asd

nac3core/irrt/irrt_numpy_ndarray.hpp

@@ -212,11 +212,11 @@ namespace {
             return this->size() * itemsize;
         }
 
-        void set_value_at_pelement(uint8_t* pelement, const uint8_t* pvalue) {
+        void set_pelement_value(uint8_t* pelement, const uint8_t* pvalue) {
             __builtin_memcpy(pelement, pvalue, itemsize);
         }
 
-        uint8_t* get_pelement(const SizeT *indices) {
+        uint8_t* get_pelement_by_indices(const SizeT *indices) {
             uint8_t* element = data;
             for (SizeT dim_i = 0; dim_i < ndims; dim_i++)
                 element += indices[dim_i] * strides[dim_i];
@@ -229,7 +229,7 @@ namespace {
 
             SizeT* indices = (SizeT*) __builtin_alloca(sizeof(SizeT) * this->ndims);
             ndarray_util::set_indices_by_nth(this->ndims, this->shape, indices, nth);
-            return get_pelement(indices);
+            return get_pelement_by_indices(indices);
         }
 
         // Get pointer to the first element of this ndarray, assuming
@@ -259,8 +259,8 @@ namespace {
             iter.set_indices_zero();
 
             for (SizeT i = 0; i < this->size(); i++, iter.next()) {
-                uint8_t* pelement = get_pelement(iter.indices);
-                set_value_at_pelement(pelement, pvalue);
+                uint8_t* pelement = get_pelement_by_indices(iter.indices);
+                set_pelement_value(pelement, pvalue);
             }
         }
 
@@ -283,8 +283,8 @@ namespace {
 
                 if (!in_bounds(indices)) continue;
 
-                uint8_t* pelement = get_pelement(indices);
-                set_value_at_pelement(pelement, one_pvalue);
+                uint8_t* pelement = get_pelement_by_indices(indices);
+                set_pelement_value(pelement, one_pvalue);
             }
         }
 
@@ -435,9 +435,9 @@ namespace {
             };
             const SizeT this_size = this->size();
             for (SizeT i = 0; i < this_size; i++, iter.next()) {
-                uint8_t* src_pelement = broadcasted_src_ndarray_strides->get_pelement(indices);
-                uint8_t* this_pelement = this->get_pelement(indices);
-                this->set_value_at_pelement(src_pelement, src_pelement);
+                uint8_t* src_pelement = broadcasted_src_ndarray_strides->get_pelement_by_indices(indices);
+                uint8_t* this_pelement = this->get_pelement_by_indices(indices);
+                this->set_pelement_value(src_pelement, src_pelement);
             }
         }
     };

nac3core/irrt/irrt_test.cpp

@@ -81,7 +81,7 @@ void __print_ndarray_aux(const char *format, bool first, bool last, SizeT* curso
         SizeT* indices = (SizeT*) __builtin_alloca(sizeof(SizeT) * ndarray->ndims);
         for (SizeT i = 0; i < dim; i++) {
             ndarray_util::set_indices_by_nth(ndarray->ndims, ndarray->shape, indices, *cursor);
-            ElementT* pelement = (ElementT*) ndarray->get_pelement(indices);
+            ElementT* pelement = (ElementT*) ndarray->get_pelement_by_indices(indices);
             ElementT element = *pelement;
 
             if (i != 0) printf(", "); // List delimiter
@@ -394,10 +394,10 @@ void test_ndslice_1() {
     assert_arrays_match("shape", "%d", dst_ndims, expected_shape, dst_ndarray.shape);
     assert_arrays_match("strides", "%d", dst_ndims, expected_strides, dst_ndarray.strides);
 
-    assert_values_match("dst_ndarray[0, 0]", "%f", 5.0, *((double *) dst_ndarray.get_pelement((int32_t[dst_ndims]) { 0, 0 })));
-    assert_values_match("dst_ndarray[0, 1]", "%f", 7.0, *((double *) dst_ndarray.get_pelement((int32_t[dst_ndims]) { 0, 1 })));
-    assert_values_match("dst_ndarray[1, 0]", "%f", 9.0, *((double *) dst_ndarray.get_pelement((int32_t[dst_ndims]) { 1, 0 })));
-    assert_values_match("dst_ndarray[1, 1]", "%f", 11.0, *((double *) dst_ndarray.get_pelement((int32_t[dst_ndims]) { 1, 1 })));
+    assert_values_match("dst_ndarray[0, 0]", "%f", 5.0, *((double *) dst_ndarray.get_pelement_by_indices((int32_t[dst_ndims]) { 0, 0 })));
+    assert_values_match("dst_ndarray[0, 1]", "%f", 7.0, *((double *) dst_ndarray.get_pelement_by_indices((int32_t[dst_ndims]) { 0, 1 })));
+    assert_values_match("dst_ndarray[1, 0]", "%f", 9.0, *((double *) dst_ndarray.get_pelement_by_indices((int32_t[dst_ndims]) { 1, 0 })));
+    assert_values_match("dst_ndarray[1, 1]", "%f", 11.0, *((double *) dst_ndarray.get_pelement_by_indices((int32_t[dst_ndims]) { 1, 1 })));
 }
 
 void test_ndslice_2() {
@@ -471,8 +471,8 @@ void test_ndslice_2() {
     assert_arrays_match("strides", "%d", dst_ndims, expected_strides, dst_ndarray.strides);
 
     // [5.0, 3.0]
-    assert_values_match("dst_ndarray[0]", "%f", 11.0, *((double *) dst_ndarray.get_pelement((int32_t[dst_ndims]) { 0 })));
-    assert_values_match("dst_ndarray[1]", "%f", 9.0, *((double *) dst_ndarray.get_pelement((int32_t[dst_ndims]) { 1 })));
+    assert_values_match("dst_ndarray[0]", "%f", 11.0, *((double *) dst_ndarray.get_pelement_by_indices((int32_t[dst_ndims]) { 0 })));
+    assert_values_match("dst_ndarray[1]", "%f", 9.0, *((double *) dst_ndarray.get_pelement_by_indices((int32_t[dst_ndims]) { 1 })));
 }
 
 void test_can_broadcast_shape() {
@@ -618,24 +618,15 @@ void test_ndarray_broadcast_1() {
 
     assert_arrays_match("dst_ndarray->strides", "%d", dst_ndims, (int32_t[]) { 0, 0, 8 }, dst_ndarray.strides);
 
-    assert_values_match("dst_ndarray[0, 0, 0]", "%f", 19.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 0, 0})));
-    assert_values_match("dst_ndarray[0, 0, 1]", "%f", 29.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 0, 1})));
-    assert_values_match("dst_ndarray[0, 0, 2]", "%f", 39.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 0, 2})));
-    assert_values_match("dst_ndarray[0, 0, 3]", "%f", 49.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 0, 3})));
-    assert_values_match("dst_ndarray[0, 1, 0]", "%f", 19.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 1, 0})));
-    assert_values_match("dst_ndarray[0, 1, 1]", "%f", 29.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 1, 1})));
-    assert_values_match("dst_ndarray[0, 1, 2]", "%f", 39.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 1, 2})));
-    assert_values_match("dst_ndarray[0, 1, 3]", "%f", 49.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 1, 3})));
-    assert_values_match("dst_ndarray[1, 2, 3]", "%f", 49.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {1, 2, 3})));
-}
-
-void test_assign_with() {
-    /*
-        ```
-        xs = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]], dtype=np.float64)
-        ys = xs.shape
-        ```
-    */
+    assert_values_match("dst_ndarray[0, 0, 0]", "%f", 19.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 0, 0})));
+    assert_values_match("dst_ndarray[0, 0, 1]", "%f", 29.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 0, 1})));
+    assert_values_match("dst_ndarray[0, 0, 2]", "%f", 39.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 0, 2})));
+    assert_values_match("dst_ndarray[0, 0, 3]", "%f", 49.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 0, 3})));
+    assert_values_match("dst_ndarray[0, 1, 0]", "%f", 19.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 1, 0})));
+    assert_values_match("dst_ndarray[0, 1, 1]", "%f", 29.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 1, 1})));
+    assert_values_match("dst_ndarray[0, 1, 2]", "%f", 39.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 1, 2})));
+    assert_values_match("dst_ndarray[0, 1, 3]", "%f", 49.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {0, 1, 3})));
+    assert_values_match("dst_ndarray[1, 2, 3]", "%f", 49.9, *((double*) dst_ndarray.get_pelement_by_indices((int32_t[]) {1, 2, 3})));
 }
 
 int main() {
@@ -653,6 +644,5 @@ int main() {
     test_ndslice_2();
     test_can_broadcast_shape();
     test_ndarray_broadcast_1();
-    test_assign_with();
     return 0;
 }

nac3core/src/codegen/builtin_fns.rs

@@ -702,53 +702,54 @@ pub fn call_numpy_min<'ctx, G: CodeGenerator + ?Sized>(
         BasicValueEnum::PointerValue(n)
             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);
+            todo!()
+            // let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, a_ty);
+            // let llvm_ndarray_ty = ctx.get_llvm_type(generator, elem_ty);
 
-            let n = NDArrayValue::from_ptr_val(n, llvm_usize, None);
-            let n_sz = irrt::call_ndarray_calc_size(generator, ctx, &n.dim_sizes(), (None, None));
-            if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
-                let n_sz_eqz = ctx
-                    .builder
-                    .build_int_compare(IntPredicate::NE, n_sz, n_sz.get_type().const_zero(), "")
-                    .unwrap();
+            // let n = NDArrayValue::from_ptr_val(n, llvm_usize, None);
+            // let n_sz = irrt::call_ndarray_calc_size(generator, ctx, &n.dim_sizes(), (None, None));
+            // if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
+            //     let n_sz_eqz = ctx
+            //         .builder
+            //         .build_int_compare(IntPredicate::NE, n_sz, n_sz.get_type().const_zero(), "")
+            //         .unwrap();
 
-                ctx.make_assert(
-                    generator,
-                    n_sz_eqz,
-                    "0:ValueError",
-                    "zero-size array to reduction operation minimum which has no identity",
-                    [None, None, None],
-                    ctx.current_loc,
-                );
-            }
+            //     ctx.make_assert(
+            //         generator,
+            //         n_sz_eqz,
+            //         "0:ValueError",
+            //         "zero-size array to reduction operation minimum which has no identity",
+            //         [None, None, None],
+            //         ctx.current_loc,
+            //     );
+            // }
 
-            let accumulator_addr = generator.gen_var_alloc(ctx, llvm_ndarray_ty, None)?;
-            unsafe {
-                let identity =
-                    n.data().get_unchecked(ctx, generator, &llvm_usize.const_zero(), None);
-                ctx.builder.build_store(accumulator_addr, identity).unwrap();
-            }
+            // let accumulator_addr = generator.gen_var_alloc(ctx, llvm_ndarray_ty, None)?;
+            // unsafe {
+            //     let identity =
+            //         n.data().get_unchecked(ctx, generator, &llvm_usize.const_zero(), None);
+            //     ctx.builder.build_store(accumulator_addr, identity).unwrap();
+            // }
 
-            gen_for_callback_incrementing(
-                generator,
-                ctx,
-                llvm_usize.const_int(1, false),
-                (n_sz, false),
-                |generator, ctx, _, idx| {
-                    let elem = unsafe { n.data().get_unchecked(ctx, generator, &idx, None) };
+            // gen_for_callback_incrementing(
+            //     generator,
+            //     ctx,
+            //     llvm_usize.const_int(1, false),
+            //     (n_sz, false),
+            //     |generator, ctx, _, idx| {
+            //         let elem = unsafe { n.data().get_unchecked(ctx, generator, &idx, None) };
 
-                    let accumulator = ctx.builder.build_load(accumulator_addr, "").unwrap();
-                    let result = call_min(ctx, (elem_ty, accumulator), (elem_ty, elem));
-                    ctx.builder.build_store(accumulator_addr, result).unwrap();
+            //         let accumulator = ctx.builder.build_load(accumulator_addr, "").unwrap();
+            //         let result = call_min(ctx, (elem_ty, accumulator), (elem_ty, elem));
+            //         ctx.builder.build_store(accumulator_addr, result).unwrap();
 
-                    Ok(())
-                },
-                llvm_usize.const_int(1, false),
-            )?;
+            //         Ok(())
+            //     },
+            //     llvm_usize.const_int(1, false),
+            // )?;
 
-            let accumulator = ctx.builder.build_load(accumulator_addr, "").unwrap();
-            accumulator
+            // let accumulator = ctx.builder.build_load(accumulator_addr, "").unwrap();
+            // accumulator
         }
 
         _ => unsupported_type(ctx, FN_NAME, &[a_ty]),
@@ -920,53 +921,54 @@ pub fn call_numpy_max<'ctx, G: CodeGenerator + ?Sized>(
         BasicValueEnum::PointerValue(n)
             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);
+            todo!()
+            // let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, a_ty);
+            // let llvm_ndarray_ty = ctx.get_llvm_type(generator, elem_ty);
 
-            let n = NDArrayValue::from_ptr_val(n, llvm_usize, None);
-            let n_sz = irrt::call_ndarray_calc_size(generator, ctx, &n.dim_sizes(), (None, None));
-            if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
-                let n_sz_eqz = ctx
-                    .builder
-                    .build_int_compare(IntPredicate::NE, n_sz, n_sz.get_type().const_zero(), "")
-                    .unwrap();
+            // let n = NDArrayValue::from_ptr_val(n, llvm_usize, None);
+            // let n_sz = irrt::call_ndarray_calc_size(generator, ctx, &n.dim_sizes(), (None, None));
+            // if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
+            //     let n_sz_eqz = ctx
+            //         .builder
+            //         .build_int_compare(IntPredicate::NE, n_sz, n_sz.get_type().const_zero(), "")
+            //         .unwrap();
 
-                ctx.make_assert(
-                    generator,
-                    n_sz_eqz,
-                    "0:ValueError",
-                    "zero-size array to reduction operation minimum which has no identity",
-                    [None, None, None],
-                    ctx.current_loc,
-                );
-            }
+            //     ctx.make_assert(
+            //         generator,
+            //         n_sz_eqz,
+            //         "0:ValueError",
+            //         "zero-size array to reduction operation minimum which has no identity",
+            //         [None, None, None],
+            //         ctx.current_loc,
+            //     );
+            // }
 
-            let accumulator_addr = generator.gen_var_alloc(ctx, llvm_ndarray_ty, None)?;
-            unsafe {
-                let identity =
-                    n.data().get_unchecked(ctx, generator, &llvm_usize.const_zero(), None);
-                ctx.builder.build_store(accumulator_addr, identity).unwrap();
-            }
+            // let accumulator_addr = generator.gen_var_alloc(ctx, llvm_ndarray_ty, None)?;
+            // unsafe {
+            //     let identity =
+            //         n.data().get_unchecked(ctx, generator, &llvm_usize.const_zero(), None);
+            //     ctx.builder.build_store(accumulator_addr, identity).unwrap();
+            // }
 
-            gen_for_callback_incrementing(
-                generator,
-                ctx,
-                llvm_usize.const_int(1, false),
-                (n_sz, false),
-                |generator, ctx, _, idx| {
-                    let elem = unsafe { n.data().get_unchecked(ctx, generator, &idx, None) };
+            // gen_for_callback_incrementing(
+            //     generator,
+            //     ctx,
+            //     llvm_usize.const_int(1, false),
+            //     (n_sz, false),
+            //     |generator, ctx, _, idx| {
+            //         let elem = unsafe { n.data().get_unchecked(ctx, generator, &idx, None) };
 
-                    let accumulator = ctx.builder.build_load(accumulator_addr, "").unwrap();
-                    let result = call_max(ctx, (elem_ty, accumulator), (elem_ty, elem));
-                    ctx.builder.build_store(accumulator_addr, result).unwrap();
+            //         let accumulator = ctx.builder.build_load(accumulator_addr, "").unwrap();
+            //         let result = call_max(ctx, (elem_ty, accumulator), (elem_ty, elem));
+            //         ctx.builder.build_store(accumulator_addr, result).unwrap();
 
-                    Ok(())
-                },
-                llvm_usize.const_int(1, false),
-            )?;
+            //         Ok(())
+            //     },
+            //     llvm_usize.const_int(1, false),
+            // )?;
 
-            let accumulator = ctx.builder.build_load(accumulator_addr, "").unwrap();
-            accumulator
+            // let accumulator = ctx.builder.build_load(accumulator_addr, "").unwrap();
+            // accumulator
         }
 
         _ => unsupported_type(ctx, FN_NAME, &[a_ty]),

nac3core/src/codegen/classes.rs

@@ -1,5 +1,8 @@
 use crate::codegen::{
-    llvm_intrinsics::call_int_umin, stmt::gen_for_callback_incrementing, CodeGenContext,
+    // irrt::{call_ndarray_calc_size, call_ndarray_flatten_index},
+    llvm_intrinsics::call_int_umin,
+    stmt::gen_for_callback_incrementing,
+    CodeGenContext,
     CodeGenerator,
 };
 use inkwell::context::Context;
@@ -1207,25 +1210,27 @@ impl<'ctx> NDArrayType<'ctx> {
         ctx: &'ctx Context,
         dtype: BasicTypeEnum<'ctx>,
     ) -> Self {
-        let llvm_usize = generator.get_size_type(ctx);
+        todo!()
 
-        // 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());
+        // let llvm_usize = generator.get_size_type(ctx);
 
-        NDArrayType::from_type(llvm_ndarray, 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)
     }
 
     /// Creates an [`NDArrayType`] from a [`PointerType`].
@@ -1659,23 +1664,22 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
         indices: &Index,
         name: Option<&str>,
     ) -> PointerValue<'ctx> {
-        let llvm_usize = generator.get_size_type(ctx.ctx);
-
-        let indices_elem_ty = indices
-            .ptr_offset(ctx, generator, &llvm_usize.const_zero(), None)
-            .get_type()
-            .get_element_type();
-        let Ok(indices_elem_ty) = IntType::try_from(indices_elem_ty) else {
-            panic!("Expected list[int32] but got {indices_elem_ty}")
-        };
-        assert_eq!(
-            indices_elem_ty.get_bit_width(),
-            32,
-            "Expected list[int32] but got list[int{}]",
-            indices_elem_ty.get_bit_width()
-        );
-
         todo!()
+        // let llvm_usize = generator.get_size_type(ctx.ctx);
+
+        // let indices_elem_ty = indices
+        //     .ptr_offset(ctx, generator, &llvm_usize.const_zero(), None)
+        //     .get_type()
+        //     .get_element_type();
+        // let Ok(indices_elem_ty) = IntType::try_from(indices_elem_ty) else {
+        //     panic!("Expected list[int32] but got {indices_elem_ty}")
+        // };
+        // assert_eq!(
+        //     indices_elem_ty.get_bit_width(),
+        //     32,
+        //     "Expected list[int32] but got list[int{}]",
+        //     indices_elem_ty.get_bit_width()
+        // );
 
         // let index = call_ndarray_flatten_index(generator, ctx, *self.0, indices);
 
@@ -1797,27 +1801,39 @@ struct StructFieldsBuilder<'ctx> {
 }
 
 impl<'ctx> StructField<'ctx> {
+    /// TODO: DOCUMENT ME
     pub fn gep(
         &self,
         ctx: &CodeGenContext<'ctx, '_>,
-        ptr: PointerValue<'ctx>,
+        struct_ptr: PointerValue<'ctx>,
     ) -> PointerValue<'ctx> {
-        ctx.builder.build_struct_gep(ptr, self.gep_index, self.name).unwrap()
+        let index_type = ctx.ctx.i32_type(); // TODO: I think I'm not supposed to use i32 for GEP like that
+        unsafe {
+            ctx.builder
+                .build_in_bounds_gep(
+                    struct_ptr,
+                    &[index_type.const_zero(), index_type.const_int(self.gep_index as u64, false)],
+                    self.name,
+                )
+                .unwrap()
+        }
     }
 
+    /// TODO: DOCUMENT ME
     pub fn load(
         &self,
         ctx: &CodeGenContext<'ctx, '_>,
-        ptr: PointerValue<'ctx>,
+        struct_ptr: PointerValue<'ctx>,
     ) -> BasicValueEnum<'ctx> {
-        ctx.builder.build_load(self.gep(ctx, ptr), self.name).unwrap()
+        ctx.builder.build_load(self.gep(ctx, struct_ptr), self.name).unwrap()
     }
 
-    pub fn store<V>(&self, ctx: &CodeGenContext<'ctx, '_>, ptr: PointerValue<'ctx>, value: V)
+    /// TODO: DOCUMENT ME
+    pub fn store<V>(&self, ctx: &CodeGenContext<'ctx, '_>, struct_ptr: PointerValue<'ctx>, value: V)
     where
         V: BasicValue<'ctx>,
     {
-        ctx.builder.build_store(ptr, value).unwrap();
+        ctx.builder.build_store(self.gep(ctx, struct_ptr), value).unwrap();
     }
 }
 
@@ -1856,7 +1872,7 @@ impl<'ctx> StructFields<'ctx> {
         self.fields.len() as u32
     }
 
-    pub fn as_struct_type(&self, ctx: &'ctx Context) -> StructType<'ctx> {
+    pub fn get_struct_type(&self, ctx: &'ctx Context) -> StructType<'ctx> {
         let llvm_fields = self.fields.iter().map(|field| field.ty).collect_vec();
         ctx.struct_type(llvm_fields.as_slice(), false)
     }
@@ -1900,7 +1916,11 @@ impl<'ctx> StructFieldsBuilder<'ctx> {
     fn add_field(&mut self, name: &'static str, ty: BasicTypeEnum<'ctx>) -> StructField<'ctx> {
         let index = self.gep_index_counter;
         self.gep_index_counter += 1;
-        StructField { gep_index: index, name, ty }
+
+        let field = StructField { gep_index: index, name, ty };
+        self.fields.push(field); // Register into self.fields
+
+        field // Return to the caller to conveniently let them do whatever they want
     }
 
     fn end(self) -> StructFields<'ctx> {
@@ -1931,8 +1951,8 @@ impl<'ctx> NpArrayType<'ctx> {
         NpArrayType { size_type, elem_type: ctx.ctx.i8_type().as_basic_type_enum() }
     }
 
-    pub fn struct_type(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructType<'ctx> {
-        self.fields().whole_struct.as_struct_type(ctx.ctx)
+    pub fn get_struct_type(&self, ctx: &'ctx Context) -> StructType<'ctx> {
+        self.fields().whole_struct.get_struct_type(ctx)
     }
 
     pub fn fields(&self) -> NpArrayStructFields<'ctx> {
@@ -1958,29 +1978,43 @@ impl<'ctx> NpArrayType<'ctx> {
     /// - `ndarray.itemsize` will be initialized to the size of `self.elem_type.size_of()`.
     /// - `ndarray.shape` and `ndarray.strides` will be allocated on the stack with number of elements being `in_ndims`,
     /// all with empty/uninitialized values.
-    pub fn alloca(
+    pub fn var_alloc<G>(
         &self,
-        ctx: &CodeGenContext<'ctx, '_>,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
         in_ndims: IntValue<'ctx>,
-        name: &str,
-    ) -> NpArrayValue<'ctx> {
-        let fields = self.fields();
-        let ptr =
-            ctx.builder.build_alloca(fields.whole_struct.as_struct_type(ctx.ctx), name).unwrap();
+        name: Option<&str>,
+    ) -> NpArrayValue<'ctx>
+    where
+        G: CodeGenerator + ?Sized,
+    {
+        let ptr = generator
+            .gen_var_alloc(ctx, self.get_struct_type(ctx.ctx).as_basic_type_enum(), name)
+            .unwrap();
 
         // Allocate `in_dims` number of `size_type` on the stack for `shape` and `strides`
-        let allocated_shape =
-            ctx.builder.build_array_alloca(fields.shape.ty, in_ndims, "allocated_shape").unwrap();
-        let allocated_strides = ctx
-            .builder
-            .build_array_alloca(fields.strides.ty, in_ndims, "allocated_strides")
+        let allocated_shape = generator
+            .gen_array_var_alloc(
+                ctx,
+                self.size_type.as_basic_type_enum(),
+                in_ndims,
+                Some("allocated_shape"),
+            )
+            .unwrap();
+        let allocated_strides = generator
+            .gen_array_var_alloc(
+                ctx,
+                self.size_type.as_basic_type_enum(),
+                in_ndims,
+                Some("allocated_strides"),
+            )
             .unwrap();
 
         let value = NpArrayValue { ty: *self, ptr };
         value.store_ndims(ctx, in_ndims);
         value.store_itemsize(ctx, self.elem_type.size_of().unwrap());
-        value.store_shape(ctx, allocated_shape);
-        value.store_strides(ctx, allocated_strides);
+        value.store_shape(ctx, allocated_shape.base_ptr(ctx, generator));
+        value.store_strides(ctx, allocated_strides.base_ptr(ctx, generator));
 
         return value;
     }
@@ -2038,13 +2072,15 @@ impl<'ctx> NpArrayValue<'ctx> {
         &self,
         ctx: &CodeGenContext<'ctx, '_>,
     ) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
+        // Get the pointer to `shape`
         let field = self.ty.fields().shape;
-        field.gep(ctx, self.ptr);
+        let shape = field.load(ctx, self.ptr).into_pointer_value();
 
+        // Load `ndims`
         let ndims = self.load_ndims(ctx);
 
         TypedArrayLikeAdapter {
-            adapted: ArraySliceValue(self.ptr, ndims, Some(field.name)),
+            adapted: ArraySliceValue(shape, ndims, Some(field.name)),
             downcast_fn: Box::new(|_ctx, x| x.into_int_value()),
             upcast_fn: Box::new(|_ctx, x| x.as_basic_value_enum()),
         }
@@ -2055,13 +2091,15 @@ impl<'ctx> NpArrayValue<'ctx> {
         &self,
         ctx: &CodeGenContext<'ctx, '_>,
     ) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
+        // Get the pointer to `strides`
         let field = self.ty.fields().strides;
-        field.gep(ctx, self.ptr);
+        let strides = field.load(ctx, self.ptr).into_pointer_value();
 
+        // Load `ndims`
         let ndims = self.load_ndims(ctx);
 
         TypedArrayLikeAdapter {
-            adapted: ArraySliceValue(self.ptr, ndims, Some(field.name)),
+            adapted: ArraySliceValue(strides, ndims, Some(field.name)),
             downcast_fn: Box::new(|_ctx, x| x.into_int_value()),
             upcast_fn: Box::new(|_ctx, x| x.as_basic_value_enum()),
         }

nac3core/src/codegen/irrt/mod.rs

@@ -4,8 +4,8 @@ mod test;
 
 use super::{
     classes::{
-        ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue, NpArrayType,
-        NpArrayValue, TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
+        check_basic_types_match, ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue,
+        NDArrayValue, NpArrayType, NpArrayValue, TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
     },
     llvm_intrinsics, CodeGenContext, CodeGenerator,
 };
@@ -17,7 +17,7 @@ use inkwell::{
     memory_buffer::MemoryBuffer,
     module::Module,
     types::{BasicType, BasicTypeEnum, FunctionType, IntType, PointerType},
-    values::{BasicValueEnum, CallSiteValue, FloatValue, FunctionValue, IntValue},
+    values::{BasicValue, BasicValueEnum, CallSiteValue, FloatValue, FunctionValue, IntValue},
     AddressSpace, IntPredicate,
 };
 use itertools::Either;
@@ -565,370 +565,370 @@ pub fn call_j0<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> Flo
         .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 => unreachable!("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 => unreachable!("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 => unreachable!("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 => unreachable!("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,
-        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 => unreachable!("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()),
-    )
-}
+// /// 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 => unreachable!("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 => unreachable!("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 => unreachable!("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 => unreachable!("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,
+//         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 => unreachable!("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()),
+//     )
+// }
 
 fn get_size_variant<'ctx>(ty: IntType<'ctx>) -> SizeVariant {
     match ty.get_bit_width() {
@@ -965,21 +965,28 @@ where
     })
 }
 
-fn get_ndarray_struct_ptr<'ctx>(ctx: &'ctx Context, size_type: IntType<'ctx>) -> PointerType<'ctx> {
-    let i8_type = ctx.i8_type();
+fn get_irrt_ndarray_ptr_type<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    size_type: IntType<'ctx>,
+) -> PointerType<'ctx> {
+    let i8_type = ctx.ctx.i8_type();
 
     let ndarray_ty = NpArrayType { size_type, elem_type: i8_type.as_basic_type_enum() };
-    let struct_ty = ndarray_ty.fields().whole_struct.as_struct_type(ctx);
+    let struct_ty = ndarray_ty.get_struct_type(ctx.ctx);
     struct_ty.ptr_type(AddressSpace::default())
 }
 
+fn get_irrt_opaque_uint8_ptr_type<'ctx>(ctx: &CodeGenContext<'ctx, '_>) -> PointerType<'ctx> {
+    ctx.ctx.i8_type().ptr_type(AddressSpace::default())
+}
+
 pub fn call_nac3_ndarray_size<'ctx>(
     ctx: &CodeGenContext<'ctx, '_>,
     ndarray: NpArrayValue<'ctx>,
 ) -> IntValue<'ctx> {
     let size_type = ndarray.ty.size_type;
     let function = get_size_type_dependent_function(ctx, size_type, "__nac3_ndarray_size", || {
-        size_type.fn_type(&[get_ndarray_struct_ptr(ctx.ctx, size_type).into()], false)
+        size_type.fn_type(&[get_irrt_ndarray_ptr_type(ctx, size_type).into()], false)
     });
 
     ctx.builder
@@ -989,3 +996,44 @@ pub fn call_nac3_ndarray_size<'ctx>(
         .unwrap_left()
         .into_int_value()
 }
+
+pub fn call_nac3_ndarray_fill_generic<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NpArrayValue<'ctx>,
+    fill_value: BasicValueEnum<'ctx>,
+) {
+    // Sanity check on type of `fill_value`
+    check_basic_types_match(ndarray.ty.elem_type, fill_value.get_type().as_basic_type_enum())
+        .unwrap();
+
+    let size_type = ndarray.ty.size_type;
+    let function =
+        get_size_type_dependent_function(ctx, size_type, "__nac3_ndarray_fill_generic", || {
+            ctx.ctx.void_type().fn_type(
+                &[
+                    get_irrt_ndarray_ptr_type(ctx, size_type).into(), // NDArray<SizeT>* ndarray
+                    get_irrt_opaque_uint8_ptr_type(ctx).into(), // uint8_t* pvalue
+                ],
+                false,
+            )
+        });
+
+    // Put `fill_value` onto the stack and get a pointer to it, and that pointer will be `pvalue`
+    let pvalue = ctx.builder.build_alloca(ndarray.ty.elem_type, "fill_value").unwrap();
+    ctx.builder.build_store(pvalue, fill_value).unwrap();
+
+    // Cast pvalue to `uint8_t*`
+    let pvalue = ctx.builder.build_pointer_cast(pvalue, get_irrt_opaque_uint8_ptr_type(ctx), "").unwrap();
+
+    // Call the IRRT function
+    ctx.builder
+        .build_call(
+            function,
+            &[
+                ndarray.ptr.into(), // ndarray
+                pvalue.into(),      // pvalue
+            ],
+            "",
+        )
+        .unwrap();
+}

nac3core/src/codegen/mod.rs

@@ -7,6 +7,7 @@ use crate::{
         typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
     },
 };
+use classes::NpArrayType;
 use crossbeam::channel::{unbounded, Receiver, Sender};
 use inkwell::{
     attributes::{Attribute, AttributeLoc},
@@ -476,7 +477,11 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
                                 ctx, module, generator, unifier, top_level, type_cache, dtype,
                             );
 
-                            NDArrayType::new(generator, ctx, element_type).as_base_type().into()
+                            let ndarray_ty = NpArrayType {
+                                size_type: generator.get_size_type(ctx),
+                                elem_type: element_type,
+                            };
+                            ndarray_ty.get_struct_type(ctx).as_basic_type_enum()
                         }
 
                         _ => unreachable!(

nac3core/src/codegen/numpy.rs

@@ -2,15 +2,11 @@ use crate::{
     codegen::{
         classes::{
             ArrayLikeIndexer, ArrayLikeValue, ListType, ListValue, NDArrayType, NDArrayValue,
-            ProxyType, ProxyValue, TypedArrayLikeAccessor, TypedArrayLikeAdapter,
+            NpArrayType, ProxyType, ProxyValue, TypedArrayLikeAccessor, TypedArrayLikeAdapter,
             TypedArrayLikeMutator, UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
         },
         expr::gen_binop_expr_with_values,
-        irrt::{
-            calculate_len_for_slice_range, call_ndarray_calc_broadcast,
-            call_ndarray_calc_broadcast_index, call_ndarray_calc_nd_indices,
-            call_ndarray_calc_size,
-        },
+        irrt::call_nac3_ndarray_fill_generic,
         llvm_intrinsics::{self, call_memcpy_generic},
         stmt::{gen_for_callback_incrementing, gen_for_range_callback, gen_if_else_expr_callback},
         CodeGenContext, CodeGenerator,
@@ -26,7 +22,7 @@ use crate::{
         typedef::{FunSignature, Type, TypeEnum},
     },
 };
-use inkwell::types::{AnyTypeEnum, BasicTypeEnum, PointerType};
+use inkwell::types::{AnyTypeEnum, BasicTypeEnum, IntType, PointerType};
 use inkwell::{
     types::BasicType,
     values::{BasicValueEnum, IntValue, PointerValue},
@@ -34,6 +30,8 @@ use inkwell::{
 };
 use nac3parser::ast::{Operator, StrRef};
 
+use super::{classes::NpArrayValue, stmt::gen_return};
+
 // /// Creates an uninitialized `NDArray` instance.
 // fn create_ndarray_uninitialized<'ctx, G: CodeGenerator + ?Sized>(
 //     generator: &mut G,
@@ -2015,3 +2013,335 @@ use nac3parser::ast::{Operator, StrRef};
 //     Ok(())
 // }
 //
+
+fn simple_assert<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    cond: IntValue<'ctx>,
+    msg: &str,
+) where
+    G: CodeGenerator + ?Sized,
+{
+    let mut full_msg = String::from("simple_assert failed: ");
+    full_msg.push_str(msg);
+    ctx.make_assert(
+        generator,
+        cond,
+        "0:ValueError",
+        full_msg.as_str(),
+        [None, None, None],
+        ctx.current_loc,
+    );
+}
+
+fn copy_array_slice<'ctx, G, Src, Dst>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    dst: Dst,
+    src: Src,
+) where
+    G: CodeGenerator + ?Sized,
+    Dst: TypedArrayLikeMutator<'ctx, IntType<'ctx>>,
+    Src: TypedArrayLikeAccessor<'ctx, IntType<'ctx>>,
+{
+    // Sanity check
+    let len_match = ctx
+        .builder
+        .build_int_compare(
+            IntPredicate::EQ,
+            src.size(ctx, generator),
+            dst.size(ctx, generator),
+            "len_match",
+        )
+        .unwrap();
+    simple_assert(generator, ctx, len_match, "copy_array_slice length mismatched");
+
+    let size_type = generator.get_size_type(ctx.ctx);
+
+    let init_val = size_type.const_zero();
+    let max_val = (dst.size(ctx, generator), false);
+    let incr_val = size_type.const_int(1, false);
+    gen_for_callback_incrementing(
+        generator,
+        ctx,
+        init_val,
+        max_val,
+        |generator, ctx, _hooks, idx| {
+            let value = src.get_typed(ctx, generator, &idx, Some("copy_array_slice.tmp"));
+            dst.set_typed(ctx, generator, &idx, value);
+            Ok(())
+        },
+        incr_val,
+    )
+    .unwrap();
+}
+
+pub fn alloca_ndarray_uninitialized<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    elem_type: BasicTypeEnum<'ctx>,
+    ndims: IntValue<'ctx>,
+    name: Option<&str>,
+) -> Result<NpArrayValue<'ctx>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let size_type = generator.get_size_type(ctx.ctx);
+    let ndarray_ty = NpArrayType { size_type, elem_type };
+    let ndarray = ndarray_ty.var_alloc(generator, ctx, ndims, name);
+    Ok(ndarray)
+}
+
+pub struct Producer<'ctx, G: CodeGenerator + ?Sized, T> {
+    pub count: IntValue<'ctx>,
+    pub write_to_slice: Box<
+        dyn Fn(
+                &mut G,
+                &mut CodeGenContext<'ctx, '_>,
+                &TypedArrayLikeAdapter<'ctx, T>,
+            ) -> Result<(), String>
+            + 'ctx,
+    >,
+}
+
+/// TODO: UPDATE DOCUMENTATION
+/// LLVM-typed implementation for generating a [`Producer`] that sets a list of ints.
+///
+/// * `elem_ty` - The element type of the `NDArray`.
+/// * `shape` - The `shape` parameter used to construct the `NDArray`.
+///
+/// ### Notes on `shape`
+///
+/// Just like numpy, the `shape` argument can be:
+///   1. A list of `int32`;   e.g., `np.empty([600, 800, 3])`
+///   2. A tuple of `int32`;  e.g., `np.empty((600, 800, 3))`
+///   3. A scalar `int32`;     e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
+///
+/// See also [`typecheck::type_inferencer::fold_numpy_function_call_shape_argument`] to
+/// learn how `shape` gets from being a Python user expression to here.
+fn parse_input_shape_arg<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    shape: BasicValueEnum<'ctx>,
+    shape_ty: Type,
+) -> Result<Producer<'ctx, G, IntValue<'ctx>>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let size_type = generator.get_size_type(ctx.ctx);
+
+    match &*ctx.unifier.get_ty(shape_ty) {
+        TypeEnum::TObj { obj_id, .. }
+            if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
+        {
+            // 1. A list of ints; e.g., `np.empty([600, 800, 3])`
+
+            // A list has to be a PointerValue
+            let shape_list = ListValue::from_ptr_val(shape.into_pointer_value(), size_type, None);
+
+            // Create `Producer`
+            let ndims = shape_list.load_size(ctx, Some("count"));
+            Ok(Producer {
+                count: ndims,
+                write_to_slice: Box::new(move |ctx, generator, dst_slice| {
+                    // Basically iterate through the list and write to `dst_slice` accordingly
+                    let init_val = size_type.const_zero();
+                    let max_val = (ndims, false);
+                    let incr_val = size_type.const_int(1, false);
+                    gen_for_callback_incrementing(
+                        ctx,
+                        generator,
+                        init_val,
+                        max_val,
+                        |generator, ctx, _hooks, idx| {
+                            // Get the dimension at `idx`
+                            let dim =
+                                shape_list.data().get(ctx, generator, &idx, None).into_int_value();
+
+                            // Cast `dim` to SizeT
+                            let dim = ctx
+                                .builder
+                                .build_int_s_extend_or_bit_cast(dim, size_type, "dim_casted")
+                                .unwrap();
+
+                            // Write
+                            dst_slice.set_typed(ctx, generator, &idx, dim);
+                            Ok(())
+                        },
+                        incr_val,
+                    )?;
+                    Ok(())
+                }),
+            })
+        }
+        TypeEnum::TTuple { ty: tuple_types } => {
+            // 2. A tuple of ints; e.g., `np.empty((600, 800, 3))`
+
+            // Get the length/size of the tuple, which also happens to be the value of `ndims`.
+            let ndims = tuple_types.len();
+
+            // A tuple has to be a StructValue
+            // Read [`codegen::expr::gen_expr`] to see how `nac3core` translates a Python tuple into LLVM.
+            let shape_tuple = shape.into_struct_value();
+
+            Ok(Producer {
+                count: size_type.const_int(ndims as u64, false),
+                write_to_slice: Box::new(move |generator, ctx, dst_slice| {
+                    for dim_i in 0..ndims {
+                        // Get the dimension at `dim_i`
+                        let dim = ctx
+                            .builder
+                            .build_extract_value(
+                                shape_tuple,
+                                dim_i as u32,
+                                format!("dim{dim_i}").as_str(),
+                            )
+                            .unwrap()
+                            .into_int_value();
+
+                        // Cast `dim` to SizeT
+                        let dim = ctx
+                            .builder
+                            .build_int_s_extend_or_bit_cast(dim, size_type, "dim_casted")
+                            .unwrap();
+
+                        // Write
+                        dst_slice.set_typed(
+                            ctx,
+                            generator,
+                            &size_type.const_int(dim_i as u64, false),
+                            dim,
+                        );
+                    }
+                    Ok(())
+                }),
+            })
+        }
+        TypeEnum::TObj { obj_id, .. }
+            if *obj_id == ctx.primitives.int32.obj_id(&ctx.unifier).unwrap() =>
+        {
+            // 3. A scalar int; e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
+
+            // The value has to be an integer
+            let shape_int = shape.into_int_value();
+
+            Ok(Producer {
+                count: size_type.const_int(1, false),
+                write_to_slice: Box::new(move |generator, ctx, dst_slice| {
+                    // Only index 0 is set with the input value
+                    let dim_i = size_type.const_zero();
+
+                    // Cast `shape_int` to SizeT
+                    let dim = ctx
+                        .builder
+                        .build_int_s_extend_or_bit_cast(shape_int, size_type, "dim_casted")
+                        .unwrap();
+
+                    // Write
+                    dst_slice.set_typed(ctx, generator, &dim_i, dim);
+                    Ok(())
+                }),
+            })
+        }
+        _ => panic!("parse_input_shape_arg encountered unknown type"),
+    }
+}
+
+/// TODO: DOCUMENT ME
+fn alloca_ndarray_uninitialized_shaped<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    elem_type: BasicTypeEnum<'ctx>,
+    shape_producer: Producer<'ctx, G, IntValue<'ctx>>,
+    name: Option<&str>,
+) -> Result<NpArrayValue<'ctx>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    // Allocate an uninitialized ndarray
+    let ndims = shape_producer.count;
+    let ndarray = alloca_ndarray_uninitialized(generator, ctx, elem_type, ndims, name)?;
+
+    // Fill `ndarray.shape` with `shape_producer`
+    (shape_producer.write_to_slice)(generator, ctx, &ndarray.shape_slice(ctx))?;
+    Ok(ndarray)
+}
+
+/// LLVM-typed implementation for generating the implementation for constructing an empty `NDArray`.
+fn call_ndarray_empty_impl<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    elem_ty: Type,
+    shape: BasicValueEnum<'ctx>,
+    shape_ty: Type,
+    name: Option<&str>,
+) -> Result<NpArrayValue<'ctx>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let elem_type = ctx.get_llvm_type(generator, elem_ty);
+    let shape_producer = parse_input_shape_arg(generator, ctx, shape, shape_ty)?;
+    alloca_ndarray_uninitialized_shaped(generator, ctx, elem_type, shape_producer, name)
+}
+
+/// Generates LLVM IR for `np.empty`.
+pub fn gen_ndarray_empty<'ctx>(
+    context: &mut CodeGenContext<'ctx, '_>,
+    obj: &Option<(Type, ValueEnum<'ctx>)>,
+    fun: (&FunSignature, DefinitionId),
+    args: &[(Option<StrRef>, ValueEnum<'ctx>)],
+    generator: &mut dyn CodeGenerator,
+) -> Result<PointerValue<'ctx>, String> {
+    assert!(obj.is_none());
+    assert_eq!(args.len(), 1);
+
+    let shape_ty = fun.0.args[0].ty;
+    let shape = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
+
+    let ndarray = call_ndarray_empty_impl(
+        generator,
+        context,
+        context.primitives.float,
+        shape,
+        shape_ty,
+        None,
+    )?;
+    Ok(ndarray.ptr)
+}
+
+/// Generates LLVM IR for `np.zeros`.
+///
+/// NOTE: Current `dtype` is always `float64`.
+pub fn gen_ndarray_zeros<'ctx>(
+    context: &mut CodeGenContext<'ctx, '_>,
+    obj: &Option<(Type, ValueEnum<'ctx>)>,
+    fun: (&FunSignature, DefinitionId),
+    args: &[(Option<StrRef>, ValueEnum<'ctx>)],
+    generator: &mut dyn CodeGenerator,
+) -> Result<PointerValue<'ctx>, String> {
+    assert!(obj.is_none());
+    assert_eq!(args.len(), 1);
+
+    let shape_ty = fun.0.args[0].ty;
+    let shape = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
+
+    // Allocate an ndarray and fill it later
+    let ndarray = call_ndarray_empty_impl(
+        generator,
+        context,
+        context.primitives.float, // float64
+        shape,
+        shape_ty,
+        None,
+    )?;
+
+    // TRICK: The float64 type could be conveniently extracted out of `ndarray`
+    let float_type = ndarray.ty.elem_type.into_float_type();
+
+    // Fill the ndarray
+    call_nac3_ndarray_fill_generic(context, ndarray, float_type.const_float(1.0).into());
+
+    // Return our ndarray
+    println!("ndarray.ptr = {}", ndarray.ptr);
+    Ok(ndarray.ptr)
+}

nac3core/src/lib.rs

@@ -23,4 +23,4 @@ pub mod codegen;
 pub mod symbol_resolver;
 pub mod toplevel;
 pub mod typecheck;
-pub mod util;
+pub mod util;

nac3core/src/toplevel/builtins.rs

@@ -1193,14 +1193,13 @@ impl<'a> BuiltinBuilder<'a> {
             self.ndarray_float,
             &[(self.ndarray_factory_fn_shape_arg_tvar.ty, "shape")],
             Box::new(move |ctx, obj, fun, args, generator| {
-                todo!()
-                // let func = match prim {
-                //     PrimDef::FunNpNDArray | PrimDef::FunNpEmpty => gen_ndarray_empty,
-                //     PrimDef::FunNpZeros => gen_ndarray_zeros,
-                //     PrimDef::FunNpOnes => gen_ndarray_ones,
-                //     _ => unreachable!(),
-                // };
-                // func(ctx, &obj, fun, &args, generator).map(|val| Some(val.as_basic_value_enum()))
+                let func = match prim {
+                    PrimDef::FunNpNDArray | PrimDef::FunNpEmpty => gen_ndarray_empty,
+                    PrimDef::FunNpZeros => gen_ndarray_zeros,
+                    PrimDef::FunNpOnes => todo!(), // gen_ndarray_ones,
+                    _ => unreachable!(),
+                };
+                func(ctx, &obj, fun, &args, generator).map(|val| Some(val.as_basic_value_enum()))
             }),
         )
     }

nac3core/src/util.rs

@@ -0,0 +1,5 @@
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+pub enum SizeVariant {
+    Bits32,
+    Bits64,
+}

nac3standalone/demo/src/my_ndarray.py

@@ -0,0 +1,3 @@
+def run() -> int32:
+    hello = np_zeros((3, 4))
+    return 0

nac3standalone/src/main.rs

@@ -449,6 +449,9 @@ fn main() {
         .create_target_machine(llvm_options.opt_level)
         .expect("couldn't create target machine");
 
+    // NOTE: DEBUG PRINT
+    main.print_to_file("standalone.ll").unwrap();
+
     let pass_options = PassBuilderOptions::create();
     pass_options.set_merge_functions(true);
     let passes = format!("default<O{}>", opt_level as u32);