forked from M-Labs/nac3
core/numpy: Implement ndarray_sliced_{copy,copyto_impl}
Performing copying with optional support for slicing. Also made copy_impl delegate to sliced_copy, as sliced_copy now performs a superset of operations that copy_impl can already do.
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a176c3eb70
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135ef557f9
@ -9,6 +9,7 @@ use crate::{
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NDArrayValue,
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TypedArrayLikeAccessor,
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TypedArrayLikeAdapter,
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TypedArrayLikeMutator,
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UntypedArrayLikeAccessor,
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UntypedArrayLikeMutator,
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},
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@ -16,6 +17,7 @@ use crate::{
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CodeGenerator,
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expr::gen_binop_expr_with_values,
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irrt::{
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calculate_len_for_slice_range,
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call_ndarray_calc_broadcast,
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call_ndarray_calc_broadcast_index,
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call_ndarray_calc_nd_indices,
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@ -23,7 +25,7 @@ use crate::{
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},
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llvm_intrinsics,
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llvm_intrinsics::{call_memcpy_generic},
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stmt::{gen_for_callback_incrementing, gen_if_else_expr_callback},
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stmt::{gen_for_callback_incrementing, gen_for_range_callback, gen_if_else_expr_callback},
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},
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symbol_resolver::ValueEnum,
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toplevel::{
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@ -645,6 +647,240 @@ fn call_ndarray_eye_impl<'ctx, G: CodeGenerator + ?Sized>(
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Ok(ndarray)
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}
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/// Copies a slice of an [`NDArrayValue`] to another.
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///
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/// - `dst_arr`: The [`NDArrayValue`] instance of the destination array. The `ndims` and `dim_sz`
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/// fields should be populated before calling this function.
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/// - `dst_slice_ptr`: The [`PointerValue`] to the first element of the currently processing
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/// dimensional slice in the destination array.
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/// - `src_arr`: The [`NDArrayValue`] instance of the source array.
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/// - `src_slice_ptr`: The [`PointerValue`] to the first element of the currently processing
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/// dimensional slice in the source array.
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/// - `dim`: The index of the currently processing dimension.
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/// - `slices`: List of all slices, with the first element corresponding to the slice applicable to
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/// this dimension. The `start`/`stop` values of each slice must be non-negative indices.
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fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
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generator: &mut G,
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ctx: &mut CodeGenContext<'ctx, '_>,
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elem_ty: Type,
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(dst_arr, dst_slice_ptr): (NDArrayValue<'ctx>, PointerValue<'ctx>),
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(src_arr, src_slice_ptr): (NDArrayValue<'ctx>, PointerValue<'ctx>),
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dim: u64,
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slices: &[(IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>)],
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) -> Result<(), String> {
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let llvm_i1 = ctx.ctx.bool_type();
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let llvm_usize = generator.get_size_type(ctx.ctx);
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// If there are no (remaining) slice expressions, memcpy the entire dimension
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if slices.is_empty() {
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let stride = call_ndarray_calc_size(
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generator,
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ctx,
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&src_arr.dim_sizes(),
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(Some(llvm_usize.const_int(dim, false)), None),
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);
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let sizeof_elem = ctx.get_llvm_type(generator, elem_ty).size_of().unwrap();
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let cpy_len = ctx.builder.build_int_mul(
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stride,
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sizeof_elem,
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""
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).unwrap();
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call_memcpy_generic(
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ctx,
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dst_slice_ptr,
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src_slice_ptr,
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cpy_len,
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llvm_i1.const_zero(),
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);
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return Ok(())
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}
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// The stride of elements in this dimension, i.e. the number of elements between arr[i] and
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// arr[i + 1] in this dimension
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let src_stride = call_ndarray_calc_size(
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generator,
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ctx,
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&src_arr.dim_sizes(),
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(Some(llvm_usize.const_int(dim + 1, false)), None),
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);
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let dst_stride = call_ndarray_calc_size(
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generator,
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ctx,
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&dst_arr.dim_sizes(),
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(Some(llvm_usize.const_int(dim + 1, false)), None),
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);
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let (start, stop, step) = slices[0];
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let start = ctx.builder.build_int_s_extend_or_bit_cast(start, llvm_usize, "").unwrap();
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let stop = ctx.builder.build_int_s_extend_or_bit_cast(stop, llvm_usize, "").unwrap();
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let step = ctx.builder.build_int_s_extend_or_bit_cast(step, llvm_usize, "").unwrap();
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let dst_i_addr = generator.gen_var_alloc(ctx, start.get_type().into(), None).unwrap();
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ctx.builder.build_store(dst_i_addr, start.get_type().const_zero()).unwrap();
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gen_for_range_callback(
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generator,
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ctx,
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false,
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|_, _| Ok(start),
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(|_, _| Ok(stop), true),
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|_, _| Ok(step),
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|generator, ctx, src_i| {
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// Calculate the offset of the active slice
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let src_data_offset = ctx.builder.build_int_mul(
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src_stride,
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src_i,
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"",
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).unwrap();
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let dst_i = ctx.builder
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.build_load(dst_i_addr, "")
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.map(BasicValueEnum::into_int_value)
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.unwrap();
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let dst_data_offset = ctx.builder.build_int_mul(
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dst_stride,
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dst_i,
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"",
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).unwrap();
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let (src_ptr, dst_ptr) = unsafe {
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(
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ctx.builder.build_gep(src_slice_ptr, &[src_data_offset], "").unwrap(),
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ctx.builder.build_gep(dst_slice_ptr, &[dst_data_offset], "").unwrap(),
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)
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};
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ndarray_sliced_copyto_impl(
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generator,
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ctx,
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elem_ty,
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(dst_arr, dst_ptr),
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(src_arr, src_ptr),
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dim + 1,
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&slices[1..],
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)?;
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let dst_i = ctx.builder
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.build_load(dst_i_addr, "")
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.map(BasicValueEnum::into_int_value)
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.unwrap();
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let dst_i_add1 = ctx.builder
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.build_int_add(dst_i, llvm_usize.const_int(1, false), "")
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.unwrap();
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ctx.builder.build_store(dst_i_addr, dst_i_add1).unwrap();
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Ok(())
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},
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)?;
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Ok(())
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}
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/// Copies a [`NDArrayValue`] using slices.
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///
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/// * `elem_ty` - The element type of the `NDArray`.
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/// - `slices`: List of all slices, with the first element corresponding to the slice applicable to
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/// this dimension. The `start`/`stop` values of each slice must be positive indices.
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pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
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generator: &mut G,
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ctx: &mut CodeGenContext<'ctx, '_>,
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elem_ty: Type,
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this: NDArrayValue<'ctx>,
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slices: &[(IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>)],
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) -> Result<NDArrayValue<'ctx>, String> {
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let llvm_i32 = ctx.ctx.i32_type();
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let llvm_usize = generator.get_size_type(ctx.ctx);
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let ndarray = if slices.is_empty() {
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create_ndarray_dyn_shape(
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generator,
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ctx,
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elem_ty,
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&this,
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|_, ctx, shape| {
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Ok(shape.load_ndims(ctx))
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},
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|generator, ctx, shape, idx| {
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unsafe { Ok(shape.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None)) }
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},
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)?
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} else {
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let ndarray = create_ndarray_uninitialized(generator, ctx, elem_ty)?;
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ndarray.store_ndims(ctx, generator, this.load_ndims(ctx));
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let ndims = this.load_ndims(ctx);
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ndarray.create_dim_sizes(ctx, llvm_usize, ndims);
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// Populate the first slices.len() dimensions by computing the size of each dim slice
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for (i, (start, stop, step)) in slices.iter().enumerate() {
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// HACK: workaround calculate_len_for_slice_range requiring exclusive stop
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let stop = ctx.builder
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.build_select(
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ctx.builder.build_int_compare(
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IntPredicate::SLT,
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*step,
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llvm_i32.const_zero(),
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"is_neg",
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).unwrap(),
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ctx.builder.build_int_sub(*stop, llvm_i32.const_int(1, true), "e_min_one").unwrap(),
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ctx.builder.build_int_add(*stop, llvm_i32.const_int(1, true), "e_add_one").unwrap(),
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"final_e",
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)
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.map(BasicValueEnum::into_int_value)
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.unwrap();
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let slice_len = calculate_len_for_slice_range(generator, ctx, *start, stop, *step);
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let slice_len = ctx.builder.build_int_z_extend_or_bit_cast(
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slice_len,
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llvm_usize,
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""
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).unwrap();
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unsafe {
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ndarray.dim_sizes()
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.set_typed_unchecked(
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ctx,
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generator,
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&llvm_usize.const_int(i as u64, false),
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slice_len,
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);
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}
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}
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// Populate the rest by directly copying the dim size from the source array
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gen_for_callback_incrementing(
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generator,
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ctx,
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llvm_usize.const_int(slices.len() as u64, false),
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(this.load_ndims(ctx), false),
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|generator, ctx, idx| {
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unsafe {
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let dim_sz = this.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None);
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ndarray.dim_sizes().set_typed_unchecked(ctx, generator, &idx, dim_sz);
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}
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Ok(())
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},
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llvm_usize.const_int(1, false),
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).unwrap();
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ndarray_init_data(generator, ctx, elem_ty, ndarray)
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};
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ndarray_sliced_copyto_impl(
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generator,
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ctx,
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elem_ty,
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(ndarray, ndarray.data().base_ptr(ctx, generator)),
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(this, this.data().base_ptr(ctx, generator)),
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0,
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slices,
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)?;
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Ok(ndarray)
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}
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/// LLVM-typed implementation for generating the implementation for `ndarray.copy`.
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///
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/// * `elem_ty` - The element type of the `NDArray`.
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@ -654,45 +890,7 @@ fn ndarray_copy_impl<'ctx, G: CodeGenerator + ?Sized>(
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elem_ty: Type,
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this: NDArrayValue<'ctx>,
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) -> Result<NDArrayValue<'ctx>, String> {
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let llvm_i1 = ctx.ctx.bool_type();
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let ndarray = create_ndarray_dyn_shape(
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generator,
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ctx,
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elem_ty,
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&this,
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|_, ctx, shape| {
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Ok(shape.load_ndims(ctx))
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},
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|generator, ctx, shape, idx| {
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unsafe { Ok(shape.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None)) }
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},
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)?;
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let len = call_ndarray_calc_size(
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generator,
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ctx,
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&ndarray.dim_sizes().as_slice_value(ctx, generator),
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(None, None),
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);
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let sizeof_ty = ctx.get_llvm_type(generator, elem_ty);
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let len_bytes = ctx.builder
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.build_int_mul(
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len,
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sizeof_ty.size_of().unwrap(),
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"",
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)
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.unwrap();
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call_memcpy_generic(
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ctx,
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ndarray.data().base_ptr(ctx, generator),
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this.data().base_ptr(ctx, generator),
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len_bytes,
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llvm_i1.const_zero(),
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);
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Ok(ndarray)
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ndarray_sliced_copy(generator, ctx, elem_ty, this, &[])
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}
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pub fn ndarray_elementwise_unaryop_impl<'ctx, 'a, G, MapFn>(
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