M-Labs/nac3
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core/ndstrides: remove unnecessary Result<_, String>

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This commit is contained in:
lyken 2024-07-29 17:20:54 +08:00
parent 28e6f23034
commit ac7cc15d90
4 changed files with 9 additions and 9 deletions
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2
nac3core/src/codegen/expr.rs
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@ -2244,7 +2244,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
ctx, ctx,
sizet_model.constant(tyctx, ctx.ctx, dst_ndims as u64), sizet_model.constant(tyctx, ctx.ctx, dst_ndims as u64),
"subndarray", "subndarray",
)?; );
// Prepare the subscripts // Prepare the subscripts
let (num_ndindexes, ndindexes) = RustNDIndex::alloca_ndindexes(tyctx, ctx, &rust_ndindexes); let (num_ndindexes, ndindexes) = RustNDIndex::alloca_ndindexes(tyctx, ctx, &rust_ndindexes);

2
nac3core/src/codegen/numpy_new/factory.rs
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@ -43,7 +43,7 @@ where
let shape_writer = make_shape_writer(generator, ctx, shape, shape_ty); let shape_writer = make_shape_writer(generator, ctx, shape, shape_ty);
let ndims = shape_writer.len; let ndims = shape_writer.len;
let ndarray = alloca_ndarray(generator, ctx, ndims, name)?; let ndarray = alloca_ndarray(generator, ctx, ndims, name);
init_ndarray_shape(generator, ctx, ndarray, &shape_writer)?; init_ndarray_shape(generator, ctx, ndarray, &shape_writer)?;
let itemsize = ctx.get_llvm_type(generator, elem_ty).size_of().unwrap(); let itemsize = ctx.get_llvm_type(generator, elem_ty).size_of().unwrap();

12
nac3core/src/codegen/numpy_new/util.rs
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@ -34,7 +34,7 @@ pub fn alloca_ndarray<'ctx, G>(
ctx: &mut CodeGenContext<'ctx, '_>, ctx: &mut CodeGenContext<'ctx, '_>,
ndims: Int<'ctx, SizeT>, ndims: Int<'ctx, SizeT>,
name: &str, name: &str,
) -> Result<Ptr<'ctx, StructModel<NpArray>>, String> ) -> Ptr<'ctx, StructModel<NpArray>>
where where
G: CodeGenerator + ?Sized, G: CodeGenerator + ?Sized,
{ {
@ -54,7 +54,7 @@ where
ndarray_ptr.gep(ctx, |f| f.shape).store(ctx, shape); ndarray_ptr.gep(ctx, |f| f.shape).store(ctx, shape);
ndarray_ptr.gep(ctx, |f| f.strides).store(ctx, strides); ndarray_ptr.gep(ctx, |f| f.strides).store(ctx, strides);
Ok(ndarray_ptr) ndarray_ptr
} }
/// Initialize an ndarray's `shape` and asserts on. /// Initialize an ndarray's `shape` and asserts on.
@ -107,7 +107,7 @@ pub fn as_ndarray<'ctx, G: CodeGenerator + ?Sized>(
ctx: &mut CodeGenContext<'ctx, '_>, ctx: &mut CodeGenContext<'ctx, '_>,
input: BasicValueEnum<'ctx>, input: BasicValueEnum<'ctx>,
input_ty: Type, input_ty: Type,
) -> Result<(Ptr<'ctx, StructModel<NpArray>>, Type), String> { ) -> (Ptr<'ctx, StructModel<NpArray>>, Type) {
let tyctx = generator.type_context(ctx.ctx); let tyctx = generator.type_context(ctx.ctx);
let sizet_model = IntModel(SizeT); let sizet_model = IntModel(SizeT);
let pbyte_model = PtrModel(IntModel(Byte)); let pbyte_model = PtrModel(IntModel(Byte));
@ -120,11 +120,11 @@ pub fn as_ndarray<'ctx, G: CodeGenerator + ?Sized>(
{ {
let pndarray = pndarray_model.check_value(tyctx, ctx.ctx, input).unwrap(); let pndarray = pndarray_model.check_value(tyctx, ctx.ctx, input).unwrap();
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, input_ty); let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, input_ty);
Ok((pndarray, elem_ty)) (pndarray, elem_ty)
} }
_ => { _ => {
let ndims = sizet_model.const_0(tyctx, ctx.ctx); let ndims = sizet_model.const_0(tyctx, ctx.ctx);
let pndarray = alloca_ndarray(generator, ctx, ndims, "ndarray")?; let pndarray = alloca_ndarray(generator, ctx, ndims, "ndarray");
// We have to put `input` onto the stack to get a data pointer. // We have to put `input` onto the stack to get a data pointer.
let data = ctx.builder.build_alloca(input.get_type(), "as_ndarray_scalar").unwrap(); let data = ctx.builder.build_alloca(input.get_type(), "as_ndarray_scalar").unwrap();
@ -137,7 +137,7 @@ pub fn as_ndarray<'ctx, G: CodeGenerator + ?Sized>(
let itemsize = sizet_model.check_value(tyctx, ctx.ctx, itemsize).unwrap(); let itemsize = sizet_model.check_value(tyctx, ctx.ctx, itemsize).unwrap();
pndarray.gep(ctx, |f| f.itemsize).store(ctx, itemsize); pndarray.gep(ctx, |f| f.itemsize).store(ctx, itemsize);
Ok((pndarray, input_ty)) (pndarray, input_ty)
} }
} }
} }

2
nac3core/src/codegen/numpy_new/view.rs
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@ -37,7 +37,7 @@ fn gen_reshape_ndarray_or_copy<'ctx, G: CodeGenerator + ?Sized>(
let end_bb = ctx.ctx.insert_basic_block_after(else_bb, "end_bb"); let end_bb = ctx.ctx.insert_basic_block_after(else_bb, "end_bb");
// Inserting into current_bb // Inserting into current_bb
let dst_ndarray = alloca_ndarray(generator, ctx, new_shape.len, "ndarray").unwrap(); let dst_ndarray = alloca_ndarray(generator, ctx, new_shape.len, "ndarray");
// Set shape - directly from user input // Set shape - directly from user input
init_ndarray_shape(generator, ctx, dst_ndarray, new_shape)?; init_ndarray_shape(generator, ctx, dst_ndarray, new_shape)?;