WIP

compile_irrt.sh

@@ -0,0 +1,3 @@
+#!/usr/bin/env bash
+clang-irrt --target=wasm32 -x c++ -fno-discard-value-names -fno-exceptions -fno-rtti -O0 -emit-llvm -S -Wall -Wextra nac3core/irrt/irrt.cpp
+clang -x c++ -fno-discard-value-names -fno-exceptions -fno-rtti -O0 -emit-llvm -S -Wall -Wextra nac3core/irrt/irrt_test.cpp

flake.nix

@@ -41,7 +41,7 @@
               '';
             installPhase =
               ''
-              PYTHON_SITEPACKAGES=$out/${pkgs.python3Packages.python.sitePackages}
+u             PYTHON_SITEPACKAGES=$out/${pkgs.python3Packages.python.sitePackages}
               mkdir -p $PYTHON_SITEPACKAGES
               cp target/x86_64-unknown-linux-gnu/release/libnac3artiq.so $PYTHON_SITEPACKAGES/nac3artiq.so
 
@@ -163,7 +163,10 @@
           clippy
           pre-commit
           rustfmt
+          rust-analyzer
         ];
+        # https://nixos.wiki/wiki/Rust#Shell.nix_example
+        RUST_SRC_PATH = "${pkgs.rust.packages.stable.rustPlatform.rustLibSrc}";
       };
       devShells.x86_64-linux.msys2 = pkgs.mkShell {
         name = "nac3-dev-shell-msys2";

nac3core/build.rs

@@ -31,6 +31,7 @@ fn compile_irrt(irrt_dir: &Path, out_dir: &Path) {
         "-S",
         "-Wall",
         "-Wextra",
+        "-Werror=return-type",
         "-I",
         irrt_dir.to_str().unwrap(),
         "-o",
@@ -100,6 +101,7 @@ fn compile_irrt_test(irrt_dir: &Path, out_dir: &Path) {
         "-O0",
         "-Wall",
         "-Wextra",
+        "-Werror=return-type",
         "-lm", // for `tgamma()`, `lgamma()`
         "-o",
         exe_path.to_str().unwrap(),

nac3core/irrt/irrt.cpp

@@ -1,3 +1,5 @@
-#include "irrt.hpp"
+#include "irrt_everything.hpp"
 
-// All the implementations are from `irrt.hpp`
+/*
+    This file will be read by `clang-irrt` to conveniently produce LLVM IR for `nac3core/codegen`.
+*/

nac3core/irrt/irrt_basic.hpp

@@ -1,28 +1,19 @@
-#ifndef IRRT_DONT_TYPEDEF_INTS
+#pragma once
-typedef _BitInt(8) int8_t;
+
-typedef unsigned _BitInt(8) uint8_t;
+#include "irrt_utils.hpp"
-typedef _BitInt(32) int32_t;
+#include "irrt_typedefs.hpp"
-typedef unsigned _BitInt(32) uint32_t;
+
-typedef _BitInt(64) int64_t;
+/*
-typedef unsigned _BitInt(64) uint64_t;
+    This header contains IRRT implementations
-#endif
+    that do not deserved to be categorized (e.g., into numpy, etc.)
+
+    Check out other *.hpp files before including them here!!
+*/
 
-// NDArray indices are always `uint32_t`.
-typedef uint32_t NDIndex;
 // The type of an index or a value describing the length of a range/slice is
 // always `int32_t`.
 typedef int32_t SliceIndex;
 
-template <typename T>
-static T max(T a, T b) {
-    return a > b ? a : b;
-}
-
-template <typename T>
-static T min(T a, T b) {
-    return a > b ? b : a;
-}
-
 // adapted from GNU Scientific Library: https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
 // need to make sure `exp >= 0` before calling this function
 template <typename T>
@@ -39,119 +30,6 @@ static T __nac3_int_exp_impl(T base, T exp) {
     return res;
 }
 
-template <typename SizeT>
-static SizeT __nac3_ndarray_calc_size_impl(
-    const SizeT *list_data,
-    SizeT list_len,
-    SizeT begin_idx,
-    SizeT end_idx
-) {
-    __builtin_assume(end_idx <= list_len);
-
-    SizeT num_elems = 1;
-    for (SizeT i = begin_idx; i < end_idx; ++i) {
-        SizeT val = list_data[i];
-        __builtin_assume(val > 0);
-        num_elems *= val;
-    }
-    return num_elems;
-}
-
-template <typename SizeT>
-static void __nac3_ndarray_calc_nd_indices_impl(
-    SizeT index,
-    const SizeT *dims,
-    SizeT num_dims,
-    NDIndex *idxs
-) {
-    SizeT stride = 1;
-    for (SizeT dim = 0; dim < num_dims; dim++) {
-        SizeT i = num_dims - dim - 1;
-        __builtin_assume(dims[i] > 0);
-        idxs[i] = (index / stride) % dims[i];
-        stride *= dims[i];
-    }
-}
-
-template <typename SizeT>
-static SizeT __nac3_ndarray_flatten_index_impl(
-    const SizeT *dims,
-    SizeT num_dims,
-    const NDIndex *indices,
-    SizeT num_indices
-) {
-    SizeT idx = 0;
-    SizeT stride = 1;
-    for (SizeT i = 0; i < num_dims; ++i) {
-        SizeT ri = num_dims - i - 1;
-        if (ri < num_indices) {
-            idx += stride * indices[ri];
-        }
-
-        __builtin_assume(dims[i] > 0);
-        stride *= dims[ri];
-    }
-    return idx;
-}
-
-template <typename SizeT>
-static void __nac3_ndarray_calc_broadcast_impl(
-    const SizeT *lhs_dims,
-    SizeT lhs_ndims,
-    const SizeT *rhs_dims,
-    SizeT rhs_ndims,
-    SizeT *out_dims
-) {
-    SizeT max_ndims = lhs_ndims > rhs_ndims ? lhs_ndims : rhs_ndims;
-
-    for (SizeT i = 0; i < max_ndims; ++i) {
-        const SizeT *lhs_dim_sz = i < lhs_ndims ? &lhs_dims[lhs_ndims - i - 1] : nullptr;
-        const SizeT *rhs_dim_sz = i < rhs_ndims ? &rhs_dims[rhs_ndims - i - 1] : nullptr;
-        SizeT *out_dim = &out_dims[max_ndims - i - 1];
-
-        if (lhs_dim_sz == nullptr) {
-            *out_dim = *rhs_dim_sz;
-        } else if (rhs_dim_sz == nullptr) {
-            *out_dim = *lhs_dim_sz;
-        } else if (*lhs_dim_sz == 1) {
-            *out_dim = *rhs_dim_sz;
-        } else if (*rhs_dim_sz == 1) {
-            *out_dim = *lhs_dim_sz;
-        } else if (*lhs_dim_sz == *rhs_dim_sz) {
-            *out_dim = *lhs_dim_sz;
-        } else {
-            __builtin_unreachable();
-        }
-    }
-}
-
-template <typename SizeT>
-static void __nac3_ndarray_calc_broadcast_idx_impl(
-    const SizeT *src_dims,
-    SizeT src_ndims,
-    const NDIndex *in_idx,
-    NDIndex *out_idx
-) {
-    for (SizeT i = 0; i < src_ndims; ++i) {
-        SizeT src_i = src_ndims - i - 1;
-        out_idx[src_i] = src_dims[src_i] == 1 ? 0 : in_idx[src_i];
-    }
-}
-
-template<typename SizeT>
-static void __nac3_ndarray_strides_from_shape_impl(
-    SizeT ndims,
-    SizeT *shape,
-    SizeT *dst_strides
-) {
-    SizeT stride_product = 1;
-    for (SizeT i = 0; i < ndims; i++) {
-        int dim_i = ndims - i - 1;
-        dst_strides[dim_i] = stride_product;
-        stride_product *= shape[dim_i];
-    }
-}
-
 extern "C" {
     #define DEF_nac3_int_exp_(T) \
         T __nac3_int_exp_##T(T base, T exp) {\
@@ -334,104 +212,4 @@ extern "C" {
 
         return j0(x);
     }
-
-    uint32_t __nac3_ndarray_calc_size(
-        const uint32_t *list_data,
-        uint32_t list_len,
-        uint32_t begin_idx,
-        uint32_t end_idx
-    ) {
-        return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
-    }
-
-    uint64_t __nac3_ndarray_calc_size64(
-        const uint64_t *list_data,
-        uint64_t list_len,
-        uint64_t begin_idx,
-        uint64_t end_idx
-    ) {
-        return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
-    }
-
-    void __nac3_ndarray_calc_nd_indices(
-        uint32_t index,
-        const uint32_t* dims,
-        uint32_t num_dims,
-        NDIndex* idxs
-    ) {
-        __nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
-    }
-
-    void __nac3_ndarray_calc_nd_indices64(
-        uint64_t index,
-        const uint64_t* dims,
-        uint64_t num_dims,
-        NDIndex* idxs
-    ) {
-        __nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
-    }
-
-    uint32_t __nac3_ndarray_flatten_index(
-        const uint32_t* dims,
-        uint32_t num_dims,
-        const NDIndex* indices,
-        uint32_t num_indices
-    ) {
-        return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
-    }
-
-    uint64_t __nac3_ndarray_flatten_index64(
-        const uint64_t* dims,
-        uint64_t num_dims,
-        const NDIndex* indices,
-        uint64_t num_indices
-    ) {
-        return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
-    }
-
-    void __nac3_ndarray_calc_broadcast(
-        const uint32_t *lhs_dims,
-        uint32_t lhs_ndims,
-        const uint32_t *rhs_dims,
-        uint32_t rhs_ndims,
-        uint32_t *out_dims
-    ) {
-        return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
-    }
-
-    void __nac3_ndarray_calc_broadcast64(
-        const uint64_t *lhs_dims,
-        uint64_t lhs_ndims,
-        const uint64_t *rhs_dims,
-        uint64_t rhs_ndims,
-        uint64_t *out_dims
-    ) {
-        return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
-    }
-
-    void __nac3_ndarray_calc_broadcast_idx(
-        const uint32_t *src_dims,
-        uint32_t src_ndims,
-        const NDIndex *in_idx,
-        NDIndex *out_idx
-    ) {
-        __nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
-    }
-
-    void __nac3_ndarray_calc_broadcast_idx64(
-        const uint64_t *src_dims,
-        uint64_t src_ndims,
-        const NDIndex *in_idx,
-        NDIndex *out_idx
-    ) {
-        __nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
-    }
-
-    void __nac3_ndarray_strides_from_shape(uint32_t ndims, uint32_t* shape, uint32_t* dst_strides) {
-        __nac3_ndarray_strides_from_shape_impl(ndims, shape, dst_strides);
-    }
-
-    void __nac3_ndarray_strides_from_shape64(uint64_t ndims, uint64_t* shape, uint64_t* dst_strides) {
-        __nac3_ndarray_strides_from_shape_impl(ndims, shape, dst_strides);
-    }
 }

nac3core/irrt/irrt_everything.hpp

@@ -0,0 +1,11 @@
+#pragma once
+
+#include "irrt_basic.hpp"
+#include "irrt_numpy_ndarray.hpp"
+
+/*
+    All IRRT implementations.
+
+    We don't have any pre-compiled objects, so we are writing all implementations in headers and
+    concatenate them with `#include` into one massive source file that contains all the IRRT stuff.
+*/

nac3core/irrt/irrt_numpy_ndarray.hpp

@@ -0,0 +1,196 @@
+#pragma once
+
+#include "irrt_utils.hpp"
+#include "irrt_typedefs.hpp"
+
+/*
+    NDArray-related implementations.
+`*/
+
+// NDArray indices are always `uint32_t`.
+using NDIndex = uint32_t;
+
+namespace {
+namespace ndarray_util {
+    // Compute the strides of an ndarray given an ndarray `shape`
+    // and assuming that the ndarray is *fully C-contagious*.
+    //
+    // You might want to read up on https://ajcr.net/stride-guide-part-1/.
+    template <typename SizeT>
+    static void set_strides_by_shape(SizeT ndims, SizeT* dst_strides, const SizeT* shape) {
+        SizeT stride_product = 1;
+        for (SizeT i = 0; i < ndims; i++) {
+            int dim_i = ndims - i - 1;
+            dst_strides[dim_i] = stride_product;
+            stride_product *= shape[dim_i];
+        }
+    }
+
+    // Compute the size/# of elements of an ndarray given its shape
+    template <typename SizeT>
+    static SizeT calc_size_from_shape(SizeT ndims, const SizeT* shape) {
+        SizeT size = 1;
+        for (SizeT dim_i = 0; dim_i < ndims; dim_i++) size *= shape[dim_i];
+        return size;
+    }
+}
+
+template <typename SizeT>
+struct NDArrayIndicesIter {
+    SizeT ndims;
+    const SizeT *shape;
+    SizeT *indices;
+
+    void set_indices_zero() {
+        __builtin_memset(indices, 0, sizeof(SizeT) * ndims);
+    }
+
+    void next() {
+        for (SizeT i = 0; i < ndims; i++) {
+            SizeT dim_i = ndims - i - 1;
+
+            indices[dim_i]++;
+            if (indices[dim_i] < shape[dim_i]) {
+                break;
+            } else {
+                indices[dim_i] = 0;
+            }
+        }
+    }
+};
+
+// The NDArray object. `SizeT` is the *signed* size type of this ndarray.
+//
+// NOTE: The order of fields is IMPORTANT. DON'T TOUCH IT
+//
+// Some resources you might find helpful:
+// - The official numpy implementations:
+//   - https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst
+// - On strides (about reshaping, slicing, C-contagiousness, etc)
+//   - https://ajcr.net/stride-guide-part-1/.
+//   - https://ajcr.net/stride-guide-part-2/.
+//   - https://ajcr.net/stride-guide-part-3/.
+template <typename SizeT>
+struct NDArray {
+    // The underlying data this `ndarray` is pointing to.
+    //
+    // NOTE: Formally this should be of type `void *`, but clang
+    // translates `void *` to `i8 *` when run with `-S -emit-llvm`,
+    // so we will put `uint8_t *` here for clarity.
+    uint8_t *data;
+
+    // The number of bytes of a single element in `data`.
+    //
+    // The `SizeT` is treated as `unsigned`.
+    SizeT itemsize;
+
+    // The number of dimensions of this shape.
+    //
+    // The `SizeT` is treated as `unsigned`.
+    SizeT ndims;
+
+    // Array shape, with length equal to `ndims`.
+    //
+    // The `SizeT` is treated as `unsigned`.
+    //
+    // NOTE: `shape` can contain 0.
+    //   (those appear when the user makes an out of bounds slice into an ndarray, e.g., `np.zeros((3, 3))[400:].shape == (0, 3)`)
+    SizeT *shape;
+
+    // Array strides (stride value is in number of bytes, NOT number of elements), with length equal to `ndims`.
+    //
+    // The `SizeT` is treated as `signed`.
+    //
+    // NOTE: `strides` can have negative numbers.
+    //   (those appear when there is a slice with a negative step, e.g., `my_array[::-1]`)
+    SizeT *strides;
+
+    // Calculate the size/# of elements of an `ndarray`.
+    // This function corresponds to `np.size(<ndarray>)` or `ndarray.size`
+    SizeT size() {
+        return ndarray_util::calc_size_from_shape(ndims, shape);
+    }
+
+    // Calculate the number of bytes of its content of an `ndarray` *in its view*.
+    // This function corresponds to `ndarray.nbytes`
+    SizeT nbytes() {
+        return this->size() * itemsize;
+    }
+
+    void set_value_at_pelement(uint8_t* pelement, uint8_t* pvalue) {
+        __builtin_memcpy(pelement, pvalue, itemsize);
+    }
+
+    uint8_t* get_pelement(SizeT *indices) {
+        uint8_t* element = data;
+        for (SizeT dim_i = 0; dim_i < ndims; dim_i++)
+            element += indices[dim_i] * strides[dim_i] * itemsize;
+        return element;
+    }
+
+    // Is the given `indices` valid/in-bounds?
+    bool in_bounds(SizeT *indices) {
+        for (SizeT dim_i = 0; dim_i < ndims; dim_i++) {
+            bool dim_ok = indices[dim_i] < shape[dim_i];
+            if (!dim_ok) return false;
+        }
+        return true;
+    }
+
+    // Fill the ndarray with a value
+    void fill_generic(uint8_t* pvalue) {
+        NDArrayIndicesIter<SizeT> iter;
+        iter.ndims = this->ndims;
+        iter.shape = this->shape;
+        iter.indices = (SizeT*) __builtin_alloca(sizeof(SizeT) * ndims);
+        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);
+        }
+    }
+
+    // Set the strides of the ndarray with `ndarray_util::set_strides_by_shape`
+    void set_strides_by_shape() {
+        ndarray_util::set_strides_by_shape(ndims, strides, shape);
+    }
+
+    // https://numpy.org/doc/stable/reference/generated/numpy.eye.html
+    void set_to_eye(SizeT k, uint8_t* zero_pvalue, uint8_t* one_pvalue) {
+        __builtin_assume(ndims == 2);
+
+        // TODO: Better implementation
+
+        fill_generic(zero_pvalue);
+        for (SizeT i = 0; i < min(shape[0], shape[1]); i++) {
+            SizeT row = i;
+            SizeT col = i + k;
+            SizeT indices[2] = { row, col };
+
+            if (!in_bounds(indices)) continue;
+
+            uint8_t* pelement = get_pelement(indices);
+            set_value_at_pelement(pelement, one_pvalue);
+        }
+    }
+};
+}
+
+extern "C" {
+    uint32_t __nac3_ndarray_size(NDArray<int32_t>* ndarray) {
+        return ndarray->size();
+    }
+
+    uint64_t __nac3_ndarray_size64(NDArray<int64_t>* ndarray) {
+        return ndarray->size();
+    }
+
+    void __nac3_ndarray_fill_generic(NDArray<int32_t>* ndarray, uint8_t* pvalue) {
+        ndarray->fill_generic(pvalue);
+    }
+
+    void __nac3_ndarray_fill_generic64(NDArray<int64_t>* ndarray, uint8_t* pvalue) {
+        ndarray->fill_generic(pvalue);
+    }
+}

nac3core/irrt/irrt_test.cpp

@@ -2,17 +2,21 @@
 #include <cstdio>
 #include <cstdlib>
 
+// set `IRRT_DONT_TYPEDEF_INTS` because `cstdint` has it all
 #define IRRT_DONT_TYPEDEF_INTS
-#include "irrt.hpp"
+#include "irrt_everything.hpp"
 
-static void __test_fail(const char *file, int line) {
+namespace {
-    // NOTE: Try to make the location info follow a format that
+static void test_fail() {
-    // VSCode/other IDEs would recognize as a clickable URL.
+    printf("[!] Test failed\n");
-    printf("[!] test_fail() invoked at %s:%d", file, line);
     exit(1);
 }
 
-#define test_fail() __test_fail(__FILE__, __LINE__);
+static void __begin_test(const char* function_name, const char* file, int line) {
+    printf("######### Running %s @ %s:%d\n", function_name, file, line);
+}
+
+#define BEGIN_TEST() __begin_test(__FUNCTION__, __FILE__, __LINE__)
 
 template <typename T>
 bool arrays_match(int len, T *as, T *bs) {
@@ -23,40 +27,163 @@ bool arrays_match(int len, T *as, T *bs) {
 }
 
 template <typename T>
-void debug_print_array(const char* format, int len, T *as) {
+void debug_print_array(const char* format, int len, T* as) {
     printf("[");
     for (int i = 0; i < len; i++) {
         if (i != 0) printf(", ");
         printf(format, as[i]);
     }
-    printf("]\n");
+    printf("]");
 }
 
 template <typename T>
-bool assert_arrays_match(const char *label, const char *format, int len, T *expected, T *got) {
+void assert_arrays_match(const char* label, const char* format, int len, T* expected, T* got) {
-    auto match = arrays_match(len, expected, got);
+    if (!arrays_match(len, expected, got)) {
-
-    if (!match) {
         printf("expected %s: ", label);
         debug_print_array(format, len, expected);
+        printf("\n");
         printf("got %s: ", label);
         debug_print_array(format, len, got);
+        printf("\n");
+        test_fail();
     }
-
-    return match;
 }
 
-static void test_strides_from_shape() {
+template <typename T>
-    const uint64_t ndims = 4;
+void assert_values_match(const char* label, const char* format, T expected, T got) {
-    uint64_t shape[ndims] = { 999, 3, 5, 7 };
+    if (expected != got) {
-    uint64_t strides[ndims] = { 0 };
+        printf("expected %s: ", label);
-    __nac3_ndarray_strides_from_shape64(ndims, shape, strides);
+        printf(format, expected);
+        printf("\n");
+        printf("got %s: ", label);
+        printf(format, got);
+        printf("\n");
+        test_fail();
+    }
+}
 
-    uint64_t expected_strides[ndims] = { 3*5*7, 5*7, 7, 1 };
+void test_calc_size_from_shape_normal() {
-    if (!assert_arrays_match("strides", "%u", ndims, expected_strides, strides)) test_fail();
+    // Test shapes with normal values
+    BEGIN_TEST();
+
+    int32_t shape[4] = { 2, 3, 5, 7 };
+    debug_print_array("%d", 4, shape);
+    assert_values_match("size", "%d", 210, ndarray_util::calc_size_from_shape<int32_t>(4, shape));
+}
+
+void test_calc_size_from_shape_has_zero() {
+    // Test shapes with 0 in them
+    BEGIN_TEST();
+
+    int32_t shape[4] = { 2, 0, 5, 7 };
+    assert_values_match("size", "%d", 0, ndarray_util::calc_size_from_shape<int32_t>(4, shape));
+}
+
+void test_set_strides_by_shape() {
+    // Test `set_strides_by_shape()`
+    BEGIN_TEST();
+
+    int32_t shape[4] = { 99, 3, 5, 7 };
+    int32_t strides[4] = { 0 };
+    ndarray_util::set_strides_by_shape(4, strides, shape);
+
+    int32_t expected_strides[4] = { 105, 35, 7, 1 };
+    assert_arrays_match("strides", "%u", 4u, expected_strides, strides);
+}
+
+void test_ndarray_indices_iter_normal() {
+    // Test NDArrayIndicesIter normal behavior
+    BEGIN_TEST();
+
+    int32_t shape[3] = { 1, 2, 3 };
+    int32_t indices[3] = { 0, 0, 0 };
+    auto iter = NDArrayIndicesIter<int32_t> {
+        .ndims = 3u,
+        .shape = shape,
+        .indices = indices
+    };
+
+    assert_arrays_match("indices #0", "%u", 3u, iter.indices, (int32_t[3]) { 0, 0, 0 });
+    iter.next();
+    assert_arrays_match("indices #1", "%u", 3u, iter.indices, (int32_t[3]) { 0, 0, 1 });
+    iter.next();
+    assert_arrays_match("indices #2", "%u", 3u, iter.indices, (int32_t[3]) { 0, 0, 2 });
+    iter.next();
+    assert_arrays_match("indices #3", "%u", 3u, iter.indices, (int32_t[3]) { 0, 1, 0 });
+    iter.next();
+    assert_arrays_match("indices #4", "%u", 3u, iter.indices, (int32_t[3]) { 0, 1, 1 });
+    iter.next();
+    assert_arrays_match("indices #5", "%u", 3u, iter.indices, (int32_t[3]) { 0, 1, 2 });
+    iter.next();
+    assert_arrays_match("indices #6", "%u", 3u, iter.indices, (int32_t[3]) { 0, 0, 0 }); // Loops back
+    iter.next();
+    assert_arrays_match("indices #7", "%u", 3u, iter.indices, (int32_t[3]) { 0, 0, 1 });
+}
+
+void test_ndarray_fill_generic() {
+    // Test ndarray fill_generic
+    BEGIN_TEST();
+
+    // Choose a type that's neither int32_t nor uint64_t (candidates of SizeT) to spice it up
+    // Also make all the octets non-zero, to see if `memcpy` in `fill_generic` is working perfectly.
+    uint16_t fill_value = 0xFACE;
+
+    uint16_t in_data[6] = { 100, 101, 102, 103, 104, 105 }; // Fill `data` with values that != `999`
+    int32_t in_itemsize = sizeof(uint16_t);
+    const int32_t in_ndims = 2;
+    int32_t in_shape[in_ndims] = { 2, 3 };
+    int32_t in_strides[in_ndims] = {};
+    NDArray<int32_t> ndarray = {
+        .data = (uint8_t*) in_data,
+        .itemsize = in_itemsize,
+        .ndims = in_ndims,
+        .shape = in_shape,
+        .strides = in_strides,
+    };
+    ndarray.set_strides_by_shape();
+    ndarray.fill_generic((uint8_t*) &fill_value); // `fill_generic` here
+
+    uint16_t expected_data[6] = { fill_value, fill_value, fill_value, fill_value, fill_value, fill_value };
+    assert_arrays_match("data", "0x%hX", 6, expected_data, in_data);
+}
+
+void test_ndarray_set_to_eye() {
+    double in_data[9] = { 99.0, 99.0, 99.0, 99.0, 99.0, 99.0, 99.0, 99.0, 99.0 };
+    int32_t in_itemsize = sizeof(double);
+    const int32_t in_ndims = 2;
+    int32_t in_shape[in_ndims] = { 3, 3 };
+    int32_t in_strides[in_ndims] = {};
+    NDArray<int32_t> ndarray = {
+        .data = (uint8_t*) in_data,
+        .itemsize = in_itemsize,
+        .ndims = in_ndims,
+        .shape = in_shape,
+        .strides = in_strides,
+    };
+    ndarray.set_strides_by_shape();
+
+    double zero = 0.0;
+    double one = 1.0;
+    ndarray.set_to_eye(1, (uint8_t*) &zero, (uint8_t*) &one);
+
+    assert_values_match("in_data[0]", "%f", 0.0, in_data[0]);
+    assert_values_match("in_data[1]", "%f", 1.0, in_data[1]);
+    assert_values_match("in_data[2]", "%f", 0.0, in_data[2]);
+    assert_values_match("in_data[3]", "%f", 0.0, in_data[3]);
+    assert_values_match("in_data[4]", "%f", 0.0, in_data[4]);
+    assert_values_match("in_data[5]", "%f", 1.0, in_data[5]);
+    assert_values_match("in_data[6]", "%f", 0.0, in_data[6]);
+    assert_values_match("in_data[7]", "%f", 0.0, in_data[7]);
+    assert_values_match("in_data[8]", "%f", 0.0, in_data[8]);
+}
 }
 
 int main() {
-    test_strides_from_shape();
+    test_calc_size_from_shape_normal();
+    test_calc_size_from_shape_has_zero();
+    test_set_strides_by_shape();
+    test_ndarray_indices_iter_normal();
+    test_ndarray_fill_generic();
+    test_ndarray_set_to_eye();
     return 0;
 }

nac3core/irrt/irrt_typedefs.hpp

@@ -0,0 +1,12 @@
+#pragma once
+
+// This is made toggleable since `irrt_test.cpp` itself would include
+// headers that define the `int_t` family.
+#ifndef IRRT_DONT_TYPEDEF_INTS
+typedef _BitInt(8) int8_t;
+typedef unsigned _BitInt(8) uint8_t;
+typedef _BitInt(32) int32_t;
+typedef unsigned _BitInt(32) uint32_t;
+typedef _BitInt(64) int64_t;
+typedef unsigned _BitInt(64) uint64_t;
+#endif

nac3core/irrt/irrt_utils.hpp

@@ -0,0 +1,11 @@
+#pragma once
+
+template <typename T>
+static T max(T a, T b) {
+    return a > b ? a : b;
+}
+
+template <typename T>
+static T min(T a, T b) {
+    return a > b ? b : a;
+}

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

nac3core/src/codegen/classes.rs

@@ -1,8 +1,6 @@
 use crate::codegen::{
-    irrt::{call_ndarray_calc_size, call_ndarray_flatten_index},
+    llvm_intrinsics::call_int_umin, stmt::gen_for_callback_incrementing, CodeGenContext,
-    llvm_intrinsics::call_int_umin,
+    CodeGenerator,
-    stmt::gen_for_callback_incrementing,
-    CodeGenContext, CodeGenerator,
 };
 use inkwell::context::Context;
 use inkwell::types::{ArrayType, BasicType, StructType};
@@ -12,6 +10,7 @@ use inkwell::{
     values::{BasicValueEnum, IntValue, PointerValue},
     AddressSpace, IntPredicate,
 };
+use itertools::Itertools;
 
 /// A LLVM type that is used to represent a non-primitive type in NAC3.
 pub trait ProxyType<'ctx>: Into<Self::Base> {
@@ -1601,7 +1600,8 @@ impl<'ctx> ArrayLikeValue<'ctx> for NDArrayDataProxy<'ctx, '_> {
         ctx: &CodeGenContext<'ctx, '_>,
         generator: &G,
     ) -> IntValue<'ctx> {
-        call_ndarray_calc_size(generator, ctx, &self.as_slice_value(ctx, generator), (None, None))
+        todo!()
+        // call_ndarray_calc_size(generator, ctx, &self.as_slice_value(ctx, generator), (None, None))
     }
 }
 
@@ -1675,17 +1675,19 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
             indices_elem_ty.get_bit_width()
         );
 
-        let index = call_ndarray_flatten_index(generator, ctx, *self.0, indices);
+        todo!()
 
-        unsafe {
+        // let index = call_ndarray_flatten_index(generator, ctx, *self.0, indices);
-            ctx.builder
+
-                .build_in_bounds_gep(
+        // unsafe {
-                    self.base_ptr(ctx, generator),
+        //     ctx.builder
-                    &[index],
+        //         .build_in_bounds_gep(
-                    name.unwrap_or_default(),
+        //             self.base_ptr(ctx, generator),
-                )
+        //             &[index],
-                .unwrap()
+        //             name.unwrap_or_default(),
-        }
+        //         )
+        //         .unwrap()
+        // }
     }
 
     fn ptr_offset<G: CodeGenerator + ?Sized>(
@@ -1761,3 +1763,307 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> UntypedArrayLikeMutator<'ctx,
     for NDArrayDataProxy<'ctx, '_>
 {
 }
+
+#[derive(Debug, Clone, Copy)]
+pub struct StructField<'ctx> {
+    /// The GEP index of this struct field.
+    pub gep_index: u32,
+    /// Name of this struct field.
+    ///
+    /// Used for generating names.
+    pub name: &'static str,
+    /// The type of this struct field.
+    pub ty: BasicTypeEnum<'ctx>,
+}
+
+pub struct StructFields<'ctx> {
+    /// Name of the struct.
+    ///
+    /// Used for generating names.
+    pub name: &'static str,
+
+    /// All the [`StructField`]s of this struct.
+    ///
+    /// **NOTE:** The index position of a [`StructField`]
+    /// matches the element's [`StructField::index`].
+    pub fields: Vec<StructField<'ctx>>,
+}
+
+struct StructFieldsBuilder<'ctx> {
+    gep_index_counter: u32,
+    /// Name of the struct to be built.
+    name: &'static str,
+    fields: Vec<StructField<'ctx>>,
+}
+
+impl<'ctx> StructField<'ctx> {
+    pub fn gep(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        ptr: PointerValue<'ctx>,
+    ) -> PointerValue<'ctx> {
+        ctx.builder.build_struct_gep(ptr, self.gep_index, self.name).unwrap()
+    }
+
+    pub fn load(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        ptr: PointerValue<'ctx>,
+    ) -> BasicValueEnum<'ctx> {
+        ctx.builder.build_load(self.gep(ctx, ptr), self.name).unwrap()
+    }
+
+    pub fn store<V>(&self, ctx: &CodeGenContext<'ctx, '_>, ptr: PointerValue<'ctx>, value: V)
+    where
+        V: BasicValue<'ctx>,
+    {
+        ctx.builder.build_store(ptr, value).unwrap();
+    }
+}
+
+type IsInstanceError = String;
+type IsInstanceResult = Result<(), IsInstanceError>;
+
+pub fn check_basic_types_match<'ctx, A, B>(expected: A, got: B) -> IsInstanceResult
+where
+    A: BasicType<'ctx>,
+    B: BasicType<'ctx>,
+{
+    let expected = expected.as_basic_type_enum();
+    let got = got.as_basic_type_enum();
+
+    // Put those logic into here,
+    // otherwise there is always a fallback reporting on any kind of mismatch
+    match (expected, got) {
+        (BasicTypeEnum::IntType(expected), BasicTypeEnum::IntType(got)) => {
+            if expected.get_bit_width() != got.get_bit_width() {
+                return Err(format!(
+                    "Expected IntType ({expected}-bit(s)), got IntType ({got}-bit(s))"
+                ));
+            }
+        }
+        (expected, got) => {
+            if expected != got {
+                return Err(format!("Expected {expected}, got {got}"));
+            }
+        }
+    }
+    Ok(())
+}
+
+impl<'ctx> StructFields<'ctx> {
+    pub fn num_fields(&self) -> u32 {
+        self.fields.len() as u32
+    }
+
+    pub fn as_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)
+    }
+
+    pub fn is_type(&self, scrutinee: StructType<'ctx>) -> IsInstanceResult {
+        // Check scrutinee's number of struct fields
+        if scrutinee.count_fields() != self.num_fields() {
+            return Err(format!(
+                "Expected {expected_count} field(s) in `{struct_name}` type, got {got_count}",
+                struct_name = self.name,
+                expected_count = self.num_fields(),
+                got_count = scrutinee.count_fields(),
+            ));
+        }
+
+        // Check the scrutinee's field types
+        for field in self.fields.iter() {
+            let expected_field_ty = field.ty;
+            let got_field_ty = scrutinee.get_field_type_at_index(field.gep_index).unwrap();
+
+            if let Err(field_err) = check_basic_types_match(expected_field_ty, got_field_ty) {
+                return Err(format!(
+                    "Field GEP index {gep_index} does not match the expected type of ({struct_name}::{field_name}): {field_err}",
+                    gep_index = field.gep_index,
+                    struct_name = self.name,
+                    field_name = field.name,
+                ));
+            }
+        }
+
+        // Done
+        Ok(())
+    }
+}
+
+impl<'ctx> StructFieldsBuilder<'ctx> {
+    fn start(name: &'static str) -> Self {
+        StructFieldsBuilder { gep_index_counter: 0, name, fields: Vec::new() }
+    }
+
+    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 }
+    }
+
+    fn end(self) -> StructFields<'ctx> {
+        StructFields { name: self.name, fields: self.fields }
+    }
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct NpArrayType<'ctx> {
+    pub size_type: IntType<'ctx>,
+    pub elem_type: BasicTypeEnum<'ctx>,
+}
+
+pub struct NpArrayStructFields<'ctx> {
+    pub whole_struct: StructFields<'ctx>,
+    pub data: StructField<'ctx>,
+    pub itemsize: StructField<'ctx>,
+    pub ndims: StructField<'ctx>,
+    pub shape: StructField<'ctx>,
+    pub strides: StructField<'ctx>,
+}
+
+impl<'ctx> NpArrayType<'ctx> {
+    pub fn new_opaque_elem(
+        ctx: &CodeGenContext<'ctx, '_>,
+        size_type: IntType<'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 fields(&self) -> NpArrayStructFields<'ctx> {
+        let mut builder = StructFieldsBuilder::start("NpArray");
+
+        let addrspace = AddressSpace::default();
+
+        let byte_type = self.size_type.get_context().i8_type();
+
+        // Make sure the struct matches PERFECTLY with that defined in `nac3core/irrt`.
+        let data = builder.add_field("data", byte_type.ptr_type(addrspace).into());
+        let itemsize = builder.add_field("itemsize", self.size_type.into());
+        let ndims = builder.add_field("ndims", self.size_type.into());
+        let shape = builder.add_field("shape", self.size_type.ptr_type(addrspace).into());
+        let strides = builder.add_field("strides", self.size_type.ptr_type(addrspace).into());
+
+        NpArrayStructFields { whole_struct: builder.end(), data, itemsize, ndims, shape, strides }
+    }
+
+    /// Allocate an `ndarray` on stack, with the following notes:
+    ///
+    /// - `ndarray.ndims` will be initialized to `in_ndims`.
+    /// - `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(
+        &self,
+        ctx: &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();
+
+        // 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")
+            .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);
+
+        return value;
+    }
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct NpArrayValue<'ctx> {
+    pub ty: NpArrayType<'ctx>,
+    pub ptr: PointerValue<'ctx>,
+}
+
+impl<'ctx> NpArrayValue<'ctx> {
+    pub fn load_ndims(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        let field = self.ty.fields().ndims;
+        field.load(ctx, self.ptr).into_int_value()
+    }
+
+    pub fn store_ndims(&self, ctx: &CodeGenContext<'ctx, '_>, value: IntValue<'ctx>) {
+        let field = self.ty.fields().ndims;
+        field.store(ctx, self.ptr, value);
+    }
+
+    pub fn load_itemsize(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        let field = self.ty.fields().itemsize;
+        field.load(ctx, self.ptr).into_int_value()
+    }
+
+    pub fn store_itemsize(&self, ctx: &CodeGenContext<'ctx, '_>, value: IntValue<'ctx>) {
+        let field = self.ty.fields().itemsize;
+        field.store(ctx, self.ptr, value);
+    }
+
+    pub fn load_shape(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
+        let field = self.ty.fields().shape;
+        field.load(ctx, self.ptr).into_pointer_value()
+    }
+
+    pub fn store_shape(&self, ctx: &CodeGenContext<'ctx, '_>, value: PointerValue<'ctx>) {
+        let field = self.ty.fields().shape;
+        field.store(ctx, self.ptr, value);
+    }
+
+    pub fn load_strides(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
+        let field = self.ty.fields().strides;
+        field.load(ctx, self.ptr).into_pointer_value()
+    }
+
+    pub fn store_strides(&self, ctx: &CodeGenContext<'ctx, '_>, value: PointerValue<'ctx>) {
+        let field = self.ty.fields().strides;
+        field.store(ctx, self.ptr, value);
+    }
+
+    /// TODO: DOCUMENT ME -- NDIMS WOULD NEVER CHANGE!!!!!
+    pub fn shape_slice(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
+        let field = self.ty.fields().shape;
+        field.gep(ctx, self.ptr);
+
+        let ndims = self.load_ndims(ctx);
+
+        TypedArrayLikeAdapter {
+            adapted: ArraySliceValue(self.ptr, 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()),
+        }
+    }
+
+    /// TODO: DOCUMENT ME -- NDIMS WOULD NEVER CHANGE!!!!!
+    pub fn strides_slice(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
+        let field = self.ty.fields().strides;
+        field.gep(ctx, self.ptr);
+
+        let ndims = self.load_ndims(ctx);
+
+        TypedArrayLikeAdapter {
+            adapted: ArraySliceValue(self.ptr, 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

@@ -1,10 +1,14 @@
-use crate::typecheck::typedef::Type;
+use crate::{
+    codegen::classes::{NDArrayType, NpArrayType},
+    typecheck::typedef::Type,
+    util::SizeVariant,
+};
 
 mod test;
 
 use super::{
     classes::{
-        ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue,
+        ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue, NpArrayValue,
         TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
     },
     llvm_intrinsics, CodeGenContext, CodeGenerator,
@@ -16,8 +20,8 @@ use inkwell::{
     context::Context,
     memory_buffer::MemoryBuffer,
     module::Module,
-    types::{BasicTypeEnum, IntType},
+    types::{BasicType, BasicTypeEnum, FunctionType, IntType, PointerType},
-    values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue},
+    values::{BasicValueEnum, CallSiteValue, FloatValue, FunctionValue, IntValue, PointerValue},
     AddressSpace, IntPredicate,
 };
 use itertools::Either;
@@ -565,367 +569,62 @@ 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
+fn get_size_variant<'ctx>(ty: IntType<'ctx>) -> SizeVariant {
-/// calculated total size.
+    match ty.get_bit_width() {
-///
+        32 => SizeVariant::Bits32,
-/// * `dims` - An [`ArrayLikeIndexer`] containing the size of each dimension.
+        64 => SizeVariant::Bits64,
-/// * `range` - The dimension index to begin and end (exclusively) calculating the dimensions for,
+        _ => unreachable!("Unsupported int type bit width {}", ty.get_bit_width()),
-/// 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,
+
+fn get_size_type_dependent_function<'ctx, BuildFuncTypeFn>(
     ctx: &CodeGenContext<'ctx, '_>,
-    dims: &Dims,
+    size_type: IntType<'ctx>,
-    (begin, end): (Option<IntValue<'ctx>>, Option<IntValue<'ctx>>),
+    base_name: &str,
-) -> IntValue<'ctx>
+    build_func_type: BuildFuncTypeFn,
+) -> FunctionValue<'ctx>
 where
-    G: CodeGenerator + ?Sized,
+    BuildFuncTypeFn: Fn() -> FunctionType<'ctx>,
-    Dims: ArrayLikeIndexer<'ctx>,
 {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let mut fn_name = base_name.to_owned();
-    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
+    match get_size_variant(size_type) {
+        SizeVariant::Bits32 => {
+            // The original fn_name is the correct function name
+        }
+        SizeVariant::Bits64 => {
+            // Append "64" at the end, this is the naming convention for 64-bit
+            fn_name.push_str("64");
+        }
+    }
 
-    let ndarray_calc_size_fn_name = match llvm_usize.get_bit_width() {
+    // Get (or declare then get if does not exist) the corresponding function
-        32 => "__nac3_ndarray_calc_size",
+    ctx.module.get_function(&fn_name).unwrap_or_else(|| {
-        64 => "__nac3_ndarray_calc_size64",
+        let fn_type = build_func_type();
-        bw => unreachable!("Unsupported size type bit width: {}", bw),
+        ctx.module.add_function(&fn_name, fn_type, None)
-    };
+    })
-    let ndarray_calc_size_fn_t = llvm_usize.fn_type(
+}
-        &[llvm_pusize.into(), llvm_usize.into(), llvm_usize.into(), llvm_usize.into()],
+
-        false,
+fn get_ndarray_struct_ptr<'ctx>(ctx: &'ctx Context, size_type: IntType<'ctx>) -> PointerType<'ctx> {
-    );
+    let i8_type = ctx.i8_type();
-    let ndarray_calc_size_fn =
+
-        ctx.module.get_function(ndarray_calc_size_fn_name).unwrap_or_else(|| {
+    let ndarray_ty = NpArrayType { size_type, elem_type: i8_type.as_basic_type_enum() };
-            ctx.module.add_function(ndarray_calc_size_fn_name, ndarray_calc_size_fn_t, None)
+    let struct_ty = ndarray_ty.fields().whole_struct.as_struct_type(ctx);
-        });
+    struct_ty.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)
+    });
 
-    let begin = begin.unwrap_or_else(|| llvm_usize.const_zero());
-    let end = end.unwrap_or_else(|| dims.size(ctx, generator));
     ctx.builder
-        .build_call(
+        .build_call(function, &[ndarray.ptr.into()], "size")
-            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()
+        .try_as_basic_value()
+        .unwrap_left()
+        .into_int_value()
 }
-
-/// 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()),
-    )
-}

nac3core/src/lib.rs

@@ -23,3 +23,4 @@ pub mod codegen;
 pub mod symbol_resolver;
 pub mod toplevel;
 pub mod typecheck;
+pub mod util;

nac3core/src/toplevel/builtins.rs

@@ -1,5 +1,6 @@
 use std::iter::once;
 
+use crate::util::SizeVariant;
 use helper::{debug_assert_prim_is_allowed, make_exception_fields, PrimDefDetails};
 use indexmap::IndexMap;
 use inkwell::{
@@ -278,19 +279,10 @@ pub fn get_builtins(unifier: &mut Unifier, primitives: &PrimitiveStore) -> Built
         .collect()
 }
 
-/// A helper enum used by [`BuiltinBuilder`]
+fn size_variant_to_int_type(variant: SizeVariant, primitives: &PrimitiveStore) -> Type {
-#[derive(Clone, Copy)]
+    match variant {
-enum SizeVariant {
+        SizeVariant::Bits32 => primitives.int32,
-    Bits32,
+        SizeVariant::Bits64 => primitives.int64,
-    Bits64,
-}
-
-impl SizeVariant {
-    fn of_int(self, primitives: &PrimitiveStore) -> Type {
-        match self {
-            SizeVariant::Bits32 => primitives.int32,
-            SizeVariant::Bits64 => primitives.int64,
-        }
     }
 }
 
@@ -1061,7 +1053,7 @@ impl<'a> BuiltinBuilder<'a> {
         );
 
         // The size variant of the function determines the size of the returned int.
-        let int_sized = size_variant.of_int(self.primitives);
+        let int_sized = size_variant_to_int_type(size_variant, self.primitives);
 
         let ndarray_int_sized =
             make_ndarray_ty(self.unifier, self.primitives, Some(int_sized), Some(common_ndim.ty));
@@ -1086,7 +1078,7 @@ impl<'a> BuiltinBuilder<'a> {
                 let arg_ty = fun.0.args[0].ty;
                 let arg = args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
 
-                let ret_elem_ty = size_variant.of_int(&ctx.primitives);
+                let ret_elem_ty = size_variant_to_int_type(size_variant, &ctx.primitives);
                 Ok(Some(builtin_fns::call_round(generator, ctx, (arg_ty, arg), ret_elem_ty)?))
             }),
         )
@@ -1127,7 +1119,7 @@ impl<'a> BuiltinBuilder<'a> {
             make_ndarray_ty(self.unifier, self.primitives, Some(float), Some(common_ndim.ty));
 
         // The size variant of the function determines the type of int returned
-        let int_sized = size_variant.of_int(self.primitives);
+        let int_sized = size_variant_to_int_type(size_variant, self.primitives);
         let ndarray_int_sized =
             make_ndarray_ty(self.unifier, self.primitives, Some(int_sized), Some(common_ndim.ty));
 
@@ -1150,7 +1142,7 @@ impl<'a> BuiltinBuilder<'a> {
                 let arg_ty = fun.0.args[0].ty;
                 let arg = args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
 
-                let ret_elem_ty = size_variant.of_int(&ctx.primitives);
+                let ret_elem_ty = size_variant_to_int_type(size_variant, &ctx.primitives);
                 let func = match kind {
                     Kind::Ceil => builtin_fns::call_ceil,
                     Kind::Floor => builtin_fns::call_floor,

nac3core/src/toplevel/mod.rs

@@ -34,6 +34,7 @@ pub mod numpy;
 pub mod type_annotation;
 use composer::*;
 use type_annotation::*;
+
 #[cfg(test)]
 mod test;
 

nac3core/src/util.rs

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