WIP: core: stuck on Instruction does not dominate all uses!

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;
     };
@@ -123,7 +124,7 @@ 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;
@@ -213,8 +214,7 @@ namespace {
         }
 
         void set_pelement_value(uint8_t* pelement, const uint8_t* pvalue) {
-            // *pelement = 0;
+            __builtin_memcpy(pelement, pvalue, itemsize);
-            // __builtin_memcpy(pelement, pvalue, itemsize);
         }
 
         uint8_t* get_pelement_by_indices(const SizeT *indices) {
@@ -284,7 +284,13 @@ namespace {
             }
         }
 
-        // 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
@@ -295,7 +301,7 @@ 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
 
@@ -322,15 +328,15 @@ 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;
+                    UserSlice* user_slice = (UserSlice*) ndslice->slice;
-                    Slice<SizeT> slice = user_slice->indices(this->shape[this_axis]); // To resolve negative indices and other funny stuff written by the user
+                    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->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] = slice.step * this->strides[this_axis]; // Determine stride
+                    dst_ndarray->strides[dst_axis] = ((SizeT) slice.step) * this->strides[this_axis]; // Determine stride
-                    dst_ndarray->shape[dst_axis] = slice.len(); // Determine shape dimension
+                    dst_ndarray->shape[dst_axis] = (SizeT) slice.len(); // Determine shape dimension
 
                     // Next
                     dst_axis++;
@@ -426,7 +432,7 @@ namespace {
             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(src_pelement, src_pelement);
+                this->set_pelement_value(this_pelement, src_pelement);
             }
         }
     };
@@ -457,7 +463,19 @@ 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) {
+    int32_t __nac3_ndarray_deduce_ndims_after_slicing(int32_t ndims, int32_t num_slices, const NDSlice* slices) {
-    //     // ndarray->slice(num_slices, slices, dst_ndarray);
+        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);
+    }
 }

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;
+        SliceIndex start;
-        T stop;
+        SliceIndex stop;
-        T step;
+        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() {
+        SliceIndex len() {
-            T diff = stop - start;
+            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>
+    SliceIndex resolve_index_in_length(SliceIndex length, SliceIndex index) {
-    T resolve_index_in_length(T length, T 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

@@ -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,
@@ -387,7 +387,7 @@ 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 };
@@ -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 };

nac3core/src/codegen/classes.rs

@@ -1793,7 +1793,7 @@ pub struct StructFields<'ctx> {
     pub fields: Vec<StructField<'ctx>>,
 }
 
-struct StructFieldsBuilder<'ctx> {
+pub struct StructFieldsBuilder<'ctx> {
     gep_index_counter: u32,
     /// Name of the struct to be built.
     name: &'static str,
@@ -1909,11 +1909,11 @@ impl<'ctx> StructFields<'ctx> {
 }
 
 impl<'ctx> StructFieldsBuilder<'ctx> {
-    fn start(name: &'static str) -> Self {
+    pub 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> {
+    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;
 
@@ -1923,11 +1923,12 @@ impl<'ctx> StructFieldsBuilder<'ctx> {
         field // Return to the caller to conveniently let them do whatever they want
     }
 
-    fn end(self) -> StructFields<'ctx> {
+    pub fn end(self) -> StructFields<'ctx> {
         StructFields { name: self.name, fields: self.fields }
     }
 }
 
+// TODO: Use derppening's abstraction
 #[derive(Debug, Clone, Copy)]
 pub struct NpArrayType<'ctx> {
     pub size_type: IntType<'ctx>,
@@ -1952,15 +1953,15 @@ impl<'ctx> NpArrayType<'ctx> {
     }
 
     pub fn get_struct_type(&self, ctx: &'ctx Context) -> StructType<'ctx> {
-        self.fields().whole_struct.get_struct_type(ctx)
+        self.fields(ctx).whole_struct.get_struct_type(ctx)
     }
 
-    pub fn fields(&self) -> NpArrayStructFields<'ctx> {
+    pub fn fields(&self, ctx: &'ctx Context) -> NpArrayStructFields<'ctx> {
         let mut builder = StructFieldsBuilder::start("NpArray");
 
         let addrspace = AddressSpace::default();
 
-        let byte_type = self.size_type.get_context().i8_type();
+        let byte_type = ctx.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());
@@ -2018,6 +2019,23 @@ impl<'ctx> NpArrayType<'ctx> {
 
         return value;
     }
+
+    pub fn value_from_ptr(
+        &self,
+        ctx: &'ctx Context,
+        in_ndarray_ptr: PointerValue<'ctx>,
+    ) -> NpArrayValue<'ctx> {
+        if cfg!(debug_assertions) {
+            // Sanity check on `in_ndarray_ptr`'s type
+
+            let in_ndarray_struct_type =
+                in_ndarray_ptr.get_type().get_element_type().into_struct_type();
+
+            // unwrap to check
+            self.fields(ctx).whole_struct.is_type(in_ndarray_struct_type).unwrap();
+        }
+        NpArrayValue { ty: *self, ptr: in_ndarray_ptr }
+    }
 }
 
 #[derive(Debug, Clone, Copy)]
@@ -2028,47 +2046,47 @@ pub struct NpArrayValue<'ctx> {
 
 impl<'ctx> NpArrayValue<'ctx> {
     pub fn store_data(&self, ctx: &CodeGenContext<'ctx, '_>, new_data_ptr: PointerValue<'ctx>) {
-        let field = self.ty.fields().data;
+        let field = self.ty.fields(ctx.ctx).data;
         field.store(ctx, self.ptr, new_data_ptr);
     }
 
     pub fn load_ndims(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
-        let field = self.ty.fields().ndims;
+        let field = self.ty.fields(ctx.ctx).ndims;
         field.load(ctx, self.ptr).into_int_value()
     }
 
     pub fn store_ndims(&self, ctx: &CodeGenContext<'ctx, '_>, new_ndims: IntValue<'ctx>) {
-        let field = self.ty.fields().ndims;
+        let field = self.ty.fields(ctx.ctx).ndims;
         field.store(ctx, self.ptr, new_ndims);
     }
 
     pub fn load_itemsize(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
-        let field = self.ty.fields().itemsize;
+        let field = self.ty.fields(ctx.ctx).itemsize;
         field.load(ctx, self.ptr).into_int_value()
     }
 
     pub fn store_itemsize(&self, ctx: &CodeGenContext<'ctx, '_>, new_itemsize: IntValue<'ctx>) {
-        let field = self.ty.fields().itemsize;
+        let field = self.ty.fields(ctx.ctx).itemsize;
         field.store(ctx, self.ptr, new_itemsize);
     }
 
     pub fn load_shape(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
-        let field = self.ty.fields().shape;
+        let field = self.ty.fields(ctx.ctx).shape;
         field.load(ctx, self.ptr).into_pointer_value()
     }
 
     pub fn store_shape(&self, ctx: &CodeGenContext<'ctx, '_>, new_shape_ptr: PointerValue<'ctx>) {
-        let field = self.ty.fields().shape;
+        let field = self.ty.fields(ctx.ctx).shape;
         field.store(ctx, self.ptr, new_shape_ptr);
     }
 
     pub fn load_strides(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
-        let field = self.ty.fields().strides;
+        let field = self.ty.fields(ctx.ctx).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;
+        let field = self.ty.fields(ctx.ctx).strides;
         field.store(ctx, self.ptr, value);
     }
 
@@ -2078,7 +2096,7 @@ impl<'ctx> NpArrayValue<'ctx> {
         ctx: &CodeGenContext<'ctx, '_>,
     ) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
         // Get the pointer to `shape`
-        let field = self.ty.fields().shape;
+        let field = self.ty.fields(ctx.ctx).shape;
         let shape = field.load(ctx, self.ptr).into_pointer_value();
 
         // Load `ndims`
@@ -2097,7 +2115,7 @@ impl<'ctx> NpArrayValue<'ctx> {
         ctx: &CodeGenContext<'ctx, '_>,
     ) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
         // Get the pointer to `strides`
-        let field = self.ty.fields().strides;
+        let field = self.ty.fields(ctx.ctx).strides;
         let strides = field.load(ctx, self.ptr).into_pointer_value();
 
         // Load `ndims`

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,
+            ArrayLikeIndexer, ArrayLikeValue, ListType, ListValue, NDArrayDataProxy, NDArrayValue,
-            ProxyValue, RangeValue, TypedArrayLikeAccessor, UntypedArrayLikeAccessor,
+            ProxyType, ProxyValue, RangeValue, TypedArrayLikeAccessor, UntypedArrayLikeAccessor,
         },
         concrete_type::{ConcreteFuncArg, ConcreteTypeEnum, ConcreteTypeStore},
         gen_in_range_check, get_llvm_abi_type, get_llvm_type,
@@ -39,10 +43,12 @@ use inkwell::{
 };
 use itertools::{chain, izip, Either, Itertools};
 use nac3parser::ast::{
-    self, Boolop, Cmpop, Comprehension, Constant, Expr, ExprKind, Location, Operator, StrRef,
+    self, Boolop, Cmpop, Comprehension, Constant, Expr, ExprKind, Located, Location, Operator,
-    Unaryop,
+    StrRef, Unaryop,
 };
 
+use super::classes::{NpArrayType, NpArrayValue};
+
 pub fn get_subst_key(
     unifier: &mut Unifier,
     obj: Option<Type>,
@@ -2094,18 +2100,97 @@ pub fn gen_cmpop_expr<'ctx, G: CodeGenerator>(
 /// Generates code for a subscript expression on an `ndarray`.
 ///
 /// * `ty` - The `Type` of the `NDArray` elements.
-/// * `ndims` - The `Type` of the `NDArray` number-of-dimensions `Literal`.
+/// * `ndarray` - The `NDArray` value.
-/// * `v` - 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,
+    ndarray: NpArrayValue<'ctx>,
-    v: NDArrayValue<'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)?;
+
+                // NOTE: Now 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);
+    }
+
+    // Finally, perform the actual subscript logic
+    let subndarray = call_nac3_ndarray_subscript_and_alloc_dst(generator, ctx, ndarray, &ndslices.iter().collect_vec());
+
+    // ...and return the result
+    let result = ValueEnum::Dynamic(subndarray.ptr.into());
+    Ok(Some(result))
 
     // let llvm_i1 = ctx.ctx.bool_type();
     // let llvm_i32 = ctx.ctx.i32_type();
@@ -3031,17 +3116,27 @@ 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, _) = 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, ndarray, slice);
                 }
                 TypeEnum::TTuple { .. } => {
                     let index: u32 =

nac3core/src/codegen/irrt/mod.rs

@@ -1,11 +1,18 @@
-use crate::{typecheck::typedef::Type, util::SizeVariant};
+use std::ops::Deref;
+
+use crate::{
+    codegen::classes::{NDArrayType, StructFieldsBuilder},
+    typecheck::typedef::Type,
+    util::SizeVariant,
+};
 
 mod test;
 
 use super::{
     classes::{
         check_basic_types_match, ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue,
-        NDArrayValue, NpArrayType, NpArrayValue, TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
+        NDArrayValue, NpArrayType, NpArrayValue, StructField, StructFields, TypedArrayLikeAdapter,
+        UntypedArrayLikeAccessor,
     },
     llvm_intrinsics, CodeGenContext, CodeGenerator,
 };
@@ -16,8 +23,11 @@ use inkwell::{
     context::Context,
     memory_buffer::MemoryBuffer,
     module::Module,
-    types::{BasicType, BasicTypeEnum, FunctionType, IntType, PointerType},
+    types::{BasicType, BasicTypeEnum, FunctionType, IntType, PointerType, StructType},
-    values::{BasicValue, BasicValueEnum, CallSiteValue, FloatValue, FunctionValue, IntValue},
+    values::{
+        BasicValue, BasicValueEnum, CallSiteValue, FloatValue, FunctionValue, IntValue,
+        PointerValue,
+    },
     AddressSpace, IntPredicate,
 };
 use itertools::Either;
@@ -930,6 +940,202 @@ pub fn call_j0<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> Flo
 //     )
 // }
 
+pub fn get_sliceindex_type<'ctx>(ctx: &'ctx Context) -> IntType<'ctx> {
+    ctx.i32_type()
+}
+
+pub fn get_ndslicetype_constant_type<'ctx>(ctx: &'ctx Context) -> IntType<'ctx> {
+    ctx.i8_type()
+}
+
+// TODO: Move to classes.rs?
+/// NOTE: All `IntValue<'ctx>` must be `int32_t`
+pub struct UserSlice<'ctx> {
+    pub start: Option<IntValue<'ctx>>,
+    pub stop: Option<IntValue<'ctx>>,
+    pub step: Option<IntValue<'ctx>>,
+}
+
+pub struct IrrtUserSliceStructFields<'ctx> {
+    pub whole_struct: StructFields<'ctx>,
+
+    pub start_defined: StructField<'ctx>,
+    pub start: StructField<'ctx>,
+
+    pub stop_defined: StructField<'ctx>,
+    pub stop: StructField<'ctx>,
+
+    pub step_defined: StructField<'ctx>,
+    pub step: StructField<'ctx>,
+}
+
+// TODO: EMPTY STRUCT
+struct IrrtUserSlice {}
+
+impl IrrtUserSlice {
+    pub fn fields<'ctx>(ctx: &'ctx Context) -> IrrtUserSliceStructFields<'ctx> {
+        let int8 = ctx.i8_type();
+
+        // MUST match the corresponding struct defined in IRRT
+        let mut builder = StructFieldsBuilder::start("NDSlice");
+        let start_defined = builder.add_field("start_defined", int8.into());
+        let start = builder.add_field("start", get_sliceindex_type(ctx).into());
+        let stop_defined = builder.add_field("stop_defined", int8.into());
+        let stop = builder.add_field("stop", get_sliceindex_type(ctx).into());
+        let step_defined = builder.add_field("step_defined", int8.into());
+        let step = builder.add_field("step", get_sliceindex_type(ctx).into());
+
+        IrrtUserSliceStructFields {
+            start_defined,
+            start,
+            stop_defined,
+            stop,
+            step_defined,
+            step,
+            whole_struct: builder.end(),
+        }
+    }
+
+    pub fn alloca_user_slice<'ctx>(
+        ctx: &CodeGenContext<'ctx, '_>,
+        user_slice: &UserSlice<'ctx>,
+    ) -> PointerValue<'ctx> {
+        // Derive the struct_type
+        let fields = Self::fields(ctx.ctx);
+        let struct_type = fields.whole_struct.get_struct_type(ctx.ctx);
+
+        // ...and then allocate for a real `UserSlice` in LLVM
+        let user_slice_ptr = ctx.builder.build_alloca(struct_type, "user_slice").unwrap();
+
+        // i8 type to set start_defined, stop_defined, step_defined.
+        let llvm_i8 = ctx.ctx.i8_type();
+
+        // Now write to `user_slice_ptr`
+        let help = |value_defined_field: StructField<'ctx>,
+                    value_field: StructField<'ctx>,
+                    value: Option<IntValue<'ctx>>| {
+            match value {
+                None => {
+                    value_defined_field.store(ctx, user_slice_ptr, llvm_i8.const_zero());
+                    value_field.store(
+                        ctx,
+                        user_slice_ptr,
+                        get_sliceindex_type(ctx.ctx).const_zero(),
+                    );
+                }
+                Some(value) => {
+                    debug_assert_eq!(get_sliceindex_type(ctx.ctx), value.get_type()); // Sanity check just in case there is a bug somewhere
+                    value_defined_field.store(ctx, user_slice_ptr, llvm_i8.const_int(1, false));
+                    value_field.store(ctx, user_slice_ptr, value);
+                }
+            }
+        };
+
+        help(fields.start_defined, fields.start, user_slice.start);
+        help(fields.stop_defined, fields.stop, user_slice.stop);
+        help(fields.step_defined, fields.step, user_slice.step);
+
+        user_slice_ptr
+    }
+}
+
+// TODO: Move to classes.rs?
+/// A numpy slice. This corresponds to `NDSlice` defined in IRRT,
+/// but with more Rust sugar to help with implementing codegen.
+pub enum NDSlice<'ctx> {
+    /// Index [`IntValue`] must be `int32_t`
+    Index(IntValue<'ctx>),
+    Slice(UserSlice<'ctx>),
+    // TODO: Support https://numpy.org/doc/stable/user/basics.indexing.html#dimensional-indexing-tools; *should* be very easy to implement
+}
+
+// TODO: Empty struct
+pub struct IrrtNDSlice {}
+
+pub struct IrrtNDSliceStructFields<'ctx> {
+    pub whole_struct: StructFields<'ctx>,
+    pub type_: StructField<'ctx>,
+    pub slice: StructField<'ctx>,
+}
+
+impl IrrtNDSlice {
+    pub fn fields<'ctx>(ctx: &'ctx Context) -> IrrtNDSliceStructFields<'ctx> {
+        let mut builder = StructFieldsBuilder::start("NDSlice");
+
+        // MUST match the corresponding struct defined in IRRT
+        let type_ = builder.add_field("type", get_ndslicetype_constant_type(ctx).into());
+        let slice = builder.add_field("slice", get_opaque_uint8_ptr_type(ctx).into());
+
+        IrrtNDSliceStructFields { type_, slice, whole_struct: builder.end() }
+    }
+
+    pub fn alloca_ndslices<'ctx>(
+        ctx: &CodeGenContext<'ctx, '_>,
+        ndslices: &Vec<&NDSlice<'ctx>>,
+    ) -> PointerValue<'ctx> {
+        let fields = Self::fields(ctx.ctx);
+
+        // Derive the number of slices
+        let count = ndslices.len();
+        let count_llvm = ctx.ctx.i32_type().const_int(count as u64, false);
+
+        // Allocate `count` number of ndslices, and ready to write
+        let struct_type = fields.whole_struct.get_struct_type(ctx.ctx);
+        let ndslices_ptr =
+            ctx.builder.build_array_alloca(struct_type, count_llvm, "ndslices").unwrap();
+
+        for (ndslice_i, ndslice) in ndslices.iter().enumerate() {
+            // Setup the values that will build a real `NDSlice` in LLVM
+            // NOTE: (A INPUT_SLICE_TYPE_* constant value for `NDSlice::type`, the ptr for `NDArray::slice`)
+            let (type_, slice_ptr): (u8, PointerValue<'ctx>) = match ndslice {
+                NDSlice::Index(index) => {
+                    // Sanity check on `index.get_type()` just in case there is a bug somewhere
+                    debug_assert_eq!(get_sliceindex_type(ctx.ctx), index.get_type());
+
+                    // Refer to the IRRT to see what should be set to `uint8_t* slice`.
+                    let slice_ptr = ctx
+                        .builder
+                        .build_alloca(get_sliceindex_type(ctx.ctx), "index_slice")
+                        .unwrap();
+                    ctx.builder.build_store(slice_ptr, *index).unwrap();
+
+                    let type_ = 0; // const NDSliceType INPUT_SLICE_TYPE_INDEX = 0;
+                    (type_, slice_ptr)
+                }
+                NDSlice::Slice(user_slice) => {
+                    // Allocate the user_slice
+                    let slice_ptr = IrrtUserSlice::alloca_user_slice(ctx, user_slice);
+
+                    let type_ = 1; // const NDSliceType INPUT_SLICE_TYPE_SLICE = 1;
+                    (type_, slice_ptr)
+                }
+            };
+
+            // Get the pointer to the ndslice_i-th entry of `ndslices_llvm` and write to it.
+            let gep_index = ctx.ctx.i32_type().const_int(ndslice_i as u64, false);
+            let ndslice_entry_ptr = unsafe {
+                ctx.builder
+                    .build_in_bounds_gep(ndslices_ptr, &[gep_index], "ndslice_entry")
+                    .unwrap()
+            };
+
+            // Write `type_`
+            let type_llvm = get_ndslicetype_constant_type(ctx.ctx).const_int(type_ as u64, false);
+            fields.type_.store(ctx, ndslice_entry_ptr, type_llvm);
+
+            // Write `slice`
+            // `slice_ptr` has to be casted to `uint8_t*` beforehand
+            let slice_ptr = ctx
+                .builder
+                .build_pointer_cast(slice_ptr, get_opaque_uint8_ptr_type(ctx.ctx), "slices_casted")
+                .unwrap();
+            fields.slice.store(ctx, ndslice_entry_ptr, slice_ptr);
+        }
+
+        ndslices_ptr
+    }
+}
+
 fn get_size_variant<'ctx>(ty: IntType<'ctx>) -> SizeVariant {
     match ty.get_bit_width() {
         32 => SizeVariant::Bits32,
@@ -966,18 +1172,18 @@ where
 }
 
 pub fn get_irrt_ndarray_ptr_type<'ctx>(
-    ctx: &CodeGenContext<'ctx, '_>,
+    ctx: &'ctx Context,
     size_type: IntType<'ctx>,
 ) -> PointerType<'ctx> {
-    let i8_type = ctx.ctx.i8_type();
+    let i8_type = ctx.i8_type();
 
     let ndarray_ty = NpArrayType { size_type, elem_type: i8_type.as_basic_type_enum() };
-    let struct_ty = ndarray_ty.get_struct_type(ctx.ctx);
+    let struct_ty = ndarray_ty.get_struct_type(ctx);
     struct_ty.ptr_type(AddressSpace::default())
 }
 
-pub fn get_irrt_opaque_uint8_ptr_type<'ctx>(ctx: &CodeGenContext<'ctx, '_>) -> PointerType<'ctx> {
+pub fn get_opaque_uint8_ptr_type<'ctx>(ctx: &'ctx Context) -> PointerType<'ctx> {
-    ctx.ctx.i8_type().ptr_type(AddressSpace::default())
+    ctx.i8_type().ptr_type(AddressSpace::default())
 }
 
 pub fn call_nac3_ndarray_size<'ctx>(
@@ -987,7 +1193,7 @@ pub fn call_nac3_ndarray_size<'ctx>(
     // Get the IRRT function
     let size_type = ndarray.ty.size_type;
     let function = get_size_type_dependent_function(ctx, size_type, "__nac3_ndarray_size", || {
-        size_type.fn_type(&[get_irrt_ndarray_ptr_type(ctx, size_type).into()], false)
+        size_type.fn_type(&[get_irrt_ndarray_ptr_type(ctx.ctx, size_type).into()], false)
     });
 
     // Call the IRRT function
@@ -1014,8 +1220,8 @@ pub fn call_nac3_ndarray_fill_generic<'ctx>(
         get_size_type_dependent_function(ctx, size_type, "__nac3_ndarray_fill_generic", || {
             ctx.ctx.void_type().fn_type(
                 &[
-                    get_irrt_ndarray_ptr_type(ctx, size_type).into(), // NDArray<SizeT>* ndarray
+                    get_irrt_ndarray_ptr_type(ctx.ctx, size_type).into(), // NDArray<SizeT>* ndarray
-                    get_irrt_opaque_uint8_ptr_type(ctx).into(), // uint8_t* pvalue
+                    get_opaque_uint8_ptr_type(ctx.ctx).into(),            // uint8_t* pvalue
                 ],
                 false,
             )
@@ -1026,7 +1232,8 @@ pub fn call_nac3_ndarray_fill_generic<'ctx>(
     ctx.builder.build_store(pvalue, fill_value).unwrap();
 
     // Cast pvalue to `uint8_t*`
-    let pvalue = ctx.builder.build_pointer_cast(pvalue, get_irrt_opaque_uint8_ptr_type(ctx), "").unwrap();
+    let pvalue =
+        ctx.builder.build_pointer_cast(pvalue, get_opaque_uint8_ptr_type(ctx.ctx), "").unwrap();
 
     // Call the IRRT function
     ctx.builder
@@ -1041,22 +1248,25 @@ pub fn call_nac3_ndarray_fill_generic<'ctx>(
         .unwrap();
 }
 
-
 pub fn call_nac3_ndarray_set_strides_by_shape<'ctx>(
     ctx: &CodeGenContext<'ctx, '_>,
     ndarray: NpArrayValue<'ctx>,
 ) {
     // Get the IRRT function
     let size_type = ndarray.ty.size_type;
-    let function =
+    let function = get_size_type_dependent_function(
-        get_size_type_dependent_function(ctx, size_type, "__nac3_ndarray_set_strides_by_shape", || {
+        ctx,
+        size_type,
+        "__nac3_ndarray_set_strides_by_shape",
+        || {
             ctx.ctx.void_type().fn_type(
                 &[
-                    get_irrt_ndarray_ptr_type(ctx, size_type).into(), // NDArray<SizeT>* ndarray
+                    get_irrt_ndarray_ptr_type(ctx.ctx, size_type).into(), // NDArray<SizeT>* ndarray
                 ],
                 false,
             )
-        });
+        },
+    );
 
     // Call the IRRT function
     ctx.builder
@@ -1069,3 +1279,132 @@ pub fn call_nac3_ndarray_set_strides_by_shape<'ctx>(
         )
         .unwrap();
 }
+
+pub fn call_nac3_ndarray_deduce_ndims_after_slicing_raw<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    size_type: IntType<'ctx>,
+    ndims: IntValue<'ctx>,
+    num_slices: IntValue<'ctx>,
+    ndslices_ptr: PointerValue<'ctx>,
+) -> IntValue<'ctx> {
+    // Get the IRRT function
+    let function = get_size_type_dependent_function(
+        ctx,
+        size_type,
+        "__nac3_ndarray_deduce_ndims_after_slicing",
+        || {
+            size_type.fn_type(
+                &[
+                    size_type.into(), // SizeT ndims
+                    size_type.into(), // SizeT num_slices
+                    IrrtNDSlice::fields(ctx.ctx)
+                        .whole_struct
+                        .get_struct_type(ctx.ctx)
+                        .ptr_type(AddressSpace::default())
+                        .into(), // NDSlice* slices
+                ],
+                false,
+            )
+        },
+    );
+
+    // Call the IRRT function
+    ctx.builder
+        .build_call(
+            function,
+            &[
+                ndims.into(),        // ndims
+                num_slices.into(),   // num_slices
+                ndslices_ptr.into(), // slices
+            ],
+            "ndims_after_slicing",
+        )
+        .unwrap()
+        .try_as_basic_value()
+        .unwrap_left()
+        .into_int_value()
+}
+
+// TODO: RENAME ME AND MY FRIENDS
+pub fn call_nac3_ndarray_subscript_raw<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NpArrayValue<'ctx>,
+    num_slices: IntValue<'ctx>,
+    slices: PointerValue<'ctx>,
+    dst_ndarray: NpArrayValue<'ctx>,
+) {
+    // Get the IRRT function
+    let size_type = ndarray.ty.size_type;
+    let function =
+        get_size_type_dependent_function(ctx, size_type, "__nac3_ndarray_subscript", || {
+            ctx.ctx.void_type().fn_type(
+                &[
+                    get_irrt_ndarray_ptr_type(ctx.ctx, size_type).into(), // NDArray<SizeT>* ndarray
+                    size_type.into(),                                     // SizeT num_slices
+                    IrrtNDSlice::fields(ctx.ctx)
+                        .whole_struct
+                        .get_struct_type(ctx.ctx)
+                        .ptr_type(AddressSpace::default())
+                        .into(), // NDSlice* slices
+                    get_irrt_ndarray_ptr_type(ctx.ctx, size_type).into(), // NDArray<SizeT>* dst_ndarray
+                ],
+                false,
+            )
+        });
+
+    // Call the IRRT function
+    ctx.builder
+        .build_call(
+            function,
+            &[
+                ndarray.ptr.into(),     // ndarray
+                num_slices.into(),      // num_slices
+                slices.into(),          // slices
+                dst_ndarray.ptr.into(), // dst_ndarray
+            ],
+            "subndarray",
+        )
+        .unwrap();
+}
+
+pub fn call_nac3_ndarray_subscript_and_alloc_dst<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: NpArrayValue<'ctx>,
+    ndslices: &Vec<&NDSlice<'ctx>>,
+) -> NpArrayValue<'ctx>
+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 = IrrtNDSlice::alloca_ndslices(ctx, ndslices);
+
+    // Deduce the ndims
+    let dst_ndims = call_nac3_ndarray_deduce_ndims_after_slicing_raw(
+        ctx,
+        ndarray.ty.size_type,
+        ndims,
+        num_slices,
+        ndslices_ptr,
+    );
+
+    // Allocate `dst_ndarray`
+    let dst_ndarray =
+        ndarray.ty.var_alloc(generator, ctx, dst_ndims, Some("subscript_dst_ndarray"));
+
+    call_nac3_ndarray_subscript_raw(ctx, ndarray, num_slices, ndslices_ptr, dst_ndarray);
+
+    dst_ndarray
+}

nac3core/src/codegen/numpy.rs

@@ -37,7 +37,7 @@ use super::{
     classes::NpArrayValue,
     irrt::{
         call_nac3_ndarray_set_strides_by_shape, call_nac3_ndarray_size, get_irrt_ndarray_ptr_type,
-        get_irrt_opaque_uint8_ptr_type,
+        get_opaque_uint8_ptr_type,
     },
     stmt::gen_return,
 };
@@ -2306,7 +2306,7 @@ where
             // 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_irrt_opaque_uint8_ptr_type(ctx), "data_casted")
+                .build_pointer_cast(data_ptr, get_opaque_uint8_ptr_type(ctx.ctx), "data_casted")
                 .unwrap();
             ndarray.store_data(ctx, data_ptr);
 
@@ -2410,7 +2410,7 @@ pub fn gen_ndarray_zeros<'ctx>(
     let ndarray = call_ndarray_fill_impl(
         generator,
         context,
-        float64_ty,
+        float64_ty, // `elem_ty` is always `float64`
         shape,
         shape_ty,
         float64_llvm_type.const_zero().as_basic_value_enum(),
@@ -2442,11 +2442,11 @@ pub fn gen_ndarray_ones<'ctx>(
     let ndarray = call_ndarray_fill_impl(
         generator,
         context,
-        float64_ty,
+        float64_ty, // `elem_ty` is always `float64`
         shape,
         shape_ty,
         float64_llvm_type.const_float(1.0).as_basic_value_enum(),
-        Some("np_zeros.result"),
+        Some("np_ones.result"),
     )?;
     Ok(ndarray.ptr)
 }