|
||||
};
|
||||
pub use list::*;
|
||||
pub use range::*;
|
||||
|
||||
mod list;
|
||||
pub mod ndarray;
|
||||
mod range;
|
||||
pub mod structure;
|
||||
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>;
|
||||
|
||||
/// Creates a new value of this type, returning the LLVM instance of this value.
|
||||
fn raw_alloca<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> <Self::Value as ProxyValue<'ctx>>::Base;
|
||||
|
||||
/// Creates a new array value of this type, returning an [`ArraySliceValue`] encapsulating the
|
||||
/// resulting array.
|
||||
fn array_alloca<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
size: IntValue<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> ArraySliceValue<'ctx>;
|
||||
|
||||
/// Returns the [base type][Self::Base] of this proxy.
|
||||
fn as_base_type(&self) -> Self::Base;
|
||||
}
|
@ -1,257 +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, ArraySliceValue, 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 ContiguousNDArrayFields<'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> ContiguousNDArrayFields<'ctx> {
|
||||
#[must_use]
|
||||
pub fn new_typed(item: BasicTypeEnum<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
|
||||
let mut counter = FieldIndexCounter::default();
|
||||
|
||||
ContiguousNDArrayFields {
|
||||
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 = ContiguousNDArrayFields::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>,
|
||||
) -> ContiguousNDArrayFields<'ctx> {
|
||||
ContiguousNDArrayFields::new_typed(item, llvm_usize)
|
||||
}
|
||||
|
||||
/// See [`NDArrayType::fields`].
|
||||
// TODO: Move this into e.g. StructProxyType
|
||||
#[must_use]
|
||||
pub fn get_fields(&self) -> ContiguousNDArrayFields<'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.
|
||||
#[must_use]
|
||||
pub fn alloca<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(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 raw_alloca<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> <Self::Value as ProxyValue<'ctx>>::Base {
|
||||
generator
|
||||
.gen_var_alloc(
|
||||
ctx,
|
||||
self.as_base_type().get_element_type().into_struct_type().into(),
|
||||
name,
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
fn array_alloca<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.as_base_type().get_element_type().into_struct_type().into(),
|
||||
size,
|
||||
name,
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
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()
|
||||
}
|
||||
}
|
@ -1,215 +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 }
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn alloca<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(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(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 raw_alloca<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> <Self::Value as ProxyValue<'ctx>>::Base {
|
||||
generator
|
||||
.gen_var_alloc(
|
||||
ctx,
|
||||
self.as_base_type().get_element_type().into_struct_type().into(),
|
||||
name,
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
fn array_alloca<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.as_base_type().get_element_type().into_struct_type().into(),
|
||||
size,
|
||||
name,
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
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()
|
||||
}
|
||||
}
|
@ -1,469 +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, ArraySliceValue, ProxyValue, TypedArrayLikeMutator},
|
||||
{CodeGenContext, CodeGenerator},
|
||||
},
|
||||
toplevel::{helper::extract_ndims, numpy::unpack_ndarray_var_tys},
|
||||
typecheck::typedef::Type,
|
||||
};
|
||||
pub use contiguous::*;
|
||||
pub use indexing::*;
|
||||
pub use nditer::*;
|
||||
|
||||
mod contiguous;
|
||||
mod indexing;
|
||||
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: Option<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: Option<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`] 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: Some(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: Some(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: Option<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) -> Option<u64> {
|
||||
self.ndims
|
||||
}
|
||||
|
||||
/// Allocates an instance of [`NDArrayValue`] as if by calling `alloca` on the base type.
|
||||
#[must_use]
|
||||
pub fn alloca<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(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(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 {
|
||||
assert!(self.ndims.is_some(), "NDArrayType::construct can only be called on an instance with compile-time known ndims (self.ndims = Some(ndims))");
|
||||
|
||||
let Some(ndims) = self.ndims.map(|ndims| self.llvm_usize.const_int(ndims, false)) else {
|
||||
unreachable!()
|
||||
};
|
||||
|
||||
self.construct_impl(generator, ctx, ndims, name)
|
||||
}
|
||||
|
||||
/// Allocate an [`NDArrayValue`] on the stack given its `ndims` and `dtype`.
|
||||
///
|
||||
/// `shape` and `strides` will be automatically allocated onto the stack.
|
||||
///
|
||||
/// The returned ndarray's content will be:
|
||||
/// - `data`: uninitialized.
|
||||
/// - `itemsize`: set to the size of `dtype`.
|
||||
/// - `ndims`: set to the value of `ndims`.
|
||||
/// - `shape`: allocated with an array of length `ndims` with uninitialized values.
|
||||
/// - `strides`: allocated with an array of length `ndims` with uninitialized values.
|
||||
#[deprecated = "Prefer construct_uninitialized or construct_*_shape."]
|
||||
#[must_use]
|
||||
pub fn construct_dyn_ndims<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndims: IntValue<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> <Self as ProxyType<'ctx>>::Value {
|
||||
assert!(self.ndims.is_none(), "NDArrayType::construct_dyn_ndims can only be called on an instance with compile-time unknown ndims (self.ndims = None)");
|
||||
|
||||
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!(self.ndims.is_none_or(|ndims| shape.len() as u64 == ndims));
|
||||
|
||||
let ndarray = Self::new(generator, ctx.ctx, self.dtype, Some(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!(self.ndims.is_none_or(|ndims| shape.len() as u64 == ndims));
|
||||
|
||||
let ndarray = Self::new(generator, ctx.ctx, self.dtype, Some(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!(self.ndims.is_none_or(|ndims| 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 raw_alloca<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> <Self::Value as ProxyValue<'ctx>>::Base {
|
||||
generator
|
||||
.gen_var_alloc(
|
||||
ctx,
|
||||
self.as_base_type().get_element_type().into_struct_type().into(),
|
||||
name,
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
fn array_alloca<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.as_base_type().get_element_type().into_struct_type().into(),
|
||||
size,
|
||||
name,
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
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()
|
||||
}
|
||||
}
|
@ -1,241 +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 super::ProxyType;
|
||||
use crate::codegen::{
|
||||
irrt,
|
||||
types::structure::{check_struct_type_matches_fields, StructField, StructFields},
|
||||
values::{
|
||||
ndarray::{NDArrayValue, NDIterValue},
|
||||
ArraySliceValue, ProxyValue,
|
||||
},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
#[derive(Debug, PartialEq, Eq, Clone, Copy)]
|
||||
pub struct NDIterType<'ctx> {
|
||||
ty: PointerType<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
}
|
||||
|
||||
#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
|
||||
pub struct NDIterStructFields<'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(usize.ptr_type(AddressSpace::default()))]
|
||||
pub strides: StructField<'ctx, PointerValue<'ctx>>,
|
||||
#[value_type(usize.ptr_type(AddressSpace::default()))]
|
||||
pub indices: StructField<'ctx, PointerValue<'ctx>>,
|
||||
#[value_type(usize)]
|
||||
pub nth: StructField<'ctx, IntValue<'ctx>>,
|
||||
#[value_type(i8_type().ptr_type(AddressSpace::default()))]
|
||||
pub element: StructField<'ctx, PointerValue<'ctx>>,
|
||||
#[value_type(usize)]
|
||||
pub size: StructField<'ctx, IntValue<'ctx>>,
|
||||
}
|
||||
|
||||
impl<'ctx> NDIterType<'ctx> {
|
||||
/// Checks whether `llvm_ty` represents a `nditer` 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_ndarray_ty) = llvm_ty else {
|
||||
return Err(format!("Expected struct type for `NDIter` type, got {llvm_ty}"));
|
||||
};
|
||||
|
||||
check_struct_type_matches_fields(
|
||||
Self::fields(ctx, llvm_usize),
|
||||
llvm_ndarray_ty,
|
||||
"NDIter",
|
||||
&[],
|
||||
)
|
||||
}
|
||||
|
||||
/// Returns an instance of [`StructFields`] containing all field accessors for this type.
|
||||
#[must_use]
|
||||
fn fields(ctx: impl AsContextRef<'ctx>, llvm_usize: IntType<'ctx>) -> NDIterStructFields<'ctx> {
|
||||
NDIterStructFields::new(ctx, llvm_usize)
|
||||
}
|
||||
|
||||
/// See [`NDIterType::fields`].
|
||||
// TODO: Move this into e.g. StructProxyType
|
||||
#[must_use]
|
||||
pub fn get_fields(&self, ctx: impl AsContextRef<'ctx>) -> NDIterStructFields<'ctx> {
|
||||
Self::fields(ctx, self.llvm_usize)
|
||||
}
|
||||
|
||||
/// Creates an LLVM type corresponding to the expected structure of an `NDIter`.
|
||||
#[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 [`NDIter`].
|
||||
#[must_use]
|
||||
pub fn new<G: CodeGenerator + ?Sized>(generator: &G, ctx: &'ctx Context) -> Self {
|
||||
let llvm_usize = generator.get_size_type(ctx);
|
||||
let llvm_nditer = Self::llvm_type(ctx, llvm_usize);
|
||||
|
||||
Self { ty: llvm_nditer, llvm_usize }
|
||||
}
|
||||
|
||||
/// Creates an [`NDIterType`] from a [`PointerType`] representing an `NDIter`.
|
||||
#[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 }
|
||||
}
|
||||
|
||||
/// Returns the type of the `size` field of this `nditer` type.
|
||||
#[must_use]
|
||||
pub fn size_type(&self) -> IntType<'ctx> {
|
||||
self.llvm_usize
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn alloca<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
parent: NDArrayValue<'ctx>,
|
||||
indices: ArraySliceValue<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> <Self as ProxyType<'ctx>>::Value {
|
||||
<Self as ProxyType<'ctx>>::Value::from_pointer_value(
|
||||
self.raw_alloca(generator, ctx, name),
|
||||
parent,
|
||||
indices,
|
||||
self.llvm_usize,
|
||||
name,
|
||||
)
|
||||
}
|
||||
|
||||
/// Allocate an [`NDIter`] that iterates through the given `ndarray`.
|
||||
#[must_use]
|
||||
pub fn construct<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndarray: NDArrayValue<'ctx>,
|
||||
) -> <Self as ProxyType<'ctx>>::Value {
|
||||
let nditer = self.raw_alloca(generator, ctx, None);
|
||||
let ndims = ndarray.load_ndims(ctx);
|
||||
|
||||
// The caller has the responsibility to allocate 'indices' for `NDIter`.
|
||||
let indices =
|
||||
generator.gen_array_var_alloc(ctx, self.llvm_usize.into(), ndims, None).unwrap();
|
||||
|
||||
let nditer = <Self as ProxyType<'ctx>>::Value::from_pointer_value(
|
||||
nditer,
|
||||
ndarray,
|
||||
indices,
|
||||
self.llvm_usize,
|
||||
None,
|
||||
);
|
||||
|
||||
irrt::ndarray::call_nac3_nditer_initialize(generator, ctx, nditer, ndarray, indices);
|
||||
|
||||
nditer
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn map_value(
|
||||
&self,
|
||||
value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
|
||||
parent: NDArrayValue<'ctx>,
|
||||
indices: ArraySliceValue<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> <Self as ProxyType<'ctx>>::Value {
|
||||
<Self as ProxyType<'ctx>>::Value::from_pointer_value(
|
||||
value,
|
||||
parent,
|
||||
indices,
|
||||
self.llvm_usize,
|
||||
name,
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> ProxyType<'ctx> for NDIterType<'ctx> {
|
||||
type Base = PointerType<'ctx>;
|
||||
type Value = NDIterValue<'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 raw_alloca<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> <Self::Value as ProxyValue<'ctx>>::Base {
|
||||
generator
|
||||
.gen_var_alloc(
|
||||
ctx,
|
||||
self.as_base_type().get_element_type().into_struct_type().into(),
|
||||
name,
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
fn array_alloca<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.as_base_type().get_element_type().into_struct_type().into(),
|
||||
size,
|
||||
name,
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
fn as_base_type(&self) -> Self::Base {
|
||||
self.ty
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> From<NDIterType<'ctx>> for PointerType<'ctx> {
|
||||
fn from(value: NDIterType<'ctx>) -> Self {
|
||||
value.as_base_type()
|
||||
}
|
||||
}
|
@ -1,170 +0,0 @@
|
||||
use inkwell::{
|
||||
context::Context,
|
||||
types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
|
||||
values::IntValue,
|
||||
AddressSpace,
|
||||
};
|
||||
|
||||
use super::ProxyType;
|
||||
use crate::codegen::{
|
||||
values::{ArraySliceValue, ProxyValue, RangeValue},
|
||||
{CodeGenContext, CodeGenerator},
|
||||
};
|
||||
|
||||
/// Proxy type for a `range` type in LLVM.
|
||||
#[derive(Debug, PartialEq, Eq, Clone, Copy)]
|
||||
pub struct RangeType<'ctx> {
|
||||
ty: PointerType<'ctx>,
|
||||
}
|
||||
|
||||
impl<'ctx> RangeType<'ctx> {
|
||||
/// Checks whether `llvm_ty` represents a `range` type, returning [Err] if it does not.
|
||||
pub fn is_representable(llvm_ty: PointerType<'ctx>) -> Result<(), String> {
|
||||
let llvm_range_ty = llvm_ty.get_element_type();
|
||||
let AnyTypeEnum::ArrayType(llvm_range_ty) = llvm_range_ty else {
|
||||
return Err(format!("Expected array type for `range` type, got {llvm_range_ty}"));
|
||||
};
|
||||
if llvm_range_ty.len() != 3 {
|
||||
return Err(format!(
|
||||
"Expected 3 elements for `range` type, got {}",
|
||||
llvm_range_ty.len()
|
||||
));
|
||||
}
|
||||
|
||||
let llvm_range_elem_ty = llvm_range_ty.get_element_type();
|
||||
let Ok(llvm_range_elem_ty) = IntType::try_from(llvm_range_elem_ty) else {
|
||||
return Err(format!(
|
||||
"Expected int type for `range` element type, got {llvm_range_elem_ty}"
|
||||
));
|
||||
};
|
||||
if llvm_range_elem_ty.get_bit_width() != 32 {
|
||||
return Err(format!(
|
||||
"Expected 32-bit int type for `range` element type, got {}",
|
||||
llvm_range_elem_ty.get_bit_width()
|
||||
));
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// Creates an LLVM type corresponding to the expected structure of a `Range`.
|
||||
#[must_use]
|
||||
fn llvm_type(ctx: &'ctx Context) -> PointerType<'ctx> {
|
||||
// typedef int32_t Range[3];
|
||||
let llvm_i32 = ctx.i32_type();
|
||||
llvm_i32.array_type(3).ptr_type(AddressSpace::default())
|
||||
}
|
||||
|
||||
/// Creates an instance of [`RangeType`].
|
||||
#[must_use]
|
||||
pub fn new(ctx: &'ctx Context) -> Self {
|
||||
let llvm_range = Self::llvm_type(ctx);
|
||||
|
||||
RangeType::from_type(llvm_range)
|
||||
}
|
||||
|
||||
/// Creates an [`RangeType`] from a [`PointerType`].
|
||||
#[must_use]
|
||||
pub fn from_type(ptr_ty: PointerType<'ctx>) -> Self {
|
||||
debug_assert!(Self::is_representable(ptr_ty).is_ok());
|
||||
|
||||
RangeType { ty: ptr_ty }
|
||||
}
|
||||
|
||||
/// Returns the type of all fields of this `range` type.
|
||||
#[must_use]
|
||||
pub fn value_type(&self) -> IntType<'ctx> {
|
||||
self.as_base_type().get_element_type().into_array_type().get_element_type().into_int_type()
|
||||
}
|
||||
|
||||
/// Allocates an instance of [`RangeValue`] as if by calling `alloca` on the base type.
|
||||
#[must_use]
|
||||
pub fn alloca<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(generator, ctx, name),
|
||||
name,
|
||||
)
|
||||
}
|
||||
|
||||
/// Converts an existing value into a [`RangeValue`].
|
||||
#[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, name)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> ProxyType<'ctx> for RangeType<'ctx> {
|
||||
type Base = PointerType<'ctx>;
|
||||
type Value = RangeValue<'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>(
|
||||
_: &G,
|
||||
_: &'ctx Context,
|
||||
llvm_ty: Self::Base,
|
||||
) -> Result<(), String> {
|
||||
Self::is_representable(llvm_ty)
|
||||
}
|
||||
|
||||
fn raw_alloca<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> <Self::Value as ProxyValue<'ctx>>::Base {
|
||||
generator
|
||||
.gen_var_alloc(
|
||||
ctx,
|
||||
self.as_base_type().get_element_type().into_struct_type().into(),
|
||||
name,
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
fn array_alloca<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.as_base_type().get_element_type().into_struct_type().into(),
|
||||
size,
|
||||
name,
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
fn as_base_type(&self) -> Self::Base {
|
||||
self.ty
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> From<RangeType<'ctx>> for PointerType<'ctx> {
|
||||
fn from(value: RangeType<'ctx>) -> Self {
|
||||
value.as_base_type()
|
||||
}
|
||||
}
|
@ -1,255 +0,0 @@
|
||||
use std::marker::PhantomData;
|
||||
|
||||
use inkwell::{
|
||||
context::AsContextRef,
|
||||
types::{BasicTypeEnum, IntType, StructType},
|
||||
values::{BasicValue, BasicValueEnum, IntValue, PointerValue, StructValue},
|
||||
};
|
||||
|
||||
use crate::codegen::CodeGenContext;
|
||||
|
||||
/// Trait indicating that the structure is a field-wise representation of an LLVM structure.
|
||||
///
|
||||
/// # Usage
|
||||
///
|
||||
/// For example, for a simple C-slice LLVM structure:
|
||||
///
|
||||
/// ```ignore
|
||||
/// struct CSliceFields<'ctx> {
|
||||
/// ptr: StructField<'ctx, PointerValue<'ctx>>,
|
||||
/// len: StructField<'ctx, IntValue<'ctx>>
|
||||
/// }
|
||||
/// ```
|
||||
pub trait StructFields<'ctx>: Eq + Copy {
|
||||
/// Creates an instance of [`StructFields`] using the given `ctx` and `size_t` types.
|
||||
fn new(ctx: impl AsContextRef<'ctx>, llvm_usize: IntType<'ctx>) -> Self;
|
||||
|
||||
/// Returns a [`Vec`] that contains the fields of the structure in the order as they appear in
|
||||
/// the type definition.
|
||||
#[must_use]
|
||||
fn to_vec(&self) -> Vec<(&'static str, BasicTypeEnum<'ctx>)>;
|
||||
|
||||
/// Returns a [`Iterator`] that contains the fields of the structure in the order as they appear
|
||||
/// in the type definition.
|
||||
#[must_use]
|
||||
fn iter(&self) -> impl Iterator<Item = (&'static str, BasicTypeEnum<'ctx>)> {
|
||||
self.to_vec().into_iter()
|
||||
}
|
||||
|
||||
/// Returns a [`Vec`] that contains the fields of the structure in the order as they appear in
|
||||
/// the type definition.
|
||||
#[must_use]
|
||||
fn into_vec(self) -> Vec<(&'static str, BasicTypeEnum<'ctx>)>
|
||||
where
|
||||
Self: Sized,
|
||||
{
|
||||
self.to_vec()
|
||||
}
|
||||
|
||||
/// Returns a [`Iterator`] that contains the fields of the structure in the order as they appear
|
||||
/// in the type definition.
|
||||
#[must_use]
|
||||
fn into_iter(self) -> impl Iterator<Item = (&'static str, BasicTypeEnum<'ctx>)>
|
||||
where
|
||||
Self: Sized,
|
||||
{
|
||||
self.into_vec().into_iter()
|
||||
}
|
||||
}
|
||||
|
||||
/// A single field of an LLVM structure.
|
||||
#[derive(Debug, PartialEq, Eq, Clone, Copy)]
|
||||
pub struct StructField<'ctx, Value>
|
||||
where
|
||||
Value: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>, Error = ()>,
|
||||
{
|
||||
/// The index of this field within the structure.
|
||||
index: u32,
|
||||
|
||||
/// The name of this field.
|
||||
name: &'static str,
|
||||
|
||||
/// The type of this field.
|
||||
ty: BasicTypeEnum<'ctx>,
|
||||
|
||||
/// Instance of [`PhantomData`] containing [`Value`], used to implement automatic downcasts.
|
||||
_value_ty: PhantomData<Value>,
|
||||
}
|
||||
|
||||
impl<'ctx, Value> StructField<'ctx, Value>
|
||||
where
|
||||
Value: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>, Error = ()>,
|
||||
{
|
||||
/// Creates an instance of [`StructField`].
|
||||
///
|
||||
/// * `idx_counter` - The instance of [`FieldIndexCounter`] used to track the current field
|
||||
/// index.
|
||||
/// * `name` - Name of the field.
|
||||
/// * `ty` - The type of this field.
|
||||
pub fn create(
|
||||
idx_counter: &mut FieldIndexCounter,
|
||||
name: &'static str,
|
||||
ty: impl Into<BasicTypeEnum<'ctx>>,
|
||||
) -> Self {
|
||||
StructField { index: idx_counter.increment(), name, ty: ty.into(), _value_ty: PhantomData }
|
||||
}
|
||||
|
||||
/// Creates an instance of [`StructField`] with a given index.
|
||||
///
|
||||
/// * `index` - The index of this field within its enclosing structure.
|
||||
/// * `name` - Name of the field.
|
||||
/// * `ty` - The type of this field.
|
||||
pub fn create_at(index: u32, name: &'static str, ty: impl Into<BasicTypeEnum<'ctx>>) -> Self {
|
||||
StructField { index, name, ty: ty.into(), _value_ty: PhantomData }
|
||||
}
|
||||
|
||||
/// Returns the name of this field.
|
||||
#[must_use]
|
||||
pub fn name(&self) -> &'static str {
|
||||
self.name
|
||||
}
|
||||
|
||||
/// Creates a pointer to this field in an arbitrary structure by performing a `getelementptr i32
|
||||
/// {idx...}, i32 {self.index}`.
|
||||
pub fn ptr_by_array_gep(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
pobj: PointerValue<'ctx>,
|
||||
idx: &[IntValue<'ctx>],
|
||||
) -> PointerValue<'ctx> {
|
||||
unsafe {
|
||||
ctx.builder.build_in_bounds_gep(
|
||||
pobj,
|
||||
&[idx, &[ctx.ctx.i32_type().const_int(u64::from(self.index), false)]].concat(),
|
||||
"",
|
||||
)
|
||||
}
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Creates a pointer to this field in an arbitrary structure by performing the equivalent of
|
||||
/// `getelementptr i32 0, i32 {self.index}`.
|
||||
pub fn ptr_by_gep(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
pobj: PointerValue<'ctx>,
|
||||
obj_name: Option<&'ctx str>,
|
||||
) -> PointerValue<'ctx> {
|
||||
ctx.builder
|
||||
.build_struct_gep(
|
||||
pobj,
|
||||
self.index,
|
||||
&obj_name.map(|name| format!("{name}.{}.addr", self.name)).unwrap_or_default(),
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Gets the value of this field for a given `obj`.
|
||||
#[must_use]
|
||||
pub fn get_from_value(&self, obj: StructValue<'ctx>) -> Value {
|
||||
obj.get_field_at_index(self.index).and_then(|value| Value::try_from(value).ok()).unwrap()
|
||||
}
|
||||
|
||||
/// Sets the value of this field for a given `obj`.
|
||||
pub fn set_for_value(&self, obj: StructValue<'ctx>, value: Value) {
|
||||
obj.set_field_at_index(self.index, value);
|
||||
}
|
||||
|
||||
/// Gets the value of this field for a pointer-to-structure.
|
||||
pub fn get(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
pobj: PointerValue<'ctx>,
|
||||
obj_name: Option<&'ctx str>,
|
||||
) -> Value {
|
||||
ctx.builder
|
||||
.build_load(
|
||||
self.ptr_by_gep(ctx, pobj, obj_name),
|
||||
&obj_name.map(|name| format!("{name}.{}", self.name)).unwrap_or_default(),
|
||||
)
|
||||
.map_err(|_| ())
|
||||
.and_then(|value| Value::try_from(value))
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Sets the value of this field for a pointer-to-structure.
|
||||
pub fn set(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
pobj: PointerValue<'ctx>,
|
||||
value: Value,
|
||||
obj_name: Option<&'ctx str>,
|
||||
) {
|
||||
ctx.builder.build_store(self.ptr_by_gep(ctx, pobj, obj_name), value).unwrap();
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, Value> From<StructField<'ctx, Value>> for (&'static str, BasicTypeEnum<'ctx>)
|
||||
where
|
||||
Value: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>, Error = ()>,
|
||||
{
|
||||
fn from(value: StructField<'ctx, Value>) -> Self {
|
||||
(value.name, value.ty)
|
||||
}
|
||||
}
|
||||
|
||||
/// A counter that tracks the next index of a field using a monotonically increasing counter.
|
||||
#[derive(Default, Debug, PartialEq, Eq, Clone, Copy)]
|
||||
pub struct FieldIndexCounter(u32);
|
||||
|
||||
impl FieldIndexCounter {
|
||||
/// Increments the number stored by this counter, returning the previous value.
|
||||
///
|
||||
/// Functionally equivalent to `i++` in C-based languages.
|
||||
pub fn increment(&mut self) -> u32 {
|
||||
let v = self.0;
|
||||
self.0 += 1;
|
||||
v
|
||||
}
|
||||
}
|
||||
|
||||
type FieldTypeVerifier<'ctx> = dyn Fn(BasicTypeEnum<'ctx>) -> Result<(), String>;
|
||||
|
||||
/// Checks whether [`llvm_ty`][StructType] contains the fields described by the given
|
||||
/// [`StructFields`] instance.
|
||||
///
|
||||
/// By default, this function will compare the type of each field in `expected_fields` against
|
||||
/// `llvm_ty`. To override this behavior for individual fields, pass in overrides to
|
||||
/// `custom_verifiers`, which will use the specified verifier when a field with the matching field
|
||||
/// name is being checked.
|
||||
pub(super) fn check_struct_type_matches_fields<'ctx>(
|
||||
expected_fields: impl StructFields<'ctx>,
|
||||
llvm_ty: StructType<'ctx>,
|
||||
ty_name: &'static str,
|
||||
custom_verifiers: &[(&str, &FieldTypeVerifier<'ctx>)],
|
||||
) -> Result<(), String> {
|
||||
let expected_fields = expected_fields.to_vec();
|
||||
|
||||
if llvm_ty.count_fields() != u32::try_from(expected_fields.len()).unwrap() {
|
||||
return Err(format!(
|
||||
"Expected {} fields in `{ty_name}`, got {}",
|
||||
expected_fields.len(),
|
||||
llvm_ty.count_fields(),
|
||||
));
|
||||
}
|
||||
|
||||
expected_fields
|
||||
.into_iter()
|
||||
.enumerate()
|
||||
.map(|(i, (field_name, expected_ty))| {
|
||||
(field_name, expected_ty, llvm_ty.get_field_type_at_index(i as u32).unwrap())
|
||||
})
|
||||
.try_for_each(|(field_name, expected_ty, actual_ty)| {
|
||||
if let Some((_, verifier)) =
|
||||
custom_verifiers.iter().find(|verifier| verifier.0 == field_name)
|
||||
{
|
||||
verifier(actual_ty)
|
||||
} else if expected_ty == actual_ty {
|
||||
Ok(())
|
||||
} else {
|
||||
Err(format!("Expected {expected_ty} for `{ty_name}.{field_name}`, got {actual_ty}"))
|
||||
}
|
||||
})?;
|
||||
|
||||
Ok(())
|
||||
}
|
@ -1,3 +0,0 @@
|
||||
pub use slice::*;
|
||||
|
||||
mod slice;
|
@ -1,254 +0,0 @@
|
||||
use inkwell::{
|
||||
context::{AsContextRef, Context, ContextRef},
|
||||
types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
|
||||
values::IntValue,
|
||||
AddressSpace,
|
||||
};
|
||||
use itertools::Itertools;
|
||||
|
||||
use nac3core_derive::StructFields;
|
||||
|
||||
use crate::codegen::{
|
||||
types::{
|
||||
structure::{
|
||||
check_struct_type_matches_fields, FieldIndexCounter, StructField, StructFields,
|
||||
},
|
||||
ProxyType,
|
||||
},
|
||||
values::{utils::SliceValue, ArraySliceValue, ProxyValue},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
#[derive(Debug, PartialEq, Eq, Clone, Copy)]
|
||||
pub struct SliceType<'ctx> {
|
||||
ty: PointerType<'ctx>,
|
||||
int_ty: IntType<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
}
|
||||
|
||||
#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
|
||||
pub struct SliceFields<'ctx> {
|
||||
#[value_type(bool_type())]
|
||||
pub start_defined: StructField<'ctx, IntValue<'ctx>>,
|
||||
#[value_type(usize)]
|
||||
pub start: StructField<'ctx, IntValue<'ctx>>,
|
||||
#[value_type(bool_type())]
|
||||
pub stop_defined: StructField<'ctx, IntValue<'ctx>>,
|
||||
#[value_type(usize)]
|
||||
pub stop: StructField<'ctx, IntValue<'ctx>>,
|
||||
#[value_type(bool_type())]
|
||||
pub step_defined: StructField<'ctx, IntValue<'ctx>>,
|
||||
#[value_type(usize)]
|
||||
pub step: StructField<'ctx, IntValue<'ctx>>,
|
||||
}
|
||||
|
||||
impl<'ctx> SliceFields<'ctx> {
|
||||
/// Creates a new instance of [`SliceFields`] with a custom integer type for its range values.
|
||||
#[must_use]
|
||||
pub fn new_sized(ctx: &impl AsContextRef<'ctx>, int_ty: IntType<'ctx>) -> Self {
|
||||
let ctx = unsafe { ContextRef::new(ctx.as_ctx_ref()) };
|
||||
let mut counter = FieldIndexCounter::default();
|
||||
|
||||
SliceFields {
|
||||
start_defined: StructField::create(&mut counter, "start_defined", ctx.bool_type()),
|
||||
start: StructField::create(&mut counter, "start", int_ty),
|
||||
stop_defined: StructField::create(&mut counter, "stop_defined", ctx.bool_type()),
|
||||
stop: StructField::create(&mut counter, "stop", int_ty),
|
||||
step_defined: StructField::create(&mut counter, "step_defined", ctx.bool_type()),
|
||||
step: StructField::create(&mut counter, "step", int_ty),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> SliceType<'ctx> {
|
||||
/// Checks whether `llvm_ty` represents a `slice` 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 fields = SliceFields::new(ctx, llvm_usize);
|
||||
|
||||
let llvm_ty = llvm_ty.get_element_type();
|
||||
let AnyTypeEnum::StructType(llvm_ty) = llvm_ty else {
|
||||
return Err(format!("Expected struct type for `Slice` type, got {llvm_ty}"));
|
||||
};
|
||||
|
||||
check_struct_type_matches_fields(
|
||||
fields,
|
||||
llvm_ty,
|
||||
"Slice",
|
||||
&[
|
||||
(fields.start.name(), &|ty| {
|
||||
if ty.is_int_type() {
|
||||
Ok(())
|
||||
} else {
|
||||
Err(format!("Expected int type for `Slice.start`, got {ty}"))
|
||||
}
|
||||
}),
|
||||
(fields.stop.name(), &|ty| {
|
||||
if ty.is_int_type() {
|
||||
Ok(())
|
||||
} else {
|
||||
Err(format!("Expected int type for `Slice.stop`, got {ty}"))
|
||||
}
|
||||
}),
|
||||
(fields.step.name(), &|ty| {
|
||||
if ty.is_int_type() {
|
||||
Ok(())
|
||||
} else {
|
||||
Err(format!("Expected int type for `Slice.step`, got {ty}"))
|
||||
}
|
||||
}),
|
||||
],
|
||||
)
|
||||
}
|
||||
|
||||
// TODO: Move this into e.g. StructProxyType
|
||||
#[must_use]
|
||||
pub fn get_fields(&self) -> SliceFields<'ctx> {
|
||||
SliceFields::new_sized(&self.int_ty.get_context(), self.int_ty)
|
||||
}
|
||||
|
||||
/// Creates an LLVM type corresponding to the expected structure of a `Slice`.
|
||||
#[must_use]
|
||||
fn llvm_type(ctx: &'ctx Context, int_ty: IntType<'ctx>) -> PointerType<'ctx> {
|
||||
let field_tys = SliceFields::new_sized(&int_ty.get_context(), int_ty)
|
||||
.into_iter()
|
||||
.map(|field| field.1)
|
||||
.collect_vec();
|
||||
|
||||
ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
|
||||
}
|
||||
|
||||
/// Creates an instance of [`SliceType`] with `int_ty` as its backing integer type.
|
||||
#[must_use]
|
||||
pub fn new(ctx: &'ctx Context, int_ty: IntType<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
|
||||
let llvm_ty = Self::llvm_type(ctx, int_ty);
|
||||
|
||||
Self { ty: llvm_ty, int_ty, llvm_usize }
|
||||
}
|
||||
|
||||
/// Creates an instance of [`SliceType`] with `usize` as its backing integer type.
|
||||
#[must_use]
|
||||
pub fn new_usize<G: CodeGenerator + ?Sized>(generator: &G, ctx: &'ctx Context) -> Self {
|
||||
let llvm_usize = generator.get_size_type(ctx);
|
||||
Self::new(ctx, llvm_usize, llvm_usize)
|
||||
}
|
||||
|
||||
/// Creates an [`SliceType`] from a [`PointerType`] representing a `slice`.
|
||||
#[must_use]
|
||||
pub fn from_type(
|
||||
ptr_ty: PointerType<'ctx>,
|
||||
int_ty: IntType<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
) -> Self {
|
||||
debug_assert!(Self::is_representable(ptr_ty, int_ty).is_ok());
|
||||
|
||||
Self { ty: ptr_ty, int_ty, llvm_usize }
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn element_type(&self) -> IntType<'ctx> {
|
||||
self.int_ty
|
||||
}
|
||||
|
||||
/// Allocates an instance of [`ContiguousNDArrayValue`] as if by calling `alloca` on the base type.
|
||||
#[must_use]
|
||||
pub fn alloca<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(generator, ctx, name),
|
||||
self.int_ty,
|
||||
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.int_ty,
|
||||
self.llvm_usize,
|
||||
name,
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> ProxyType<'ctx> for SliceType<'ctx> {
|
||||
type Base = PointerType<'ctx>;
|
||||
type Value = SliceValue<'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 raw_alloca<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> <Self::Value as ProxyValue<'ctx>>::Base {
|
||||
generator
|
||||
.gen_var_alloc(
|
||||
ctx,
|
||||
self.as_base_type().get_element_type().into_struct_type().into(),
|
||||
name,
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
fn array_alloca<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.as_base_type().get_element_type().into_struct_type().into(),
|
||||
size,
|
||||
name,
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
fn as_base_type(&self) -> Self::Base {
|
||||
self.ty
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> From<SliceType<'ctx>> for PointerType<'ctx> {
|
||||
fn from(value: SliceType<'ctx>) -> Self {
|
||||
value.as_base_type()
|
||||
}
|
||||
}
|
@ -1,426 +0,0 @@
|
||||
use inkwell::{
|
||||
types::AnyTypeEnum,
|
||||
values::{BasicValueEnum, IntValue, PointerValue},
|
||||
IntPredicate,
|
||||
};
|
||||
|
||||
use crate::codegen::{CodeGenContext, CodeGenerator};
|
||||
|
||||
/// An LLVM value that is array-like, i.e. it contains a contiguous, sequenced collection of
|
||||
/// elements.
|
||||
pub trait ArrayLikeValue<'ctx> {
|
||||
/// Returns the element type of this array-like value.
|
||||
fn element_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
generator: &G,
|
||||
) -> AnyTypeEnum<'ctx>;
|
||||
|
||||
/// Returns the base pointer to the array.
|
||||
fn base_ptr<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
generator: &G,
|
||||
) -> PointerValue<'ctx>;
|
||||
|
||||
/// Returns the size of this array-like value.
|
||||
fn size<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
generator: &G,
|
||||
) -> IntValue<'ctx>;
|
||||
|
||||
/// Returns a [`ArraySliceValue`] representing this value.
|
||||
fn as_slice_value<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
generator: &G,
|
||||
) -> ArraySliceValue<'ctx> {
|
||||
ArraySliceValue::from_ptr_val(
|
||||
self.base_ptr(ctx, generator),
|
||||
self.size(ctx, generator),
|
||||
None,
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
/// An array-like value that can be indexed by memory offset.
|
||||
pub trait ArrayLikeIndexer<'ctx, Index = IntValue<'ctx>>: ArrayLikeValue<'ctx> {
|
||||
/// # Safety
|
||||
///
|
||||
/// This function should be called with a valid index.
|
||||
unsafe fn ptr_offset_unchecked<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
generator: &mut G,
|
||||
idx: &Index,
|
||||
name: Option<&str>,
|
||||
) -> PointerValue<'ctx>;
|
||||
|
||||
/// Returns the pointer to the data at the `idx`-th index.
|
||||
fn ptr_offset<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
generator: &mut G,
|
||||
idx: &Index,
|
||||
name: Option<&str>,
|
||||
) -> PointerValue<'ctx>;
|
||||
}
|
||||
|
||||
/// An array-like value that can have its array elements accessed as a [`BasicValueEnum`].
|
||||
pub trait UntypedArrayLikeAccessor<'ctx, Index = IntValue<'ctx>>:
|
||||
ArrayLikeIndexer<'ctx, Index>
|
||||
{
|
||||
/// # Safety
|
||||
///
|
||||
/// This function should be called with a valid index.
|
||||
unsafe fn get_unchecked<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
generator: &mut G,
|
||||
idx: &Index,
|
||||
name: Option<&str>,
|
||||
) -> BasicValueEnum<'ctx> {
|
||||
let ptr = unsafe { self.ptr_offset_unchecked(ctx, generator, idx, name) };
|
||||
ctx.builder.build_load(ptr, name.unwrap_or_default()).unwrap()
|
||||
}
|
||||
|
||||
/// Returns the data at the `idx`-th index.
|
||||
fn get<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
generator: &mut G,
|
||||
idx: &Index,
|
||||
name: Option<&str>,
|
||||
) -> BasicValueEnum<'ctx> {
|
||||
let ptr = self.ptr_offset(ctx, generator, idx, name);
|
||||
ctx.builder.build_load(ptr, name.unwrap_or_default()).unwrap()
|
||||
}
|
||||
}
|
||||
|
||||
/// An array-like value that can have its array elements mutated as a [`BasicValueEnum`].
|
||||
pub trait UntypedArrayLikeMutator<'ctx, Index = IntValue<'ctx>>:
|
||||
ArrayLikeIndexer<'ctx, Index>
|
||||
{
|
||||
/// # Safety
|
||||
///
|
||||
/// This function should be called with a valid index.
|
||||
unsafe fn set_unchecked<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
generator: &mut G,
|
||||
idx: &Index,
|
||||
value: BasicValueEnum<'ctx>,
|
||||
) {
|
||||
let ptr = unsafe { self.ptr_offset_unchecked(ctx, generator, idx, None) };
|
||||
ctx.builder.build_store(ptr, value).unwrap();
|
||||
}
|
||||
|
||||
/// Sets the data at the `idx`-th index.
|
||||
fn set<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
generator: &mut G,
|
||||
idx: &Index,
|
||||
value: BasicValueEnum<'ctx>,
|
||||
) {
|
||||
let ptr = self.ptr_offset(ctx, generator, idx, None);
|
||||
ctx.builder.build_store(ptr, value).unwrap();
|
||||
}
|
||||
}
|
||||
|
||||
/// An array-like value that can have its array elements accessed as an arbitrary type `T`.
|
||||
pub trait TypedArrayLikeAccessor<'ctx, T, Index = IntValue<'ctx>>:
|
||||
UntypedArrayLikeAccessor<'ctx, Index>
|
||||
{
|
||||
/// Casts an element from [`BasicValueEnum`] into `T`.
|
||||
fn downcast_to_type(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
value: BasicValueEnum<'ctx>,
|
||||
) -> T;
|
||||
|
||||
/// # Safety
|
||||
///
|
||||
/// This function should be called with a valid index.
|
||||
unsafe fn get_typed_unchecked<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
generator: &mut G,
|
||||
idx: &Index,
|
||||
name: Option<&str>,
|
||||
) -> T {
|
||||
let value = unsafe { self.get_unchecked(ctx, generator, idx, name) };
|
||||
self.downcast_to_type(ctx, value)
|
||||
}
|
||||
|
||||
/// Returns the data at the `idx`-th index.
|
||||
fn get_typed<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
generator: &mut G,
|
||||
idx: &Index,
|
||||
name: Option<&str>,
|
||||
) -> T {
|
||||
let value = self.get(ctx, generator, idx, name);
|
||||
self.downcast_to_type(ctx, value)
|
||||
}
|
||||
}
|
||||
|
||||
/// An array-like value that can have its array elements mutated as an arbitrary type `T`.
|
||||
pub trait TypedArrayLikeMutator<'ctx, T, Index = IntValue<'ctx>>:
|
||||
UntypedArrayLikeMutator<'ctx, Index>
|
||||
{
|
||||
/// Casts an element from T into [`BasicValueEnum`].
|
||||
fn upcast_from_type(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
value: T,
|
||||
) -> BasicValueEnum<'ctx>;
|
||||
|
||||
/// # Safety
|
||||
///
|
||||
/// This function should be called with a valid index.
|
||||
unsafe fn set_typed_unchecked<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
generator: &mut G,
|
||||
idx: &Index,
|
||||
value: T,
|
||||
) {
|
||||
let value = self.upcast_from_type(ctx, value);
|
||||
unsafe { self.set_unchecked(ctx, generator, idx, value) }
|
||||
}
|
||||
|
||||
/// Sets the data at the `idx`-th index.
|
||||
fn set_typed<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
generator: &mut G,
|
||||
idx: &Index,
|
||||
value: T,
|
||||
) {
|
||||
let value = self.upcast_from_type(ctx, value);
|
||||
self.set(ctx, generator, idx, value);
|
||||
}
|
||||
}
|
||||
|
||||
/// Type alias for a function that casts a [`BasicValueEnum`] into a `T`.
|
||||
type ValueDowncastFn<'ctx, T> =
|
||||
Box<dyn Fn(&mut CodeGenContext<'ctx, '_>, BasicValueEnum<'ctx>) -> T + 'ctx>;
|
||||
/// Type alias for a function that casts a `T` into a [`BasicValueEnum`].
|
||||
type ValueUpcastFn<'ctx, T> = Box<dyn Fn(&mut CodeGenContext<'ctx, '_>, T) -> BasicValueEnum<'ctx>>;
|
||||
|
||||
/// An adapter for constraining untyped array values as typed values.
|
||||
pub struct TypedArrayLikeAdapter<'ctx, T, Adapted: ArrayLikeValue<'ctx> = ArraySliceValue<'ctx>> {
|
||||
adapted: Adapted,
|
||||
downcast_fn: ValueDowncastFn<'ctx, T>,
|
||||
upcast_fn: ValueUpcastFn<'ctx, T>,
|
||||
}
|
||||
|
||||
impl<'ctx, T, Adapted> TypedArrayLikeAdapter<'ctx, T, Adapted>
|
||||
where
|
||||
Adapted: ArrayLikeValue<'ctx>,
|
||||
{
|
||||
/// Creates a [`TypedArrayLikeAdapter`].
|
||||
///
|
||||
/// * `adapted` - The value to be adapted.
|
||||
/// * `downcast_fn` - The function converting a [`BasicValueEnum`] into a `T`.
|
||||
/// * `upcast_fn` - The function converting a T into a [`BasicValueEnum`].
|
||||
pub fn from(
|
||||
adapted: Adapted,
|
||||
downcast_fn: ValueDowncastFn<'ctx, T>,
|
||||
upcast_fn: ValueUpcastFn<'ctx, T>,
|
||||
) -> Self {
|
||||
TypedArrayLikeAdapter { adapted, downcast_fn, upcast_fn }
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, T, Adapted> ArrayLikeValue<'ctx> for TypedArrayLikeAdapter<'ctx, T, Adapted>
|
||||
where
|
||||
Adapted: ArrayLikeValue<'ctx>,
|
||||
{
|
||||
fn element_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
generator: &G,
|
||||
) -> AnyTypeEnum<'ctx> {
|
||||
self.adapted.element_type(ctx, generator)
|
||||
}
|
||||
|
||||
fn base_ptr<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
generator: &G,
|
||||
) -> PointerValue<'ctx> {
|
||||
self.adapted.base_ptr(ctx, generator)
|
||||
}
|
||||
|
||||
fn size<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
generator: &G,
|
||||
) -> IntValue<'ctx> {
|
||||
self.adapted.size(ctx, generator)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, T, Index, Adapted> ArrayLikeIndexer<'ctx, Index>
|
||||
for TypedArrayLikeAdapter<'ctx, T, Adapted>
|
||||
where
|
||||
Adapted: ArrayLikeIndexer<'ctx, Index>,
|
||||
{
|
||||
unsafe fn ptr_offset_unchecked<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
generator: &mut G,
|
||||
idx: &Index,
|
||||
name: Option<&str>,
|
||||
) -> PointerValue<'ctx> {
|
||||
unsafe { self.adapted.ptr_offset_unchecked(ctx, generator, idx, name) }
|
||||
}
|
||||
|
||||
fn ptr_offset<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
generator: &mut G,
|
||||
idx: &Index,
|
||||
name: Option<&str>,
|
||||
) -> PointerValue<'ctx> {
|
||||
self.adapted.ptr_offset(ctx, generator, idx, name)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, T, Index, Adapted> UntypedArrayLikeAccessor<'ctx, Index>
|
||||
for TypedArrayLikeAdapter<'ctx, T, Adapted>
|
||||
where
|
||||
Adapted: UntypedArrayLikeAccessor<'ctx, Index>,
|
||||
{
|
||||
}
|
||||
impl<'ctx, T, Index, Adapted> UntypedArrayLikeMutator<'ctx, Index>
|
||||
for TypedArrayLikeAdapter<'ctx, T, Adapted>
|
||||
where
|
||||
Adapted: UntypedArrayLikeMutator<'ctx, Index>,
|
||||
{
|
||||
}
|
||||
|
||||
impl<'ctx, T, Index, Adapted> TypedArrayLikeAccessor<'ctx, T, Index>
|
||||
for TypedArrayLikeAdapter<'ctx, T, Adapted>
|
||||
where
|
||||
Adapted: UntypedArrayLikeAccessor<'ctx, Index>,
|
||||
{
|
||||
fn downcast_to_type(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
value: BasicValueEnum<'ctx>,
|
||||
) -> T {
|
||||
(self.downcast_fn)(ctx, value)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx, T, Index, Adapted> TypedArrayLikeMutator<'ctx, T, Index>
|
||||
for TypedArrayLikeAdapter<'ctx, T, Adapted>
|
||||
where
|
||||
Adapted: UntypedArrayLikeMutator<'ctx, Index>,
|
||||
{
|
||||
fn upcast_from_type(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
value: T,
|
||||
) -> BasicValueEnum<'ctx> {
|
||||
(self.upcast_fn)(ctx, value)
|
||||
}
|
||||
}
|
||||
|
||||
/// An LLVM value representing an array slice, consisting of a pointer to the data and the size of
|
||||
/// the slice.
|
||||
#[derive(Copy, Clone)]
|
||||
pub struct ArraySliceValue<'ctx>(PointerValue<'ctx>, IntValue<'ctx>, Option<&'ctx str>);
|
||||
|
||||
impl<'ctx> ArraySliceValue<'ctx> {
|
||||
/// Creates an [`ArraySliceValue`] from a [`PointerValue`] and its size.
|
||||
#[must_use]
|
||||
pub fn from_ptr_val(
|
||||
ptr: PointerValue<'ctx>,
|
||||
size: IntValue<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> Self {
|
||||
ArraySliceValue(ptr, size, name)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> From<ArraySliceValue<'ctx>> for PointerValue<'ctx> {
|
||||
fn from(value: ArraySliceValue<'ctx>) -> Self {
|
||||
value.0
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> ArrayLikeValue<'ctx> for ArraySliceValue<'ctx> {
|
||||
fn element_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
_: &CodeGenContext<'ctx, '_>,
|
||||
_: &G,
|
||||
) -> AnyTypeEnum<'ctx> {
|
||||
self.0.get_type().get_element_type()
|
||||
}
|
||||
|
||||
fn base_ptr<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
_: &CodeGenContext<'ctx, '_>,
|
||||
_: &G,
|
||||
) -> PointerValue<'ctx> {
|
||||
self.0
|
||||
}
|
||||
|
||||
fn size<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
_: &CodeGenContext<'ctx, '_>,
|
||||
_: &G,
|
||||
) -> IntValue<'ctx> {
|
||||
self.1
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> ArrayLikeIndexer<'ctx> for ArraySliceValue<'ctx> {
|
||||
unsafe fn ptr_offset_unchecked<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
generator: &mut G,
|
||||
idx: &IntValue<'ctx>,
|
||||
name: Option<&str>,
|
||||
) -> PointerValue<'ctx> {
|
||||
let var_name = name.map(|v| format!("{v}.addr")).unwrap_or_default();
|
||||
|
||||
unsafe {
|
||||
ctx.builder
|
||||
.build_in_bounds_gep(self.base_ptr(ctx, generator), &[*idx], var_name.as_str())
|
||||
.unwrap()
|
||||
}
|
||||
}
|
||||
|
||||
fn ptr_offset<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
generator: &mut G,
|
||||
idx: &IntValue<'ctx>,
|
||||
name: Option<&str>,
|
||||
) -> PointerValue<'ctx> {
|
||||
debug_assert_eq!(idx.get_type(), generator.get_size_type(ctx.ctx));
|
||||
|
||||
let size = self.size(ctx, generator);
|
||||
let in_range = ctx.builder.build_int_compare(IntPredicate::ULT, *idx, size, "").unwrap();
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
in_range,
|
||||
"0:IndexError",
|
||||
"list index out of range",
|
||||
[None, None, None],
|
||||
ctx.current_loc,
|
||||
);
|
||||
|
||||
unsafe { self.ptr_offset_unchecked(ctx, generator, idx, name) }
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> UntypedArrayLikeAccessor<'ctx> for ArraySliceValue<'ctx> {}
|
||||
impl<'ctx> UntypedArrayLikeMutator<'ctx> for ArraySliceValue<'ctx> {}
|
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Reference in New Issue
Block a user