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misc/impl-
| Author | SHA1 | Date | |
|---|---|---|---|
| 78a070e8e0 |
24
Cargo.lock
generated
24
Cargo.lock
generated
@ -126,9 +126,9 @@ checksum = "1fd0f2584146f6f2ef48085050886acf353beff7305ebd1ae69500e27c67f64b"
|
||||
|
||||
[[package]]
|
||||
name = "cc"
|
||||
version = "1.2.4"
|
||||
version = "1.2.3"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "9157bbaa6b165880c27a4293a474c91cdcf265cc68cc829bf10be0964a391caf"
|
||||
checksum = "27f657647bcff5394bf56c7317665bbf790a137a50eaaa5c6bfbb9e27a518f2d"
|
||||
dependencies = [
|
||||
"shlex",
|
||||
]
|
||||
@ -559,9 +559,9 @@ checksum = "bbd2bcb4c963f2ddae06a2efc7e9f3591312473c50c6685e1f298068316e66fe"
|
||||
|
||||
[[package]]
|
||||
name = "libc"
|
||||
version = "0.2.168"
|
||||
version = "0.2.167"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "5aaeb2981e0606ca11d79718f8bb01164f1d6ed75080182d3abf017e6d244b6d"
|
||||
checksum = "09d6582e104315a817dff97f75133544b2e094ee22447d2acf4a74e189ba06fc"
|
||||
|
||||
[[package]]
|
||||
name = "libloading"
|
||||
@ -1004,9 +1004,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "redox_syscall"
|
||||
version = "0.5.8"
|
||||
version = "0.5.7"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "03a862b389f93e68874fbf580b9de08dd02facb9a788ebadaf4a3fd33cf58834"
|
||||
checksum = "9b6dfecf2c74bce2466cabf93f6664d6998a69eb21e39f4207930065b27b771f"
|
||||
dependencies = [
|
||||
"bitflags",
|
||||
]
|
||||
@ -1089,24 +1089,24 @@ checksum = "94143f37725109f92c262ed2cf5e59bce7498c01bcc1502d7b9afe439a4e9f49"
|
||||
|
||||
[[package]]
|
||||
name = "semver"
|
||||
version = "1.0.24"
|
||||
version = "1.0.23"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "3cb6eb87a131f756572d7fb904f6e7b68633f09cca868c5df1c4b8d1a694bbba"
|
||||
checksum = "61697e0a1c7e512e84a621326239844a24d8207b4669b41bc18b32ea5cbf988b"
|
||||
|
||||
[[package]]
|
||||
name = "serde"
|
||||
version = "1.0.216"
|
||||
version = "1.0.215"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "0b9781016e935a97e8beecf0c933758c97a5520d32930e460142b4cd80c6338e"
|
||||
checksum = "6513c1ad0b11a9376da888e3e0baa0077f1aed55c17f50e7b2397136129fb88f"
|
||||
dependencies = [
|
||||
"serde_derive",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "serde_derive"
|
||||
version = "1.0.216"
|
||||
version = "1.0.215"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "46f859dbbf73865c6627ed570e78961cd3ac92407a2d117204c49232485da55e"
|
||||
checksum = "ad1e866f866923f252f05c889987993144fb74e722403468a4ebd70c3cd756c0"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
|
||||
6
flake.lock
generated
6
flake.lock
generated
@ -2,11 +2,11 @@
|
||||
"nodes": {
|
||||
"nixpkgs": {
|
||||
"locked": {
|
||||
"lastModified": 1733940404,
|
||||
"narHash": "sha256-Pj39hSoUA86ZePPF/UXiYHHM7hMIkios8TYG29kQT4g=",
|
||||
"lastModified": 1731319897,
|
||||
"narHash": "sha256-PbABj4tnbWFMfBp6OcUK5iGy1QY+/Z96ZcLpooIbuEI=",
|
||||
"owner": "NixOS",
|
||||
"repo": "nixpkgs",
|
||||
"rev": "5d67ea6b4b63378b9c13be21e2ec9d1afc921713",
|
||||
"rev": "dc460ec76cbff0e66e269457d7b728432263166c",
|
||||
"type": "github"
|
||||
},
|
||||
"original": {
|
||||
|
||||
@ -12,17 +12,16 @@ use pyo3::{
|
||||
PyObject, PyResult, Python,
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||||
};
|
||||
|
||||
use super::{symbol_resolver::InnerResolver, timeline::TimeFns};
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||||
use nac3core::{
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||||
codegen::{
|
||||
expr::{destructure_range, gen_call},
|
||||
llvm_intrinsics::{call_int_smax, call_memcpy, call_stackrestore, call_stacksave},
|
||||
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},
|
||||
type_aligned_alloca,
|
||||
types::ndarray::NDArrayType,
|
||||
types::NDArrayType,
|
||||
values::{
|
||||
ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, ProxyValue, RangeValue,
|
||||
UntypedArrayLikeAccessor,
|
||||
ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue, ProxyValue,
|
||||
RangeValue, UntypedArrayLikeAccessor,
|
||||
},
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
@ -35,14 +34,12 @@ use nac3core::{
|
||||
},
|
||||
nac3parser::ast::{Expr, ExprKind, Located, Stmt, StmtKind, StrRef},
|
||||
symbol_resolver::ValueEnum,
|
||||
toplevel::{
|
||||
helper::{extract_ndims, PrimDef},
|
||||
numpy::unpack_ndarray_var_tys,
|
||||
DefinitionId, GenCall,
|
||||
},
|
||||
toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId, GenCall},
|
||||
typecheck::typedef::{iter_type_vars, FunSignature, FuncArg, Type, TypeEnum, VarMap},
|
||||
};
|
||||
|
||||
use super::{symbol_resolver::InnerResolver, timeline::TimeFns};
|
||||
|
||||
/// The parallelism mode within a block.
|
||||
#[derive(Copy, Clone, Eq, PartialEq)]
|
||||
enum ParallelMode {
|
||||
@ -461,49 +458,60 @@ 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_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
let llvm_arg = NDArrayValue::from_pointer_value(
|
||||
arg.into_pointer_value(),
|
||||
llvm_elem_ty,
|
||||
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.get_type().size_type().size_of(),
|
||||
llvm_usize,
|
||||
"",
|
||||
)
|
||||
.unwrap();
|
||||
let llvm_pdata_sizeof = ctx
|
||||
.builder
|
||||
.build_int_truncate_or_bit_cast(
|
||||
llvm_elem_ty.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();
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||||
let sizeof_pdata =
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||||
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]; }
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||||
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.shape().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)
|
||||
}
|
||||
|
||||
_ => {
|
||||
@ -544,8 +552,6 @@ 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 +572,8 @@ 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 +599,79 @@ 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.alloca(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_shape(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_elem_ty.ptr_type(AddressSpace::default()).size_of(),
|
||||
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_bit_cast(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 +679,7 @@ 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 +687,16 @@ 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 +705,49 @@ 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.shape().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.shape(), (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 +756,7 @@ 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 +771,12 @@ 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();
|
||||
@ -1338,50 +1375,62 @@ 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);
|
||||
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_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_pointer_value(
|
||||
value.into_pointer_value(),
|
||||
llvm_elem_ty,
|
||||
llvm_usize,
|
||||
None,
|
||||
);
|
||||
let len = call_ndarray_calc_size(generator, ctx, &val.shape(), (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);
|
||||
|
||||
@ -30,8 +30,9 @@ use tempfile::{self, TempDir};
|
||||
|
||||
use nac3core::{
|
||||
codegen::{
|
||||
concrete_type::ConcreteTypeStore, gen_func_impl, irrt::load_irrt, CodeGenLLVMOptions,
|
||||
CodeGenTargetMachineOptions, CodeGenTask, CodeGenerator, WithCall, WorkerRegistry,
|
||||
concrete_type::ConcreteTypeStore, gen_func_impl, irrt::load_irrt,
|
||||
tracert::TraceRuntimeConfig, CodeGenLLVMOptions, CodeGenTargetMachineOptions, CodeGenTask,
|
||||
CodeGenerator, WithCall, WorkerRegistry,
|
||||
},
|
||||
inkwell::{
|
||||
context::Context,
|
||||
@ -716,8 +717,13 @@ impl Nac3 {
|
||||
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);
|
||||
let (registry, handles) = WorkerRegistry::create_workers(
|
||||
threads,
|
||||
top_level.clone(),
|
||||
&self.llvm_options,
|
||||
&TraceRuntimeConfig::default(),
|
||||
&f,
|
||||
);
|
||||
|
||||
let mut generator = ArtiqCodeGenerator::new("main".to_string(), size_t, self.time_fns);
|
||||
let context = Context::create();
|
||||
|
||||
@ -10,14 +10,12 @@ use itertools::Itertools;
|
||||
use parking_lot::RwLock;
|
||||
use pyo3::{
|
||||
types::{PyDict, PyTuple},
|
||||
PyAny, PyErr, PyObject, PyResult, Python,
|
||||
PyAny, PyObject, PyResult, Python,
|
||||
};
|
||||
|
||||
use super::PrimitivePythonId;
|
||||
use nac3core::{
|
||||
codegen::{
|
||||
types::{ndarray::NDArrayType, ProxyType},
|
||||
values::ndarray::make_contiguous_strides,
|
||||
types::{NDArrayType, ProxyType},
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
inkwell::{
|
||||
@ -39,6 +37,8 @@ use nac3core::{
|
||||
},
|
||||
};
|
||||
|
||||
use super::PrimitivePythonId;
|
||||
|
||||
pub enum PrimitiveValue {
|
||||
I32(i32),
|
||||
I64(i64),
|
||||
@ -1085,19 +1085,18 @@ 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_base_type().get_element_type().into_struct_type(),
|
||||
Some(AddressSpace::default()),
|
||||
&id_str,
|
||||
)
|
||||
@ -1107,41 +1106,40 @@ 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 +1147,17 @@ 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 +1182,38 @@ 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
|
||||
|
||||
// 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
|
||||
let value = ndarray_llvm_ty
|
||||
.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(),
|
||||
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(),
|
||||
]);
|
||||
|
||||
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_base_type().get_element_type().into_struct_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 {
|
||||
|
||||
@ -8,6 +8,7 @@ edition = "2021"
|
||||
default = ["derive"]
|
||||
derive = ["dep:nac3core_derive"]
|
||||
no-escape-analysis = []
|
||||
tracing = []
|
||||
|
||||
[dependencies]
|
||||
itertools = "0.13"
|
||||
@ -31,4 +32,5 @@ indoc = "2.0"
|
||||
insta = "=1.11.0"
|
||||
|
||||
[build-dependencies]
|
||||
itertools = "0.13"
|
||||
regex = "1.10"
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
use std::ffi::OsStr;
|
||||
use std::{
|
||||
env,
|
||||
fs::File,
|
||||
@ -6,14 +7,28 @@ use std::{
|
||||
process::{Command, Stdio},
|
||||
};
|
||||
|
||||
use itertools::Itertools;
|
||||
use regex::Regex;
|
||||
|
||||
fn main() {
|
||||
struct IRRTCompilation<'a> {
|
||||
pub file: &'a str,
|
||||
pub gcc_options: Vec<&'a str>,
|
||||
pub cargo_instructions: Vec<&'a str>,
|
||||
}
|
||||
|
||||
/// Extracts the extension-less filename from a [`Path`].
|
||||
fn path_to_extless_filename(path: &Path) -> &str {
|
||||
path.file_name().map(Path::new).and_then(Path::file_stem).and_then(OsStr::to_str).unwrap()
|
||||
}
|
||||
|
||||
/// Compiles a source C file into LLVM bitcode.
|
||||
fn compile_file_to_ir(compile_opts: &IRRTCompilation) {
|
||||
let out_dir = env::var("OUT_DIR").unwrap();
|
||||
let out_dir = Path::new(&out_dir);
|
||||
let out_path = Path::new(&out_dir);
|
||||
let irrt_dir = Path::new("irrt");
|
||||
|
||||
let irrt_cpp_path = irrt_dir.join("irrt.cpp");
|
||||
let path = Path::new(compile_opts.file);
|
||||
let filename_without_ext = path_to_extless_filename(path);
|
||||
|
||||
/*
|
||||
* HACK: Sadly, clang doesn't let us emit generic LLVM bitcode.
|
||||
@ -35,22 +50,22 @@ fn main() {
|
||||
"-",
|
||||
"-I",
|
||||
irrt_dir.to_str().unwrap(),
|
||||
irrt_cpp_path.to_str().unwrap(),
|
||||
];
|
||||
|
||||
// Apply custom flags from IRRTCompilation
|
||||
flags.extend_from_slice(&compile_opts.gcc_options);
|
||||
|
||||
match env::var("PROFILE").as_deref() {
|
||||
Ok("debug") => {
|
||||
flags.push("-O0");
|
||||
flags.push("-DIRRT_DEBUG_ASSERT");
|
||||
}
|
||||
Ok("release") => {
|
||||
flags.push("-O3");
|
||||
}
|
||||
Ok("debug") => flags.extend_from_slice(&["-O0", "-DIRRT_DEBUG_ASSERT"]),
|
||||
Ok("release") => flags.push("-O3"),
|
||||
flavor => panic!("Unknown or missing build flavor {flavor:?}"),
|
||||
}
|
||||
|
||||
// Tell Cargo to rerun if any file under `irrt_dir` (recursive) changes
|
||||
println!("cargo:rerun-if-changed={}", irrt_dir.to_str().unwrap());
|
||||
flags.push(path.to_str().unwrap());
|
||||
|
||||
// Tell Cargo to rerun if the main IRRT source is changed
|
||||
println!("cargo:rerun-if-changed={}", path.to_str().unwrap());
|
||||
compile_opts.cargo_instructions.iter().for_each(|inst| println!("cargo::{inst}"));
|
||||
|
||||
// Compile IRRT and capture the LLVM IR output
|
||||
let output = Command::new("clang-irrt")
|
||||
@ -61,8 +76,7 @@ fn main() {
|
||||
})
|
||||
.unwrap();
|
||||
|
||||
// https://github.com/rust-lang/regex/issues/244
|
||||
let output = std::str::from_utf8(&output.stdout).unwrap().replace("\r\n", "\n");
|
||||
let output = std::str::from_utf8(&output.stdout).unwrap();
|
||||
let mut filtered_output = String::with_capacity(output.len());
|
||||
|
||||
// Filter out irrelevant IR
|
||||
@ -76,7 +90,7 @@ fn main() {
|
||||
r"(?ms:^define.*?\}$)|(?m:^declare.*?$)|(?m:^%.+?=\s*type\s*\{.+?\}$)|(?m:^@.+?=.+$)",
|
||||
)
|
||||
.unwrap();
|
||||
for f in regex_filter.captures_iter(&output) {
|
||||
for f in regex_filter.captures_iter(output) {
|
||||
assert_eq!(f.len(), 1);
|
||||
filtered_output.push_str(&f[0]);
|
||||
filtered_output.push('\n');
|
||||
@ -90,20 +104,47 @@ fn main() {
|
||||
// Doing `DEBUG_DUMP_IRRT=1 cargo build -p nac3core` dumps the LLVM IR generated
|
||||
const DEBUG_DUMP_IRRT: &str = "DEBUG_DUMP_IRRT";
|
||||
println!("cargo:rerun-if-env-changed={DEBUG_DUMP_IRRT}");
|
||||
if env::var(DEBUG_DUMP_IRRT).is_ok() {
|
||||
let mut file = File::create(out_dir.join("irrt.ll")).unwrap();
|
||||
if env::var("DEBUG_DUMP_IRRT").is_ok() {
|
||||
let mut file = File::create(out_path.join(format!("{filename_without_ext}.ll"))).unwrap();
|
||||
file.write_all(output.as_bytes()).unwrap();
|
||||
|
||||
let mut file = File::create(out_dir.join("irrt-filtered.ll")).unwrap();
|
||||
let mut file =
|
||||
File::create(out_path.join(format!("{filename_without_ext}-filtered.ll"))).unwrap();
|
||||
file.write_all(filtered_output.as_bytes()).unwrap();
|
||||
}
|
||||
|
||||
let mut llvm_as = Command::new("llvm-as-irrt")
|
||||
.stdin(Stdio::piped())
|
||||
.arg("-o")
|
||||
.arg(out_dir.join("irrt.bc"))
|
||||
.arg(out_path.join(format!("{filename_without_ext}.bc")))
|
||||
.spawn()
|
||||
.unwrap();
|
||||
llvm_as.stdin.as_mut().unwrap().write_all(filtered_output.as_bytes()).unwrap();
|
||||
assert!(llvm_as.wait().unwrap().success());
|
||||
}
|
||||
|
||||
fn main() {
|
||||
let irrt_compilations: &[IRRTCompilation] = &[
|
||||
IRRTCompilation {
|
||||
file: "irrt/irrt.cpp",
|
||||
gcc_options: Vec::default(),
|
||||
cargo_instructions: vec!["rerun-if-changed=irrt/irrt"],
|
||||
},
|
||||
IRRTCompilation {
|
||||
file: "irrt/tracert.cpp",
|
||||
gcc_options: Vec::default(),
|
||||
cargo_instructions: Vec::default(),
|
||||
},
|
||||
];
|
||||
|
||||
assert!(irrt_compilations
|
||||
.iter()
|
||||
.map(|comp| comp.file)
|
||||
.map(Path::new)
|
||||
.map(path_to_extless_filename)
|
||||
.all_unique());
|
||||
|
||||
for path in irrt_compilations {
|
||||
compile_file_to_ir(path)
|
||||
}
|
||||
}
|
||||
|
||||
@ -2,9 +2,4 @@
|
||||
#include "irrt/list.hpp"
|
||||
#include "irrt/math.hpp"
|
||||
#include "irrt/ndarray.hpp"
|
||||
#include "irrt/range.hpp"
|
||||
#include "irrt/slice.hpp"
|
||||
#include "irrt/ndarray/basic.hpp"
|
||||
#include "irrt/ndarray/def.hpp"
|
||||
#include "irrt/ndarray/iter.hpp"
|
||||
#include "irrt/ndarray/indexing.hpp"
|
||||
|
||||
@ -22,6 +22,6 @@ using uint64_t = unsigned _ExtInt(64);
|
||||
#endif
|
||||
|
||||
// NDArray indices are always `uint32_t`.
|
||||
using NDIndexInt = uint32_t;
|
||||
using NDIndex = uint32_t;
|
||||
// The type of an index or a value describing the length of a range/slice is always `int32_t`.
|
||||
using SliceIndex = int32_t;
|
||||
|
||||
@ -2,8 +2,6 @@
|
||||
|
||||
#include "irrt/int_types.hpp"
|
||||
|
||||
// TODO: To be deleted since NDArray with strides is done.
|
||||
|
||||
namespace {
|
||||
template<typename SizeT>
|
||||
SizeT __nac3_ndarray_calc_size_impl(const SizeT* list_data, SizeT list_len, SizeT begin_idx, SizeT end_idx) {
|
||||
@ -19,7 +17,7 @@ SizeT __nac3_ndarray_calc_size_impl(const SizeT* list_data, SizeT list_len, Size
|
||||
}
|
||||
|
||||
template<typename SizeT>
|
||||
void __nac3_ndarray_calc_nd_indices_impl(SizeT index, const SizeT* dims, SizeT num_dims, NDIndexInt* idxs) {
|
||||
void __nac3_ndarray_calc_nd_indices_impl(SizeT index, const SizeT* dims, SizeT num_dims, NDIndex* idxs) {
|
||||
SizeT stride = 1;
|
||||
for (SizeT dim = 0; dim < num_dims; dim++) {
|
||||
SizeT i = num_dims - dim - 1;
|
||||
@ -30,10 +28,7 @@ void __nac3_ndarray_calc_nd_indices_impl(SizeT index, const SizeT* dims, SizeT n
|
||||
}
|
||||
|
||||
template<typename SizeT>
|
||||
SizeT __nac3_ndarray_flatten_index_impl(const SizeT* dims,
|
||||
SizeT num_dims,
|
||||
const NDIndexInt* indices,
|
||||
SizeT num_indices) {
|
||||
SizeT __nac3_ndarray_flatten_index_impl(const SizeT* dims, SizeT num_dims, const NDIndex* indices, SizeT num_indices) {
|
||||
SizeT idx = 0;
|
||||
SizeT stride = 1;
|
||||
for (SizeT i = 0; i < num_dims; ++i) {
|
||||
@ -80,8 +75,8 @@ void __nac3_ndarray_calc_broadcast_impl(const SizeT* lhs_dims,
|
||||
template<typename SizeT>
|
||||
void __nac3_ndarray_calc_broadcast_idx_impl(const SizeT* src_dims,
|
||||
SizeT src_ndims,
|
||||
const NDIndexInt* in_idx,
|
||||
NDIndexInt* out_idx) {
|
||||
const NDIndex* in_idx,
|
||||
NDIndex* out_idx) {
|
||||
for (SizeT i = 0; i < src_ndims; ++i) {
|
||||
SizeT src_i = src_ndims - i - 1;
|
||||
out_idx[src_i] = src_dims[src_i] == 1 ? 0 : in_idx[src_i];
|
||||
@ -99,23 +94,21 @@ __nac3_ndarray_calc_size64(const uint64_t* list_data, uint64_t list_len, uint64_
|
||||
return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_calc_nd_indices(uint32_t index, const uint32_t* dims, uint32_t num_dims, NDIndexInt* idxs) {
|
||||
void __nac3_ndarray_calc_nd_indices(uint32_t index, const uint32_t* dims, uint32_t num_dims, NDIndex* idxs) {
|
||||
__nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_calc_nd_indices64(uint64_t index, const uint64_t* dims, uint64_t num_dims, NDIndexInt* idxs) {
|
||||
void __nac3_ndarray_calc_nd_indices64(uint64_t index, const uint64_t* dims, uint64_t num_dims, NDIndex* idxs) {
|
||||
__nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
|
||||
}
|
||||
|
||||
uint32_t
|
||||
__nac3_ndarray_flatten_index(const uint32_t* dims, uint32_t num_dims, const NDIndexInt* indices, uint32_t num_indices) {
|
||||
__nac3_ndarray_flatten_index(const uint32_t* dims, uint32_t num_dims, const NDIndex* indices, uint32_t num_indices) {
|
||||
return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
|
||||
}
|
||||
|
||||
uint64_t __nac3_ndarray_flatten_index64(const uint64_t* dims,
|
||||
uint64_t num_dims,
|
||||
const NDIndexInt* indices,
|
||||
uint64_t num_indices) {
|
||||
uint64_t
|
||||
__nac3_ndarray_flatten_index64(const uint64_t* dims, uint64_t num_dims, const NDIndex* indices, uint64_t num_indices) {
|
||||
return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
|
||||
}
|
||||
|
||||
@ -137,15 +130,15 @@ void __nac3_ndarray_calc_broadcast64(const uint64_t* lhs_dims,
|
||||
|
||||
void __nac3_ndarray_calc_broadcast_idx(const uint32_t* src_dims,
|
||||
uint32_t src_ndims,
|
||||
const NDIndexInt* in_idx,
|
||||
NDIndexInt* out_idx) {
|
||||
const NDIndex* in_idx,
|
||||
NDIndex* out_idx) {
|
||||
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_calc_broadcast_idx64(const uint64_t* src_dims,
|
||||
uint64_t src_ndims,
|
||||
const NDIndexInt* in_idx,
|
||||
NDIndexInt* out_idx) {
|
||||
const NDIndex* in_idx,
|
||||
NDIndex* out_idx) {
|
||||
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
|
||||
}
|
||||
} // namespace
|
||||
@ -1,342 +0,0 @@
|
||||
#pragma once
|
||||
|
||||
#include "irrt/debug.hpp"
|
||||
#include "irrt/exception.hpp"
|
||||
#include "irrt/int_types.hpp"
|
||||
#include "irrt/ndarray/def.hpp"
|
||||
|
||||
namespace {
|
||||
namespace ndarray {
|
||||
namespace basic {
|
||||
/**
|
||||
* @brief Assert that `shape` does not contain negative dimensions.
|
||||
*
|
||||
* @param ndims Number of dimensions in `shape`
|
||||
* @param shape The shape to check on
|
||||
*/
|
||||
template<typename SizeT>
|
||||
void assert_shape_no_negative(SizeT ndims, const SizeT* shape) {
|
||||
for (SizeT axis = 0; axis < ndims; axis++) {
|
||||
if (shape[axis] < 0) {
|
||||
raise_exception(SizeT, EXN_VALUE_ERROR,
|
||||
"negative dimensions are not allowed; axis {0} "
|
||||
"has dimension {1}",
|
||||
axis, shape[axis], NO_PARAM);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Assert that two shapes are the same in the context of writing output to an ndarray.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
void assert_output_shape_same(SizeT ndarray_ndims,
|
||||
const SizeT* ndarray_shape,
|
||||
SizeT output_ndims,
|
||||
const SizeT* output_shape) {
|
||||
if (ndarray_ndims != output_ndims) {
|
||||
// There is no corresponding NumPy error message like this.
|
||||
raise_exception(SizeT, EXN_VALUE_ERROR, "Cannot write output of ndims {0} to an ndarray with ndims {1}",
|
||||
output_ndims, ndarray_ndims, NO_PARAM);
|
||||
}
|
||||
|
||||
for (SizeT axis = 0; axis < ndarray_ndims; axis++) {
|
||||
if (ndarray_shape[axis] != output_shape[axis]) {
|
||||
// There is no corresponding NumPy error message like this.
|
||||
raise_exception(SizeT, EXN_VALUE_ERROR,
|
||||
"Mismatched dimensions on axis {0}, output has "
|
||||
"dimension {1}, but destination ndarray has dimension {2}.",
|
||||
axis, output_shape[axis], ndarray_shape[axis]);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Return the number of elements of an ndarray given its shape.
|
||||
*
|
||||
* @param ndims Number of dimensions in `shape`
|
||||
* @param shape The shape of the ndarray
|
||||
*/
|
||||
template<typename SizeT>
|
||||
SizeT calc_size_from_shape(SizeT ndims, const SizeT* shape) {
|
||||
SizeT size = 1;
|
||||
for (SizeT axis = 0; axis < ndims; axis++)
|
||||
size *= shape[axis];
|
||||
return size;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Compute the array indices of the `nth` (0-based) element of an ndarray given only its shape.
|
||||
*
|
||||
* @param ndims Number of elements in `shape` and `indices`
|
||||
* @param shape The shape of the ndarray
|
||||
* @param indices The returned indices indexing the ndarray with shape `shape`.
|
||||
* @param nth The index of the element of interest.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
void set_indices_by_nth(SizeT ndims, const SizeT* shape, SizeT* indices, SizeT nth) {
|
||||
for (SizeT i = 0; i < ndims; i++) {
|
||||
SizeT axis = ndims - i - 1;
|
||||
SizeT dim = shape[axis];
|
||||
|
||||
indices[axis] = nth % dim;
|
||||
nth /= dim;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Return the number of elements of an `ndarray`
|
||||
*
|
||||
* This function corresponds to `<an_ndarray>.size`
|
||||
*/
|
||||
template<typename SizeT>
|
||||
SizeT size(const NDArray<SizeT>* ndarray) {
|
||||
return calc_size_from_shape(ndarray->ndims, ndarray->shape);
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Return of the number of its content of an `ndarray`.
|
||||
*
|
||||
* This function corresponds to `<an_ndarray>.nbytes`.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
SizeT nbytes(const NDArray<SizeT>* ndarray) {
|
||||
return size(ndarray) * ndarray->itemsize;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Get the `len()` of an ndarray, and asserts that `ndarray` is a sized object.
|
||||
*
|
||||
* This function corresponds to `<an_ndarray>.__len__`.
|
||||
*
|
||||
* @param dst_length The length.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
SizeT len(const NDArray<SizeT>* ndarray) {
|
||||
if (ndarray->ndims != 0) {
|
||||
return ndarray->shape[0];
|
||||
}
|
||||
|
||||
// numpy prohibits `__len__` on unsized objects
|
||||
raise_exception(SizeT, EXN_TYPE_ERROR, "len() of unsized object", NO_PARAM, NO_PARAM, NO_PARAM);
|
||||
__builtin_unreachable();
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Return a boolean indicating if `ndarray` is (C-)contiguous.
|
||||
*
|
||||
* You may want to see ndarray's rules for C-contiguity:
|
||||
* https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45
|
||||
*/
|
||||
template<typename SizeT>
|
||||
bool is_c_contiguous(const NDArray<SizeT>* ndarray) {
|
||||
// References:
|
||||
// - tinynumpy's implementation:
|
||||
// https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L102
|
||||
// - ndarray's flags["C_CONTIGUOUS"]:
|
||||
// https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html#numpy.ndarray.flags
|
||||
// - ndarray's rules for C-contiguity:
|
||||
// https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45
|
||||
|
||||
// From
|
||||
// https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45:
|
||||
//
|
||||
// The traditional rule is that for an array to be flagged as C contiguous,
|
||||
// the following must hold:
|
||||
//
|
||||
// strides[-1] == itemsize
|
||||
// strides[i] == shape[i+1] * strides[i + 1]
|
||||
// [...]
|
||||
// According to these rules, a 0- or 1-dimensional array is either both
|
||||
// C- and F-contiguous, or neither; and an array with 2+ dimensions
|
||||
// can be C- or F- contiguous, or neither, but not both. Though there
|
||||
// there are exceptions for arrays with zero or one item, in the first
|
||||
// case the check is relaxed up to and including the first dimension
|
||||
// with shape[i] == 0. In the second case `strides == itemsize` will
|
||||
// can be true for all dimensions and both flags are set.
|
||||
|
||||
if (ndarray->ndims == 0) {
|
||||
return true;
|
||||
}
|
||||
|
||||
if (ndarray->strides[ndarray->ndims - 1] != ndarray->itemsize) {
|
||||
return false;
|
||||
}
|
||||
|
||||
for (SizeT i = 1; i < ndarray->ndims; i++) {
|
||||
SizeT axis_i = ndarray->ndims - i - 1;
|
||||
if (ndarray->strides[axis_i] != ndarray->shape[axis_i + 1] * ndarray->strides[axis_i + 1]) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Return the pointer to the element indexed by `indices` along the ndarray's axes.
|
||||
*
|
||||
* This function does no bound check.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
void* get_pelement_by_indices(const NDArray<SizeT>* ndarray, const SizeT* indices) {
|
||||
void* element = ndarray->data;
|
||||
for (SizeT dim_i = 0; dim_i < ndarray->ndims; dim_i++)
|
||||
element = static_cast<uint8_t*>(element) + indices[dim_i] * ndarray->strides[dim_i];
|
||||
return element;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Return the pointer to the nth (0-based) element of `ndarray` in flattened view.
|
||||
*
|
||||
* This function does no bound check.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
void* get_nth_pelement(const NDArray<SizeT>* ndarray, SizeT nth) {
|
||||
void* element = ndarray->data;
|
||||
for (SizeT i = 0; i < ndarray->ndims; i++) {
|
||||
SizeT axis = ndarray->ndims - i - 1;
|
||||
SizeT dim = ndarray->shape[axis];
|
||||
element = static_cast<uint8_t*>(element) + ndarray->strides[axis] * (nth % dim);
|
||||
nth /= dim;
|
||||
}
|
||||
return element;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Update the strides of an ndarray given an ndarray `shape` to be contiguous.
|
||||
*
|
||||
* You might want to read https://ajcr.net/stride-guide-part-1/.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
void set_strides_by_shape(NDArray<SizeT>* ndarray) {
|
||||
SizeT stride_product = 1;
|
||||
for (SizeT i = 0; i < ndarray->ndims; i++) {
|
||||
SizeT axis = ndarray->ndims - i - 1;
|
||||
ndarray->strides[axis] = stride_product * ndarray->itemsize;
|
||||
stride_product *= ndarray->shape[axis];
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Set an element in `ndarray`.
|
||||
*
|
||||
* @param pelement Pointer to the element in `ndarray` to be set.
|
||||
* @param pvalue Pointer to the value `pelement` will be set to.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
void set_pelement_value(NDArray<SizeT>* ndarray, void* pelement, const void* pvalue) {
|
||||
__builtin_memcpy(pelement, pvalue, ndarray->itemsize);
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Copy data from one ndarray to another of the exact same size and itemsize.
|
||||
*
|
||||
* Both ndarrays will be viewed in their flatten views when copying the elements.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
void copy_data(const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
|
||||
// TODO: Make this faster with memcpy when we see a contiguous segment.
|
||||
// TODO: Handle overlapping.
|
||||
|
||||
debug_assert_eq(SizeT, src_ndarray->itemsize, dst_ndarray->itemsize);
|
||||
|
||||
for (SizeT i = 0; i < size(src_ndarray); i++) {
|
||||
auto src_element = ndarray::basic::get_nth_pelement(src_ndarray, i);
|
||||
auto dst_element = ndarray::basic::get_nth_pelement(dst_ndarray, i);
|
||||
ndarray::basic::set_pelement_value(dst_ndarray, dst_element, src_element);
|
||||
}
|
||||
}
|
||||
} // namespace basic
|
||||
} // namespace ndarray
|
||||
} // namespace
|
||||
|
||||
extern "C" {
|
||||
using namespace ndarray::basic;
|
||||
|
||||
void __nac3_ndarray_util_assert_shape_no_negative(int32_t ndims, int32_t* shape) {
|
||||
assert_shape_no_negative(ndims, shape);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_util_assert_shape_no_negative64(int64_t ndims, int64_t* shape) {
|
||||
assert_shape_no_negative(ndims, shape);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_util_assert_output_shape_same(int32_t ndarray_ndims,
|
||||
const int32_t* ndarray_shape,
|
||||
int32_t output_ndims,
|
||||
const int32_t* output_shape) {
|
||||
assert_output_shape_same(ndarray_ndims, ndarray_shape, output_ndims, output_shape);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_util_assert_output_shape_same64(int64_t ndarray_ndims,
|
||||
const int64_t* ndarray_shape,
|
||||
int64_t output_ndims,
|
||||
const int64_t* output_shape) {
|
||||
assert_output_shape_same(ndarray_ndims, ndarray_shape, output_ndims, output_shape);
|
||||
}
|
||||
|
||||
uint32_t __nac3_ndarray_size(NDArray<int32_t>* ndarray) {
|
||||
return size(ndarray);
|
||||
}
|
||||
|
||||
uint64_t __nac3_ndarray_size64(NDArray<int64_t>* ndarray) {
|
||||
return size(ndarray);
|
||||
}
|
||||
|
||||
uint32_t __nac3_ndarray_nbytes(NDArray<int32_t>* ndarray) {
|
||||
return nbytes(ndarray);
|
||||
}
|
||||
|
||||
uint64_t __nac3_ndarray_nbytes64(NDArray<int64_t>* ndarray) {
|
||||
return nbytes(ndarray);
|
||||
}
|
||||
|
||||
int32_t __nac3_ndarray_len(NDArray<int32_t>* ndarray) {
|
||||
return len(ndarray);
|
||||
}
|
||||
|
||||
int64_t __nac3_ndarray_len64(NDArray<int64_t>* ndarray) {
|
||||
return len(ndarray);
|
||||
}
|
||||
|
||||
bool __nac3_ndarray_is_c_contiguous(NDArray<int32_t>* ndarray) {
|
||||
return is_c_contiguous(ndarray);
|
||||
}
|
||||
|
||||
bool __nac3_ndarray_is_c_contiguous64(NDArray<int64_t>* ndarray) {
|
||||
return is_c_contiguous(ndarray);
|
||||
}
|
||||
|
||||
void* __nac3_ndarray_get_nth_pelement(const NDArray<int32_t>* ndarray, int32_t nth) {
|
||||
return get_nth_pelement(ndarray, nth);
|
||||
}
|
||||
|
||||
void* __nac3_ndarray_get_nth_pelement64(const NDArray<int64_t>* ndarray, int64_t nth) {
|
||||
return get_nth_pelement(ndarray, nth);
|
||||
}
|
||||
|
||||
void* __nac3_ndarray_get_pelement_by_indices(const NDArray<int32_t>* ndarray, int32_t* indices) {
|
||||
return get_pelement_by_indices(ndarray, indices);
|
||||
}
|
||||
|
||||
void* __nac3_ndarray_get_pelement_by_indices64(const NDArray<int64_t>* ndarray, int64_t* indices) {
|
||||
return get_pelement_by_indices(ndarray, indices);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_set_strides_by_shape(NDArray<int32_t>* ndarray) {
|
||||
set_strides_by_shape(ndarray);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_set_strides_by_shape64(NDArray<int64_t>* ndarray) {
|
||||
set_strides_by_shape(ndarray);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_copy_data(NDArray<int32_t>* src_ndarray, NDArray<int32_t>* dst_ndarray) {
|
||||
copy_data(src_ndarray, dst_ndarray);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_copy_data64(NDArray<int64_t>* src_ndarray, NDArray<int64_t>* dst_ndarray) {
|
||||
copy_data(src_ndarray, dst_ndarray);
|
||||
}
|
||||
}
|
||||
@ -1,51 +0,0 @@
|
||||
#pragma once
|
||||
|
||||
#include "irrt/int_types.hpp"
|
||||
|
||||
namespace {
|
||||
/**
|
||||
* @brief The NDArray object
|
||||
*
|
||||
* Official numpy implementation:
|
||||
* https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst#pyarrayinterface
|
||||
*
|
||||
* Note that this implementation is based on `PyArrayInterface` rather of `PyArrayObject`. The
|
||||
* difference between `PyArrayInterface` and `PyArrayObject` (relevant to our implementation) is
|
||||
* that `PyArrayInterface` *has* `itemsize` and uses `void*` for its `data`, whereas `PyArrayObject`
|
||||
* does not require `itemsize` (probably using `strides[-1]` instead) and uses `char*` for its
|
||||
* `data`. There are also minor differences in the struct layout.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
struct NDArray {
|
||||
/**
|
||||
* @brief The number of bytes of a single element in `data`.
|
||||
*/
|
||||
SizeT itemsize;
|
||||
|
||||
/**
|
||||
* @brief The number of dimensions of this shape.
|
||||
*/
|
||||
SizeT ndims;
|
||||
|
||||
/**
|
||||
* @brief The NDArray shape, with length equal to `ndims`.
|
||||
*
|
||||
* Note that it may contain 0.
|
||||
*/
|
||||
SizeT* shape;
|
||||
|
||||
/**
|
||||
* @brief Array strides, with length equal to `ndims`
|
||||
*
|
||||
* The stride values are in units of bytes, not number of elements.
|
||||
*
|
||||
* Note that `strides` can have negative values or contain 0.
|
||||
*/
|
||||
SizeT* strides;
|
||||
|
||||
/**
|
||||
* @brief The underlying data this `ndarray` is pointing to.
|
||||
*/
|
||||
void* data;
|
||||
};
|
||||
} // namespace
|
||||
@ -1,220 +0,0 @@
|
||||
#pragma once
|
||||
|
||||
#include "irrt/exception.hpp"
|
||||
#include "irrt/int_types.hpp"
|
||||
#include "irrt/ndarray/basic.hpp"
|
||||
#include "irrt/ndarray/def.hpp"
|
||||
#include "irrt/range.hpp"
|
||||
#include "irrt/slice.hpp"
|
||||
|
||||
namespace {
|
||||
typedef uint8_t NDIndexType;
|
||||
|
||||
/**
|
||||
* @brief A single element index
|
||||
*
|
||||
* `data` points to a `int32_t`.
|
||||
*/
|
||||
const NDIndexType ND_INDEX_TYPE_SINGLE_ELEMENT = 0;
|
||||
|
||||
/**
|
||||
* @brief A slice index
|
||||
*
|
||||
* `data` points to a `Slice<int32_t>`.
|
||||
*/
|
||||
const NDIndexType ND_INDEX_TYPE_SLICE = 1;
|
||||
|
||||
/**
|
||||
* @brief `np.newaxis` / `None`
|
||||
*
|
||||
* `data` is unused.
|
||||
*/
|
||||
const NDIndexType ND_INDEX_TYPE_NEWAXIS = 2;
|
||||
|
||||
/**
|
||||
* @brief `Ellipsis` / `...`
|
||||
*
|
||||
* `data` is unused.
|
||||
*/
|
||||
const NDIndexType ND_INDEX_TYPE_ELLIPSIS = 3;
|
||||
|
||||
/**
|
||||
* @brief An index used in ndarray indexing
|
||||
*
|
||||
* That is:
|
||||
* ```
|
||||
* my_ndarray[::-1, 3, ..., np.newaxis]
|
||||
* ^^^^ ^ ^^^ ^^^^^^^^^^ each of these is represented by an NDIndex.
|
||||
* ```
|
||||
*/
|
||||
struct NDIndex {
|
||||
/**
|
||||
* @brief Enum tag to specify the type of index.
|
||||
*
|
||||
* Please see the comment of each enum constant.
|
||||
*/
|
||||
NDIndexType type;
|
||||
|
||||
/**
|
||||
* @brief The accompanying data associated with `type`.
|
||||
*
|
||||
* Please see the comment of each enum constant.
|
||||
*/
|
||||
uint8_t* data;
|
||||
};
|
||||
} // namespace
|
||||
|
||||
namespace {
|
||||
namespace ndarray {
|
||||
namespace indexing {
|
||||
/**
|
||||
* @brief Perform ndarray "basic indexing" (https://numpy.org/doc/stable/user/basics.indexing.html#basic-indexing)
|
||||
*
|
||||
* This function is very similar to performing `dst_ndarray = src_ndarray[indices]` in Python.
|
||||
*
|
||||
* This function also does proper assertions on `indices` to check for out of bounds access and more.
|
||||
*
|
||||
* # Notes on `dst_ndarray`
|
||||
* The caller is responsible for allocating space for the resulting ndarray.
|
||||
* Here is what this function expects from `dst_ndarray` when called:
|
||||
* - `dst_ndarray->data` does not have to be initialized.
|
||||
* - `dst_ndarray->itemsize` does not have to be initialized.
|
||||
* - `dst_ndarray->ndims` must be initialized, and it must be equal to the expected `ndims` of the `dst_ndarray` after
|
||||
* indexing `src_ndarray` with `indices`.
|
||||
* - `dst_ndarray->shape` must be allocated, through it can contain uninitialized values.
|
||||
* - `dst_ndarray->strides` must be allocated, through it can contain uninitialized values.
|
||||
* When this function call ends:
|
||||
* - `dst_ndarray->data` is set to `src_ndarray->data`.
|
||||
* - `dst_ndarray->itemsize` is set to `src_ndarray->itemsize`.
|
||||
* - `dst_ndarray->ndims` is unchanged.
|
||||
* - `dst_ndarray->shape` is updated according to how `src_ndarray` is indexed.
|
||||
* - `dst_ndarray->strides` is updated accordingly by how ndarray indexing works.
|
||||
*
|
||||
* @param indices indices to index `src_ndarray`, ordered in the same way you would write them in Python.
|
||||
* @param src_ndarray The NDArray to be indexed.
|
||||
* @param dst_ndarray The resulting NDArray after indexing. Further details in the comments above,
|
||||
*/
|
||||
template<typename SizeT>
|
||||
void index(SizeT num_indices, const NDIndex* indices, const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
|
||||
// Validate `indices`.
|
||||
|
||||
// Expected value of `dst_ndarray->ndims`.
|
||||
SizeT expected_dst_ndims = src_ndarray->ndims;
|
||||
// To check for "too many indices for array: array is ?-dimensional, but ? were indexed"
|
||||
SizeT num_indexed = 0;
|
||||
// There may be ellipsis `...` in `indices`. There can only be 0 or 1 ellipsis.
|
||||
SizeT num_ellipsis = 0;
|
||||
|
||||
for (SizeT i = 0; i < num_indices; i++) {
|
||||
if (indices[i].type == ND_INDEX_TYPE_SINGLE_ELEMENT) {
|
||||
expected_dst_ndims--;
|
||||
num_indexed++;
|
||||
} else if (indices[i].type == ND_INDEX_TYPE_SLICE) {
|
||||
num_indexed++;
|
||||
} else if (indices[i].type == ND_INDEX_TYPE_NEWAXIS) {
|
||||
expected_dst_ndims++;
|
||||
} else if (indices[i].type == ND_INDEX_TYPE_ELLIPSIS) {
|
||||
num_ellipsis++;
|
||||
if (num_ellipsis > 1) {
|
||||
raise_exception(SizeT, EXN_INDEX_ERROR, "an index can only have a single ellipsis ('...')", NO_PARAM,
|
||||
NO_PARAM, NO_PARAM);
|
||||
}
|
||||
} else {
|
||||
__builtin_unreachable();
|
||||
}
|
||||
}
|
||||
|
||||
debug_assert_eq(SizeT, expected_dst_ndims, dst_ndarray->ndims);
|
||||
|
||||
if (src_ndarray->ndims - num_indexed < 0) {
|
||||
raise_exception(SizeT, EXN_INDEX_ERROR,
|
||||
"too many indices for array: array is {0}-dimensional, "
|
||||
"but {1} were indexed",
|
||||
src_ndarray->ndims, num_indices, NO_PARAM);
|
||||
}
|
||||
|
||||
dst_ndarray->data = src_ndarray->data;
|
||||
dst_ndarray->itemsize = src_ndarray->itemsize;
|
||||
|
||||
// Reference code:
|
||||
// https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L652
|
||||
SizeT src_axis = 0;
|
||||
SizeT dst_axis = 0;
|
||||
|
||||
for (int32_t i = 0; i < num_indices; i++) {
|
||||
const NDIndex* index = &indices[i];
|
||||
if (index->type == ND_INDEX_TYPE_SINGLE_ELEMENT) {
|
||||
SizeT input = (SizeT) * ((int32_t*)index->data);
|
||||
|
||||
SizeT k = slice::resolve_index_in_length(src_ndarray->shape[src_axis], input);
|
||||
if (k == -1) {
|
||||
raise_exception(SizeT, EXN_INDEX_ERROR,
|
||||
"index {0} is out of bounds for axis {1} "
|
||||
"with size {2}",
|
||||
input, src_axis, src_ndarray->shape[src_axis]);
|
||||
}
|
||||
|
||||
dst_ndarray->data = static_cast<uint8_t*>(dst_ndarray->data) + k * src_ndarray->strides[src_axis];
|
||||
|
||||
src_axis++;
|
||||
} else if (index->type == ND_INDEX_TYPE_SLICE) {
|
||||
Slice<int32_t>* slice = (Slice<int32_t>*)index->data;
|
||||
|
||||
Range<int32_t> range = slice->indices_checked<SizeT>(src_ndarray->shape[src_axis]);
|
||||
|
||||
dst_ndarray->data = static_cast<uint8_t*>(dst_ndarray->data) + (SizeT)range.start * src_ndarray->strides[src_axis];
|
||||
dst_ndarray->strides[dst_axis] = ((SizeT)range.step) * src_ndarray->strides[src_axis];
|
||||
dst_ndarray->shape[dst_axis] = (SizeT)range.len<SizeT>();
|
||||
|
||||
dst_axis++;
|
||||
src_axis++;
|
||||
} else if (index->type == ND_INDEX_TYPE_NEWAXIS) {
|
||||
dst_ndarray->strides[dst_axis] = 0;
|
||||
dst_ndarray->shape[dst_axis] = 1;
|
||||
|
||||
dst_axis++;
|
||||
} else if (index->type == ND_INDEX_TYPE_ELLIPSIS) {
|
||||
// The number of ':' entries this '...' implies.
|
||||
SizeT ellipsis_size = src_ndarray->ndims - num_indexed;
|
||||
|
||||
for (SizeT j = 0; j < ellipsis_size; j++) {
|
||||
dst_ndarray->strides[dst_axis] = src_ndarray->strides[src_axis];
|
||||
dst_ndarray->shape[dst_axis] = src_ndarray->shape[src_axis];
|
||||
|
||||
dst_axis++;
|
||||
src_axis++;
|
||||
}
|
||||
} else {
|
||||
__builtin_unreachable();
|
||||
}
|
||||
}
|
||||
|
||||
for (; dst_axis < dst_ndarray->ndims; dst_axis++, src_axis++) {
|
||||
dst_ndarray->shape[dst_axis] = src_ndarray->shape[src_axis];
|
||||
dst_ndarray->strides[dst_axis] = src_ndarray->strides[src_axis];
|
||||
}
|
||||
|
||||
debug_assert_eq(SizeT, src_ndarray->ndims, src_axis);
|
||||
debug_assert_eq(SizeT, dst_ndarray->ndims, dst_axis);
|
||||
}
|
||||
} // namespace indexing
|
||||
} // namespace ndarray
|
||||
} // namespace
|
||||
|
||||
extern "C" {
|
||||
using namespace ndarray::indexing;
|
||||
|
||||
void __nac3_ndarray_index(int32_t num_indices,
|
||||
NDIndex* indices,
|
||||
NDArray<int32_t>* src_ndarray,
|
||||
NDArray<int32_t>* dst_ndarray) {
|
||||
index(num_indices, indices, src_ndarray, dst_ndarray);
|
||||
}
|
||||
|
||||
void __nac3_ndarray_index64(int64_t num_indices,
|
||||
NDIndex* indices,
|
||||
NDArray<int64_t>* src_ndarray,
|
||||
NDArray<int64_t>* dst_ndarray) {
|
||||
index(num_indices, indices, src_ndarray, dst_ndarray);
|
||||
}
|
||||
}
|
||||
@ -1,146 +0,0 @@
|
||||
#pragma once
|
||||
|
||||
#include "irrt/int_types.hpp"
|
||||
#include "irrt/ndarray/def.hpp"
|
||||
|
||||
namespace {
|
||||
/**
|
||||
* @brief Helper struct to enumerate through an ndarray *efficiently*.
|
||||
*
|
||||
* Example usage (in pseudo-code):
|
||||
* ```
|
||||
* // Suppose my_ndarray has been initialized, with shape [2, 3] and dtype `double`
|
||||
* NDIter nditer;
|
||||
* nditer.initialize(my_ndarray);
|
||||
* while (nditer.has_element()) {
|
||||
* // This body is run 6 (= my_ndarray.size) times.
|
||||
*
|
||||
* // [0, 0] -> [0, 1] -> [0, 2] -> [1, 0] -> [1, 1] -> [1, 2] -> end
|
||||
* print(nditer.indices);
|
||||
*
|
||||
* // 0 -> 1 -> 2 -> 3 -> 4 -> 5
|
||||
* print(nditer.nth);
|
||||
*
|
||||
* // <1st element> -> <2nd element> -> ... -> <6th element> -> end
|
||||
* print(*((double *) nditer.element))
|
||||
*
|
||||
* nditer.next(); // Go to next element.
|
||||
* }
|
||||
* ```
|
||||
*
|
||||
* Interesting cases:
|
||||
* - If `my_ndarray.ndims` == 0, there is one iteration.
|
||||
* - If `my_ndarray.shape` contains zeroes, there are no iterations.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
struct NDIter {
|
||||
// Information about the ndarray being iterated over.
|
||||
SizeT ndims;
|
||||
SizeT* shape;
|
||||
SizeT* strides;
|
||||
|
||||
/**
|
||||
* @brief The current indices.
|
||||
*
|
||||
* Must be allocated by the caller.
|
||||
*/
|
||||
SizeT* indices;
|
||||
|
||||
/**
|
||||
* @brief The nth (0-based) index of the current indices.
|
||||
*
|
||||
* Initially this is 0.
|
||||
*/
|
||||
SizeT nth;
|
||||
|
||||
/**
|
||||
* @brief Pointer to the current element.
|
||||
*
|
||||
* Initially this points to first element of the ndarray.
|
||||
*/
|
||||
void* element;
|
||||
|
||||
/**
|
||||
* @brief Cache for the product of shape.
|
||||
*
|
||||
* Could be 0 if `shape` has 0s in it.
|
||||
*/
|
||||
SizeT size;
|
||||
|
||||
void initialize(SizeT ndims, SizeT* shape, SizeT* strides, void* element, SizeT* indices) {
|
||||
this->ndims = ndims;
|
||||
this->shape = shape;
|
||||
this->strides = strides;
|
||||
|
||||
this->indices = indices;
|
||||
this->element = element;
|
||||
|
||||
// Compute size
|
||||
this->size = 1;
|
||||
for (SizeT i = 0; i < ndims; i++) {
|
||||
this->size *= shape[i];
|
||||
}
|
||||
|
||||
// `indices` starts on all 0s.
|
||||
for (SizeT axis = 0; axis < ndims; axis++)
|
||||
indices[axis] = 0;
|
||||
nth = 0;
|
||||
}
|
||||
|
||||
void initialize_by_ndarray(NDArray<SizeT>* ndarray, SizeT* indices) {
|
||||
// NOTE: ndarray->data is pointing to the first element, and `NDIter`'s `element` should also point to the first
|
||||
// element as well.
|
||||
this->initialize(ndarray->ndims, ndarray->shape, ndarray->strides, ndarray->data, indices);
|
||||
}
|
||||
|
||||
// Is the current iteration valid?
|
||||
// If true, then `element`, `indices` and `nth` contain details about the current element.
|
||||
bool has_element() { return nth < size; }
|
||||
|
||||
// Go to the next element.
|
||||
void next() {
|
||||
for (SizeT i = 0; i < ndims; i++) {
|
||||
SizeT axis = ndims - i - 1;
|
||||
indices[axis]++;
|
||||
if (indices[axis] >= shape[axis]) {
|
||||
indices[axis] = 0;
|
||||
|
||||
// TODO: There is something called backstrides to speedup iteration.
|
||||
// See https://ajcr.net/stride-guide-part-1/, and
|
||||
// https://docs.scipy.org/doc/numpy-1.13.0/reference/c-api.types-and-structures.html#c.PyArrayIterObject.PyArrayIterObject.backstrides.
|
||||
element = static_cast<void*>(reinterpret_cast<uint8_t*>(element) - strides[axis] * (shape[axis] - 1));
|
||||
} else {
|
||||
element = static_cast<void*>(reinterpret_cast<uint8_t*>(element) + strides[axis]);
|
||||
break;
|
||||
}
|
||||
}
|
||||
nth++;
|
||||
}
|
||||
};
|
||||
} // namespace
|
||||
|
||||
extern "C" {
|
||||
void __nac3_nditer_initialize(NDIter<int32_t>* iter, NDArray<int32_t>* ndarray, int32_t* indices) {
|
||||
iter->initialize_by_ndarray(ndarray, indices);
|
||||
}
|
||||
|
||||
void __nac3_nditer_initialize64(NDIter<int64_t>* iter, NDArray<int64_t>* ndarray, int64_t* indices) {
|
||||
iter->initialize_by_ndarray(ndarray, indices);
|
||||
}
|
||||
|
||||
bool __nac3_nditer_has_element(NDIter<int32_t>* iter) {
|
||||
return iter->has_element();
|
||||
}
|
||||
|
||||
bool __nac3_nditer_has_element64(NDIter<int64_t>* iter) {
|
||||
return iter->has_element();
|
||||
}
|
||||
|
||||
void __nac3_nditer_next(NDIter<int32_t>* iter) {
|
||||
iter->next();
|
||||
}
|
||||
|
||||
void __nac3_nditer_next64(NDIter<int64_t>* iter) {
|
||||
iter->next();
|
||||
}
|
||||
}
|
||||
@ -1,47 +0,0 @@
|
||||
#pragma once
|
||||
|
||||
#include "irrt/debug.hpp"
|
||||
#include "irrt/int_types.hpp"
|
||||
|
||||
namespace {
|
||||
namespace range {
|
||||
template<typename T>
|
||||
T len(T start, T stop, T step) {
|
||||
// Reference:
|
||||
// https://github.com/python/cpython/blob/9dbd12375561a393eaec4b21ee4ac568a407cdb0/Objects/rangeobject.c#L933
|
||||
if (step > 0 && start < stop)
|
||||
return 1 + (stop - 1 - start) / step;
|
||||
else if (step < 0 && start > stop)
|
||||
return 1 + (start - 1 - stop) / (-step);
|
||||
else
|
||||
return 0;
|
||||
}
|
||||
} // namespace range
|
||||
|
||||
/**
|
||||
* @brief A Python range.
|
||||
*/
|
||||
template<typename T>
|
||||
struct Range {
|
||||
T start;
|
||||
T stop;
|
||||
T step;
|
||||
|
||||
/**
|
||||
* @brief Calculate the `len()` of this range.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
T len() {
|
||||
debug_assert(SizeT, step != 0);
|
||||
return range::len(start, stop, step);
|
||||
}
|
||||
};
|
||||
} // namespace
|
||||
|
||||
extern "C" {
|
||||
using namespace range;
|
||||
|
||||
SliceIndex __nac3_range_slice_len(const SliceIndex start, const SliceIndex end, const SliceIndex step) {
|
||||
return len(start, end, step);
|
||||
}
|
||||
}
|
||||
@ -1,145 +1,6 @@
|
||||
#pragma once
|
||||
|
||||
#include "irrt/debug.hpp"
|
||||
#include "irrt/exception.hpp"
|
||||
#include "irrt/int_types.hpp"
|
||||
#include "irrt/math_util.hpp"
|
||||
#include "irrt/range.hpp"
|
||||
|
||||
namespace {
|
||||
namespace slice {
|
||||
/**
|
||||
* @brief Resolve a possibly negative index in a list of a known length.
|
||||
*
|
||||
* Returns -1 if the resolved index is out of the list's bounds.
|
||||
*/
|
||||
template<typename T>
|
||||
T resolve_index_in_length(T length, T index) {
|
||||
T resolved = index < 0 ? length + index : index;
|
||||
if (0 <= resolved && resolved < length) {
|
||||
return resolved;
|
||||
} else {
|
||||
return -1;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Resolve a slice as a range.
|
||||
*
|
||||
* This is equivalent to `range(*slice(start, stop, step).indices(length))` in Python.
|
||||
*/
|
||||
template<typename T>
|
||||
void indices(bool start_defined,
|
||||
T start,
|
||||
bool stop_defined,
|
||||
T stop,
|
||||
bool step_defined,
|
||||
T step,
|
||||
T length,
|
||||
T* range_start,
|
||||
T* range_stop,
|
||||
T* range_step) {
|
||||
// Reference: https://github.com/python/cpython/blob/main/Objects/sliceobject.c#L388
|
||||
*range_step = step_defined ? step : 1;
|
||||
bool step_is_negative = *range_step < 0;
|
||||
|
||||
T lower, upper;
|
||||
if (step_is_negative) {
|
||||
lower = -1;
|
||||
upper = length - 1;
|
||||
} else {
|
||||
lower = 0;
|
||||
upper = length;
|
||||
}
|
||||
|
||||
if (start_defined) {
|
||||
*range_start = start < 0 ? max(lower, start + length) : min(upper, start);
|
||||
} else {
|
||||
*range_start = step_is_negative ? upper : lower;
|
||||
}
|
||||
|
||||
if (stop_defined) {
|
||||
*range_stop = stop < 0 ? max(lower, stop + length) : min(upper, stop);
|
||||
} else {
|
||||
*range_stop = step_is_negative ? lower : upper;
|
||||
}
|
||||
}
|
||||
} // namespace slice
|
||||
|
||||
/**
|
||||
* @brief A Python-like slice with **unresolved** indices.
|
||||
*/
|
||||
template<typename T>
|
||||
struct Slice {
|
||||
bool start_defined;
|
||||
T start;
|
||||
|
||||
bool stop_defined;
|
||||
T stop;
|
||||
|
||||
bool step_defined;
|
||||
T step;
|
||||
|
||||
Slice() { this->reset(); }
|
||||
|
||||
void reset() {
|
||||
this->start_defined = false;
|
||||
this->stop_defined = false;
|
||||
this->step_defined = false;
|
||||
}
|
||||
|
||||
void set_start(T start) {
|
||||
this->start_defined = true;
|
||||
this->start = start;
|
||||
}
|
||||
|
||||
void set_stop(T stop) {
|
||||
this->stop_defined = true;
|
||||
this->stop = stop;
|
||||
}
|
||||
|
||||
void set_step(T step) {
|
||||
this->step_defined = true;
|
||||
this->step = step;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Resolve this slice as a range.
|
||||
*
|
||||
* In Python, this would be `range(*slice(start, stop, step).indices(length))`.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
Range<T> indices(T length) {
|
||||
// Reference:
|
||||
// https://github.com/python/cpython/blob/main/Objects/sliceobject.c#L388
|
||||
debug_assert(SizeT, length >= 0);
|
||||
|
||||
Range<T> result;
|
||||
slice::indices(start_defined, start, stop_defined, stop, step_defined, step, length, &result.start,
|
||||
&result.stop, &result.step);
|
||||
return result;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Like `.indices()` but with assertions.
|
||||
*/
|
||||
template<typename SizeT>
|
||||
Range<T> indices_checked(T length) {
|
||||
// TODO: Switch to `SizeT length`
|
||||
|
||||
if (length < 0) {
|
||||
raise_exception(SizeT, EXN_VALUE_ERROR, "length should not be negative, got {0}", length, NO_PARAM,
|
||||
NO_PARAM);
|
||||
}
|
||||
|
||||
if (this->step_defined && this->step == 0) {
|
||||
raise_exception(SizeT, EXN_VALUE_ERROR, "slice step cannot be zero", NO_PARAM, NO_PARAM, NO_PARAM);
|
||||
}
|
||||
|
||||
return this->indices<SizeT>(length);
|
||||
}
|
||||
};
|
||||
} // namespace
|
||||
|
||||
extern "C" {
|
||||
SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
|
||||
@ -153,4 +14,15 @@ SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
|
||||
}
|
||||
return i;
|
||||
}
|
||||
|
||||
SliceIndex __nac3_range_slice_len(const SliceIndex start, const SliceIndex end, const SliceIndex step) {
|
||||
SliceIndex diff = end - start;
|
||||
if (diff > 0 && step > 0) {
|
||||
return ((diff - 1) / step) + 1;
|
||||
} else if (diff < 0 && step < 0) {
|
||||
return ((diff + 1) / step) + 1;
|
||||
} else {
|
||||
return 0;
|
||||
}
|
||||
}
|
||||
} // namespace
|
||||
4
nac3core/irrt/tracert.cpp
Normal file
4
nac3core/irrt/tracert.cpp
Normal file
@ -0,0 +1,4 @@
|
||||
extern "C" {
|
||||
// stdio.h
|
||||
int printf(const char *format, ...);
|
||||
} // extern "C"
|
||||
File diff suppressed because it is too large
Load Diff
@ -32,10 +32,9 @@ use super::{
|
||||
gen_for_callback_incrementing, gen_if_callback, gen_if_else_expr_callback, gen_raise,
|
||||
gen_var,
|
||||
},
|
||||
types::{ndarray::NDArrayType, ListType},
|
||||
types::ListType,
|
||||
values::{
|
||||
ndarray::{NDArrayValue, RustNDIndex},
|
||||
ArrayLikeIndexer, ArrayLikeValue, ListValue, ProxyValue, RangeValue,
|
||||
ArrayLikeIndexer, ArrayLikeValue, ListValue, NDArrayValue, ProxyValue, RangeValue,
|
||||
TypedArrayLikeAccessor, UntypedArrayLikeAccessor,
|
||||
},
|
||||
CodeGenContext, CodeGenTask, CodeGenerator,
|
||||
@ -43,8 +42,8 @@ use super::{
|
||||
use crate::{
|
||||
symbol_resolver::{SymbolValue, ValueEnum},
|
||||
toplevel::{
|
||||
helper::{extract_ndims, PrimDef},
|
||||
numpy::unpack_ndarray_var_tys,
|
||||
helper::PrimDef,
|
||||
numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
|
||||
DefinitionId, TopLevelDef,
|
||||
},
|
||||
typecheck::{
|
||||
@ -1554,6 +1553,8 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
|
||||
} else if ty1.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id())
|
||||
|| ty2.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id())
|
||||
{
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
let is_ndarray1 = ty1.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id());
|
||||
let is_ndarray2 = ty2.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id());
|
||||
|
||||
@ -1563,10 +1564,21 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
|
||||
|
||||
assert!(ctx.unifier.unioned(ndarray_dtype1, ndarray_dtype2));
|
||||
|
||||
let left_val = NDArrayType::from_unifier_type(generator, ctx, ty1)
|
||||
.map_value(left_val.into_pointer_value(), None);
|
||||
let right_val = NDArrayType::from_unifier_type(generator, ctx, ty2)
|
||||
.map_value(right_val.into_pointer_value(), None);
|
||||
let llvm_ndarray_dtype1 = ctx.get_llvm_type(generator, ndarray_dtype1);
|
||||
let llvm_ndarray_dtype2 = ctx.get_llvm_type(generator, ndarray_dtype2);
|
||||
|
||||
let left_val = NDArrayValue::from_pointer_value(
|
||||
left_val.into_pointer_value(),
|
||||
llvm_ndarray_dtype1,
|
||||
llvm_usize,
|
||||
None,
|
||||
);
|
||||
let right_val = NDArrayValue::from_pointer_value(
|
||||
right_val.into_pointer_value(),
|
||||
llvm_ndarray_dtype2,
|
||||
llvm_usize,
|
||||
None,
|
||||
);
|
||||
|
||||
let res = if op.base == Operator::MatMult {
|
||||
// MatMult is the only binop which is not an elementwise op
|
||||
@ -1615,12 +1627,13 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
|
||||
} else {
|
||||
let (ndarray_dtype, _) =
|
||||
unpack_ndarray_var_tys(&mut ctx.unifier, if is_ndarray1 { ty1 } else { ty2 });
|
||||
let ndarray_val =
|
||||
NDArrayType::from_unifier_type(generator, ctx, if is_ndarray1 { ty1 } else { ty2 })
|
||||
.map_value(
|
||||
if is_ndarray1 { left_val } else { right_val }.into_pointer_value(),
|
||||
None,
|
||||
);
|
||||
let llvm_ndarray_dtype = ctx.get_llvm_type(generator, ndarray_dtype);
|
||||
let ndarray_val = NDArrayValue::from_pointer_value(
|
||||
if is_ndarray1 { left_val } else { right_val }.into_pointer_value(),
|
||||
llvm_ndarray_dtype,
|
||||
llvm_usize,
|
||||
None,
|
||||
);
|
||||
let res = numpy::ndarray_elementwise_binop_impl(
|
||||
generator,
|
||||
ctx,
|
||||
@ -1808,10 +1821,16 @@ pub fn gen_unaryop_expr_with_values<'ctx, G: CodeGenerator>(
|
||||
_ => val.into(),
|
||||
}
|
||||
} else if ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) {
|
||||
let llvm_ndarray_ty = NDArrayType::from_unifier_type(generator, ctx, ty);
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
let (ndarray_dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
|
||||
let llvm_ndarray_dtype = ctx.get_llvm_type(generator, ndarray_dtype);
|
||||
|
||||
let val = llvm_ndarray_ty.map_value(val.into_pointer_value(), None);
|
||||
let val = NDArrayValue::from_pointer_value(
|
||||
val.into_pointer_value(),
|
||||
llvm_ndarray_dtype,
|
||||
llvm_usize,
|
||||
None,
|
||||
);
|
||||
|
||||
// ndarray uses `~` rather than `not` to perform elementwise inversion, convert it before
|
||||
// passing it to the elementwise codegen function
|
||||
@ -1885,6 +1904,8 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
|
||||
if left_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id())
|
||||
|| right_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id())
|
||||
{
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
let (Some(left_ty), lhs) = left else { codegen_unreachable!(ctx) };
|
||||
let (Some(right_ty), rhs) = comparators[0] else { codegen_unreachable!(ctx) };
|
||||
let op = ops[0];
|
||||
@ -1900,8 +1921,14 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
|
||||
|
||||
assert!(ctx.unifier.unioned(ndarray_dtype1, ndarray_dtype2));
|
||||
|
||||
let left_val = NDArrayType::from_unifier_type(generator, ctx, left_ty)
|
||||
.map_value(lhs.into_pointer_value(), None);
|
||||
let llvm_ndarray_dtype1 = ctx.get_llvm_type(generator, ndarray_dtype1);
|
||||
|
||||
let left_val = NDArrayValue::from_pointer_value(
|
||||
lhs.into_pointer_value(),
|
||||
llvm_ndarray_dtype1,
|
||||
llvm_usize,
|
||||
None,
|
||||
);
|
||||
let res = numpy::ndarray_elementwise_binop_impl(
|
||||
generator,
|
||||
ctx,
|
||||
@ -2522,7 +2549,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ty: Type,
|
||||
ndims_ty: Type,
|
||||
ndims: Type,
|
||||
v: NDArrayValue<'ctx>,
|
||||
slice: &Expr<Option<Type>>,
|
||||
) -> Result<Option<ValueEnum<'ctx>>, String> {
|
||||
@ -2530,7 +2557,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
|
||||
let llvm_i32 = ctx.ctx.i32_type();
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
let TypeEnum::TLiteral { values, .. } = &*ctx.unifier.get_ty_immutable(ndims_ty) else {
|
||||
let TypeEnum::TLiteral { values, .. } = &*ctx.unifier.get_ty_immutable(ndims) else {
|
||||
codegen_unreachable!(ctx)
|
||||
};
|
||||
|
||||
@ -2563,6 +2590,14 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
|
||||
_ => 1,
|
||||
};
|
||||
|
||||
let ndarray_ndims_ty = ctx.unifier.get_fresh_literal(
|
||||
ndims.iter().map(|v| SymbolValue::U64(v - subscripted_dims)).collect(),
|
||||
None,
|
||||
);
|
||||
let ndarray_ty =
|
||||
make_ndarray_ty(&mut ctx.unifier, &ctx.primitives, Some(ty), Some(ndarray_ndims_ty));
|
||||
let llvm_pndarray_t = ctx.get_llvm_type(generator, ndarray_ty).into_pointer_type();
|
||||
let llvm_ndarray_t = llvm_pndarray_t.get_element_type().into_struct_type();
|
||||
let llvm_ndarray_data_t = ctx.get_llvm_type(generator, ty).as_basic_type_enum();
|
||||
let sizeof_elem = llvm_ndarray_data_t.size_of().unwrap();
|
||||
|
||||
@ -2754,15 +2789,31 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
|
||||
|
||||
_ => {
|
||||
// Accessing an element from a multi-dimensional `ndarray`
|
||||
let Some(index_addr) = make_indices_arr(generator, ctx)? else { return Ok(None) };
|
||||
|
||||
let num_dims = extract_ndims(&ctx.unifier, ndims_ty) - 1;
|
||||
let Some(index_addr) = make_indices_arr(generator, ctx)? else { return Ok(None) };
|
||||
|
||||
// Create a new array, remove the top dimension from the dimension-size-list, and copy the
|
||||
// elements over
|
||||
let ndarray =
|
||||
NDArrayType::new(generator, ctx.ctx, llvm_ndarray_data_t, Some(num_dims))
|
||||
.construct_uninitialized(generator, ctx, None);
|
||||
let subscripted_ndarray =
|
||||
generator.gen_var_alloc(ctx, llvm_ndarray_t.into(), None)?;
|
||||
let ndarray = NDArrayValue::from_pointer_value(
|
||||
subscripted_ndarray,
|
||||
llvm_ndarray_data_t,
|
||||
llvm_usize,
|
||||
None,
|
||||
);
|
||||
|
||||
let num_dims = v.load_ndims(ctx);
|
||||
ndarray.store_ndims(
|
||||
ctx,
|
||||
generator,
|
||||
ctx.builder
|
||||
.build_int_sub(num_dims, llvm_usize.const_int(1, false), "")
|
||||
.unwrap(),
|
||||
);
|
||||
|
||||
let ndarray_num_dims = ndarray.load_ndims(ctx);
|
||||
ndarray.create_shape(ctx, llvm_usize, ndarray_num_dims);
|
||||
|
||||
let ndarray_num_dims = ctx
|
||||
.builder
|
||||
@ -2791,7 +2842,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
|
||||
llvm_i1.const_zero(),
|
||||
);
|
||||
|
||||
let ndarray_num_elems = ndarray::call_ndarray_calc_size(
|
||||
let ndarray_num_elems = call_ndarray_calc_size(
|
||||
generator,
|
||||
ctx,
|
||||
&ndarray.shape().as_slice_value(ctx, generator),
|
||||
@ -2801,7 +2852,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
|
||||
.builder
|
||||
.build_int_z_extend_or_bit_cast(ndarray_num_elems, sizeof_elem.get_type(), "")
|
||||
.unwrap();
|
||||
unsafe { ndarray.create_data(generator, ctx) };
|
||||
ndarray.create_data(ctx, llvm_ndarray_data_t, ndarray_num_elems);
|
||||
|
||||
let v_data_src_ptr = v.data().ptr_offset(ctx, generator, &index_addr, None);
|
||||
call_memcpy_generic(
|
||||
@ -3486,22 +3537,19 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
|
||||
v.data().get(ctx, generator, &index, None).into()
|
||||
}
|
||||
}
|
||||
TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
|
||||
let Some(ndarray) = generator.gen_expr(ctx, value)? else {
|
||||
TypeEnum::TObj { obj_id, params, .. } if *obj_id == PrimDef::NDArray.id() => {
|
||||
let (ty, ndims) = params.iter().map(|(_, ty)| ty).collect_tuple().unwrap();
|
||||
let llvm_ty = ctx.get_llvm_type(generator, *ty);
|
||||
|
||||
let v = if let Some(v) = generator.gen_expr(ctx, value)? {
|
||||
v.to_basic_value_enum(ctx, generator, value.custom.unwrap())?
|
||||
.into_pointer_value()
|
||||
} else {
|
||||
return Ok(None);
|
||||
};
|
||||
let v = NDArrayValue::from_pointer_value(v, llvm_ty, usize, None);
|
||||
|
||||
let ndarray_ty = value.custom.unwrap();
|
||||
let ndarray = ndarray.to_basic_value_enum(ctx, generator, ndarray_ty)?;
|
||||
let ndarray = NDArrayType::from_unifier_type(generator, ctx, ndarray_ty)
|
||||
.map_value(ndarray.into_pointer_value(), None);
|
||||
|
||||
let indices = RustNDIndex::from_subscript_expr(generator, ctx, slice)?;
|
||||
let result = ndarray
|
||||
.index(generator, ctx, &indices)
|
||||
.split_unsized(generator, ctx)
|
||||
.to_basic_value_enum();
|
||||
return Ok(Some(ValueEnum::Dynamic(result)));
|
||||
return gen_ndarray_subscript_expr(generator, ctx, *ty, *ndims, v, slice);
|
||||
}
|
||||
TypeEnum::TTuple { .. } => {
|
||||
let index: u32 =
|
||||
@ -3550,97 +3598,3 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
|
||||
_ => unimplemented!(),
|
||||
}))
|
||||
}
|
||||
|
||||
/// Creates a function in the current module and inserts a `call` instruction into the LLVM IR.
|
||||
#[allow(clippy::too_many_arguments)]
|
||||
pub fn create_fn_and_call<'ctx>(
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
fn_name: &str,
|
||||
ret_type: Option<BasicTypeEnum<'ctx>>,
|
||||
params: &[BasicTypeEnum<'ctx>],
|
||||
args: &[BasicValueEnum<'ctx>],
|
||||
is_var_args: bool,
|
||||
call_value_name: Option<&str>,
|
||||
configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
|
||||
) -> Option<BasicValueEnum<'ctx>> {
|
||||
let intrinsic_fn = ctx.module.get_function(fn_name).unwrap_or_else(|| {
|
||||
let params = params.iter().copied().map(BasicTypeEnum::into).collect_vec();
|
||||
let fn_type = if let Some(ret_type) = ret_type {
|
||||
ret_type.fn_type(params.as_slice(), is_var_args)
|
||||
} else {
|
||||
ctx.ctx.void_type().fn_type(params.as_slice(), is_var_args)
|
||||
};
|
||||
|
||||
ctx.module.add_function(fn_name, fn_type, None)
|
||||
});
|
||||
|
||||
if let Some(configure) = configure {
|
||||
configure(&intrinsic_fn);
|
||||
}
|
||||
|
||||
let args = args.iter().copied().map(BasicValueEnum::into).collect_vec();
|
||||
ctx.builder
|
||||
.build_call(intrinsic_fn, args.as_slice(), call_value_name.unwrap_or_default())
|
||||
.map(CallSiteValue::try_as_basic_value)
|
||||
.map(Either::left)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Creates a function in the current module and inserts a `call` instruction into the LLVM IR.
|
||||
///
|
||||
/// This is a wrapper around [`create_fn_and_call`] for non-vararg function. This function allows
|
||||
/// parameters and arguments to be specified as tuples to better indicate the expected type and
|
||||
/// actual value of each parameter-argument pair of the call.
|
||||
pub fn create_and_call_function<'ctx>(
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
fn_name: &str,
|
||||
ret_type: Option<BasicTypeEnum<'ctx>>,
|
||||
params: &[(BasicTypeEnum<'ctx>, BasicValueEnum<'ctx>)],
|
||||
value_name: Option<&str>,
|
||||
configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
|
||||
) -> Option<BasicValueEnum<'ctx>> {
|
||||
let param_tys = params.iter().map(|(ty, _)| ty).copied().map(BasicTypeEnum::into).collect_vec();
|
||||
let arg_values =
|
||||
params.iter().map(|(_, value)| value).copied().map(BasicValueEnum::into).collect_vec();
|
||||
|
||||
create_fn_and_call(
|
||||
ctx,
|
||||
fn_name,
|
||||
ret_type,
|
||||
param_tys.as_slice(),
|
||||
arg_values.as_slice(),
|
||||
false,
|
||||
value_name,
|
||||
configure,
|
||||
)
|
||||
}
|
||||
|
||||
/// Creates a function in the current module and inserts a `call` instruction into the LLVM IR.
|
||||
///
|
||||
/// This is a wrapper around [`create_fn_and_call`] for non-vararg function. This function allows
|
||||
/// only arguments to be specified and performs inference for the parameter types of the function
|
||||
/// using [`BasicValueEnum::get_type`] on the arguments.
|
||||
///
|
||||
/// This function is recommended if it is known that all function arguments match the parameter
|
||||
/// types of the invoked function.
|
||||
pub fn infer_and_call_function<'ctx>(
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
fn_name: &str,
|
||||
ret_type: Option<BasicTypeEnum<'ctx>>,
|
||||
args: &[BasicValueEnum<'ctx>],
|
||||
value_name: Option<&str>,
|
||||
configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
|
||||
) -> Option<BasicValueEnum<'ctx>> {
|
||||
let param_tys = args.iter().map(BasicValueEnum::get_type).collect_vec();
|
||||
|
||||
create_fn_and_call(
|
||||
ctx,
|
||||
fn_name,
|
||||
ret_type,
|
||||
param_tys.as_slice(),
|
||||
args,
|
||||
false,
|
||||
value_name,
|
||||
configure,
|
||||
)
|
||||
}
|
||||
|
||||
@ -1,8 +1,11 @@
|
||||
use std::iter::once;
|
||||
|
||||
use inkwell::{
|
||||
attributes::{Attribute, AttributeLoc},
|
||||
values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue},
|
||||
values::{BasicValue, BasicValueEnum, CallSiteValue, FloatValue, IntValue},
|
||||
AddressSpace,
|
||||
};
|
||||
use itertools::Either;
|
||||
use itertools::{Either, Itertools};
|
||||
|
||||
use super::CodeGenContext;
|
||||
|
||||
@ -20,7 +23,7 @@ use super::CodeGenContext;
|
||||
/// These will be used unless other attributes are specified
|
||||
/// * `$(,$args:ident)*`: Operands of the extern function
|
||||
/// The data type of these operands will be set to `FloatValue`
|
||||
///
|
||||
///
|
||||
macro_rules! generate_extern_fn {
|
||||
("unary", $fn_name:ident, $extern_fn:literal) => {
|
||||
generate_extern_fn!($fn_name, $extern_fn, arg, "mustprogress", "nofree", "nounwind", "willreturn", "writeonly");
|
||||
@ -191,3 +194,49 @@ generate_linalg_extern_fn!(call_np_linalg_det, "np_linalg_det", 2);
|
||||
generate_linalg_extern_fn!(call_sp_linalg_lu, "sp_linalg_lu", 3);
|
||||
generate_linalg_extern_fn!(call_sp_linalg_schur, "sp_linalg_schur", 3);
|
||||
generate_linalg_extern_fn!(call_sp_linalg_hessenberg, "sp_linalg_hessenberg", 3);
|
||||
|
||||
/// Invokes the `printf` function.
|
||||
pub fn call_printf<'ctx>(
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
format: &str,
|
||||
args: &[BasicValueEnum<'ctx>],
|
||||
) -> IntValue<'ctx> {
|
||||
const FN_NAME: &str = "printf";
|
||||
|
||||
let llvm_i8 = ctx.ctx.i8_type();
|
||||
let llvm_i32 = ctx.ctx.i32_type();
|
||||
let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
|
||||
|
||||
let extern_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
|
||||
let fn_type = llvm_i32.fn_type(&[llvm_pi8.into()], true);
|
||||
let func = ctx.module.add_function(FN_NAME, fn_type, None);
|
||||
for attr in ["nofree", "nounwind"] {
|
||||
func.add_attribute(
|
||||
AttributeLoc::Function,
|
||||
ctx.ctx.create_enum_attribute(Attribute::get_named_enum_kind_id(attr), 0),
|
||||
);
|
||||
}
|
||||
|
||||
func
|
||||
});
|
||||
|
||||
let pformat = ctx
|
||||
.builder
|
||||
.build_global_string_ptr(&format!("{format}\0"), "")
|
||||
.map(|v| v.as_basic_value_enum())
|
||||
.map(BasicValueEnum::into_pointer_value)
|
||||
.unwrap();
|
||||
|
||||
let fn_args = once(&pformat.as_basic_value_enum())
|
||||
.chain(args)
|
||||
.copied()
|
||||
.map(BasicValueEnum::into)
|
||||
.collect_vec();
|
||||
|
||||
ctx.builder
|
||||
.build_call(extern_fn, fn_args.as_slice(), "")
|
||||
.map(CallSiteValue::try_as_basic_value)
|
||||
.map(|v| v.map_left(BasicValueEnum::into_int_value))
|
||||
.map(Either::unwrap_left)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
@ -13,13 +13,12 @@ use super::{CodeGenContext, CodeGenerator};
|
||||
use crate::{symbol_resolver::SymbolResolver, typecheck::typedef::Type};
|
||||
pub use list::*;
|
||||
pub use math::*;
|
||||
pub use range::*;
|
||||
pub use ndarray::*;
|
||||
pub use slice::*;
|
||||
|
||||
mod list;
|
||||
mod math;
|
||||
pub mod ndarray;
|
||||
mod range;
|
||||
mod ndarray;
|
||||
mod slice;
|
||||
|
||||
#[must_use]
|
||||
@ -61,27 +60,6 @@ pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver)
|
||||
irrt_mod
|
||||
}
|
||||
|
||||
/// Returns the name of a function which contains variants for 32-bit and 64-bit `size_t`.
|
||||
///
|
||||
/// - When [`TypeContext::size_type`] is 32-bits, the function name is `fn_name}`.
|
||||
/// - When [`TypeContext::size_type`] is 64-bits, the function name is `{fn_name}64`.
|
||||
#[must_use]
|
||||
pub fn get_usize_dependent_function_name<G: CodeGenerator + ?Sized>(
|
||||
generator: &G,
|
||||
ctx: &CodeGenContext<'_, '_>,
|
||||
name: &str,
|
||||
) -> String {
|
||||
let mut name = name.to_owned();
|
||||
match generator.get_size_type(ctx.ctx).get_bit_width() {
|
||||
32 => {}
|
||||
64 => name.push_str("64"),
|
||||
bit_width => {
|
||||
panic!("Unsupported int type bit width {bit_width}, must be either 32-bits or 64-bits")
|
||||
}
|
||||
}
|
||||
name
|
||||
}
|
||||
|
||||
/// NOTE: the output value of the end index of this function should be compared ***inclusively***,
|
||||
/// because python allows `a[2::-1]`, whose semantic is `[a[2], a[1], a[0]]`, which is equivalent to
|
||||
/// NO numeric slice in python.
|
||||
|
||||
@ -10,18 +10,11 @@ use crate::codegen::{
|
||||
macros::codegen_unreachable,
|
||||
stmt::gen_for_callback_incrementing,
|
||||
values::{
|
||||
ndarray::NDArrayValue, ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue,
|
||||
TypedArrayLikeAccessor, TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
|
||||
ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, NDArrayValue, 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.
|
||||
@ -84,7 +77,7 @@ where
|
||||
/// `NDArray`.
|
||||
pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
index: IntValue<'ctx>,
|
||||
ndarray: NDArrayValue<'ctx>,
|
||||
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
|
||||
@ -208,8 +201,8 @@ where
|
||||
/// `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, '_>,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ndarray: NDArrayValue<'ctx>,
|
||||
indices: &Index,
|
||||
) -> IntValue<'ctx>
|
||||
@ -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);
|
||||
}
|
||||
@ -1,42 +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()
|
||||
}
|
||||
@ -1,6 +1,8 @@
|
||||
use inkwell::values::{BasicValueEnum, CallSiteValue, IntValue};
|
||||
use inkwell::{
|
||||
values::{BasicValueEnum, CallSiteValue, IntValue},
|
||||
IntPredicate,
|
||||
};
|
||||
use itertools::Either;
|
||||
|
||||
use nac3parser::ast::Expr;
|
||||
|
||||
use crate::{
|
||||
@ -37,3 +39,38 @@ pub fn handle_slice_index_bound<'ctx, G: CodeGenerator>(
|
||||
.unwrap(),
|
||||
))
|
||||
}
|
||||
|
||||
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()
|
||||
}
|
||||
|
||||
@ -201,49 +201,6 @@ 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 +343,3 @@ 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()
|
||||
}
|
||||
|
||||
@ -30,11 +30,7 @@ use nac3parser::ast::{Location, Stmt, StrRef};
|
||||
|
||||
use crate::{
|
||||
symbol_resolver::{StaticValue, SymbolResolver},
|
||||
toplevel::{
|
||||
helper::{extract_ndims, PrimDef},
|
||||
numpy::unpack_ndarray_var_tys,
|
||||
TopLevelContext, TopLevelDef,
|
||||
},
|
||||
toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, TopLevelContext, TopLevelDef},
|
||||
typecheck::{
|
||||
type_inferencer::{CodeLocation, PrimitiveStore},
|
||||
typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
|
||||
@ -42,7 +38,8 @@ use crate::{
|
||||
};
|
||||
use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
|
||||
pub use generator::{CodeGenerator, DefaultCodeGenerator};
|
||||
use types::{ndarray::NDArrayType, ListType, ProxyType, RangeType};
|
||||
use tracert::{TraceRuntimeConfig, TraceRuntimeState};
|
||||
use types::{ListType, NDArrayType, ProxyType, RangeType};
|
||||
|
||||
pub mod builtin_fns;
|
||||
pub mod concrete_type;
|
||||
@ -53,6 +50,7 @@ pub mod irrt;
|
||||
pub mod llvm_intrinsics;
|
||||
pub mod numpy;
|
||||
pub mod stmt;
|
||||
pub mod tracert;
|
||||
pub mod types;
|
||||
pub mod values;
|
||||
|
||||
@ -224,6 +222,8 @@ pub struct CodeGenContext<'ctx, 'a> {
|
||||
/// See [`need_sret`].
|
||||
pub need_sret: bool,
|
||||
|
||||
pub tracert_state: Option<TraceRuntimeState>,
|
||||
|
||||
/// The current source location.
|
||||
pub current_loc: Location,
|
||||
}
|
||||
@ -271,6 +271,8 @@ pub struct WorkerRegistry {
|
||||
|
||||
/// LLVM-related options for code generation.
|
||||
pub llvm_options: CodeGenLLVMOptions,
|
||||
|
||||
tracert_config: TraceRuntimeConfig,
|
||||
}
|
||||
|
||||
impl WorkerRegistry {
|
||||
@ -280,6 +282,7 @@ impl WorkerRegistry {
|
||||
generators: Vec<Box<G>>,
|
||||
top_level_ctx: Arc<TopLevelContext>,
|
||||
llvm_options: &CodeGenLLVMOptions,
|
||||
tracert_config: &TraceRuntimeConfig,
|
||||
f: &Arc<WithCall>,
|
||||
) -> (Arc<WorkerRegistry>, Vec<thread::JoinHandle<()>>) {
|
||||
let (sender, receiver) = unbounded();
|
||||
@ -301,6 +304,7 @@ impl WorkerRegistry {
|
||||
wait_condvar,
|
||||
top_level_ctx,
|
||||
llvm_options: llvm_options.clone(),
|
||||
tracert_config: tracert_config.clone(),
|
||||
});
|
||||
|
||||
let mut handles = Vec::new();
|
||||
@ -514,13 +518,12 @@ 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 (dtype, _) = unpack_ndarray_var_tys(unifier, ty);
|
||||
let element_type = get_llvm_type(
|
||||
ctx, module, generator, unifier, top_level, type_cache, dtype,
|
||||
);
|
||||
|
||||
NDArrayType::new(generator, ctx, element_type, Some(ndims)).as_base_type().into()
|
||||
NDArrayType::new(generator, ctx, element_type).as_base_type().into()
|
||||
}
|
||||
|
||||
_ => unreachable!(
|
||||
@ -985,6 +988,13 @@ pub fn gen_func_impl<
|
||||
unifier,
|
||||
static_value_store,
|
||||
need_sret: has_sret,
|
||||
tracert_state: if cfg!(feature = "tracing")
|
||||
|| registry.tracert_config.enabled_tags.is_empty()
|
||||
{
|
||||
None
|
||||
} else {
|
||||
Some(TraceRuntimeState::create(registry.tracert_config.clone()))
|
||||
},
|
||||
current_loc: Location::default(),
|
||||
debug_info: (dibuilder, compile_unit, func_scope.as_debug_info_scope()),
|
||||
};
|
||||
@ -1124,106 +1134,3 @@ 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()
|
||||
}
|
||||
|
||||
@ -3,25 +3,21 @@ use inkwell::{
|
||||
values::{BasicValue, BasicValueEnum, IntValue, PointerValue},
|
||||
AddressSpace, IntPredicate, OptimizationLevel,
|
||||
};
|
||||
use itertools::Itertools;
|
||||
|
||||
use nac3parser::ast::{Operator, StrRef};
|
||||
|
||||
use super::{
|
||||
expr::gen_binop_expr_with_values,
|
||||
irrt::{
|
||||
calculate_len_for_slice_range,
|
||||
ndarray::{
|
||||
call_ndarray_calc_broadcast, call_ndarray_calc_broadcast_index,
|
||||
call_ndarray_calc_nd_indices, call_ndarray_calc_size,
|
||||
},
|
||||
calculate_len_for_slice_range, call_ndarray_calc_broadcast,
|
||||
call_ndarray_calc_broadcast_index, call_ndarray_calc_nd_indices, call_ndarray_calc_size,
|
||||
},
|
||||
llvm_intrinsics::{self, call_memcpy_generic},
|
||||
macros::codegen_unreachable,
|
||||
stmt::{gen_for_callback_incrementing, gen_for_range_callback, gen_if_else_expr_callback},
|
||||
types::{ndarray::NDArrayType, ListType, ProxyType},
|
||||
types::{ListType, NDArrayType, ProxyType},
|
||||
values::{
|
||||
ndarray::NDArrayValue, ArrayLikeIndexer, ArrayLikeValue, ListValue, ProxyValue,
|
||||
ArrayLikeIndexer, ArrayLikeValue, ListValue, NDArrayValue, ProxyValue,
|
||||
TypedArrayLikeAccessor, TypedArrayLikeAdapter, TypedArrayLikeMutator,
|
||||
UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
|
||||
},
|
||||
@ -29,13 +25,39 @@ use super::{
|
||||
};
|
||||
use crate::{
|
||||
symbol_resolver::ValueEnum,
|
||||
toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId},
|
||||
toplevel::{
|
||||
helper::{arraylike_flatten_element_type, PrimDef},
|
||||
numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
|
||||
DefinitionId,
|
||||
},
|
||||
typecheck::{
|
||||
magic_methods::Binop,
|
||||
typedef::{FunSignature, Type, TypeEnum},
|
||||
},
|
||||
};
|
||||
|
||||
/// Creates an uninitialized `NDArray` instance.
|
||||
fn create_ndarray_uninitialized<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
elem_ty: Type,
|
||||
) -> Result<NDArrayValue<'ctx>, String> {
|
||||
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
let ndarray_ty = make_ndarray_ty(&mut ctx.unifier, &ctx.primitives, Some(elem_ty), None);
|
||||
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
let llvm_ndarray_t = ctx
|
||||
.get_llvm_type(generator, ndarray_ty)
|
||||
.into_pointer_type()
|
||||
.get_element_type()
|
||||
.into_struct_type();
|
||||
|
||||
let ndarray = generator.gen_var_alloc(ctx, llvm_ndarray_t.into(), None)?;
|
||||
|
||||
Ok(NDArrayValue::from_pointer_value(ndarray, llvm_elem_ty, llvm_usize, None))
|
||||
}
|
||||
|
||||
/// Creates an `NDArray` instance from a dynamic shape.
|
||||
///
|
||||
/// * `elem_ty` - The element type of the `NDArray`.
|
||||
@ -61,7 +83,6 @@ where
|
||||
) -> Result<IntValue<'ctx>, String>,
|
||||
{
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
|
||||
// Assert that all dimensions are non-negative
|
||||
let shape_len = shape_len_fn(generator, ctx, shape)?;
|
||||
@ -94,17 +115,20 @@ where
|
||||
ctx.current_loc,
|
||||
);
|
||||
|
||||
// TODO: Disallow shape > u32_MAX
|
||||
// TODO: Disallow dim_sz > u32_MAX
|
||||
|
||||
Ok(())
|
||||
},
|
||||
llvm_usize.const_int(1, false),
|
||||
)?;
|
||||
|
||||
let num_dims = shape_len_fn(generator, ctx, shape)?;
|
||||
let ndarray = create_ndarray_uninitialized(generator, ctx, elem_ty)?;
|
||||
|
||||
let ndarray = NDArrayType::new(generator, ctx.ctx, llvm_elem_ty, None)
|
||||
.construct_dyn_ndims(generator, ctx, num_dims, None);
|
||||
let num_dims = shape_len_fn(generator, ctx, shape)?;
|
||||
ndarray.store_ndims(ctx, generator, num_dims);
|
||||
|
||||
let ndarray_num_dims = ndarray.load_ndims(ctx);
|
||||
ndarray.create_shape(ctx, llvm_usize, ndarray_num_dims);
|
||||
|
||||
// Copy the dimension sizes from shape to ndarray.dims
|
||||
let shape_len = shape_len_fn(generator, ctx, shape)?;
|
||||
@ -129,7 +153,7 @@ where
|
||||
llvm_usize.const_int(1, false),
|
||||
)?;
|
||||
|
||||
unsafe { ndarray.create_data(generator, ctx) };
|
||||
let ndarray = ndarray_init_data(generator, ctx, elem_ty, ndarray);
|
||||
|
||||
Ok(ndarray)
|
||||
}
|
||||
@ -162,18 +186,57 @@ pub fn create_ndarray_const_shape<'ctx, G: CodeGenerator + ?Sized>(
|
||||
ctx.current_loc,
|
||||
);
|
||||
|
||||
// TODO: Disallow shape > u32_MAX
|
||||
// TODO: Disallow dim_sz > u32_MAX
|
||||
}
|
||||
|
||||
let llvm_dtype = ctx.get_llvm_type(generator, elem_ty);
|
||||
let ndarray = create_ndarray_uninitialized(generator, ctx, elem_ty)?;
|
||||
|
||||
let ndarray = NDArrayType::new(generator, ctx.ctx, llvm_dtype, Some(shape.len() as u64))
|
||||
.construct_dyn_shape(generator, ctx, shape, None);
|
||||
unsafe { ndarray.create_data(generator, ctx) };
|
||||
let num_dims = llvm_usize.const_int(shape.len() as u64, false);
|
||||
ndarray.store_ndims(ctx, generator, num_dims);
|
||||
|
||||
let ndarray_num_dims = ndarray.load_ndims(ctx);
|
||||
ndarray.create_shape(ctx, llvm_usize, ndarray_num_dims);
|
||||
|
||||
for (i, &shape_dim) in shape.iter().enumerate() {
|
||||
let shape_dim = ctx.builder.build_int_z_extend(shape_dim, llvm_usize, "").unwrap();
|
||||
let ndarray_dim = unsafe {
|
||||
ndarray.shape().ptr_offset_unchecked(
|
||||
ctx,
|
||||
generator,
|
||||
&llvm_usize.const_int(i as u64, true),
|
||||
None,
|
||||
)
|
||||
};
|
||||
|
||||
ctx.builder.build_store(ndarray_dim, shape_dim).unwrap();
|
||||
}
|
||||
|
||||
let ndarray = ndarray_init_data(generator, ctx, elem_ty, ndarray);
|
||||
|
||||
Ok(ndarray)
|
||||
}
|
||||
|
||||
/// Initializes the `data` field of [`NDArrayValue`] based on the `ndims` and `dim_sz` fields.
|
||||
fn ndarray_init_data<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
elem_ty: Type,
|
||||
ndarray: NDArrayValue<'ctx>,
|
||||
) -> NDArrayValue<'ctx> {
|
||||
let llvm_ndarray_data_t = ctx.get_llvm_type(generator, elem_ty).as_basic_type_enum();
|
||||
assert!(llvm_ndarray_data_t.is_sized());
|
||||
|
||||
let ndarray_num_elems = call_ndarray_calc_size(
|
||||
generator,
|
||||
ctx,
|
||||
&ndarray.shape().as_slice_value(ctx, generator),
|
||||
(None, None),
|
||||
);
|
||||
ndarray.create_data(ctx, llvm_ndarray_data_t, ndarray_num_elems);
|
||||
|
||||
ndarray
|
||||
}
|
||||
|
||||
fn ndarray_zero_value<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
@ -275,24 +338,20 @@ fn call_ndarray_empty_impl<'ctx, G: CodeGenerator + ?Sized>(
|
||||
// Get the length/size of the tuple, which also happens to be the value of `ndims`.
|
||||
let ndims = shape_tuple.get_type().count_fields();
|
||||
|
||||
let shape = (0..ndims)
|
||||
.map(|dim_i| {
|
||||
ctx.builder
|
||||
.build_extract_value(shape_tuple, dim_i, format!("dim{dim_i}").as_str())
|
||||
.map(BasicValueEnum::into_int_value)
|
||||
.map(|v| {
|
||||
ctx.builder.build_int_z_extend_or_bit_cast(v, llvm_usize, "").unwrap()
|
||||
})
|
||||
.unwrap()
|
||||
})
|
||||
.collect_vec();
|
||||
let mut shape = Vec::with_capacity(ndims as usize);
|
||||
for dim_i in 0..ndims {
|
||||
let dim = ctx
|
||||
.builder
|
||||
.build_extract_value(shape_tuple, dim_i, format!("dim{dim_i}").as_str())
|
||||
.unwrap()
|
||||
.into_int_value();
|
||||
|
||||
shape.push(dim);
|
||||
}
|
||||
create_ndarray_const_shape(generator, ctx, elem_ty, shape.as_slice())
|
||||
}
|
||||
BasicValueEnum::IntValue(shape_int) => {
|
||||
// 3. A scalar int; e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
|
||||
let shape_int =
|
||||
ctx.builder.build_int_z_extend_or_bit_cast(shape_int, llvm_usize, "").unwrap();
|
||||
|
||||
create_ndarray_const_shape(generator, ctx, elem_ty, &[shape_int])
|
||||
}
|
||||
@ -415,8 +474,8 @@ fn ndarray_broadcast_fill<'ctx, 'a, G, ValueFn>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, 'a>,
|
||||
res: NDArrayValue<'ctx>,
|
||||
(lhs_ty, lhs_val, lhs_scalar): (Type, BasicValueEnum<'ctx>, bool),
|
||||
(rhs_ty, rhs_val, rhs_scalar): (Type, BasicValueEnum<'ctx>, bool),
|
||||
lhs: (Type, BasicValueEnum<'ctx>, bool),
|
||||
rhs: (Type, BasicValueEnum<'ctx>, bool),
|
||||
value_fn: ValueFn,
|
||||
) -> Result<NDArrayValue<'ctx>, String>
|
||||
where
|
||||
@ -427,6 +486,11 @@ where
|
||||
(BasicValueEnum<'ctx>, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String>,
|
||||
{
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
let (lhs_ty, lhs_val, lhs_scalar) = lhs;
|
||||
let (rhs_ty, rhs_val, rhs_scalar) = rhs;
|
||||
|
||||
assert!(
|
||||
!(lhs_scalar && rhs_scalar),
|
||||
"One of the operands must be a ndarray instance: `{}`, `{}`",
|
||||
@ -436,14 +500,26 @@ where
|
||||
|
||||
// Assert that all ndarray operands are broadcastable to the target size
|
||||
if !lhs_scalar {
|
||||
let lhs_val = NDArrayType::from_unifier_type(generator, ctx, lhs_ty)
|
||||
.map_value(lhs_val.into_pointer_value(), None);
|
||||
let lhs_dtype = arraylike_flatten_element_type(&mut ctx.unifier, lhs_ty);
|
||||
let llvm_lhs_elem_ty = ctx.get_llvm_type(generator, lhs_dtype);
|
||||
let lhs_val = NDArrayValue::from_pointer_value(
|
||||
lhs_val.into_pointer_value(),
|
||||
llvm_lhs_elem_ty,
|
||||
llvm_usize,
|
||||
None,
|
||||
);
|
||||
ndarray_assert_is_broadcastable(generator, ctx, res, lhs_val);
|
||||
}
|
||||
|
||||
if !rhs_scalar {
|
||||
let rhs_val = NDArrayType::from_unifier_type(generator, ctx, rhs_ty)
|
||||
.map_value(rhs_val.into_pointer_value(), None);
|
||||
let rhs_dtype = arraylike_flatten_element_type(&mut ctx.unifier, rhs_ty);
|
||||
let llvm_rhs_elem_ty = ctx.get_llvm_type(generator, rhs_dtype);
|
||||
let rhs_val = NDArrayValue::from_pointer_value(
|
||||
rhs_val.into_pointer_value(),
|
||||
llvm_rhs_elem_ty,
|
||||
llvm_usize,
|
||||
None,
|
||||
);
|
||||
ndarray_assert_is_broadcastable(generator, ctx, res, rhs_val);
|
||||
}
|
||||
|
||||
@ -451,8 +527,14 @@ where
|
||||
let lhs_elem = if lhs_scalar {
|
||||
lhs_val
|
||||
} else {
|
||||
let lhs = NDArrayType::from_unifier_type(generator, ctx, lhs_ty)
|
||||
.map_value(lhs_val.into_pointer_value(), None);
|
||||
let lhs_dtype = arraylike_flatten_element_type(&mut ctx.unifier, lhs_ty);
|
||||
let llvm_lhs_elem_ty = ctx.get_llvm_type(generator, lhs_dtype);
|
||||
let lhs = NDArrayValue::from_pointer_value(
|
||||
lhs_val.into_pointer_value(),
|
||||
llvm_lhs_elem_ty,
|
||||
llvm_usize,
|
||||
None,
|
||||
);
|
||||
let lhs_idx = call_ndarray_calc_broadcast_index(generator, ctx, lhs, idx);
|
||||
|
||||
unsafe { lhs.data().get_unchecked(ctx, generator, &lhs_idx, None) }
|
||||
@ -461,8 +543,14 @@ where
|
||||
let rhs_elem = if rhs_scalar {
|
||||
rhs_val
|
||||
} else {
|
||||
let rhs = NDArrayType::from_unifier_type(generator, ctx, rhs_ty)
|
||||
.map_value(rhs_val.into_pointer_value(), None);
|
||||
let rhs_dtype = arraylike_flatten_element_type(&mut ctx.unifier, rhs_ty);
|
||||
let llvm_rhs_elem_ty = ctx.get_llvm_type(generator, rhs_dtype);
|
||||
let rhs = NDArrayValue::from_pointer_value(
|
||||
rhs_val.into_pointer_value(),
|
||||
llvm_rhs_elem_ty,
|
||||
llvm_usize,
|
||||
None,
|
||||
);
|
||||
let rhs_idx = call_ndarray_calc_broadcast_index(generator, ctx, rhs, idx);
|
||||
|
||||
unsafe { rhs.data().get_unchecked(ctx, generator, &rhs_idx, None) }
|
||||
@ -616,7 +704,9 @@ fn llvm_arraylike_get_ndims<'ctx, G: CodeGenerator + ?Sized>(
|
||||
BasicValueEnum::PointerValue(v)
|
||||
if NDArrayValue::is_representable(v, llvm_usize).is_ok() =>
|
||||
{
|
||||
NDArrayType::from_unifier_type(generator, ctx, ty).map_value(v, None).load_ndims(ctx)
|
||||
let dtype = arraylike_flatten_element_type(&mut ctx.unifier, ty);
|
||||
let llvm_elem_ty = ctx.get_llvm_type(generator, dtype);
|
||||
NDArrayValue::from_pointer_value(v, llvm_elem_ty, llvm_usize, None).load_ndims(ctx)
|
||||
}
|
||||
|
||||
BasicValueEnum::PointerValue(v) if ListValue::is_representable(v, llvm_usize).is_ok() => {
|
||||
@ -767,7 +857,7 @@ fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
|
||||
// object is an NDArray instance - copy object unless copy=0 && ndmin < object.ndims
|
||||
if NDArrayValue::is_representable(object, llvm_usize).is_ok() {
|
||||
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
let object = NDArrayValue::from_pointer_value(object, llvm_elem_ty, None, llvm_usize, None);
|
||||
let object = NDArrayValue::from_pointer_value(object, llvm_elem_ty, llvm_usize, None);
|
||||
|
||||
let ndarray = gen_if_else_expr_callback(
|
||||
generator,
|
||||
@ -843,7 +933,6 @@ fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
|
||||
return Ok(NDArrayValue::from_pointer_value(
|
||||
ndarray.map(BasicValueEnum::into_pointer_value).unwrap(),
|
||||
llvm_elem_ty,
|
||||
None,
|
||||
llvm_usize,
|
||||
None,
|
||||
));
|
||||
@ -1037,7 +1126,7 @@ fn call_ndarray_eye_impl<'ctx, G: CodeGenerator + ?Sized>(
|
||||
|
||||
/// Copies a slice of an [`NDArrayValue`] to another.
|
||||
///
|
||||
/// - `dst_arr`: The [`NDArrayValue`] instance of the destination array. The `ndims` and `shape`
|
||||
/// - `dst_arr`: The [`NDArrayValue`] instance of the destination array. The `ndims` and `dim_sz`
|
||||
/// fields should be populated before calling this function.
|
||||
/// - `dst_slice_ptr`: The [`PointerValue`] to the first element of the currently processing
|
||||
/// dimensional slice in the destination array.
|
||||
@ -1181,86 +1270,85 @@ pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
|
||||
) -> Result<NDArrayValue<'ctx>, String> {
|
||||
let llvm_i32 = ctx.ctx.i32_type();
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
|
||||
let ndarray =
|
||||
if slices.is_empty() {
|
||||
create_ndarray_dyn_shape(
|
||||
generator,
|
||||
ctx,
|
||||
elem_ty,
|
||||
&this,
|
||||
|_, ctx, shape| Ok(shape.load_ndims(ctx)),
|
||||
|generator, ctx, shape, idx| unsafe {
|
||||
Ok(shape.shape().get_typed_unchecked(ctx, generator, &idx, None))
|
||||
},
|
||||
)?
|
||||
} else {
|
||||
let ndarray = NDArrayType::new(generator, ctx.ctx, llvm_elem_ty, None)
|
||||
.construct_dyn_ndims(generator, ctx, this.load_ndims(ctx), None);
|
||||
let ndarray = if slices.is_empty() {
|
||||
create_ndarray_dyn_shape(
|
||||
generator,
|
||||
ctx,
|
||||
elem_ty,
|
||||
&this,
|
||||
|_, ctx, shape| Ok(shape.load_ndims(ctx)),
|
||||
|generator, ctx, shape, idx| unsafe {
|
||||
Ok(shape.shape().get_typed_unchecked(ctx, generator, &idx, None))
|
||||
},
|
||||
)?
|
||||
} else {
|
||||
let ndarray = create_ndarray_uninitialized(generator, ctx, elem_ty)?;
|
||||
ndarray.store_ndims(ctx, generator, this.load_ndims(ctx));
|
||||
|
||||
// Populate the first slices.len() dimensions by computing the size of each dim slice
|
||||
for (i, (start, stop, step)) in slices.iter().enumerate() {
|
||||
// HACK: workaround calculate_len_for_slice_range requiring exclusive stop
|
||||
let stop = ctx
|
||||
.builder
|
||||
.build_select(
|
||||
ctx.builder
|
||||
.build_int_compare(
|
||||
IntPredicate::SLT,
|
||||
*step,
|
||||
llvm_i32.const_zero(),
|
||||
"is_neg",
|
||||
)
|
||||
.unwrap(),
|
||||
ctx.builder
|
||||
.build_int_sub(*stop, llvm_i32.const_int(1, true), "e_min_one")
|
||||
.unwrap(),
|
||||
ctx.builder
|
||||
.build_int_add(*stop, llvm_i32.const_int(1, true), "e_add_one")
|
||||
.unwrap(),
|
||||
"final_e",
|
||||
)
|
||||
.map(BasicValueEnum::into_int_value)
|
||||
.unwrap();
|
||||
let ndims = this.load_ndims(ctx);
|
||||
ndarray.create_shape(ctx, llvm_usize, ndims);
|
||||
|
||||
let slice_len = calculate_len_for_slice_range(generator, ctx, *start, stop, *step);
|
||||
let slice_len =
|
||||
ctx.builder.build_int_z_extend_or_bit_cast(slice_len, llvm_usize, "").unwrap();
|
||||
// Populate the first slices.len() dimensions by computing the size of each dim slice
|
||||
for (i, (start, stop, step)) in slices.iter().enumerate() {
|
||||
// HACK: workaround calculate_len_for_slice_range requiring exclusive stop
|
||||
let stop = ctx
|
||||
.builder
|
||||
.build_select(
|
||||
ctx.builder
|
||||
.build_int_compare(
|
||||
IntPredicate::SLT,
|
||||
*step,
|
||||
llvm_i32.const_zero(),
|
||||
"is_neg",
|
||||
)
|
||||
.unwrap(),
|
||||
ctx.builder
|
||||
.build_int_sub(*stop, llvm_i32.const_int(1, true), "e_min_one")
|
||||
.unwrap(),
|
||||
ctx.builder
|
||||
.build_int_add(*stop, llvm_i32.const_int(1, true), "e_add_one")
|
||||
.unwrap(),
|
||||
"final_e",
|
||||
)
|
||||
.map(BasicValueEnum::into_int_value)
|
||||
.unwrap();
|
||||
|
||||
unsafe {
|
||||
ndarray.shape().set_typed_unchecked(
|
||||
ctx,
|
||||
generator,
|
||||
&llvm_usize.const_int(i as u64, false),
|
||||
slice_len,
|
||||
);
|
||||
}
|
||||
let slice_len = calculate_len_for_slice_range(generator, ctx, *start, stop, *step);
|
||||
let slice_len =
|
||||
ctx.builder.build_int_z_extend_or_bit_cast(slice_len, llvm_usize, "").unwrap();
|
||||
|
||||
unsafe {
|
||||
ndarray.shape().set_typed_unchecked(
|
||||
ctx,
|
||||
generator,
|
||||
&llvm_usize.const_int(i as u64, false),
|
||||
slice_len,
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
// Populate the rest by directly copying the dim size from the source array
|
||||
gen_for_callback_incrementing(
|
||||
generator,
|
||||
ctx,
|
||||
None,
|
||||
llvm_usize.const_int(slices.len() as u64, false),
|
||||
(this.load_ndims(ctx), false),
|
||||
|generator, ctx, _, idx| {
|
||||
unsafe {
|
||||
let shape = this.shape().get_typed_unchecked(ctx, generator, &idx, None);
|
||||
ndarray.shape().set_typed_unchecked(ctx, generator, &idx, shape);
|
||||
}
|
||||
// Populate the rest by directly copying the dim size from the source array
|
||||
gen_for_callback_incrementing(
|
||||
generator,
|
||||
ctx,
|
||||
None,
|
||||
llvm_usize.const_int(slices.len() as u64, false),
|
||||
(this.load_ndims(ctx), false),
|
||||
|generator, ctx, _, idx| {
|
||||
unsafe {
|
||||
let dim_sz = this.shape().get_typed_unchecked(ctx, generator, &idx, None);
|
||||
ndarray.shape().set_typed_unchecked(ctx, generator, &idx, dim_sz);
|
||||
}
|
||||
|
||||
Ok(())
|
||||
},
|
||||
llvm_usize.const_int(1, false),
|
||||
)
|
||||
.unwrap();
|
||||
Ok(())
|
||||
},
|
||||
llvm_usize.const_int(1, false),
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
unsafe { ndarray.create_data(generator, ctx) };
|
||||
|
||||
ndarray
|
||||
};
|
||||
ndarray_init_data(generator, ctx, elem_ty, ndarray)
|
||||
};
|
||||
|
||||
ndarray_sliced_copyto_impl(
|
||||
generator,
|
||||
@ -1359,6 +1447,8 @@ where
|
||||
(BasicValueEnum<'ctx>, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String>,
|
||||
{
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
let (lhs_ty, lhs_val, lhs_scalar) = lhs;
|
||||
let (rhs_ty, rhs_val, rhs_scalar) = rhs;
|
||||
|
||||
@ -1371,10 +1461,22 @@ where
|
||||
|
||||
let ndarray = res.unwrap_or_else(|| {
|
||||
if lhs_scalar && rhs_scalar {
|
||||
let lhs_val = NDArrayType::from_unifier_type(generator, ctx, lhs_ty)
|
||||
.map_value(lhs_val.into_pointer_value(), None);
|
||||
let rhs_val = NDArrayType::from_unifier_type(generator, ctx, rhs_ty)
|
||||
.map_value(rhs_val.into_pointer_value(), None);
|
||||
let lhs_dtype = arraylike_flatten_element_type(&mut ctx.unifier, lhs_ty);
|
||||
let llvm_lhs_elem_ty = ctx.get_llvm_type(generator, lhs_dtype);
|
||||
let lhs_val = NDArrayValue::from_pointer_value(
|
||||
lhs_val.into_pointer_value(),
|
||||
llvm_lhs_elem_ty,
|
||||
llvm_usize,
|
||||
None,
|
||||
);
|
||||
let rhs_dtype = arraylike_flatten_element_type(&mut ctx.unifier, rhs_ty);
|
||||
let llvm_rhs_elem_ty = ctx.get_llvm_type(generator, rhs_dtype);
|
||||
let rhs_val = NDArrayValue::from_pointer_value(
|
||||
rhs_val.into_pointer_value(),
|
||||
llvm_rhs_elem_ty,
|
||||
llvm_usize,
|
||||
None,
|
||||
);
|
||||
|
||||
let ndarray_dims = call_ndarray_calc_broadcast(generator, ctx, lhs_val, rhs_val);
|
||||
|
||||
@ -1390,12 +1492,17 @@ where
|
||||
)
|
||||
.unwrap()
|
||||
} else {
|
||||
let ndarray = NDArrayType::from_unifier_type(
|
||||
generator,
|
||||
ctx,
|
||||
let dtype = arraylike_flatten_element_type(
|
||||
&mut ctx.unifier,
|
||||
if lhs_scalar { rhs_ty } else { lhs_ty },
|
||||
)
|
||||
.map_value(if lhs_scalar { rhs_val } else { lhs_val }.into_pointer_value(), None);
|
||||
);
|
||||
let llvm_elem_ty = ctx.get_llvm_type(generator, dtype);
|
||||
let ndarray = NDArrayValue::from_pointer_value(
|
||||
if lhs_scalar { rhs_val } else { lhs_val }.into_pointer_value(),
|
||||
llvm_elem_ty,
|
||||
llvm_usize,
|
||||
None,
|
||||
);
|
||||
|
||||
create_ndarray_dyn_shape(
|
||||
generator,
|
||||
@ -1939,18 +2046,25 @@ pub fn gen_ndarray_copy<'ctx>(
|
||||
assert!(obj.is_some());
|
||||
assert!(args.is_empty());
|
||||
|
||||
let llvm_usize = generator.get_size_type(context.ctx);
|
||||
|
||||
let this_ty = obj.as_ref().unwrap().0;
|
||||
let (this_elem_ty, _) = unpack_ndarray_var_tys(&mut context.unifier, this_ty);
|
||||
let this_arg =
|
||||
obj.as_ref().unwrap().1.clone().to_basic_value_enum(context, generator, this_ty)?;
|
||||
|
||||
let llvm_this_ty = NDArrayType::from_unifier_type(generator, context, this_ty);
|
||||
let llvm_elem_ty = context.get_llvm_type(generator, this_elem_ty);
|
||||
|
||||
ndarray_copy_impl(
|
||||
generator,
|
||||
context,
|
||||
this_elem_ty,
|
||||
llvm_this_ty.map_value(this_arg.into_pointer_value(), None),
|
||||
NDArrayValue::from_pointer_value(
|
||||
this_arg.into_pointer_value(),
|
||||
llvm_elem_ty,
|
||||
llvm_usize,
|
||||
None,
|
||||
),
|
||||
)
|
||||
.map(NDArrayValue::into)
|
||||
}
|
||||
@ -1966,7 +2080,10 @@ pub fn gen_ndarray_fill<'ctx>(
|
||||
assert!(obj.is_some());
|
||||
assert_eq!(args.len(), 1);
|
||||
|
||||
let llvm_usize = generator.get_size_type(context.ctx);
|
||||
|
||||
let this_ty = obj.as_ref().unwrap().0;
|
||||
let this_elem_ty = arraylike_flatten_element_type(&mut context.unifier, this_ty);
|
||||
let this_arg = obj
|
||||
.as_ref()
|
||||
.unwrap()
|
||||
@ -1977,12 +2094,12 @@ pub fn gen_ndarray_fill<'ctx>(
|
||||
let value_ty = fun.0.args[0].ty;
|
||||
let value_arg = args[0].1.clone().to_basic_value_enum(context, generator, value_ty)?;
|
||||
|
||||
let llvm_this_ty = NDArrayType::from_unifier_type(generator, context, this_ty);
|
||||
let llvm_elem_ty = context.get_llvm_type(generator, this_elem_ty);
|
||||
|
||||
ndarray_fill_flattened(
|
||||
generator,
|
||||
context,
|
||||
llvm_this_ty.map_value(this_arg, None),
|
||||
NDArrayValue::from_pointer_value(this_arg, llvm_elem_ty, llvm_usize, None),
|
||||
|generator, ctx, _| {
|
||||
let value = if value_arg.is_pointer_value() {
|
||||
let llvm_i1 = ctx.ctx.bool_type();
|
||||
@ -2015,16 +2132,16 @@ pub fn gen_ndarray_fill<'ctx>(
|
||||
pub fn ndarray_transpose<'ctx, G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
(x1_ty, x1): (Type, BasicValueEnum<'ctx>),
|
||||
x1: (Type, BasicValueEnum<'ctx>),
|
||||
) -> Result<BasicValueEnum<'ctx>, String> {
|
||||
const FN_NAME: &str = "ndarray_transpose";
|
||||
|
||||
let (x1_ty, x1) = x1;
|
||||
let llvm_usize = generator.get_size_type(ctx.ctx);
|
||||
|
||||
if let BasicValueEnum::PointerValue(n1) = x1 {
|
||||
let llvm_ndarray_ty = NDArrayType::from_unifier_type(generator, ctx, x1_ty);
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
|
||||
let n1 = llvm_ndarray_ty.map_value(n1, None);
|
||||
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
let n1 = NDArrayValue::from_pointer_value(n1, llvm_elem_ty, llvm_usize, None);
|
||||
let n_sz = call_ndarray_calc_size(generator, ctx, &n1.shape(), (None, None));
|
||||
|
||||
// Dimensions are reversed in the transposed array
|
||||
@ -2143,8 +2260,8 @@ pub fn ndarray_reshape<'ctx, G: CodeGenerator + ?Sized>(
|
||||
|
||||
if let BasicValueEnum::PointerValue(n1) = x1 {
|
||||
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
|
||||
let llvm_ndarray_ty = NDArrayType::from_unifier_type(generator, ctx, x1_ty);
|
||||
let n1 = llvm_ndarray_ty.map_value(n1, None);
|
||||
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
|
||||
let n1 = NDArrayValue::from_pointer_value(n1, llvm_elem_ty, llvm_usize, None);
|
||||
let n_sz = call_ndarray_calc_size(generator, ctx, &n1.shape(), (None, None));
|
||||
|
||||
let acc = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
|
||||
@ -2427,8 +2544,13 @@ pub fn ndarray_dot<'ctx, G: CodeGenerator + ?Sized>(
|
||||
|
||||
match (x1, x2) {
|
||||
(BasicValueEnum::PointerValue(n1), BasicValueEnum::PointerValue(n2)) => {
|
||||
let n1 = NDArrayType::from_unifier_type(generator, ctx, x1_ty).map_value(n1, None);
|
||||
let n2 = NDArrayType::from_unifier_type(generator, ctx, x2_ty).map_value(n2, None);
|
||||
let n1_dtype = arraylike_flatten_element_type(&mut ctx.unifier, x1_ty);
|
||||
let n2_dtype = arraylike_flatten_element_type(&mut ctx.unifier, x2_ty);
|
||||
let llvm_n1_data_ty = ctx.get_llvm_type(generator, n1_dtype);
|
||||
let llvm_n2_data_ty = ctx.get_llvm_type(generator, n2_dtype);
|
||||
|
||||
let n1 = NDArrayValue::from_pointer_value(n1, llvm_n1_data_ty, llvm_usize, None);
|
||||
let n2 = NDArrayValue::from_pointer_value(n2, llvm_n2_data_ty, llvm_usize, None);
|
||||
|
||||
let n1_sz = call_ndarray_calc_size(generator, ctx, &n1.shape(), (None, None));
|
||||
let n2_sz = call_ndarray_calc_size(generator, ctx, &n1.shape(), (None, None));
|
||||
|
||||
@ -17,7 +17,8 @@ use parking_lot::RwLock;
|
||||
|
||||
use super::{
|
||||
concrete_type::ConcreteTypeStore,
|
||||
types::{ndarray::NDArrayType, ListType, ProxyType, RangeType},
|
||||
tracert::TraceRuntimeConfig,
|
||||
types::{ListType, NDArrayType, ProxyType, RangeType},
|
||||
CodeGenContext, CodeGenLLVMOptions, CodeGenTargetMachineOptions, CodeGenTask, CodeGenerator,
|
||||
DefaultCodeGenerator, WithCall, WorkerRegistry,
|
||||
};
|
||||
@ -245,7 +246,13 @@ fn test_primitives() {
|
||||
opt_level: OptimizationLevel::Default,
|
||||
target: CodeGenTargetMachineOptions::from_host_triple(),
|
||||
};
|
||||
let (registry, handles) = WorkerRegistry::create_workers(threads, top_level, &llvm_options, &f);
|
||||
let (registry, handles) = WorkerRegistry::create_workers(
|
||||
threads,
|
||||
top_level,
|
||||
&llvm_options,
|
||||
&TraceRuntimeConfig::default(),
|
||||
&f,
|
||||
);
|
||||
registry.add_task(task);
|
||||
registry.wait_tasks_complete(handles);
|
||||
}
|
||||
@ -438,7 +445,13 @@ fn test_simple_call() {
|
||||
opt_level: OptimizationLevel::Default,
|
||||
target: CodeGenTargetMachineOptions::from_host_triple(),
|
||||
};
|
||||
let (registry, handles) = WorkerRegistry::create_workers(threads, top_level, &llvm_options, &f);
|
||||
let (registry, handles) = WorkerRegistry::create_workers(
|
||||
threads,
|
||||
top_level,
|
||||
&llvm_options,
|
||||
&TraceRuntimeConfig::default(),
|
||||
&f,
|
||||
);
|
||||
registry.add_task(task);
|
||||
registry.wait_tasks_complete(handles);
|
||||
}
|
||||
@ -471,6 +484,6 @@ 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);
|
||||
let llvm_ndarray = NDArrayType::new(&generator, &ctx, llvm_i32.into());
|
||||
assert!(NDArrayType::is_representable(llvm_ndarray.as_base_type(), llvm_usize).is_ok());
|
||||
}
|
||||
|
||||
110
nac3core/src/codegen/tracert/mod.rs
Normal file
110
nac3core/src/codegen/tracert/mod.rs
Normal file
@ -0,0 +1,110 @@
|
||||
use std::panic::Location;
|
||||
|
||||
use inkwell::context::Context;
|
||||
use inkwell::memory_buffer::MemoryBuffer;
|
||||
use inkwell::module::Module;
|
||||
use inkwell::values::BasicValueEnum;
|
||||
use inkwell::AtomicOrdering;
|
||||
|
||||
use crate::codegen::{extern_fns, CodeGenContext};
|
||||
|
||||
#[derive(Clone, Default, Eq, PartialEq)]
|
||||
pub struct TraceRuntimeConfig {
|
||||
pub enabled_tags: Vec<String>,
|
||||
}
|
||||
|
||||
#[derive(Eq, Clone, PartialEq)]
|
||||
pub struct TraceRuntimeState {
|
||||
config: TraceRuntimeConfig,
|
||||
indent: usize,
|
||||
}
|
||||
|
||||
impl TraceRuntimeState {
|
||||
#[must_use]
|
||||
pub fn create(config: TraceRuntimeConfig) -> TraceRuntimeState {
|
||||
TraceRuntimeState { config, indent: 0 }
|
||||
}
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn load_tracert<'ctx>(ctx: &'ctx Context, config: &TraceRuntimeConfig) -> Option<Module<'ctx>> {
|
||||
if cfg!(feature = "tracing") && !config.enabled_tags.is_empty() {
|
||||
let bitcode_buf = MemoryBuffer::create_from_memory_range(
|
||||
include_bytes!(concat!(env!("OUT_DIR"), "/tracert.bc")),
|
||||
"tracert_bitcode_buffer",
|
||||
);
|
||||
let module = Module::parse_bitcode_from_buffer(&bitcode_buf, ctx).unwrap();
|
||||
|
||||
return Some(module);
|
||||
}
|
||||
|
||||
None
|
||||
}
|
||||
|
||||
// TODO: Might need to redesign how trace logging should be done
|
||||
|
||||
pub fn trace_log<'ctx>(
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
tag: &'static str,
|
||||
format: &'static str,
|
||||
args: &[BasicValueEnum<'ctx>],
|
||||
) {
|
||||
if ctx.tracert_state.is_none() {
|
||||
return;
|
||||
}
|
||||
|
||||
// TODO: Add indentation
|
||||
let str = format!("[TRACING] {tag} - {format}\n\0");
|
||||
extern_fns::call_printf(ctx, &str, args);
|
||||
}
|
||||
|
||||
#[track_caller]
|
||||
pub fn trace_log_with_location<'ctx>(
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
tag: &'static str,
|
||||
format: &str,
|
||||
args: &[BasicValueEnum<'ctx>],
|
||||
) {
|
||||
if ctx.tracert_state.is_none() {
|
||||
return;
|
||||
}
|
||||
|
||||
// TODO: Add indentation
|
||||
let caller_loc = Location::caller();
|
||||
let str = format!(
|
||||
"[TRACING] {}:{}:{}: {tag} - {format}\n\0",
|
||||
caller_loc.file(),
|
||||
caller_loc.line(),
|
||||
caller_loc.column()
|
||||
);
|
||||
extern_fns::call_printf(ctx, &str, args);
|
||||
}
|
||||
|
||||
pub fn trace_push_level(ctx: &mut CodeGenContext<'_, '_>) {
|
||||
let Some(tracert_state) = &mut ctx.tracert_state else {
|
||||
return;
|
||||
};
|
||||
|
||||
debug_assert!(tracert_state.indent < usize::MAX);
|
||||
if tracert_state.indent < usize::MAX {
|
||||
tracert_state.indent = tracert_state.indent.saturating_add(1);
|
||||
}
|
||||
}
|
||||
|
||||
pub fn trace_pop_level(ctx: &mut CodeGenContext<'_, '_>) {
|
||||
let Some(tracert_state) = &mut ctx.tracert_state else {
|
||||
return;
|
||||
};
|
||||
|
||||
debug_assert!(tracert_state.indent > 0);
|
||||
if tracert_state.indent > 0 {
|
||||
tracert_state.indent = tracert_state.indent.saturating_sub(1);
|
||||
}
|
||||
}
|
||||
|
||||
#[inline]
|
||||
pub fn mfence(ctx: &mut CodeGenContext<'_, '_>) {
|
||||
if ctx.tracert_state.is_some() {
|
||||
ctx.builder.build_fence(AtomicOrdering::SequentiallyConsistent, 0, "").unwrap();
|
||||
}
|
||||
}
|
||||
@ -23,13 +23,13 @@ use super::{
|
||||
{CodeGenContext, CodeGenerator},
|
||||
};
|
||||
pub use list::*;
|
||||
pub use ndarray::*;
|
||||
pub use range::*;
|
||||
|
||||
mod list;
|
||||
pub mod ndarray;
|
||||
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> {
|
||||
|
||||
@ -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()
|
||||
}
|
||||
}
|
||||
@ -1,7 +1,7 @@
|
||||
use inkwell::{
|
||||
context::{AsContextRef, Context},
|
||||
context::Context,
|
||||
types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
|
||||
values::{BasicValue, IntValue, PointerValue},
|
||||
values::{IntValue, PointerValue},
|
||||
AddressSpace,
|
||||
};
|
||||
use itertools::Itertools;
|
||||
@ -9,49 +9,28 @@ use itertools::Itertools;
|
||||
use nac3core_derive::StructFields;
|
||||
|
||||
use super::{
|
||||
structure::{check_struct_type_matches_fields, StructField, StructFields},
|
||||
structure::{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,
|
||||
use crate::codegen::{
|
||||
values::{ArraySliceValue, NDArrayValue, ProxyValue},
|
||||
{CodeGenContext, CodeGenerator},
|
||||
};
|
||||
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>>,
|
||||
}
|
||||
@ -62,40 +41,90 @@ impl<'ctx> NDArrayType<'ctx> {
|
||||
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}"));
|
||||
};
|
||||
if llvm_ndarray_ty.count_fields() != 3 {
|
||||
return Err(format!(
|
||||
"Expected 3 fields in `NDArray`, got {}",
|
||||
llvm_ndarray_ty.count_fields()
|
||||
));
|
||||
}
|
||||
|
||||
check_struct_type_matches_fields(
|
||||
Self::fields(ctx, llvm_usize),
|
||||
llvm_ndarray_ty,
|
||||
"NDArray",
|
||||
&[],
|
||||
)
|
||||
let ndarray_ndims_ty = llvm_ndarray_ty.get_field_type_at_index(0).unwrap();
|
||||
let Ok(ndarray_ndims_ty) = IntType::try_from(ndarray_ndims_ty) else {
|
||||
return Err(format!("Expected int type for `ndarray.0`, got {ndarray_ndims_ty}"));
|
||||
};
|
||||
if ndarray_ndims_ty.get_bit_width() != llvm_usize.get_bit_width() {
|
||||
return Err(format!(
|
||||
"Expected {}-bit int type for `ndarray.0`, got {}-bit int",
|
||||
llvm_usize.get_bit_width(),
|
||||
ndarray_ndims_ty.get_bit_width()
|
||||
));
|
||||
}
|
||||
|
||||
let ndarray_dims_ty = llvm_ndarray_ty.get_field_type_at_index(1).unwrap();
|
||||
let Ok(ndarray_pdims) = PointerType::try_from(ndarray_dims_ty) else {
|
||||
return Err(format!("Expected pointer type for `ndarray.1`, got {ndarray_dims_ty}"));
|
||||
};
|
||||
let ndarray_dims = ndarray_pdims.get_element_type();
|
||||
let Ok(ndarray_dims) = IntType::try_from(ndarray_dims) else {
|
||||
return Err(format!(
|
||||
"Expected pointer-to-int type for `ndarray.1`, got pointer-to-{ndarray_dims}"
|
||||
));
|
||||
};
|
||||
if ndarray_dims.get_bit_width() != llvm_usize.get_bit_width() {
|
||||
return Err(format!(
|
||||
"Expected pointer-to-{}-bit int type for `ndarray.1`, got pointer-to-{}-bit int",
|
||||
llvm_usize.get_bit_width(),
|
||||
ndarray_dims.get_bit_width()
|
||||
));
|
||||
}
|
||||
|
||||
let ndarray_data_ty = llvm_ndarray_ty.get_field_type_at_index(2).unwrap();
|
||||
let Ok(ndarray_pdata) = PointerType::try_from(ndarray_data_ty) else {
|
||||
return Err(format!("Expected pointer type for `ndarray.2`, got {ndarray_data_ty}"));
|
||||
};
|
||||
let ndarray_data = ndarray_pdata.get_element_type();
|
||||
let Ok(ndarray_data) = IntType::try_from(ndarray_data) else {
|
||||
return Err(format!(
|
||||
"Expected pointer-to-int type for `ndarray.2`, got pointer-to-{ndarray_data}"
|
||||
));
|
||||
};
|
||||
if ndarray_data.get_bit_width() != 8 {
|
||||
return Err(format!(
|
||||
"Expected pointer-to-8-bit int type for `ndarray.1`, got pointer-to-{}-bit int",
|
||||
ndarray_data.get_bit_width()
|
||||
));
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// 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> {
|
||||
fn fields(ctx: &'ctx Context, 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> {
|
||||
pub fn get_fields(&self, ctx: &'ctx Context) -> 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> {
|
||||
// struct NDArray { num_dims: size_t, dims: size_t*, data: i8* }
|
||||
//
|
||||
// * data : Pointer to an array containing the array data
|
||||
// * itemsize: The size of each NDArray elements in bytes
|
||||
// * ndims : Number of dimensions in the array
|
||||
// * shape : Pointer to an array containing the shape of the NDArray
|
||||
// * strides : Pointer to an array indicating the number of bytes between each element at a dimension
|
||||
let field_tys =
|
||||
Self::fields(ctx, llvm_usize).into_iter().map(|field| field.1).collect_vec();
|
||||
|
||||
@ -108,46 +137,11 @@ impl<'ctx> NDArrayType<'ctx> {
|
||||
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,
|
||||
}
|
||||
NDArrayType { ty: llvm_ndarray, dtype, llvm_usize }
|
||||
}
|
||||
|
||||
/// Creates an [`NDArrayType`] from a [`PointerType`] representing an `NDArray`.
|
||||
@ -155,18 +149,22 @@ impl<'ctx> NDArrayType<'ctx> {
|
||||
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 }
|
||||
NDArrayType { ty: ptr_ty, dtype, 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
|
||||
self.as_base_type()
|
||||
.get_element_type()
|
||||
.into_struct_type()
|
||||
.get_field_type_at_index(0)
|
||||
.map(BasicTypeEnum::into_int_type)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Returns the element type of this `ndarray` type.
|
||||
@ -175,12 +173,6 @@ impl<'ctx> NDArrayType<'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>(
|
||||
@ -192,198 +184,11 @@ impl<'ctx> NDArrayType<'ctx> {
|
||||
<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(
|
||||
@ -394,7 +199,6 @@ impl<'ctx> NDArrayType<'ctx> {
|
||||
<Self as ProxyType<'ctx>>::Value::from_pointer_value(
|
||||
value,
|
||||
self.dtype,
|
||||
self.ndims,
|
||||
self.llvm_usize,
|
||||
name,
|
||||
)
|
||||
|
||||
@ -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()
|
||||
}
|
||||
}
|
||||
@ -2,7 +2,7 @@ use std::marker::PhantomData;
|
||||
|
||||
use inkwell::{
|
||||
context::AsContextRef,
|
||||
types::{BasicTypeEnum, IntType, StructType},
|
||||
types::{BasicTypeEnum, IntType},
|
||||
values::{BasicValue, BasicValueEnum, IntValue, PointerValue, StructValue},
|
||||
};
|
||||
|
||||
@ -103,12 +103,6 @@ where
|
||||
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(
|
||||
@ -207,49 +201,3 @@ impl FieldIndexCounter {
|
||||
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()
|
||||
}
|
||||
}
|
||||
@ -207,7 +207,7 @@ pub trait TypedArrayLikeMutator<'ctx, T, Index = IntValue<'ctx>>:
|
||||
|
||||
/// 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>;
|
||||
Box<dyn Fn(&mut CodeGenContext<'ctx, '_>, BasicValueEnum<'ctx>) -> T>;
|
||||
/// 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>>;
|
||||
|
||||
|
||||
@ -4,13 +4,13 @@ use super::types::ProxyType;
|
||||
use crate::codegen::CodeGenerator;
|
||||
pub use array::*;
|
||||
pub use list::*;
|
||||
pub use ndarray::*;
|
||||
pub use range::*;
|
||||
|
||||
mod array;
|
||||
mod list;
|
||||
pub mod ndarray;
|
||||
mod ndarray;
|
||||
mod range;
|
||||
pub mod utils;
|
||||
|
||||
/// A LLVM type that is used to represent a non-primitive value in NAC3.
|
||||
pub trait ProxyValue<'ctx>: Into<Self::Base> {
|
||||
|
||||
@ -1,202 +0,0 @@
|
||||
use inkwell::{
|
||||
types::{BasicType, BasicTypeEnum, IntType},
|
||||
values::{IntValue, PointerValue},
|
||||
AddressSpace,
|
||||
};
|
||||
|
||||
use super::{ArrayLikeValue, NDArrayValue, ProxyValue};
|
||||
use crate::codegen::{
|
||||
stmt::gen_if_callback,
|
||||
types::{
|
||||
ndarray::{ContiguousNDArrayType, NDArrayType},
|
||||
structure::StructField,
|
||||
},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
#[derive(Copy, Clone)]
|
||||
pub struct ContiguousNDArrayValue<'ctx> {
|
||||
value: PointerValue<'ctx>,
|
||||
item: BasicTypeEnum<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
}
|
||||
|
||||
impl<'ctx> ContiguousNDArrayValue<'ctx> {
|
||||
/// Checks whether `value` is an instance of `ContiguousNDArray`, returning [Err] if `value` is
|
||||
/// not an instance.
|
||||
pub fn is_representable(
|
||||
value: PointerValue<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
) -> Result<(), String> {
|
||||
<Self as ProxyValue<'ctx>>::Type::is_representable(value.get_type(), llvm_usize)
|
||||
}
|
||||
|
||||
/// Creates an [`ContiguousNDArrayValue`] from a [`PointerValue`].
|
||||
#[must_use]
|
||||
pub fn from_pointer_value(
|
||||
ptr: PointerValue<'ctx>,
|
||||
dtype: BasicTypeEnum<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> Self {
|
||||
debug_assert!(Self::is_representable(ptr, llvm_usize).is_ok());
|
||||
|
||||
Self { value: ptr, item: dtype, llvm_usize, name }
|
||||
}
|
||||
|
||||
fn ndims_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
|
||||
self.get_type().get_fields().ndims
|
||||
}
|
||||
|
||||
pub fn store_ndims(&self, ctx: &CodeGenContext<'ctx, '_>, value: IntValue<'ctx>) {
|
||||
self.ndims_field().set(ctx, self.as_base_value(), value, self.name);
|
||||
}
|
||||
|
||||
fn shape_field(&self) -> StructField<'ctx, PointerValue<'ctx>> {
|
||||
self.get_type().get_fields().shape
|
||||
}
|
||||
|
||||
pub fn store_shape(&self, ctx: &CodeGenContext<'ctx, '_>, value: PointerValue<'ctx>) {
|
||||
self.shape_field().set(ctx, self.as_base_value(), value, self.name);
|
||||
}
|
||||
|
||||
pub fn load_shape(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
|
||||
self.shape_field().get(ctx, self.value, self.name)
|
||||
}
|
||||
|
||||
fn data_field(&self) -> StructField<'ctx, PointerValue<'ctx>> {
|
||||
self.get_type().get_fields().data
|
||||
}
|
||||
|
||||
pub fn store_data(&self, ctx: &CodeGenContext<'ctx, '_>, value: PointerValue<'ctx>) {
|
||||
self.data_field().set(ctx, self.as_base_value(), value, self.name);
|
||||
}
|
||||
|
||||
pub fn load_data(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
|
||||
self.data_field().get(ctx, self.value, self.name)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> ProxyValue<'ctx> for ContiguousNDArrayValue<'ctx> {
|
||||
type Base = PointerValue<'ctx>;
|
||||
type Type = ContiguousNDArrayType<'ctx>;
|
||||
|
||||
fn get_type(&self) -> Self::Type {
|
||||
<Self as ProxyValue<'ctx>>::Type::from_type(
|
||||
self.as_base_value().get_type(),
|
||||
self.item,
|
||||
self.llvm_usize,
|
||||
)
|
||||
}
|
||||
|
||||
fn as_base_value(&self) -> Self::Base {
|
||||
self.value
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> From<ContiguousNDArrayValue<'ctx>> for PointerValue<'ctx> {
|
||||
fn from(value: ContiguousNDArrayValue<'ctx>) -> Self {
|
||||
value.as_base_value()
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayValue<'ctx> {
|
||||
/// Create a [`ContiguousNDArrayValue`] 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 [`ContiguousNDArrayValue`] and copy contents of this ndarray to
|
||||
/// there.
|
||||
///
|
||||
/// If this ndarray is C-contiguous, contents of this ndarray will not be copied. The created
|
||||
/// [`ContiguousNDArrayValue`] will share memory with this ndarray.
|
||||
pub fn make_contiguous_ndarray<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> ContiguousNDArrayValue<'ctx> {
|
||||
let result = ContiguousNDArrayType::new(generator, ctx.ctx, self.dtype)
|
||||
.alloca(generator, ctx, self.name);
|
||||
|
||||
// Set ndims and shape.
|
||||
let ndims = self
|
||||
.ndims
|
||||
.map_or_else(|| self.load_ndims(ctx), |ndims| self.llvm_usize.const_int(ndims, false));
|
||||
result.store_ndims(ctx, ndims);
|
||||
|
||||
let shape = self.shape();
|
||||
result.store_shape(ctx, shape.base_ptr(ctx, generator));
|
||||
|
||||
gen_if_callback(
|
||||
generator,
|
||||
ctx,
|
||||
|generator, ctx| Ok(self.is_c_contiguous(generator, ctx)),
|
||||
|_, ctx| {
|
||||
// This ndarray is contiguous.
|
||||
let data = self.data_field(ctx).get(ctx, self.as_base_value(), self.name);
|
||||
let data = ctx
|
||||
.builder
|
||||
.build_pointer_cast(data, result.item.ptr_type(AddressSpace::default()), "")
|
||||
.unwrap();
|
||||
result.store_data(ctx, data);
|
||||
|
||||
Ok(())
|
||||
},
|
||||
|generator, ctx| {
|
||||
// This ndarray is not contiguous. Do a full-copy on `data`. `make_copy` produces an
|
||||
// ndarray with contiguous `data`.
|
||||
let copied_ndarray = self.make_copy(generator, ctx);
|
||||
let data = copied_ndarray.data().base_ptr(ctx, generator);
|
||||
let data = ctx
|
||||
.builder
|
||||
.build_pointer_cast(data, result.item.ptr_type(AddressSpace::default()), "")
|
||||
.unwrap();
|
||||
result.store_data(ctx, data);
|
||||
|
||||
Ok(())
|
||||
},
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
result
|
||||
}
|
||||
|
||||
/// Create an [`NDArrayValue`] from a [`ContiguousNDArrayValue`].
|
||||
///
|
||||
/// The operation is cheap. The newly created [`NDArrayValue`] will share the same memory as the
|
||||
/// [`ContiguousNDArrayValue`].
|
||||
///
|
||||
/// `ndims` has to be provided as [`NDArrayValue`] requires a statically known `ndims` value,
|
||||
/// despite the fact that the information should be contained within the
|
||||
/// [`ContiguousNDArrayValue`].
|
||||
pub fn from_contiguous_ndarray<G: CodeGenerator + ?Sized>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
carray: ContiguousNDArrayValue<'ctx>,
|
||||
ndims: u64,
|
||||
) -> Self {
|
||||
// TODO: Debug assert `ndims == carray.ndims` to catch bugs.
|
||||
|
||||
// Allocate the resulting ndarray.
|
||||
let ndarray = NDArrayType::new(generator, ctx.ctx, carray.item, Some(ndims))
|
||||
.construct_uninitialized(generator, ctx, carray.name);
|
||||
|
||||
// Copy shape and update strides
|
||||
let shape = carray.load_shape(ctx);
|
||||
ndarray.copy_shape_from_array(generator, ctx, shape);
|
||||
ndarray.set_strides_contiguous(generator, ctx);
|
||||
|
||||
// Share data
|
||||
let data = carray.load_data(ctx);
|
||||
ndarray.store_data(
|
||||
ctx,
|
||||
ctx.builder
|
||||
.build_pointer_cast(data, ctx.ctx.i8_type().ptr_type(AddressSpace::default()), "")
|
||||
.unwrap(),
|
||||
);
|
||||
|
||||
ndarray
|
||||
}
|
||||
}
|
||||
@ -1,262 +0,0 @@
|
||||
use inkwell::{
|
||||
types::IntType,
|
||||
values::{IntValue, PointerValue},
|
||||
AddressSpace,
|
||||
};
|
||||
use itertools::Itertools;
|
||||
|
||||
use nac3parser::ast::{Expr, ExprKind};
|
||||
|
||||
use crate::{
|
||||
codegen::{
|
||||
irrt,
|
||||
types::{
|
||||
ndarray::{NDArrayType, NDIndexType},
|
||||
structure::StructField,
|
||||
utils::SliceType,
|
||||
},
|
||||
values::{ndarray::NDArrayValue, utils::RustSlice, ProxyValue},
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
typecheck::typedef::Type,
|
||||
};
|
||||
|
||||
/// An IRRT representation of an ndarray subscript index.
|
||||
#[derive(Copy, Clone)]
|
||||
pub struct NDIndexValue<'ctx> {
|
||||
value: PointerValue<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
}
|
||||
|
||||
impl<'ctx> NDIndexValue<'ctx> {
|
||||
/// Checks whether `value` is an instance of `ndindex`, returning [Err] if `value` is not an
|
||||
/// instance.
|
||||
pub fn is_representable(
|
||||
value: PointerValue<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
) -> Result<(), String> {
|
||||
<Self as ProxyValue<'ctx>>::Type::is_representable(value.get_type(), llvm_usize)
|
||||
}
|
||||
|
||||
/// Creates an [`NDIndexValue`] from a [`PointerValue`].
|
||||
#[must_use]
|
||||
pub fn from_pointer_value(
|
||||
ptr: PointerValue<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> Self {
|
||||
debug_assert!(Self::is_representable(ptr, llvm_usize).is_ok());
|
||||
|
||||
Self { value: ptr, llvm_usize, name }
|
||||
}
|
||||
|
||||
fn type_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
|
||||
self.get_type().get_fields().type_
|
||||
}
|
||||
|
||||
pub fn load_type(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
|
||||
self.type_field().get(ctx, self.value, self.name)
|
||||
}
|
||||
|
||||
pub fn store_type(&self, ctx: &CodeGenContext<'ctx, '_>, value: IntValue<'ctx>) {
|
||||
self.type_field().set(ctx, self.value, value, self.name);
|
||||
}
|
||||
|
||||
fn data_field(&self) -> StructField<'ctx, PointerValue<'ctx>> {
|
||||
self.get_type().get_fields().data
|
||||
}
|
||||
|
||||
pub fn load_data(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
|
||||
self.data_field().get(ctx, self.value, self.name)
|
||||
}
|
||||
|
||||
pub fn store_data(&self, ctx: &CodeGenContext<'ctx, '_>, value: PointerValue<'ctx>) {
|
||||
self.data_field().set(ctx, self.value, value, self.name);
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> ProxyValue<'ctx> for NDIndexValue<'ctx> {
|
||||
type Base = PointerValue<'ctx>;
|
||||
type Type = NDIndexType<'ctx>;
|
||||
|
||||
fn get_type(&self) -> Self::Type {
|
||||
Self::Type::from_type(self.value.get_type(), self.llvm_usize)
|
||||
}
|
||||
|
||||
fn as_base_value(&self) -> Self::Base {
|
||||
self.value
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> From<NDIndexValue<'ctx>> for PointerValue<'ctx> {
|
||||
fn from(value: NDIndexValue<'ctx>) -> Self {
|
||||
value.as_base_value()
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayValue<'ctx> {
|
||||
/// Get the expected `ndims` after indexing with `indices`.
|
||||
#[must_use]
|
||||
fn deduce_ndims_after_indexing_with(&self, indices: &[RustNDIndex<'ctx>]) -> Option<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(_) => {}
|
||||
}
|
||||
}
|
||||
|
||||
Some(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 {
|
||||
assert!(self.ndims.is_some(), "NDArrayValue::index is only supported for instances with compile-time known ndims (self.ndims = Some(...))");
|
||||
|
||||
let dst_ndims = self.deduce_ndims_after_indexing_with(indices);
|
||||
let dst_ndarray = NDArrayType::new(generator, ctx.ctx, self.dtype, dst_ndims)
|
||||
.construct_uninitialized(generator, ctx, None);
|
||||
|
||||
let indices =
|
||||
NDIndexType::new(generator, ctx.ctx).construct_ndindices(generator, ctx, indices);
|
||||
irrt::ndarray::call_nac3_ndarray_index(generator, ctx, indices, *self, dst_ndarray);
|
||||
|
||||
dst_ndarray
|
||||
}
|
||||
}
|
||||
|
||||
/// A convenience enum representing a [`NDIndexValue`].
|
||||
// TODO: Rename to CTConstNDIndex
|
||||
#[derive(Debug, Clone)]
|
||||
pub enum RustNDIndex<'ctx> {
|
||||
SingleElement(IntValue<'ctx>),
|
||||
Slice(RustSlice<'ctx>),
|
||||
NewAxis,
|
||||
Ellipsis,
|
||||
}
|
||||
|
||||
impl<'ctx> RustNDIndex<'ctx> {
|
||||
/// 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 from_subscript_expr<G: CodeGenerator>(
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
subscript: &Expr<Option<Type>>,
|
||||
) -> Result<Vec<RustNDIndex<'ctx>>, String> {
|
||||
// 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 = RustSlice::from_slice_expr(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 = index.into_int_value();
|
||||
|
||||
RustNDIndex::SingleElement(index)
|
||||
};
|
||||
rust_ndindices.push(ndindex);
|
||||
}
|
||||
Ok(rust_ndindices)
|
||||
}
|
||||
|
||||
/// Get the value to set `NDIndex::type` for this variant.
|
||||
#[must_use]
|
||||
pub 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 [`NDIndexValue`].
|
||||
pub fn write_to_ndindex<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
dst_ndindex: NDIndexValue<'ctx>,
|
||||
) {
|
||||
let llvm_pi8 = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
|
||||
|
||||
// Set `dst_ndindex.type`
|
||||
dst_ndindex.store_type(ctx, ctx.ctx.i8_type().const_int(self.get_type_id(), false));
|
||||
|
||||
// Set `dst_ndindex_ptr->data`
|
||||
match self {
|
||||
RustNDIndex::SingleElement(in_index) => {
|
||||
let index_ptr = ctx.builder.build_alloca(ctx.ctx.i32_type(), "").unwrap();
|
||||
ctx.builder.build_store(index_ptr, *in_index).unwrap();
|
||||
|
||||
dst_ndindex.store_data(
|
||||
ctx,
|
||||
ctx.builder.build_pointer_cast(index_ptr, llvm_pi8, "").unwrap(),
|
||||
);
|
||||
}
|
||||
RustNDIndex::Slice(in_rust_slice) => {
|
||||
let user_slice_ptr =
|
||||
SliceType::new(ctx.ctx, ctx.ctx.i32_type(), generator.get_size_type(ctx.ctx))
|
||||
.alloca(generator, ctx, None);
|
||||
in_rust_slice.write_to_slice(ctx, user_slice_ptr);
|
||||
|
||||
dst_ndindex.store_data(
|
||||
ctx,
|
||||
ctx.builder.build_pointer_cast(user_slice_ptr.into(), llvm_pi8, "").unwrap(),
|
||||
);
|
||||
}
|
||||
RustNDIndex::NewAxis | RustNDIndex::Ellipsis => {}
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -9,29 +9,18 @@ use super::{
|
||||
UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
|
||||
};
|
||||
use crate::codegen::{
|
||||
irrt,
|
||||
llvm_intrinsics::{call_int_umin, call_memcpy_generic_array},
|
||||
irrt::{call_ndarray_calc_size, call_ndarray_flatten_index},
|
||||
llvm_intrinsics::call_int_umin,
|
||||
stmt::gen_for_callback_incrementing,
|
||||
type_aligned_alloca,
|
||||
types::{ndarray::NDArrayType, structure::StructField},
|
||||
types::{structure::StructField, NDArrayType},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
pub use contiguous::*;
|
||||
pub use indexing::*;
|
||||
pub use nditer::*;
|
||||
pub use view::*;
|
||||
|
||||
mod contiguous;
|
||||
mod indexing;
|
||||
mod nditer;
|
||||
mod view;
|
||||
|
||||
/// Proxy type for accessing an `NDArray` value in LLVM.
|
||||
#[derive(Copy, Clone)]
|
||||
pub struct NDArrayValue<'ctx> {
|
||||
value: PointerValue<'ctx>,
|
||||
dtype: BasicTypeEnum<'ctx>,
|
||||
ndims: Option<u64>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
}
|
||||
@ -51,13 +40,12 @@ impl<'ctx> NDArrayValue<'ctx> {
|
||||
pub fn from_pointer_value(
|
||||
ptr: PointerValue<'ctx>,
|
||||
dtype: BasicTypeEnum<'ctx>,
|
||||
ndims: Option<u64>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> Self {
|
||||
debug_assert!(Self::is_representable(ptr, llvm_usize).is_ok());
|
||||
|
||||
NDArrayValue { value: ptr, dtype, ndims, llvm_usize, name }
|
||||
NDArrayValue { value: ptr, dtype, llvm_usize, name }
|
||||
}
|
||||
|
||||
fn ndims_field(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, IntValue<'ctx>> {
|
||||
@ -88,27 +76,6 @@ impl<'ctx> NDArrayValue<'ctx> {
|
||||
ctx.builder.build_load(pndims, "").map(BasicValueEnum::into_int_value).unwrap()
|
||||
}
|
||||
|
||||
fn itemsize_field(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, IntValue<'ctx>> {
|
||||
self.get_type().get_fields(ctx.ctx).itemsize
|
||||
}
|
||||
|
||||
/// Stores the size of each element `itemsize` into this instance.
|
||||
pub fn store_itemsize<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
generator: &G,
|
||||
itemsize: IntValue<'ctx>,
|
||||
) {
|
||||
debug_assert_eq!(itemsize.get_type(), generator.get_size_type(ctx.ctx));
|
||||
|
||||
self.itemsize_field(ctx).set(ctx, self.value, itemsize, self.name);
|
||||
}
|
||||
|
||||
/// Returns the size of each element of this `NDArray` as a value.
|
||||
pub fn load_itemsize(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
|
||||
self.itemsize_field(ctx).get(ctx, self.value, self.name)
|
||||
}
|
||||
|
||||
fn shape_field(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, PointerValue<'ctx>> {
|
||||
self.get_type().get_fields(ctx.ctx).shape
|
||||
}
|
||||
@ -140,40 +107,6 @@ impl<'ctx> NDArrayValue<'ctx> {
|
||||
NDArrayShapeProxy(self)
|
||||
}
|
||||
|
||||
fn strides_field(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
) -> StructField<'ctx, PointerValue<'ctx>> {
|
||||
self.get_type().get_fields(ctx.ctx).strides
|
||||
}
|
||||
|
||||
/// Returns the double-indirection pointer to the `strides` array, as if by calling
|
||||
/// `getelementptr` on the field.
|
||||
fn ptr_to_strides(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
|
||||
self.strides_field(ctx).ptr_by_gep(ctx, self.value, self.name)
|
||||
}
|
||||
|
||||
/// Stores the array of stride sizes `strides` into this instance.
|
||||
fn store_strides(&self, ctx: &CodeGenContext<'ctx, '_>, strides: PointerValue<'ctx>) {
|
||||
self.strides_field(ctx).set(ctx, self.as_base_value(), strides, self.name);
|
||||
}
|
||||
|
||||
/// Convenience method for creating a new array storing the stride with the given `size`.
|
||||
pub fn create_strides(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
size: IntValue<'ctx>,
|
||||
) {
|
||||
self.store_strides(ctx, ctx.builder.build_array_alloca(llvm_usize, size, "").unwrap());
|
||||
}
|
||||
|
||||
/// Returns a proxy object to the field storing the stride of each dimension of this `NDArray`.
|
||||
#[must_use]
|
||||
pub fn strides(&self) -> NDArrayStridesProxy<'ctx, '_> {
|
||||
NDArrayStridesProxy(self)
|
||||
}
|
||||
|
||||
fn data_field(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, PointerValue<'ctx>> {
|
||||
self.get_type().get_fields(ctx.ctx).data
|
||||
}
|
||||
@ -195,23 +128,23 @@ impl<'ctx> NDArrayValue<'ctx> {
|
||||
|
||||
/// Convenience method for creating a new array storing data elements with the given element
|
||||
/// type `elem_ty` and `size`.
|
||||
///
|
||||
/// The data buffer will be allocated on the stack, and is considered to be owned by this ndarray instance.
|
||||
///
|
||||
/// # Safety
|
||||
///
|
||||
/// The caller must ensure that `shape` and `itemsize` of this ndarray instance is initialized.
|
||||
pub unsafe fn create_data<G: CodeGenerator + ?Sized>(
|
||||
pub fn create_data(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
elem_ty: BasicTypeEnum<'ctx>,
|
||||
size: IntValue<'ctx>,
|
||||
) {
|
||||
let nbytes = self.nbytes(generator, ctx);
|
||||
let itemsize = ctx
|
||||
.builder
|
||||
.build_int_z_extend_or_bit_cast(elem_ty.size_of().unwrap(), size.get_type(), "")
|
||||
.unwrap();
|
||||
let nbytes = ctx.builder.build_int_mul(size, itemsize, "").unwrap();
|
||||
|
||||
let data = type_aligned_alloca(generator, ctx, self.dtype, nbytes, None);
|
||||
self.store_data(ctx, data);
|
||||
|
||||
self.set_strides_contiguous(generator, ctx);
|
||||
// TODO: What about alignment?
|
||||
self.store_data(
|
||||
ctx,
|
||||
ctx.builder.build_array_alloca(ctx.ctx.i8_type(), nbytes, "").unwrap(),
|
||||
);
|
||||
}
|
||||
|
||||
/// Returns a proxy object to the field storing the data of this `NDArray`.
|
||||
@ -219,219 +152,6 @@ impl<'ctx> NDArrayValue<'ctx> {
|
||||
pub fn data(&self) -> NDArrayDataProxy<'ctx, '_> {
|
||||
NDArrayDataProxy(self)
|
||||
}
|
||||
|
||||
/// Copy shape dimensions from an array.
|
||||
pub fn copy_shape_from_array<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
shape: PointerValue<'ctx>,
|
||||
) {
|
||||
let num_items = self.load_ndims(ctx);
|
||||
|
||||
call_memcpy_generic_array(
|
||||
ctx,
|
||||
self.shape().base_ptr(ctx, generator),
|
||||
shape,
|
||||
num_items,
|
||||
ctx.ctx.bool_type().const_zero(),
|
||||
);
|
||||
}
|
||||
|
||||
/// 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: NDArrayValue<'ctx>,
|
||||
) {
|
||||
if self.ndims.is_some() && src_ndarray.ndims.is_some() {
|
||||
assert_eq!(self.ndims, src_ndarray.ndims);
|
||||
} else {
|
||||
let self_ndims = self.load_ndims(ctx);
|
||||
let src_ndims = src_ndarray.load_ndims(ctx);
|
||||
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
ctx.builder.build_int_compare(
|
||||
IntPredicate::EQ,
|
||||
self_ndims,
|
||||
src_ndims,
|
||||
""
|
||||
).unwrap(),
|
||||
"0:AssertionError",
|
||||
"NDArrayValue::copy_shape_from_ndarray: Expected self.ndims ({0}) == src_ndarray.ndims ({1})",
|
||||
[Some(self_ndims), Some(src_ndims), None],
|
||||
ctx.current_loc
|
||||
);
|
||||
}
|
||||
|
||||
let src_shape = src_ndarray.shape().base_ptr(ctx, generator);
|
||||
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: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
strides: PointerValue<'ctx>,
|
||||
) {
|
||||
let num_items = self.load_ndims(ctx);
|
||||
|
||||
call_memcpy_generic_array(
|
||||
ctx,
|
||||
self.strides().base_ptr(ctx, generator),
|
||||
strides,
|
||||
num_items,
|
||||
ctx.ctx.bool_type().const_zero(),
|
||||
);
|
||||
}
|
||||
|
||||
/// 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: NDArrayValue<'ctx>,
|
||||
) {
|
||||
if self.ndims.is_some() && src_ndarray.ndims.is_some() {
|
||||
assert_eq!(self.ndims, src_ndarray.ndims);
|
||||
} else {
|
||||
let self_ndims = self.load_ndims(ctx);
|
||||
let src_ndims = src_ndarray.load_ndims(ctx);
|
||||
|
||||
ctx.make_assert(
|
||||
generator,
|
||||
ctx.builder.build_int_compare(
|
||||
IntPredicate::EQ,
|
||||
self_ndims,
|
||||
src_ndims,
|
||||
""
|
||||
).unwrap(),
|
||||
"0:AssertionError",
|
||||
"NDArrayValue::copy_shape_from_ndarray: Expected self.ndims ({0}) == src_ndarray.ndims ({1})",
|
||||
[Some(self_ndims), Some(src_ndims), None],
|
||||
ctx.current_loc
|
||||
);
|
||||
}
|
||||
|
||||
let src_strides = src_ndarray.strides().base_ptr(ctx, generator);
|
||||
self.copy_strides_from_array(generator, ctx, src_strides);
|
||||
}
|
||||
|
||||
/// Get the `np.size()` of this ndarray.
|
||||
pub fn size<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
) -> IntValue<'ctx> {
|
||||
irrt::ndarray::call_nac3_ndarray_size(generator, ctx, *self)
|
||||
}
|
||||
|
||||
/// Get the `ndarray.nbytes` of this ndarray.
|
||||
pub fn nbytes<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
) -> IntValue<'ctx> {
|
||||
irrt::ndarray::call_nac3_ndarray_nbytes(generator, ctx, *self)
|
||||
}
|
||||
|
||||
/// Get the `len()` of this ndarray.
|
||||
pub fn len<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
) -> IntValue<'ctx> {
|
||||
irrt::ndarray::call_nac3_ndarray_len(generator, ctx, *self)
|
||||
}
|
||||
|
||||
/// 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: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
) -> IntValue<'ctx> {
|
||||
irrt::ndarray::call_nac3_ndarray_is_c_contiguous(generator, ctx, *self)
|
||||
}
|
||||
|
||||
/// 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: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
) {
|
||||
irrt::ndarray::call_nac3_ndarray_set_strides_by_shape(generator, ctx, *self);
|
||||
}
|
||||
|
||||
#[must_use]
|
||||
pub fn make_copy<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> Self {
|
||||
let clone = if self.ndims.is_some() {
|
||||
self.get_type().construct_uninitialized(generator, ctx, None)
|
||||
} else {
|
||||
self.get_type().construct_dyn_ndims(generator, ctx, self.load_ndims(ctx), None)
|
||||
};
|
||||
|
||||
let shape = self.shape();
|
||||
clone.copy_shape_from_array(generator, ctx, shape.base_ptr(ctx, generator));
|
||||
unsafe { 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: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
src: NDArrayValue<'ctx>,
|
||||
) {
|
||||
assert_eq!(self.dtype, src.dtype, "self and src dtype should match");
|
||||
irrt::ndarray::call_nac3_ndarray_copy_data(generator, ctx, src, *self);
|
||||
}
|
||||
|
||||
/// Returns true if this ndarray is unsized - `ndims == 0` and only contains a scalar.
|
||||
#[must_use]
|
||||
pub fn is_unsized(&self) -> Option<bool> {
|
||||
self.ndims.map(|ndims| ndims == 0)
|
||||
}
|
||||
|
||||
/// If this ndarray is unsized, return its sole value as an [`AnyObject`].
|
||||
/// Otherwise, do nothing and return the ndarray itself.
|
||||
// TODO: Rename to get_unsized_element
|
||||
pub fn split_unsized<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
generator: &mut G,
|
||||
ctx: &mut CodeGenContext<'ctx, '_>,
|
||||
) -> ScalarOrNDArray<'ctx> {
|
||||
let Some(is_unsized) = self.is_unsized() else { todo!() };
|
||||
|
||||
if is_unsized {
|
||||
// NOTE: `np.size(self) == 0` here is never possible.
|
||||
let zero = generator.get_size_type(ctx.ctx).const_zero();
|
||||
let value = unsafe { self.data().get_unchecked(ctx, generator, &zero, None) };
|
||||
|
||||
ScalarOrNDArray::Scalar(value)
|
||||
} else {
|
||||
ScalarOrNDArray::NDArray(*self)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> ProxyValue<'ctx> for NDArrayValue<'ctx> {
|
||||
@ -439,12 +159,7 @@ impl<'ctx> ProxyValue<'ctx> for NDArrayValue<'ctx> {
|
||||
type Type = NDArrayType<'ctx>;
|
||||
|
||||
fn get_type(&self) -> Self::Type {
|
||||
NDArrayType::from_type(
|
||||
self.as_base_value().get_type(),
|
||||
self.dtype,
|
||||
self.ndims,
|
||||
self.llvm_usize,
|
||||
)
|
||||
NDArrayType::from_type(self.as_base_value().get_type(), self.dtype, self.llvm_usize)
|
||||
}
|
||||
|
||||
fn as_base_value(&self) -> Self::Base {
|
||||
@ -458,7 +173,7 @@ impl<'ctx> From<NDArrayValue<'ctx>> for PointerValue<'ctx> {
|
||||
}
|
||||
}
|
||||
|
||||
/// Proxy type for accessing the `shape` array of an `NDArray` instance in LLVM.
|
||||
/// Proxy type for accessing the `dims` array of an `NDArray` instance in LLVM.
|
||||
#[derive(Copy, Clone)]
|
||||
pub struct NDArrayShapeProxy<'ctx, 'a>(&'a NDArrayValue<'ctx>);
|
||||
|
||||
@ -550,98 +265,6 @@ impl<'ctx> TypedArrayLikeMutator<'ctx, IntValue<'ctx>> for NDArrayShapeProxy<'ct
|
||||
}
|
||||
}
|
||||
|
||||
/// Proxy type for accessing the `strides` array of an `NDArray` instance in LLVM.
|
||||
#[derive(Copy, Clone)]
|
||||
pub struct NDArrayStridesProxy<'ctx, 'a>(&'a NDArrayValue<'ctx>);
|
||||
|
||||
impl<'ctx> ArrayLikeValue<'ctx> for NDArrayStridesProxy<'ctx, '_> {
|
||||
fn element_type<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
generator: &G,
|
||||
) -> AnyTypeEnum<'ctx> {
|
||||
self.0.strides().base_ptr(ctx, generator).get_type().get_element_type()
|
||||
}
|
||||
|
||||
fn base_ptr<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
_: &G,
|
||||
) -> PointerValue<'ctx> {
|
||||
self.0.strides_field(ctx).get(ctx, self.0.as_base_value(), self.0.name)
|
||||
}
|
||||
|
||||
fn size<G: CodeGenerator + ?Sized>(
|
||||
&self,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
_: &G,
|
||||
) -> IntValue<'ctx> {
|
||||
self.0.load_ndims(ctx)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> ArrayLikeIndexer<'ctx, IntValue<'ctx>> for NDArrayStridesProxy<'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> {
|
||||
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",
|
||||
"index {0} is out of bounds for axis 0 with size {1}",
|
||||
[Some(*idx), Some(self.0.load_ndims(ctx)), None],
|
||||
ctx.current_loc,
|
||||
);
|
||||
|
||||
unsafe { self.ptr_offset_unchecked(ctx, generator, idx, name) }
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> UntypedArrayLikeAccessor<'ctx, IntValue<'ctx>> for NDArrayStridesProxy<'ctx, '_> {}
|
||||
impl<'ctx> UntypedArrayLikeMutator<'ctx, IntValue<'ctx>> for NDArrayStridesProxy<'ctx, '_> {}
|
||||
|
||||
impl<'ctx> TypedArrayLikeAccessor<'ctx, IntValue<'ctx>> for NDArrayStridesProxy<'ctx, '_> {
|
||||
fn downcast_to_type(
|
||||
&self,
|
||||
_: &mut CodeGenContext<'ctx, '_>,
|
||||
value: BasicValueEnum<'ctx>,
|
||||
) -> IntValue<'ctx> {
|
||||
value.into_int_value()
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> TypedArrayLikeMutator<'ctx, IntValue<'ctx>> for NDArrayStridesProxy<'ctx, '_> {
|
||||
fn upcast_from_type(
|
||||
&self,
|
||||
_: &mut CodeGenContext<'ctx, '_>,
|
||||
value: IntValue<'ctx>,
|
||||
) -> BasicValueEnum<'ctx> {
|
||||
value.into()
|
||||
}
|
||||
}
|
||||
|
||||
/// Proxy type for accessing the `data` array of an `NDArray` instance in LLVM.
|
||||
#[derive(Copy, Clone)]
|
||||
pub struct NDArrayDataProxy<'ctx, 'a>(&'a NDArrayValue<'ctx>);
|
||||
@ -668,12 +291,7 @@ impl<'ctx> ArrayLikeValue<'ctx> for NDArrayDataProxy<'ctx, '_> {
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
generator: &G,
|
||||
) -> IntValue<'ctx> {
|
||||
irrt::ndarray::call_ndarray_calc_size(
|
||||
generator,
|
||||
ctx,
|
||||
&self.as_slice_value(ctx, generator),
|
||||
(None, None),
|
||||
)
|
||||
call_ndarray_calc_size(generator, ctx, &self.as_slice_value(ctx, generator), (None, None))
|
||||
}
|
||||
}
|
||||
|
||||
@ -782,7 +400,7 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
|
||||
indices_elem_ty.get_bit_width()
|
||||
);
|
||||
|
||||
let index = irrt::ndarray::call_ndarray_flatten_index(generator, ctx, *self.0, indices);
|
||||
let index = call_ndarray_flatten_index(generator, ctx, *self.0, indices);
|
||||
let sizeof_elem = ctx
|
||||
.builder
|
||||
.build_int_truncate_or_bit_cast(
|
||||
@ -898,36 +516,3 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> UntypedArrayLikeMutator<'ctx,
|
||||
for NDArrayDataProxy<'ctx, '_>
|
||||
{
|
||||
}
|
||||
|
||||
/// A version of [`call_nac3_ndarray_set_strides_by_shape`] in Rust.
|
||||
///
|
||||
/// This function is used generating strides for globally defined contiguous ndarrays.
|
||||
#[must_use]
|
||||
pub fn make_contiguous_strides(itemsize: u64, ndims: u64, shape: &[u64]) -> Vec<u64> {
|
||||
let mut strides = Vec::with_capacity(ndims as usize);
|
||||
let mut stride_product = 1u64;
|
||||
for i in 0..ndims {
|
||||
let axis = ndims - i - 1;
|
||||
strides[axis as usize] = stride_product * itemsize;
|
||||
stride_product *= shape[axis as usize];
|
||||
}
|
||||
strides
|
||||
}
|
||||
|
||||
/// A convenience enum for implementing functions that acts on scalars or ndarrays or both.
|
||||
#[derive(Clone, Copy)]
|
||||
pub enum ScalarOrNDArray<'ctx> {
|
||||
Scalar(BasicValueEnum<'ctx>),
|
||||
NDArray(NDArrayValue<'ctx>),
|
||||
}
|
||||
|
||||
impl<'ctx> ScalarOrNDArray<'ctx> {
|
||||
/// Get the underlying [`BasicValueEnum<'ctx>`] of this [`ScalarOrNDArray`].
|
||||
#[must_use]
|
||||
pub fn to_basic_value_enum(self) -> BasicValueEnum<'ctx> {
|
||||
match self {
|
||||
ScalarOrNDArray::Scalar(scalar) => scalar,
|
||||
ScalarOrNDArray::NDArray(ndarray) => ndarray.as_base_value().into(),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -1,176 +0,0 @@
|
||||
use inkwell::{
|
||||
types::{BasicType, IntType},
|
||||
values::{BasicValueEnum, IntValue, PointerValue},
|
||||
AddressSpace,
|
||||
};
|
||||
|
||||
use super::{NDArrayValue, ProxyValue, TypedArrayLikeAccessor, TypedArrayLikeMutator};
|
||||
use crate::codegen::{
|
||||
irrt,
|
||||
stmt::{gen_for_callback, BreakContinueHooks},
|
||||
types::{ndarray::NDIterType, structure::StructField},
|
||||
values::{ArraySliceValue, TypedArrayLikeAdapter},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
#[derive(Copy, Clone)]
|
||||
pub struct NDIterValue<'ctx> {
|
||||
value: PointerValue<'ctx>,
|
||||
parent: NDArrayValue<'ctx>,
|
||||
indices: ArraySliceValue<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
}
|
||||
|
||||
impl<'ctx> NDIterValue<'ctx> {
|
||||
/// Checks whether `value` is an instance of `NDArray`, returning [Err] if `value` is not an
|
||||
/// instance.
|
||||
pub fn is_representable(
|
||||
value: PointerValue<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
) -> Result<(), String> {
|
||||
<Self as ProxyValue>::Type::is_representable(value.get_type(), llvm_usize)
|
||||
}
|
||||
|
||||
/// Creates an [`NDArrayValue`] from a [`PointerValue`].
|
||||
#[must_use]
|
||||
pub fn from_pointer_value(
|
||||
ptr: PointerValue<'ctx>,
|
||||
parent: NDArrayValue<'ctx>,
|
||||
indices: ArraySliceValue<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> Self {
|
||||
debug_assert!(Self::is_representable(ptr, llvm_usize).is_ok());
|
||||
|
||||
Self { value: ptr, parent, indices, llvm_usize, name }
|
||||
}
|
||||
|
||||
/// 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: &G,
|
||||
ctx: &CodeGenContext<'ctx, '_>,
|
||||
) -> IntValue<'ctx> {
|
||||
irrt::ndarray::call_nac3_nditer_has_element(generator, ctx, *self)
|
||||
}
|
||||
|
||||
/// 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: &G, ctx: &CodeGenContext<'ctx, '_>) {
|
||||
irrt::ndarray::call_nac3_nditer_next(generator, ctx, *self);
|
||||
}
|
||||
|
||||
fn element(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, PointerValue<'ctx>> {
|
||||
self.get_type().get_fields(ctx.ctx).element
|
||||
}
|
||||
|
||||
/// Get pointer to the current element.
|
||||
#[must_use]
|
||||
pub fn get_pointer(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
|
||||
let elem_ty = self.parent.dtype;
|
||||
|
||||
let p = self.element(ctx).get(ctx, self.as_base_value(), None);
|
||||
ctx.builder
|
||||
.build_pointer_cast(p, elem_ty.ptr_type(AddressSpace::default()), "element")
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
/// Get the value of the current element.
|
||||
#[must_use]
|
||||
pub fn get_scalar(&self, ctx: &CodeGenContext<'ctx, '_>) -> BasicValueEnum<'ctx> {
|
||||
let p = self.get_pointer(ctx);
|
||||
ctx.builder.build_load(p, "value").unwrap()
|
||||
}
|
||||
|
||||
fn nth(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, IntValue<'ctx>> {
|
||||
self.get_type().get_fields(ctx.ctx).nth
|
||||
}
|
||||
|
||||
/// Get the index of the current element if this ndarray were a flat ndarray.
|
||||
#[must_use]
|
||||
pub fn get_index(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
|
||||
self.nth(ctx).get(ctx, self.as_base_value(), None)
|
||||
}
|
||||
|
||||
/// Get the indices of the current element.
|
||||
#[must_use]
|
||||
pub fn get_indices(
|
||||
&'ctx self,
|
||||
) -> impl TypedArrayLikeAccessor<'ctx, IntValue<'ctx>> + TypedArrayLikeMutator<'ctx, IntValue<'ctx>>
|
||||
{
|
||||
TypedArrayLikeAdapter::from(
|
||||
self.indices,
|
||||
Box::new(|ctx, val| {
|
||||
ctx.builder
|
||||
.build_int_z_extend_or_bit_cast(val.into_int_value(), self.llvm_usize, "")
|
||||
.unwrap()
|
||||
}),
|
||||
Box::new(|_, val| val.into()),
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> ProxyValue<'ctx> for NDIterValue<'ctx> {
|
||||
type Base = PointerValue<'ctx>;
|
||||
type Type = NDIterType<'ctx>;
|
||||
|
||||
fn get_type(&self) -> Self::Type {
|
||||
NDIterType::from_type(self.as_base_value().get_type(), self.llvm_usize)
|
||||
}
|
||||
|
||||
fn as_base_value(&self) -> Self::Base {
|
||||
self.value
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> From<NDIterValue<'ctx>> for PointerValue<'ctx> {
|
||||
fn from(value: NDIterValue<'ctx>) -> Self {
|
||||
value.as_base_value()
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> NDArrayValue<'ctx> {
|
||||
/// Iterate through every element in the ndarray.
|
||||
///
|
||||
/// `body` has access to [`BreakContinueHooks`] to short-circuit and [`NDIterValue`] 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>,
|
||||
NDIterValue<'ctx>,
|
||||
) -> Result<(), String>,
|
||||
{
|
||||
gen_for_callback(
|
||||
generator,
|
||||
ctx,
|
||||
Some("ndarray_foreach"),
|
||||
|generator, ctx| {
|
||||
Ok(NDIterType::new(generator, ctx.ctx).construct(generator, ctx, *self))
|
||||
},
|
||||
|generator, ctx, nditer| Ok(nditer.has_element(generator, ctx)),
|
||||
|generator, ctx, hooks, nditer| body(generator, ctx, hooks, nditer),
|
||||
|generator, ctx, nditer| {
|
||||
nditer.next(generator, ctx);
|
||||
Ok(())
|
||||
},
|
||||
)
|
||||
}
|
||||
}
|
||||
@ -1,36 +0,0 @@
|
||||
use std::iter::{once, repeat_n};
|
||||
|
||||
use itertools::Itertools;
|
||||
|
||||
use crate::codegen::{
|
||||
values::ndarray::{NDArrayValue, RustNDIndex},
|
||||
CodeGenContext, CodeGenerator,
|
||||
};
|
||||
|
||||
impl<'ctx> NDArrayValue<'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. Otherwise, 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 {
|
||||
assert!(self.ndims.is_some(), "NDArrayValue::atleast_nd is only supported for instances with compile-time known ndims (self.ndims = Some(...))");
|
||||
|
||||
let ndims = self.ndims.unwrap();
|
||||
|
||||
if ndims < ndmin {
|
||||
// Extend the dimensions with np.newaxis.
|
||||
let indices = repeat_n(RustNDIndex::NewAxis, (ndmin - ndims) as usize)
|
||||
.chain(once(RustNDIndex::Ellipsis))
|
||||
.collect_vec();
|
||||
self.index(generator, ctx, &indices)
|
||||
} else {
|
||||
*self
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1,3 +0,0 @@
|
||||
pub use slice::*;
|
||||
|
||||
mod slice;
|
||||
@ -1,231 +0,0 @@
|
||||
use inkwell::{
|
||||
types::IntType,
|
||||
values::{IntValue, PointerValue},
|
||||
};
|
||||
|
||||
use nac3parser::ast::Expr;
|
||||
|
||||
use crate::{
|
||||
codegen::{
|
||||
types::{structure::StructField, utils::SliceType},
|
||||
values::ProxyValue,
|
||||
CodeGenContext, CodeGenerator,
|
||||
},
|
||||
typecheck::typedef::Type,
|
||||
};
|
||||
|
||||
/// An IRRT representation of an (unresolved) slice.
|
||||
#[derive(Copy, Clone)]
|
||||
pub struct SliceValue<'ctx> {
|
||||
value: PointerValue<'ctx>,
|
||||
int_ty: IntType<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
}
|
||||
|
||||
impl<'ctx> SliceValue<'ctx> {
|
||||
/// Checks whether `value` is an instance of `ContiguousNDArray`, returning [Err] if `value` is
|
||||
/// not an instance.
|
||||
pub fn is_representable(
|
||||
value: PointerValue<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
) -> Result<(), String> {
|
||||
<Self as ProxyValue<'ctx>>::Type::is_representable(value.get_type(), llvm_usize)
|
||||
}
|
||||
|
||||
/// Creates an [`SliceValue`] from a [`PointerValue`].
|
||||
#[must_use]
|
||||
pub fn from_pointer_value(
|
||||
ptr: PointerValue<'ctx>,
|
||||
int_ty: IntType<'ctx>,
|
||||
llvm_usize: IntType<'ctx>,
|
||||
name: Option<&'ctx str>,
|
||||
) -> Self {
|
||||
debug_assert!(Self::is_representable(ptr, llvm_usize).is_ok());
|
||||
|
||||
Self { value: ptr, int_ty, llvm_usize, name }
|
||||
}
|
||||
|
||||
fn start_defined_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
|
||||
self.get_type().get_fields().start_defined
|
||||
}
|
||||
|
||||
pub fn load_start_defined(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
|
||||
self.start_defined_field().get(ctx, self.value, self.name)
|
||||
}
|
||||
|
||||
fn start_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
|
||||
self.get_type().get_fields().start
|
||||
}
|
||||
|
||||
pub fn load_start(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
|
||||
self.start_field().get(ctx, self.value, self.name)
|
||||
}
|
||||
|
||||
pub fn store_start(&self, ctx: &CodeGenContext<'ctx, '_>, value: Option<IntValue<'ctx>>) {
|
||||
match value {
|
||||
Some(start) => {
|
||||
self.start_defined_field().set(
|
||||
ctx,
|
||||
self.value,
|
||||
ctx.ctx.bool_type().const_all_ones(),
|
||||
self.name,
|
||||
);
|
||||
self.start_field().set(ctx, self.value, start, self.name);
|
||||
}
|
||||
|
||||
None => self.start_defined_field().set(
|
||||
ctx,
|
||||
self.value,
|
||||
ctx.ctx.bool_type().const_zero(),
|
||||
self.name,
|
||||
),
|
||||
}
|
||||
}
|
||||
|
||||
fn stop_defined_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
|
||||
self.get_type().get_fields().stop_defined
|
||||
}
|
||||
|
||||
pub fn load_stop_defined(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
|
||||
self.stop_defined_field().get(ctx, self.value, self.name)
|
||||
}
|
||||
|
||||
fn stop_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
|
||||
self.get_type().get_fields().stop
|
||||
}
|
||||
|
||||
pub fn load_stop(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
|
||||
self.stop_field().get(ctx, self.value, self.name)
|
||||
}
|
||||
|
||||
pub fn store_stop(&self, ctx: &CodeGenContext<'ctx, '_>, value: Option<IntValue<'ctx>>) {
|
||||
match value {
|
||||
Some(stop) => {
|
||||
self.stop_defined_field().set(
|
||||
ctx,
|
||||
self.value,
|
||||
ctx.ctx.bool_type().const_all_ones(),
|
||||
self.name,
|
||||
);
|
||||
self.stop_field().set(ctx, self.value, stop, self.name);
|
||||
}
|
||||
|
||||
None => self.stop_defined_field().set(
|
||||
ctx,
|
||||
self.value,
|
||||
ctx.ctx.bool_type().const_zero(),
|
||||
self.name,
|
||||
),
|
||||
}
|
||||
}
|
||||
|
||||
fn step_defined_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
|
||||
self.get_type().get_fields().step_defined
|
||||
}
|
||||
|
||||
pub fn load_step_defined(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
|
||||
self.step_defined_field().get(ctx, self.value, self.name)
|
||||
}
|
||||
|
||||
fn step_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
|
||||
self.get_type().get_fields().step
|
||||
}
|
||||
|
||||
pub fn load_step(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
|
||||
self.step_field().get(ctx, self.value, self.name)
|
||||
}
|
||||
|
||||
pub fn store_step(&self, ctx: &CodeGenContext<'ctx, '_>, value: Option<IntValue<'ctx>>) {
|
||||
match value {
|
||||
Some(step) => {
|
||||
self.step_defined_field().set(
|
||||
ctx,
|
||||
self.value,
|
||||
ctx.ctx.bool_type().const_all_ones(),
|
||||
self.name,
|
||||
);
|
||||
self.step_field().set(ctx, self.value, step, self.name);
|
||||
}
|
||||
|
||||
None => self.step_defined_field().set(
|
||||
ctx,
|
||||
self.value,
|
||||
ctx.ctx.bool_type().const_zero(),
|
||||
self.name,
|
||||
),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> ProxyValue<'ctx> for SliceValue<'ctx> {
|
||||
type Base = PointerValue<'ctx>;
|
||||
type Type = SliceType<'ctx>;
|
||||
|
||||
fn get_type(&self) -> Self::Type {
|
||||
Self::Type::from_type(self.value.get_type(), self.int_ty, self.llvm_usize)
|
||||
}
|
||||
|
||||
fn as_base_value(&self) -> Self::Base {
|
||||
self.value
|
||||
}
|
||||
}
|
||||
|
||||
impl<'ctx> From<SliceValue<'ctx>> for PointerValue<'ctx> {
|
||||
fn from(value: SliceValue<'ctx>) -> Self {
|
||||
value.as_base_value()
|
||||
}
|
||||
}
|
||||
|
||||
/// A slice represented in compile-time by `start`, `stop` and `step`, all held as LLVM values.
|
||||
// TODO: Rename this to CTConstSlice
|
||||
#[derive(Debug, Copy, Clone)]
|
||||
pub struct RustSlice<'ctx> {
|
||||
int_ty: IntType<'ctx>,
|
||||
start: Option<IntValue<'ctx>>,
|
||||
stop: Option<IntValue<'ctx>>,
|
||||
step: Option<IntValue<'ctx>>,
|
||||
}
|
||||
|
||||
impl<'ctx> RustSlice<'ctx> {
|
||||
/// Generate LLVM IR for an [`ExprKind::Slice`] and convert it into a [`RustSlice`].
|
||||
#[allow(clippy::type_complexity)]
|
||||
pub fn from_slice_expr<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>, String> {
|
||||
let mut value_mapper = |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)?
|
||||
.map(|value| {
|
||||
value.to_basic_value_enum(ctx, generator, ctx.primitives.int32)
|
||||
})
|
||||
.unwrap()?;
|
||||
|
||||
Some(value_expr.into_int_value())
|
||||
}
|
||||
})
|
||||
};
|
||||
|
||||
let start = value_mapper(lower)?;
|
||||
let stop = value_mapper(upper)?;
|
||||
let step = value_mapper(step)?;
|
||||
|
||||
Ok(RustSlice { int_ty: ctx.ctx.i32_type(), start, stop, step })
|
||||
}
|
||||
|
||||
/// Write the contents to an LLVM [`SliceValue`].
|
||||
pub fn write_to_slice(&self, ctx: &CodeGenContext<'ctx, '_>, dst_slice_ptr: SliceValue<'ctx>) {
|
||||
assert_eq!(self.int_ty, dst_slice_ptr.int_ty);
|
||||
|
||||
dst_slice_ptr.store_start(ctx, self.start);
|
||||
dst_slice_ptr.store_stop(ctx, self.stop);
|
||||
dst_slice_ptr.store_step(ctx, self.step);
|
||||
}
|
||||
}
|
||||
@ -6,6 +6,7 @@ edition = "2021"
|
||||
|
||||
[features]
|
||||
no-escape-analysis = ["nac3core/no-escape-analysis"]
|
||||
tracing = ["nac3core/tracing"]
|
||||
|
||||
[dependencies]
|
||||
parking_lot = "0.12"
|
||||
|
||||
@ -65,7 +65,7 @@ struct cslice {
|
||||
size_t len;
|
||||
};
|
||||
|
||||
void output_int32_list(struct cslice* slice) {
|
||||
void output_int32_list(const struct cslice* slice) {
|
||||
const int32_t* data = (int32_t*)slice->data;
|
||||
|
||||
putchar('[');
|
||||
@ -80,7 +80,7 @@ void output_int32_list(struct cslice* slice) {
|
||||
putchar('\n');
|
||||
}
|
||||
|
||||
void output_str(struct cslice* slice) {
|
||||
void output_str(const struct cslice* slice) {
|
||||
const char* data = (const char*)slice->data;
|
||||
|
||||
for (size_t i = 0; i < slice->len; ++i) {
|
||||
@ -88,12 +88,12 @@ void output_str(struct cslice* slice) {
|
||||
}
|
||||
}
|
||||
|
||||
void output_strln(struct cslice* slice) {
|
||||
void output_strln(const struct cslice* slice) {
|
||||
output_str(slice);
|
||||
putchar('\n');
|
||||
}
|
||||
|
||||
uint64_t dbg_stack_address(__attribute__((unused)) struct cslice* slice) {
|
||||
uint64_t dbg_stack_address(__attribute__((unused)) const struct cslice* slice) {
|
||||
int i;
|
||||
void* ptr = (void*)&i;
|
||||
return (uintptr_t)ptr;
|
||||
|
||||
@ -15,8 +15,11 @@ use parking_lot::{Mutex, RwLock};
|
||||
|
||||
use nac3core::{
|
||||
codegen::{
|
||||
concrete_type::ConcreteTypeStore, irrt::load_irrt, CodeGenLLVMOptions,
|
||||
CodeGenTargetMachineOptions, CodeGenTask, DefaultCodeGenerator, WithCall, WorkerRegistry,
|
||||
concrete_type::ConcreteTypeStore,
|
||||
irrt::load_irrt,
|
||||
tracert::{load_tracert, TraceRuntimeConfig},
|
||||
CodeGenLLVMOptions, CodeGenTargetMachineOptions, CodeGenTask, DefaultCodeGenerator,
|
||||
WithCall, WorkerRegistry,
|
||||
},
|
||||
inkwell::{
|
||||
memory_buffer::MemoryBuffer, module::Linkage, passes::PassBuilderOptions,
|
||||
@ -76,6 +79,9 @@ struct CommandLineArgs {
|
||||
/// Additional target features to enable/disable, specified using the `+`/`-` prefixes.
|
||||
#[arg(long)]
|
||||
target_features: Option<String>,
|
||||
|
||||
#[arg(long)]
|
||||
trace: Vec<String>,
|
||||
}
|
||||
|
||||
fn handle_typevar_definition(
|
||||
@ -276,8 +282,16 @@ fn handle_global_var(
|
||||
|
||||
fn main() {
|
||||
let cli = CommandLineArgs::parse();
|
||||
let CommandLineArgs { file_name, threads, opt_level, emit_llvm, triple, mcpu, target_features } =
|
||||
cli;
|
||||
let CommandLineArgs {
|
||||
file_name,
|
||||
threads,
|
||||
opt_level,
|
||||
emit_llvm,
|
||||
triple,
|
||||
mcpu,
|
||||
target_features,
|
||||
trace,
|
||||
} = cli;
|
||||
|
||||
Target::initialize_all(&InitializationConfig::default());
|
||||
|
||||
@ -306,6 +320,7 @@ fn main() {
|
||||
// The default behavior for -O<n> where n>3 defaults to O3 for both Clang and GCC
|
||||
_ => OptimizationLevel::Aggressive,
|
||||
};
|
||||
let tracert_config = TraceRuntimeConfig { enabled_tags: trace };
|
||||
|
||||
let target_machine_options = CodeGenTargetMachineOptions {
|
||||
triple,
|
||||
@ -350,6 +365,14 @@ fn main() {
|
||||
irrt.write_bitcode_to_path(Path::new("irrt.bc"));
|
||||
}
|
||||
|
||||
// Process tracert
|
||||
let tracert = load_tracert(&context, &tracert_config);
|
||||
if let Some(tracert) = &tracert {
|
||||
if emit_llvm {
|
||||
tracert.write_bitcode_to_path(Path::new("tracert.bc"));
|
||||
}
|
||||
}
|
||||
|
||||
// Process the Python script
|
||||
let parser_result = parser::parse_program(&program, file_name.into()).unwrap();
|
||||
|
||||
@ -458,7 +481,8 @@ fn main() {
|
||||
let threads = (0..threads)
|
||||
.map(|i| Box::new(DefaultCodeGenerator::new(format!("module{i}"), size_t)))
|
||||
.collect();
|
||||
let (registry, handles) = WorkerRegistry::create_workers(threads, top_level, &llvm_options, &f);
|
||||
let (registry, handles) =
|
||||
WorkerRegistry::create_workers(threads, top_level, &llvm_options, &tracert_config, &f);
|
||||
registry.add_task(task);
|
||||
registry.wait_tasks_complete(handles);
|
||||
|
||||
@ -484,6 +508,9 @@ fn main() {
|
||||
}
|
||||
|
||||
main.link_in_module(irrt).unwrap();
|
||||
if let Some(tracert) = tracert {
|
||||
main.link_in_module(tracert).unwrap();
|
||||
}
|
||||
|
||||
// Private all functions except "run"
|
||||
let mut function_iter = main.get_first_function();
|
||||
|
||||
@ -1,15 +1,15 @@
|
||||
{ pkgs } : [
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libunwind-19.1.4-1-any.pkg.tar.zst";
|
||||
sha256 = "0frb5k16bbxdf8g379d16vl3qrh7n9pydn83gpfxpvwf3qlvnzyl";
|
||||
name = "mingw-w64-clang-x86_64-libunwind-19.1.4-1-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libunwind-18.1.8-2-any.pkg.tar.zst";
|
||||
sha256 = "0f9m76dx40iy794nfks0360gvjhdg6yngb2lyhwp4xd76rn5081m";
|
||||
name = "mingw-w64-clang-x86_64-libunwind-18.1.8-2-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libc++-19.1.4-1-any.pkg.tar.zst";
|
||||
sha256 = "0wh5km0v8j50pqz9bxb4f0w7r8zhsvssrjvc94np53iq8wjagk86";
|
||||
name = "mingw-w64-clang-x86_64-libc++-19.1.4-1-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libc++-18.1.8-2-any.pkg.tar.zst";
|
||||
sha256 = "17savj9wys9my2ji7vyba7wwqkvzdjwnkb3k4858wxrjbzbfa6lk";
|
||||
name = "mingw-w64-clang-x86_64-libc++-18.1.8-2-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
@ -31,9 +31,9 @@
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-xz-5.6.3-3-any.pkg.tar.zst";
|
||||
sha256 = "1a7gc462gnrjy5qb0zfkr9qm8bsnnf02y6wp3c59n618dhsq7rcf";
|
||||
name = "mingw-w64-clang-x86_64-xz-5.6.3-3-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-xz-5.6.2-2-any.pkg.tar.zst";
|
||||
sha256 = "0phb9hwqksk1rg29yhwlc7si78zav19c2kac0i841pc7mc2n9gzx";
|
||||
name = "mingw-w64-clang-x86_64-xz-5.6.2-2-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
@ -43,9 +43,9 @@
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libxml2-2.12.9-2-any.pkg.tar.zst";
|
||||
sha256 = "1b1r5llgqv88id8iwhqh23qwqmn5ic9hdamdc8xzij9hmcvdmmci";
|
||||
name = "mingw-w64-clang-x86_64-libxml2-2.12.9-2-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libxml2-2.12.9-1-any.pkg.tar.zst";
|
||||
sha256 = "0cjz2vj9yz6k5xj601cp0yk631rrr0z94ciamwqrvclb0yhakf25";
|
||||
name = "mingw-w64-clang-x86_64-libxml2-2.12.9-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
@ -55,87 +55,75 @@
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-llvm-libs-19.1.4-1-any.pkg.tar.zst";
|
||||
sha256 = "1clrbm8dk893byj8s15pgcgqqijm2zkd10zgyakamd8m354kj9q4";
|
||||
name = "mingw-w64-clang-x86_64-llvm-libs-19.1.4-1-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-llvm-libs-18.1.8-1-any.pkg.tar.zst";
|
||||
sha256 = "0rpbgvvinsqflhd3nhfxk0g0yy8j80zzw5yx6573ak0m78a9fa06";
|
||||
name = "mingw-w64-clang-x86_64-llvm-libs-18.1.8-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-llvm-19.1.4-1-any.pkg.tar.zst";
|
||||
sha256 = "1iz2c9475h8p20ydpp0znbhyb62rlrk7wr7xl7cmwbam7wkwr8rn";
|
||||
name = "mingw-w64-clang-x86_64-llvm-19.1.4-1-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-llvm-18.1.8-1-any.pkg.tar.zst";
|
||||
sha256 = "185g5h8q3x3rav9lp2njln58ny2idh2067fd02j3nsbik6glshpf";
|
||||
name = "mingw-w64-clang-x86_64-llvm-18.1.8-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-clang-libs-19.1.4-1-any.pkg.tar.zst";
|
||||
sha256 = "1hidciwlakxrp4kyb0j2v6g4lv76nn834g6b88w1j94fk3qc765d";
|
||||
name = "mingw-w64-clang-x86_64-clang-libs-19.1.4-1-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-clang-libs-18.1.8-1-any.pkg.tar.zst";
|
||||
sha256 = "089hji3yd7wsd03v9mdfgc99l5k1dql8kg7p3hy13vrbgfsabxhc";
|
||||
name = "mingw-w64-clang-x86_64-clang-libs-18.1.8-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-compiler-rt-19.1.4-1-any.pkg.tar.zst";
|
||||
sha256 = "1m1yhjkgzlbk10sv966qk4yji009ga0lr25gpgj2w7mcd2wixcr3";
|
||||
name = "mingw-w64-clang-x86_64-compiler-rt-19.1.4-1-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-compiler-rt-18.1.8-1-any.pkg.tar.zst";
|
||||
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(pkgs.fetchurl {
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(pkgs.fetchurl {
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(pkgs.fetchurl {
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(pkgs.fetchurl {
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|
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(pkgs.fetchurl {
|
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|
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(pkgs.fetchurl {
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|
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(pkgs.fetchurl {
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|
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(pkgs.fetchurl {
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|
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(pkgs.fetchurl {
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|
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(pkgs.fetchurl {
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(pkgs.fetchurl {
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@ -151,9 +139,9 @@
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(pkgs.fetchurl {
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(pkgs.fetchurl {
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@ -175,45 +163,57 @@
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(pkgs.fetchurl {
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|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-libuv-1.48.0-1-any.pkg.tar.zst";
|
||||
sha256 = "0kfzanvx7hg7bvy35h2z2vcfxvwn44sikd36mvzhkv6c3c6y84sn";
|
||||
name = "mingw-w64-clang-x86_64-libuv-1.48.0-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
@ -277,9 +277,9 @@
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-cmake-3.31.2-3-any.pkg.tar.zst";
|
||||
sha256 = "139f91r392c68hsajm0c81690pmzkywb0p4x8ms8ms53ncxnz6gz";
|
||||
name = "mingw-w64-clang-x86_64-cmake-3.31.2-3-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-cmake-3.30.3-1-any.pkg.tar.zst";
|
||||
sha256 = "0fjwf6xxzli6rcsbzr1razldmm538ibkyf5kw132lpaz5wma9bj8";
|
||||
name = "mingw-w64-clang-x86_64-cmake-3.30.3-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
@ -289,9 +289,9 @@
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-ncurses-6.5.20240831-1-any.pkg.tar.zst";
|
||||
sha256 = "1hlfj9g4s767s502sawwbcv4a0xd3ym3ip4jswmhq48wh5050iyb";
|
||||
name = "mingw-w64-clang-x86_64-ncurses-6.5.20240831-1-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-ncurses-6.4.20231217-1-any.pkg.tar.zst";
|
||||
sha256 = "00046d52zsr8zjifl7h22jfihhh53h20ipvbqmvf9myssw2fwjza";
|
||||
name = "mingw-w64-clang-x86_64-ncurses-6.4.20231217-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
@ -306,18 +306,18 @@
|
||||
name = "mingw-w64-clang-x86_64-readline-8.2.013-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-sqlite3-3.47.2-1-any.pkg.tar.zst";
|
||||
sha256 = "10pavblv9yjirlm5hix9aikpswhiamry097clba6jcvsajlx4azy";
|
||||
name = "mingw-w64-clang-x86_64-sqlite3-3.47.2-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-tcl-8.6.13-1-any.pkg.tar.zst";
|
||||
sha256 = "0paaqwk0sfy2zxwlxkmxf2bqq46lyg0sx7cqgzknvazwx8xa2z4x";
|
||||
name = "mingw-w64-clang-x86_64-tcl-8.6.13-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-sqlite3-3.46.1-1-any.pkg.tar.zst";
|
||||
sha256 = "1axplxyjnaz411qzjjqwbj55fbrh4akq3plm2p1sx64jp844xpyq";
|
||||
name = "mingw-w64-clang-x86_64-sqlite3-3.46.1-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-tk-8.6.13-1-any.pkg.tar.zst";
|
||||
sha256 = "12f6lqx1sglczcnz2ns6sxw9cxwm1klxajqzcrbnfwln1nllz2nd";
|
||||
@ -325,38 +325,44 @@
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-tzdata-2024b-1-any.pkg.tar.zst";
|
||||
sha256 = "0jihnr1i7vyzczxz60ds1x3gcm3p4ad2pq9d5vvpwjdwrxkvxmkc";
|
||||
name = "mingw-w64-clang-x86_64-tzdata-2024b-1-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-tzdata-2024a-1-any.pkg.tar.zst";
|
||||
sha256 = "1lsfn3759cyf56zlmfvgy6ihs4iks6zhlnrbfmnq5wml02k936ji";
|
||||
name = "mingw-w64-clang-x86_64-tzdata-2024a-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-python-3.12.7-3-any.pkg.tar.zst";
|
||||
sha256 = "1v15j2pzy9wj4n1rjngdi2hf8h0l9z4lri3xb86yvdv1xl2msj6h";
|
||||
name = "mingw-w64-clang-x86_64-python-3.12.7-3-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-python3.12-3.12.1-2-any.pkg.tar.zst";
|
||||
sha256 = "0wmd39wl9z237w093a7c6hl5pclca9yvwxn0kiw6i2njk3sjv51a";
|
||||
name = "mingw-w64-clang-x86_64-python3.12-3.12.1-2-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-llvm-openmp-19.1.4-2-any.pkg.tar.zst";
|
||||
sha256 = "1pn1fbj74rx837s9z8gqs4b0cr7kqi5m1m2mi9ibjpw64m1aqwxv";
|
||||
name = "mingw-w64-clang-x86_64-llvm-openmp-19.1.4-2-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-python-3.11.9-1-any.pkg.tar.zst";
|
||||
sha256 = "0ah1idjqxg7jc07a1gz9z766rjjd0f0c6ri4hpcsimsrbj1zjd3c";
|
||||
name = "mingw-w64-clang-x86_64-python-3.11.9-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-openblas-0.3.28-2-any.pkg.tar.zst";
|
||||
sha256 = "18p1zhf7h3k3phf3bl483jg3k7y9zq375z6ww75g62158ic9lfyc";
|
||||
name = "mingw-w64-clang-x86_64-openblas-0.3.28-2-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-llvm-openmp-18.1.8-1-any.pkg.tar.zst";
|
||||
sha256 = "0cy2v0l4af24j34mzj5q5nlzcqhackfajlfj1rpf6mb3rbz23qw9";
|
||||
name = "mingw-w64-clang-x86_64-llvm-openmp-18.1.8-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-python-numpy-2.1.1-2-any.pkg.tar.zst";
|
||||
sha256 = "1kiy7ail04ias47xbbhl9vpsz02g0g3f29ncgx5gcks9vgqldp6m";
|
||||
name = "mingw-w64-clang-x86_64-python-numpy-2.1.1-2-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-openblas-0.3.28-1-any.pkg.tar.zst";
|
||||
sha256 = "1pskcqc1lg9p8m8rk7bw3mz7mn7vw5fpl7zxa23bhjn02p5b79qq";
|
||||
name = "mingw-w64-clang-x86_64-openblas-0.3.28-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-python-setuptools-75.6.0-1-any.pkg.tar.zst";
|
||||
sha256 = "03l04kjmy5p9whaw0h619gdg7yw1gxbz8phifq4pzh3c1wlw7yfd";
|
||||
name = "mingw-w64-clang-x86_64-python-setuptools-75.6.0-1-any.pkg.tar.zst";
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-python-numpy-2.0.1-1-any.pkg.tar.zst";
|
||||
sha256 = "0ks6q8v58h4wmr2pzsjl2xm4f63g0psvfm0jwlz24mqfxp8gqfcc";
|
||||
name = "mingw-w64-clang-x86_64-python-numpy-2.0.1-1-any.pkg.tar.zst";
|
||||
})
|
||||
|
||||
(pkgs.fetchurl {
|
||||
url = "https://mirror.msys2.org/mingw/clang64/mingw-w64-clang-x86_64-python-setuptools-74.0.0-1-any.pkg.tar.zst";
|
||||
sha256 = "0xc95z5jzzjf5lw35bs4yn5rlwkrkmrh78yi5rranqpz5nn0wsa0";
|
||||
name = "mingw-w64-clang-x86_64-python-setuptools-74.0.0-1-any.pkg.tar.zst";
|
||||
})
|
||||
]
|
||||
|
||||
Loading…
Reference in New Issue
Block a user