forked from M-Labs/nac3
core/numpy: Implement codegen for np_array
This commit is contained in:
parent
4730b595f3
commit
6153f94b05
@ -1,12 +1,16 @@
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use inkwell::{IntPredicate, OptimizationLevel, types::BasicType, values::{BasicValueEnum, IntValue, PointerValue}};
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use inkwell::{AddressSpace, IntPredicate, OptimizationLevel, types::BasicType, values::{BasicValueEnum, IntValue, PointerValue}};
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use inkwell::types::{AnyTypeEnum, BasicTypeEnum, PointerType};
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use nac3parser::ast::{Operator, StrRef};
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use crate::{
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codegen::{
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classes::{
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ArrayLikeIndexer,
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ArrayLikeValue,
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ListType,
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ListValue,
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NDArrayType,
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NDArrayValue,
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ProxyType,
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ProxyValue,
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TypedArrayLikeAccessor,
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TypedArrayLikeAdapter,
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@ -31,9 +35,10 @@ use crate::{
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symbol_resolver::ValueEnum,
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toplevel::{
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DefinitionId,
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helper::PRIMITIVE_DEF_IDS,
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numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
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},
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typecheck::typedef::{FunSignature, Type},
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typecheck::typedef::{FunSignature, Type, TypeEnum},
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};
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/// Creates an uninitialized `NDArray` instance.
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@ -589,6 +594,405 @@ fn call_ndarray_full_impl<'ctx, G: CodeGenerator + ?Sized>(
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Ok(ndarray)
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}
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/// Returns the number of dimensions for a multidimensional list as an [`IntValue`].
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fn llvm_ndlist_get_ndims<'ctx, G: CodeGenerator + ?Sized>(
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generator: &G,
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ctx: &CodeGenContext<'ctx, '_>,
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ty: PointerType<'ctx>,
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) -> IntValue<'ctx> {
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let llvm_usize = generator.get_size_type(ctx.ctx);
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let list_ty = ListType::from_type(ty, llvm_usize);
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let list_elem_ty = list_ty.element_type();
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let ndims = llvm_usize.const_int(1, false);
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match list_elem_ty {
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AnyTypeEnum::PointerType(ptr_ty) if ListType::is_type(ptr_ty, llvm_usize).is_ok() => {
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ndims.const_add(llvm_ndlist_get_ndims(generator, ctx, ptr_ty))
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}
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AnyTypeEnum::PointerType(ptr_ty) if NDArrayType::is_type(ptr_ty, llvm_usize).is_ok() => {
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todo!("Getting ndims for list[ndarray] not supported")
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}
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_ => ndims,
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}
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}
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/// Returns the number of dimensions for an array-like object as an [`IntValue`].
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fn llvm_arraylike_get_ndims<'ctx, G: CodeGenerator + ?Sized>(
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generator: &mut G,
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ctx: &mut CodeGenContext<'ctx, '_>,
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value: BasicValueEnum<'ctx>,
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) -> IntValue<'ctx> {
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let llvm_usize = generator.get_size_type(ctx.ctx);
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match value {
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BasicValueEnum::PointerValue(v) if NDArrayValue::is_instance(v, llvm_usize).is_ok() => {
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NDArrayValue::from_ptr_val(v, llvm_usize, None).load_ndims(ctx)
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}
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BasicValueEnum::PointerValue(v) if ListValue::is_instance(v, llvm_usize).is_ok() => {
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llvm_ndlist_get_ndims(generator, ctx, v.get_type())
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}
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_ => llvm_usize.const_zero(),
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}
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}
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/// Flattens and copies the values from a multidimensional list into an [`NDArrayValue`].
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fn ndarray_from_ndlist_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_lst: ListValue<'ctx>,
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dim: u64,
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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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let list_elem_ty = src_lst.get_type().element_type();
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match list_elem_ty {
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AnyTypeEnum::PointerType(ptr_ty) if ListType::is_type(ptr_ty, llvm_usize).is_ok() => {
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// The stride of elements in this dimension, i.e. the number of elements between arr[i]
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// and arr[i + 1] in this dimension
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let 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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gen_for_range_callback(
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generator,
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ctx,
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true,
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|_, _| Ok(llvm_usize.const_zero()),
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(|_, ctx| Ok(src_lst.load_size(ctx, None)), false),
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|_, _| Ok(llvm_usize.const_int(1, false)),
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|generator, ctx, i| {
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let offset = ctx.builder.build_int_mul(
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stride,
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i,
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"",
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).unwrap();
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let dst_ptr = unsafe {
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ctx.builder.build_gep(dst_slice_ptr, &[offset], "").unwrap()
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};
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let nested_lst_elem = ListValue::from_ptr_val(
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unsafe {
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src_lst.data().get_unchecked(ctx, generator, &i, None)
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}.into_pointer_value(),
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llvm_usize,
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None,
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);
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ndarray_from_ndlist_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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nested_lst_elem,
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dim + 1,
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)?;
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Ok(())
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},
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)?;
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}
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AnyTypeEnum::PointerType(ptr_ty) if NDArrayType::is_type(ptr_ty, llvm_usize).is_ok() => {
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todo!("Not implemented for list[ndarray]")
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}
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_ => {
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let lst_len = src_lst.load_size(ctx, None);
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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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ctx.builder.build_int_z_extend_or_bit_cast(lst_len, llvm_usize, "").unwrap(),
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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_lst.data().base_ptr(ctx, generator),
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cpy_len,
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llvm_i1.const_zero(),
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);
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}
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}
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Ok(())
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}
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/// LLVM-typed implementation for `ndarray.array`.
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fn call_ndarray_array_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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object: BasicValueEnum<'ctx>,
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copy: IntValue<'ctx>,
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ndmin: IntValue<'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 llvm_usize = generator.get_size_type(ctx.ctx);
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let ndmin = ctx.builder
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.build_int_z_extend_or_bit_cast(ndmin, llvm_usize, "")
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.unwrap();
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// TODO(Derppening): Add assertions for sizes of different dimensions
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// object is not a pointer - 0-dim NDArray
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if !object.is_pointer_value() {
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let ndarray = create_ndarray_const_shape(
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generator,
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ctx,
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elem_ty,
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&[],
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)?;
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unsafe {
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ndarray.data()
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.set_unchecked(ctx, generator, &llvm_usize.const_zero(), object);
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}
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return Ok(ndarray)
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}
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let object = object.into_pointer_value();
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// object is an NDArray instance - copy object unless copy=0 && ndmin < object.ndims
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if NDArrayValue::is_instance(object, llvm_usize).is_ok() {
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let object = NDArrayValue::from_ptr_val(object, llvm_usize, None);
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let ndarray = gen_if_else_expr_callback(
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generator,
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ctx,
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|_, ctx| {
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let copy_nez = ctx.builder
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.build_int_compare(IntPredicate::NE, copy, llvm_i1.const_zero(), "")
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.unwrap();
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let ndmin_gt_ndims = ctx.builder
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.build_int_compare(IntPredicate::UGT, ndmin, object.load_ndims(ctx), "")
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.unwrap();
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Ok(ctx.builder
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.build_and(copy_nez, ndmin_gt_ndims, "")
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.unwrap())
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},
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|generator, ctx| {
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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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&object,
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|_, ctx, object| {
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let ndims = object.load_ndims(ctx);
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let ndmin_gt_ndims = ctx.builder
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.build_int_compare(IntPredicate::UGT, ndmin, object.load_ndims(ctx), "")
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.unwrap();
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Ok(ctx.builder
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.build_select(ndmin_gt_ndims, ndmin, ndims, "")
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.map(BasicValueEnum::into_int_value)
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.unwrap())
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},
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|generator, ctx, object, idx| {
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let ndims = object.load_ndims(ctx);
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let ndmin = llvm_intrinsics::call_int_umax(ctx, ndims, ndmin, None);
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// The number of dimensions to prepend 1's to
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let offset = ctx.builder.build_int_sub(ndmin, ndims, "").unwrap();
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Ok(gen_if_else_expr_callback(
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generator,
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ctx,
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|_, ctx| {
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Ok(ctx.builder
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.build_int_compare(IntPredicate::UGE, idx, offset, "")
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.unwrap())
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},
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|_, _| {
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Ok(Some(llvm_usize.const_int(1, false)))
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},
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|_, ctx| {
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Ok(Some(ctx.builder.build_int_sub(
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idx,
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offset,
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""
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).unwrap()))
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},
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)?.map(BasicValueEnum::into_int_value).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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(ndarray, ndarray.data().base_ptr(ctx, generator)),
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(object, object.data().base_ptr(ctx, generator)),
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0,
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&[],
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)?;
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Ok(Some(ndarray.as_base_value()))
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},
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|_, _| {
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Ok(Some(object.as_base_value()))
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},
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)?;
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return Ok(NDArrayValue::from_ptr_val(
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ndarray.map(BasicValueEnum::into_pointer_value).unwrap(),
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llvm_usize,
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None,
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))
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}
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// Remaining case: TList
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assert!(ListValue::is_instance(object, llvm_usize).is_ok());
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let object = ListValue::from_ptr_val(object, llvm_usize, None);
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// The number of dimensions to prepend 1's to
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let ndims = llvm_ndlist_get_ndims(generator, ctx, object.as_base_value().get_type());
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let ndmin = llvm_intrinsics::call_int_umax(ctx, ndims, ndmin, None);
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let offset = ctx.builder.build_int_sub(ndmin, ndims, "").unwrap();
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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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&object,
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|generator, ctx, object| {
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let ndims = llvm_ndlist_get_ndims(generator, ctx, object.as_base_value().get_type());
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let ndmin_gt_ndims = ctx.builder
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.build_int_compare(IntPredicate::UGT, ndmin, ndims, "")
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.unwrap();
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Ok(ctx.builder
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.build_select(ndmin_gt_ndims, ndmin, ndims, "")
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.map(BasicValueEnum::into_int_value)
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.unwrap())
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},
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|generator, ctx, object, idx| {
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Ok(gen_if_else_expr_callback(
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generator,
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ctx,
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|_, ctx| {
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Ok(ctx.builder
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.build_int_compare(IntPredicate::ULT, idx, offset, "")
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.unwrap())
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},
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|_, _| {
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Ok(Some(llvm_usize.const_int(1, false)))
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},
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|generator, ctx| {
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let make_llvm_list = |elem_ty: BasicTypeEnum<'ctx>| {
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ctx.ctx.struct_type(
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&[
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elem_ty.ptr_type(AddressSpace::default()).into(),
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llvm_usize.into(),
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],
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false,
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)
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};
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let llvm_i8 = ctx.ctx.i8_type();
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let llvm_list_i8 = make_llvm_list(llvm_i8.into());
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let llvm_plist_i8 = llvm_list_i8.ptr_type(AddressSpace::default());
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// Cast list to { i8*, usize } since we only care about the size
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let lst = generator.gen_var_alloc(
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ctx,
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ListType::new(generator, ctx.ctx, llvm_i8.into()).as_base_type().into(),
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None,
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).unwrap();
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ctx.builder.build_store(
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lst,
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ctx.builder.build_bitcast(
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object.as_base_value(),
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llvm_plist_i8,
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"",
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).unwrap(),
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).unwrap();
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let stop = ctx.builder.build_int_sub(idx, offset, "").unwrap();
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gen_for_range_callback(
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generator,
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ctx,
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true,
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|_, _| Ok(llvm_usize.const_zero()),
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(|_, _| Ok(stop), false),
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|_, _| Ok(llvm_usize.const_int(1, false)),
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|generator, ctx, _| {
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let plist_plist_i8 = make_llvm_list(llvm_plist_i8.into())
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.ptr_type(AddressSpace::default());
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let this_dim = ctx.builder
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.build_load(lst, "")
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.map(BasicValueEnum::into_pointer_value)
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.map(|v| ctx.builder.build_bitcast(v, plist_plist_i8, "").unwrap())
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.map(BasicValueEnum::into_pointer_value)
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.unwrap();
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let this_dim = ListValue::from_ptr_val(
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this_dim,
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llvm_usize,
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None,
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);
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// TODO: Assert this_dim.sz != 0
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let next_dim = unsafe {
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this_dim.data()
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.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
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}.into_pointer_value();
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ctx.builder.build_store(
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lst,
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ctx.builder.build_bitcast(
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next_dim,
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llvm_plist_i8,
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"",
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).unwrap(),
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).unwrap();
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Ok(())
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},
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)?;
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let lst = ListValue::from_ptr_val(
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ctx.builder
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.build_load(lst, "")
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.map(BasicValueEnum::into_pointer_value)
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.unwrap(),
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llvm_usize,
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None,
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);
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Ok(Some(lst.load_size(ctx, None)))
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},
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)?.map(BasicValueEnum::into_int_value).unwrap())
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},
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)?;
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ndarray_from_ndlist_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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object,
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0,
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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.eye`.
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///
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/// * `elem_ty` - The element type of the `NDArray`.
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@ -1450,6 +1854,69 @@ pub fn gen_ndarray_full<'ctx>(
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).map(NDArrayValue::into)
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}
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pub fn gen_ndarray_array<'ctx>(
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context: &mut CodeGenContext<'ctx, '_>,
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obj: &Option<(Type, ValueEnum<'ctx>)>,
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fun: (&FunSignature, DefinitionId),
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args: &[(Option<StrRef>, ValueEnum<'ctx>)],
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generator: &mut dyn CodeGenerator,
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) -> Result<PointerValue<'ctx>, String> {
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assert!(obj.is_none());
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assert!(matches!(args.len(), 1..=3));
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let obj_ty = fun.0.args[0].ty;
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let obj_elem_ty = match &*context.unifier.get_ty(obj_ty) {
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TypeEnum::TObj { obj_id, .. } if *obj_id == PRIMITIVE_DEF_IDS.ndarray => {
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unpack_ndarray_var_tys(&mut context.unifier, obj_ty).0
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}
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|
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TypeEnum::TList { ty } => {
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let mut ty = *ty;
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while let TypeEnum::TList { ty: elem_ty } = &*context.unifier.get_ty_immutable(ty) {
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ty = *elem_ty;
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}
|
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ty
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},
|
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|
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_ => obj_ty,
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};
|
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let obj_arg = args[0].1.clone()
|
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.to_basic_value_enum(context, generator, obj_ty)?;
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let copy_arg = if let Some(arg) =
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args.iter().find(|arg| arg.0.is_some_and(|name| name == fun.0.args[1].name)) {
|
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let copy_ty = fun.0.args[1].ty;
|
||||
arg.1.clone().to_basic_value_enum(context, generator, copy_ty)?
|
||||
} else {
|
||||
context.gen_symbol_val(
|
||||
generator,
|
||||
fun.0.args[1].default_value.as_ref().unwrap(),
|
||||
fun.0.args[1].ty,
|
||||
)
|
||||
};
|
||||
|
||||
let ndmin_arg = if let Some(arg) =
|
||||
args.iter().find(|arg| arg.0.is_some_and(|name| name == fun.0.args[2].name)) {
|
||||
let ndmin_ty = fun.0.args[2].ty;
|
||||
arg.1.clone().to_basic_value_enum(context, generator, ndmin_ty)?
|
||||
} else {
|
||||
context.gen_symbol_val(
|
||||
generator,
|
||||
fun.0.args[2].default_value.as_ref().unwrap(),
|
||||
fun.0.args[2].ty,
|
||||
)
|
||||
};
|
||||
|
||||
call_ndarray_array_impl(
|
||||
generator,
|
||||
context,
|
||||
obj_elem_ty,
|
||||
obj_arg,
|
||||
copy_arg.into_int_value(),
|
||||
ndmin_arg.into_int_value(),
|
||||
).map(NDArrayValue::into)
|
||||
}
|
||||
|
||||
/// Generates LLVM IR for `ndarray.eye`.
|
||||
pub fn gen_ndarray_eye<'ctx>(
|
||||
context: &mut CodeGenContext<'ctx, '_>,
|
||||
|
@ -809,15 +809,16 @@ pub fn get_builtins(unifier: &mut Unifier, primitives: &PrimitiveStore) -> Built
|
||||
},
|
||||
],
|
||||
ret: ndarray,
|
||||
vars: VarMap::default(),
|
||||
vars: VarMap::from([(tv.1, tv.0)]),
|
||||
})),
|
||||
var_id: Vec::default(),
|
||||
var_id: vec![tv.1],
|
||||
instance_to_symbol: HashMap::default(),
|
||||
instance_to_stmt: HashMap::default(),
|
||||
resolver: None,
|
||||
codegen_callback: Some(Arc::new(GenCall::new(Box::new(
|
||||
|ctx, obj, fun, args, generator| {
|
||||
todo!()
|
||||
gen_ndarray_array(ctx, &obj, fun, &args, generator)
|
||||
.map(|val| Some(val.as_basic_value_enum()))
|
||||
},
|
||||
)))),
|
||||
loc: None,
|
||||
|
Loading…
Reference in New Issue
Block a user