core/ndstrides: remove unnecessary Result<_, String>

nac3core/src/codegen/expr.rs

@@ -2244,7 +2244,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
         ctx,
         sizet_model.constant(tyctx, ctx.ctx, dst_ndims as u64),
         "subndarray",
-    )?;
+    );
 
     // Prepare the subscripts
     let (num_ndindexes, ndindexes) = RustNDIndex::alloca_ndindexes(tyctx, ctx, &rust_ndindexes);

nac3core/src/codegen/numpy_new/factory.rs

@@ -43,7 +43,7 @@ where
     let shape_writer = make_shape_writer(generator, ctx, shape, shape_ty);
     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)?;
 
     let itemsize = ctx.get_llvm_type(generator, elem_ty).size_of().unwrap();

nac3core/src/codegen/numpy_new/util.rs

@@ -34,7 +34,7 @@ pub fn alloca_ndarray<'ctx, G>(
     ctx: &mut CodeGenContext<'ctx, '_>,
     ndims: Int<'ctx, SizeT>,
     name: &str,
-) -> Result<Ptr<'ctx, StructModel<NpArray>>, String>
+) -> Ptr<'ctx, StructModel<NpArray>>
 where
     G: CodeGenerator + ?Sized,
 {
@@ -54,7 +54,7 @@ where
     ndarray_ptr.gep(ctx, |f| f.shape).store(ctx, shape);
     ndarray_ptr.gep(ctx, |f| f.strides).store(ctx, strides);
 
-    Ok(ndarray_ptr)
+    ndarray_ptr
 }
 
 /// Initialize an ndarray's `shape` and asserts on.
@@ -107,7 +107,7 @@ pub fn as_ndarray<'ctx, G: CodeGenerator + ?Sized>(
     ctx: &mut CodeGenContext<'ctx, '_>,
     input: BasicValueEnum<'ctx>,
     input_ty: Type,
-) -> Result<(Ptr<'ctx, StructModel<NpArray>>, Type), String> {
+) -> (Ptr<'ctx, StructModel<NpArray>>, Type) {
     let tyctx = generator.type_context(ctx.ctx);
     let sizet_model = IntModel(SizeT);
     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 (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 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.
             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();
             pndarray.gep(ctx, |f| f.itemsize).store(ctx, itemsize);
 
-            Ok((pndarray, input_ty))
+            (pndarray, input_ty)
         }
     }
 }

nac3core/src/codegen/numpy_new/view.rs

@@ -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");
 
     // 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
     init_ndarray_shape(generator, ctx, dst_ndarray, new_shape)?;