WIP: core: save progress

nac3core/irrt/irrt_error_context.hpp

@@ -0,0 +1,31 @@
+#pragma once
+
+#include "irrt_printer.hpp"
+
+namespace {
+    #define MAX_ERROR_NAME_LEN 32
+
+    // TODO: right now just to report some messages for now
+    struct ErrorContext {
+        Printer error;
+        // TODO: add error_class_name??
+
+        void initialize(char* string_base_ptr, uint32_t max_length) {
+            error.initialize(string_base_ptr, max_length);
+        }
+
+        bool has_error() {
+            return error.length > 0;
+        }
+    };
+}
+
+extern "C" {
+    void __nac3_error_context_init(ErrorContext* ctx, char* string_base_ptr, uint32_t max_length) {
+        ctx->initialize(string_base_ptr, max_length);
+    }
+
+    uint8_t __nac3_error_context_has_error(ErrorContext* ctx) {
+        return (uint8_t) ctx->has_error();
+    }
+}

nac3core/irrt/irrt_everything.hpp

@@ -1,10 +1,12 @@
 #pragma once
 
-#include "irrt_utils.hpp"
-#include "irrt_typedefs.hpp"
 #include "irrt_basic.hpp"
-#include "irrt_slice.hpp"
+#include "irrt_error_context.hpp"
 #include "irrt_numpy_ndarray.hpp"
+#include "irrt_printer.hpp"
+#include "irrt_slice.hpp"
+#include "irrt_typedefs.hpp"
+#include "irrt_utils.hpp"
 
 /*
     All IRRT implementations.

nac3core/irrt/irrt_numpy_ndarray.hpp

@@ -8,9 +8,6 @@
     NDArray-related implementations.
 `*/
 
-// NDArray indices are always `uint32_t`.
-using NDIndex = uint32_t;
-
 namespace {
     namespace ndarray_util {
         template <typename SizeT>
@@ -105,12 +102,16 @@ namespace {
     }
 
     struct NDSlice {
-        // A poor-man's `std::variant<int, UserRange>`
+        // A poor-man's enum variant type
         NDSliceType type;
 
         /*
             if type == INPUT_SLICE_TYPE_INDEX => `slice` points to a single `SizeT`
-            if type == INPUT_SLICE_TYPE_SLICE => `slice` points to a single `UserRange`
+            if type == INPUT_SLICE_TYPE_SLICE => `slice` points to a single `UserRange<SizeT>`
+
+            `SizeT` is controlled by the caller: `NDSlice` only cares about where that
+            slice is (the pointer), `NDSlice` does not care/know about the actual `sizeof()`
+            of the slice value.
         */
         uint8_t* slice;
     };
@@ -123,36 +124,36 @@ namespace {
             SizeT final_ndims = ndims;
             for (SizeT i = 0; i < num_slices; i++) {
                 if (slices[i].type == INPUT_SLICE_TYPE_INDEX) {
-                    final_ndims--; // An integer slice demotes the rank by 1
+                    final_ndims--; // An index demotes the rank by 1
                 }
             }
             return final_ndims;
         }
     }
 
-    template <typename SizeT>
-    struct NDArrayIndicesIter {
-        SizeT ndims;
-        const SizeT *shape;
-        SizeT *indices;
+    // template <typename SizeT>
+    // struct NDArrayIndicesIter {
+    //     SizeT ndims;
+    //     const SizeT *shape;
+    //     SizeT *indices;
 
-        void set_indices_zero() {
-            __builtin_memset(indices, 0, sizeof(SizeT) * ndims);
-        }
+    //     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;
+    //     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;
-                }
-            }
-        }
-    };
+    //             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.
     //
@@ -172,6 +173,8 @@ namespace {
         // 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.
+        //
+        // This pointer should point to the first element of the ndarray directly
         uint8_t *data;
 
         // The number of bytes of a single element in `data`.
@@ -212,11 +215,11 @@ 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 +232,7 @@ 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
@@ -252,15 +255,10 @@ namespace {
 
         // Fill the ndarray with a value
         void fill_generic(const 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);
+            const SizeT size = this->size();
+            for (SizeT i = 0; i < size; i++) {
+                uint8_t* pelement = get_nth_pelement(i);
+                set_pelement_value(pelement, pvalue);
             }
         }
 
@@ -283,12 +281,18 @@ 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);
             }
         }
 
-        // To support numpy complex slices (e.g., `my_array[:50:2,4,:2:-1]`)
+        // To support numpy "basic indexing" https://numpy.org/doc/stable/user/basics.indexing.html#basic-indexing
+        // "Advanced indexing" https://numpy.org/doc/stable/user/basics.indexing.html#advanced-indexing is not supported
+        //
+        // This function supports:
+        //   - "scalar indexing",
+        //   - "slicing and strides",
+        //   - and "dimensional indexing tools" (TODO, but this is really easy to implement).
         //
         // Things assumed by this function:
         // - `dst_ndarray` is allocated by the caller
@@ -299,13 +303,14 @@ namespace {
         // - `dst_ndarray->data` does not have to be set, it will be derived.
         // - `dst_ndarray->itemsize` does not have to be set, it will be set to `this->itemsize`
         // - `dst_ndarray->shape` and `dst_ndarray.strides` can contain empty values
-        void slice(SizeT num_ndslices, NDSlice* ndslices, NDArray<SizeT>* dst_ndarray) {
+        void subscript(SizeT num_ndslices, NDSlice* ndslices, NDArray<SizeT>* dst_ndarray) {
             // REFERENCE CODE (check out `_index_helper` in `__getitem__`):
             //   https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L652
 
             irrt_assert(dst_ndarray->ndims == ndarray_util::deduce_ndims_after_slicing(this->ndims, num_ndslices, ndslices));
 
             dst_ndarray->data = this->data;
+            dst_ndarray->itemsize = this->itemsize;
 
             SizeT this_axis = 0;
             SizeT dst_axis = 0;
@@ -326,15 +331,15 @@ namespace {
                     // Handle when the ndslice is a slice (represented by UserSlice in IRRT)
                     // e.g., `my_array[::2, -5, ::-1]`
                     //                 ^^^------^^^^----- like these
-                    UserSlice<SizeT>* user_slice = (UserSlice<SizeT>*) ndslice->slice;
-                    Slice<SizeT> slice = user_slice->indices(this->shape[this_axis]); // To resolve negative indices and other funny stuff written by the user
+                    UserSlice* user_slice = (UserSlice*) ndslice->slice;
+                    Slice slice = user_slice->indices(this->shape[this_axis]); // To resolve negative indices and other funny stuff written by the user
 
                     // NOTE: There is no need to write special code to handle negative steps/strides.
                     // This simple implementation meticulously handles both positive and negative steps/strides.
                     // Check out the tinynumpy and IRRT's test cases if you are not convinced.
-                    dst_ndarray->data += slice.start * this->strides[this_axis]; // Add offset (NOTE: no need to `* itemsize`, strides count in # of bytes)
-                    dst_ndarray->strides[dst_axis] = slice.step * this->strides[this_axis]; // Determine stride
-                    dst_ndarray->shape[dst_axis] = slice.len(); // Determine shape dimension
+                    dst_ndarray->data += (SizeT) slice.start * this->strides[this_axis]; // Add offset (NOTE: no need to `* itemsize`, strides count in # of bytes)
+                    dst_ndarray->strides[dst_axis] = ((SizeT) slice.step) * this->strides[this_axis]; // Determine stride
+                    dst_ndarray->shape[dst_axis] = (SizeT) slice.len(); // Determine shape dimension
 
                     // Next
                     dst_axis++;
@@ -344,7 +349,18 @@ namespace {
                 }
             }
 
-            irrt_assert(dst_axis == dst_ndarray->ndims); // Sanity check on the implementation
+            /*
+                Reference python code:
+                ```python
+                dst_ndarray.shape.extend(this.shape[this_axis:])
+                dst_ndarray.strides.extend(this.strides[this_axis:])
+                ```
+            */
+
+            for (; dst_axis < dst_ndarray->ndims; dst_axis++, this_axis++) {
+                dst_ndarray->shape[dst_axis] = this->shape[this_axis];
+                dst_ndarray->strides[dst_axis] = this->strides[this_axis];
+            }
         }
 
         // Similar to `np.broadcast_to(<ndarray>, <target_shape>)`
@@ -426,20 +442,30 @@ namespace {
             };
             src_ndarray->broadcast_to(&broadcasted_src_ndarray);
 
-            // Using iter instead of `get_nth_pelement` because it is slightly faster
-            SizeT* indices = __builtin_alloca(sizeof(SizeT) * this->ndims);
-            auto iter = NDArrayIndicesIter<SizeT> {
-                .ndims = this->ndims,
-                .shape = this->shape,
-                .indices = indices
-            };
-            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);
+            const SizeT size = this->size();
+            for (SizeT i = 0; i < size; i++) {
+                uint8_t* src_pelement = broadcasted_src_ndarray_strides->get_nth_pelement(i);
+                uint8_t* this_pelement = this->get_nth_pelement(i);
+                this->set_pelement_value(this_pelement, src_pelement);
             }
         }
+
+        // TODO: DOCUMENT ME
+        bool is_unsized() {
+            return this->ndims == 0;
+        }
+
+        // Simulate `len(<ndarray>)`
+        //   See (it doesn't help): https://numpy.org/doc/stable/reference/generated/numpy.ndarray.__len__.html#numpy.ndarray.__len__
+        SliceIndex len() {
+            // If you do `len(np.asarray(42))` (note that its `.shape` is just `()` - an empty tuple),
+            // numpy throws a `TypeError: len() of unsized object`
+            irrt_assert(!this->is_unsized());
+
+            // Apparently `len(<ndarray>)` is defined to be the first dimension
+            // REFERENCE: https://stackoverflow.com/questions/43081809/len-of-a-numpy-array-in-python
+            return (SliceIndex) this->shape[0];
+        }
     };
 }
 
@@ -452,6 +478,14 @@ extern "C" {
         return ndarray->size();
     }
 
+    void __nac3_ndarray_set_strides_by_shape(NDArray<int32_t>* ndarray) {
+        ndarray->set_strides_by_shape();
+    }
+
+    void __nac3_ndarray_set_strides_by_shape64(NDArray<int64_t>* ndarray) {
+        ndarray->set_strides_by_shape();
+    }
+
     void __nac3_ndarray_fill_generic(NDArray<int32_t>* ndarray, uint8_t* pvalue) {
         ndarray->fill_generic(pvalue);
     }
@@ -460,7 +494,27 @@ extern "C" {
         ndarray->fill_generic(pvalue);
     }
 
-    // void __nac3_ndarray_slice(NDArray<int32_t>* ndarray, int32_t num_slices, NDSlice<int32_t> *slices, NDArray<int32_t> *dst_ndarray) {
-    //     // ndarray->slice(num_slices, slices, dst_ndarray);
-    // }
+    int32_t __nac3_ndarray_deduce_ndims_after_slicing(int32_t ndims, int32_t num_slices, const NDSlice* slices) {
+        return ndarray_util::deduce_ndims_after_slicing(ndims, num_slices, slices);
+    }
+
+    int64_t __nac3_ndarray_deduce_ndims_after_slicing64(int64_t ndims, int64_t num_slices, const NDSlice* slices) {
+        return ndarray_util::deduce_ndims_after_slicing(ndims, num_slices, slices);
+    }
+
+    void __nac3_ndarray_subscript(NDArray<int32_t>* ndarray, int32_t num_slices, NDSlice* slices, NDArray<int32_t> *dst_ndarray) {
+        ndarray->subscript(num_slices, slices, dst_ndarray);
+    }
+
+    void __nac3_ndarray_subscript64(NDArray<int64_t>* ndarray, int32_t num_slices, NDSlice* slices, NDArray<int64_t> *dst_ndarray) {
+        ndarray->subscript(num_slices, slices, dst_ndarray);
+    }
+
+    SliceIndex __nac3_ndarray_len(NDArray<int32_t>* ndarray) {
+        return ndarray->len();
+    }
+
+    SliceIndex __nac3_ndarray_len64(NDArray<int64_t>* ndarray) {
+        return ndarray->len();
+    }
 }

nac3core/irrt/irrt_printer.hpp

@@ -0,0 +1,82 @@
+#pragma once
+
+#include "irrt_typedefs.hpp"
+
+// TODO: obviously implementing printf from scratch is bad,
+// is there a header only, no-cstdlib library for this?
+
+namespace {
+    struct Printer {
+        char* string_base_ptr;
+        uint32_t max_length;
+        uint32_t length; // NOTE: this could be incremented past max_length, which indicates
+
+        void initialize(char *string_base_ptr, uint32_t max_length) {
+            this->string_base_ptr = string_base_ptr;
+            this->max_length = max_length;
+            this->length = 0;
+        }
+
+        void put_space() {
+            put_char(' ');
+        }
+
+        void put_char(char ch) {
+            push_char(ch);
+        }
+
+        void put_string(const char* string) {
+            // TODO: optimize?
+            while (*string != '\0') {
+                push_char(*string);
+                string++; // Move to next char
+            }
+        }
+
+        template<typename T>
+        void put_int(T value) {
+            // NOTE: Try not to use recursion to print the digits
+
+            // value == 0 is a special case
+            if (value == 0) {
+                push_char('0');
+            } else {
+                // Add a '-' if the value is negative
+                if (value < 0) {
+                    push_char('-');
+                    value = -value; // Negate then continue to print the digits
+                }
+
+                // TODO: Recursion is a bad idea on embedded systems?
+                uint32_t num_digits = int_log_floor(value, 10) + 1;
+                put_int_helper(num_digits, value);
+            }
+        }
+
+        // TODO: implement put_float() and more would be useful
+    private:
+        void push_char(char ch) {
+            if (length < max_length) {
+                string_base_ptr[length] = ch;
+            }
+
+            // NOTE: this could increment past max_length,
+            // to indicate the true length of the message even if it gets cut off
+            length++;
+        }
+
+        template <typename T>
+        void put_int_helper(uint32_t num_digits, T value) {
+            // Print the digits recursively
+            __builtin_assume(0 <= value);
+
+            if (num_digits > 0) {
+                put_int_helper(num_digits - 1, value / 10);
+
+                uint32_t digit = value % 10;
+                char digit_char = '0' + (char) digit;
+                put_char(digit_char);
+            }
+        }
+    };
+}

nac3core/irrt/irrt_slice.hpp

@@ -4,19 +4,15 @@
 #include "irrt_typedefs.hpp"
 
 namespace {
-    // A proper slice in IRRT, all negative indices have be resolved to absolute values.
-    // Even though nac3core's slices are always `int32_t`, we will template slice anyway
-    // since this struct is used as a general utility.
-    template <typename T>
     struct Slice {
-        T start;
-        T stop;
-        T step;
+        SliceIndex start;
+        SliceIndex stop;
+        SliceIndex step;
 
         // The length/The number of elements of the slice if it were a range,
         // i.e., the value of `len(range(this->start, this->stop, this->end))`
-        T len() {
-            T diff = stop - start;
+        SliceIndex len() {
+            SliceIndex diff = stop - start;
             if (diff > 0 && step > 0) {
                 return ((diff - 1) / step) + 1;
             } else if (diff < 0 && step < 0) {
@@ -27,38 +23,45 @@ namespace {
         }
     };
 
-    template<typename T>
-    T resolve_index_in_length(T length, T index) {
+    SliceIndex resolve_index_in_length(SliceIndex length, SliceIndex index) {
         irrt_assert(length >= 0);
         if (index < 0) {
             // Remember that index is negative, so do a plus here
-            return max(length + index, 0);
+            return max<SliceIndex>(length + index, 0);
         } else {
-            return min(length, index);
+            return min<SliceIndex>(length, index);
         }
     }
 
+    // A user-written Python-like slice.
+    //
+    // i.e., this slice is a triple of either an int or nothing. (e.g., `my_array[:10:2]`, `start` is None)
+    //
+    // You can "resolve" a `UserSlice` by using `UserSlice::indices(<length>)`
+    //
     // NOTE: using a bitfield for the `*_defined` is better, at the
     // cost of a more annoying implementation in nac3core inkwell
-    template <typename T>
     struct UserSlice {
+        // Did the user specify `start`? If 0, `start` is undefined (and contains an empty value)
         uint8_t start_defined;
-        T start;
+        SliceIndex start;
 
+        // Similar to `start_defined`
         uint8_t stop_defined;
-        T stop;
+        SliceIndex stop;
 
+        // Similar to `start_defined`
         uint8_t step_defined;
-        T step;
+        SliceIndex step;
 
         // Like Python's `slice(start, stop, step).indices(length)`
-        Slice<T> indices(T length) {
+        Slice indices(SliceIndex length) {
             // NOTE: This function implements Python's `slice.indices` *FAITHFULLY*.
             // SEE: https://github.com/python/cpython/blob/f62161837e68c1c77961435f1b954412dd5c2b65/Objects/sliceobject.c#L546
             irrt_assert(length >= 0);
             irrt_assert(!step_defined || step != 0); // step_defined -> step != 0; step cannot be zero if specified by user
 
-            Slice<T> result;
+            Slice result;
             result.step = step_defined ? step : 1;
             bool step_is_negative = result.step < 0;
 

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
@@ -158,34 +158,34 @@ void test_set_strides_by_shape() {
     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 = 3,
-        .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_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 = 3,
+//         .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
@@ -248,10 +248,10 @@ void test_ndarray_set_to_eye() {
 }
 
 void test_slice_1() {
-    // Test `slice(5, None, None).indices(100) == slice(5, 100, 1)`
+    // Test `subscript(5, None, None).indices(100) == subscript(5, 100, 1)`
     BEGIN_TEST();
 
-    UserSlice<int> user_slice = {
+    UserSlice user_slice = {
         .start_defined = 1,
         .start = 5,
         .stop_defined = 0,
@@ -265,10 +265,10 @@ void test_slice_1() {
 }
 
 void test_slice_2() {
-    // Test `slice(400, 999, None).indices(100) == slice(100, 100, 1)`
+    // Test `subscript(400, 999, None).indices(100) == subscript(100, 100, 1)`
     BEGIN_TEST();
 
-    UserSlice<int> user_slice = {
+    UserSlice user_slice = {
         .start_defined = 1,
         .start = 400,
         .stop_defined = 0,
@@ -282,10 +282,10 @@ void test_slice_2() {
 }
 
 void test_slice_3() {
-    // Test `slice(-10, -5, None).indices(100) == slice(90, 95, 1)`
+    // Test `subscript(-10, -5, None).indices(100) == subscript(90, 95, 1)`
     BEGIN_TEST();
 
-    UserSlice<int> user_slice = {
+    UserSlice user_slice = {
         .start_defined = 1,
         .start = -10,
         .stop_defined = 1,
@@ -300,10 +300,10 @@ void test_slice_3() {
 }
 
 void test_slice_4() {
-    // Test `slice(None, None, -5).indices(100) == (99, -1, -5)`
+    // Test `subscript(None, None, -5).indices(100) == (99, -1, -5)`
     BEGIN_TEST();
 
-    UserSlice<int> user_slice = {
+    UserSlice user_slice = {
         .start_defined = 0,
         .stop_defined = 0,
         .step_defined = 1,
@@ -366,14 +366,14 @@ void test_ndslice_1() {
     };
 
     // Create the slice in `ndarray[-2::, 1::2]`
-    UserSlice<int32_t> user_slice_1 = {
+    UserSlice user_slice_1 = {
         .start_defined = 1,
         .start = -2,
         .stop_defined = 0,
         .step_defined = 0
     };
 
-    UserSlice<int32_t> user_slice_2 = {
+    UserSlice user_slice_2 = {
         .start_defined = 1,
         .start = 1,
         .stop_defined = 0,
@@ -387,17 +387,17 @@ void test_ndslice_1() {
         { .type = INPUT_SLICE_TYPE_SLICE, .slice = (uint8_t*) &user_slice_2 }
     };
 
-    ndarray.slice(num_ndslices, ndslices, &dst_ndarray);
+    ndarray.subscript(num_ndslices, ndslices, &dst_ndarray);
 
     int32_t expected_shape[dst_ndims] = { 2, 2 };
     int32_t expected_strides[dst_ndims] = { 32, 16 };
     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() {
@@ -450,7 +450,7 @@ void test_ndslice_2() {
 
     // Create the slice in `ndarray[2, ::-2]`
     int32_t user_slice_1 = 2;
-    UserSlice<int32_t> user_slice_2 = {
+    UserSlice user_slice_2 = {
         .start_defined = 0,
         .stop_defined = 0,
         .step_defined = 1,
@@ -463,7 +463,7 @@ void test_ndslice_2() {
         { .type = INPUT_SLICE_TYPE_SLICE, .slice = (uint8_t*) &user_slice_2 }
     };
 
-    ndarray.slice(num_ndslices, ndslices, &dst_ndarray);
+    ndarray.subscript(num_ndslices, ndslices, &dst_ndarray);
 
     int32_t expected_shape[dst_ndims] = { 2 };
     int32_t expected_strides[dst_ndims] = { -16 };
@@ -471,8 +471,52 @@ 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_ndslice_3() {
+    BEGIN_TEST();
+
+    double in_data[12] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
+    const int32_t in_itemsize = sizeof(double);
+    const int32_t in_ndims = 2;
+    int32_t in_shape[in_ndims] = { 3, 4 };
+    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();
+
+    const int32_t dst_ndims = 2;
+    int32_t dst_shape[dst_ndims] = {999, 999}; // Empty values
+    int32_t dst_strides[dst_ndims] = {999, 999}; // Empty values
+    NDArray<int32_t> dst_ndarray = {
+        .data = nullptr,
+        .ndims = dst_ndims,
+        .shape = dst_shape,
+        .strides = dst_strides
+    };
+
+    // Create the slice in `ndarray[2:3]`
+    UserSlice user_slice_1 = {
+        .start_defined = 1,
+        .start = 2,
+        .stop_defined = 1,
+        .stop = 3,
+        .step_defined = 0,
+    };
+
+    const int32_t num_ndslices = 1;
+    NDSlice ndslices[num_ndslices] = {
+        { .type = INPUT_SLICE_TYPE_SLICE, .slice = (uint8_t*) &user_slice_1 },
+    };
+
+    ndarray.subscript(num_ndslices, ndslices, &dst_ndarray);
 }
 
 void test_can_broadcast_shape() {
@@ -576,19 +620,21 @@ void test_can_broadcast_shape() {
 
 void test_ndarray_broadcast_1() {
     /*
-    # array = np.array([[19.9, 29.9, 39.9, 49.9]], dtype=np.float64)
-    # >>> [[19.9 29.9 39.9 49.9]]
-    #
-    # array = np.broadcast_to(array, (2, 3, 4))
-    # >>> [[[19.9 29.9 39.9 49.9]
-    # >>>   [19.9 29.9 39.9 49.9]
-    # >>>   [19.9 29.9 39.9 49.9]]
-    # >>>  [[19.9 29.9 39.9 49.9]
-    # >>>   [19.9 29.9 39.9 49.9]
-    # >>>   [19.9 29.9 39.9 49.9]]]
-    #
-    # assery array.strides == (0, 0, 8)
+        ```python
+        array = np.array([[19.9, 29.9, 39.9, 49.9]], dtype=np.float64)
+        >>> [[19.9 29.9 39.9 49.9]]
         
+        array = np.broadcast_to(array, (2, 3, 4))
+        >>> [[[19.9 29.9 39.9 49.9]
+        >>>   [19.9 29.9 39.9 49.9]
+        >>>   [19.9 29.9 39.9 49.9]]
+        >>>  [[19.9 29.9 39.9 49.9]
+        >>>   [19.9 29.9 39.9 49.9]
+        >>>   [19.9 29.9 39.9 49.9]]]
+        
+        assert array.strides == (0, 0, 8)
+        # and then pick some values in `array` and check them...
+        ```
     */
     BEGIN_TEST();
 
@@ -618,31 +664,33 @@ 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})));
+    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})));
 }
 
-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
-        ```
-    */
+void test_printer() {
+    const uint32_t buffer_len = 256;
+    char buffer[buffer_len];
+    Printer printer = {
+        .string_base_ptr = buffer,
+        .max_length = buffer_len,
+        .length = 0
+    };
+
 }
 
 int main() {
     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_indices_iter_normal();
     test_ndarray_fill_generic();
     test_ndarray_set_to_eye();
     test_slice_1();
@@ -651,8 +699,9 @@ int main() {
     test_slice_4();
     test_ndslice_1();
     test_ndslice_2();
+    test_ndslice_3();
     test_can_broadcast_shape();
     test_ndarray_broadcast_1();
-    test_assign_with();
+    test_printer();
     return 0;
 }

nac3core/irrt/irrt_utils.hpp

@@ -21,6 +21,43 @@ namespace {
         return true;
     }
 
+    template<typename T>
+    uint32_t int_log_floor(T value, T base) {
+        uint32_t result = 0;
+        while (value < base) {
+            result++;
+            value /= base;
+        }
+        return result;
+    }
+
+    bool string_is_empty(const char *str) {
+        return str[0] == '\0';
+    }
+
+    // TODO: DOCUMENT ME!!!!!
+    // returns false if `src_str` could not be fully copied over to `dst_str`
+    bool string_copy(uint32_t dst_max_size, char* dst_str, const char* src_str) {
+        // This function guarantess that `dst_str` will be null-terminated,
+
+        for (uint32_t i = 0; i < dst_max_size; i++) {
+            bool is_last = i + 1 == dst_max_size;
+            if (is_last && src_str[i] != '\0') {
+                dst_str[i] = '\0';
+                return false;
+            }
+
+            if (src_str[i] == '\0') {
+                dst_str[i] = '\0';
+                return true;
+            }
+
+            dst_str[i] = src_str[i];
+        }
+
+        __builtin_unreachable();
+    }
+
     void irrt_panic() {
         // Crash the program for now.
         // TODO: Don't crash the program

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);
 
@@ -1764,306 +1768,163 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> UntypedArrayLikeMutator<'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>,
-}
+// #[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>>,
+// }
+// 
+// pub 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> {
+//     /// TODO: DOCUMENT ME
+//     pub fn gep(
+//         &self,
+//         ctx: &CodeGenContext<'ctx, '_>,
+//         struct_ptr: PointerValue<'ctx>,
+//     ) -> PointerValue<'ctx> {
+//         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, '_>,
+//         struct_ptr: PointerValue<'ctx>,
+//     ) -> BasicValueEnum<'ctx> {
+//         ctx.builder.build_load(self.gep(ctx, struct_ptr), self.name).unwrap()
+//     }
+// 
+//     /// 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(self.gep(ctx, struct_ptr), value).unwrap();
+//     }
+// }
 
-pub struct StructFields<'ctx> {
-    /// Name of the struct.
-    ///
-    /// Used for generating names.
-    pub name: &'static str,
+// type IsInstanceError = String;
+// type IsInstanceResult = Result<(), IsInstanceError>;
 
-    /// 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>>,
-}
+// 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();
 
-struct StructFieldsBuilder<'ctx> {
-    gep_index_counter: u32,
-    /// Name of the struct to be built.
-    name: &'static str,
-    fields: Vec<StructField<'ctx>>,
-}
+//     // 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> 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()),
-        }
-    }
-}
+// impl<'ctx> StructFields<'ctx> {
+//     pub fn num_fields(&self) -> u32 {
+//         self.fields.len() as u32
+//     }
+// 
+//     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)
+//     }
+// 
+//     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> {
+//     pub fn start(name: &'static str) -> Self {
+//         StructFieldsBuilder { gep_index_counter: 0, name, fields: Vec::new() }
+//     }
+// 
+//     pub fn add_field(&mut self, name: &'static str, ty: BasicTypeEnum<'ctx>) -> StructField<'ctx> {
+//         let index = self.gep_index_counter;
+//         self.gep_index_counter += 1;
+// 
+//         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
+//     }
+// 
+//     pub fn end(self) -> StructFields<'ctx> {
+//         StructFields { name: self.name, fields: self.fields }
+//     }
+// }
+// 

nac3core/src/codegen/expr.rs

@@ -1,10 +1,14 @@
-use std::{collections::HashMap, convert::TryInto, iter::once, iter::zip};
+use std::{
+    collections::HashMap,
+    convert::TryInto,
+    iter::{once, zip},
+};
 
 use crate::{
     codegen::{
         classes::{
-            ArrayLikeIndexer, ArrayLikeValue, ListType, ListValue, NDArrayValue, ProxyType,
-            ProxyValue, RangeValue, TypedArrayLikeAccessor, UntypedArrayLikeAccessor,
+            ArrayLikeIndexer, ArrayLikeValue, ListType, ListValue, NDArrayDataProxy, NDArrayValue,
+            ProxyType, ProxyValue, RangeValue, TypedArrayLikeAccessor, UntypedArrayLikeAccessor,
         },
         concrete_type::{ConcreteFuncArg, ConcreteTypeEnum, ConcreteTypeStore},
         gen_in_range_check, get_llvm_abi_type, get_llvm_type,
@@ -13,7 +17,8 @@ use crate::{
             call_expect, call_float_floor, call_float_pow, call_float_powi, call_int_smax,
             call_memcpy_generic,
         },
-        need_sret, numpy,
+        need_sret,
+        numpy::{self, call_ndarray_subscript_impl, get_ndarray_first_element},
         stmt::{
             gen_for_callback_incrementing, gen_if_callback, gen_if_else_expr_callback, gen_raise,
             gen_var,
@@ -34,15 +39,17 @@ use crate::{
 use inkwell::{
     attributes::{Attribute, AttributeLoc},
     types::{AnyType, BasicType, BasicTypeEnum},
-    values::{BasicValueEnum, CallSiteValue, FunctionValue, IntValue, PointerValue},
+    values::{BasicValue, BasicValueEnum, CallSiteValue, FunctionValue, IntValue, PointerValue},
     AddressSpace, IntPredicate, OptimizationLevel,
 };
 use itertools::{chain, izip, Either, Itertools};
 use nac3parser::ast::{
-    self, Boolop, Cmpop, Comprehension, Constant, Expr, ExprKind, Location, Operator, StrRef,
-    Unaryop,
+    self, Boolop, Cmpop, Comprehension, Constant, Expr, ExprKind, Located, Location, Operator,
+    StrRef, Unaryop,
 };
 
+use super::classes::{NpArrayType, NpArrayValue};
+
 pub fn get_subst_key(
     unifier: &mut Unifier,
     obj: Option<Type>,
@@ -2095,17 +2102,123 @@ pub fn gen_cmpop_expr<'ctx, G: CodeGenerator>(
 ///
 /// * `ty` - The `Type` of the `NDArray` elements.
 /// * `ndims` - The `Type` of the `NDArray` number-of-dimensions `Literal`.
-/// * `v` - The `NDArray` value.
+/// * `ndarray` - The `NDArray` value.
 /// * `slice` - The slice expression used to subscript into the `ndarray`.
 fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
     ty: Type,
     ndims: Type,
-    v: NDArrayValue<'ctx>,
+    ndarray: NpArrayValue<'ctx>,
     slice: &Expr<Option<Type>>,
 ) -> Result<Option<ValueEnum<'ctx>>, String> {
-    todo!()
+    // TODO: bounds check (on IRRT (how?), or using inkwell)
+    // TODO: For invalid `slice`, throw a proper error
+    // TODO: Support https://numpy.org/doc/stable/user/basics.indexing.html#dimensional-indexing-tools
+
+    let size_type = ndarray.ty.size_type;
+    debug_assert_eq!(size_type, generator.get_size_type(ctx.ctx)); // The ndarray's size_type somehow isn't that of `generator.get_size_type()`... there would be a bug
+
+    // Annoying notes about `slice`
+    //  - `my_array[5]`
+    //    - slice is a `Constant`
+    //  - `my_array[:5]`
+    //    - slice is a `Slice`
+    //  - `my_array[:]`
+    //    - slice is a `Slice`, but lower upper step would all be `Option::None`
+    //  - `my_array[:, :]`
+    //    - slice is now a `Tuple` of two `Slice`-s
+    //
+    // In summary:
+    //  - when there is a comma "," within [], `slice` will be a `Tuple` of the entries.
+    //  - when there is not comma "," within [] (i.e., just a single entry), `slice` will be that entry itself.
+    //
+    // `entries` will flatten it out.
+    let entries = match &slice.node {
+        ExprKind::Tuple { elts, ctx } => elts.iter().collect_vec(),
+        _ => vec![slice],
+    };
+
+    // This could have been written as a `ndslices = entries.into_iter().map(...)`,
+    // but error shortcutting part would be annoying
+    let mut ndslices = vec![];
+    for entry in entries.into_iter() {
+        // NOTE: Currently nac3core's slices do not have an object representation,
+        // so the code/implementation looks awkward - we have to do pattern matching on the expression
+        let ndslice = match &entry.node {
+            ExprKind::Slice { lower: start, upper: stop, step } => {
+                // Helper function here to deduce code duplication
+                let mut help = |value_expr: &Option<
+                    Box<Located<ExprKind<Option<Type>>, Option<Type>>>,
+                >|
+                 -> Result<_, String> {
+                    Ok(match value_expr {
+                        None => None,
+                        Some(value_expr) => Some(
+                            generator
+                                .gen_expr(ctx, &value_expr)?
+                                .unwrap()
+                                .to_basic_value_enum(ctx, generator, ctx.primitives.int32)?
+                                .into_int_value(),
+                        ),
+                    })
+                };
+
+                let start = help(start)?;
+                let stop = help(stop)?;
+                let step = help(step)?;
+
+                // start stop step should all be 32-bit ints after typechecking,
+                // and `IrrtUserSlice` expects `int32`s
+                NDSlice::Slice(UserSlice { start, stop, step })
+            }
+            _ => {
+                // Anything else that is not a slice (might be illegal values),
+                // For nac3core, this should be e.g., an int32 constant, an int32 variable, otherwise its an error
+
+                let index = generator
+                    .gen_expr(ctx, entry)?
+                    .unwrap()
+                    .to_basic_value_enum(ctx, generator, ctx.primitives.int32)?
+                    .into_int_value();
+
+                NDSlice::Index(index)
+            }
+        };
+        ndslices.push(ndslice);
+    }
+
+    // TODO: what is going on? why the original implementation doesn't assert `ndims_values.len() == 1`
+    // Extract the `ndims` from a `Type` to `i128`
+    let TypeEnum::TLiteral { values: ndims_values, .. } = &*ctx.unifier.get_ty_immutable(ndims)
+    else {
+        unreachable!()
+    };
+    assert_eq!(ndims_values.len(), 1);
+    let ndims = i128::try_from(ndims_values[0].clone()).unwrap() as u64;
+    assert!(ndims > 0);
+
+    // Deduce the subndarray's ndims
+    let dst_ndims = deduce_ndims_after_slicing(ndims, ndslices.iter());
+
+    // Finally, perform the actual subscript logic
+    // TODO: `call_ndarray_subscript_impl` under the hood deduces `dst_ndims` again. We could save it some time by passing `dst_ndims` - a TODO?
+    let subndarray = call_ndarray_subscript_impl(
+        generator,
+        ctx,
+        ndarray,
+        &ndslices.iter().collect_vec(),
+    )?;
+
+    // ...and return the result, with two cases
+    let result = if dst_ndims == 0 {
+        // 1) ndims == 0 (this happens when you do `np.zerps((3, 4))[1, 1]`), return *THE ELEMENT*
+        get_ndarray_first_element(ctx, subndarray, "element")
+    } else {
+        // 2) ndims > 0 (other cases), return subndarray
+        subndarray.ptr.as_basic_value_enum()
+    };
+    Ok(Some(ValueEnum::Dynamic(result)))
 
     // let llvm_i1 = ctx.ctx.bool_type();
     // let llvm_i32 = ctx.ctx.i32_type();
@@ -3031,17 +3144,29 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
                     }
                 }
                 TypeEnum::TObj { obj_id, params, .. } if *obj_id == PrimDef::NDArray.id() => {
-                    let (ty, ndims) = params.iter().map(|(_, ty)| ty).collect_tuple().unwrap();
+                    let (elem_ty, ndims) = params.iter().map(|(_, ty)| ty).collect_tuple().unwrap();
 
-                    let v = if let Some(v) = generator.gen_expr(ctx, value)? {
+                    // Get the pointer to the ndarray described by `value`
+                    let ndarray_ptr = if let Some(v) = generator.gen_expr(ctx, value)? {
                         v.to_basic_value_enum(ctx, generator, value.custom.unwrap())?
                             .into_pointer_value()
                     } else {
                         return Ok(None);
                     };
-                    let v = NDArrayValue::from_ptr_val(v, usize, None);
 
-                    return gen_ndarray_subscript_expr(generator, ctx, *ty, *ndims, v, slice);
+                    // Derive the current NDArray struct type independently...
+                    let ndarray_ty = NpArrayType {
+                        elem_type: ctx.get_llvm_type(generator, *elem_ty),
+                        size_type: generator.get_size_type(ctx.ctx),
+                    };
+
+                    // ...and wrap it in `NDArrayValue`
+                    let ndarray = ndarray_ty.value_from_ptr(ctx.ctx, ndarray_ptr);
+
+                    // Implementation
+                    return gen_ndarray_subscript_expr(
+                        generator, ctx, *elem_ty, *ndims, ndarray, slice,
+                    );
                 }
                 TypeEnum::TTuple { .. } => {
                     let index: u32 =

nac3core/src/codegen/irrt/classes.rs

@@ -0,0 +1,87 @@
+// TODO: Use derppening's abstraction
+
+use std::marker::PhantomData;
+
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum, IntType},
+    values::BasicValueEnum,
+    AddressSpace,
+};
+
+use crate::codegen::structure::{
+    CustomStructType, CustomType, Field, FieldCreator, IntType2, Object, PointerType2,
+    PointingArrayType,
+};
+
+#[derive(Debug, Clone, Copy)]
+pub struct NpArrayType<'ctx> {
+    pub size_type: IntType<'ctx>,
+    pub elem_type: BasicTypeEnum<'ctx>,
+}
+
+pub struct NpArrayFields<'ctx> {
+    pub data: Field<'ctx, PointerType2<'ctx>>,
+    pub itemsize: Field<'ctx, IntType2<'ctx>>,
+    pub ndims: Field<'ctx, IntType2<'ctx>>,
+    pub shape: Field<'ctx, PointingArrayType<'ctx, IntType2<'ctx>>>,
+    pub strides: Field<'ctx, PointingArrayType<'ctx, IntType2<'ctx>>>,
+}
+
+pub type NpArrayValue<'ctx> = Object<'ctx, NpArrayType<'ctx>>;
+
+// impl<'ctx> CustomType<'ctx> for NpArrayType<'ctx> {
+//     type Value = NpArrayValue<'ctx>;
+//
+//     fn llvm_basic_type_enum(
+//         &self,
+//         ctx: &'ctx inkwell::context::Context,
+//     ) -> inkwell::types::BasicTypeEnum<'ctx> {
+//         self.llvm_struct_type(ctx).as_basic_type_enum()
+//     }
+//
+//     fn llvm_field_load(
+//         &self,
+//         ctx: &crate::codegen::CodeGenContext<'ctx, '_>,
+//         field: crate::codegen::structure::FieldInfo,
+//         struct_ptr: inkwell::values::PointerValue<'ctx>,
+//     ) -> Self::Value {
+//         let ok = field.llvm_load(ctx, struct_ptr);
+//         todo!()
+//     }
+//
+//     fn llvm_field_store(
+//         &self,
+//         ctx: &crate::codegen::CodeGenContext<'ctx, '_>,
+//         field: crate::codegen::structure::FieldInfo,
+//         struct_ptr: inkwell::values::PointerValue<'ctx>,
+//         value: &Self::Value,
+//     ) {
+//         todo!()
+//     }
+// }
+
+impl<'ctx> CustomStructType<'ctx> for NpArrayType<'ctx> {
+    type Fields = NpArrayFields<'ctx>;
+
+    fn llvm_struct_name() -> &'static str {
+        "NDArray"
+    }
+
+    fn add_fields_to(&self, creator: &mut FieldCreator<'ctx>) -> Self::Fields {
+        let pi8 = creator.ctx.i8_type().ptr_type(AddressSpace::default());
+        NpArrayFields {
+            data: creator.add_field("data", PointerType2(pi8)),
+            itemsize: creator.add_field("itemsize", IntType2(self.size_type)),
+            ndims: creator.add_field("ndims", IntType2(self.size_type)),
+            shape: creator.add_field("shape", PointingArrayType::new(IntType2(self.size_type))),
+            strides: creator.add_field("strides", PointingArrayType::new(IntType2(self.size_type))),
+        }
+    }
+}
+
+impl<'ctx> NpArrayType<'ctx> {
+    pub fn new_opaque_elem(ctx: &'ctx Context, size_type: IntType<'ctx>) -> Self {
+        NpArrayType { elem_type: ctx.i8_type().into(), size_type }
+    }
+}

nac3core/src/codegen/llvm_intrinsics.rs

@@ -35,6 +35,54 @@ fn get_float_intrinsic_repr(ctx: &Context, ft: FloatType) -> &'static str {
     unreachable!()
 }
 
+/// Invokes the [`llvm.lifetime.start`](https://releases.llvm.org/14.0.0/docs/LangRef.html#llvm-lifetime-start-intrinsic)
+/// intrinsic.
+pub fn call_lifetime_start<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    size: IntValue<'ctx>,
+    ptr: PointerValue<'ctx>,
+) {
+    const FN_NAME: &str = "llvm.lifetime.start";
+    // NOTE: inkwell temporary workaround, see [`call_stackrestore`] for details
+    let intrinsic_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
+        let llvm_void = ctx.ctx.void_type();
+        let llvm_i64 = ctx.ctx.i64_type();
+        let llvm_p0i8 = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
+        let fn_type = llvm_void.fn_type(&[llvm_i64.into(), llvm_p0i8.into()], false);
+
+        ctx.module.add_function(FN_NAME, fn_type, None)
+    });
+
+    ctx.builder
+        .build_call(intrinsic_fn, &[size.into(), ptr.into()], "")
+        .map(CallSiteValue::try_as_basic_value)
+        .unwrap();
+}
+
+/// Invokes the [`llvm.lifetime.end`](https://releases.llvm.org/14.0.0/docs/LangRef.html#llvm-lifetime-end-intrinsic)
+/// intrinsic.
+pub fn call_lifetime_end<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    size: IntValue<'ctx>,
+    ptr: PointerValue<'ctx>,
+) {
+    const FN_NAME: &str = "llvm.lifetime.end";
+    // NOTE: inkwell temporary workaround, see [`call_stackrestore`] for details
+    let intrinsic_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
+        let llvm_void = ctx.ctx.void_type();
+        let llvm_i64 = ctx.ctx.i64_type();
+        let llvm_p0i8 = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
+        let fn_type = llvm_void.fn_type(&[llvm_i64.into(), llvm_p0i8.into()], false);
+
+        ctx.module.add_function(FN_NAME, fn_type, None)
+    });
+
+    ctx.builder
+        .build_call(intrinsic_fn, &[size.into(), ptr.into()], "")
+        .map(CallSiteValue::try_as_basic_value)
+        .unwrap();
+}
+
 /// Invokes the [`llvm.stacksave`](https://llvm.org/docs/LangRef.html#llvm-stacksave-intrinsic)
 /// intrinsic.
 pub fn call_stacksave<'ctx>(

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},
@@ -43,6 +44,7 @@ pub mod irrt;
 pub mod llvm_intrinsics;
 pub mod numpy;
 pub mod stmt;
+pub mod structure;
 
 #[cfg(test)]
 mod test;
@@ -476,7 +478,14 @@ 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)
+                                .ptr_type(AddressSpace::default())
+                                .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,
-        },
+        get_llvm_type, irrt,
         llvm_intrinsics::{self, call_memcpy_generic},
         stmt::{gen_for_callback_incrementing, gen_for_range_callback, gen_if_else_expr_callback},
         CodeGenContext, CodeGenerator,
@@ -26,14 +22,27 @@ use crate::{
         typedef::{FunSignature, Type, TypeEnum},
     },
 };
-use inkwell::types::{AnyTypeEnum, BasicTypeEnum, PointerType};
 use inkwell::{
     types::BasicType,
     values::{BasicValueEnum, IntValue, PointerValue},
     AddressSpace, IntPredicate, OptimizationLevel,
 };
+use inkwell::{
+    types::{AnyTypeEnum, BasicTypeEnum, IntType, PointerType},
+    values::BasicValue,
+};
 use nac3parser::ast::{Operator, StrRef};
 
+use super::{
+    classes::NpArrayValue,
+    irrt::{
+        call_nac3_ndarray_deduce_ndims_after_slicing, call_nac3_ndarray_set_strides_by_shape,
+        call_nac3_ndarray_size, call_nac3_ndarray_subscript, get_irrt_ndarray_ptr_type,
+        get_opaque_uint8_ptr_type, IrrtNDSliceType, NDSlice,
+    },
+    stmt::gen_return,
+};
+
 // /// Creates an uninitialized `NDArray` instance.
 // fn create_ndarray_uninitialized<'ctx, G: CodeGenerator + ?Sized>(
 //     generator: &mut G,
@@ -2015,3 +2024,499 @@ 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();
+}
+
+fn alloca_ndarray<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    elem_type: BasicTypeEnum<'ctx>,
+    ndims: IntValue<'ctx>,
+    name: &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.alloca(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"),
+    }
+}
+
+enum NDArrayInitMode<'ctx, G: CodeGenerator + ?Sized> {
+    SetNDim { ndim: IntValue<'ctx> },
+    SetShape { shape: Producer<'ctx, G, IntValue<'ctx>> },
+    SetShapeAndAllocaData { shape: Producer<'ctx, G, IntValue<'ctx>> },
+}
+
+/// TODO: DOCUMENT ME
+fn alloca_ndarray_and_init<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    elem_type: BasicTypeEnum<'ctx>,
+    init_mode: NDArrayInitMode<'ctx, G>,
+    name: &str,
+) -> Result<NpArrayValue<'ctx>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    // It is implemented verbosely in order to make the initialization modes super clear in their intent.
+    match init_mode {
+        NDArrayInitMode::SetNDim { ndim: ndims } => {
+            let ndarray = alloca_ndarray(generator, ctx, elem_type, ndims, name)?;
+            Ok(ndarray)
+        }
+        NDArrayInitMode::SetShape { shape } => {
+            let ndims = shape.count;
+            let ndarray = alloca_ndarray(generator, ctx, elem_type, ndims, name)?;
+
+            // Fill `ndarray.shape` with `shape_producer`
+            (shape.write_to_slice)(generator, ctx, &ndarray.shape_slice(ctx));
+
+            Ok(ndarray)
+        }
+        NDArrayInitMode::SetShapeAndAllocaData { shape } => {
+            let ndims = shape.count;
+            let ndarray = alloca_ndarray(generator, ctx, elem_type, ndims, name)?;
+
+            // Fill `ndarray.shape` with `shape_producer`
+            (shape.write_to_slice)(generator, ctx, &ndarray.shape_slice(ctx));
+
+            // Now we populate `ndarray.data` by alloca-ing.
+            // But first, we need to know the size of the ndarray to know how many elements to alloca
+            // NOTE: calculating the size of an ndarray requires `ndarray.shape` to be set.
+            let ndarray_size = call_nac3_ndarray_size(ctx, ndarray);
+
+            // Alloca `data` and assign it to `ndarray.data`
+            let data_ptr = ctx.builder.build_array_alloca(elem_type, ndarray_size, "data").unwrap();
+            // We also have to cast `data_ptr` to `uint8_t*` because that is what `NDArray` has.
+            let data_ptr = ctx
+                .builder
+                .build_pointer_cast(data_ptr, get_opaque_uint8_ptr_type(ctx.ctx), "data_casted")
+                .unwrap();
+            ndarray.store_data(ctx, data_ptr);
+
+            // Finally, do `set_strides_by_shape`
+            // Check out https://ajcr.net/stride-guide-part-1/ to see what numpy "strides" are.
+            call_nac3_ndarray_set_strides_by_shape(ctx, ndarray);
+
+            Ok(ndarray)
+        }
+    }
+}
+
+pub fn get_ndarray_first_element<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NpArrayValue<'ctx>,
+    name: &str,
+) -> BasicValueEnum<'ctx> {
+    let data = ndarray.load_data(ctx);
+
+    // Cast `data` to the actual element the `subndarray` holds
+    // otherwise `subndarray.data` is just a bunch of `uint8_t*`
+    let data = ctx
+        .builder
+        .build_pointer_cast(
+            data,
+            ndarray.ty.elem_type.ptr_type(AddressSpace::default()),
+            "data_casted",
+        )
+        .unwrap();
+
+    // Load the element
+    ctx.builder.build_load(data, name).unwrap()
+}
+
+pub fn call_ndarray_subscript_impl<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: NpArrayValue<'ctx>,
+    ndslices: &Vec<&NDSlice<'ctx>>,
+) -> Result<NpArrayValue<'ctx>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    // First we will calculate the correct ndims of the dst_ndarray
+    // Then allocate for dst_ndarray (A known `ndims` value is required for this)
+    // Finally do call the IRRT function that actually does subscript
+
+    let size_type = ndarray.ty.size_type;
+
+    // Prepare the argument `ndims`
+    let ndims = ndarray.load_ndims(ctx);
+
+    // Prepare the argument `num_slices` in LLVM - which conveniently is simply `ndslices.len()`
+    let num_slices = size_type.const_int(ndslices.len() as u64, false);
+
+    // Prepare the argument `slices`
+    let ndslices_ptr = IrrtNDSliceType::alloca_ndslices(ctx, ndslices);
+
+    // Get `dst_ndims`
+    let dst_ndims = call_nac3_ndarray_deduce_ndims_after_slicing(
+        ctx,
+        size_type,
+        ndims,
+        num_slices,
+        ndslices_ptr,
+    );
+
+    // Allocate `dst_ndarray`
+    let dst_ndarray = alloca_ndarray_and_init(
+        generator,
+        ctx,
+        ndarray.ty.elem_type,
+        NDArrayInitMode::SetNDim { ndim: dst_ndims },
+        "subndarray",
+    )?;
+
+    call_nac3_ndarray_subscript(ctx, ndarray, num_slices, ndslices_ptr, dst_ndarray);
+
+    Ok(dst_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: &str,
+) -> Result<NpArrayValue<'ctx>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let elem_type = ctx.get_llvm_type(generator, elem_ty);
+    let shape = parse_input_shape_arg(generator, ctx, shape, shape_ty)?;
+    let ndarray = alloca_ndarray_and_init(
+        generator,
+        ctx,
+        elem_type,
+        NDArrayInitMode::SetShapeAndAllocaData { shape },
+        name,
+    )?;
+    Ok(ndarray)
+}
+
+fn call_ndarray_fill_impl<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    elem_ty: Type,
+    shape: BasicValueEnum<'ctx>,
+    shape_ty: Type,
+    fill_value: BasicValueEnum<'ctx>,
+    name: &str,
+) -> Result<NpArrayValue<'ctx>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let ndarray = call_ndarray_empty_impl(generator, ctx, elem_ty, shape, shape_ty, name)?;
+    irrt::call_nac3_ndarray_fill_generic(ctx, ndarray, fill_value);
+    Ok(ndarray)
+}
+
+/// 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);
+
+    // Parse arguments
+    let shape_ty = fun.0.args[0].ty;
+    let shape = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
+
+    // Implementation
+    let ndarray = call_ndarray_empty_impl(
+        generator,
+        context,
+        context.primitives.float,
+        shape,
+        shape_ty,
+        "empty_ndarray",
+    )?;
+    Ok(ndarray.ptr)
+}
+
+/// Generates LLVM IR for `np.zeros`.
+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);
+
+    // Parse arguments
+    let shape_ty = fun.0.args[0].ty;
+    let shape = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
+
+    // Implementation
+    // NOTE: Currently nac3's `np.zeros` is always `float64`.
+    let float64_ty = context.primitives.float;
+    let float64_llvm_type = context.get_llvm_type(generator, float64_ty).into_float_type();
+
+    let ndarray = call_ndarray_fill_impl(
+        generator,
+        context,
+        float64_ty, // `elem_ty` is always `float64`
+        shape,
+        shape_ty,
+        float64_llvm_type.const_zero().as_basic_value_enum(),
+        "zeros_ndarray",
+    )?;
+    Ok(ndarray.ptr)
+}
+
+/// Generates LLVM IR for `np.ones`.
+pub fn gen_ndarray_ones<'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);
+
+    // Parse arguments
+    let shape_ty = fun.0.args[0].ty;
+    let shape = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
+
+    // Implementation
+    // NOTE: Currently nac3's `np.ones` is always `float64`.
+    let float64_ty = context.primitives.float;
+    let float64_llvm_type = context.get_llvm_type(generator, float64_ty).into_float_type();
+
+    let ndarray = call_ndarray_fill_impl(
+        generator,
+        context,
+        float64_ty, // `elem_ty` is always `float64`
+        shape,
+        shape_ty,
+        float64_llvm_type.const_float(1.0).as_basic_value_enum(),
+        "ones_ndarray",
+    )?;
+    Ok(ndarray.ptr)
+}

nac3core/src/codegen/structure.rs

@@ -0,0 +1,318 @@
+use std::marker::PhantomData;
+
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum, IntType, PointerType, StructType},
+    values::{BasicValue, BasicValueEnum, IntValue, PointerValue},
+    AddressSpace,
+};
+
+use super::CodeGenContext;
+
+#[derive(Debug, Clone, Copy)]
+pub struct FieldInfo {
+    gep_index: u32,
+    name: &'static str,
+}
+
+impl FieldInfo {
+    pub fn llvm_gep<'ctx>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        struct_ptr: PointerValue<'ctx>,
+    ) -> PointerValue<'ctx> {
+        let index_type = ctx.ctx.i32_type(); // TODO: I think I'm not supposed to *just* 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()
+        }
+    }
+
+    pub fn llvm_load<'ctx>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        struct_ptr: PointerValue<'ctx>,
+    ) -> BasicValueEnum<'ctx> {
+        // We will use `self.name` as the LLVM label for debugging purposes
+        ctx.builder.build_load(self.llvm_gep(ctx, struct_ptr), self.name).unwrap()
+    }
+
+    pub fn llvm_store<'ctx>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        struct_ptr: PointerValue<'ctx>,
+        value: BasicValueEnum<'ctx>,
+    ) {
+        ctx.builder.build_store(self.llvm_gep(ctx, struct_ptr), value).unwrap();
+    }
+}
+
+pub struct Object<'ctx, T> {
+    pub ty: T,
+    pub ptr: PointerValue<'ctx>,
+}
+
+pub struct Field<'ctx, T: CustomType<'ctx>> {
+    pub info: FieldInfo,
+    pub ty: T,
+    _phantom: PhantomData<&'ctx ()>,
+}
+
+pub struct FieldCreator<'ctx> {
+    pub ctx: &'ctx Context,
+    struct_name: &'ctx str,
+    gep_index_counter: u32,
+    fields: Vec<(FieldInfo, BasicTypeEnum<'ctx>)>,
+}
+
+impl<'ctx> FieldCreator<'ctx> {
+    pub fn new(ctx: &'ctx Context, struct_name: &'ctx str) -> Self {
+        FieldCreator { ctx, struct_name, gep_index_counter: 0, fields: Vec::new() }
+    }
+
+    fn next_gep_index(&mut self) -> u32 {
+        let index = self.gep_index_counter;
+        self.gep_index_counter += 1;
+        index
+    }
+
+    fn get_struct_field_types(&self) -> Vec<BasicTypeEnum<'ctx>> {
+        self.fields.iter().map(|x| x.1.clone()).collect()
+    }
+
+    pub fn add_field<T: CustomType<'ctx>>(&mut self, name: &'static str, ty: T) -> Field<'ctx, T> {
+        let gep_index = self.next_gep_index();
+
+        let field_type = ty.llvm_basic_type_enum(self.ctx);
+        let field_info = FieldInfo { gep_index, name };
+        let field = Field { info: field_info, ty, _phantom: PhantomData };
+
+        self.fields.push((field_info.clone(), field_type));
+
+        field
+    }
+
+    fn num_fields(&self) -> u32 {
+        self.fields.len() as u32 // casted to u32 because that is what inkwell returns
+    }
+}
+
+pub trait CustomType<'ctx>: Clone {
+    type Value;
+
+    fn llvm_basic_type_enum(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx>;
+
+    fn llvm_field_load(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        field: FieldInfo,
+        struct_ptr: PointerValue<'ctx>,
+    ) -> Self::Value;
+
+    fn llvm_field_store(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        field: FieldInfo,
+        struct_ptr: PointerValue<'ctx>,
+        value: &Self::Value,
+    );
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct IntType2<'ctx>(pub IntType<'ctx>);
+
+impl<'ctx> CustomType<'ctx> for IntType2<'ctx> {
+    type Value = IntValue<'ctx>;
+
+    fn llvm_basic_type_enum(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
+        self.0.as_basic_type_enum()
+    }
+
+    fn llvm_field_load(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        field: FieldInfo,
+        struct_ptr: PointerValue<'ctx>,
+    ) -> Self::Value {
+        let int_value = field.llvm_load(ctx, struct_ptr).into_int_value();
+        assert_eq!(int_value.get_type().get_bit_width(), self.0.get_bit_width());
+        int_value
+    }
+
+    fn llvm_field_store(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        field: FieldInfo,
+        struct_ptr: PointerValue<'ctx>,
+        int_value: &Self::Value,
+    ) {
+        assert_eq!(int_value.get_type().get_bit_width(), self.0.get_bit_width());
+        field.llvm_store(ctx, struct_ptr, int_value.as_basic_value_enum());
+    }
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct PointerType2<'ctx>(pub PointerType<'ctx>);
+
+impl<'ctx> CustomType<'ctx> for PointerType2<'ctx> {
+    type Value = PointerValue<'ctx>;
+
+    fn llvm_basic_type_enum(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
+        self.0.as_basic_type_enum()
+    }
+
+    fn llvm_field_load(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        field: FieldInfo,
+        struct_ptr: PointerValue<'ctx>,
+    ) -> Self::Value {
+        field.llvm_load(ctx, struct_ptr).into_pointer_value()
+    }
+
+    fn llvm_field_store(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        field: FieldInfo,
+        struct_ptr: PointerValue<'ctx>,
+        pointer_value: &Self::Value,
+    ) {
+        field.llvm_store(ctx, struct_ptr, pointer_value.as_basic_value_enum());
+    }
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct PointingArrayType<'ctx, ElementType: CustomType<'ctx>> {
+    pub element_type: ElementType,
+    _phantom: PhantomData<&'ctx ()>,
+}
+
+impl<'ctx, ElementType: CustomType<'ctx>> PointingArrayType<'ctx, ElementType> {
+    pub fn new(element_type: ElementType) -> Self {
+        PointingArrayType { element_type, _phantom: PhantomData }
+    }
+}
+
+impl<'ctx, Element: CustomType<'ctx>> CustomType<'ctx> for PointingArrayType<'ctx, Element> {
+    type Value = Object<'ctx, Self>;
+
+    fn llvm_basic_type_enum(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
+        // Element*
+        self.element_type
+            .llvm_basic_type_enum(ctx)
+            .ptr_type(AddressSpace::default())
+            .as_basic_type_enum()
+    }
+
+    fn llvm_field_load(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        field: FieldInfo,
+        struct_ptr: PointerValue<'ctx>,
+    ) -> Self::Value {
+        // Remember that it is just a pointer
+        Object { ty: self.clone(), ptr: field.llvm_load(ctx, struct_ptr).into_pointer_value() }
+    }
+
+    fn llvm_field_store(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        field: FieldInfo,
+        struct_ptr: PointerValue<'ctx>,
+        value: &Self::Value,
+    ) {
+        // Remember that it is just a pointer
+        todo!()
+    }
+}
+
+pub fn check_basic_types_match<'ctx, A, B>(expected: A, got: B) -> Result<(), String>
+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(())
+}
+
+pub trait CustomStructType<'ctx> {
+    type Fields;
+
+    fn llvm_struct_name() -> &'static str;
+
+    fn add_fields_to(&self, creator: &mut FieldCreator<'ctx>) -> Self::Fields;
+
+    fn fields(&self, ctx: &'ctx Context) -> Self::Fields {
+        let mut creator = FieldCreator::new(ctx, Self::llvm_struct_name());
+        let fields = self.add_fields_to(&mut creator);
+        fields
+    }
+
+    fn llvm_struct_type(&self, ctx: &'ctx Context) -> StructType<'ctx> {
+        let mut creator = FieldCreator::new(ctx, Self::llvm_struct_name());
+        self.add_fields_to(&mut creator);
+
+        ctx.struct_type(&creator.get_struct_field_types(), false)
+    }
+
+    fn check_struct_type(
+        &self,
+        ctx: &'ctx Context,
+        scrutinee: StructType<'ctx>,
+    ) -> Result<(), String> {
+        let mut creator = FieldCreator::new(ctx, Self::llvm_struct_name());
+        self.add_fields_to(&mut creator);
+
+        // Check scrutinee's number of struct fields
+        let expected_field_count = creator.num_fields();
+        let got_field_count = scrutinee.count_fields();
+        if got_field_count != expected_field_count {
+            return Err(format!(
+                "Expected {expected_count} field(s) in `{struct_name}` type, got {got_count}",
+                struct_name = Self::llvm_struct_name(),
+                expected_count = expected_field_count,
+                got_count = got_field_count,
+            ));
+        }
+
+        // Check the scrutinee's field types
+        for (field_info, expected_field_ty) in creator.fields {
+            let got_field_ty = scrutinee.get_field_type_at_index(field_info.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_info.gep_index,
+                    struct_name = Self::llvm_struct_name(),
+                    field_name = field_info.name,
+                ));
+            }
+        }
+
+        // Done
+        Ok(())
+    }
+}

nac3core/src/codegen/test.rs

@@ -438,14 +438,15 @@ fn test_classes_range_type_new() {
     assert!(RangeType::is_type(llvm_range.as_base_type()).is_ok());
 }
 
-#[test]
-fn test_classes_ndarray_type_new() {
-    let ctx = inkwell::context::Context::create();
-    let generator = DefaultCodeGenerator::new(String::new(), 64);
-
-    let llvm_i32 = ctx.i32_type();
-    let llvm_usize = generator.get_size_type(&ctx);
-
-    let llvm_ndarray = NDArrayType::new(&generator, &ctx, llvm_i32.into());
-    assert!(NDArrayType::is_type(llvm_ndarray.as_base_type(), llvm_usize).is_ok());
-}
+// #[test]
+// fn test_classes_ndarray_type_new() {
+//     let ctx = inkwell::context::Context::create();
+//     let generator = DefaultCodeGenerator::new(String::new(), 64);
+//
+//     let llvm_i32 = ctx.i32_type();
+//     let llvm_usize = generator.get_size_type(&ctx);
+//
+//     let llvm_ndarray = NDArrayType::new(&generator, &ctx, llvm_i32.into());
+//     assert!(NDArrayType::is_type(llvm_ndarray.as_base_type(), llvm_usize).is_ok());
+// }
+//

nac3core/src/lib.rs

@@ -7,6 +7,7 @@
 )]
 #![warn(clippy::pedantic)]
 #![allow(
+    unused,
     dead_code,
     clippy::cast_possible_truncation,
     clippy::cast_sign_loss,

nac3core/src/toplevel/builtins.rs

@@ -1,6 +1,7 @@
 use std::iter::once;
 
 use crate::util::SizeVariant;
+use classes::NpArrayType;
 use helper::{debug_assert_prim_is_allowed, make_exception_fields, PrimDefDetails};
 use indexmap::IndexMap;
 use inkwell::{
@@ -1193,14 +1194,13 @@ 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 => gen_ndarray_ones, // gen_ndarray_ones,
+                    _ => unreachable!(),
+                };
+                func(ctx, &obj, fun, &args, generator).map(|val| Some(val.as_basic_value_enum()))
             }),
         )
     }
@@ -1461,51 +1461,65 @@ impl<'a> BuiltinBuilder<'a> {
                                 }
                             }
                             TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-                                let llvm_i32 = ctx.ctx.i32_type();
-                                let llvm_usize = generator.get_size_type(ctx.ctx);
+                                // TODO: Check is unsized and throw error if so
 
-                                let arg = NDArrayValue::from_ptr_val(
-                                    arg.into_pointer_value(),
-                                    llvm_usize,
-                                    None,
-                                );
+                                // Parse `arg`
+                                let ndarray_ptr = arg.into_pointer_value(); // It has to be an ndarray
 
-                                let ndims = arg.dim_sizes().size(ctx, generator);
-                                ctx.make_assert(
-                                    generator,
-                                    ctx.builder
-                                        .build_int_compare(
-                                            IntPredicate::NE,
-                                            ndims,
-                                            llvm_usize.const_zero(),
-                                            "",
-                                        )
-                                        .unwrap(),
-                                    "0:TypeError",
-                                    &format!("{name}() of unsized object", name = prim.name()),
-                                    [None, None, None],
-                                    ctx.current_loc,
-                                );
+                                let size_type = generator.get_size_type(ctx.ctx);
+                                let ndarray_ty = NpArrayType::new_opaque_elem(ctx.ctx, size_type); // We don't need to care about the element type - we only want the shape
+                                let ndarray = ndarray_ty.value_from_ptr(ctx.ctx, ndarray_ptr);
 
-                                let len = unsafe {
-                                    arg.dim_sizes().get_typed_unchecked(
-                                        ctx,
-                                        generator,
-                                        &llvm_usize.const_zero(),
-                                        None,
-                                    )
-                                };
+                                let result = call_nac3_len(ctx, ndarray).as_basic_value_enum();
+                                Some(result)
 
-                                if len.get_type().get_bit_width() == 32 {
-                                    Some(len.into())
-                                } else {
-                                    Some(
-                                        ctx.builder
-                                            .build_int_truncate(len, llvm_i32, "len")
-                                            .map(Into::into)
-                                            .unwrap(),
-                                    )
-                                }
+                                // Some(.as_basic_value_enum())
+
+                                // let llvm_i32 = ctx.ctx.i32_type();
+                                // let llvm_usize = generator.get_size_type(ctx.ctx);
+
+                                // let arg = NDArrayValue::from_ptr_val(
+                                //     arg.into_pointer_value(),
+                                //     llvm_usize,
+                                //     None,
+                                // );
+
+                                // let ndims = arg.dim_sizes().size(ctx, generator);
+                                // ctx.make_assert(
+                                //     generator,
+                                //     ctx.builder
+                                //         .build_int_compare(
+                                //             IntPredicate::NE,
+                                //             ndims,
+                                //             llvm_usize.const_zero(),
+                                //             "",
+                                //         )
+                                //         .unwrap(),
+                                //     "0:TypeError",
+                                //     &format!("{name}() of unsized object", name = prim.name()),
+                                //     [None, None, None],
+                                //     ctx.current_loc,
+                                // );
+
+                                // let len = unsafe {
+                                //     arg.dim_sizes().get_typed_unchecked(
+                                //         ctx,
+                                //         generator,
+                                //         &llvm_usize.const_zero(),
+                                //         None,
+                                //     )
+                                // };
+
+                                // if len.get_type().get_bit_width() == 32 {
+                                //     Some(len.into())
+                                // } else {
+                                //     Some(
+                                //         ctx.builder
+                                //             .build_int_truncate(len, llvm_i32, "len")
+                                //             .map(Into::into)
+                                //             .unwrap(),
+                                //     )
+                                // }
                             }
                             _ => unreachable!(),
                         }

nac3core/src/util.rs

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

nac3standalone/demo/src/my_ndarray.py

@@ -0,0 +1,18 @@
+@extern
+def output_float64(x: float):
+    ...
+
+def output_ndarray_float_1(n: ndarray[float, Literal[1]]):
+    for i in range(len(n)):
+        output_float64(n[i])
+
+def output_ndarray_float_2(n: ndarray[float, Literal[2]]):
+    for r in range(len(n)):
+        for c in range(len(n[r])):
+            output_float64(n[r][c])
+
+def run() -> int32:
+    hello = np_ones((3, 4))
+    # output_float64(hello[2, 3])
+    output_ndarray_float_1(hello[::-2, 2])
+    return 0

nac3standalone/src/main.rs

@@ -449,6 +449,11 @@ fn main() {
         .create_target_machine(llvm_options.opt_level)
         .expect("couldn't create target machine");
 
+    // Debug print if DEBUG_STANDALONE_DUMP_IR is defined
+    if std::env::var("DEBUG_STANDALONE_DUMP_IR").is_ok() {
+        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);