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11 Commits

Author SHA1 Message Date
David Mak c862dbd861 [core] WIP - Implemented construct_* for NDArrays 2024-11-15 15:29:22 +08:00
David Mak 684aafe54c [core] Add itemsize and strides to NDArray struct 2024-11-15 15:28:37 +08:00
David Mak a770d9f415 [core] coregen/types: Implement StructFields for NDArray
Also rename some fields to better align with their naming in numpy.
2024-11-15 15:27:45 +08:00
David Mak 6f702ac250 [core] codegen/types: Implement NDArray in terms of i8*
Better aligns with the future implementation of ndstrides.
2024-11-15 15:19:23 +08:00
David Mak 64ec66d3dd [core] irrt: Break IRRT into several impl files
Each IRRT file is now mapped to one Rust file.
2024-11-15 15:19:23 +08:00
David Mak 3c336b0ea5 [core] irrt: Update some IRRT implementation
- Change CSlice to use `void*` for better pointer compatibility
- Remove __STDC_VERSION__ guard
- Only include impl *.hpp files in irrt.cpp
- Refactor typedef to using declaration
- Add missing ``// namespace`
2024-11-15 15:19:23 +08:00
David Mak 9fab65109a [core] codegen: Add dtype to NDArrayType
We won't have this once NDArray is refactored to strided impl.
2024-11-15 15:19:23 +08:00
David Mak 3a5e7a98b1 [core] codegen: Add Self::llvm_type to all type abstractions 2024-11-15 15:19:23 +08:00
lyken d3fb4204e7 core/irrt: fix exception.hpp C++ castings 2024-11-15 15:19:23 +08:00
lyken 8631fc8b58 core/toplevel/helper: add {extract,create}_ndims 2024-11-15 15:19:23 +08:00
David Mak 4b666f8706 [core] codegen/types: Implement StructField{,s}
Loosely based on FieldTraversal.
2024-11-15 15:19:06 +08:00
28 changed files with 2589 additions and 1233 deletions

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@ -461,8 +461,7 @@ fn format_rpc_arg<'ctx>(
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_ty = NDArrayType::new(generator, ctx.ctx, llvm_elem_ty);
let llvm_arg =
NDArrayValue::from_pointer_value(arg.into_pointer_value(), llvm_usize, None);
let llvm_arg = llvm_arg_ty.map_value(arg.into_pointer_value(), None);
let llvm_usize_sizeof = ctx
.builder
@ -499,7 +498,7 @@ fn format_rpc_arg<'ctx>(
call_memcpy_generic(
ctx,
pbuffer_dims_begin,
llvm_arg.dim_sizes().base_ptr(ctx, generator),
llvm_arg.shape().base_ptr(ctx, generator),
dims_buf_sz,
llvm_i1.const_zero(),
);
@ -613,7 +612,7 @@ fn format_rpc_ret<'ctx>(
// Set `ndarray.ndims`
ndarray.store_ndims(ctx, generator, llvm_usize.const_int(ndims, false));
// Allocate `ndarray.shape` [size_t; ndims]
ndarray.create_dim_sizes(ctx, llvm_usize, ndarray.load_ndims(ctx));
ndarray.create_shape(ctx, llvm_usize, ndarray.load_ndims(ctx));
/*
ndarray now:
@ -703,7 +702,7 @@ fn format_rpc_ret<'ctx>(
call_memcpy_generic(
ctx,
ndarray.dim_sizes().base_ptr(ctx, generator),
ndarray.shape().base_ptr(ctx, generator),
pbuffer_dims,
sizeof_dims,
llvm_i1.const_zero(),
@ -715,7 +714,7 @@ fn format_rpc_ret<'ctx>(
// `ndarray.shape` must be initialized beforehand in this implementation
// (for ndarray.create_data() to know how many elements to allocate)
let num_elements =
call_ndarray_calc_size(generator, ctx, &ndarray.dim_sizes(), (None, None));
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 {
@ -1363,13 +1362,19 @@ 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 val =
NDArrayValue::from_pointer_value(value.into_pointer_value(), llvm_usize, None);
let len = call_ndarray_calc_size(generator, ctx, &val.dim_sizes(), (None, None));
let val = NDArrayValue::from_pointer_value(
value.into_pointer_value(),
llvm_elem_ty,
None,
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();

View File

@ -1,6 +1,7 @@
#include "irrt/exception.hpp"
#include "irrt/int_types.hpp"
#include "irrt/list.hpp"
#include "irrt/math.hpp"
#include "irrt/ndarray.hpp"
#include "irrt/slice.hpp"
#include "irrt/ndarray/basic.hpp"
#include "irrt/ndarray/def.hpp"

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@ -4,6 +4,6 @@
template<typename SizeT>
struct CSlice {
uint8_t* base;
void* base;
SizeT len;
};

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@ -6,7 +6,7 @@
/**
* @brief The int type of ARTIQ exception IDs.
*/
typedef int32_t ExceptionId;
using ExceptionId = int32_t;
/*
* Set of exceptions C++ IRRT can use.
@ -55,11 +55,14 @@ void _raise_exception_helper(ExceptionId id,
int64_t param2) {
Exception<SizeT> e = {
.id = id,
.filename = {.base = reinterpret_cast<const uint8_t*>(filename), .len = __builtin_strlen(filename)},
.filename = {.base = reinterpret_cast<void*>(const_cast<char*>(filename)),
.len = static_cast<SizeT>(__builtin_strlen(filename))},
.line = line,
.column = 0,
.function = {.base = reinterpret_cast<const uint8_t*>(function), .len = __builtin_strlen(function)},
.msg = {.base = reinterpret_cast<const uint8_t*>(msg), .len = __builtin_strlen(msg)},
.function = {.base = reinterpret_cast<void*>(const_cast<char*>(function)),
.len = static_cast<SizeT>(__builtin_strlen(function))},
.msg = {.base = reinterpret_cast<void*>(const_cast<char*>(msg)),
.len = static_cast<SizeT>(__builtin_strlen(msg))},
};
e.params[0] = param0;
e.params[1] = param1;
@ -67,6 +70,7 @@ void _raise_exception_helper(ExceptionId id,
__nac3_raise(reinterpret_cast<void*>(&e));
__builtin_unreachable();
}
} // namespace
/**
* @brief Raise an exception with location details (location in the IRRT source files).
@ -79,4 +83,3 @@ void _raise_exception_helper(ExceptionId id,
*/
#define raise_exception(SizeT, id, msg, param0, param1, param2) \
_raise_exception_helper<SizeT>(id, __FILE__, __LINE__, __FUNCTION__, msg, param0, param1, param2)
} // namespace

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@ -1,20 +1,11 @@
#pragma once
#if __STDC_VERSION__ >= 202000
using int8_t = _BitInt(8);
using uint8_t = unsigned _BitInt(8);
using int32_t = _BitInt(32);
using uint32_t = unsigned _BitInt(32);
using int64_t = _BitInt(64);
using uint64_t = unsigned _BitInt(64);
#else
using int8_t = _ExtInt(8);
using uint8_t = unsigned _ExtInt(8);
using int32_t = _ExtInt(32);
using uint32_t = unsigned _ExtInt(32);
using int64_t = _ExtInt(64);
using uint64_t = unsigned _ExtInt(64);
#endif
// NDArray indices are always `uint32_t`.
using NDIndex = uint32_t;

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@ -13,12 +13,12 @@ extern "C" {
SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
SliceIndex dest_end,
SliceIndex dest_step,
uint8_t* dest_arr,
void* dest_arr,
SliceIndex dest_arr_len,
SliceIndex src_start,
SliceIndex src_end,
SliceIndex src_step,
uint8_t* src_arr,
void* src_arr,
SliceIndex src_arr_len,
const SliceIndex size) {
/* if dest_arr_len == 0, do nothing since we do not support extending list */
@ -29,11 +29,13 @@ SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
const SliceIndex src_len = (src_end >= src_start) ? (src_end - src_start + 1) : 0;
const SliceIndex dest_len = (dest_end >= dest_start) ? (dest_end - dest_start + 1) : 0;
if (src_len > 0) {
__builtin_memmove(dest_arr + dest_start * size, src_arr + src_start * size, src_len * size);
__builtin_memmove(static_cast<uint8_t*>(dest_arr) + dest_start * size,
static_cast<uint8_t*>(src_arr) + src_start * size, src_len * size);
}
if (dest_len > 0) {
/* dropping */
__builtin_memmove(dest_arr + (dest_start + src_len) * size, dest_arr + (dest_end + 1) * size,
__builtin_memmove(static_cast<uint8_t*>(dest_arr) + (dest_start + src_len) * size,
static_cast<uint8_t*>(dest_arr) + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size);
}
/* shrink size */
@ -44,7 +46,7 @@ SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
&& !(max(dest_start, dest_end) < min(src_start, src_end)
|| max(src_start, src_end) < min(dest_start, dest_end));
if (need_alloca) {
uint8_t* tmp = reinterpret_cast<uint8_t*>(__builtin_alloca(src_arr_len * size));
void* tmp = __builtin_alloca(src_arr_len * size);
__builtin_memcpy(tmp, src_arr, src_arr_len * size);
src_arr = tmp;
}
@ -53,20 +55,24 @@ SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
for (; (src_step > 0) ? (src_ind <= src_end) : (src_ind >= src_end); src_ind += src_step, dest_ind += dest_step) {
/* for constant optimization */
if (size == 1) {
__builtin_memcpy(dest_arr + dest_ind, src_arr + src_ind, 1);
__builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind, static_cast<uint8_t*>(src_arr) + src_ind, 1);
} else if (size == 4) {
__builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
__builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind * 4,
static_cast<uint8_t*>(src_arr) + src_ind * 4, 4);
} else if (size == 8) {
__builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
__builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind * 8,
static_cast<uint8_t*>(src_arr) + src_ind * 8, 8);
} else {
/* memcpy for var size, cannot overlap after previous alloca */
__builtin_memcpy(dest_arr + dest_ind * size, src_arr + src_ind * size, size);
__builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind * size,
static_cast<uint8_t*>(src_arr) + src_ind * size, size);
}
}
/* only dest_step == 1 can we shrink the dest list. */
/* size should be ensured prior to calling this function */
if (dest_step == 1 && dest_end >= dest_start) {
__builtin_memmove(dest_arr + dest_ind * size, dest_arr + (dest_end + 1) * size,
__builtin_memmove(static_cast<uint8_t*>(dest_arr) + dest_ind * size,
static_cast<uint8_t*>(dest_arr) + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size);
return dest_arr_len - (dest_end - dest_ind) - 1;
}

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@ -90,4 +90,4 @@ double __nac3_j0(double x) {
return j0(x);
}
}
} // namespace

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@ -2,6 +2,8 @@
#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) {
@ -141,4 +143,4 @@ void __nac3_ndarray_calc_broadcast_idx64(const uint64_t* src_dims,
NDIndex* out_idx) {
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
}
}
} // namespace

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@ -0,0 +1,342 @@
#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);
}
}

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@ -0,0 +1,51 @@
#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

View File

@ -25,4 +25,4 @@ SliceIndex __nac3_range_slice_len(const SliceIndex start, const SliceIndex end,
return 0;
}
}
}
} // namespace

View File

@ -21,7 +21,10 @@ use super::{
CodeGenContext, CodeGenerator,
};
use crate::{
toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys},
toplevel::{
helper::{arraylike_flatten_element_type, PrimDef},
numpy::unpack_ndarray_var_tys,
},
typecheck::typedef::{Type, TypeEnum},
};
@ -65,12 +68,18 @@ pub fn call_len<'ctx, G: CodeGenerator + ?Sized>(
ctx.builder.build_int_truncate_or_bit_cast(len, llvm_i32, "len").unwrap()
}
TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
let elem_ty = arraylike_flatten_element_type(&mut ctx.unifier, arg_ty);
let llvm_usize = generator.get_size_type(ctx.ctx);
let arg =
NDArrayValue::from_pointer_value(arg.into_pointer_value(), llvm_usize, None);
let arg = NDArrayValue::from_pointer_value(
arg.into_pointer_value(),
ctx.get_llvm_type(generator, elem_ty),
None,
llvm_usize,
None,
);
let ndims = arg.dim_sizes().size(ctx, generator);
let ndims = arg.shape().size(ctx, generator);
ctx.make_assert(
generator,
ctx.builder
@ -83,12 +92,7 @@ pub fn call_len<'ctx, G: CodeGenerator + ?Sized>(
);
let len = unsafe {
arg.dim_sizes().get_typed_unchecked(
ctx,
generator,
&llvm_usize.const_zero(),
None,
)
arg.shape().get_typed_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
};
ctx.builder.build_int_truncate_or_bit_cast(len, llvm_i32, "len").unwrap()
@ -143,13 +147,14 @@ pub fn call_int32<'ctx, G: CodeGenerator + ?Sized>(
if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
{
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let ndarray = ndarray_elementwise_unaryop_impl(
generator,
ctx,
ctx.primitives.int32,
None,
NDArrayValue::from_pointer_value(n, llvm_usize, None),
NDArrayValue::from_pointer_value(n, llvm_elem_ty, None, llvm_usize, None),
|generator, ctx, val| call_int32(generator, ctx, (elem_ty, val)),
)?;
@ -205,13 +210,14 @@ pub fn call_int64<'ctx, G: CodeGenerator + ?Sized>(
if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
{
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let ndarray = ndarray_elementwise_unaryop_impl(
generator,
ctx,
ctx.primitives.int64,
None,
NDArrayValue::from_pointer_value(n, llvm_usize, None),
NDArrayValue::from_pointer_value(n, llvm_elem_ty, None, llvm_usize, None),
|generator, ctx, val| call_int64(generator, ctx, (elem_ty, val)),
)?;
@ -283,13 +289,14 @@ pub fn call_uint32<'ctx, G: CodeGenerator + ?Sized>(
if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
{
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let ndarray = ndarray_elementwise_unaryop_impl(
generator,
ctx,
ctx.primitives.uint32,
None,
NDArrayValue::from_pointer_value(n, llvm_usize, None),
NDArrayValue::from_pointer_value(n, llvm_elem_ty, None, llvm_usize, None),
|generator, ctx, val| call_uint32(generator, ctx, (elem_ty, val)),
)?;
@ -350,13 +357,14 @@ pub fn call_uint64<'ctx, G: CodeGenerator + ?Sized>(
if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
{
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let ndarray = ndarray_elementwise_unaryop_impl(
generator,
ctx,
ctx.primitives.uint64,
None,
NDArrayValue::from_pointer_value(n, llvm_usize, None),
NDArrayValue::from_pointer_value(n, llvm_elem_ty, None, llvm_usize, None),
|generator, ctx, val| call_uint64(generator, ctx, (elem_ty, val)),
)?;
@ -416,13 +424,14 @@ pub fn call_float<'ctx, G: CodeGenerator + ?Sized>(
if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
{
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let ndarray = ndarray_elementwise_unaryop_impl(
generator,
ctx,
ctx.primitives.float,
None,
NDArrayValue::from_pointer_value(n, llvm_usize, None),
NDArrayValue::from_pointer_value(n, llvm_elem_ty, None, llvm_usize, None),
|generator, ctx, val| call_float(generator, ctx, (elem_ty, val)),
)?;
@ -462,13 +471,14 @@ pub fn call_round<'ctx, G: CodeGenerator + ?Sized>(
if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
{
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let ndarray = ndarray_elementwise_unaryop_impl(
generator,
ctx,
ret_elem_ty,
None,
NDArrayValue::from_pointer_value(n, llvm_usize, None),
NDArrayValue::from_pointer_value(n, llvm_elem_ty, None, llvm_usize, None),
|generator, ctx, val| call_round(generator, ctx, (elem_ty, val), ret_elem_ty),
)?;
@ -502,13 +512,14 @@ pub fn call_numpy_round<'ctx, G: CodeGenerator + ?Sized>(
if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
{
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let ndarray = ndarray_elementwise_unaryop_impl(
generator,
ctx,
ctx.primitives.float,
None,
NDArrayValue::from_pointer_value(n, llvm_usize, None),
NDArrayValue::from_pointer_value(n, llvm_elem_ty, None, llvm_usize, None),
|generator, ctx, val| call_numpy_round(generator, ctx, (elem_ty, val)),
)?;
@ -567,13 +578,14 @@ pub fn call_bool<'ctx, G: CodeGenerator + ?Sized>(
if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
{
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let ndarray = ndarray_elementwise_unaryop_impl(
generator,
ctx,
ctx.primitives.bool,
None,
NDArrayValue::from_pointer_value(n, llvm_usize, None),
NDArrayValue::from_pointer_value(n, llvm_elem_ty, None, llvm_usize, None),
|generator, ctx, val| {
let elem = call_bool(generator, ctx, (elem_ty, val))?;
@ -621,13 +633,14 @@ pub fn call_floor<'ctx, G: CodeGenerator + ?Sized>(
if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
{
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let ndarray = ndarray_elementwise_unaryop_impl(
generator,
ctx,
ret_elem_ty,
None,
NDArrayValue::from_pointer_value(n, llvm_usize, None),
NDArrayValue::from_pointer_value(n, llvm_elem_ty, None, llvm_usize, None),
|generator, ctx, val| call_floor(generator, ctx, (elem_ty, val), ret_elem_ty),
)?;
@ -671,13 +684,14 @@ pub fn call_ceil<'ctx, G: CodeGenerator + ?Sized>(
if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
{
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let ndarray = ndarray_elementwise_unaryop_impl(
generator,
ctx,
ret_elem_ty,
None,
NDArrayValue::from_pointer_value(n, llvm_usize, None),
NDArrayValue::from_pointer_value(n, llvm_elem_ty, None, llvm_usize, None),
|generator, ctx, val| call_ceil(generator, ctx, (elem_ty, val), ret_elem_ty),
)?;
@ -806,8 +820,8 @@ pub fn call_numpy_minimum<'ctx, G: CodeGenerator + ?Sized>(
ctx,
dtype,
None,
(x1, !is_ndarray1),
(x2, !is_ndarray2),
(x1_ty, x1, !is_ndarray1),
(x2_ty, x2, !is_ndarray2),
|generator, ctx, (lhs, rhs)| {
call_numpy_minimum(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
},
@ -906,10 +920,10 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
if a_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
{
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, a_ty);
let llvm_ndarray_ty = ctx.get_llvm_type(generator, elem_ty);
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let n = NDArrayValue::from_pointer_value(n, llvm_usize, None);
let n_sz = irrt::call_ndarray_calc_size(generator, ctx, &n.dim_sizes(), (None, None));
let n = NDArrayValue::from_pointer_value(n, llvm_elem_ty, None, llvm_usize, None);
let n_sz = irrt::call_ndarray_calc_size(generator, ctx, &n.shape(), (None, None));
if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
let n_sz_eqz = ctx
.builder
@ -926,7 +940,7 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
);
}
let accumulator_addr = generator.gen_var_alloc(ctx, llvm_ndarray_ty, None)?;
let accumulator_addr = generator.gen_var_alloc(ctx, llvm_elem_ty, None)?;
let res_idx = generator.gen_var_alloc(ctx, llvm_int64.into(), None)?;
unsafe {
@ -1068,8 +1082,8 @@ pub fn call_numpy_maximum<'ctx, G: CodeGenerator + ?Sized>(
ctx,
dtype,
None,
(x1, !is_ndarray1),
(x2, !is_ndarray2),
(x1_ty, x1, !is_ndarray1),
(x2_ty, x2, !is_ndarray2),
|generator, ctx, (lhs, rhs)| {
call_numpy_maximum(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
},
@ -1114,6 +1128,7 @@ where
{
let llvm_usize = generator.get_size_type(ctx.ctx);
let (arg_elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, arg_ty);
let llvm_arg_elem_ty = ctx.get_llvm_type(generator, arg_elem_ty);
let ret_elem_ty = get_ret_elem_type(ctx, arg_elem_ty);
let ndarray = ndarray_elementwise_unaryop_impl(
@ -1121,7 +1136,7 @@ where
ctx,
ret_elem_ty,
None,
NDArrayValue::from_pointer_value(x, llvm_usize, None),
NDArrayValue::from_pointer_value(x, llvm_arg_elem_ty, None, llvm_usize, None),
|generator, ctx, elem_val| {
helper_call_numpy_unary_elementwise(
generator,
@ -1508,8 +1523,8 @@ pub fn call_numpy_arctan2<'ctx, G: CodeGenerator + ?Sized>(
ctx,
dtype,
None,
(x1, !is_ndarray1),
(x2, !is_ndarray2),
(x1_ty, x1, !is_ndarray1),
(x2_ty, x2, !is_ndarray2),
|generator, ctx, (lhs, rhs)| {
call_numpy_arctan2(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
},
@ -1575,8 +1590,8 @@ pub fn call_numpy_copysign<'ctx, G: CodeGenerator + ?Sized>(
ctx,
dtype,
None,
(x1, !is_ndarray1),
(x2, !is_ndarray2),
(x1_ty, x1, !is_ndarray1),
(x2_ty, x2, !is_ndarray2),
|generator, ctx, (lhs, rhs)| {
call_numpy_copysign(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
},
@ -1642,8 +1657,8 @@ pub fn call_numpy_fmax<'ctx, G: CodeGenerator + ?Sized>(
ctx,
dtype,
None,
(x1, !is_ndarray1),
(x2, !is_ndarray2),
(x1_ty, x1, !is_ndarray1),
(x2_ty, x2, !is_ndarray2),
|generator, ctx, (lhs, rhs)| {
call_numpy_fmax(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
},
@ -1709,8 +1724,8 @@ pub fn call_numpy_fmin<'ctx, G: CodeGenerator + ?Sized>(
ctx,
dtype,
None,
(x1, !is_ndarray1),
(x2, !is_ndarray2),
(x1_ty, x1, !is_ndarray1),
(x2_ty, x2, !is_ndarray2),
|generator, ctx, (lhs, rhs)| {
call_numpy_fmin(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
},
@ -1765,8 +1780,8 @@ pub fn call_numpy_ldexp<'ctx, G: CodeGenerator + ?Sized>(
ctx,
dtype,
None,
(x1, !is_ndarray1),
(x2, !is_ndarray2),
(x1_ty, x1, !is_ndarray1),
(x2_ty, x2, !is_ndarray2),
|generator, ctx, (lhs, rhs)| {
call_numpy_ldexp(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
},
@ -1832,8 +1847,8 @@ pub fn call_numpy_hypot<'ctx, G: CodeGenerator + ?Sized>(
ctx,
dtype,
None,
(x1, !is_ndarray1),
(x2, !is_ndarray2),
(x1_ty, x1, !is_ndarray1),
(x2_ty, x2, !is_ndarray2),
|generator, ctx, (lhs, rhs)| {
call_numpy_hypot(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
},
@ -1899,8 +1914,8 @@ pub fn call_numpy_nextafter<'ctx, G: CodeGenerator + ?Sized>(
ctx,
dtype,
None,
(x1, !is_ndarray1),
(x2, !is_ndarray2),
(x1_ty, x1, !is_ndarray1),
(x2_ty, x2, !is_ndarray2),
|generator, ctx, (lhs, rhs)| {
call_numpy_nextafter(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
},
@ -1960,14 +1975,14 @@ pub fn call_np_linalg_cholesky<'ctx, G: CodeGenerator + ?Sized>(
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
let n1 = NDArrayValue::from_pointer_value(n1, llvm_usize, None);
let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, None, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let dim1 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
.into_int_value()
};
@ -2002,14 +2017,14 @@ pub fn call_np_linalg_qr<'ctx, G: CodeGenerator + ?Sized>(
unimplemented!("{FN_NAME} operates on float type NdArrays only");
};
let n1 = NDArrayValue::from_pointer_value(n1, llvm_usize, None);
let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, None, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let dim1 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
.into_int_value()
};
@ -2052,15 +2067,15 @@ pub fn call_np_linalg_svd<'ctx, G: CodeGenerator + ?Sized>(
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
let n1 = NDArrayValue::from_pointer_value(n1, llvm_usize, None);
let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, None, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let dim1 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
.into_int_value()
};
@ -2107,14 +2122,14 @@ pub fn call_np_linalg_inv<'ctx, G: CodeGenerator + ?Sized>(
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
let n1 = NDArrayValue::from_pointer_value(n1, llvm_usize, None);
let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, None, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let dim1 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
.into_int_value()
};
@ -2149,15 +2164,15 @@ pub fn call_np_linalg_pinv<'ctx, G: CodeGenerator + ?Sized>(
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
let n1 = NDArrayValue::from_pointer_value(n1, llvm_usize, None);
let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, None, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let dim1 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
.into_int_value()
};
@ -2192,15 +2207,15 @@ pub fn call_sp_linalg_lu<'ctx, G: CodeGenerator + ?Sized>(
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
let n1 = NDArrayValue::from_pointer_value(n1, llvm_usize, None);
let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, None, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let dim1 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
.into_int_value()
};
@ -2245,7 +2260,7 @@ pub fn call_np_linalg_matrix_power<'ctx, G: CodeGenerator + ?Sized>(
unsupported_type(ctx, FN_NAME, &[x1_ty, x2_ty]);
};
let n1 = NDArrayValue::from_pointer_value(n1, llvm_usize, None);
let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, None, llvm_usize, None);
// Changing second parameter to a `NDArray` for uniformity in function call
let n2_array = numpy::create_ndarray_const_shape(
generator,
@ -2265,12 +2280,12 @@ pub fn call_np_linalg_matrix_power<'ctx, G: CodeGenerator + ?Sized>(
let n2_array = n2_array.as_base_value().as_basic_value_enum();
let outdim0 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let outdim1 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
.into_int_value()
};
@ -2340,10 +2355,10 @@ pub fn call_sp_linalg_schur<'ctx, G: CodeGenerator + ?Sized>(
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
let n1 = NDArrayValue::from_pointer_value(n1, llvm_usize, None);
let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, None, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
@ -2383,10 +2398,10 @@ pub fn call_sp_linalg_hessenberg<'ctx, G: CodeGenerator + ?Sized>(
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
let n1 = NDArrayValue::from_pointer_value(n1, llvm_usize, None);
let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, None, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
n1.shape()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};

View File

@ -1564,10 +1564,23 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
assert!(ctx.unifier.unioned(ndarray_dtype1, ndarray_dtype2));
let left_val =
NDArrayValue::from_pointer_value(left_val.into_pointer_value(), llvm_usize, None);
let right_val =
NDArrayValue::from_pointer_value(right_val.into_pointer_value(), llvm_usize, 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,
None,
llvm_usize,
None,
);
let right_val = NDArrayValue::from_pointer_value(
right_val.into_pointer_value(),
llvm_ndarray_dtype2,
None,
llvm_usize,
None,
);
let res = if op.base == Operator::MatMult {
// MatMult is the only binop which is not an elementwise op
@ -1591,8 +1604,8 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
BinopVariant::Normal => None,
BinopVariant::AugAssign => Some(left_val),
},
(left_val.as_base_value().into(), false),
(right_val.as_base_value().into(), false),
(ty1, left_val.as_base_value().into(), false),
(ty2, right_val.as_base_value().into(), false),
|generator, ctx, (lhs, rhs)| {
gen_binop_expr_with_values(
generator,
@ -1616,8 +1629,11 @@ 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 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,
None,
llvm_usize,
None,
);
@ -1629,8 +1645,8 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
BinopVariant::Normal => None,
BinopVariant::AugAssign => Some(ndarray_val),
},
(left_val, !is_ndarray1),
(right_val, !is_ndarray2),
(ty1, left_val, !is_ndarray1),
(ty2, right_val, !is_ndarray2),
|generator, ctx, (lhs, rhs)| {
gen_binop_expr_with_values(
generator,
@ -1810,8 +1826,15 @@ pub fn gen_unaryop_expr_with_values<'ctx, G: CodeGenerator>(
} else if ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) {
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 = NDArrayValue::from_pointer_value(val.into_pointer_value(), llvm_usize, None);
let val = NDArrayValue::from_pointer_value(
val.into_pointer_value(),
llvm_ndarray_dtype,
None,
llvm_usize,
None,
);
// ndarray uses `~` rather than `not` to perform elementwise inversion, convert it before
// passing it to the elementwise codegen function
@ -1902,15 +1925,22 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
assert!(ctx.unifier.unioned(ndarray_dtype1, ndarray_dtype2));
let left_val =
NDArrayValue::from_pointer_value(lhs.into_pointer_value(), llvm_usize, 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,
None,
llvm_usize,
None,
);
let res = numpy::ndarray_elementwise_binop_impl(
generator,
ctx,
ctx.primitives.bool,
None,
(left_val.as_base_value().into(), false),
(rhs, false),
(left_ty, left_val.as_base_value().into(), false),
(right_ty, rhs, false),
|generator, ctx, (lhs, rhs)| {
let val = gen_cmpop_expr_with_values(
generator,
@ -1941,8 +1971,8 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
ctx,
ctx.primitives.bool,
None,
(lhs, !is_ndarray1),
(rhs, !is_ndarray2),
(left_ty, lhs, !is_ndarray1),
(right_ty, rhs, !is_ndarray2),
|generator, ctx, (lhs, rhs)| {
let val = gen_cmpop_expr_with_values(
generator,
@ -2606,7 +2636,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
let llvm_i32 = ctx.ctx.i32_type();
let len = unsafe {
v.dim_sizes().get_typed_unchecked(
v.shape().get_typed_unchecked(
ctx,
generator,
&llvm_usize.const_int(dim, true),
@ -2647,7 +2677,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
ExprKind::Slice { lower, upper, step } => {
let dim_sz = unsafe {
v.dim_sizes().get_typed_unchecked(
v.shape().get_typed_unchecked(
ctx,
generator,
&llvm_usize.const_int(dim, false),
@ -2771,8 +2801,13 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
// elements over
let subscripted_ndarray =
generator.gen_var_alloc(ctx, llvm_ndarray_t.into(), None)?;
let ndarray =
NDArrayValue::from_pointer_value(subscripted_ndarray, llvm_usize, None);
let ndarray = NDArrayValue::from_pointer_value(
subscripted_ndarray,
llvm_ndarray_data_t,
None,
llvm_usize,
None,
);
let num_dims = v.load_ndims(ctx);
ndarray.store_ndims(
@ -2784,7 +2819,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
);
let ndarray_num_dims = ndarray.load_ndims(ctx);
ndarray.create_dim_sizes(ctx, llvm_usize, ndarray_num_dims);
ndarray.create_shape(ctx, llvm_usize, ndarray_num_dims);
let ndarray_num_dims = ctx
.builder
@ -2795,7 +2830,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
)
.unwrap();
let v_dims_src_ptr = unsafe {
v.dim_sizes().ptr_offset_unchecked(
v.shape().ptr_offset_unchecked(
ctx,
generator,
&llvm_usize.const_int(1, false),
@ -2804,7 +2839,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
};
call_memcpy_generic(
ctx,
ndarray.dim_sizes().base_ptr(ctx, generator),
ndarray.shape().base_ptr(ctx, generator),
v_dims_src_ptr,
ctx.builder
.build_int_mul(ndarray_num_dims, llvm_usize.size_of(), "")
@ -2816,7 +2851,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
let ndarray_num_elems = call_ndarray_calc_size(
generator,
ctx,
&ndarray.dim_sizes().as_slice_value(ctx, generator),
&ndarray.shape().as_slice_value(ctx, generator),
(None, None),
);
let ndarray_num_elems = ctx
@ -3505,6 +3540,7 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
}
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())?
@ -3512,7 +3548,7 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
} else {
return Ok(None);
};
let v = NDArrayValue::from_pointer_value(v, usize, None);
let v = NDArrayValue::from_pointer_value(v, llvm_ty, None, usize, None);
return gen_ndarray_subscript_expr(generator, ctx, *ty, *ndims, v, slice);
}

View File

@ -0,0 +1,162 @@
use inkwell::{
types::BasicTypeEnum,
values::{BasicValueEnum, CallSiteValue, IntValue},
AddressSpace, IntPredicate,
};
use itertools::Either;
use super::calculate_len_for_slice_range;
use crate::codegen::{
macros::codegen_unreachable,
values::{ArrayLikeValue, ListValue},
CodeGenContext, CodeGenerator,
};
/// This function handles 'end' **inclusively**.
/// Order of tuples `assign_idx` and `value_idx` is ('start', 'end', 'step').
/// Negative index should be handled before entering this function
pub fn list_slice_assignment<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
ty: BasicTypeEnum<'ctx>,
dest_arr: ListValue<'ctx>,
dest_idx: (IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>),
src_arr: ListValue<'ctx>,
src_idx: (IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>),
) {
let size_ty = generator.get_size_type(ctx.ctx);
let int8_ptr = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
let int32 = ctx.ctx.i32_type();
let (fun_symbol, elem_ptr_type) = ("__nac3_list_slice_assign_var_size", int8_ptr);
let slice_assign_fun = {
let ty_vec = vec![
int32.into(), // dest start idx
int32.into(), // dest end idx
int32.into(), // dest step
elem_ptr_type.into(), // dest arr ptr
int32.into(), // dest arr len
int32.into(), // src start idx
int32.into(), // src end idx
int32.into(), // src step
elem_ptr_type.into(), // src arr ptr
int32.into(), // src arr len
int32.into(), // size
];
ctx.module.get_function(fun_symbol).unwrap_or_else(|| {
let fn_t = int32.fn_type(ty_vec.as_slice(), false);
ctx.module.add_function(fun_symbol, fn_t, None)
})
};
let zero = int32.const_zero();
let one = int32.const_int(1, false);
let dest_arr_ptr = dest_arr.data().base_ptr(ctx, generator);
let dest_arr_ptr =
ctx.builder.build_pointer_cast(dest_arr_ptr, elem_ptr_type, "dest_arr_ptr_cast").unwrap();
let dest_len = dest_arr.load_size(ctx, Some("dest.len"));
let dest_len = ctx.builder.build_int_truncate_or_bit_cast(dest_len, int32, "srclen32").unwrap();
let src_arr_ptr = src_arr.data().base_ptr(ctx, generator);
let src_arr_ptr =
ctx.builder.build_pointer_cast(src_arr_ptr, elem_ptr_type, "src_arr_ptr_cast").unwrap();
let src_len = src_arr.load_size(ctx, Some("src.len"));
let src_len = ctx.builder.build_int_truncate_or_bit_cast(src_len, int32, "srclen32").unwrap();
// index in bound and positive should be done
// assert if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest), and
// throw exception if not satisfied
let src_end = ctx
.builder
.build_select(
ctx.builder.build_int_compare(IntPredicate::SLT, src_idx.2, zero, "is_neg").unwrap(),
ctx.builder.build_int_sub(src_idx.1, one, "e_min_one").unwrap(),
ctx.builder.build_int_add(src_idx.1, one, "e_add_one").unwrap(),
"final_e",
)
.map(BasicValueEnum::into_int_value)
.unwrap();
let dest_end = ctx
.builder
.build_select(
ctx.builder.build_int_compare(IntPredicate::SLT, dest_idx.2, zero, "is_neg").unwrap(),
ctx.builder.build_int_sub(dest_idx.1, one, "e_min_one").unwrap(),
ctx.builder.build_int_add(dest_idx.1, one, "e_add_one").unwrap(),
"final_e",
)
.map(BasicValueEnum::into_int_value)
.unwrap();
let src_slice_len =
calculate_len_for_slice_range(generator, ctx, src_idx.0, src_end, src_idx.2);
let dest_slice_len =
calculate_len_for_slice_range(generator, ctx, dest_idx.0, dest_end, dest_idx.2);
let src_eq_dest = ctx
.builder
.build_int_compare(IntPredicate::EQ, src_slice_len, dest_slice_len, "slice_src_eq_dest")
.unwrap();
let src_slt_dest = ctx
.builder
.build_int_compare(IntPredicate::SLT, src_slice_len, dest_slice_len, "slice_src_slt_dest")
.unwrap();
let dest_step_eq_one = ctx
.builder
.build_int_compare(
IntPredicate::EQ,
dest_idx.2,
dest_idx.2.get_type().const_int(1, false),
"slice_dest_step_eq_one",
)
.unwrap();
let cond_1 = ctx.builder.build_and(dest_step_eq_one, src_slt_dest, "slice_cond_1").unwrap();
let cond = ctx.builder.build_or(src_eq_dest, cond_1, "slice_cond").unwrap();
ctx.make_assert(
generator,
cond,
"0:ValueError",
"attempt to assign sequence of size {0} to slice of size {1} with step size {2}",
[Some(src_slice_len), Some(dest_slice_len), Some(dest_idx.2)],
ctx.current_loc,
);
let new_len = {
let args = vec![
dest_idx.0.into(), // dest start idx
dest_idx.1.into(), // dest end idx
dest_idx.2.into(), // dest step
dest_arr_ptr.into(), // dest arr ptr
dest_len.into(), // dest arr len
src_idx.0.into(), // src start idx
src_idx.1.into(), // src end idx
src_idx.2.into(), // src step
src_arr_ptr.into(), // src arr ptr
src_len.into(), // src arr len
{
let s = match ty {
BasicTypeEnum::FloatType(t) => t.size_of(),
BasicTypeEnum::IntType(t) => t.size_of(),
BasicTypeEnum::PointerType(t) => t.size_of(),
BasicTypeEnum::StructType(t) => t.size_of().unwrap(),
_ => codegen_unreachable!(ctx),
};
ctx.builder.build_int_truncate_or_bit_cast(s, int32, "size").unwrap()
}
.into(),
];
ctx.builder
.build_call(slice_assign_fun, args.as_slice(), "slice_assign")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap()
};
// update length
let need_update =
ctx.builder.build_int_compare(IntPredicate::NE, new_len, dest_len, "need_update").unwrap();
let current = ctx.builder.get_insert_block().unwrap().get_parent().unwrap();
let update_bb = ctx.ctx.append_basic_block(current, "update");
let cont_bb = ctx.ctx.append_basic_block(current, "cont");
ctx.builder.build_conditional_branch(need_update, update_bb, cont_bb).unwrap();
ctx.builder.position_at_end(update_bb);
let new_len = ctx.builder.build_int_z_extend_or_bit_cast(new_len, size_ty, "new_len").unwrap();
dest_arr.store_size(ctx, generator, new_len);
ctx.builder.build_unconditional_branch(cont_bb).unwrap();
ctx.builder.position_at_end(cont_bb);
}

View File

@ -0,0 +1,152 @@
use inkwell::{
values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue},
IntPredicate,
};
use itertools::Either;
use crate::codegen::{
macros::codegen_unreachable,
{CodeGenContext, CodeGenerator},
};
// repeated squaring method adapted from GNU Scientific Library:
// https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
pub fn integer_power<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
base: IntValue<'ctx>,
exp: IntValue<'ctx>,
signed: bool,
) -> IntValue<'ctx> {
let symbol = match (base.get_type().get_bit_width(), exp.get_type().get_bit_width(), signed) {
(32, 32, true) => "__nac3_int_exp_int32_t",
(64, 64, true) => "__nac3_int_exp_int64_t",
(32, 32, false) => "__nac3_int_exp_uint32_t",
(64, 64, false) => "__nac3_int_exp_uint64_t",
_ => codegen_unreachable!(ctx),
};
let base_type = base.get_type();
let pow_fun = ctx.module.get_function(symbol).unwrap_or_else(|| {
let fn_type = base_type.fn_type(&[base_type.into(), base_type.into()], false);
ctx.module.add_function(symbol, fn_type, None)
});
// throw exception when exp < 0
let ge_zero = ctx
.builder
.build_int_compare(
IntPredicate::SGE,
exp,
exp.get_type().const_zero(),
"assert_int_pow_ge_0",
)
.unwrap();
ctx.make_assert(
generator,
ge_zero,
"0:ValueError",
"integer power must be positive or zero",
[None, None, None],
ctx.current_loc,
);
ctx.builder
.build_call(pow_fun, &[base.into(), exp.into()], "call_int_pow")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap()
}
/// Generates a call to `isinf` in IR. Returns an `i1` representing the result.
pub fn call_isinf<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &CodeGenContext<'ctx, '_>,
v: FloatValue<'ctx>,
) -> IntValue<'ctx> {
let intrinsic_fn = ctx.module.get_function("__nac3_isinf").unwrap_or_else(|| {
let fn_type = ctx.ctx.i32_type().fn_type(&[ctx.ctx.f64_type().into()], false);
ctx.module.add_function("__nac3_isinf", fn_type, None)
});
let ret = ctx
.builder
.build_call(intrinsic_fn, &[v.into()], "isinf")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap();
generator.bool_to_i1(ctx, ret)
}
/// Generates a call to `isnan` in IR. Returns an `i1` representing the result.
pub fn call_isnan<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &CodeGenContext<'ctx, '_>,
v: FloatValue<'ctx>,
) -> IntValue<'ctx> {
let intrinsic_fn = ctx.module.get_function("__nac3_isnan").unwrap_or_else(|| {
let fn_type = ctx.ctx.i32_type().fn_type(&[ctx.ctx.f64_type().into()], false);
ctx.module.add_function("__nac3_isnan", fn_type, None)
});
let ret = ctx
.builder
.build_call(intrinsic_fn, &[v.into()], "isnan")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap();
generator.bool_to_i1(ctx, ret)
}
/// Generates a call to `gamma` in IR. Returns an `f64` representing the result.
pub fn call_gamma<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
let llvm_f64 = ctx.ctx.f64_type();
let intrinsic_fn = ctx.module.get_function("__nac3_gamma").unwrap_or_else(|| {
let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
ctx.module.add_function("__nac3_gamma", fn_type, None)
});
ctx.builder
.build_call(intrinsic_fn, &[v.into()], "gamma")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_float_value))
.map(Either::unwrap_left)
.unwrap()
}
/// Generates a call to `gammaln` in IR. Returns an `f64` representing the result.
pub fn call_gammaln<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
let llvm_f64 = ctx.ctx.f64_type();
let intrinsic_fn = ctx.module.get_function("__nac3_gammaln").unwrap_or_else(|| {
let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
ctx.module.add_function("__nac3_gammaln", fn_type, None)
});
ctx.builder
.build_call(intrinsic_fn, &[v.into()], "gammaln")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_float_value))
.map(Either::unwrap_left)
.unwrap()
}
/// Generates a call to `j0` in IR. Returns an `f64` representing the result.
pub fn call_j0<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
let llvm_f64 = ctx.ctx.f64_type();
let intrinsic_fn = ctx.module.get_function("__nac3_j0").unwrap_or_else(|| {
let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
ctx.module.add_function("__nac3_j0", fn_type, None)
});
ctx.builder
.build_call(intrinsic_fn, &[v.into()], "j0")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_float_value))
.map(Either::unwrap_left)
.unwrap()
}

View File

@ -3,25 +3,23 @@ use inkwell::{
context::Context,
memory_buffer::MemoryBuffer,
module::Module,
types::{BasicTypeEnum, IntType},
values::{BasicValue, BasicValueEnum, CallSiteValue, FloatValue, IntValue},
AddressSpace, IntPredicate,
values::{BasicValue, BasicValueEnum, IntValue},
IntPredicate,
};
use itertools::Either;
use nac3parser::ast::Expr;
use super::{
llvm_intrinsics,
macros::codegen_unreachable,
stmt::gen_for_callback_incrementing,
values::{
ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue,
TypedArrayLikeAccessor, TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
},
CodeGenContext, CodeGenerator,
};
use super::{CodeGenContext, CodeGenerator};
use crate::{symbol_resolver::SymbolResolver, typecheck::typedef::Type};
pub use list::*;
pub use math::*;
pub use ndarray::*;
pub use slice::*;
mod list;
mod math;
mod ndarray;
mod slice;
#[must_use]
pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver) -> Module<'ctx> {
@ -62,88 +60,6 @@ pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver)
irrt_mod
}
// repeated squaring method adapted from GNU Scientific Library:
// https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
pub fn integer_power<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
base: IntValue<'ctx>,
exp: IntValue<'ctx>,
signed: bool,
) -> IntValue<'ctx> {
let symbol = match (base.get_type().get_bit_width(), exp.get_type().get_bit_width(), signed) {
(32, 32, true) => "__nac3_int_exp_int32_t",
(64, 64, true) => "__nac3_int_exp_int64_t",
(32, 32, false) => "__nac3_int_exp_uint32_t",
(64, 64, false) => "__nac3_int_exp_uint64_t",
_ => codegen_unreachable!(ctx),
};
let base_type = base.get_type();
let pow_fun = ctx.module.get_function(symbol).unwrap_or_else(|| {
let fn_type = base_type.fn_type(&[base_type.into(), base_type.into()], false);
ctx.module.add_function(symbol, fn_type, None)
});
// throw exception when exp < 0
let ge_zero = ctx
.builder
.build_int_compare(
IntPredicate::SGE,
exp,
exp.get_type().const_zero(),
"assert_int_pow_ge_0",
)
.unwrap();
ctx.make_assert(
generator,
ge_zero,
"0:ValueError",
"integer power must be positive or zero",
[None, None, None],
ctx.current_loc,
);
ctx.builder
.build_call(pow_fun, &[base.into(), exp.into()], "call_int_pow")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap()
}
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()
}
/// 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.
@ -309,644 +225,3 @@ pub fn handle_slice_indices<'ctx, G: CodeGenerator>(
}
}))
}
/// this function allows index out of range, since python
/// allows index out of range in slice (`a = [1,2,3]; a[1:10] == [2,3]`).
pub fn handle_slice_index_bound<'ctx, G: CodeGenerator>(
i: &Expr<Option<Type>>,
ctx: &mut CodeGenContext<'ctx, '_>,
generator: &mut G,
length: IntValue<'ctx>,
) -> Result<Option<IntValue<'ctx>>, String> {
const SYMBOL: &str = "__nac3_slice_index_bound";
let func = ctx.module.get_function(SYMBOL).unwrap_or_else(|| {
let i32_t = ctx.ctx.i32_type();
let fn_t = i32_t.fn_type(&[i32_t.into(), i32_t.into()], false);
ctx.module.add_function(SYMBOL, fn_t, None)
});
let i = if let Some(v) = generator.gen_expr(ctx, i)? {
v.to_basic_value_enum(ctx, generator, i.custom.unwrap())?
} else {
return Ok(None);
};
Ok(Some(
ctx.builder
.build_call(func, &[i.into(), length.into()], "bounded_ind")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap(),
))
}
/// This function handles 'end' **inclusively**.
/// Order of tuples `assign_idx` and `value_idx` is ('start', 'end', 'step').
/// Negative index should be handled before entering this function
pub fn list_slice_assignment<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
ty: BasicTypeEnum<'ctx>,
dest_arr: ListValue<'ctx>,
dest_idx: (IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>),
src_arr: ListValue<'ctx>,
src_idx: (IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>),
) {
let size_ty = generator.get_size_type(ctx.ctx);
let int8_ptr = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
let int32 = ctx.ctx.i32_type();
let (fun_symbol, elem_ptr_type) = ("__nac3_list_slice_assign_var_size", int8_ptr);
let slice_assign_fun = {
let ty_vec = vec![
int32.into(), // dest start idx
int32.into(), // dest end idx
int32.into(), // dest step
elem_ptr_type.into(), // dest arr ptr
int32.into(), // dest arr len
int32.into(), // src start idx
int32.into(), // src end idx
int32.into(), // src step
elem_ptr_type.into(), // src arr ptr
int32.into(), // src arr len
int32.into(), // size
];
ctx.module.get_function(fun_symbol).unwrap_or_else(|| {
let fn_t = int32.fn_type(ty_vec.as_slice(), false);
ctx.module.add_function(fun_symbol, fn_t, None)
})
};
let zero = int32.const_zero();
let one = int32.const_int(1, false);
let dest_arr_ptr = dest_arr.data().base_ptr(ctx, generator);
let dest_arr_ptr =
ctx.builder.build_pointer_cast(dest_arr_ptr, elem_ptr_type, "dest_arr_ptr_cast").unwrap();
let dest_len = dest_arr.load_size(ctx, Some("dest.len"));
let dest_len = ctx.builder.build_int_truncate_or_bit_cast(dest_len, int32, "srclen32").unwrap();
let src_arr_ptr = src_arr.data().base_ptr(ctx, generator);
let src_arr_ptr =
ctx.builder.build_pointer_cast(src_arr_ptr, elem_ptr_type, "src_arr_ptr_cast").unwrap();
let src_len = src_arr.load_size(ctx, Some("src.len"));
let src_len = ctx.builder.build_int_truncate_or_bit_cast(src_len, int32, "srclen32").unwrap();
// index in bound and positive should be done
// assert if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest), and
// throw exception if not satisfied
let src_end = ctx
.builder
.build_select(
ctx.builder.build_int_compare(IntPredicate::SLT, src_idx.2, zero, "is_neg").unwrap(),
ctx.builder.build_int_sub(src_idx.1, one, "e_min_one").unwrap(),
ctx.builder.build_int_add(src_idx.1, one, "e_add_one").unwrap(),
"final_e",
)
.map(BasicValueEnum::into_int_value)
.unwrap();
let dest_end = ctx
.builder
.build_select(
ctx.builder.build_int_compare(IntPredicate::SLT, dest_idx.2, zero, "is_neg").unwrap(),
ctx.builder.build_int_sub(dest_idx.1, one, "e_min_one").unwrap(),
ctx.builder.build_int_add(dest_idx.1, one, "e_add_one").unwrap(),
"final_e",
)
.map(BasicValueEnum::into_int_value)
.unwrap();
let src_slice_len =
calculate_len_for_slice_range(generator, ctx, src_idx.0, src_end, src_idx.2);
let dest_slice_len =
calculate_len_for_slice_range(generator, ctx, dest_idx.0, dest_end, dest_idx.2);
let src_eq_dest = ctx
.builder
.build_int_compare(IntPredicate::EQ, src_slice_len, dest_slice_len, "slice_src_eq_dest")
.unwrap();
let src_slt_dest = ctx
.builder
.build_int_compare(IntPredicate::SLT, src_slice_len, dest_slice_len, "slice_src_slt_dest")
.unwrap();
let dest_step_eq_one = ctx
.builder
.build_int_compare(
IntPredicate::EQ,
dest_idx.2,
dest_idx.2.get_type().const_int(1, false),
"slice_dest_step_eq_one",
)
.unwrap();
let cond_1 = ctx.builder.build_and(dest_step_eq_one, src_slt_dest, "slice_cond_1").unwrap();
let cond = ctx.builder.build_or(src_eq_dest, cond_1, "slice_cond").unwrap();
ctx.make_assert(
generator,
cond,
"0:ValueError",
"attempt to assign sequence of size {0} to slice of size {1} with step size {2}",
[Some(src_slice_len), Some(dest_slice_len), Some(dest_idx.2)],
ctx.current_loc,
);
let new_len = {
let args = vec![
dest_idx.0.into(), // dest start idx
dest_idx.1.into(), // dest end idx
dest_idx.2.into(), // dest step
dest_arr_ptr.into(), // dest arr ptr
dest_len.into(), // dest arr len
src_idx.0.into(), // src start idx
src_idx.1.into(), // src end idx
src_idx.2.into(), // src step
src_arr_ptr.into(), // src arr ptr
src_len.into(), // src arr len
{
let s = match ty {
BasicTypeEnum::FloatType(t) => t.size_of(),
BasicTypeEnum::IntType(t) => t.size_of(),
BasicTypeEnum::PointerType(t) => t.size_of(),
BasicTypeEnum::StructType(t) => t.size_of().unwrap(),
_ => codegen_unreachable!(ctx),
};
ctx.builder.build_int_truncate_or_bit_cast(s, int32, "size").unwrap()
}
.into(),
];
ctx.builder
.build_call(slice_assign_fun, args.as_slice(), "slice_assign")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap()
};
// update length
let need_update =
ctx.builder.build_int_compare(IntPredicate::NE, new_len, dest_len, "need_update").unwrap();
let current = ctx.builder.get_insert_block().unwrap().get_parent().unwrap();
let update_bb = ctx.ctx.append_basic_block(current, "update");
let cont_bb = ctx.ctx.append_basic_block(current, "cont");
ctx.builder.build_conditional_branch(need_update, update_bb, cont_bb).unwrap();
ctx.builder.position_at_end(update_bb);
let new_len = ctx.builder.build_int_z_extend_or_bit_cast(new_len, size_ty, "new_len").unwrap();
dest_arr.store_size(ctx, generator, new_len);
ctx.builder.build_unconditional_branch(cont_bb).unwrap();
ctx.builder.position_at_end(cont_bb);
}
/// Generates a call to `isinf` in IR. Returns an `i1` representing the result.
pub fn call_isinf<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &CodeGenContext<'ctx, '_>,
v: FloatValue<'ctx>,
) -> IntValue<'ctx> {
let intrinsic_fn = ctx.module.get_function("__nac3_isinf").unwrap_or_else(|| {
let fn_type = ctx.ctx.i32_type().fn_type(&[ctx.ctx.f64_type().into()], false);
ctx.module.add_function("__nac3_isinf", fn_type, None)
});
let ret = ctx
.builder
.build_call(intrinsic_fn, &[v.into()], "isinf")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap();
generator.bool_to_i1(ctx, ret)
}
/// Generates a call to `isnan` in IR. Returns an `i1` representing the result.
pub fn call_isnan<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &CodeGenContext<'ctx, '_>,
v: FloatValue<'ctx>,
) -> IntValue<'ctx> {
let intrinsic_fn = ctx.module.get_function("__nac3_isnan").unwrap_or_else(|| {
let fn_type = ctx.ctx.i32_type().fn_type(&[ctx.ctx.f64_type().into()], false);
ctx.module.add_function("__nac3_isnan", fn_type, None)
});
let ret = ctx
.builder
.build_call(intrinsic_fn, &[v.into()], "isnan")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap();
generator.bool_to_i1(ctx, ret)
}
/// Generates a call to `gamma` in IR. Returns an `f64` representing the result.
pub fn call_gamma<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
let llvm_f64 = ctx.ctx.f64_type();
let intrinsic_fn = ctx.module.get_function("__nac3_gamma").unwrap_or_else(|| {
let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
ctx.module.add_function("__nac3_gamma", fn_type, None)
});
ctx.builder
.build_call(intrinsic_fn, &[v.into()], "gamma")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_float_value))
.map(Either::unwrap_left)
.unwrap()
}
/// Generates a call to `gammaln` in IR. Returns an `f64` representing the result.
pub fn call_gammaln<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
let llvm_f64 = ctx.ctx.f64_type();
let intrinsic_fn = ctx.module.get_function("__nac3_gammaln").unwrap_or_else(|| {
let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
ctx.module.add_function("__nac3_gammaln", fn_type, None)
});
ctx.builder
.build_call(intrinsic_fn, &[v.into()], "gammaln")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_float_value))
.map(Either::unwrap_left)
.unwrap()
}
/// Generates a call to `j0` in IR. Returns an `f64` representing the result.
pub fn call_j0<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
let llvm_f64 = ctx.ctx.f64_type();
let intrinsic_fn = ctx.module.get_function("__nac3_j0").unwrap_or_else(|| {
let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
ctx.module.add_function("__nac3_j0", fn_type, None)
});
ctx.builder
.build_call(intrinsic_fn, &[v.into()], "j0")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_float_value))
.map(Either::unwrap_left)
.unwrap()
}
/// Generates a call to `__nac3_ndarray_calc_size`. Returns an [`IntValue`] representing the
/// calculated total size.
///
/// * `dims` - An [`ArrayLikeIndexer`] containing the size of each dimension.
/// * `range` - The dimension index to begin and end (exclusively) calculating the dimensions for,
/// or [`None`] if starting from the first dimension and ending at the last dimension
/// respectively.
pub fn call_ndarray_calc_size<'ctx, G, Dims>(
generator: &G,
ctx: &CodeGenContext<'ctx, '_>,
dims: &Dims,
(begin, end): (Option<IntValue<'ctx>>, Option<IntValue<'ctx>>),
) -> IntValue<'ctx>
where
G: CodeGenerator + ?Sized,
Dims: ArrayLikeIndexer<'ctx>,
{
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
let ndarray_calc_size_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_size",
64 => "__nac3_ndarray_calc_size64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_calc_size_fn_t = llvm_usize.fn_type(
&[llvm_pusize.into(), llvm_usize.into(), llvm_usize.into(), llvm_usize.into()],
false,
);
let ndarray_calc_size_fn =
ctx.module.get_function(ndarray_calc_size_fn_name).unwrap_or_else(|| {
ctx.module.add_function(ndarray_calc_size_fn_name, ndarray_calc_size_fn_t, None)
});
let begin = begin.unwrap_or_else(|| llvm_usize.const_zero());
let end = end.unwrap_or_else(|| dims.size(ctx, generator));
ctx.builder
.build_call(
ndarray_calc_size_fn,
&[
dims.base_ptr(ctx, generator).into(),
dims.size(ctx, generator).into(),
begin.into(),
end.into(),
],
"",
)
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap()
}
/// Generates a call to `__nac3_ndarray_calc_nd_indices`. Returns a [`TypeArrayLikeAdpater`]
/// containing `i32` indices of the flattened index.
///
/// * `index` - The index to compute the multidimensional index for.
/// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
/// `NDArray`.
pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
generator: &G,
ctx: &mut CodeGenContext<'ctx, '_>,
index: IntValue<'ctx>,
ndarray: NDArrayValue<'ctx>,
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
let llvm_void = ctx.ctx.void_type();
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
let ndarray_calc_nd_indices_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_nd_indices",
64 => "__nac3_ndarray_calc_nd_indices64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_calc_nd_indices_fn =
ctx.module.get_function(ndarray_calc_nd_indices_fn_name).unwrap_or_else(|| {
let fn_type = llvm_void.fn_type(
&[llvm_usize.into(), llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into()],
false,
);
ctx.module.add_function(ndarray_calc_nd_indices_fn_name, fn_type, None)
});
let ndarray_num_dims = ndarray.load_ndims(ctx);
let ndarray_dims = ndarray.dim_sizes();
let indices = ctx.builder.build_array_alloca(llvm_i32, ndarray_num_dims, "").unwrap();
ctx.builder
.build_call(
ndarray_calc_nd_indices_fn,
&[
index.into(),
ndarray_dims.base_ptr(ctx, generator).into(),
ndarray_num_dims.into(),
indices.into(),
],
"",
)
.unwrap();
TypedArrayLikeAdapter::from(
ArraySliceValue::from_ptr_val(indices, ndarray_num_dims, None),
Box::new(|_, v| v.into_int_value()),
Box::new(|_, v| v.into()),
)
}
fn call_ndarray_flatten_index_impl<'ctx, G, Indices>(
generator: &G,
ctx: &CodeGenContext<'ctx, '_>,
ndarray: NDArrayValue<'ctx>,
indices: &Indices,
) -> IntValue<'ctx>
where
G: CodeGenerator + ?Sized,
Indices: ArrayLikeIndexer<'ctx>,
{
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
debug_assert_eq!(
IntType::try_from(indices.element_type(ctx, generator))
.map(IntType::get_bit_width)
.unwrap_or_default(),
llvm_i32.get_bit_width(),
"Expected i32 value for argument `indices` to `call_ndarray_flatten_index_impl`"
);
debug_assert_eq!(
indices.size(ctx, generator).get_type().get_bit_width(),
llvm_usize.get_bit_width(),
"Expected usize integer value for argument `indices_size` to `call_ndarray_flatten_index_impl`"
);
let ndarray_flatten_index_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_flatten_index",
64 => "__nac3_ndarray_flatten_index64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_flatten_index_fn =
ctx.module.get_function(ndarray_flatten_index_fn_name).unwrap_or_else(|| {
let fn_type = llvm_usize.fn_type(
&[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_usize.into()],
false,
);
ctx.module.add_function(ndarray_flatten_index_fn_name, fn_type, None)
});
let ndarray_num_dims = ndarray.load_ndims(ctx);
let ndarray_dims = ndarray.dim_sizes();
let index = ctx
.builder
.build_call(
ndarray_flatten_index_fn,
&[
ndarray_dims.base_ptr(ctx, generator).into(),
ndarray_num_dims.into(),
indices.base_ptr(ctx, generator).into(),
indices.size(ctx, generator).into(),
],
"",
)
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap();
index
}
/// Generates a call to `__nac3_ndarray_flatten_index`. Returns the flattened index for the
/// multidimensional index.
///
/// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
/// `NDArray`.
/// * `indices` - The multidimensional index to compute the flattened index for.
pub fn call_ndarray_flatten_index<'ctx, G, Index>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
ndarray: NDArrayValue<'ctx>,
indices: &Index,
) -> IntValue<'ctx>
where
G: CodeGenerator + ?Sized,
Index: ArrayLikeIndexer<'ctx>,
{
call_ndarray_flatten_index_impl(generator, ctx, ndarray, indices)
}
/// Generates a call to `__nac3_ndarray_calc_broadcast`. Returns a tuple containing the number of
/// dimension and size of each dimension of the resultant `ndarray`.
pub fn call_ndarray_calc_broadcast<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
lhs: NDArrayValue<'ctx>,
rhs: NDArrayValue<'ctx>,
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_broadcast",
64 => "__nac3_ndarray_calc_broadcast64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_calc_broadcast_fn =
ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
let fn_type = llvm_usize.fn_type(
&[
llvm_pusize.into(),
llvm_usize.into(),
llvm_pusize.into(),
llvm_usize.into(),
llvm_pusize.into(),
],
false,
);
ctx.module.add_function(ndarray_calc_broadcast_fn_name, fn_type, None)
});
let lhs_ndims = lhs.load_ndims(ctx);
let rhs_ndims = rhs.load_ndims(ctx);
let min_ndims = llvm_intrinsics::call_int_umin(ctx, lhs_ndims, rhs_ndims, None);
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(min_ndims, false),
|generator, ctx, _, idx| {
let idx = ctx.builder.build_int_sub(min_ndims, idx, "").unwrap();
let (lhs_dim_sz, rhs_dim_sz) = unsafe {
(
lhs.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None),
rhs.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None),
)
};
let llvm_usize_const_one = llvm_usize.const_int(1, false);
let lhs_eqz = ctx
.builder
.build_int_compare(IntPredicate::EQ, lhs_dim_sz, llvm_usize_const_one, "")
.unwrap();
let rhs_eqz = ctx
.builder
.build_int_compare(IntPredicate::EQ, rhs_dim_sz, llvm_usize_const_one, "")
.unwrap();
let lhs_or_rhs_eqz = ctx.builder.build_or(lhs_eqz, rhs_eqz, "").unwrap();
let lhs_eq_rhs = ctx
.builder
.build_int_compare(IntPredicate::EQ, lhs_dim_sz, rhs_dim_sz, "")
.unwrap();
let is_compatible = ctx.builder.build_or(lhs_or_rhs_eqz, lhs_eq_rhs, "").unwrap();
ctx.make_assert(
generator,
is_compatible,
"0:ValueError",
"operands could not be broadcast together",
[None, None, None],
ctx.current_loc,
);
Ok(())
},
llvm_usize.const_int(1, false),
)
.unwrap();
let max_ndims = llvm_intrinsics::call_int_umax(ctx, lhs_ndims, rhs_ndims, None);
let lhs_dims = lhs.dim_sizes().base_ptr(ctx, generator);
let lhs_ndims = lhs.load_ndims(ctx);
let rhs_dims = rhs.dim_sizes().base_ptr(ctx, generator);
let rhs_ndims = rhs.load_ndims(ctx);
let out_dims = ctx.builder.build_array_alloca(llvm_usize, max_ndims, "").unwrap();
let out_dims = ArraySliceValue::from_ptr_val(out_dims, max_ndims, None);
ctx.builder
.build_call(
ndarray_calc_broadcast_fn,
&[
lhs_dims.into(),
lhs_ndims.into(),
rhs_dims.into(),
rhs_ndims.into(),
out_dims.base_ptr(ctx, generator).into(),
],
"",
)
.unwrap();
TypedArrayLikeAdapter::from(
out_dims,
Box::new(|_, v| v.into_int_value()),
Box::new(|_, v| v.into()),
)
}
/// Generates a call to `__nac3_ndarray_calc_broadcast_idx`. Returns an [`ArrayAllocaValue`]
/// containing the indices used for accessing `array` corresponding to the index of the broadcasted
/// array `broadcast_idx`.
pub fn call_ndarray_calc_broadcast_index<
'ctx,
G: CodeGenerator + ?Sized,
BroadcastIdx: UntypedArrayLikeAccessor<'ctx>,
>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
array: NDArrayValue<'ctx>,
broadcast_idx: &BroadcastIdx,
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_broadcast_idx",
64 => "__nac3_ndarray_calc_broadcast_idx64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_calc_broadcast_fn =
ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
let fn_type = llvm_usize.fn_type(
&[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_pi32.into()],
false,
);
ctx.module.add_function(ndarray_calc_broadcast_fn_name, fn_type, None)
});
let broadcast_size = broadcast_idx.size(ctx, generator);
let out_idx = ctx.builder.build_array_alloca(llvm_i32, broadcast_size, "").unwrap();
let array_dims = array.dim_sizes().base_ptr(ctx, generator);
let array_ndims = array.load_ndims(ctx);
let broadcast_idx_ptr = unsafe {
broadcast_idx.ptr_offset_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
};
ctx.builder
.build_call(
ndarray_calc_broadcast_fn,
&[array_dims.into(), array_ndims.into(), broadcast_idx_ptr.into(), out_idx.into()],
"",
)
.unwrap();
TypedArrayLikeAdapter::from(
ArraySliceValue::from_ptr_val(out_idx, broadcast_size, None),
Box::new(|_, v| v.into_int_value()),
Box::new(|_, v| v.into()),
)
}

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use crate::codegen::{CodeGenContext, CodeGenerator};
/// 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: &mut 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
}
// pub fn call_nac3_ndarray_util_assert_shape_no_negative<'ctx, G: CodeGenerator + ?Sized>(
// generator: &mut G,
// ctx: &mut CodeGenContext<'ctx, '_>,
// ndims: Instance<'ctx, Int<SizeT>>,
// shape: Instance<'ctx, Ptr<Int<SizeT>>>,
// ) {
// let name = get_usize_dependent_function_name(
// generator,
// ctx,
// "__nac3_ndarray_util_assert_shape_no_negative",
// );
// FnCall::builder(generator, ctx, &name).arg(ndims).arg(shape).returning_void();
// }
//
// pub fn call_nac3_ndarray_util_assert_output_shape_same<'ctx, G: CodeGenerator + ?Sized>(
// generator: &mut G,
// ctx: &mut CodeGenContext<'ctx, '_>,
// ndarray_ndims: Instance<'ctx, Int<SizeT>>,
// ndarray_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
// output_ndims: Instance<'ctx, Int<SizeT>>,
// output_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
// ) {
// let name = get_usize_dependent_function_name(
// generator,
// ctx,
// "__nac3_ndarray_util_assert_output_shape_same",
// );
// FnCall::builder(generator, ctx, &name)
// .arg(ndarray_ndims)
// .arg(ndarray_shape)
// .arg(output_ndims)
// .arg(output_shape)
// .returning_void();
// }
//
// pub fn call_nac3_ndarray_size<'ctx, G: CodeGenerator + ?Sized>(
// generator: &mut G,
// ctx: &mut CodeGenContext<'ctx, '_>,
// ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
// ) -> Instance<'ctx, Int<SizeT>> {
// let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_size");
// FnCall::builder(generator, ctx, &name).arg(ndarray).returning_auto("size")
// }
//
// pub fn call_nac3_ndarray_nbytes<'ctx, G: CodeGenerator + ?Sized>(
// generator: &mut G,
// ctx: &mut CodeGenContext<'ctx, '_>,
// ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
// ) -> Instance<'ctx, Int<SizeT>> {
// let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_nbytes");
// FnCall::builder(generator, ctx, &name).arg(ndarray).returning_auto("nbytes")
// }
//
// pub fn call_nac3_ndarray_len<'ctx, G: CodeGenerator + ?Sized>(
// generator: &mut G,
// ctx: &mut CodeGenContext<'ctx, '_>,
// ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
// ) -> Instance<'ctx, Int<SizeT>> {
// let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_len");
// FnCall::builder(generator, ctx, &name).arg(ndarray).returning_auto("len")
// }
//
// pub fn call_nac3_ndarray_is_c_contiguous<'ctx, G: CodeGenerator + ?Sized>(
// generator: &mut G,
// ctx: &mut CodeGenContext<'ctx, '_>,
// ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
// ) -> Instance<'ctx, Int<Bool>> {
// let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_is_c_contiguous");
// FnCall::builder(generator, ctx, &name).arg(ndarray).returning_auto("is_c_contiguous")
// }
//
// pub fn call_nac3_ndarray_get_nth_pelement<'ctx, G: CodeGenerator + ?Sized>(
// generator: &mut G,
// ctx: &mut CodeGenContext<'ctx, '_>,
// ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
// index: Instance<'ctx, Int<SizeT>>,
// ) -> Instance<'ctx, Ptr<Int<Byte>>> {
// let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_get_nth_pelement");
// FnCall::builder(generator, ctx, &name).arg(ndarray).arg(index).returning_auto("pelement")
// }
//
// pub fn call_nac3_ndarray_get_pelement_by_indices<'ctx, G: CodeGenerator + ?Sized>(
// generator: &mut G,
// ctx: &mut CodeGenContext<'ctx, '_>,
// ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
// indices: Instance<'ctx, Ptr<Int<SizeT>>>,
// ) -> Instance<'ctx, Ptr<Int<Byte>>> {
// let name =
// get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_get_pelement_by_indices");
// FnCall::builder(generator, ctx, &name).arg(ndarray).arg(indices).returning_auto("pelement")
// }
//
// pub fn call_nac3_ndarray_set_strides_by_shape<'ctx, G: CodeGenerator + ?Sized>(
// generator: &mut G,
// ctx: &mut CodeGenContext<'ctx, '_>,
// ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
// ) {
// let name =
// get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_set_strides_by_shape");
// FnCall::builder(generator, ctx, &name).arg(ndarray).returning_void();
// }
//
// pub fn call_nac3_ndarray_copy_data<'ctx, G: CodeGenerator + ?Sized>(
// generator: &mut G,
// ctx: &mut CodeGenContext<'ctx, '_>,
// src_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
// dst_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
// ) {
// let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_copy_data");
// FnCall::builder(generator, ctx, &name).arg(src_ndarray).arg(dst_ndarray).returning_void();
// }

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@ -0,0 +1,387 @@
use inkwell::{
types::IntType,
values::{BasicValueEnum, CallSiteValue, IntValue},
AddressSpace, IntPredicate,
};
use itertools::Either;
use crate::codegen::{
llvm_intrinsics,
macros::codegen_unreachable,
stmt::gen_for_callback_incrementing,
values::{
ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, NDArrayValue, TypedArrayLikeAccessor,
TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
},
CodeGenContext, CodeGenerator,
};
pub use basic::*;
mod basic;
/// Generates a call to `__nac3_ndarray_calc_size`. Returns an [`IntValue`] representing the
/// calculated total size.
///
/// * `dims` - An [`ArrayLikeIndexer`] containing the size of each dimension.
/// * `range` - The dimension index to begin and end (exclusively) calculating the dimensions for,
/// or [`None`] if starting from the first dimension and ending at the last dimension
/// respectively.
pub fn call_ndarray_calc_size<'ctx, G, Dims>(
generator: &G,
ctx: &CodeGenContext<'ctx, '_>,
dims: &Dims,
(begin, end): (Option<IntValue<'ctx>>, Option<IntValue<'ctx>>),
) -> IntValue<'ctx>
where
G: CodeGenerator + ?Sized,
Dims: ArrayLikeIndexer<'ctx>,
{
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
let ndarray_calc_size_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_size",
64 => "__nac3_ndarray_calc_size64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_calc_size_fn_t = llvm_usize.fn_type(
&[llvm_pusize.into(), llvm_usize.into(), llvm_usize.into(), llvm_usize.into()],
false,
);
let ndarray_calc_size_fn =
ctx.module.get_function(ndarray_calc_size_fn_name).unwrap_or_else(|| {
ctx.module.add_function(ndarray_calc_size_fn_name, ndarray_calc_size_fn_t, None)
});
let begin = begin.unwrap_or_else(|| llvm_usize.const_zero());
let end = end.unwrap_or_else(|| dims.size(ctx, generator));
ctx.builder
.build_call(
ndarray_calc_size_fn,
&[
dims.base_ptr(ctx, generator).into(),
dims.size(ctx, generator).into(),
begin.into(),
end.into(),
],
"",
)
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap()
}
/// Generates a call to `__nac3_ndarray_calc_nd_indices`. Returns a [`TypeArrayLikeAdpater`]
/// containing `i32` indices of the flattened index.
///
/// * `index` - The index to compute the multidimensional index for.
/// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
/// `NDArray`.
pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
generator: &G,
ctx: &mut CodeGenContext<'ctx, '_>,
index: IntValue<'ctx>,
ndarray: NDArrayValue<'ctx>,
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
let llvm_void = ctx.ctx.void_type();
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
let ndarray_calc_nd_indices_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_nd_indices",
64 => "__nac3_ndarray_calc_nd_indices64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_calc_nd_indices_fn =
ctx.module.get_function(ndarray_calc_nd_indices_fn_name).unwrap_or_else(|| {
let fn_type = llvm_void.fn_type(
&[llvm_usize.into(), llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into()],
false,
);
ctx.module.add_function(ndarray_calc_nd_indices_fn_name, fn_type, None)
});
let ndarray_num_dims = ndarray.load_ndims(ctx);
let ndarray_dims = ndarray.shape();
let indices = ctx.builder.build_array_alloca(llvm_i32, ndarray_num_dims, "").unwrap();
ctx.builder
.build_call(
ndarray_calc_nd_indices_fn,
&[
index.into(),
ndarray_dims.base_ptr(ctx, generator).into(),
ndarray_num_dims.into(),
indices.into(),
],
"",
)
.unwrap();
TypedArrayLikeAdapter::from(
ArraySliceValue::from_ptr_val(indices, ndarray_num_dims, None),
Box::new(|_, v| v.into_int_value()),
Box::new(|_, v| v.into()),
)
}
fn call_ndarray_flatten_index_impl<'ctx, G, Indices>(
generator: &G,
ctx: &CodeGenContext<'ctx, '_>,
ndarray: NDArrayValue<'ctx>,
indices: &Indices,
) -> IntValue<'ctx>
where
G: CodeGenerator + ?Sized,
Indices: ArrayLikeIndexer<'ctx>,
{
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
debug_assert_eq!(
IntType::try_from(indices.element_type(ctx, generator))
.map(IntType::get_bit_width)
.unwrap_or_default(),
llvm_i32.get_bit_width(),
"Expected i32 value for argument `indices` to `call_ndarray_flatten_index_impl`"
);
debug_assert_eq!(
indices.size(ctx, generator).get_type().get_bit_width(),
llvm_usize.get_bit_width(),
"Expected usize integer value for argument `indices_size` to `call_ndarray_flatten_index_impl`"
);
let ndarray_flatten_index_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_flatten_index",
64 => "__nac3_ndarray_flatten_index64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_flatten_index_fn =
ctx.module.get_function(ndarray_flatten_index_fn_name).unwrap_or_else(|| {
let fn_type = llvm_usize.fn_type(
&[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_usize.into()],
false,
);
ctx.module.add_function(ndarray_flatten_index_fn_name, fn_type, None)
});
let ndarray_num_dims = ndarray.load_ndims(ctx);
let ndarray_dims = ndarray.shape();
let index = ctx
.builder
.build_call(
ndarray_flatten_index_fn,
&[
ndarray_dims.base_ptr(ctx, generator).into(),
ndarray_num_dims.into(),
indices.base_ptr(ctx, generator).into(),
indices.size(ctx, generator).into(),
],
"",
)
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap();
index
}
/// Generates a call to `__nac3_ndarray_flatten_index`. Returns the flattened index for the
/// multidimensional index.
///
/// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
/// `NDArray`.
/// * `indices` - The multidimensional index to compute the flattened index for.
pub fn call_ndarray_flatten_index<'ctx, G, Index>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
ndarray: NDArrayValue<'ctx>,
indices: &Index,
) -> IntValue<'ctx>
where
G: CodeGenerator + ?Sized,
Index: ArrayLikeIndexer<'ctx>,
{
call_ndarray_flatten_index_impl(generator, ctx, ndarray, indices)
}
/// Generates a call to `__nac3_ndarray_calc_broadcast`. Returns a tuple containing the number of
/// dimension and size of each dimension of the resultant `ndarray`.
pub fn call_ndarray_calc_broadcast<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
lhs: NDArrayValue<'ctx>,
rhs: NDArrayValue<'ctx>,
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_broadcast",
64 => "__nac3_ndarray_calc_broadcast64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_calc_broadcast_fn =
ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
let fn_type = llvm_usize.fn_type(
&[
llvm_pusize.into(),
llvm_usize.into(),
llvm_pusize.into(),
llvm_usize.into(),
llvm_pusize.into(),
],
false,
);
ctx.module.add_function(ndarray_calc_broadcast_fn_name, fn_type, None)
});
let lhs_ndims = lhs.load_ndims(ctx);
let rhs_ndims = rhs.load_ndims(ctx);
let min_ndims = llvm_intrinsics::call_int_umin(ctx, lhs_ndims, rhs_ndims, None);
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(min_ndims, false),
|generator, ctx, _, idx| {
let idx = ctx.builder.build_int_sub(min_ndims, idx, "").unwrap();
let (lhs_dim_sz, rhs_dim_sz) = unsafe {
(
lhs.shape().get_typed_unchecked(ctx, generator, &idx, None),
rhs.shape().get_typed_unchecked(ctx, generator, &idx, None),
)
};
let llvm_usize_const_one = llvm_usize.const_int(1, false);
let lhs_eqz = ctx
.builder
.build_int_compare(IntPredicate::EQ, lhs_dim_sz, llvm_usize_const_one, "")
.unwrap();
let rhs_eqz = ctx
.builder
.build_int_compare(IntPredicate::EQ, rhs_dim_sz, llvm_usize_const_one, "")
.unwrap();
let lhs_or_rhs_eqz = ctx.builder.build_or(lhs_eqz, rhs_eqz, "").unwrap();
let lhs_eq_rhs = ctx
.builder
.build_int_compare(IntPredicate::EQ, lhs_dim_sz, rhs_dim_sz, "")
.unwrap();
let is_compatible = ctx.builder.build_or(lhs_or_rhs_eqz, lhs_eq_rhs, "").unwrap();
ctx.make_assert(
generator,
is_compatible,
"0:ValueError",
"operands could not be broadcast together",
[None, None, None],
ctx.current_loc,
);
Ok(())
},
llvm_usize.const_int(1, false),
)
.unwrap();
let max_ndims = llvm_intrinsics::call_int_umax(ctx, lhs_ndims, rhs_ndims, None);
let lhs_dims = lhs.shape().base_ptr(ctx, generator);
let lhs_ndims = lhs.load_ndims(ctx);
let rhs_dims = rhs.shape().base_ptr(ctx, generator);
let rhs_ndims = rhs.load_ndims(ctx);
let out_dims = ctx.builder.build_array_alloca(llvm_usize, max_ndims, "").unwrap();
let out_dims = ArraySliceValue::from_ptr_val(out_dims, max_ndims, None);
ctx.builder
.build_call(
ndarray_calc_broadcast_fn,
&[
lhs_dims.into(),
lhs_ndims.into(),
rhs_dims.into(),
rhs_ndims.into(),
out_dims.base_ptr(ctx, generator).into(),
],
"",
)
.unwrap();
TypedArrayLikeAdapter::from(
out_dims,
Box::new(|_, v| v.into_int_value()),
Box::new(|_, v| v.into()),
)
}
/// Generates a call to `__nac3_ndarray_calc_broadcast_idx`. Returns an [`ArrayAllocaValue`]
/// containing the indices used for accessing `array` corresponding to the index of the broadcasted
/// array `broadcast_idx`.
pub fn call_ndarray_calc_broadcast_index<
'ctx,
G: CodeGenerator + ?Sized,
BroadcastIdx: UntypedArrayLikeAccessor<'ctx>,
>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
array: NDArrayValue<'ctx>,
broadcast_idx: &BroadcastIdx,
) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_broadcast_idx",
64 => "__nac3_ndarray_calc_broadcast_idx64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
};
let ndarray_calc_broadcast_fn =
ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
let fn_type = llvm_usize.fn_type(
&[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_pi32.into()],
false,
);
ctx.module.add_function(ndarray_calc_broadcast_fn_name, fn_type, None)
});
let broadcast_size = broadcast_idx.size(ctx, generator);
let out_idx = ctx.builder.build_array_alloca(llvm_i32, broadcast_size, "").unwrap();
let array_dims = array.shape().base_ptr(ctx, generator);
let array_ndims = array.load_ndims(ctx);
let broadcast_idx_ptr = unsafe {
broadcast_idx.ptr_offset_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
};
ctx.builder
.build_call(
ndarray_calc_broadcast_fn,
&[array_dims.into(), array_ndims.into(), broadcast_idx_ptr.into(), out_idx.into()],
"",
)
.unwrap();
TypedArrayLikeAdapter::from(
ArraySliceValue::from_ptr_val(out_idx, broadcast_size, None),
Box::new(|_, v| v.into_int_value()),
Box::new(|_, v| v.into()),
)
}

View File

@ -0,0 +1,76 @@
use inkwell::{
values::{BasicValueEnum, CallSiteValue, IntValue},
IntPredicate,
};
use itertools::Either;
use nac3parser::ast::Expr;
use crate::{
codegen::{CodeGenContext, CodeGenerator},
typecheck::typedef::Type,
};
/// this function allows index out of range, since python
/// allows index out of range in slice (`a = [1,2,3]; a[1:10] == [2,3]`).
pub fn handle_slice_index_bound<'ctx, G: CodeGenerator>(
i: &Expr<Option<Type>>,
ctx: &mut CodeGenContext<'ctx, '_>,
generator: &mut G,
length: IntValue<'ctx>,
) -> Result<Option<IntValue<'ctx>>, String> {
const SYMBOL: &str = "__nac3_slice_index_bound";
let func = ctx.module.get_function(SYMBOL).unwrap_or_else(|| {
let i32_t = ctx.ctx.i32_type();
let fn_t = i32_t.fn_type(&[i32_t.into(), i32_t.into()], false);
ctx.module.add_function(SYMBOL, fn_t, None)
});
let i = if let Some(v) = generator.gen_expr(ctx, i)? {
v.to_basic_value_enum(ctx, generator, i.custom.unwrap())?
} else {
return Ok(None);
};
Ok(Some(
ctx.builder
.build_call(func, &[i.into(), length.into()], "bounded_ind")
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap(),
))
}
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()
}

View File

@ -3,6 +3,7 @@ use inkwell::{
values::{BasicValue, BasicValueEnum, IntValue, PointerValue},
AddressSpace, IntPredicate, OptimizationLevel,
};
use itertools::Itertools;
use nac3parser::ast::{Operator, StrRef};
@ -26,8 +27,8 @@ use super::{
use crate::{
symbol_resolver::ValueEnum,
toplevel::{
helper::PrimDef,
numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
helper::{arraylike_flatten_element_type, PrimDef},
numpy::unpack_ndarray_var_tys,
DefinitionId,
},
typecheck::{
@ -42,19 +43,17 @@ fn create_ndarray_uninitialized<'ctx, G: CodeGenerator + ?Sized>(
ctx: &mut CodeGenContext<'ctx, '_>,
elem_ty: Type,
) -> Result<NDArrayValue<'ctx>, String> {
let ndarray_ty = make_ndarray_ty(&mut ctx.unifier, &ctx.primitives, Some(elem_ty), None);
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_ndarray_t = ctx
.get_llvm_type(generator, ndarray_ty)
.into_pointer_type()
let llvm_ndarray_t = NDArrayType::new(generator, ctx.ctx, llvm_elem_ty)
.as_base_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_usize, None))
Ok(NDArrayValue::from_pointer_value(ndarray, llvm_elem_ty, None, llvm_usize, None))
}
/// Creates an `NDArray` instance from a dynamic shape.
@ -127,7 +126,7 @@ where
ndarray.store_ndims(ctx, generator, num_dims);
let ndarray_num_dims = ndarray.load_ndims(ctx);
ndarray.create_dim_sizes(ctx, llvm_usize, ndarray_num_dims);
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)?;
@ -143,7 +142,7 @@ where
let shape_dim = ctx.builder.build_int_z_extend(shape_dim, llvm_usize, "").unwrap();
let ndarray_pdim =
unsafe { ndarray.dim_sizes().ptr_offset_unchecked(ctx, generator, &i, None) };
unsafe { ndarray.shape().ptr_offset_unchecked(ctx, generator, &i, None) };
ctx.builder.build_store(ndarray_pdim, shape_dim).unwrap();
@ -188,28 +187,10 @@ pub fn create_ndarray_const_shape<'ctx, G: CodeGenerator + ?Sized>(
// TODO: Disallow dim_sz > u32_MAX
}
let ndarray = create_ndarray_uninitialized(generator, ctx, elem_ty)?;
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_dim_sizes(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.dim_sizes().ptr_offset_unchecked(
ctx,
generator,
&llvm_usize.const_int(i as u64, true),
None,
)
};
ctx.builder.build_store(ndarray_dim, shape_dim).unwrap();
}
let llvm_dtype = ctx.get_llvm_type(generator, elem_ty);
let ndarray = NDArrayType::new(generator, ctx.ctx, llvm_dtype)
.construct_dyn_shape(generator, ctx, shape, None);
let ndarray = ndarray_init_data(generator, ctx, elem_ty, ndarray);
Ok(ndarray)
@ -228,7 +209,7 @@ fn ndarray_init_data<'ctx, G: CodeGenerator + ?Sized>(
let ndarray_num_elems = call_ndarray_calc_size(
generator,
ctx,
&ndarray.dim_sizes().as_slice_value(ctx, generator),
&ndarray.shape().as_slice_value(ctx, generator),
(None, None),
);
ndarray.create_data(ctx, llvm_ndarray_data_t, ndarray_num_elems);
@ -337,20 +318,24 @@ 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 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();
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();
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])
}
@ -379,7 +364,7 @@ where
let ndarray_num_elems = call_ndarray_calc_size(
generator,
ctx,
&ndarray.dim_sizes().as_slice_value(ctx, generator),
&ndarray.shape().as_slice_value(ctx, generator),
(None, None),
);
@ -473,8 +458,8 @@ fn ndarray_broadcast_fill<'ctx, 'a, G, ValueFn>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, 'a>,
res: NDArrayValue<'ctx>,
lhs: (BasicValueEnum<'ctx>, bool),
rhs: (BasicValueEnum<'ctx>, bool),
lhs: (Type, BasicValueEnum<'ctx>, bool),
rhs: (Type, BasicValueEnum<'ctx>, bool),
value_fn: ValueFn,
) -> Result<NDArrayValue<'ctx>, String>
where
@ -487,8 +472,8 @@ where
{
let llvm_usize = generator.get_size_type(ctx.ctx);
let (lhs_val, lhs_scalar) = lhs;
let (rhs_val, rhs_scalar) = rhs;
let (lhs_ty, lhs_val, lhs_scalar) = lhs;
let (rhs_ty, rhs_val, rhs_scalar) = rhs;
assert!(
!(lhs_scalar && rhs_scalar),
@ -499,14 +484,28 @@ where
// Assert that all ndarray operands are broadcastable to the target size
if !lhs_scalar {
let lhs_val =
NDArrayValue::from_pointer_value(lhs_val.into_pointer_value(), llvm_usize, 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,
None,
llvm_usize,
None,
);
ndarray_assert_is_broadcastable(generator, ctx, res, lhs_val);
}
if !rhs_scalar {
let rhs_val =
NDArrayValue::from_pointer_value(rhs_val.into_pointer_value(), 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,
None,
llvm_usize,
None,
);
ndarray_assert_is_broadcastable(generator, ctx, res, rhs_val);
}
@ -514,8 +513,15 @@ where
let lhs_elem = if lhs_scalar {
lhs_val
} else {
let lhs =
NDArrayValue::from_pointer_value(lhs_val.into_pointer_value(), llvm_usize, 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,
None,
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) }
@ -524,8 +530,15 @@ where
let rhs_elem = if rhs_scalar {
rhs_val
} else {
let rhs =
NDArrayValue::from_pointer_value(rhs_val.into_pointer_value(), 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 = NDArrayValue::from_pointer_value(
rhs_val.into_pointer_value(),
llvm_rhs_elem_ty,
None,
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) }
@ -671,7 +684,7 @@ fn llvm_ndlist_get_ndims<'ctx, G: CodeGenerator + ?Sized>(
fn llvm_arraylike_get_ndims<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
value: BasicValueEnum<'ctx>,
(ty, value): (Type, BasicValueEnum<'ctx>),
) -> IntValue<'ctx> {
let llvm_usize = generator.get_size_type(ctx.ctx);
@ -679,7 +692,10 @@ fn llvm_arraylike_get_ndims<'ctx, G: CodeGenerator + ?Sized>(
BasicValueEnum::PointerValue(v)
if NDArrayValue::is_representable(v, llvm_usize).is_ok() =>
{
NDArrayValue::from_pointer_value(v, llvm_usize, 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, None, llvm_usize, None)
.load_ndims(ctx)
}
BasicValueEnum::PointerValue(v) if ListValue::is_representable(v, llvm_usize).is_ok() => {
@ -694,7 +710,6 @@ fn llvm_arraylike_get_ndims<'ctx, G: CodeGenerator + ?Sized>(
fn ndarray_from_ndlist_impl<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
elem_ty: Type,
(dst_arr, dst_slice_ptr): (NDArrayValue<'ctx>, PointerValue<'ctx>),
src_lst: ListValue<'ctx>,
dim: u64,
@ -713,7 +728,7 @@ fn ndarray_from_ndlist_impl<'ctx, G: CodeGenerator + ?Sized>(
let stride = call_ndarray_calc_size(
generator,
ctx,
&dst_arr.dim_sizes(),
&dst_arr.shape(),
(Some(llvm_usize.const_int(dim + 1, false)), None),
);
@ -727,6 +742,20 @@ fn ndarray_from_ndlist_impl<'ctx, G: CodeGenerator + ?Sized>(
|_, _| Ok(llvm_usize.const_int(1, false)),
|generator, ctx, _, i| {
let offset = ctx.builder.build_int_mul(stride, i, "").unwrap();
let offset = ctx
.builder
.build_int_mul(
offset,
ctx.builder
.build_int_truncate_or_bit_cast(
dst_arr.get_type().element_type().size_of().unwrap(),
offset.get_type(),
"",
)
.unwrap(),
"",
)
.unwrap();
let dst_ptr =
unsafe { ctx.builder.build_gep(dst_slice_ptr, &[offset], "").unwrap() };
@ -741,7 +770,6 @@ fn ndarray_from_ndlist_impl<'ctx, G: CodeGenerator + ?Sized>(
ndarray_from_ndlist_impl(
generator,
ctx,
elem_ty,
(dst_arr, dst_ptr),
nested_lst_elem,
dim + 1,
@ -760,7 +788,7 @@ fn ndarray_from_ndlist_impl<'ctx, G: CodeGenerator + ?Sized>(
_ => {
let lst_len = src_lst.load_size(ctx, None);
let sizeof_elem = ctx.get_llvm_type(generator, elem_ty).size_of().unwrap();
let sizeof_elem = dst_arr.get_type().element_type().size_of().unwrap();
let sizeof_elem = ctx.builder.build_int_cast(sizeof_elem, llvm_usize, "").unwrap();
let cpy_len = ctx
@ -816,7 +844,8 @@ 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 object = NDArrayValue::from_pointer_value(object, llvm_usize, None);
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 ndarray = gen_if_else_expr_callback(
generator,
@ -878,7 +907,6 @@ fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
ndarray_sliced_copyto_impl(
generator,
ctx,
elem_ty,
(ndarray, ndarray.data().base_ptr(ctx, generator)),
(object, object.data().base_ptr(ctx, generator)),
0,
@ -892,6 +920,8 @@ 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,
));
@ -1026,7 +1056,6 @@ fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
ndarray_from_ndlist_impl(
generator,
ctx,
elem_ty,
(ndarray, ndarray.data().base_ptr(ctx, generator)),
object,
0,
@ -1099,7 +1128,6 @@ fn call_ndarray_eye_impl<'ctx, G: CodeGenerator + ?Sized>(
fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
elem_ty: Type,
(dst_arr, dst_slice_ptr): (NDArrayValue<'ctx>, PointerValue<'ctx>),
(src_arr, src_slice_ptr): (NDArrayValue<'ctx>, PointerValue<'ctx>),
dim: u64,
@ -1108,14 +1136,16 @@ fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
let llvm_i1 = ctx.ctx.bool_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
assert_eq!(dst_arr.get_type().element_type(), src_arr.get_type().element_type());
let sizeof_elem = dst_arr.get_type().element_type().size_of().unwrap();
// If there are no (remaining) slice expressions, memcpy the entire dimension
if slices.is_empty() {
let sizeof_elem = ctx.get_llvm_type(generator, elem_ty).size_of().unwrap();
let stride = call_ndarray_calc_size(
generator,
ctx,
&src_arr.dim_sizes(),
&src_arr.shape(),
(Some(llvm_usize.const_int(dim, false)), None),
);
let stride =
@ -1133,13 +1163,13 @@ fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
let src_stride = call_ndarray_calc_size(
generator,
ctx,
&src_arr.dim_sizes(),
&src_arr.shape(),
(Some(llvm_usize.const_int(dim + 1, false)), None),
);
let dst_stride = call_ndarray_calc_size(
generator,
ctx,
&dst_arr.dim_sizes(),
&dst_arr.shape(),
(Some(llvm_usize.const_int(dim + 1, false)), None),
);
@ -1162,9 +1192,29 @@ fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
|generator, ctx, _, src_i| {
// Calculate the offset of the active slice
let src_data_offset = ctx.builder.build_int_mul(src_stride, src_i, "").unwrap();
let src_data_offset = ctx
.builder
.build_int_mul(
src_data_offset,
ctx.builder
.build_int_cast(sizeof_elem, src_data_offset.get_type(), "")
.unwrap(),
"",
)
.unwrap();
let dst_i =
ctx.builder.build_load(dst_i_addr, "").map(BasicValueEnum::into_int_value).unwrap();
let dst_data_offset = ctx.builder.build_int_mul(dst_stride, dst_i, "").unwrap();
let dst_data_offset = ctx
.builder
.build_int_mul(
dst_data_offset,
ctx.builder
.build_int_cast(sizeof_elem, dst_data_offset.get_type(), "")
.unwrap(),
"",
)
.unwrap();
let (src_ptr, dst_ptr) = unsafe {
(
@ -1176,7 +1226,6 @@ fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
ndarray_sliced_copyto_impl(
generator,
ctx,
elem_ty,
(dst_arr, dst_ptr),
(src_arr, src_ptr),
dim + 1,
@ -1219,7 +1268,7 @@ pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
&this,
|_, ctx, shape| Ok(shape.load_ndims(ctx)),
|generator, ctx, shape, idx| unsafe {
Ok(shape.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None))
Ok(shape.shape().get_typed_unchecked(ctx, generator, &idx, None))
},
)?
} else {
@ -1227,7 +1276,7 @@ pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
ndarray.store_ndims(ctx, generator, this.load_ndims(ctx));
let ndims = this.load_ndims(ctx);
ndarray.create_dim_sizes(ctx, llvm_usize, ndims);
ndarray.create_shape(ctx, llvm_usize, ndims);
// Populate the first slices.len() dimensions by computing the size of each dim slice
for (i, (start, stop, step)) in slices.iter().enumerate() {
@ -1259,7 +1308,7 @@ pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
ctx.builder.build_int_z_extend_or_bit_cast(slice_len, llvm_usize, "").unwrap();
unsafe {
ndarray.dim_sizes().set_typed_unchecked(
ndarray.shape().set_typed_unchecked(
ctx,
generator,
&llvm_usize.const_int(i as u64, false),
@ -1277,8 +1326,8 @@ pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
(this.load_ndims(ctx), false),
|generator, ctx, _, idx| {
unsafe {
let dim_sz = this.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None);
ndarray.dim_sizes().set_typed_unchecked(ctx, generator, &idx, dim_sz);
let dim_sz = this.shape().get_typed_unchecked(ctx, generator, &idx, None);
ndarray.shape().set_typed_unchecked(ctx, generator, &idx, dim_sz);
}
Ok(())
@ -1293,7 +1342,6 @@ pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
ndarray_sliced_copyto_impl(
generator,
ctx,
elem_ty,
(ndarray, ndarray.data().base_ptr(ctx, generator)),
(this, this.data().base_ptr(ctx, generator)),
0,
@ -1339,7 +1387,7 @@ where
&operand,
|_, ctx, v| Ok(v.load_ndims(ctx)),
|generator, ctx, v, idx| unsafe {
Ok(v.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None))
Ok(v.shape().get_typed_unchecked(ctx, generator, &idx, None))
},
)
.unwrap()
@ -1376,8 +1424,8 @@ pub fn ndarray_elementwise_binop_impl<'ctx, 'a, G, ValueFn>(
ctx: &mut CodeGenContext<'ctx, 'a>,
elem_ty: Type,
res: Option<NDArrayValue<'ctx>>,
lhs: (BasicValueEnum<'ctx>, bool),
rhs: (BasicValueEnum<'ctx>, bool),
lhs: (Type, BasicValueEnum<'ctx>, bool),
rhs: (Type, BasicValueEnum<'ctx>, bool),
value_fn: ValueFn,
) -> Result<NDArrayValue<'ctx>, String>
where
@ -1390,8 +1438,8 @@ where
{
let llvm_usize = generator.get_size_type(ctx.ctx);
let (lhs_val, lhs_scalar) = lhs;
let (rhs_val, rhs_scalar) = rhs;
let (lhs_ty, lhs_val, lhs_scalar) = lhs;
let (rhs_ty, rhs_val, rhs_scalar) = rhs;
assert!(
!(lhs_scalar && rhs_scalar),
@ -1402,10 +1450,24 @@ where
let ndarray = res.unwrap_or_else(|| {
if lhs_scalar && rhs_scalar {
let lhs_val =
NDArrayValue::from_pointer_value(lhs_val.into_pointer_value(), llvm_usize, None);
let rhs_val =
NDArrayValue::from_pointer_value(rhs_val.into_pointer_value(), llvm_usize, 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,
None,
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,
None,
llvm_usize,
None,
);
let ndarray_dims = call_ndarray_calc_broadcast(generator, ctx, lhs_val, rhs_val);
@ -1421,8 +1483,15 @@ where
)
.unwrap()
} else {
let dtype = arraylike_flatten_element_type(
&mut ctx.unifier,
if lhs_scalar { rhs_ty } else { lhs_ty },
);
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,
None,
llvm_usize,
None,
);
@ -1434,7 +1503,7 @@ where
&ndarray,
|_, ctx, v| Ok(v.load_ndims(ctx)),
|generator, ctx, v, idx| unsafe {
Ok(v.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None))
Ok(v.shape().get_typed_unchecked(ctx, generator, &idx, None))
},
)
.unwrap()
@ -1495,10 +1564,10 @@ pub fn ndarray_matmul_2d<'ctx, G: CodeGenerator>(
if let Some(res) = res {
let res_ndims = res.load_ndims(ctx);
let res_dim0 = unsafe {
res.dim_sizes().get_typed_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
res.shape().get_typed_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
};
let res_dim1 = unsafe {
res.dim_sizes().get_typed_unchecked(
res.shape().get_typed_unchecked(
ctx,
generator,
&llvm_usize.const_int(1, false),
@ -1506,10 +1575,10 @@ pub fn ndarray_matmul_2d<'ctx, G: CodeGenerator>(
)
};
let lhs_dim0 = unsafe {
lhs.dim_sizes().get_typed_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
lhs.shape().get_typed_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
};
let rhs_dim1 = unsafe {
rhs.dim_sizes().get_typed_unchecked(
rhs.shape().get_typed_unchecked(
ctx,
generator,
&llvm_usize.const_int(1, false),
@ -1558,15 +1627,10 @@ pub fn ndarray_matmul_2d<'ctx, G: CodeGenerator>(
if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
let lhs_dim1 = unsafe {
lhs.dim_sizes().get_typed_unchecked(
ctx,
generator,
&llvm_usize.const_int(1, false),
None,
)
lhs.shape().get_typed_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
};
let rhs_dim0 = unsafe {
rhs.dim_sizes().get_typed_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
rhs.shape().get_typed_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
};
// lhs.dims[1] == rhs.dims[0]
@ -1605,7 +1669,7 @@ pub fn ndarray_matmul_2d<'ctx, G: CodeGenerator>(
},
|generator, ctx| {
Ok(Some(unsafe {
lhs.dim_sizes().get_typed_unchecked(
lhs.shape().get_typed_unchecked(
ctx,
generator,
&llvm_usize.const_zero(),
@ -1615,7 +1679,7 @@ pub fn ndarray_matmul_2d<'ctx, G: CodeGenerator>(
},
|generator, ctx| {
Ok(Some(unsafe {
rhs.dim_sizes().get_typed_unchecked(
rhs.shape().get_typed_unchecked(
ctx,
generator,
&llvm_usize.const_int(1, false),
@ -1642,7 +1706,7 @@ pub fn ndarray_matmul_2d<'ctx, G: CodeGenerator>(
let common_dim = {
let lhs_idx1 = unsafe {
lhs.dim_sizes().get_typed_unchecked(
lhs.shape().get_typed_unchecked(
ctx,
generator,
&llvm_usize.const_int(1, false),
@ -1650,7 +1714,7 @@ pub fn ndarray_matmul_2d<'ctx, G: CodeGenerator>(
)
};
let rhs_idx0 = unsafe {
rhs.dim_sizes().get_typed_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
rhs.shape().get_typed_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
};
let idx = llvm_intrinsics::call_expect(ctx, rhs_idx0, lhs_idx1, None);
@ -1981,11 +2045,19 @@ pub fn gen_ndarray_copy<'ctx>(
let this_arg =
obj.as_ref().unwrap().1.clone().to_basic_value_enum(context, generator, this_ty)?;
let llvm_elem_ty = context.get_llvm_type(generator, this_elem_ty);
ndarray_copy_impl(
generator,
context,
this_elem_ty,
NDArrayValue::from_pointer_value(this_arg.into_pointer_value(), llvm_usize, None),
NDArrayValue::from_pointer_value(
this_arg.into_pointer_value(),
llvm_elem_ty,
None,
llvm_usize,
None,
),
)
.map(NDArrayValue::into)
}
@ -2004,6 +2076,7 @@ pub fn gen_ndarray_fill<'ctx>(
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()
@ -2014,10 +2087,12 @@ 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_elem_ty = context.get_llvm_type(generator, this_elem_ty);
ndarray_fill_flattened(
generator,
context,
NDArrayValue::from_pointer_value(this_arg, llvm_usize, None),
NDArrayValue::from_pointer_value(this_arg, llvm_elem_ty, None, llvm_usize, None),
|generator, ctx, _| {
let value = if value_arg.is_pointer_value() {
let llvm_i1 = ctx.ctx.bool_type();
@ -2058,8 +2133,9 @@ pub fn ndarray_transpose<'ctx, G: CodeGenerator + ?Sized>(
if let BasicValueEnum::PointerValue(n1) = x1 {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
let n1 = NDArrayValue::from_pointer_value(n1, llvm_usize, None);
let n_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let n1 = NDArrayValue::from_pointer_value(n1, llvm_elem_ty, None, llvm_usize, None);
let n_sz = call_ndarray_calc_size(generator, ctx, &n1.shape(), (None, None));
// Dimensions are reversed in the transposed array
let out = create_ndarray_dyn_shape(
@ -2074,7 +2150,7 @@ pub fn ndarray_transpose<'ctx, G: CodeGenerator + ?Sized>(
.builder
.build_int_sub(new_idx, new_idx.get_type().const_int(1, false), "")
.unwrap();
unsafe { Ok(n.dim_sizes().get_typed_unchecked(ctx, generator, &new_idx, None)) }
unsafe { Ok(n.shape().get_typed_unchecked(ctx, generator, &new_idx, None)) }
},
)
.unwrap();
@ -2111,7 +2187,7 @@ pub fn ndarray_transpose<'ctx, G: CodeGenerator + ?Sized>(
.build_int_sub(ndim_rev, llvm_usize.const_int(1, false), "")
.unwrap();
let dim = unsafe {
n1.dim_sizes().get_typed_unchecked(ctx, generator, &ndim_rev, None)
n1.shape().get_typed_unchecked(ctx, generator, &ndim_rev, None)
};
let rem_idx_val =
@ -2177,8 +2253,9 @@ 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 n1 = NDArrayValue::from_pointer_value(n1, llvm_usize, None);
let n_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let n1 = NDArrayValue::from_pointer_value(n1, llvm_elem_ty, None, 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)?;
let num_neg = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
@ -2406,7 +2483,7 @@ pub fn ndarray_reshape<'ctx, G: CodeGenerator + ?Sized>(
);
// The new shape must be compatible with the old shape
let out_sz = call_ndarray_calc_size(generator, ctx, &out.dim_sizes(), (None, None));
let out_sz = call_ndarray_calc_size(generator, ctx, &out.shape(), (None, None));
ctx.make_assert(
generator,
ctx.builder.build_int_compare(IntPredicate::EQ, out_sz, n_sz, "").unwrap(),
@ -2454,17 +2531,22 @@ pub fn ndarray_dot<'ctx, G: CodeGenerator + ?Sized>(
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "ndarray_dot";
let (x1_ty, x1) = x1;
let (_, x2) = x2;
let (x2_ty, x2) = x2;
let llvm_usize = generator.get_size_type(ctx.ctx);
match (x1, x2) {
(BasicValueEnum::PointerValue(n1), BasicValueEnum::PointerValue(n2)) => {
let n1 = NDArrayValue::from_pointer_value(n1, llvm_usize, None);
let n2 = NDArrayValue::from_pointer_value(n2, llvm_usize, 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_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
let n2_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
let n1 = NDArrayValue::from_pointer_value(n1, llvm_n1_data_ty, None, llvm_usize, None);
let n2 = NDArrayValue::from_pointer_value(n2, llvm_n2_data_ty, None, 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));
ctx.make_assert(
generator,
@ -2501,7 +2583,7 @@ pub fn ndarray_dot<'ctx, G: CodeGenerator + ?Sized>(
.build_float_mul(e1, elem2.into_float_value(), "")
.unwrap()
.as_basic_value_enum(),
_ => codegen_unreachable!(ctx),
_ => codegen_unreachable!(ctx, "product: {}", elem1.get_type()),
};
let acc_val = ctx.builder.build_load(acc, "").unwrap();
let acc_val = match acc_val {
@ -2515,7 +2597,7 @@ pub fn ndarray_dot<'ctx, G: CodeGenerator + ?Sized>(
.build_float_add(e1, product.into_float_value(), "")
.unwrap()
.as_basic_value_enum(),
_ => codegen_unreachable!(ctx),
_ => codegen_unreachable!(ctx, "acc_val: {}", acc_val.get_type()),
};
ctx.builder.build_store(acc, acc_val).unwrap();

View File

@ -55,6 +55,19 @@ impl<'ctx> ListType<'ctx> {
Ok(())
}
/// Creates an LLVM type corresponding to the expected structure of a `List`.
#[must_use]
fn llvm_type(
ctx: &'ctx Context,
element_type: BasicTypeEnum<'ctx>,
llvm_usize: IntType<'ctx>,
) -> PointerType<'ctx> {
// struct List { data: T*, size: size_t }
let field_tys = [element_type.ptr_type(AddressSpace::default()).into(), llvm_usize.into()];
ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
}
/// Creates an instance of [`ListType`].
#[must_use]
pub fn new<G: CodeGenerator + ?Sized>(
@ -63,12 +76,7 @@ impl<'ctx> ListType<'ctx> {
element_type: BasicTypeEnum<'ctx>,
) -> Self {
let llvm_usize = generator.get_size_type(ctx);
let llvm_list = ctx
.struct_type(
&[element_type.ptr_type(AddressSpace::default()).into(), llvm_usize.into()],
false,
)
.ptr_type(AddressSpace::default());
let llvm_list = Self::llvm_type(ctx, element_type, llvm_usize);
ListType::from_type(llvm_list, llvm_usize)
}

View File

@ -11,6 +11,7 @@ pub use range::*;
mod list;
mod ndarray;
mod range;
pub mod structure;
/// A LLVM type that is used to represent a corresponding type in NAC3.
pub trait ProxyType<'ctx>: Into<Self::Base> {

View File

@ -1,79 +1,155 @@
use inkwell::{
context::Context,
context::{AsContextRef, Context, ContextRef},
types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
values::IntValue,
values::{IntValue, PointerValue},
AddressSpace,
};
use itertools::Itertools;
use super::ProxyType;
use crate::codegen::{
values::{ArraySliceValue, NDArrayValue, ProxyValue},
{CodeGenContext, CodeGenerator},
use super::{
structure::{FieldIndexCounter, StructField, StructFields},
ProxyType,
};
use crate::{
codegen::{
values::{ArraySliceValue, NDArrayValue, ProxyValue, TypedArrayLikeMutator},
{CodeGenContext, CodeGenerator},
},
toplevel::{helper::extract_ndims, numpy::unpack_ndarray_var_tys},
typecheck::typedef::Type,
};
/// Proxy type for a `ndarray` type in LLVM.
#[derive(Debug, PartialEq, Eq, Clone, Copy)]
pub struct NDArrayType<'ctx> {
ty: PointerType<'ctx>,
dtype: BasicTypeEnum<'ctx>,
// TODO(Derppening): Make this non-optional
ndims: Option<u64>,
llvm_usize: IntType<'ctx>,
}
#[derive(PartialEq, Eq, Clone, Copy)]
pub struct NDArrayStructFields<'ctx> {
pub itemsize: StructField<'ctx, IntValue<'ctx>>,
pub ndims: StructField<'ctx, IntValue<'ctx>>,
pub shape: StructField<'ctx, PointerValue<'ctx>>,
pub strides: StructField<'ctx, PointerValue<'ctx>>,
pub data: StructField<'ctx, PointerValue<'ctx>>,
}
impl<'ctx> StructFields<'ctx> for NDArrayStructFields<'ctx> {
fn new(ctx: impl AsContextRef<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
let ctx = unsafe { ContextRef::new(ctx.as_ctx_ref()) };
let mut counter = FieldIndexCounter::default();
NDArrayStructFields {
itemsize: StructField::create(&mut counter, "itemsize", llvm_usize),
ndims: StructField::create(&mut counter, "ndims", llvm_usize),
shape: StructField::create(
&mut counter,
"shape",
llvm_usize.ptr_type(AddressSpace::default()),
),
strides: StructField::create(
&mut counter,
"strides",
llvm_usize.ptr_type(AddressSpace::default()),
),
data: StructField::create(
&mut counter,
"data",
ctx.i8_type().ptr_type(AddressSpace::default()),
),
}
}
fn to_vec(&self) -> Vec<(&'static str, BasicTypeEnum<'ctx>)> {
vec![
self.itemsize.into(),
self.ndims.into(),
self.shape.into(),
self.strides.into(),
self.data.into(),
]
}
}
impl<'ctx> NDArrayType<'ctx> {
/// Checks whether `llvm_ty` represents a `ndarray` type, returning [Err] if it does not.
pub fn is_representable(
llvm_ty: PointerType<'ctx>,
llvm_usize: IntType<'ctx>,
) -> Result<(), String> {
let ctx = llvm_ty.get_context();
let llvm_expected_ty = Self::fields(ctx, llvm_usize).into_vec();
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 {
if llvm_ndarray_ty.count_fields() != u32::try_from(llvm_expected_ty.len()).unwrap() {
return Err(format!(
"Expected 3 fields in `NDArray`, got {}",
"Expected {} fields in `NDArray`, got {}",
llvm_expected_ty.len(),
llvm_ndarray_ty.count_fields()
));
}
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(_) = PointerType::try_from(ndarray_data_ty) else {
return Err(format!("Expected pointer type for `ndarray.2`, got {ndarray_data_ty}"));
};
llvm_expected_ty
.iter()
.enumerate()
.map(|(i, expected_ty)| {
(expected_ty.1, llvm_ndarray_ty.get_field_type_at_index(i as u32).unwrap())
})
.try_for_each(|(expected_ty, actual_ty)| {
if expected_ty == actual_ty {
Ok(())
} else {
Err(format!("Expected {expected_ty} for `ndarray.data`, got {actual_ty}"))
}
})?;
Ok(())
}
/// Creates an instance of [`ListType`].
// TODO: Move this into e.g. StructProxyType
#[must_use]
fn fields(
ctx: impl AsContextRef<'ctx>,
llvm_usize: IntType<'ctx>,
) -> NDArrayStructFields<'ctx> {
NDArrayStructFields::new(ctx, llvm_usize)
}
// TODO: Move this into e.g. StructProxyType
#[must_use]
pub fn get_fields(
&self,
ctx: impl AsContextRef<'ctx>,
llvm_usize: IntType<'ctx>,
) -> NDArrayStructFields<'ctx> {
Self::fields(ctx, 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 { data: i8*, itemsize: size_t, ndims: size_t, shape: size_t*, strides: size_t* }
//
// * 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();
ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
}
/// Creates an instance of [`NDArrayType`].
#[must_use]
pub fn new<G: CodeGenerator + ?Sized>(
generator: &G,
@ -81,32 +157,42 @@ impl<'ctx> NDArrayType<'ctx> {
dtype: BasicTypeEnum<'ctx>,
) -> Self {
let llvm_usize = generator.get_size_type(ctx);
let llvm_ndarray = Self::llvm_type(ctx, llvm_usize);
// struct NDArray { num_dims: size_t, dims: size_t*, data: T* }
//
// * num_dims: Number of dimensions in the array
// * dims: Pointer to an array containing the size of each dimension
// * data: Pointer to an array containing the array data
let llvm_ndarray = ctx
.struct_type(
&[
llvm_usize.into(),
llvm_usize.ptr_type(AddressSpace::default()).into(),
dtype.ptr_type(AddressSpace::default()).into(),
],
false,
)
.ptr_type(AddressSpace::default());
NDArrayType::from_type(llvm_ndarray, llvm_usize)
NDArrayType { ty: llvm_ndarray, dtype, ndims: None, llvm_usize }
}
/// Creates an [`NDArrayType`] from a [`PointerType`].
/// Creates an [`NDArrayType`] from a [unifier type][Type].
#[must_use]
pub fn from_type(ptr_ty: PointerType<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
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 ndims = extract_ndims(&ctx.unifier, ndims);
let llvm_dtype = ctx.get_llvm_type(generator, dtype);
let llvm_usize = generator.get_size_type(ctx.ctx);
NDArrayType {
ty: Self::llvm_type(ctx.ctx, llvm_usize),
dtype: llvm_dtype,
ndims: Some(ndims),
llvm_usize,
}
}
/// Creates an [`NDArrayType`] from a [`PointerType`] representing an `NDArray`.
#[must_use]
pub fn from_type(
ptr_ty: PointerType<'ctx>,
dtype: BasicTypeEnum<'ctx>,
llvm_usize: IntType<'ctx>,
) -> Self {
debug_assert!(Self::is_representable(ptr_ty, llvm_usize).is_ok());
NDArrayType { ty: ptr_ty, llvm_usize }
NDArrayType { ty: ptr_ty, dtype, ndims: None, llvm_usize }
}
/// Returns the type of the `size` field of this `ndarray` type.
@ -115,21 +201,123 @@ impl<'ctx> NDArrayType<'ctx> {
self.as_base_type()
.get_element_type()
.into_struct_type()
.get_field_type_at_index(0)
.get_field_type_at_index(1)
.map(BasicTypeEnum::into_int_type)
.unwrap()
}
/// Returns the element type of this `ndarray` type.
#[must_use]
pub fn element_type(&self) -> AnyTypeEnum<'ctx> {
self.as_base_type()
.get_element_type()
.into_struct_type()
.get_field_type_at_index(2)
.map(BasicTypeEnum::into_pointer_type)
.map(PointerType::get_element_type)
.unwrap()
pub fn element_type(&self) -> BasicTypeEnum<'ctx> {
self.dtype
}
/// Returns the number of dimensions represented by this [`NDArrayType`], or [`None`] if it is
/// not known.
#[must_use]
pub fn ndims_as_value(&self) -> Option<IntValue<'ctx>> {
self.ndims.map(|ndims| self.llvm_usize.const_int(ndims, false))
}
/// Allocate an ndarray on the stack given its `ndims` and `dtype`.
///
/// `shape` and `strides` will be automatically allocated onto the stack.
///
/// The returned ndarray's content will be:
/// - `data`: uninitialized.
/// - `itemsize`: set to the `sizeof()` of `dtype`.
/// - `ndims`: set to the value of `ndims`.
/// - `shape`: allocated with an array of length `ndims` with uninitialized values.
/// - `strides`: allocated with an array of length `ndims` with uninitialized values.
#[must_use]
pub fn construct_uninitialized<G: CodeGenerator + ?Sized>(
&self,
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
ndims: Option<u64>,
name: Option<&'ctx str>,
) -> <Self as ProxyType<'ctx>>::Value {
let ndarray = self.new_value(generator, ctx, name);
let itemsize = ctx
.builder
.build_int_z_extend_or_bit_cast(self.dtype.size_of().unwrap(), self.llvm_usize, "")
.unwrap();
ndarray.store_itemsize(ctx, generator, itemsize);
let ndims_val = self.llvm_usize.const_int(ndims.or(self.ndims).unwrap(), false);
ndarray.store_ndims(ctx, generator, ndims_val);
ndarray.create_shape(ctx, self.llvm_usize, ndims_val);
ndarray.create_strides(ctx, self.llvm_usize, ndims_val);
ndarray
}
/// Convenience function. Allocate an [`NDArrayObject`] with a statically known shape.
///
/// The returned [`NDArrayObject`]'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 {
let ndarray = self.construct_uninitialized(generator, ctx, Some(shape.len() as u64), name);
// Write shape
let ndarray_shape = ndarray.shape();
for (i, dim) in shape.iter().enumerate() {
let dim = self.llvm_usize.const_int(*dim, false);
unsafe {
ndarray_shape.set_typed_unchecked(
ctx,
generator,
&self.llvm_usize.const_int(i as u64, false),
dim,
);
}
}
ndarray
}
/// Convenience function. Allocate an [`NDArrayObject`] with a dynamically known shape.
///
/// The returned [`NDArrayObject`]'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 {
let ndarray = self.construct_uninitialized(generator, ctx, Some(shape.len() as u64), name);
// Write shape
let ndarray_shape = ndarray.shape();
for (i, dim) in shape.iter().enumerate() {
assert_eq!(
dim.get_type(),
self.llvm_usize,
"Expected {} but got {}",
self.llvm_usize.print_to_string(),
dim.get_type().print_to_string()
);
unsafe {
ndarray_shape.set_typed_unchecked(
ctx,
generator,
&self.llvm_usize.const_int(i as u64, false),
*dim,
);
}
}
ndarray
}
}
@ -199,7 +387,7 @@ impl<'ctx> ProxyType<'ctx> for NDArrayType<'ctx> {
) -> Self::Value {
debug_assert_eq!(value.get_type(), self.as_base_type());
NDArrayValue::from_pointer_value(value, self.llvm_usize, name)
NDArrayValue::from_pointer_value(value, self.dtype, self.ndims, self.llvm_usize, name)
}
fn as_base_type(&self) -> Self::Base {

View File

@ -47,11 +47,18 @@ impl<'ctx> RangeType<'ctx> {
Ok(())
}
/// Creates an LLVM type corresponding to the expected structure of a `Range`.
#[must_use]
fn llvm_type(ctx: &'ctx Context) -> PointerType<'ctx> {
// typedef int32_t Range[3];
let llvm_i32 = ctx.i32_type();
llvm_i32.array_type(3).ptr_type(AddressSpace::default())
}
/// Creates an instance of [`RangeType`].
#[must_use]
pub fn new(ctx: &'ctx Context) -> Self {
let llvm_i32 = ctx.i32_type();
let llvm_range = llvm_i32.array_type(3).ptr_type(AddressSpace::default());
let llvm_range = Self::llvm_type(ctx);
RangeType::from_type(llvm_range)
}

View File

@ -0,0 +1,207 @@
use std::marker::PhantomData;
use inkwell::{
context::AsContextRef,
types::{BasicTypeEnum, IntType},
values::{BasicValue, BasicValueEnum, IntValue, PointerValue, StructValue},
};
use crate::codegen::CodeGenContext;
/// Trait indicating that the structure is a field-wise representation of an LLVM structure.
///
/// # Usage
///
/// For example, for a simple C-slice LLVM structure:
///
/// ```ignore
/// struct CSliceFields<'ctx> {
/// ptr: StructField<'ctx, PointerValue<'ctx>>,
/// len: StructField<'ctx, IntValue<'ctx>>
/// }
/// ```
pub trait StructFields<'ctx>: Eq + Copy {
/// Creates an instance of [`StructFields`] using the given `ctx` and `size_t` types.
fn new(ctx: impl AsContextRef<'ctx>, llvm_usize: IntType<'ctx>) -> Self;
/// Returns a [`Vec`] that contains the fields of the structure in the order as they appear in
/// the type definition.
#[must_use]
fn to_vec(&self) -> Vec<(&'static str, BasicTypeEnum<'ctx>)>;
/// Returns a [`Iterator`] that contains the fields of the structure in the order as they appear
/// in the type definition.
#[must_use]
fn iter(&self) -> impl Iterator<Item = (&'static str, BasicTypeEnum<'ctx>)> {
self.to_vec().into_iter()
}
/// Returns a [`Vec`] that contains the fields of the structure in the order as they appear in
/// the type definition.
#[must_use]
fn into_vec(self) -> Vec<(&'static str, BasicTypeEnum<'ctx>)>
where
Self: Sized,
{
self.to_vec()
}
/// Returns a [`Iterator`] that contains the fields of the structure in the order as they appear
/// in the type definition.
#[must_use]
fn into_iter(self) -> impl Iterator<Item = (&'static str, BasicTypeEnum<'ctx>)>
where
Self: Sized,
{
self.into_vec().into_iter()
}
}
/// A single field of an LLVM structure.
#[derive(Debug, PartialEq, Eq, Clone, Copy)]
pub struct StructField<'ctx, Value>
where
Value: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>, Error = ()>,
{
/// The index of this field within the structure.
index: u32,
/// The name of this field.
name: &'static str,
/// The type of this field.
ty: BasicTypeEnum<'ctx>,
/// Instance of [`PhantomData`] containing [`Value`], used to implement automatic downcasts.
_value_ty: PhantomData<Value>,
}
impl<'ctx, Value> StructField<'ctx, Value>
where
Value: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>, Error = ()>,
{
/// Creates an instance of [`StructField`].
///
/// * `idx_counter` - The instance of [`FieldIndexCounter`] used to track the current field
/// index.
/// * `name` - Name of the field.
/// * `ty` - The type of this field.
pub(super) fn create(
idx_counter: &mut FieldIndexCounter,
name: &'static str,
ty: impl Into<BasicTypeEnum<'ctx>>,
) -> Self {
StructField { index: idx_counter.increment(), name, ty: ty.into(), _value_ty: PhantomData }
}
/// Creates an instance of [`StructField`] with a given index.
///
/// * `index` - The index of this field within its enclosing structure.
/// * `name` - Name of the field.
/// * `ty` - The type of this field.
pub(super) fn create_at(
index: u32,
name: &'static str,
ty: impl Into<BasicTypeEnum<'ctx>>,
) -> Self {
StructField { index, name, ty: ty.into(), _value_ty: PhantomData }
}
/// Creates a pointer to this field in an arbitrary structure by performing a `getelementptr i32
/// {idx...}, i32 {self.index}`.
pub fn ptr_by_array_gep(
&self,
ctx: &CodeGenContext<'ctx, '_>,
pobj: PointerValue<'ctx>,
idx: &[IntValue<'ctx>],
) -> PointerValue<'ctx> {
unsafe {
ctx.builder.build_in_bounds_gep(
pobj,
&[idx, &[ctx.ctx.i32_type().const_int(u64::from(self.index), false)]].concat(),
"",
)
}
.unwrap()
}
/// Creates a pointer to this field in an arbitrary structure by performing the equivalent of
/// `getelementptr i32 0, i32 {self.index}`.
pub fn ptr_by_gep(
&self,
ctx: &CodeGenContext<'ctx, '_>,
pobj: PointerValue<'ctx>,
obj_name: Option<&'ctx str>,
) -> PointerValue<'ctx> {
ctx.builder
.build_struct_gep(
pobj,
self.index,
&obj_name.map(|name| format!("{name}.{}.addr", self.name)).unwrap_or_default(),
)
.unwrap()
}
/// Gets the value of this field for a given `obj`.
#[must_use]
pub fn get_from_value(&self, obj: StructValue<'ctx>) -> Value {
obj.get_field_at_index(self.index).and_then(|value| Value::try_from(value).ok()).unwrap()
}
/// Sets the value of this field for a given `obj`.
pub fn set_from_value(&self, obj: StructValue<'ctx>, value: Value) {
obj.set_field_at_index(self.index, value);
}
/// Gets the value of this field for a pointer-to-structure.
pub fn get(
&self,
ctx: &CodeGenContext<'ctx, '_>,
pobj: PointerValue<'ctx>,
obj_name: Option<&'ctx str>,
) -> Value {
ctx.builder
.build_load(
self.ptr_by_gep(ctx, pobj, obj_name),
&obj_name.map(|name| format!("{name}.{}", self.name)).unwrap_or_default(),
)
.map_err(|_| ())
.and_then(|value| Value::try_from(value))
.unwrap()
}
/// Sets the value of this field for a pointer-to-structure.
pub fn set(
&self,
ctx: &CodeGenContext<'ctx, '_>,
pobj: PointerValue<'ctx>,
value: Value,
obj_name: Option<&'ctx str>,
) {
ctx.builder.build_store(self.ptr_by_gep(ctx, pobj, obj_name), value).unwrap();
}
}
impl<'ctx, Value> From<StructField<'ctx, Value>> for (&'static str, BasicTypeEnum<'ctx>)
where
Value: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>, Error = ()>,
{
fn from(value: StructField<'ctx, Value>) -> Self {
(value.name, value.ty)
}
}
/// A counter that tracks the next index of a field using a monotonically increasing counter.
#[derive(Default, Debug, PartialEq, Eq, Clone, Copy)]
pub(super) struct FieldIndexCounter(u32);
impl FieldIndexCounter {
/// Increments the number stored by this counter, returning the previous value.
///
/// Functionally equivalent to `i++` in C-based languages.
pub fn increment(&mut self) -> u32 {
let v = self.0;
self.0 += 1;
v
}
}

View File

@ -1,7 +1,7 @@
use inkwell::{
types::{AnyTypeEnum, BasicTypeEnum, IntType},
types::{AnyType, AnyTypeEnum, BasicType, BasicTypeEnum, IntType},
values::{BasicValueEnum, IntValue, PointerValue},
IntPredicate,
AddressSpace, IntPredicate,
};
use super::{
@ -20,6 +20,8 @@ use crate::codegen::{
#[derive(Copy, Clone)]
pub struct NDArrayValue<'ctx> {
value: PointerValue<'ctx>,
dtype: BasicTypeEnum<'ctx>,
ndims: Option<u64>,
llvm_usize: IntType<'ctx>,
name: Option<&'ctx str>,
}
@ -38,28 +40,22 @@ impl<'ctx> NDArrayValue<'ctx> {
#[must_use]
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, llvm_usize, name }
NDArrayValue { value: ptr, dtype, ndims, llvm_usize, name }
}
/// Returns the pointer to the field storing the number of dimensions of this `NDArray`.
fn ptr_to_ndims(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
let llvm_i32 = ctx.ctx.i32_type();
let var_name = self.name.map(|v| format!("{v}.ndims.addr")).unwrap_or_default();
unsafe {
ctx.builder
.build_in_bounds_gep(
self.as_base_value(),
&[llvm_i32.const_zero(), llvm_i32.const_zero()],
var_name.as_str(),
)
.unwrap()
}
self.get_type()
.get_fields(ctx.ctx, self.llvm_usize)
.ndims
.ptr_by_gep(ctx, self.value, self.name)
}
/// Stores the number of dimensions `ndims` into this instance.
@ -81,63 +77,108 @@ impl<'ctx> NDArrayValue<'ctx> {
ctx.builder.build_load(pndims, "").map(BasicValueEnum::into_int_value).unwrap()
}
/// Returns the double-indirection pointer to the `dims` array, as if by calling `getelementptr`
/// on the field.
fn ptr_to_dims(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
let llvm_i32 = ctx.ctx.i32_type();
let var_name = self.name.map(|v| format!("{v}.dims.addr")).unwrap_or_default();
/// Returns the pointer to the field storing the size of each element of this `NDArray`.
fn ptr_to_itemsize(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
self.get_type()
.get_fields(ctx.ctx, self.llvm_usize)
.itemsize
.ptr_by_gep(ctx, self.value, self.name)
}
unsafe {
ctx.builder
.build_in_bounds_gep(
self.as_base_value(),
&[llvm_i32.const_zero(), llvm_i32.const_int(1, true)],
var_name.as_str(),
)
.unwrap()
}
/// Stores the size of each element `itemsize` into this instance.
pub fn store_itemsize<G: CodeGenerator + ?Sized>(
&self,
ctx: &CodeGenContext<'ctx, '_>,
generator: &G,
ndims: IntValue<'ctx>,
) {
debug_assert_eq!(ndims.get_type(), generator.get_size_type(ctx.ctx));
let pndims = self.ptr_to_ndims(ctx);
ctx.builder.build_store(pndims, ndims).unwrap();
}
/// Returns the size of each element of this `NDArray` as a value.
pub fn load_itemsize(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
let pndims = self.ptr_to_ndims(ctx);
ctx.builder.build_load(pndims, "").map(BasicValueEnum::into_int_value).unwrap()
}
/// Returns the double-indirection pointer to the `shape` array, as if by calling
/// `getelementptr` on the field.
fn ptr_to_shape(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
self.get_type()
.get_fields(ctx.ctx, self.llvm_usize)
.shape
.ptr_by_gep(ctx, self.value, self.name)
}
/// Stores the array of dimension sizes `dims` into this instance.
fn store_dim_sizes(&self, ctx: &CodeGenContext<'ctx, '_>, dims: PointerValue<'ctx>) {
ctx.builder.build_store(self.ptr_to_dims(ctx), dims).unwrap();
fn store_shape(&self, ctx: &CodeGenContext<'ctx, '_>, dims: PointerValue<'ctx>) {
ctx.builder.build_store(self.ptr_to_shape(ctx), dims).unwrap();
}
/// Convenience method for creating a new array storing dimension sizes with the given `size`.
pub fn create_dim_sizes(
pub fn create_shape(
&self,
ctx: &CodeGenContext<'ctx, '_>,
llvm_usize: IntType<'ctx>,
size: IntValue<'ctx>,
) {
self.store_dim_sizes(ctx, ctx.builder.build_array_alloca(llvm_usize, size, "").unwrap());
self.store_shape(ctx, ctx.builder.build_array_alloca(llvm_usize, size, "").unwrap());
}
/// Returns a proxy object to the field storing the size of each dimension of this `NDArray`.
#[must_use]
pub fn dim_sizes(&self) -> NDArrayDimsProxy<'ctx, '_> {
NDArrayDimsProxy(self)
pub fn shape(&self) -> NDArrayShapeProxy<'ctx, '_> {
NDArrayShapeProxy(self)
}
/// Returns the double-indirection pointer to the `stride` array, as if by calling
/// `getelementptr` on the field.
fn ptr_to_strides(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
self.get_type()
.get_fields(ctx.ctx, self.llvm_usize)
.strides
.ptr_by_gep(ctx, self.value, self.name)
}
/// Stores the array of dimension sizes `dims` into this instance.
fn store_strides(&self, ctx: &CodeGenContext<'ctx, '_>, dims: PointerValue<'ctx>) {
ctx.builder.build_store(self.ptr_to_shape(ctx), dims).unwrap();
}
/// 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_shape(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)
}
/// Returns the double-indirection pointer to the `data` array, as if by calling `getelementptr`
/// on the field.
pub fn ptr_to_data(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
let llvm_i32 = ctx.ctx.i32_type();
let var_name = self.name.map(|v| format!("{v}.data.addr")).unwrap_or_default();
unsafe {
ctx.builder
.build_in_bounds_gep(
self.as_base_value(),
&[llvm_i32.const_zero(), llvm_i32.const_int(2, true)],
var_name.as_str(),
)
.unwrap()
}
self.get_type()
.get_fields(ctx.ctx, self.llvm_usize)
.data
.ptr_by_gep(ctx, self.value, self.name)
}
/// Stores the array of data elements `data` into this instance.
fn store_data(&self, ctx: &CodeGenContext<'ctx, '_>, data: PointerValue<'ctx>) {
let data = ctx
.builder
.build_bit_cast(data, ctx.ctx.i8_type().ptr_type(AddressSpace::default()), "")
.unwrap();
ctx.builder.build_store(self.ptr_to_data(ctx), data).unwrap();
}
@ -149,7 +190,15 @@ impl<'ctx> NDArrayValue<'ctx> {
elem_ty: BasicTypeEnum<'ctx>,
size: IntValue<'ctx>,
) {
self.store_data(ctx, ctx.builder.build_array_alloca(elem_ty, size, "").unwrap());
let itemsize =
ctx.builder.build_int_cast(elem_ty.size_of().unwrap(), size.get_type(), "").unwrap();
let nbytes = ctx.builder.build_int_mul(size, itemsize, "").unwrap();
// 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`.
@ -164,7 +213,7 @@ 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.llvm_usize)
NDArrayType::from_type(self.as_base_value().get_type(), self.dtype, self.llvm_usize)
}
fn as_base_value(&self) -> Self::Base {
@ -178,103 +227,6 @@ impl<'ctx> From<NDArrayValue<'ctx>> for PointerValue<'ctx> {
}
}
/// Proxy type for accessing the `dims` array of an `NDArray` instance in LLVM.
#[derive(Copy, Clone)]
pub struct NDArrayDimsProxy<'ctx, 'a>(&'a NDArrayValue<'ctx>);
impl<'ctx> ArrayLikeValue<'ctx> for NDArrayDimsProxy<'ctx, '_> {
fn element_type<G: CodeGenerator + ?Sized>(
&self,
ctx: &CodeGenContext<'ctx, '_>,
generator: &G,
) -> AnyTypeEnum<'ctx> {
self.0.dim_sizes().base_ptr(ctx, generator).get_type().get_element_type()
}
fn base_ptr<G: CodeGenerator + ?Sized>(
&self,
ctx: &CodeGenContext<'ctx, '_>,
_: &G,
) -> PointerValue<'ctx> {
let var_name = self.0.name.map(|v| format!("{v}.data")).unwrap_or_default();
ctx.builder
.build_load(self.0.ptr_to_dims(ctx), var_name.as_str())
.map(BasicValueEnum::into_pointer_value)
.unwrap()
}
fn size<G: CodeGenerator + ?Sized>(
&self,
ctx: &CodeGenContext<'ctx, '_>,
_: &G,
) -> IntValue<'ctx> {
self.0.load_ndims(ctx)
}
}
impl<'ctx> ArrayLikeIndexer<'ctx, IntValue<'ctx>> for NDArrayDimsProxy<'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 NDArrayDimsProxy<'ctx, '_> {}
impl<'ctx> UntypedArrayLikeMutator<'ctx, IntValue<'ctx>> for NDArrayDimsProxy<'ctx, '_> {}
impl<'ctx> TypedArrayLikeAccessor<'ctx, IntValue<'ctx>> for NDArrayDimsProxy<'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 NDArrayDimsProxy<'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>);
@ -282,10 +234,10 @@ pub struct NDArrayDataProxy<'ctx, 'a>(&'a NDArrayValue<'ctx>);
impl<'ctx> ArrayLikeValue<'ctx> for NDArrayDataProxy<'ctx, '_> {
fn element_type<G: CodeGenerator + ?Sized>(
&self,
ctx: &CodeGenContext<'ctx, '_>,
generator: &G,
_: &CodeGenContext<'ctx, '_>,
_: &G,
) -> AnyTypeEnum<'ctx> {
self.0.data().base_ptr(ctx, generator).get_type().get_element_type()
self.0.dtype.as_any_type_enum()
}
fn base_ptr<G: CodeGenerator + ?Sized>(
@ -318,15 +270,34 @@ impl<'ctx> ArrayLikeIndexer<'ctx> for NDArrayDataProxy<'ctx, '_> {
idx: &IntValue<'ctx>,
name: Option<&str>,
) -> PointerValue<'ctx> {
unsafe {
let sizeof_elem = ctx
.builder
.build_int_truncate_or_bit_cast(
self.element_type(ctx, generator).size_of().unwrap(),
idx.get_type(),
"",
)
.unwrap();
let idx = ctx.builder.build_int_mul(*idx, sizeof_elem, "").unwrap();
let ptr = unsafe {
ctx.builder
.build_in_bounds_gep(
self.base_ptr(ctx, generator),
&[*idx],
&[idx],
name.unwrap_or_default(),
)
.unwrap()
}
};
// TODO: Current implementation is transparent
ctx.builder
.build_pointer_cast(
ptr,
BasicTypeEnum::try_from(self.element_type(ctx, generator))
.unwrap()
.ptr_type(AddressSpace::default()),
"",
)
.unwrap()
}
fn ptr_offset<G: CodeGenerator + ?Sized>(
@ -347,7 +318,17 @@ impl<'ctx> ArrayLikeIndexer<'ctx> for NDArrayDataProxy<'ctx, '_> {
ctx.current_loc,
);
unsafe { self.ptr_offset_unchecked(ctx, generator, idx, name) }
let ptr = unsafe { self.ptr_offset_unchecked(ctx, generator, idx, name) };
// TODO: Current implementation is transparent
ctx.builder
.build_pointer_cast(
ptr,
BasicTypeEnum::try_from(self.element_type(ctx, generator))
.unwrap()
.ptr_type(AddressSpace::default()),
"",
)
.unwrap()
}
}
@ -381,8 +362,17 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
);
let index = call_ndarray_flatten_index(generator, ctx, *self.0, indices);
let sizeof_elem = ctx
.builder
.build_int_truncate_or_bit_cast(
self.element_type(ctx, generator).size_of().unwrap(),
index.get_type(),
"",
)
.unwrap();
let index = ctx.builder.build_int_mul(index, sizeof_elem, "").unwrap();
unsafe {
let ptr = unsafe {
ctx.builder
.build_in_bounds_gep(
self.base_ptr(ctx, generator),
@ -390,7 +380,17 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
name.unwrap_or_default(),
)
.unwrap()
}
};
// TODO: Current implementation is transparent
ctx.builder
.build_pointer_cast(
ptr,
BasicTypeEnum::try_from(self.element_type(ctx, generator))
.unwrap()
.ptr_type(AddressSpace::default()),
"",
)
.unwrap()
}
fn ptr_offset<G: CodeGenerator + ?Sized>(
@ -429,7 +429,7 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
let (dim_idx, dim_sz) = unsafe {
(
indices.get_unchecked(ctx, generator, &i, None).into_int_value(),
self.0.dim_sizes().get_typed_unchecked(ctx, generator, &i, None),
self.0.shape().get_typed_unchecked(ctx, generator, &i, None),
)
};
let dim_idx = ctx
@ -455,7 +455,17 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
)
.unwrap();
unsafe { self.ptr_offset_unchecked(ctx, generator, indices, name) }
let ptr = unsafe { self.ptr_offset_unchecked(ctx, generator, indices, name) };
// TODO: Current implementation is transparent
ctx.builder
.build_pointer_cast(
ptr,
BasicTypeEnum::try_from(self.element_type(ctx, generator))
.unwrap()
.ptr_type(AddressSpace::default()),
"",
)
.unwrap()
}
}
@ -467,3 +477,197 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> UntypedArrayLikeMutator<'ctx,
for NDArrayDataProxy<'ctx, '_>
{
}
/// Proxy type for accessing the `dims` array of an `NDArray` instance in LLVM.
#[derive(Copy, Clone)]
pub struct NDArrayShapeProxy<'ctx, 'a>(&'a NDArrayValue<'ctx>);
impl<'ctx> ArrayLikeValue<'ctx> for NDArrayShapeProxy<'ctx, '_> {
fn element_type<G: CodeGenerator + ?Sized>(
&self,
ctx: &CodeGenContext<'ctx, '_>,
generator: &G,
) -> AnyTypeEnum<'ctx> {
self.0.shape().base_ptr(ctx, generator).get_type().get_element_type()
}
fn base_ptr<G: CodeGenerator + ?Sized>(
&self,
ctx: &CodeGenContext<'ctx, '_>,
_: &G,
) -> PointerValue<'ctx> {
let var_name = self.0.name.map(|v| format!("{v}.data")).unwrap_or_default();
ctx.builder
.build_load(self.0.ptr_to_shape(ctx), var_name.as_str())
.map(BasicValueEnum::into_pointer_value)
.unwrap()
}
fn size<G: CodeGenerator + ?Sized>(
&self,
ctx: &CodeGenContext<'ctx, '_>,
_: &G,
) -> IntValue<'ctx> {
self.0.load_ndims(ctx)
}
}
impl<'ctx> ArrayLikeIndexer<'ctx, IntValue<'ctx>> for NDArrayShapeProxy<'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 NDArrayShapeProxy<'ctx, '_> {}
impl<'ctx> UntypedArrayLikeMutator<'ctx, IntValue<'ctx>> for NDArrayShapeProxy<'ctx, '_> {}
impl<'ctx> TypedArrayLikeAccessor<'ctx, IntValue<'ctx>> for NDArrayShapeProxy<'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 NDArrayShapeProxy<'ctx, '_> {
fn upcast_from_type(
&self,
_: &mut CodeGenContext<'ctx, '_>,
value: IntValue<'ctx>,
) -> BasicValueEnum<'ctx> {
value.into()
}
}
/// Proxy type for accessing the `dims` 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.shape().base_ptr(ctx, generator).get_type().get_element_type()
}
fn base_ptr<G: CodeGenerator + ?Sized>(
&self,
ctx: &CodeGenContext<'ctx, '_>,
_: &G,
) -> PointerValue<'ctx> {
let var_name = self.0.name.map(|v| format!("{v}.data")).unwrap_or_default();
ctx.builder
.build_load(self.0.ptr_to_shape(ctx), var_name.as_str())
.map(BasicValueEnum::into_pointer_value)
.unwrap()
}
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()
}
}

View File

@ -1134,3 +1134,23 @@ pub fn arraylike_get_ndims(unifier: &mut Unifier, ty: Type) -> u64 {
_ => 0,
}
}
/// Extract an ndarray's `ndims` [type][`Type`] in `u64`. Panic if not possible.
/// The `ndims` must only contain 1 value.
#[must_use]
pub fn extract_ndims(unifier: &Unifier, ndims_ty: Type) -> u64 {
let ndims_ty_enum = unifier.get_ty_immutable(ndims_ty);
let TypeEnum::TLiteral { values, .. } = &*ndims_ty_enum else {
panic!("ndims_ty should be a TLiteral");
};
assert_eq!(values.len(), 1, "ndims_ty TLiteral should only contain 1 value");
let ndims = values[0].clone();
u64::try_from(ndims).unwrap()
}
/// Return an ndarray's `ndims` as a typechecker [`Type`] from its `u64` value.
pub fn create_ndims(unifier: &mut Unifier, ndims: u64) -> Type {
unifier.get_fresh_literal(vec![SymbolValue::U64(ndims)], None)
}

View File

@ -144,6 +144,7 @@ def test_ndarray_array():
# Copy
n2_cpy: ndarray[float, 2] = np_array(n2, copy=False)
output_ndarray_float_2(n2_cpy)
n2_cpy.fill(0.0)
output_ndarray_float_2(n2_cpy)
@ -1756,16 +1757,16 @@ def run() -> int32:
test_ndarray_nextafter_broadcast_rhs_scalar()
test_ndarray_transpose()
test_ndarray_reshape()
test_ndarray_dot()
test_ndarray_cholesky()
test_ndarray_qr()
test_ndarray_svd()
test_ndarray_linalg_inv()
test_ndarray_pinv()
test_ndarray_matrix_power()
test_ndarray_det()
test_ndarray_lu()
test_ndarray_schur()
test_ndarray_hessenberg()
# test_ndarray_cholesky()
# test_ndarray_qr()
# test_ndarray_svd()
# test_ndarray_linalg_inv()
# test_ndarray_pinv()
# test_ndarray_matrix_power()
# test_ndarray_det()
# test_ndarray_lu()
# test_ndarray_schur()
# test_ndarray_hessenberg()
return 0