WIP 6

nac3core/build.rs

@@ -3,20 +3,34 @@ use std::{
     env,
     fs::File,
     io::Write,
-    path::Path,
+    path::{Path, PathBuf},
     process::{Command, Stdio},
 };
 
-fn compile_irrt(irrt_dir: &Path, out_dir: &Path) {
-    let irrt_cpp_path = irrt_dir.join("irrt.cpp");
+const CMD_IRRT_CLANG: &str = "clang-irrt";
+const CMD_IRRT_CLANG_TEST: &str = "clang-irrt-test";
+const CMD_IRRT_LLVM_AS: &str = "llvm-as-irrt";
+
+fn get_out_dir() -> PathBuf {
+    PathBuf::from(env::var("OUT_DIR").unwrap())
+}
+
+fn get_irrt_dir() -> &'static Path {
+    Path::new("irrt")
+}
+
+/// Compile `irrt.cpp` for use in `src/codegen`
+fn compile_irrt_cpp() {
+    let out_dir = get_out_dir();
+    let irrt_dir = get_irrt_dir();
 
     /*
      * HACK: Sadly, clang doesn't let us emit generic LLVM bitcode.
      * Compiling for WASM32 and filtering the output with regex is the closest we can get.
      */
+    let irrt_cpp_path = irrt_dir.join("irrt.cpp");
     let flags: &[&str] = &[
         "--target=wasm32",
-        irrt_cpp_path.to_str().unwrap(),
         "-x",
         "c++",
         "-fno-discard-value-names",
@@ -36,11 +50,14 @@ fn compile_irrt(irrt_dir: &Path, out_dir: &Path) {
         irrt_dir.to_str().unwrap(),
         "-o",
         "-",
+        irrt_cpp_path.to_str().unwrap(),
     ];
 
-    println!("cargo:rerun-if-changed={}", out_dir.to_str().unwrap());
+    // Tell Cargo to rerun if any file under `irrt_dir` (recursive) changes
+    println!("cargo:rerun-if-changed={}", irrt_dir.to_str().unwrap());
 
-    let output = Command::new("clang-irrt")
+    // Compile IRRT and capture the LLVM IR output
+    let output = Command::new(CMD_IRRT_CLANG)
         .args(flags)
         .output()
         .map(|o| {
@@ -53,11 +70,17 @@ fn compile_irrt(irrt_dir: &Path, out_dir: &Path) {
     let output = std::str::from_utf8(&output.stdout).unwrap().replace("\r\n", "\n");
     let mut filtered_output = String::with_capacity(output.len());
 
-    // (?ms:^define.*?\}$) to capture `define` blocks
-    // (?m:^declare.*?$) to capture `declare` blocks
-    // (?m:^%.+?=\s*type\s*\{.+?\}$) to capture `type` declarations
-    let regex_filter =
-        Regex::new(r"(?ms:^define.*?\}$)|(?m:^declare.*?$)|(?m:^%.+?=\s*type\s*\{.+?\}$)").unwrap();
+    // Filter out irrelevant IR
+    //
+    // Regex:
+    // - `(?ms:^define.*?\}$)` captures LLVM `define` blocks
+    // - `(?m:^declare.*?$)` captures LLVM `declare` lines
+    // - `(?m:^%.+?=\s*type\s*\{.+?\}$)` captures LLVM `type` declarations
+    // - `(?m:^@.+?=.+$)` captures global constants
+    let regex_filter = Regex::new(
+        r"(?ms:^define.*?\}$)|(?m:^declare.*?$)|(?m:^%.+?=\s*type\s*\{.+?\}$)|(?m:^@.+?=.+$)",
+    )
+    .unwrap();
     for f in regex_filter.captures_iter(&output) {
         assert_eq!(f.len(), 1);
         filtered_output.push_str(&f[0]);
@@ -68,15 +91,21 @@ fn compile_irrt(irrt_dir: &Path, out_dir: &Path) {
         .unwrap()
         .replace_all(&filtered_output, "");
 
-    println!("cargo:rerun-if-env-changed=DEBUG_DUMP_IRRT");
-    if env::var("DEBUG_DUMP_IRRT").is_ok() {
+    // For debugging
+    // Doing `DEBUG_DUMP_IRRT=1 cargo build -p nac3core` dumps the LLVM IR generated
+    const DEBUG_DUMP_IRRT: &str = "DEBUG_DUMP_IRRT";
+    println!("cargo:rerun-if-env-changed={DEBUG_DUMP_IRRT}");
+    if env::var(DEBUG_DUMP_IRRT).is_ok() {
         let mut file = File::create(out_dir.join("irrt.ll")).unwrap();
         file.write_all(output.as_bytes()).unwrap();
+
         let mut file = File::create(out_dir.join("irrt-filtered.ll")).unwrap();
         file.write_all(filtered_output.as_bytes()).unwrap();
     }
 
-    let mut llvm_as = Command::new("llvm-as-irrt")
+    // Assemble the emitted and filtered IR to .bc
+    // That .bc will be integrated into nac3core's codegen
+    let mut llvm_as = Command::new(CMD_IRRT_LLVM_AS)
         .stdin(Stdio::piped())
         .arg("-o")
         .arg(out_dir.join("irrt.bc"))
@@ -86,10 +115,13 @@ fn compile_irrt(irrt_dir: &Path, out_dir: &Path) {
     assert!(llvm_as.wait().unwrap().success());
 }
 
-fn compile_irrt_test(irrt_dir: &Path, out_dir: &Path) {
-    let irrt_test_cpp_path = irrt_dir.join("irrt_test.cpp");
-    let exe_path = out_dir.join("irrt_test.out");
+/// Compile `irrt_test.cpp` for testing
+fn compile_irrt_test_cpp() {
+    let out_dir = get_out_dir();
+    let irrt_dir = get_irrt_dir();
 
+    let exe_path = out_dir.join("irrt_test.out"); // Output path of the compiled test executable
+    let irrt_test_cpp_path = irrt_dir.join("irrt_test.cpp");
     let flags: &[&str] = &[
         irrt_test_cpp_path.to_str().unwrap(),
         "-x",
@@ -103,11 +135,13 @@ fn compile_irrt_test(irrt_dir: &Path, out_dir: &Path) {
         "-Wextra",
         "-Werror=return-type",
         "-lm", // for `tgamma()`, `lgamma()`
+        "-I",
+        irrt_dir.to_str().unwrap(),
         "-o",
         exe_path.to_str().unwrap(),
     ];
 
-    Command::new("clang-irrt-test")
+    Command::new(CMD_IRRT_CLANG_TEST)
         .args(flags)
         .output()
         .map(|o| {
@@ -115,20 +149,15 @@ fn compile_irrt_test(irrt_dir: &Path, out_dir: &Path) {
             o
         })
         .unwrap();
-    println!("cargo:rerun-if-changed={}", out_dir.to_str().unwrap());
+    println!("cargo:rerun-if-changed={}", irrt_dir.to_str().unwrap());
 }
 
 fn main() {
-    let out_dir = env::var("OUT_DIR").unwrap();
-    let out_dir = Path::new(&out_dir);
-
-    let irrt_dir = Path::new("./irrt");
-
-    compile_irrt(irrt_dir, out_dir);
+    compile_irrt_cpp();
 
     // https://github.com/rust-lang/cargo/issues/2549
     // `cargo test -F test` to also build `irrt_test.cpp
     if cfg!(feature = "test") {
-        compile_irrt_test(irrt_dir, out_dir);
+        compile_irrt_test_cpp();
     }
 }

nac3core/irrt/irrt.cpp

@@ -1,5 +1,9 @@
-#include "irrt_everything.hpp"
+#define IRRT_DEFINE_TYPEDEF_INTS
+#include <irrt_everything.hpp>
 
 /*
-    This file will be read by `clang-irrt` to conveniently produce LLVM IR for `nac3core/codegen`.
+    All IRRT implementations.
+
+    We don't have any pre-compiled objects, so we are writing all implementations in headers and
+    concatenate them with `#include` into one massive source file that contains all the IRRT stuff.
 */

nac3core/irrt/irrt.hpp

@@ -1,437 +0,0 @@
-#ifndef IRRT_DONT_TYPEDEF_INTS
-typedef _BitInt(8) int8_t;
-typedef unsigned _BitInt(8) uint8_t;
-typedef _BitInt(32) int32_t;
-typedef unsigned _BitInt(32) uint32_t;
-typedef _BitInt(64) int64_t;
-typedef unsigned _BitInt(64) uint64_t;
-#endif
-
-// NDArray indices are always `uint32_t`.
-typedef uint32_t NDIndex;
-// The type of an index or a value describing the length of a range/slice is
-// always `int32_t`.
-typedef int32_t SliceIndex;
-
-template <typename T>
-static T max(T a, T b) {
-    return a > b ? a : b;
-}
-
-template <typename T>
-static T min(T a, T b) {
-    return a > b ? b : a;
-}
-
-// adapted from GNU Scientific Library: https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
-// need to make sure `exp >= 0` before calling this function
-template <typename T>
-static T __nac3_int_exp_impl(T base, T exp) {
-    T res = 1;
-    /* repeated squaring method */
-    do {
-        if (exp & 1) {
-            res *= base; /* for n odd */
-        }
-        exp >>= 1;
-        base *= base;
-    } while (exp);
-    return res;
-}
-
-template <typename SizeT>
-static SizeT __nac3_ndarray_calc_size_impl(
-    const SizeT *list_data,
-    SizeT list_len,
-    SizeT begin_idx,
-    SizeT end_idx
-) {
-    __builtin_assume(end_idx <= list_len);
-
-    SizeT num_elems = 1;
-    for (SizeT i = begin_idx; i < end_idx; ++i) {
-        SizeT val = list_data[i];
-        __builtin_assume(val > 0);
-        num_elems *= val;
-    }
-    return num_elems;
-}
-
-template <typename SizeT>
-static void __nac3_ndarray_calc_nd_indices_impl(
-    SizeT index,
-    const SizeT *dims,
-    SizeT num_dims,
-    NDIndex *idxs
-) {
-    SizeT stride = 1;
-    for (SizeT dim = 0; dim < num_dims; dim++) {
-        SizeT i = num_dims - dim - 1;
-        __builtin_assume(dims[i] > 0);
-        idxs[i] = (index / stride) % dims[i];
-        stride *= dims[i];
-    }
-}
-
-template <typename SizeT>
-static SizeT __nac3_ndarray_flatten_index_impl(
-    const SizeT *dims,
-    SizeT num_dims,
-    const NDIndex *indices,
-    SizeT num_indices
-) {
-    SizeT idx = 0;
-    SizeT stride = 1;
-    for (SizeT i = 0; i < num_dims; ++i) {
-        SizeT ri = num_dims - i - 1;
-        if (ri < num_indices) {
-            idx += stride * indices[ri];
-        }
-
-        __builtin_assume(dims[i] > 0);
-        stride *= dims[ri];
-    }
-    return idx;
-}
-
-template <typename SizeT>
-static void __nac3_ndarray_calc_broadcast_impl(
-    const SizeT *lhs_dims,
-    SizeT lhs_ndims,
-    const SizeT *rhs_dims,
-    SizeT rhs_ndims,
-    SizeT *out_dims
-) {
-    SizeT max_ndims = lhs_ndims > rhs_ndims ? lhs_ndims : rhs_ndims;
-
-    for (SizeT i = 0; i < max_ndims; ++i) {
-        const SizeT *lhs_dim_sz = i < lhs_ndims ? &lhs_dims[lhs_ndims - i - 1] : nullptr;
-        const SizeT *rhs_dim_sz = i < rhs_ndims ? &rhs_dims[rhs_ndims - i - 1] : nullptr;
-        SizeT *out_dim = &out_dims[max_ndims - i - 1];
-
-        if (lhs_dim_sz == nullptr) {
-            *out_dim = *rhs_dim_sz;
-        } else if (rhs_dim_sz == nullptr) {
-            *out_dim = *lhs_dim_sz;
-        } else if (*lhs_dim_sz == 1) {
-            *out_dim = *rhs_dim_sz;
-        } else if (*rhs_dim_sz == 1) {
-            *out_dim = *lhs_dim_sz;
-        } else if (*lhs_dim_sz == *rhs_dim_sz) {
-            *out_dim = *lhs_dim_sz;
-        } else {
-            __builtin_unreachable();
-        }
-    }
-}
-
-template <typename SizeT>
-static void __nac3_ndarray_calc_broadcast_idx_impl(
-    const SizeT *src_dims,
-    SizeT src_ndims,
-    const NDIndex *in_idx,
-    NDIndex *out_idx
-) {
-    for (SizeT i = 0; i < src_ndims; ++i) {
-        SizeT src_i = src_ndims - i - 1;
-        out_idx[src_i] = src_dims[src_i] == 1 ? 0 : in_idx[src_i];
-    }
-}
-
-template<typename SizeT>
-static void __nac3_ndarray_strides_from_shape_impl(
-    SizeT ndims,
-    SizeT *shape,
-    SizeT *dst_strides
-) {
-    SizeT stride_product = 1;
-    for (SizeT i = 0; i < ndims; i++) {
-        int dim_i = ndims - i - 1;
-        dst_strides[dim_i] = stride_product;
-        stride_product *= shape[dim_i];
-    }
-}
-
-extern "C" {
-    #define DEF_nac3_int_exp_(T) \
-        T __nac3_int_exp_##T(T base, T exp) {\
-            return __nac3_int_exp_impl(base, exp);\
-        }
-
-    DEF_nac3_int_exp_(int32_t)
-    DEF_nac3_int_exp_(int64_t)
-    DEF_nac3_int_exp_(uint32_t)
-    DEF_nac3_int_exp_(uint64_t)
-
-    SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
-        if (i < 0) {
-            i = len + i;
-        }
-        if (i < 0) {
-            return 0;
-        } else if (i > len) {
-            return len;
-        }
-        return i;
-    }
-
-    SliceIndex __nac3_range_slice_len(
-        const SliceIndex start,
-        const SliceIndex end,
-        const SliceIndex step
-    ) {
-        SliceIndex diff = end - start;
-        if (diff > 0 && step > 0) {
-            return ((diff - 1) / step) + 1;
-        } else if (diff < 0 && step < 0) {
-            return ((diff + 1) / step) + 1;
-        } else {
-            return 0;
-        }
-    }
-
-    // Handle list assignment and dropping part of the list when
-    // both dest_step and src_step are +1.
-    // - All the index must *not* be out-of-bound or negative,
-    // - The end index is *inclusive*,
-    // - The length of src and dest slice size should already
-    // be checked: if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest)
-    SliceIndex __nac3_list_slice_assign_var_size(
-        SliceIndex dest_start,
-        SliceIndex dest_end,
-        SliceIndex dest_step,
-        uint8_t *dest_arr,
-        SliceIndex dest_arr_len,
-        SliceIndex src_start,
-        SliceIndex src_end,
-        SliceIndex src_step,
-        uint8_t *src_arr,
-        SliceIndex src_arr_len,
-        const SliceIndex size
-    ) {
-        /* if dest_arr_len == 0, do nothing since we do not support extending list */
-        if (dest_arr_len == 0) return dest_arr_len;
-        /* if both step is 1, memmove directly, handle the dropping of the list, and shrink size */
-        if (src_step == dest_step && dest_step == 1) {
-            const SliceIndex src_len = (src_end >= src_start) ? (src_end - src_start + 1) : 0;
-            const SliceIndex dest_len = (dest_end >= dest_start) ? (dest_end - dest_start + 1) : 0;
-            if (src_len > 0) {
-                __builtin_memmove(
-                    dest_arr + dest_start * size,
-                    src_arr + src_start * size,
-                    src_len * size
-                );
-            }
-            if (dest_len > 0) {
-                /* dropping */
-                __builtin_memmove(
-                    dest_arr + (dest_start + src_len) * size,
-                    dest_arr + (dest_end + 1) * size,
-                    (dest_arr_len - dest_end - 1) * size
-                );
-            }
-            /* shrink size */
-            return dest_arr_len - (dest_len - src_len);
-        }
-        /* if two range overlaps, need alloca */
-        uint8_t need_alloca =
-            (dest_arr == src_arr)
-            && !(
-                max(dest_start, dest_end) < min(src_start, src_end)
-                || max(src_start, src_end) < min(dest_start, dest_end)
-            );
-        if (need_alloca) {
-            uint8_t *tmp = reinterpret_cast<uint8_t *>(__builtin_alloca(src_arr_len * size));
-            __builtin_memcpy(tmp, src_arr, src_arr_len * size);
-            src_arr = tmp;
-        }
-        SliceIndex src_ind = src_start;
-        SliceIndex dest_ind = dest_start;
-        for (;
-            (src_step > 0) ? (src_ind <= src_end) : (src_ind >= src_end);
-            src_ind += src_step, dest_ind += dest_step
-        ) {
-            /* for constant optimization */
-            if (size == 1) {
-                __builtin_memcpy(dest_arr + dest_ind, src_arr + src_ind, 1);
-            } else if (size == 4) {
-                __builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
-            } else if (size == 8) {
-                __builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
-            } else {
-                /* memcpy for var size, cannot overlap after previous alloca */
-                __builtin_memcpy(dest_arr + dest_ind * size, src_arr + src_ind * size, size);
-            }
-        }
-        /* only dest_step == 1 can we shrink the dest list. */
-        /* size should be ensured prior to calling this function */
-        if (dest_step == 1 && dest_end >= dest_start) {
-            __builtin_memmove(
-                dest_arr + dest_ind * size,
-                dest_arr + (dest_end + 1) * size,
-                (dest_arr_len - dest_end - 1) * size
-            );
-            return dest_arr_len - (dest_end - dest_ind) - 1;
-        }
-        return dest_arr_len;
-    }
-
-    int32_t __nac3_isinf(double x) {
-        return __builtin_isinf(x);
-    }
-
-    int32_t __nac3_isnan(double x) {
-        return __builtin_isnan(x);
-    }
-
-    double tgamma(double arg);
-
-    double __nac3_gamma(double z) {
-        // Handling for denormals
-        //     | x                 | Python gamma(x) | C tgamma(x) |
-        // --- | ----------------- | --------------- | ----------- |
-        // (1) | nan               | nan             | nan         |
-        // (2) | -inf              | -inf            | inf         |
-        // (3) | inf               | inf             | inf         |
-        // (4) | 0.0               | inf             | inf         |
-        // (5) | {-1.0, -2.0, ...} | inf             | nan         |
-
-        // (1)-(3)
-        if (__builtin_isinf(z) || __builtin_isnan(z)) {
-            return z;
-        }
-
-        double v = tgamma(z);
-
-        // (4)-(5)
-        return __builtin_isinf(v) || __builtin_isnan(v) ? __builtin_inf() : v;
-    }
-
-    double lgamma(double arg);
-
-    double __nac3_gammaln(double x) {
-        // libm's handling of value overflows differs from scipy:
-        // - scipy: gammaln(-inf) -> -inf
-        // - libm : lgamma(-inf) -> inf
-
-        if (__builtin_isinf(x)) {
-            return x;
-        }
-
-        return lgamma(x);
-    }
-
-    double j0(double x);
-
-    double __nac3_j0(double x) {
-        // libm's handling of value overflows differs from scipy:
-        // - scipy: j0(inf) -> nan
-        // - libm : j0(inf) -> 0.0
-
-        if (__builtin_isinf(x)) {
-            return __builtin_nan("");
-        }
-
-        return j0(x);
-    }
-
-    uint32_t __nac3_ndarray_calc_size(
-        const uint32_t *list_data,
-        uint32_t list_len,
-        uint32_t begin_idx,
-        uint32_t end_idx
-    ) {
-        return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
-    }
-
-    uint64_t __nac3_ndarray_calc_size64(
-        const uint64_t *list_data,
-        uint64_t list_len,
-        uint64_t begin_idx,
-        uint64_t end_idx
-    ) {
-        return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
-    }
-
-    void __nac3_ndarray_calc_nd_indices(
-        uint32_t index,
-        const uint32_t* dims,
-        uint32_t num_dims,
-        NDIndex* idxs
-    ) {
-        __nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
-    }
-
-    void __nac3_ndarray_calc_nd_indices64(
-        uint64_t index,
-        const uint64_t* dims,
-        uint64_t num_dims,
-        NDIndex* idxs
-    ) {
-        __nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
-    }
-
-    uint32_t __nac3_ndarray_flatten_index(
-        const uint32_t* dims,
-        uint32_t num_dims,
-        const NDIndex* indices,
-        uint32_t num_indices
-    ) {
-        return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
-    }
-
-    uint64_t __nac3_ndarray_flatten_index64(
-        const uint64_t* dims,
-        uint64_t num_dims,
-        const NDIndex* indices,
-        uint64_t num_indices
-    ) {
-        return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
-    }
-
-    void __nac3_ndarray_calc_broadcast(
-        const uint32_t *lhs_dims,
-        uint32_t lhs_ndims,
-        const uint32_t *rhs_dims,
-        uint32_t rhs_ndims,
-        uint32_t *out_dims
-    ) {
-        return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
-    }
-
-    void __nac3_ndarray_calc_broadcast64(
-        const uint64_t *lhs_dims,
-        uint64_t lhs_ndims,
-        const uint64_t *rhs_dims,
-        uint64_t rhs_ndims,
-        uint64_t *out_dims
-    ) {
-        return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
-    }
-
-    void __nac3_ndarray_calc_broadcast_idx(
-        const uint32_t *src_dims,
-        uint32_t src_ndims,
-        const NDIndex *in_idx,
-        NDIndex *out_idx
-    ) {
-        __nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
-    }
-
-    void __nac3_ndarray_calc_broadcast_idx64(
-        const uint64_t *src_dims,
-        uint64_t src_ndims,
-        const NDIndex *in_idx,
-        NDIndex *out_idx
-    ) {
-        __nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
-    }
-
-    void __nac3_ndarray_strides_from_shape(uint32_t ndims, uint32_t* shape, uint32_t* dst_strides) {
-        __nac3_ndarray_strides_from_shape_impl(ndims, shape, dst_strides);
-    }
-
-    void __nac3_ndarray_strides_from_shape64(uint64_t ndims, uint64_t* shape, uint64_t* dst_strides) {
-        __nac3_ndarray_strides_from_shape_impl(ndims, shape, dst_strides);
-    }
-}

nac3core/irrt/irrt/core.hpp

@@ -0,0 +1,402 @@
+#pragma once
+
+#include <irrt/utils.hpp>
+#include <irrt/int_defs.hpp>
+
+// NDArray indices are always `uint32_t`.
+using NDIndex = uint32_t;
+// The type of an index or a value describing the length of a range/slice is always `int32_t`.
+using SliceIndex = int32_t;
+
+namespace {
+// adapted from GNU Scientific Library: https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
+// need to make sure `exp >= 0` before calling this function
+template <typename T>
+T __nac3_int_exp_impl(T base, T exp) {
+    T res = 1;
+    /* repeated squaring method */
+    do {
+        if (exp & 1) {
+            res *= base; /* for n odd */
+        }
+        exp >>= 1;
+        base *= base;
+    } while (exp);
+    return res;
+}
+
+template <typename SizeT>
+SizeT __nac3_ndarray_calc_size_impl(
+    const SizeT* list_data,
+    SizeT list_len,
+    SizeT begin_idx,
+    SizeT end_idx
+) {
+    __builtin_assume(end_idx <= list_len);
+
+    SizeT num_elems = 1;
+    for (SizeT i = begin_idx; i < end_idx; ++i) {
+        SizeT val = list_data[i];
+        __builtin_assume(val > 0);
+        num_elems *= val;
+    }
+    return num_elems;
+}
+
+template <typename SizeT>
+void __nac3_ndarray_calc_nd_indices_impl(
+    SizeT index,
+    const SizeT* dims,
+    SizeT num_dims,
+    NDIndex* idxs
+) {
+    SizeT stride = 1;
+    for (SizeT dim = 0; dim < num_dims; dim++) {
+        SizeT i = num_dims - dim - 1;
+        __builtin_assume(dims[i] > 0);
+        idxs[i] = (index / stride) % dims[i];
+        stride *= dims[i];
+    }
+}
+
+template <typename SizeT>
+SizeT __nac3_ndarray_flatten_index_impl(
+    const SizeT* dims,
+    SizeT num_dims,
+    const NDIndex* indices,
+    SizeT num_indices
+) {
+    SizeT idx = 0;
+    SizeT stride = 1;
+    for (SizeT i = 0; i < num_dims; ++i) {
+        SizeT ri = num_dims - i - 1;
+        if (ri < num_indices) {
+            idx += stride * indices[ri];
+        }
+
+        __builtin_assume(dims[i] > 0);
+        stride *= dims[ri];
+    }
+    return idx;
+}
+
+template <typename SizeT>
+void __nac3_ndarray_calc_broadcast_impl(
+    const SizeT* lhs_dims,
+    SizeT lhs_ndims,
+    const SizeT* rhs_dims,
+    SizeT rhs_ndims,
+    SizeT* out_dims
+) {
+    SizeT max_ndims = lhs_ndims > rhs_ndims ? lhs_ndims : rhs_ndims;
+
+    for (SizeT i = 0; i < max_ndims; ++i) {
+        const SizeT* lhs_dim_sz = i < lhs_ndims ? &lhs_dims[lhs_ndims - i - 1] : nullptr;
+        const SizeT* rhs_dim_sz = i < rhs_ndims ? &rhs_dims[rhs_ndims - i - 1] : nullptr;
+        SizeT* out_dim = &out_dims[max_ndims - i - 1];
+
+        if (lhs_dim_sz == nullptr) {
+            *out_dim = *rhs_dim_sz;
+        } else if (rhs_dim_sz == nullptr) {
+            *out_dim = *lhs_dim_sz;
+        } else if (*lhs_dim_sz == 1) {
+            *out_dim = *rhs_dim_sz;
+        } else if (*rhs_dim_sz == 1) {
+            *out_dim = *lhs_dim_sz;
+        } else if (*lhs_dim_sz == *rhs_dim_sz) {
+            *out_dim = *lhs_dim_sz;
+        } else {
+            __builtin_unreachable();
+        }
+    }
+}
+
+template <typename SizeT>
+void __nac3_ndarray_calc_broadcast_idx_impl(
+    const SizeT* src_dims,
+    SizeT src_ndims,
+    const NDIndex* in_idx,
+    NDIndex* out_idx
+) {
+    for (SizeT i = 0; i < src_ndims; ++i) {
+        SizeT src_i = src_ndims - i - 1;
+        out_idx[src_i] = src_dims[src_i] == 1 ? 0 : in_idx[src_i];
+    }
+}
+}  // namespace
+
+extern "C" {
+#define DEF_nac3_int_exp_(T) \
+    T __nac3_int_exp_##T(T base, T exp) {\
+        return __nac3_int_exp_impl(base, exp);\
+    }
+
+DEF_nac3_int_exp_(int32_t)
+DEF_nac3_int_exp_(int64_t)
+DEF_nac3_int_exp_(uint32_t)
+DEF_nac3_int_exp_(uint64_t)
+
+SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
+    if (i < 0) {
+        i = len + i;
+    }
+    if (i < 0) {
+        return 0;
+    } else if (i > len) {
+        return len;
+    }
+    return i;
+}
+
+SliceIndex __nac3_range_slice_len(
+    const SliceIndex start,
+    const SliceIndex end,
+    const SliceIndex step
+) {
+    SliceIndex diff = end - start;
+    if (diff > 0 && step > 0) {
+        return ((diff - 1) / step) + 1;
+    } else if (diff < 0 && step < 0) {
+        return ((diff + 1) / step) + 1;
+    } else {
+        return 0;
+    }
+}
+
+// Handle list assignment and dropping part of the list when
+// both dest_step and src_step are +1.
+// - All the index must *not* be out-of-bound or negative,
+// - The end index is *inclusive*,
+// - The length of src and dest slice size should already
+// be checked: if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest)
+SliceIndex __nac3_list_slice_assign_var_size(
+    SliceIndex dest_start,
+    SliceIndex dest_end,
+    SliceIndex dest_step,
+    uint8_t* dest_arr,
+    SliceIndex dest_arr_len,
+    SliceIndex src_start,
+    SliceIndex src_end,
+    SliceIndex src_step,
+    uint8_t* src_arr,
+    SliceIndex src_arr_len,
+    const SliceIndex size
+) {
+    /* if dest_arr_len == 0, do nothing since we do not support extending list */
+    if (dest_arr_len == 0) return dest_arr_len;
+    /* if both step is 1, memmove directly, handle the dropping of the list, and shrink size */
+    if (src_step == dest_step && dest_step == 1) {
+        const SliceIndex src_len = (src_end >= src_start) ? (src_end - src_start + 1) : 0;
+        const SliceIndex dest_len = (dest_end >= dest_start) ? (dest_end - dest_start + 1) : 0;
+        if (src_len > 0) {
+            __builtin_memmove(
+                dest_arr + dest_start * size,
+                src_arr + src_start * size,
+                src_len * size
+            );
+        }
+        if (dest_len > 0) {
+            /* dropping */
+            __builtin_memmove(
+                dest_arr + (dest_start + src_len) * size,
+                dest_arr + (dest_end + 1) * size,
+                (dest_arr_len - dest_end - 1) * size
+            );
+        }
+        /* shrink size */
+        return dest_arr_len - (dest_len - src_len);
+    }
+    /* if two range overlaps, need alloca */
+    uint8_t need_alloca =
+        (dest_arr == src_arr)
+        && !(
+            max(dest_start, dest_end) < min(src_start, src_end)
+            || max(src_start, src_end) < min(dest_start, dest_end)
+        );
+    if (need_alloca) {
+        uint8_t* tmp = reinterpret_cast<uint8_t *>(__builtin_alloca(src_arr_len * size));
+        __builtin_memcpy(tmp, src_arr, src_arr_len * size);
+        src_arr = tmp;
+    }
+    SliceIndex src_ind = src_start;
+    SliceIndex dest_ind = dest_start;
+    for (;
+        (src_step > 0) ? (src_ind <= src_end) : (src_ind >= src_end);
+        src_ind += src_step, dest_ind += dest_step
+    ) {
+        /* for constant optimization */
+        if (size == 1) {
+            __builtin_memcpy(dest_arr + dest_ind, src_arr + src_ind, 1);
+        } else if (size == 4) {
+            __builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
+        } else if (size == 8) {
+            __builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
+        } else {
+            /* memcpy for var size, cannot overlap after previous alloca */
+            __builtin_memcpy(dest_arr + dest_ind * size, src_arr + src_ind * size, size);
+        }
+    }
+    /* only dest_step == 1 can we shrink the dest list. */
+    /* size should be ensured prior to calling this function */
+    if (dest_step == 1 && dest_end >= dest_start) {
+        __builtin_memmove(
+            dest_arr + dest_ind * size,
+            dest_arr + (dest_end + 1) * size,
+            (dest_arr_len - dest_end - 1) * size
+        );
+        return dest_arr_len - (dest_end - dest_ind) - 1;
+    }
+    return dest_arr_len;
+}
+
+int32_t __nac3_isinf(double x) {
+    return __builtin_isinf(x);
+}
+
+int32_t __nac3_isnan(double x) {
+    return __builtin_isnan(x);
+}
+
+double tgamma(double arg);
+
+double __nac3_gamma(double z) {
+    // Handling for denormals
+    //     | x                 | Python gamma(x) | C tgamma(x) |
+    // --- | ----------------- | --------------- | ----------- |
+    // (1) | nan               | nan             | nan         |
+    // (2) | -inf              | -inf            | inf         |
+    // (3) | inf               | inf             | inf         |
+    // (4) | 0.0               | inf             | inf         |
+    // (5) | {-1.0, -2.0, ...} | inf             | nan         |
+
+    // (1)-(3)
+    if (__builtin_isinf(z) || __builtin_isnan(z)) {
+        return z;
+    }
+
+    double v = tgamma(z);
+
+    // (4)-(5)
+    return __builtin_isinf(v) || __builtin_isnan(v) ? __builtin_inf() : v;
+}
+
+double lgamma(double arg);
+
+double __nac3_gammaln(double x) {
+    // libm's handling of value overflows differs from scipy:
+    // - scipy: gammaln(-inf) -> -inf
+    // - libm : lgamma(-inf) -> inf
+
+    if (__builtin_isinf(x)) {
+        return x;
+    }
+
+    return lgamma(x);
+}
+
+double j0(double x);
+
+double __nac3_j0(double x) {
+    // libm's handling of value overflows differs from scipy:
+    // - scipy: j0(inf) -> nan
+    // - libm : j0(inf) -> 0.0
+
+    if (__builtin_isinf(x)) {
+        return __builtin_nan("");
+    }
+
+    return j0(x);
+}
+
+uint32_t __nac3_ndarray_calc_size(
+    const uint32_t* list_data,
+    uint32_t list_len,
+    uint32_t begin_idx,
+    uint32_t end_idx
+) {
+    return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
+}
+
+uint64_t __nac3_ndarray_calc_size64(
+    const uint64_t* list_data,
+    uint64_t list_len,
+    uint64_t begin_idx,
+    uint64_t end_idx
+) {
+    return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
+}
+
+void __nac3_ndarray_calc_nd_indices(
+    uint32_t index,
+    const uint32_t* dims,
+    uint32_t num_dims,
+    NDIndex* idxs
+) {
+    __nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
+}
+
+void __nac3_ndarray_calc_nd_indices64(
+    uint64_t index,
+    const uint64_t* dims,
+    uint64_t num_dims,
+    NDIndex* idxs
+) {
+    __nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
+}
+
+uint32_t __nac3_ndarray_flatten_index(
+    const uint32_t* dims,
+    uint32_t num_dims,
+    const NDIndex* indices,
+    uint32_t num_indices
+) {
+    return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
+}
+
+uint64_t __nac3_ndarray_flatten_index64(
+    const uint64_t* dims,
+    uint64_t num_dims,
+    const NDIndex* indices,
+    uint64_t num_indices
+) {
+    return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
+}
+
+void __nac3_ndarray_calc_broadcast(
+    const uint32_t* lhs_dims,
+    uint32_t lhs_ndims,
+    const uint32_t* rhs_dims,
+    uint32_t rhs_ndims,
+    uint32_t* out_dims
+) {
+    return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
+}
+
+void __nac3_ndarray_calc_broadcast64(
+    const uint64_t* lhs_dims,
+    uint64_t lhs_ndims,
+    const uint64_t* rhs_dims,
+    uint64_t rhs_ndims,
+    uint64_t* out_dims
+) {
+    return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
+}
+
+void __nac3_ndarray_calc_broadcast_idx(
+    const uint32_t* src_dims,
+    uint32_t src_ndims,
+    const NDIndex* in_idx,
+    NDIndex* out_idx
+) {
+    __nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
+}
+
+void __nac3_ndarray_calc_broadcast_idx64(
+    const uint64_t* src_dims,
+    uint64_t src_ndims,
+    const NDIndex* in_idx,
+    NDIndex* out_idx
+) {
+    __nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
+}
+}  // extern "C"

nac3core/irrt/irrt/error_context.hpp

@@ -0,0 +1,85 @@
+#pragma once
+
+#include <irrt/int_defs.hpp>
+#include <irrt/utils.hpp>
+
+namespace {
+// nac3core's "str" struct type definition
+template <typename SizeT>
+struct Str {
+    const char* content;
+    SizeT length;
+};
+
+// A limited set of errors IRRT could use.
+typedef uint32_t ErrorId;
+struct ErrorIds {
+    ErrorId index_error;
+    ErrorId value_error;
+    ErrorId assertion_error;
+    ErrorId runtime_error;
+};
+
+struct ErrorContext {
+    // Context
+    ErrorIds* error_ids;
+
+    // Error thrown by IRRT
+    ErrorId error_id;
+    const char* message_template; // MUST BE `&'static`
+    uint64_t param1;
+    uint64_t param2;
+    uint64_t param3;
+
+    void initialize(ErrorIds* error_ids) {
+        this->error_ids = error_ids;
+        clear_error();
+    }
+
+    void clear_error() {
+        // Point the message_template to an empty str. Don't set it to nullptr as a sentinel
+        this->message_template = "";
+    }
+
+    void set_error(ErrorId error_id, const char* message, uint64_t param1 = 0, uint64_t param2 = 0, uint64_t param3 = 0) {
+        this->error_id = error_id;
+        this->message_template = message;
+        this->param1 = param1;
+        this->param2 = param2;
+        this->param3 = param3;
+    }
+
+    bool has_error() {
+        return !cstr_utils::is_empty(message_template);
+    }
+
+    template <typename SizeT>
+    void set_error_str(Str<SizeT> *dst_str) {
+        dst_str->content = message_template;
+        dst_str->length = (SizeT) cstr_utils::length(message_template);
+    }
+};
+}
+
+extern "C" {
+
+void __nac3_error_context_initialize(ErrorContext* errctx, ErrorIds* error_ids) {
+    errctx->initialize(error_ids);
+}
+
+uint8_t __nac3_error_context_has_no_error(ErrorContext* errctx) {
+    return !errctx->has_error();
+}
+
+void __nac3_error_context_get_error_str(ErrorContext* errctx, Str<int32_t> *dst_str) {
+    errctx->set_error_str<int32_t>(dst_str);
+}
+
+void __nac3_error_context_get_error_str64(ErrorContext* errctx, Str<int64_t> *dst_str) {
+    errctx->set_error_str<int64_t>(dst_str);
+}
+
+void __nac3_error_dummy_raise(ErrorContext* errctx) {
+    errctx->set_error(errctx->error_ids->runtime_error, "THROWN FROM __nac3_error_dummy_raise!!!!!!");
+}
+}

nac3core/irrt/irrt/int_defs.hpp

@@ -1,8 +1,8 @@
 #pragma once
 
 // This is made toggleable since `irrt_test.cpp` itself would include
-// headers that define the `int_t` family.
-#ifndef IRRT_DONT_TYPEDEF_INTS
+// headers that define these typedefs
+#ifdef IRRT_DEFINE_TYPEDEF_INTS
 typedef _BitInt(8) int8_t;
 typedef unsigned _BitInt(8) uint8_t;
 typedef _BitInt(32) int32_t;
@@ -10,5 +10,3 @@ typedef unsigned _BitInt(32) uint32_t;
 typedef _BitInt(64) int64_t;
 typedef unsigned _BitInt(64) uint64_t;
 #endif
-
-typedef int32_t SliceIndex;

nac3core/irrt/irrt/ndarray/ndarray.hpp

@@ -0,0 +1,155 @@
+#pragma once
+
+#include <irrt/int_defs.hpp>
+#include <irrt/ndarray/ndarray_util.hpp>
+
+namespace {
+
+// The NDArray object. `SizeT` is the *signed* size type of this ndarray.
+//
+// NOTE: The order of fields is IMPORTANT. DON'T TOUCH IT
+//
+// Some resources you might find helpful:
+// - The official numpy implementations:
+//   - https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst
+// - On strides (about reshaping, slicing, C-contagiousness, etc)
+//   - https://ajcr.net/stride-guide-part-1/.
+//   - https://ajcr.net/stride-guide-part-2/.
+//   - https://ajcr.net/stride-guide-part-3/.
+template <typename SizeT>
+struct NDArray {
+    // The underlying data this `ndarray` is pointing to.
+    //
+    // NOTE: Formally this should be of type `void *`, but clang
+    // translates `void *` to `i8 *` when run with `-S -emit-llvm`,
+    // so we will put `uint8_t *` here for clarity.
+    //
+    // 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`.
+    //
+    // The `SizeT` is treated as `unsigned`.
+    SizeT itemsize;
+
+    // The number of dimensions of this shape.
+    //
+    // The `SizeT` is treated as `unsigned`.
+    SizeT ndims;
+
+    // Array shape, with length equal to `ndims`.
+    //
+    // The `SizeT` is treated as `unsigned`.
+    //
+    // NOTE: `shape` can contain 0.
+    //   (those appear when the user makes an out of bounds slice into an ndarray, e.g., `np.zeros((3, 3))[400:].shape == (0, 3)`)
+    SizeT *shape;
+
+    // Array strides (stride value is in number of bytes, NOT number of elements), with length equal to `ndims`.
+    //
+    // The `SizeT` is treated as `signed`.
+    //
+    // NOTE: `strides` can have negative numbers.
+    //   (those appear when there is a slice with a negative step, e.g., `my_array[::-1]`)
+    SizeT *strides;
+
+    // Calculate the size/# of elements of an `ndarray`.
+    // This function corresponds to `np.size(<ndarray>)` or `ndarray.size`
+    SizeT size() {
+        return ndarray_util::calc_size_from_shape(ndims, shape);
+    }
+
+    // Calculate the number of bytes of its content of an `ndarray` *in its view*.
+    // This function corresponds to `ndarray.nbytes`
+    SizeT nbytes() {
+        return this->size() * itemsize;
+    }
+
+    // Set the strides of the ndarray with `ndarray_util::set_strides_by_shape`
+    void set_strides_by_shape() {
+        ndarray_util::set_strides_by_shape(itemsize, ndims, strides, shape);
+    }
+
+    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];
+        return element;
+    }
+
+    uint8_t* get_nth_pelement(SizeT nth) {
+        SizeT* indices = (SizeT*) __builtin_alloca(sizeof(SizeT) * this->ndims);
+        ndarray_util::set_indices_by_nth(this->ndims, this->shape, indices, nth);
+        return get_pelement_by_indices(indices);
+    }
+
+    // Get the pointer to the nth element of the ndarray as if it were flattened.
+    uint8_t* checked_get_nth_pelement(ErrorContext* errctx, SizeT nth) {
+        SizeT arr_size = this->size();
+        if (!(0 <= nth && nth < arr_size)) {
+            errctx->set_error(
+                errctx->error_ids->index_error,
+                "index {0} is out of bounds, valid range is {1} <= index < {2}",
+                nth, 0, arr_size
+            );
+            return 0;
+        }
+        return get_nth_pelement(nth);
+    }
+
+    void set_pelement_value(uint8_t* pelement, const uint8_t* pvalue) {
+        __builtin_memcpy(pelement, pvalue, itemsize);
+    }
+
+    // Fill the ndarray with a value
+    void fill_generic(const uint8_t* pvalue) {
+        const SizeT size = this->size();
+        for (SizeT i = 0; i < size; i++) {
+            uint8_t* pelement = get_nth_pelement(i); // No need for checked_get_nth_pelement
+            set_pelement_value(pelement, pvalue);
+        }
+    }
+};
+}
+
+extern "C" {
+uint32_t __nac3_ndarray_size(NDArray<int32_t>* ndarray) {
+    return ndarray->size();
+}
+
+uint64_t __nac3_ndarray_size64(NDArray<int64_t>* ndarray) {
+    return ndarray->size();
+}
+
+uint32_t __nac3_ndarray_nbytes(NDArray<int32_t>* ndarray) {
+    return ndarray->nbytes();
+}
+
+uint64_t __nac3_ndarray_nbytes64(NDArray<int64_t>* ndarray) {
+    return ndarray->nbytes();
+}
+
+void __nac3_ndarray_util_assert_shape_no_negative(ErrorContext* errctx, int32_t ndims, int32_t* shape) {
+    ndarray_util::assert_shape_no_negative(errctx, ndims, shape);
+}
+
+void __nac3_ndarray_util_assert_shape_no_negative64(ErrorContext* errctx, int64_t ndims, int64_t* shape) {
+    ndarray_util::assert_shape_no_negative(errctx, ndims, shape);
+}
+
+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);
+}
+
+void __nac3_ndarray_fill_generic64(NDArray<int64_t>* ndarray, uint8_t* pvalue) {
+    ndarray->fill_generic(pvalue);
+}
+}

nac3core/irrt/irrt/ndarray/ndarray_util.hpp

@@ -0,0 +1,107 @@
+#pragma once
+
+#include <irrt/int_defs.hpp>
+
+namespace {
+namespace ndarray_util {
+
+// Throw an error if there is an axis with negative dimension
+template <typename SizeT>
+void assert_shape_no_negative(ErrorContext* errctx, SizeT ndims, const SizeT* shape) {
+    for (SizeT axis = 0; axis < ndims; axis++) {
+        if (shape[axis] < 0) {
+            errctx->set_error(
+                errctx->error_ids->value_error,
+                "negative dimensions are not allowed; axis {0} has dimension {1}",
+                axis, shape[axis]
+            );
+            return;
+        }
+    }
+}
+
+// Compute the size/# of elements of an ndarray given its shape
+template <typename SizeT>
+SizeT calc_size_from_shape(SizeT ndims, const SizeT* shape) {
+    SizeT size = 1;
+    for (SizeT axis = 0; axis < ndims; axis++) size *= shape[axis];
+    return size;
+}
+
+// Compute the strides of an ndarray given an ndarray `shape`
+// and assuming that the ndarray is *fully C-contagious*.
+//
+// You might want to read up on https://ajcr.net/stride-guide-part-1/.
+template <typename SizeT>
+void set_strides_by_shape(SizeT itemsize, SizeT ndims, SizeT* dst_strides, const SizeT* shape) {
+    SizeT stride_product = 1;
+    for (SizeT i = 0; i < ndims; i++) {
+        int axis = ndims - i - 1;
+        dst_strides[axis] = stride_product * itemsize;
+        stride_product *= shape[axis];
+    }
+}
+
+template <typename SizeT>
+void set_indices_by_nth(SizeT ndims, const SizeT* shape, SizeT* indices, SizeT nth) {
+    for (int32_t i = 0; i < ndims; i++) {
+        int32_t axis = ndims - i - 1;
+        int32_t dim = shape[axis];
+
+        indices[axis] = nth % dim;
+        nth /= dim;
+    }
+}
+
+template <typename SizeT>
+bool can_broadcast_shape_to(
+    const SizeT target_ndims,
+    const SizeT *target_shape,
+    const SizeT src_ndims,
+    const SizeT *src_shape
+) {
+    /*
+        // See https://numpy.org/doc/stable/user/basics.broadcasting.html
+
+        This function handles this example:
+        ```
+        Image  (3d array): 256 x 256 x 3
+        Scale  (1d array):             3
+        Result (3d array): 256 x 256 x 3
+        ```
+
+        Other interesting examples to consider:
+        - `can_broadcast_shape_to([3], [1, 1, 1, 1, 3]) == true`
+        - `can_broadcast_shape_to([3], [3, 1]) == false`
+        - `can_broadcast_shape_to([256, 256, 3], [256, 1, 3]) == true`
+
+        In cases when the shapes contain zero(es):
+        - `can_broadcast_shape_to([0], [1]) == true`
+        - `can_broadcast_shape_to([0], [2]) == false`
+        - `can_broadcast_shape_to([0, 4, 0, 0], [1]) == true`
+        - `can_broadcast_shape_to([0, 4, 0, 0], [1, 1, 1, 1]) == true`
+        - `can_broadcast_shape_to([0, 4, 0, 0], [1, 4, 1, 1]) == true`
+        - `can_broadcast_shape_to([4, 3], [0, 3]) == false`
+        - `can_broadcast_shape_to([4, 3], [0, 0]) == false`
+    */
+
+    // This is essentially doing the following in Python:
+    // `for target_dim, src_dim in itertools.zip_longest(target_shape[::-1], src_shape[::-1], fillvalue=1)`
+    for (SizeT i = 0; i < max(target_ndims, src_ndims); i++) {
+        SizeT target_axis = target_ndims - i - 1;
+        SizeT src_axis = src_ndims - i - 1;
+
+        bool target_dim_exists = target_axis >= 0;
+        bool src_dim_exists = src_axis >= 0;
+
+        SizeT target_dim = target_dim_exists ? target_shape[target_axis] : 1;
+        SizeT src_dim = src_dim_exists ? src_shape[src_axis] : 1;
+
+        bool ok = src_dim == 1 || target_dim == src_dim;
+        if (!ok) return false;
+    }
+
+    return true;
+}
+}
+}

nac3core/irrt/irrt/string_utils.hpp

@@ -0,0 +1,60 @@
+#pragma once
+
+#include <irrt/int_defs.hpp>
+
+namespace {
+namespace string {
+    bool is_empty(const char* str) {
+        return str[0] == '\0';
+    }
+
+    int8_t compare(const char* a, const char* b) {
+        uint32_t i = 0;
+        while (true) {
+            if (a[i] < b[i]) {
+                return -1;
+            } else if (a[i] > b[i]) {
+                return 1;
+            } else { // a[i] == b[i]
+                if (a[i] == '\0') {
+                    return 0;
+                } else {
+                    continue;
+                }
+            }
+        }
+    }
+
+    int8_t equal(const char* a, const char* b) {
+        return compare(a, b) == 0;
+    }
+
+    uint32_t length(const char* str) {
+        uint32_t length = 0;
+        while (*str != '\0') {
+            length++;
+            str++;
+        }
+        return length;
+    }
+
+    bool copy(const char* src, char* dst, uint32_t dst_max_size) {
+        for (uint32_t i = 0; i < dst_max_size; i++) {
+            bool is_last = i + 1 == dst_max_size;
+            if (is_last && src[i] != '\0') {
+                dst[i] = '\0';
+                return false;
+            }
+
+            if (src[i] == '\0') {
+                dst[i] = '\0';
+                return true;
+            }
+
+            dst[i] = src[i];
+        }
+
+        __builtin_unreachable();
+    }
+}
+}

nac3core/irrt/irrt/utils.hpp

@@ -0,0 +1,88 @@
+#pragma once
+
+#include <irrt/int_defs.hpp>
+
+namespace {
+template <typename T>
+const T& max(const T& a, const T& b) {
+    return a > b ? a : b;
+}
+
+template <typename T>
+const T& min(const T& a, const T& b) {
+    return a > b ? b : a;
+}
+
+template <typename T>
+bool arrays_match(int len, T* as, T* bs) {
+    for (int i = 0; i < len; i++) {
+        if (as[i] != bs[i]) return false;
+    }
+    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;
+}
+
+namespace cstr_utils {
+    bool is_empty(const char* str) {
+        return str[0] == '\0';
+    }
+
+    int8_t compare(const char* a, const char* b) {
+        uint32_t i = 0;
+        while (true) {
+            if (a[i] < b[i]) {
+                return -1;
+            } else if (a[i] > b[i]) {
+                return 1;
+            } else { // a[i] == b[i] 
+                if (a[i] == '\0') {
+                    return 0;
+                } else {
+                    i++;
+                }
+            }
+        }
+    }
+
+    int8_t equal(const char* a, const char* b) {
+        return compare(a, b) == 0;
+    }
+
+    uint32_t length(const char* str) {
+        uint32_t length = 0;
+        while (*str != '\0') {
+            length++;
+            str++;
+        }
+        return length;
+    }
+
+    bool copy(const char* src, char* dst, uint32_t dst_max_size) {
+        for (uint32_t i = 0; i < dst_max_size; i++) {
+            bool is_last = i + 1 == dst_max_size;
+            if (is_last && src[i] != '\0') {
+                dst[i] = '\0';
+                return false;
+            }
+
+            if (src[i] == '\0') {
+                dst[i] = '\0';
+                return true;
+            }
+
+            dst[i] = src[i];
+        }
+
+        __builtin_unreachable();
+    }
+}
+}

nac3core/irrt/irrt_basic.hpp

@@ -1,216 +0,0 @@
-#pragma once
-
-#include "irrt_utils.hpp"
-#include "irrt_typedefs.hpp"
-
-/*
-    This header contains IRRT implementations
-    that do not deserved to be categorized (e.g., into numpy, etc.)
-
-    Check out other *.hpp files before including them here!!
-*/
-
-// The type of an index or a value describing the length of a range/slice is
-// always `int32_t`.
-
-namespace {
-    // adapted from GNU Scientific Library: https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
-    // need to make sure `exp >= 0` before calling this function
-    template <typename T>
-    T __nac3_int_exp_impl(T base, T exp) {
-        T res = 1;
-        /* repeated squaring method */
-        do {
-            if (exp & 1) {
-                res *= base; /* for n odd */
-            }
-            exp >>= 1;
-            base *= base;
-        } while (exp);
-        return res;
-    }
-}
-
-extern "C" {
-    #define DEF_nac3_int_exp_(T) \
-        T __nac3_int_exp_##T(T base, T exp) {\
-            return __nac3_int_exp_impl(base, exp);\
-        }
-
-    DEF_nac3_int_exp_(int32_t)
-    DEF_nac3_int_exp_(int64_t)
-    DEF_nac3_int_exp_(uint32_t)
-    DEF_nac3_int_exp_(uint64_t)
-
-    SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
-        if (i < 0) {
-            i = len + i;
-        }
-        if (i < 0) {
-            return 0;
-        } else if (i > len) {
-            return len;
-        }
-        return i;
-    }
-
-    SliceIndex __nac3_range_slice_len(
-        const SliceIndex start,
-        const SliceIndex end,
-        const SliceIndex step
-    ) {
-        SliceIndex diff = end - start;
-        if (diff > 0 && step > 0) {
-            return ((diff - 1) / step) + 1;
-        } else if (diff < 0 && step < 0) {
-            return ((diff + 1) / step) + 1;
-        } else {
-            return 0;
-        }
-    }
-
-    // Handle list assignment and dropping part of the list when
-    // both dest_step and src_step are +1.
-    // - All the index must *not* be out-of-bound or negative,
-    // - The end index is *inclusive*,
-    // - The length of src and dest slice size should already
-    // be checked: if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest)
-    SliceIndex __nac3_list_slice_assign_var_size(
-        SliceIndex dest_start,
-        SliceIndex dest_end,
-        SliceIndex dest_step,
-        uint8_t *dest_arr,
-        SliceIndex dest_arr_len,
-        SliceIndex src_start,
-        SliceIndex src_end,
-        SliceIndex src_step,
-        uint8_t *src_arr,
-        SliceIndex src_arr_len,
-        const SliceIndex size
-    ) {
-        /* if dest_arr_len == 0, do nothing since we do not support extending list */
-        if (dest_arr_len == 0) return dest_arr_len;
-        /* if both step is 1, memmove directly, handle the dropping of the list, and shrink size */
-        if (src_step == dest_step && dest_step == 1) {
-            const SliceIndex src_len = (src_end >= src_start) ? (src_end - src_start + 1) : 0;
-            const SliceIndex dest_len = (dest_end >= dest_start) ? (dest_end - dest_start + 1) : 0;
-            if (src_len > 0) {
-                __builtin_memmove(
-                    dest_arr + dest_start * size,
-                    src_arr + src_start * size,
-                    src_len * size
-                );
-            }
-            if (dest_len > 0) {
-                /* dropping */
-                __builtin_memmove(
-                    dest_arr + (dest_start + src_len) * size,
-                    dest_arr + (dest_end + 1) * size,
-                    (dest_arr_len - dest_end - 1) * size
-                );
-            }
-            /* shrink size */
-            return dest_arr_len - (dest_len - src_len);
-        }
-        /* if two range overlaps, need alloca */
-        uint8_t need_alloca =
-            (dest_arr == src_arr)
-            && !(
-                max(dest_start, dest_end) < min(src_start, src_end)
-                || max(src_start, src_end) < min(dest_start, dest_end)
-            );
-        if (need_alloca) {
-            uint8_t *tmp = reinterpret_cast<uint8_t *>(__builtin_alloca(src_arr_len * size));
-            __builtin_memcpy(tmp, src_arr, src_arr_len * size);
-            src_arr = tmp;
-        }
-        SliceIndex src_ind = src_start;
-        SliceIndex dest_ind = dest_start;
-        for (;
-            (src_step > 0) ? (src_ind <= src_end) : (src_ind >= src_end);
-            src_ind += src_step, dest_ind += dest_step
-        ) {
-            /* for constant optimization */
-            if (size == 1) {
-                __builtin_memcpy(dest_arr + dest_ind, src_arr + src_ind, 1);
-            } else if (size == 4) {
-                __builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
-            } else if (size == 8) {
-                __builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
-            } else {
-                /* memcpy for var size, cannot overlap after previous alloca */
-                __builtin_memcpy(dest_arr + dest_ind * size, src_arr + src_ind * size, size);
-            }
-        }
-        /* only dest_step == 1 can we shrink the dest list. */
-        /* size should be ensured prior to calling this function */
-        if (dest_step == 1 && dest_end >= dest_start) {
-            __builtin_memmove(
-                dest_arr + dest_ind * size,
-                dest_arr + (dest_end + 1) * size,
-                (dest_arr_len - dest_end - 1) * size
-            );
-            return dest_arr_len - (dest_end - dest_ind) - 1;
-        }
-        return dest_arr_len;
-    }
-
-    int32_t __nac3_isinf(double x) {
-        return __builtin_isinf(x);
-    }
-
-    int32_t __nac3_isnan(double x) {
-        return __builtin_isnan(x);
-    }
-
-    double tgamma(double arg);
-
-    double __nac3_gamma(double z) {
-        // Handling for denormals
-        //     | x                 | Python gamma(x) | C tgamma(x) |
-        // --- | ----------------- | --------------- | ----------- |
-        // (1) | nan               | nan             | nan         |
-        // (2) | -inf              | -inf            | inf         |
-        // (3) | inf               | inf             | inf         |
-        // (4) | 0.0               | inf             | inf         |
-        // (5) | {-1.0, -2.0, ...} | inf             | nan         |
-
-        // (1)-(3)
-        if (__builtin_isinf(z) || __builtin_isnan(z)) {
-            return z;
-        }
-
-        double v = tgamma(z);
-
-        // (4)-(5)
-        return __builtin_isinf(v) || __builtin_isnan(v) ? __builtin_inf() : v;
-    }
-
-    double lgamma(double arg);
-
-    double __nac3_gammaln(double x) {
-        // libm's handling of value overflows differs from scipy:
-        // - scipy: gammaln(-inf) -> -inf
-        // - libm : lgamma(-inf) -> inf
-
-        if (__builtin_isinf(x)) {
-            return x;
-        }
-
-        return lgamma(x);
-    }
-
-    double j0(double x);
-
-    double __nac3_j0(double x) {
-        // libm's handling of value overflows differs from scipy:
-        // - scipy: j0(inf) -> nan
-        // - libm : j0(inf) -> 0.0
-
-        if (__builtin_isinf(x)) {
-            return __builtin_nan("");
-        }
-
-        return j0(x);
-    }
-}

nac3core/irrt/irrt_everything.hpp

@@ -1,14 +1,7 @@
 #pragma once
 
-#include "irrt_utils.hpp"
-#include "irrt_typedefs.hpp"
-#include "irrt_basic.hpp"
-#include "irrt_slice.hpp"
-#include "irrt_numpy_ndarray.hpp"
-
-/*
-    All IRRT implementations.
-
-    We don't have any pre-compiled objects, so we are writing all implementations in headers and
-    concatenate them with `#include` into one massive source file that contains all the IRRT stuff.
-*/
+#include <irrt/core.hpp>
+#include <irrt/error_context.hpp>
+#include <irrt/int_defs.hpp>
+#include <irrt/utils.hpp>
+#include <irrt/ndarray/ndarray.hpp>

nac3core/irrt/irrt_numpy_ndarray.hpp

@@ -1,466 +0,0 @@
-#pragma once
-
-#include "irrt_utils.hpp"
-#include "irrt_typedefs.hpp"
-#include "irrt_slice.hpp"
-
-/*
-    NDArray-related implementations.
-`*/
-
-// NDArray indices are always `uint32_t`.
-using NDIndex = uint32_t;
-
-namespace {
-    namespace ndarray_util {
-        template <typename SizeT>
-        static void set_indices_by_nth(SizeT ndims, const SizeT* shape, SizeT* indices, SizeT nth) {
-            for (int32_t i = 0; i < ndims; i++) {
-                int32_t dim_i = ndims - i - 1;
-                int32_t dim = shape[dim_i];
-
-                indices[dim_i] = nth % dim;
-                nth /= dim;
-            }
-        }
-
-        // Compute the strides of an ndarray given an ndarray `shape`
-        // and assuming that the ndarray is *fully C-contagious*.
-        //
-        // You might want to read up on https://ajcr.net/stride-guide-part-1/.
-        template <typename SizeT>
-        static void set_strides_by_shape(SizeT itemsize, SizeT ndims, SizeT* dst_strides, const SizeT* shape) {
-            SizeT stride_product = 1;
-            for (SizeT i = 0; i < ndims; i++) {
-                int dim_i = ndims - i - 1;
-                dst_strides[dim_i] = stride_product * itemsize;
-                stride_product *= shape[dim_i];
-            }
-        }
-
-        // Compute the size/# of elements of an ndarray given its shape
-        template <typename SizeT>
-        static SizeT calc_size_from_shape(SizeT ndims, const SizeT* shape) {
-            SizeT size = 1;
-            for (SizeT dim_i = 0; dim_i < ndims; dim_i++) size *= shape[dim_i];
-            return size;
-        }
-
-        template <typename SizeT>
-        static bool can_broadcast_shape_to(
-            const SizeT target_ndims,
-            const SizeT *target_shape,
-            const SizeT src_ndims,
-            const SizeT *src_shape
-        ) {
-            /*
-                // See https://numpy.org/doc/stable/user/basics.broadcasting.html
-
-                This function handles this example:
-                ```
-                Image  (3d array): 256 x 256 x 3
-                Scale  (1d array):             3
-                Result (3d array): 256 x 256 x 3
-                ```
-
-                Other interesting examples to consider:
-                - `can_broadcast_shape_to([3], [1, 1, 1, 1, 3]) == true`
-                - `can_broadcast_shape_to([3], [3, 1]) == false`
-                - `can_broadcast_shape_to([256, 256, 3], [256, 1, 3]) == true`
-
-                In cases when the shapes contain zero(es):
-                - `can_broadcast_shape_to([0], [1]) == true`
-                - `can_broadcast_shape_to([0], [2]) == false`
-                - `can_broadcast_shape_to([0, 4, 0, 0], [1]) == true`
-                - `can_broadcast_shape_to([0, 4, 0, 0], [1, 1, 1, 1]) == true`
-                - `can_broadcast_shape_to([0, 4, 0, 0], [1, 4, 1, 1]) == true`
-                - `can_broadcast_shape_to([4, 3], [0, 3]) == false`
-                - `can_broadcast_shape_to([4, 3], [0, 0]) == false`
-            */
-
-            // This is essentially doing the following in Python:
-            // `for target_dim, src_dim in itertools.zip_longest(target_shape[::-1], src_shape[::-1], fillvalue=1)`
-            for (SizeT i = 0; i < max(target_ndims, src_ndims); i++) {
-                SizeT target_dim_i = target_ndims - i - 1;
-                SizeT src_dim_i = src_ndims - i - 1;
-
-                bool target_dim_exists = target_dim_i >= 0;
-                bool src_dim_exists = src_dim_i >= 0;
-
-                SizeT target_dim = target_dim_exists ? target_shape[target_dim_i] : 1;
-                SizeT src_dim = src_dim_exists ? src_shape[src_dim_i] : 1;
-
-                bool ok = src_dim == 1 || target_dim == src_dim;
-                if (!ok) return false;
-            }
-
-            return true;
-        }
-    }
-
-    typedef uint8_t NDSliceType;
-    extern "C" {
-        const NDSliceType INPUT_SLICE_TYPE_INDEX = 0;
-        const NDSliceType INPUT_SLICE_TYPE_SLICE = 1;
-    }
-
-    struct NDSlice {
-        // A poor-man's `std::variant<int, UserRange>`
-        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`
-        */
-        uint8_t *slice;
-    };
-
-    namespace ndarray_util {
-        template<typename SizeT>
-        SizeT deduce_ndims_after_slicing(SizeT ndims, SizeT num_slices, const NDSlice *slices) {
-            irrt_assert(num_slices <= ndims);
-
-            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
-                }
-            }
-            return final_ndims;
-        }
-    }
-
-    template <typename SizeT>
-    struct NDArrayIndicesIter {
-        SizeT ndims;
-        const SizeT *shape;
-        SizeT *indices;
-
-        void set_indices_zero() {
-            __builtin_memset(indices, 0, sizeof(SizeT) * ndims);
-        }
-
-        void next() {
-            for (SizeT i = 0; i < ndims; i++) {
-                SizeT dim_i = ndims - i - 1;
-
-                indices[dim_i]++;
-                if (indices[dim_i] < shape[dim_i]) {
-                    break;
-                } else {
-                    indices[dim_i] = 0;
-                }
-            }
-        }
-    };
-
-    // The NDArray object. `SizeT` is the *signed* size type of this ndarray.
-    //
-    // NOTE: The order of fields is IMPORTANT. DON'T TOUCH IT
-    //
-    // Some resources you might find helpful:
-    // - The official numpy implementations:
-    //   - https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst
-    // - On strides (about reshaping, slicing, C-contagiousness, etc)
-    //   - https://ajcr.net/stride-guide-part-1/.
-    //   - https://ajcr.net/stride-guide-part-2/.
-    //   - https://ajcr.net/stride-guide-part-3/.
-    template <typename SizeT>
-    struct NDArray {
-        // The underlying data this `ndarray` is pointing to.
-        //
-        // NOTE: Formally this should be of type `void *`, but clang
-        // translates `void *` to `i8 *` when run with `-S -emit-llvm`,
-        // so we will put `uint8_t *` here for clarity.
-        uint8_t *data;
-
-        // The number of bytes of a single element in `data`.
-        //
-        // The `SizeT` is treated as `unsigned`.
-        SizeT itemsize;
-
-        // The number of dimensions of this shape.
-        //
-        // The `SizeT` is treated as `unsigned`.
-        SizeT ndims;
-
-        // Array shape, with length equal to `ndims`.
-        //
-        // The `SizeT` is treated as `unsigned`.
-        //
-        // NOTE: `shape` can contain 0.
-        //   (those appear when the user makes an out of bounds slice into an ndarray, e.g., `np.zeros((3, 3))[400:].shape == (0, 3)`)
-        SizeT *shape;
-
-        // Array strides (stride value is in number of bytes, NOT number of elements), with length equal to `ndims`.
-        //
-        // The `SizeT` is treated as `signed`.
-        //
-        // NOTE: `strides` can have negative numbers.
-        //   (those appear when there is a slice with a negative step, e.g., `my_array[::-1]`)
-        SizeT *strides;
-
-        // Calculate the size/# of elements of an `ndarray`.
-        // This function corresponds to `np.size(<ndarray>)` or `ndarray.size`
-        SizeT size() {
-            return ndarray_util::calc_size_from_shape(ndims, shape);
-        }
-
-        // Calculate the number of bytes of its content of an `ndarray` *in its view*.
-        // This function corresponds to `ndarray.nbytes`
-        SizeT nbytes() {
-            return this->size() * itemsize;
-        }
-
-        void set_value_at_pelement(uint8_t* pelement, const uint8_t* pvalue) {
-            __builtin_memcpy(pelement, pvalue, itemsize);
-        }
-
-        uint8_t* get_pelement(const SizeT *indices) {
-            uint8_t* element = data;
-            for (SizeT dim_i = 0; dim_i < ndims; dim_i++)
-                element += indices[dim_i] * strides[dim_i];
-            return element;
-        }
-
-        uint8_t* get_nth_pelement(SizeT nth) {
-            irrt_assert(0 <= nth);
-            irrt_assert(nth < this->size());
-
-            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);
-        }
-
-        // Get pointer to the first element of this ndarray, assuming
-        // `this->size() > 0`, i.e., not "degenerate" due to zeroes in `this->shape`)
-        //
-        // This is particularly useful for when the ndarray is just containing a single scalar.
-        uint8_t* get_first_pelement() {
-            irrt_assert(this->size() > 0);
-            return this->data; // ...It is simply `this->data`
-        }
-
-        // Is the given `indices` valid/in-bounds?
-        bool in_bounds(const SizeT *indices) {
-            for (SizeT dim_i = 0; dim_i < ndims; dim_i++) {
-                bool dim_ok = indices[dim_i] < shape[dim_i];
-                if (!dim_ok) return false;
-            }
-            return true;
-        }
-
-        // Fill the ndarray with a value
-        void fill_generic(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);
-            }
-        }
-
-        // Set the strides of the ndarray with `ndarray_util::set_strides_by_shape`
-        void set_strides_by_shape() {
-            ndarray_util::set_strides_by_shape(itemsize, ndims, strides, shape);
-        }
-
-        // https://numpy.org/doc/stable/reference/generated/numpy.eye.html
-        void set_to_eye(SizeT k, const uint8_t* zero_pvalue, const uint8_t* one_pvalue) {
-            __builtin_assume(ndims == 2);
-
-            // TODO: Better implementation
-
-            fill_generic(zero_pvalue);
-            for (SizeT i = 0; i < min(shape[0], shape[1]); i++) {
-                SizeT row = i;
-                SizeT col = i + k;
-                SizeT indices[2] = { row, col };
-
-                if (!in_bounds(indices)) continue;
-
-                uint8_t* pelement = get_pelement(indices);
-                set_value_at_pelement(pelement, one_pvalue);
-            }
-        }
-
-        // To support numpy complex slices (e.g., `my_array[:50:2,4,:2:-1]`)
-        //
-        // Things assumed by this function:
-        // - `dst_ndarray` is allocated by the caller
-        // - `dst_ndarray.ndims` has the correct value (according to `ndarray_util::deduce_ndims_after_slicing`).
-        //   - ... and `dst_ndarray.shape` and `dst_ndarray.strides` have been allocated by the caller as well
-        //
-        // Other notes:
-        // - `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) {
-            // 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;
-
-            SizeT this_axis = 0;
-            SizeT dst_axis = 0;
-
-            for (SizeT i = 0; i < num_ndslices; i++) {
-                NDSlice *ndslice = &ndslices[i];
-                if (ndslice->type == INPUT_SLICE_TYPE_INDEX) {
-                    // Handle when the ndslice is just a single (possibly negative) integer
-                    // e.g., `my_array[::2, -5, ::-1]`
-                    //                      ^^------ like this
-                    SizeT index_user = *((SizeT*) ndslice->slice);
-                    SizeT index = resolve_index_in_length(this->shape[this_axis], index_user);
-                    dst_ndarray->data += index * this->strides[this_axis]; // Add offset
-
-                    // Next
-                    this_axis++;
-                } else if (ndslice->type == INPUT_SLICE_TYPE_SLICE) {
-                    // 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
-
-                    // 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
-
-                    // Next
-                    dst_axis++;
-                    this_axis++;
-                } else {
-                    __builtin_unreachable();
-                }
-            }
-
-            irrt_assert(dst_axis == dst_ndarray->ndims); // Sanity check on the implementation
-        }
-
-        // Similar to `np.broadcast_to(<ndarray>, <target_shape>)`
-        // Assumptions:
-        //   - `this` has to be fully initialized.
-        //   - `dst_ndarray->ndims` has to be set.
-        //   - `dst_ndarray->shape` has to be set, this determines the shape `this` broadcasts to.
-        //
-        // Other notes:
-        //   - `dst_ndarray->data` does not have to be set, it will be set to `this->data`.
-        //   - `dst_ndarray->itemsize` does not have to be set, it will be set to `this->data`.
-        //   - `dst_ndarray->strides` does not have to be set, it will be overwritten.
-        //
-        // Cautions:
-        //   ```
-        //   xs = np.zeros((4,))
-        //   ys = np.zero((4, 1))
-        //   ys[:] = xs # ok
-        // 
-        //   xs = np.zeros((1, 4))
-        //   ys = np.zero((4,))
-        //   ys[:] = xs # allowed
-        //   # However `np.broadcast_to(xs, (4,))` would fails, as per numpy's broadcasting rule.
-        //   # and apparently numpy will "deprecate" this? SEE https://github.com/numpy/numpy/issues/21744
-        //   # This implementation will NOT support this assignment.
-        //   ```
-        void broadcast_to(NDArray<SizeT>* dst_ndarray) {
-            dst_ndarray->data = this->data;
-            dst_ndarray->itemsize = this->itemsize;
-
-            irrt_assert(
-                ndarray_util::can_broadcast_shape_to(
-                    dst_ndarray->ndims,
-                    dst_ndarray->shape,
-                    this->ndims,
-                    this->shape
-                )
-            );
-
-            SizeT stride_product = 1;
-            for (SizeT i = 0; i < max(this->ndims, dst_ndarray->ndims); i++) {
-                SizeT this_dim_i = this->ndims - i - 1;
-                SizeT dst_dim_i = dst_ndarray->ndims - i - 1;
-
-                bool this_dim_exists = this_dim_i >= 0;
-                bool dst_dim_exists = dst_dim_i >= 0;
-
-                // TODO: Explain how this works
-                bool c1 = this_dim_exists && this->shape[this_dim_i] == 1;
-                bool c2 = dst_dim_exists && dst_ndarray->shape[dst_dim_i] != 1;
-                if (!this_dim_exists || (c1 && c2)) {
-                    dst_ndarray->strides[dst_dim_i] = 0; // Freeze it in-place
-                } else {
-                    dst_ndarray->strides[dst_dim_i] = stride_product * this->itemsize;
-                    stride_product *= this->shape[this_dim_i]; // NOTE: this_dim_exist must be true here.
-                }
-            }
-        }
-
-        // Simulates `this_ndarray[:] = src_ndarray`, with automatic broadcasting.
-        // Caution on https://github.com/numpy/numpy/issues/21744
-        // Also see `NDArray::broadcast_to`
-        void assign_with(NDArray<SizeT>* src_ndarray) {
-            irrt_assert(
-                ndarray_util::can_broadcast_shape_to(
-                    this->ndims,
-                    this->shape,
-                    src_ndarray->ndims,
-                    src_ndarray->shape
-                )
-            );
-
-            // Broadcast the `src_ndarray` to make the reading process *much* easier
-            SizeT* broadcasted_src_ndarray_strides = __builtin_alloca(sizeof(SizeT) * this->ndims); // Remember to allocate strides beforehand
-            NDArray<SizeT> broadcasted_src_ndarray = {
-                .ndims = this->ndims,
-                .shape = this->shape,
-                .strides = broadcasted_src_ndarray_strides
-            };
-            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);
-            }
-        }
-    };
-}
-
-extern "C" {
-    uint32_t __nac3_ndarray_size(NDArray<int32_t>* ndarray) {
-        return ndarray->size();
-    }
-
-    uint64_t __nac3_ndarray_size64(NDArray<int64_t>* ndarray) {
-        return ndarray->size();
-    }
-
-    void __nac3_ndarray_fill_generic(NDArray<int32_t>* ndarray, uint8_t* pvalue) {
-        ndarray->fill_generic(pvalue);
-    }
-
-    void __nac3_ndarray_fill_generic64(NDArray<int64_t>* ndarray, uint8_t* pvalue) {
-        ndarray->fill_generic(pvalue);
-    }
-
-    // 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);
-    // }
-}

nac3core/irrt/irrt_slice.hpp

@@ -1,80 +0,0 @@
-#pragma once
-
-#include "irrt_utils.hpp"
-#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;
-
-        // 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;
-            if (diff > 0 && step > 0) {
-                return ((diff - 1) / step) + 1;
-            } else if (diff < 0 && step < 0) {
-                return ((diff + 1) / step) + 1;
-            } else {
-                return 0;
-            }
-        }
-    };
-
-    template<typename T>
-    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);
-        } else {
-            return min(length, index);
-        }
-    }
-
-    // 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 {
-        uint8_t start_defined;
-        T start;
-
-        uint8_t stop_defined;
-        T stop;
-
-        uint8_t step_defined;
-        T step;
-
-        // Like Python's `slice(start, stop, step).indices(length)`
-        Slice<T> indices(T 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;
-            result.step = step_defined ? step : 1;
-            bool step_is_negative = result.step < 0;
-
-            if (start_defined) {
-                result.start = resolve_index_in_length(length, start);
-            } else {
-                result.start = step_is_negative ? length - 1 : 0;
-            }
-            
-            if (stop_defined) {
-                result.stop = resolve_index_in_length(length, stop);
-            } else {
-                result.stop = step_is_negative ? -1 : length;
-            }
-
-            return result;
-        }
-    };
-}

nac3core/irrt/irrt_test.cpp

@@ -5,654 +5,14 @@
 #include <cstdio>
 #include <cstdlib>
 
-// Set `IRRT_DONT_TYPEDEF_INTS` because `cstdint` defines them
-#define IRRT_DONT_TYPEDEF_INTS
-#include "irrt_everything.hpp"
+#include <irrt_everything.hpp>
 
-void test_fail() {
-    printf("[!] Test failed\n");
-    exit(1);
-}
-
-void __begin_test(const char* function_name, const char* file, int line) {
-    printf("######### Running %s @ %s:%d\n", function_name, file, line);
-}
-
-#define BEGIN_TEST() __begin_test(__FUNCTION__, __FILE__, __LINE__)
-
-template <typename T>
-void debug_print_array(const char* format, int len, T* as) {
-    printf("[");
-    for (int i = 0; i < len; i++) {
-        if (i != 0) printf(", ");
-        printf(format, as[i]);
-    }
-    printf("]");
-}
-
-template <typename T>
-void assert_arrays_match(const char* label, const char* format, int len, T* expected, T* got) {
-    if (!arrays_match(len, expected, got)) {
-        printf(">>>>>>> %s\n", label);
-        printf("    Expecting = ");
-        debug_print_array(format, len, expected);
-        printf("\n");
-        printf("          Got = ");
-        debug_print_array(format, len, got);
-        printf("\n");
-        test_fail();
-    }
-}
-
-template <typename T>
-void assert_values_match(const char* label, const char* format, T expected, T got) {
-    if (expected != got) {
-        printf(">>>>>>> %s\n", label);
-        printf("    Expecting = ");
-        printf(format, expected);
-        printf("\n");
-        printf("          Got = ");
-        printf(format, got);
-        printf("\n");
-        test_fail();
-    }
-}
-
-void print_repeated(const char *str, int count) {
-    for (int i = 0; i < count; i++) {
-        printf("%s", str);
-    }
-}
-
-template<typename SizeT, typename ElementT>
-void __print_ndarray_aux(const char *format, bool first, bool last, SizeT* cursor, SizeT depth, NDArray<SizeT>* ndarray) {
-    // A really lazy recursive implementation
-    
-    // Add left padding unless its the first entry (since there would be "[[[" before it)
-    if (!first) {
-        print_repeated(" ", depth);
-    }
-
-    const SizeT dim = ndarray->shape[depth];
-    if (depth + 1 == ndarray->ndims) {
-        // Recursed down to last dimension, print the values in a nice list
-        printf("[");
-
-        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 element = *pelement;
-
-            if (i != 0) printf(", "); // List delimiter
-            printf(format, element);
-            printf("(@");
-            debug_print_array("%d", ndarray->ndims, indices);
-            printf(")");
-
-            (*cursor)++;
-        }
-        printf("]");
-    } else {
-        printf("[");
-        for (SizeT i = 0; i < ndarray->shape[depth]; i++) {
-            __print_ndarray_aux<SizeT, ElementT>(
-                format,
-                i == 0, // first?
-                i + 1 == dim, // last?
-                cursor,
-                depth + 1,
-                ndarray
-            );
-        }
-        printf("]");
-    }
-
-    // Add newline unless its the last entry (since there will be "]]]" after it)
-    if (!last) {
-        print_repeated("\n", depth);
-    }
-}
-
-template<typename SizeT, typename ElementT>
-void print_ndarray(const char *format, NDArray<SizeT>* ndarray) {
-    if (ndarray->ndims == 0) {
-        printf("<empty ndarray>");
-    } else {
-        SizeT cursor = 0;
-        __print_ndarray_aux<SizeT, ElementT>(format, true, true, &cursor, 0, ndarray);
-    }
-    printf("\n");
-}
-
-void test_calc_size_from_shape_normal() {
-    // Test shapes with normal values
-    BEGIN_TEST();
-
-    int32_t shape[4] = { 2, 3, 5, 7 };
-    assert_values_match("size", "%d", 210, ndarray_util::calc_size_from_shape<int32_t>(4, shape));
-}
-
-void test_calc_size_from_shape_has_zero() {
-    // Test shapes with 0 in them
-    BEGIN_TEST();
-
-    int32_t shape[4] = { 2, 0, 5, 7 };
-    assert_values_match("size", "%d", 0, ndarray_util::calc_size_from_shape<int32_t>(4, shape));
-}
-
-void test_set_strides_by_shape() {
-    // Test `set_strides_by_shape()`
-    BEGIN_TEST();
-
-    int32_t shape[4] = { 99, 3, 5, 7 };
-    int32_t strides[4] = { 0 };
-    ndarray_util::set_strides_by_shape((int32_t) sizeof(int32_t), 4, strides, shape);
-
-    int32_t expected_strides[4] = {
-        105 * sizeof(int32_t),
-        35 * sizeof(int32_t),
-        7 * sizeof(int32_t),
-        1 * sizeof(int32_t)
-    };
-    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_fill_generic() {
-    // Test ndarray fill_generic
-    BEGIN_TEST();
-
-    // Choose a type that's neither int32_t nor uint64_t (candidates of SizeT) to spice it up
-    // Also make all the octets non-zero, to see if `memcpy` in `fill_generic` is working perfectly.
-    uint16_t fill_value = 0xFACE;
-
-    uint16_t in_data[6] = { 100, 101, 102, 103, 104, 105 }; // Fill `data` with values that != `999`
-    int32_t in_itemsize = sizeof(uint16_t);
-    const int32_t in_ndims = 2;
-    int32_t in_shape[in_ndims] = { 2, 3 };
-    int32_t in_strides[in_ndims] = {};
-    NDArray<int32_t> ndarray = {
-        .data = (uint8_t*) in_data,
-        .itemsize = in_itemsize,
-        .ndims = in_ndims,
-        .shape = in_shape,
-        .strides = in_strides,
-    };
-    ndarray.set_strides_by_shape();
-    ndarray.fill_generic((uint8_t*) &fill_value); // `fill_generic` here
-
-    uint16_t expected_data[6] = { fill_value, fill_value, fill_value, fill_value, fill_value, fill_value };
-    assert_arrays_match("data", "0x%hX", 6, expected_data, in_data);
-}
-
-void test_ndarray_set_to_eye() {
-    // Test `set_to_eye` behavior (helper function to implement `np.eye()`)
-    BEGIN_TEST();
-
-    double in_data[9] = { 99.0, 99.0, 99.0, 99.0, 99.0, 99.0, 99.0, 99.0, 99.0 };
-    int32_t in_itemsize = sizeof(double);
-    const int32_t in_ndims = 2;
-    int32_t in_shape[in_ndims] = { 3, 3 };
-    int32_t in_strides[in_ndims] = {};
-    NDArray<int32_t> ndarray = {
-        .data = (uint8_t*) in_data,
-        .itemsize = in_itemsize,
-        .ndims = in_ndims,
-        .shape = in_shape,
-        .strides = in_strides,
-    };
-    ndarray.set_strides_by_shape();
-
-    double zero = 0.0;
-    double one = 1.0;
-    ndarray.set_to_eye(1, (uint8_t*) &zero, (uint8_t*) &one);
-
-    assert_values_match("in_data[0]", "%f", 0.0, in_data[0]);
-    assert_values_match("in_data[1]", "%f", 1.0, in_data[1]);
-    assert_values_match("in_data[2]", "%f", 0.0, in_data[2]);
-    assert_values_match("in_data[3]", "%f", 0.0, in_data[3]);
-    assert_values_match("in_data[4]", "%f", 0.0, in_data[4]);
-    assert_values_match("in_data[5]", "%f", 1.0, in_data[5]);
-    assert_values_match("in_data[6]", "%f", 0.0, in_data[6]);
-    assert_values_match("in_data[7]", "%f", 0.0, in_data[7]);
-    assert_values_match("in_data[8]", "%f", 0.0, in_data[8]);
-}
-
-void test_slice_1() {
-    // Test `slice(5, None, None).indices(100) == slice(5, 100, 1)`
-    BEGIN_TEST();
-
-    UserSlice<int> user_slice = {
-        .start_defined = 1,
-        .start = 5,
-        .stop_defined = 0,
-        .step_defined = 0,
-    };
-
-    auto slice = user_slice.indices(100);
-    assert_values_match("start", "%d", 5, slice.start);
-    assert_values_match("stop", "%d", 100, slice.stop);
-    assert_values_match("step", "%d", 1, slice.step);
-}
-
-void test_slice_2() {
-    // Test `slice(400, 999, None).indices(100) == slice(100, 100, 1)`
-    BEGIN_TEST();
-
-    UserSlice<int> user_slice = {
-        .start_defined = 1,
-        .start = 400,
-        .stop_defined = 0,
-        .step_defined = 0,
-    };
-
-    auto slice = user_slice.indices(100);
-    assert_values_match("start", "%d", 100, slice.start);
-    assert_values_match("stop", "%d", 100, slice.stop);
-    assert_values_match("step", "%d", 1, slice.step);
-}
-
-void test_slice_3() {
-    // Test `slice(-10, -5, None).indices(100) == slice(90, 95, 1)`
-    BEGIN_TEST();
-
-    UserSlice<int> user_slice = {
-        .start_defined = 1,
-        .start = -10,
-        .stop_defined = 1,
-        .stop = -5,
-        .step_defined = 0,
-    };
-
-    auto slice = user_slice.indices(100);
-    assert_values_match("start", "%d", 90, slice.start);
-    assert_values_match("stop", "%d", 95, slice.stop);
-    assert_values_match("step", "%d", 1, slice.step);
-}
-
-void test_slice_4() {
-    // Test `slice(None, None, -5).indices(100) == (99, -1, -5)`
-    BEGIN_TEST();
-
-    UserSlice<int> user_slice = {
-        .start_defined = 0,
-        .stop_defined = 0,
-        .step_defined = 1,
-        .step = -5
-    };
-
-    auto slice = user_slice.indices(100);
-    assert_values_match("start", "%d", 99, slice.start);
-    assert_values_match("stop", "%d", -1, slice.stop);
-    assert_values_match("step", "%d", -5, slice.step);
-}
-
-void test_ndslice_1() {
-    /*
-        Reference Python code:
-        ```python
-        ndarray = np.arange(12, dtype=np.float64).reshape((3, 4));
-        # array([[ 0.,  1.,  2.,  3.],
-        #        [ 4.,  5.,  6.,  7.],
-        #        [ 8.,  9., 10., 11.]])
-
-        dst_ndarray = ndarray[-2:, 1::2]
-        # array([[ 5.,  7.],
-        #        [ 9., 11.]])
-
-        assert dst_ndarray.shape == (2, 2)
-        assert dst_ndarray.strides == (32, 16)
-        assert dst_ndarray[0, 0] == 5.0
-        assert dst_ndarray[0, 1] == 7.0
-        assert dst_ndarray[1, 0] == 9.0
-        assert dst_ndarray[1, 1] == 11.0
-        ```
-    */
-    BEGIN_TEST();
-
-    double in_data[12] = { 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 };
-    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();
-
-    // Destination ndarray
-    // As documented, ndims and shape & strides must be allocated and determined by the caller.
-    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::, 1::2]`
-    UserSlice<int32_t> user_slice_1 = {
-        .start_defined = 1,
-        .start = -2,
-        .stop_defined = 0,
-        .step_defined = 0
-    };
-
-    UserSlice<int32_t> user_slice_2 = {
-        .start_defined = 1,
-        .start = 1,
-        .stop_defined = 0,
-        .step_defined = 1,
-        .step = 2
-    };
-
-    const int32_t num_ndslices = 2;
-    NDSlice ndslices[num_ndslices] = {
-        { .type = INPUT_SLICE_TYPE_SLICE, .slice = (uint8_t*) &user_slice_1 },
-        { .type = INPUT_SLICE_TYPE_SLICE, .slice = (uint8_t*) &user_slice_2 }
-    };
-
-    ndarray.slice(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 })));
-}
-
-void test_ndslice_2() {
-    /*
-        ```python
-        ndarray = np.arange(12, dtype=np.float64).reshape((3, 4))
-        # array([[ 0.,  1.,  2.,  3.],
-        #        [ 4.,  5.,  6.,  7.],
-        #        [ 8.,  9., 10., 11.]])
-
-        dst_ndarray = ndarray[2, ::-2]
-        # array([11.,  9.])
-
-        assert dst_ndarray.shape == (2,)
-        assert dst_ndarray.strides == (-16,)
-        assert dst_ndarray[0] == 11.0
-        assert dst_ndarray[1] == 9.0
-
-        dst_ndarray[1, 0] == 99 # If you write to `dst_ndarray`
-        assert ndarray[1, 3] == 99 # `ndarray` also updates!!
-        ```
-    */
-    BEGIN_TEST();
-
-    double in_data[12] = { 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 };
-    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();
-
-    // Destination ndarray
-    // As documented, ndims and shape & strides must be allocated and determined by the caller.
-    const int32_t dst_ndims = 1;
-    int32_t dst_shape[dst_ndims] = {999}; // Empty values
-    int32_t dst_strides[dst_ndims] = {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, ::-2]`
-    int32_t user_slice_1 = 2;
-    UserSlice<int32_t> user_slice_2 = {
-        .start_defined = 0,
-        .stop_defined = 0,
-        .step_defined = 1,
-        .step = -2
-    };
-
-    const int32_t num_ndslices = 2;
-    NDSlice ndslices[num_ndslices] = {
-        { .type = INPUT_SLICE_TYPE_INDEX, .slice = (uint8_t*) &user_slice_1 },
-        { .type = INPUT_SLICE_TYPE_SLICE, .slice = (uint8_t*) &user_slice_2 }
-    };
-
-    ndarray.slice(num_ndslices, ndslices, &dst_ndarray);
-
-    int32_t expected_shape[dst_ndims] = { 2 };
-    int32_t expected_strides[dst_ndims] = { -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);
-
-    // [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 })));
-}
-
-void test_can_broadcast_shape() {
-    BEGIN_TEST();
-
-    assert_values_match(
-        "can_broadcast_shape_to([3], [1, 1, 1, 1, 3]) == true",
-        "%d",
-        true,
-        ndarray_util::can_broadcast_shape_to(1, (int32_t[]) { 3 }, 5, (int32_t[]) { 1, 1, 1, 1, 3 })
-    );
-    assert_values_match(
-        "can_broadcast_shape_to([3], [3, 1]) == false",
-        "%d",
-        false,
-        ndarray_util::can_broadcast_shape_to(1, (int32_t[]) { 3 }, 2, (int32_t[]) { 3, 1 }));
-    assert_values_match(
-        "can_broadcast_shape_to([3], [3]) == true",
-        "%d",
-        true,
-        ndarray_util::can_broadcast_shape_to(1, (int32_t[]) { 3 }, 1, (int32_t[]) { 3 }));
-    assert_values_match(
-        "can_broadcast_shape_to([1], [3]) == false",
-        "%d",
-        false,
-        ndarray_util::can_broadcast_shape_to(1, (int32_t[]) { 1 }, 1, (int32_t[]) { 3 }));
-    assert_values_match(
-        "can_broadcast_shape_to([1], [1]) == true",
-        "%d",
-        true,
-        ndarray_util::can_broadcast_shape_to(1, (int32_t[]) { 1 }, 1, (int32_t[]) { 1 }));
-    assert_values_match(
-        "can_broadcast_shape_to([256, 256, 3], [256, 1, 3]) == true",
-        "%d",
-        true,
-        ndarray_util::can_broadcast_shape_to(3, (int32_t[]) { 256, 256, 3 }, 3, (int32_t[]) { 256, 1, 3 })
-    );
-    assert_values_match(
-        "can_broadcast_shape_to([256, 256, 3], [3]) == true",
-        "%d",
-        true,
-        ndarray_util::can_broadcast_shape_to(3, (int32_t[]) { 256, 256, 3 }, 1, (int32_t[]) { 3 })
-    );
-    assert_values_match(
-        "can_broadcast_shape_to([256, 256, 3], [2]) == false",
-        "%d",
-        false,
-        ndarray_util::can_broadcast_shape_to(3, (int32_t[]) { 256, 256, 3 }, 1, (int32_t[]) { 2 })
-    );
-    assert_values_match(
-        "can_broadcast_shape_to([256, 256, 3], [1]) == true",
-        "%d",
-        true,
-        ndarray_util::can_broadcast_shape_to(3, (int32_t[]) { 256, 256, 3 }, 1, (int32_t[]) { 1 })
-    );
-
-    // In cases when the shapes contain zero(es)
-    assert_values_match(
-        "can_broadcast_shape_to([0], [1]) == true",
-        "%d",
-        true,
-        ndarray_util::can_broadcast_shape_to(1, (int32_t[]) { 0 }, 1, (int32_t[]) { 1 })
-    );
-    assert_values_match(
-        "can_broadcast_shape_to([0], [2]) == false",
-        "%d",
-        false,
-        ndarray_util::can_broadcast_shape_to(1, (int32_t[]) { 0 }, 1, (int32_t[]) { 2 })
-    );
-    assert_values_match(
-        "can_broadcast_shape_to([0, 4, 0, 0], [1]) == true",
-        "%d",
-        true,
-        ndarray_util::can_broadcast_shape_to(4, (int32_t[]) { 0, 4, 0, 0 }, 1, (int32_t[]) { 1 })
-    );
-    assert_values_match(
-        "can_broadcast_shape_to([0, 4, 0, 0], [1, 1, 1, 1]) == true",
-        "%d",
-        true,
-        ndarray_util::can_broadcast_shape_to(4, (int32_t[]) { 0, 4, 0, 0 }, 4, (int32_t[]) { 1, 1, 1, 1 })
-    );
-    assert_values_match(
-        "can_broadcast_shape_to([0, 4, 0, 0], [1, 4, 1, 1]) == true",
-        "%d",
-        true,
-        ndarray_util::can_broadcast_shape_to(4, (int32_t[]) { 0, 4, 0, 0 }, 4, (int32_t[]) { 1, 4, 1, 1 })
-    );
-    assert_values_match(
-        "can_broadcast_shape_to([4, 3], [0, 3]) == false",
-        "%d",
-        false,
-        ndarray_util::can_broadcast_shape_to(2, (int32_t[]) { 4, 3 }, 2, (int32_t[]) { 0, 3 })
-    );
-    assert_values_match(
-        "can_broadcast_shape_to([4, 3], [0, 0]) == false",
-        "%d",
-        false,
-        ndarray_util::can_broadcast_shape_to(2, (int32_t[]) { 4, 3 }, 2, (int32_t[]) { 0, 0 })
-    );
-}
-
-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)
-
-    */
-    BEGIN_TEST();
-
-    double in_data[4] = { 19.9, 29.9, 39.9, 49.9 };
-    const int32_t in_ndims = 2;
-    int32_t in_shape[in_ndims] = {1, 4};
-    int32_t in_strides[in_ndims] = {};
-    NDArray<int32_t> ndarray = {
-        .data = (uint8_t*) in_data,
-        .itemsize = sizeof(double),
-        .ndims = in_ndims,
-        .shape = in_shape,
-        .strides = in_strides
-    };
-    ndarray.set_strides_by_shape();
-
-    const int32_t dst_ndims = 3;
-    int32_t dst_shape[dst_ndims] = {2, 3, 4};
-    int32_t dst_strides[dst_ndims] = {};
-    NDArray<int32_t> dst_ndarray = {
-        .ndims = dst_ndims,
-        .shape = dst_shape,
-        .strides = dst_strides
-    };
-
-    ndarray.broadcast_to(&dst_ndarray);
-
-    assert_arrays_match("dst_ndarray->strides", "%d", dst_ndims, (int32_t[]) { 0, 0, 8 }, dst_ndarray.strides);
-
-    assert_values_match("dst_ndarray[0, 0, 0]", "%f", 19.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 0, 0})));
-    assert_values_match("dst_ndarray[0, 0, 1]", "%f", 29.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 0, 1})));
-    assert_values_match("dst_ndarray[0, 0, 2]", "%f", 39.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 0, 2})));
-    assert_values_match("dst_ndarray[0, 0, 3]", "%f", 49.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 0, 3})));
-    assert_values_match("dst_ndarray[0, 1, 0]", "%f", 19.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 1, 0})));
-    assert_values_match("dst_ndarray[0, 1, 1]", "%f", 29.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 1, 1})));
-    assert_values_match("dst_ndarray[0, 1, 2]", "%f", 39.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 1, 2})));
-    assert_values_match("dst_ndarray[0, 1, 3]", "%f", 49.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {0, 1, 3})));
-    assert_values_match("dst_ndarray[1, 2, 3]", "%f", 49.9, *((double*) dst_ndarray.get_pelement((int32_t[]) {1, 2, 3})));
-}
-
-void test_assign_with() {
-    /*
-        ```
-        xs = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]], dtype=np.float64)
-        ys = xs.shape
-        ```
-    */
-}
+#include <test/core.hpp>
+#include <test/test_core.hpp>
+#include <test/test_utils.hpp>
 
 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_fill_generic();
-    test_ndarray_set_to_eye();
-    test_slice_1();
-    test_slice_2();
-    test_slice_3();
-    test_slice_4();
-    test_ndslice_1();
-    test_ndslice_2();
-    test_can_broadcast_shape();
-    test_ndarray_broadcast_1();
-    test_assign_with();
+    run_test_core();
+    run_test_utils();
     return 0;
 }

nac3core/irrt/irrt_utils.hpp

@@ -1,37 +0,0 @@
-#pragma once
-
-#include "irrt_typedefs.hpp"
-
-namespace {
-    template <typename T>
-    T max(T a, T b) {
-        return a > b ? a : b;
-    }
-
-    template <typename T>
-    T min(T a, T b) {
-        return a > b ? b : a;
-    }
-
-    template <typename T>
-    bool arrays_match(int len, T *as, T *bs) {
-        for (int i = 0; i < len; i++) {
-            if (as[i] != bs[i]) return false;
-        }
-        return true;
-    }
-
-    void irrt_panic() {
-        // Crash the program for now.
-        // TODO: Don't crash the program
-        //       ... or at least produce a good message when doing testing IRRT
-            
-        uint8_t* death = nullptr;
-        *death = 0; // TODO: address 0 on hardware might be writable?
-    }
-
-    // TODO: Make this a macro and allow it to be toggled on/off (e.g., debug vs release)
-    void irrt_assert(bool condition) {
-        if (!condition) irrt_panic();
-    }
-}

nac3core/irrt/test/core.hpp

@@ -0,0 +1,88 @@
+#pragma once
+
+// Include this header for every test_*.cpp
+
+#include <cstdint>
+#include <cstdio>
+#include <cstdlib>
+
+#include <test/print.hpp>
+
+// Some utils can be used here
+#include "../irrt/utils.hpp"
+
+void __begin_test(const char* function_name, const char* file, int line) {
+    printf("######### Running %s @ %s:%d\n", function_name, file, line);
+}
+
+#define BEGIN_TEST() __begin_test(__FUNCTION__, __FILE__, __LINE__)
+
+void test_fail() {
+    printf("[!] Test failed. Exiting with status code 1.\n");
+    exit(1);
+}
+
+template <typename T>
+void debug_print_array(int len, const T* as) {
+    printf("[");
+    for (int i = 0; i < len; i++) {
+        if (i != 0) printf(", ");
+        print_value(as[i]);
+    }
+    printf("]");
+}
+
+void print_assertion_passed(const char* file, int line) {
+    printf("[*] Assertion passed on %s:%d\n", file, line);
+}
+
+void print_assertion_failed(const char* file, int line) {
+    printf("[!] Assertion failed on %s:%d\n", file, line);
+}
+
+void __assert_true(const char* file, int line, bool cond) {
+    if (cond) {
+        print_assertion_passed(file, line);
+    } else {
+        print_assertion_failed(file, line);
+        test_fail();
+    }
+}
+
+#define assert_true(cond) __assert_true(__FILE__, __LINE__, cond)
+
+template <typename T>
+void __assert_arrays_match(const char* file, int line, int len, const T* expected, const T* got) {
+    if (arrays_match(len, expected, got)) {
+        print_assertion_passed(file, line);
+    } else {
+        print_assertion_failed(file, line);
+        printf("Expect = ");
+        debug_print_array(len, expected);
+        printf("\n");
+        printf("   Got = ");
+        debug_print_array(len, got);
+        printf("\n");
+        test_fail();
+    }
+}
+
+#define assert_arrays_match(len, expected, got) __assert_arrays_match(__FILE__, __LINE__, len, expected, got)
+
+template <typename T>
+void __assert_values_match(const char* file, int line, T expected, T got) {
+    if (expected == got) {
+        print_assertion_passed(file, line);
+    } else {
+        print_assertion_failed(file, line);
+        printf("Expect = ");
+        print_value(expected);
+        printf("\n");
+        printf("   Got = ");
+        print_value(got);
+        printf("\n");
+        test_fail();
+    }
+}
+
+#define assert_values_match(expected, got) __assert_values_match(__FILE__, __LINE__, expected, got)

nac3core/irrt/test/print.hpp

@@ -0,0 +1,42 @@
+#pragma once
+
+#include <cstdlib>
+#include <cstdio>
+
+template <class T>
+void print_value(T value);
+
+template <>
+void print_value(char value) {
+    printf("'%c' (ord=%d)", value, value);
+}
+
+template <>
+void print_value(int8_t value) {
+    printf("%d", value);
+}
+
+template <>
+void print_value(int32_t value) {
+    printf("%d", value);
+}
+
+template <>
+void print_value(uint8_t value) {
+    printf("%u", value);
+}
+
+template <>
+void print_value(uint32_t value) {
+    printf("%u", value);
+}
+
+template <>
+void print_value(double value) {
+    printf("%f", value);
+}
+
+template <>
+void print_value(char* value) {
+    printf("%s", value);
+}

nac3core/irrt/test/test_core.hpp

@@ -0,0 +1,15 @@
+#pragma once
+
+#include <test/core.hpp>
+#include <irrt/core.hpp>
+
+void test_int_exp() {
+    BEGIN_TEST();
+
+    assert_values_match(125, __nac3_int_exp_impl<int32_t>(5, 3));
+    assert_values_match(3125, __nac3_int_exp_impl<int32_t>(5, 5));
+}
+
+void run_test_core() {
+    test_int_exp();
+}

nac3core/irrt/test/test_utils.hpp

@@ -0,0 +1,27 @@
+#pragma once
+
+#include <test/core.hpp>
+#include <irrt/utils.hpp>
+
+void test_int_log_10() {
+    BEGIN_TEST();
+
+    assert_values_match((uint32_t) 0, int_log_floor(0, 10));
+    assert_values_match((uint32_t) 0, int_log_floor(9, 10));
+    assert_values_match((uint32_t) 1, int_log_floor(10, 10));
+    assert_values_match((uint32_t) 1, int_log_floor(11, 10));
+    assert_values_match((uint32_t) 1, int_log_floor(99, 10));
+    assert_values_match((uint32_t) 2, int_log_floor(100, 10));
+    assert_values_match((uint32_t) 2, int_log_floor(101, 10));
+}
+
+void test_cstr_utils() {
+    BEGIN_TEST();
+
+    assert_values_match((uint32_t) 42, (uint32_t) cstr_utils::length("THROWN FROM __nac3_error_dummy_raise!!!!!!"));
+}
+
+void run_test_utils() {
+    test_int_log_10();
+    test_cstr_utils();
+}

nac3core/src/codegen/classes.rs

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

nac3core/src/codegen/irrt/error_context.rs

@@ -0,0 +1,196 @@
+use inkwell::types::IntType;
+use inkwell::values::IntValue;
+
+use crate::codegen::optics::*;
+use crate::codegen::CodeGenContext;
+use crate::codegen::CodeGenerator;
+
+use super::util::get_sized_dependent_function_name;
+use super::util::FunctionBuilder;
+
+#[derive(Debug, Clone)]
+pub struct StrLens<'ctx> {
+    pub size_type: IntType<'ctx>,
+}
+
+// TODO: nac3core has hardcoded a lot of "str"
+pub struct StrFields<'ctx> {
+    pub content: GepGetter<AddressLens<IntLens<'ctx>>>,
+    pub length: GepGetter<IntLens<'ctx>>,
+}
+
+impl<'ctx> StructureOptic<'ctx> for StrLens<'ctx> {
+    type Fields = StrFields<'ctx>;
+
+    fn struct_name(&self) -> &'static str {
+        "str"
+    }
+
+    fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields {
+        StrFields {
+            content: builder.add_field("content", AddressLens(IntLens(builder.ctx.i8_type()))),
+            length: builder.add_field("length", IntLens(self.size_type)),
+        }
+    }
+}
+
+pub struct ErrorIdsFields<'ctx> {
+    pub index_error: GepGetter<IntLens<'ctx>>,
+    pub value_error: GepGetter<IntLens<'ctx>>,
+    pub assertion_error: GepGetter<IntLens<'ctx>>,
+    pub runtime_error: GepGetter<IntLens<'ctx>>,
+}
+
+#[derive(Debug, Clone)]
+pub struct ErrorIdsLens;
+
+impl<'ctx> StructureOptic<'ctx> for ErrorIdsLens {
+    type Fields = ErrorIdsFields<'ctx>;
+
+    fn struct_name(&self) -> &'static str {
+        "ErrorIds"
+    }
+
+    fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields {
+        let i32_lens = IntLens(builder.ctx.i32_type());
+        ErrorIdsFields {
+            index_error: builder.add_field("index_error", i32_lens),
+            value_error: builder.add_field("value_error", i32_lens),
+            assertion_error: builder.add_field("assertion_error", i32_lens),
+            runtime_error: builder.add_field("runtime_error", i32_lens),
+        }
+    }
+}
+
+pub struct ErrorContextFields<'ctx> {
+    pub error_ids: GepGetter<AddressLens<ErrorIdsLens>>,
+    pub error_id: GepGetter<IntLens<'ctx>>,
+    pub message_template: GepGetter<AddressLens<IntLens<'ctx>>>,
+    pub param1: GepGetter<IntLens<'ctx>>,
+    pub param2: GepGetter<IntLens<'ctx>>,
+    pub param3: GepGetter<IntLens<'ctx>>,
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct ErrorContextLens;
+
+impl<'ctx> StructureOptic<'ctx> for ErrorContextLens {
+    type Fields = ErrorContextFields<'ctx>;
+
+    fn struct_name(&self) -> &'static str {
+        "ErrorContext"
+    }
+
+    fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields {
+        ErrorContextFields {
+            error_ids: builder.add_field("error_ids", AddressLens(ErrorIdsLens)),
+            error_id: builder.add_field("error_id", IntLens(builder.ctx.i32_type())),
+            message_template: builder
+                .add_field("message_template", AddressLens(IntLens(builder.ctx.i8_type()))),
+            param1: builder.add_field("param1", IntLens(builder.ctx.i64_type())),
+            param2: builder.add_field("param2", IntLens(builder.ctx.i64_type())),
+            param3: builder.add_field("param3", IntLens(builder.ctx.i64_type())),
+        }
+    }
+}
+
+fn build_error_ids<'ctx>(ctx: &CodeGenContext<'ctx, '_>) -> Address<'ctx, ErrorIdsLens> {
+    // ErrorIdsLens.get_fields(ctx.ctx).assertion_error.
+    let error_ids = ErrorIdsLens.alloca(ctx, "error_ids");
+    let llvm_i32 = ctx.ctx.i32_type();
+
+    let get_string_id =
+        |string_id| llvm_i32.const_int(ctx.resolver.get_string_id(string_id) as u64, false);
+
+    error_ids.focus(ctx, |fields| &fields.index_error).store(ctx, &get_string_id("0:IndexError"));
+    error_ids.focus(ctx, |fields| &fields.value_error).store(ctx, &get_string_id("0:ValueError"));
+    error_ids
+        .focus(ctx, |fields| &fields.assertion_error)
+        .store(ctx, &get_string_id("0:AssertionError"));
+    error_ids
+        .focus(ctx, |fields| &fields.runtime_error)
+        .store(ctx, &get_string_id("0:RuntimeError"));
+
+    error_ids
+}
+
+pub fn call_nac3_error_context_initialize<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    errctx: &Address<'ctx, ErrorContextLens>,
+    error_ids: &Address<'ctx, ErrorIdsLens>,
+) {
+    FunctionBuilder::begin(ctx, "__nac3_error_context_initialize")
+        .arg("errctx", &AddressLens(ErrorContextLens), errctx)
+        .arg("error_ids", &AddressLens(ErrorIdsLens), error_ids)
+        .returning_void();
+}
+
+pub fn call_nac3_error_context_has_no_error<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    errctx: &Address<'ctx, ErrorContextLens>,
+) -> IntValue<'ctx> {
+    FunctionBuilder::begin(ctx, "__nac3_error_context_has_no_error")
+        .arg("errctx", &AddressLens(ErrorContextLens), errctx)
+        .returning("has_error", &IntLens(ctx.ctx.bool_type()))
+}
+
+pub fn call_nac3_error_context_get_error_str<'ctx>(
+    size_type: IntType<'ctx>,
+    ctx: &CodeGenContext<'ctx, '_>,
+    errctx: &Address<'ctx, ErrorContextLens>,
+    dst_str: &Address<'ctx, StrLens<'ctx>>,
+) -> IntValue<'ctx> {
+    FunctionBuilder::begin(
+        ctx,
+        &get_sized_dependent_function_name(size_type, "__nac3_error_context_get_error_str"),
+    )
+    .arg("errctx", &AddressLens(ErrorContextLens), errctx)
+    .arg("dst_str", &AddressLens(StrLens { size_type }), dst_str)
+    .returning("has_error", &IntLens(ctx.ctx.bool_type()))
+}
+
+pub fn prepare_error_context<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+) -> Address<'ctx, ErrorContextLens> {
+    let error_ids = build_error_ids(ctx);
+    let errctx_ptr = ErrorContextLens.alloca(ctx, "errctx");
+    call_nac3_error_context_initialize(ctx, &errctx_ptr, &error_ids);
+    errctx_ptr
+}
+
+pub fn check_error_context<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    errctx_ptr: &Address<'ctx, ErrorContextLens>,
+) {
+    let size_type = generator.get_size_type(ctx.ctx);
+
+    let has_error = call_nac3_error_context_has_no_error(ctx, errctx_ptr);
+    let error_str_ptr = StrLens { size_type }.alloca(ctx, "error_str");
+    call_nac3_error_context_get_error_str(size_type, ctx, errctx_ptr, &error_str_ptr);
+
+    let error_id = errctx_ptr.focus(ctx, |fields| &fields.error_id).load(ctx, "error_id");
+    let error_str = error_str_ptr.load(ctx, "error_str");
+    let param1 = errctx_ptr.focus(ctx, |fields| &fields.param1).load(ctx, "param1");
+    let param2 = errctx_ptr.focus(ctx, |fields| &fields.param2).load(ctx, "param2");
+    let param3 = errctx_ptr.focus(ctx, |fields| &fields.param3).load(ctx, "param3");
+    ctx.make_assert_impl_by_id(
+        generator,
+        has_error,
+        error_id,
+        error_str.get_llvm_value(),
+        [Some(param1), Some(param2), Some(param3)],
+        ctx.current_loc,
+    );
+}
+
+pub fn call_nac3_dummy_raise<G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext,
+) {
+    let errctx = prepare_error_context(ctx);
+    FunctionBuilder::begin(ctx, "__nac3_error_dummy_raise")
+        .arg("errctx", &AddressLens(ErrorContextLens), &errctx)
+        .returning_void();
+    check_error_context(generator, ctx, &errctx);
+}

nac3core/src/codegen/irrt/mod.rs

@@ -1,11 +1,9 @@
-use crate::{typecheck::typedef::Type, util::SizeVariant};
-
-mod test;
+use crate::typecheck::typedef::Type;
 
 use super::{
     classes::{
-        ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue, NpArrayType,
-        NpArrayValue, TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
+        ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue,
+        TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
     },
     llvm_intrinsics, CodeGenContext, CodeGenerator,
 };
@@ -16,13 +14,18 @@ use inkwell::{
     context::Context,
     memory_buffer::MemoryBuffer,
     module::Module,
-    types::{BasicType, BasicTypeEnum, FunctionType, IntType, PointerType},
-    values::{BasicValueEnum, CallSiteValue, FloatValue, FunctionValue, IntValue},
+    types::{BasicTypeEnum, IntType},
+    values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue},
     AddressSpace, IntPredicate,
 };
 use itertools::Either;
 use nac3parser::ast::Expr;
 
+pub mod error_context;
+pub mod numpy;
+pub mod test;
+pub mod util;
+
 #[must_use]
 pub fn load_irrt(ctx: &Context) -> Module {
     let bitcode_buf = MemoryBuffer::create_from_memory_range(
@@ -929,63 +932,3 @@ pub fn call_ndarray_calc_broadcast_index<
         Box::new(|_, v| v.into()),
     )
 }
-
-fn get_size_variant<'ctx>(ty: IntType<'ctx>) -> SizeVariant {
-    match ty.get_bit_width() {
-        32 => SizeVariant::Bits32,
-        64 => SizeVariant::Bits64,
-        _ => unreachable!("Unsupported int type bit width {}", ty.get_bit_width()),
-    }
-}
-
-fn get_size_type_dependent_function<'ctx, BuildFuncTypeFn>(
-    ctx: &CodeGenContext<'ctx, '_>,
-    size_type: IntType<'ctx>,
-    base_name: &str,
-    build_func_type: BuildFuncTypeFn,
-) -> FunctionValue<'ctx>
-where
-    BuildFuncTypeFn: Fn() -> FunctionType<'ctx>,
-{
-    let mut fn_name = base_name.to_owned();
-    match get_size_variant(size_type) {
-        SizeVariant::Bits32 => {
-            // The original fn_name is the correct function name
-        }
-        SizeVariant::Bits64 => {
-            // Append "64" at the end, this is the naming convention for 64-bit
-            fn_name.push_str("64");
-        }
-    }
-
-    // Get (or declare then get if does not exist) the corresponding function
-    ctx.module.get_function(&fn_name).unwrap_or_else(|| {
-        let fn_type = build_func_type();
-        ctx.module.add_function(&fn_name, fn_type, None)
-    })
-}
-
-fn get_ndarray_struct_ptr<'ctx>(ctx: &'ctx Context, size_type: IntType<'ctx>) -> PointerType<'ctx> {
-    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.fields().whole_struct.as_struct_type(ctx);
-    struct_ty.ptr_type(AddressSpace::default())
-}
-
-pub fn call_nac3_ndarray_size<'ctx>(
-    ctx: &CodeGenContext<'ctx, '_>,
-    ndarray: NpArrayValue<'ctx>,
-) -> IntValue<'ctx> {
-    let size_type = ndarray.ty.size_type;
-    let function = get_size_type_dependent_function(ctx, size_type, "__nac3_ndarray_size", || {
-        size_type.fn_type(&[get_ndarray_struct_ptr(ctx.ctx, size_type).into()], false)
-    });
-
-    ctx.builder
-        .build_call(function, &[ndarray.ptr.into()], "size")
-        .unwrap()
-        .try_as_basic_value()
-        .unwrap_left()
-        .into_int_value()
-}

nac3core/src/codegen/irrt/numpy.rs

@@ -0,0 +1,415 @@
+use std::marker::PhantomData;
+
+use inkwell::{
+    types::{BasicType, BasicTypeEnum, IntType},
+    values::{BasicValueEnum, IntValue, PointerValue},
+};
+
+use crate::codegen::optics::*;
+use crate::{
+    codegen::{
+        classes::{ListValue, UntypedArrayLikeAccessor},
+        stmt::gen_for_callback_incrementing,
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::{Type, TypeEnum},
+};
+
+use super::{
+    error_context::{check_error_context, prepare_error_context, ErrorContextLens},
+    util::{get_sized_dependent_function_name, FunctionBuilder},
+};
+
+pub struct NpArrayFields<'ctx> {
+    pub data: GepGetter<AddressLens<IntLens<'ctx>>>,
+    pub itemsize: GepGetter<IntLens<'ctx>>,
+    pub ndims: GepGetter<IntLens<'ctx>>,
+    pub shape: GepGetter<AddressLens<IntLens<'ctx>>>,
+    pub strides: GepGetter<AddressLens<IntLens<'ctx>>>,
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct NpArrayLens<'ctx> {
+    pub size_type: IntType<'ctx>,
+}
+
+impl<'ctx> StructureOptic<'ctx> for NpArrayLens<'ctx> {
+    type Fields = NpArrayFields<'ctx>;
+
+    fn struct_name(&self) -> &'static str {
+        "NDArray"
+    }
+
+    fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields {
+        NpArrayFields {
+            data: builder.add_field("data", AddressLens(IntLens(builder.ctx.i8_type()))),
+            itemsize: builder.add_field("itemsize", IntLens(builder.ctx.i8_type())),
+            ndims: builder.add_field("ndims", IntLens(builder.ctx.i8_type())),
+            shape: builder.add_field("shape", AddressLens(IntLens(self.size_type))),
+            strides: builder.add_field("strides", AddressLens(IntLens(self.size_type))),
+        }
+    }
+}
+
+// Other convenient utilities for NpArray
+impl<'ctx> Address<'ctx, NpArrayLens<'ctx>> {
+    pub fn shape_array(&self, ctx: &CodeGenContext<'ctx, '_>) -> ArraySlice<'ctx, IntLens<'ctx>> {
+        let ndims = self.focus(ctx, |fields| &fields.ndims).load(ctx, "ndims");
+        let shape_base_ptr = self.focus(ctx, |fields| &fields.shape).load(ctx, "shape");
+        ArraySlice { num_elements: ndims, base: shape_base_ptr }
+    }
+
+    pub fn strides_array(&self, ctx: &CodeGenContext<'ctx, '_>) -> ArraySlice<'ctx, IntLens<'ctx>> {
+        let ndims = self.focus(ctx, |fields| &fields.ndims).load(ctx, "ndims");
+        let strides_base_ptr = self.focus(ctx, |fields| &fields.strides).load(ctx, "strides");
+        ArraySlice { num_elements: ndims, base: strides_base_ptr }
+    }
+}
+
+type ProducerWriteToArray<'ctx, G, ElementOptic> = Box<
+    dyn Fn(
+            &mut G,
+            &mut CodeGenContext<'ctx, '_>,
+            &ArraySlice<'ctx, ElementOptic>,
+        ) -> Result<(), String>
+        + 'ctx,
+>;
+
+struct Producer<'ctx, G: CodeGenerator + ?Sized, ElementOptic> {
+    pub count: IntValue<'ctx>,
+    pub write_to_array: ProducerWriteToArray<'ctx, G, ElementOptic>,
+}
+
+/// 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.
+pub fn parse_input_shape_arg<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    shape: BasicValueEnum<'ctx>,
+    shape_ty: Type,
+) -> Producer<'ctx, G, IntLens<'ctx>>
+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"));
+            Producer {
+                count: ndims,
+                write_to_array: Box::new(move |ctx, generator, dst_array| {
+                    // 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, axis| {
+                            // Get the dimension at `axis`
+                            let dim =
+                                shape_list.data().get(ctx, generator, &axis, 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_array.ix(ctx, axis, "dim").store(ctx, &dim);
+                            Ok(())
+                        },
+                        incr_val,
+                    )
+                }),
+            }
+        }
+        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();
+
+            Producer {
+                count: size_type.const_int(ndims as u64, false),
+                write_to_array: Box::new(move |_generator, ctx, dst_array| {
+                    for axis in 0..ndims {
+                        // Get the dimension at `axis`
+                        let dim = ctx
+                            .builder
+                            .build_extract_value(
+                                shape_tuple,
+                                axis as u32,
+                                format!("dim{axis}").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_array
+                            .ix(ctx, size_type.const_int(axis as u64, false), "dim")
+                            .store(ctx, &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();
+
+            Producer {
+                count: size_type.const_int(1, false),
+                write_to_array: Box::new(move |_generator, ctx, dst_array| {
+                    // 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_array
+                        .ix(ctx, size_type.const_zero() /* Only index 0 is set */, "dim")
+                        .store(ctx, &dim);
+
+                    Ok(())
+                }),
+            }
+        }
+        _ => panic!("parse_input_shape_arg encountered unknown type"),
+    }
+}
+
+pub fn alloca_ndarray<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    elem_type: BasicTypeEnum<'ctx>,
+    ndims: IntValue<'ctx>,
+    name: &str,
+) -> Result<Address<'ctx, NpArrayLens<'ctx>>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let size_type = generator.get_size_type(ctx.ctx);
+
+    // Allocate ndarray
+    let ndarray_ptr = NpArrayLens { size_type }.alloca(ctx, name);
+
+    // Set ndims
+    ndarray_ptr.focus(ctx, |fields| &fields.ndims).store(ctx, &ndims);
+
+    // Set itemsize
+    let itemsize = elem_type.size_of().unwrap();
+    let itemsize =
+        ctx.builder.build_int_s_extend_or_bit_cast(itemsize, size_type, "itemsize").unwrap();
+    ndarray_ptr.focus(ctx, |fields| &fields.itemsize).store(ctx, &itemsize);
+
+    // Allocate and set shape
+    let shape_ptr = ctx.builder.build_array_alloca(size_type, ndims, "shape").unwrap();
+    ndarray_ptr
+        .focus(ctx, |fields| &fields.shape)
+        .store(ctx, &Address { addressee_optic: IntLens(size_type), address: shape_ptr });
+
+    // Allocate and set strides
+    let strides_ptr = ctx.builder.build_array_alloca(size_type, ndims, "strides").unwrap();
+    ndarray_ptr
+        .focus(ctx, |fields| &fields.strides)
+        .store(ctx, &Address { addressee_optic: IntLens(size_type), address: strides_ptr });
+
+    Ok(ndarray_ptr)
+}
+
+pub enum NDArrayInitMode<'ctx, G: CodeGenerator + ?Sized> {
+    NDim { ndim: IntValue<'ctx> },
+    Shape { shape: Producer<'ctx, G, IntLens<'ctx>> },
+    ShapeAndAllocaData { shape: Producer<'ctx, G, IntLens<'ctx>> },
+}
+
+/// TODO: DOCUMENT ME
+pub 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<Address<'ctx, NpArrayLens<'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::NDim { ndim } => {
+            let ndarray = alloca_ndarray(generator, ctx, elem_type, ndims, name)?;
+            Ok(ndarray)
+        }
+        NDArrayInitMode::Shape { shape } => {
+            let ndims = shape.count;
+            let ndarray_ptr = alloca_ndarray(generator, ctx, elem_type, ndims, name)?;
+
+            // Fill `ndarray.shape`
+            (shape.write_to_array)(generator, ctx, &ndarray_ptr.shape_array(ctx))?;
+
+            // Check if `shape` has bad inputs
+            call_nac3_ndarray_util_assert_shape_no_negative(
+                generator,
+                ctx,
+                ndims,
+                &ndarray_ptr.focus(ctx, |fields| &fields.shape).load(ctx, "shape"),
+            );
+
+            // NOTE: DO NOT DO `set_strides_by_shape` HERE.
+            // Simply this is because we specified that `SetShape` wouldn't do `set_strides_by_shape`
+
+            Ok(ndarray_ptr)
+        }
+        NDArrayInitMode::ShapeAndAllocaData { shape } => {
+            let ndims = shape.count;
+            let ndarray_ptr = alloca_ndarray(generator, ctx, elem_type, ndims, name)?;
+
+            // Fill `ndarray.shape`
+            (shape.write_to_array)(generator, ctx, &ndarray_ptr.shape_array(ctx))?;
+
+            // Check if `shape` has bad inputs
+            call_nac3_ndarray_util_assert_shape_no_negative(
+                generator,
+                ctx,
+                ndims,
+                &ndarray_ptr.focus(ctx, |fields| &fields.shape).load(ctx, "shape"),
+            );
+
+            // 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,
+            // since calculating nbytes of an ndarray requires `ndarray.shape` to be set.
+            let ndarray_nbytes = call_nac3_ndarray_nbytes(generator, ctx, &ndarray_ptr);
+
+            // Alloca `data` and assign it to `ndarray.data`
+            let data_ptr =
+                ctx.builder.build_array_alloca(ctx.ctx.i8_type(), ndarray_nbytes, "data").unwrap();
+            ndarray_ptr.focus(ctx, |fields| &fields.data).store(
+                ctx,
+                &Address { addressee_optic: IntLens::int8(ctx.ctx), address: 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(generator, ctx, &ndarray_ptr);
+
+            Ok(ndarray_ptr)
+        }
+    }
+}
+
+fn call_nac3_ndarray_util_assert_shape_no_negative<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndims: IntValue<'ctx>,
+    shape_ptr: &Address<'ctx, IntLens<'ctx>>,
+) {
+    let size_type = generator.get_size_type(ctx.ctx);
+
+    let errctx = prepare_error_context(ctx);
+    FunctionBuilder::begin(
+        ctx,
+        &get_sized_dependent_function_name(
+            size_type,
+            "__nac3_ndarray_util_assert_shape_no_negative",
+        ),
+    )
+    .arg("errctx", &AddressLens(ErrorContextLens), &errctx)
+    .arg("ndims", &IntLens(size_type), &ndims)
+    .arg("shape", &AddressLens(IntLens(size_type)), shape_ptr)
+    .returning_void();
+    check_error_context(generator, ctx, &errctx);
+}
+
+fn call_nac3_ndarray_set_strides_by_shape<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray_ptr: &Address<'ctx, NpArrayLens<'ctx>>,
+) {
+    let size_type = generator.get_size_type(ctx.ctx);
+
+    FunctionBuilder::begin(
+        ctx,
+        &get_sized_dependent_function_name(
+            size_type,
+            "__nac3_ndarray_util_assert_shape_no_negative",
+        ),
+    )
+    .arg("ndarray", &AddressLens(NpArrayLens { size_type }), ndarray_ptr)
+    .returning_void();
+}
+
+fn call_nac3_ndarray_nbytes<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray_ptr: &Address<'ctx, NpArrayLens<'ctx>>,
+) -> IntValue<'ctx> {
+    let size_type = generator.get_size_type(ctx.ctx);
+
+    FunctionBuilder::begin(
+        ctx,
+        &get_sized_dependent_function_name(
+            size_type,
+            "__nac3_ndarray_util_assert_shape_no_negative",
+        ),
+    )
+    .arg("ndarray", &AddressLens(NpArrayLens { size_type }), ndarray_ptr)
+    .returning("nbytes", &IntLens(size_type))
+}
+
+pub fn call_nac3_ndarray_fill_generic<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray_ptr: &Address<'ctx, NpArrayLens<'ctx>>,
+    fill_value_ptr: PointerValue<'ctx>,
+) {
+    let size_type = generator.get_size_type(ctx.ctx);
+
+    FunctionBuilder::begin(
+        ctx,
+        &get_sized_dependent_function_name(size_type, "__nac3_ndarray_fill_generic"),
+    )
+    .arg("ndarray", &AddressLens(NpArrayLens { size_type }), ndarray_ptr)
+    .arg("pvalue", &OpaqueAddressLens, fill_value_ptr)
+    .returning_void();
+}

nac3core/src/codegen/irrt/test.rs

@@ -11,7 +11,6 @@ mod tests {
 
         let irrt_test_out_path = Path::new(concat!(env!("OUT_DIR"), "/irrt_test.out"));
         let output = Command::new(irrt_test_out_path.to_str().unwrap()).output().unwrap();
-
         if !output.status.success() {
             eprintln!("irrt_test failed with status {}:", output.status);
             eprintln!("====== stdout ======");

nac3core/src/codegen/irrt/util.rs

@@ -0,0 +1,77 @@
+use inkwell::{
+    types::{BasicMetadataTypeEnum, BasicType, IntType},
+    values::{AnyValue, BasicMetadataValueEnum},
+};
+
+use crate::codegen::optics::*;
+use crate::{codegen::CodeGenContext, util::SizeVariant};
+
+fn get_size_variant(ty: IntType) -> SizeVariant {
+    match ty.get_bit_width() {
+        32 => SizeVariant::Bits32,
+        64 => SizeVariant::Bits64,
+        _ => unreachable!("Unsupported int type bit width {}", ty.get_bit_width()),
+    }
+}
+
+#[must_use]
+pub fn get_sized_dependent_function_name(ty: IntType, fn_name: &str) -> String {
+    let mut fn_name = fn_name.to_owned();
+    match get_size_variant(ty) {
+        SizeVariant::Bits32 => {
+            // Do nothing, `fn_name` already has the correct name
+        }
+        SizeVariant::Bits64 => {
+            // Append "64", this is the naming convention
+            fn_name.push_str("64");
+        }
+    }
+    fn_name
+}
+
+// TODO: Variadic argument?
+pub struct FunctionBuilder<'ctx, 'a> {
+    ctx: &'a CodeGenContext<'ctx, 'a>,
+    fn_name: &'a str,
+    arguments: Vec<(BasicMetadataTypeEnum<'ctx>, BasicMetadataValueEnum<'ctx>)>,
+}
+
+impl<'ctx, 'a> FunctionBuilder<'ctx, 'a> {
+    pub fn begin(ctx: &'a CodeGenContext<'ctx, 'a>, fn_name: &'a str) -> Self {
+        FunctionBuilder { ctx, fn_name, arguments: Vec::new() }
+    }
+
+    // The name is for self-documentation
+    #[must_use]
+    pub fn arg<S: MemoryOptic<'ctx>>(mut self, _name: &'static str, optic: &S, arg: &S::MemoryValue) -> Self {
+        self.arguments
+            .push((optic.get_llvm_type(self.ctx.ctx).into(), arg.get_llvm_value().into()));
+        self
+    }
+
+    pub fn returning<S: Prism<'ctx>>(self, name: &'static str, return_prism: &S) -> S::MemoryValue {
+        let (param_tys, param_vals): (Vec<_>, Vec<_>) = self.arguments.into_iter().unzip();
+
+        let function = self.ctx.module.get_function(self.fn_name).unwrap_or_else(|| {
+            let return_type = return_prism.get_llvm_type(self.ctx.ctx);
+            let fn_type = return_type.fn_type(&param_tys, false);
+            self.ctx.module.add_function(self.fn_name, fn_type, None)
+        });
+
+        let ret = self.ctx.builder.build_call(function, &param_vals, name).unwrap();
+        return_prism.review(ret.as_any_value_enum())
+    }
+
+    // TODO: Code duplication, but otherwise returning<S: Optic<'ctx>> cannot resolve S if return_optic = None
+    pub fn returning_void(self) {
+        let (param_tys, param_vals): (Vec<_>, Vec<_>) = self.arguments.into_iter().unzip();
+
+        let function = self.ctx.module.get_function(self.fn_name).unwrap_or_else(|| {
+            let return_type = self.ctx.ctx.void_type();
+            let fn_type = return_type.fn_type(&param_tys, false);
+            self.ctx.module.add_function(self.fn_name, fn_type, None)
+        });
+
+        self.ctx.builder.build_call(function, &param_vals, "").unwrap();
+    }
+}

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

@@ -23,8 +23,10 @@ use inkwell::{
     values::{BasicValueEnum, FunctionValue, IntValue, PhiValue, PointerValue},
     AddressSpace, IntPredicate, OptimizationLevel,
 };
+use irrt::error_context::StrLens;
 use itertools::Itertools;
 use nac3parser::ast::{Location, Stmt, StrRef};
+use optics::MemoryOptic as _;
 use parking_lot::{Condvar, Mutex};
 use std::collections::{HashMap, HashSet};
 use std::sync::{
@@ -42,6 +44,8 @@ mod generator;
 pub mod irrt;
 pub mod llvm_intrinsics;
 pub mod numpy;
+pub mod numpy_new;
+pub mod optics;
 pub mod stmt;
 
 #[cfg(test)]
@@ -646,6 +650,8 @@ pub fn gen_func_impl<
         ..primitives
     };
 
+    let llvm_str_ty =
+        StrLens { size_type: generator.get_size_type(context) }.get_llvm_type(context);
     let mut type_cache: HashMap<_, _> = [
         (primitives.int32, context.i32_type().into()),
         (primitives.int64, context.i64_type().into()),
@@ -653,21 +659,7 @@ pub fn gen_func_impl<
         (primitives.uint64, context.i64_type().into()),
         (primitives.float, context.f64_type().into()),
         (primitives.bool, context.i8_type().into()),
-        (primitives.str, {
-            let name = "str";
-            match module.get_struct_type(name) {
-                None => {
-                    let str_type = context.opaque_struct_type("str");
-                    let fields = [
-                        context.i8_type().ptr_type(AddressSpace::default()).into(),
-                        generator.get_size_type(context).into(),
-                    ];
-                    str_type.set_body(&fields, false);
-                    str_type.into()
-                }
-                Some(t) => t.as_basic_type_enum(),
-            }
-        }),
+        (primitives.str, llvm_str_ty),
         (primitives.range, RangeType::new(context).as_base_type().into()),
         (primitives.exception, {
             let name = "Exception";
@@ -677,7 +669,7 @@ pub fn gen_func_impl<
                 let exception = context.opaque_struct_type("Exception");
                 let int32 = context.i32_type().into();
                 let int64 = context.i64_type().into();
-                let str_ty = module.get_struct_type("str").unwrap().as_basic_type_enum();
+                let str_ty = llvm_str_ty;
                 let fields = [int32, str_ty, int32, int32, str_ty, str_ty, int64, int64, int64];
                 exception.set_body(&fields, false);
                 exception.ptr_type(AddressSpace::default()).as_basic_type_enum()

nac3core/src/codegen/numpy_new.rs

@@ -0,0 +1,91 @@
+use inkwell::values::{BasicValueEnum, PointerValue};
+use nac3parser::ast::StrRef;
+
+use crate::{
+    codegen::optics::build_opaque_alloca, symbol_resolver::ValueEnum, toplevel::DefinitionId, typecheck::typedef::{FunSignature, Type}
+};
+
+use super::{
+    irrt::{
+        self,
+        numpy::{alloca_ndarray_and_init, parse_input_shape_arg, NDArrayInitMode, NpArrayLens},
+    },
+    optics::Address,
+    CodeGenContext, CodeGenerator,
+};
+
+/// 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<Address<'ctx, NpArrayLens<'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_ptr = alloca_ndarray_and_init(
+        generator,
+        ctx,
+        elem_type,
+        NDArrayInitMode::ShapeAndAllocaData { shape },
+        name,
+    )?;
+    Ok(ndarray_ptr)
+}
+
+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<Address<'ctx, NpArrayLens<'ctx>>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let ndarray_ptr = call_ndarray_empty_impl(generator, ctx, elem_ty, shape, shape_ty, name)?;
+
+    // NOTE: fill_value's type is not checked!!
+    let fill_value_ptr = build_opaque_alloca(ctx, fill_value.get_type(), name);
+    fill_value_ptr.store(ctx, );
+    // let fill_value_ptr = ctx.builder.build_alloca(, "fill_value_ptr").unwrap();
+    // ctx.builder.build_store(fill_value_ptr, fill_value);
+
+    // let ok = irrt::numpy::call_nac3_ndarray_fill_generic(generator, ctx, ndarray_ptr, Address { fill_value_ptr } );
+    todo!()
+    Ok(ndarray_ptr)
+}
+
+/// Generates LLVM IR for `np.empty`.
+pub fn gen_ndarray_empty<'ctx, G>(
+    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_ptr = call_ndarray_empty_impl(
+        generator,
+        context,
+        context.primitives.float,
+        shape,
+        shape_ty,
+        "empty_ndarray",
+    )?;
+    Ok(ndarray_ptr.address)
+}

nac3core/src/codegen/optics/address.rs

@@ -0,0 +1,130 @@
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum},
+    values::{AnyValue, BasicValue, BasicValueEnum, PointerValue},
+    AddressSpace,
+};
+
+use crate::codegen::CodeGenContext;
+
+use super::core::{MemoryGetter, MemoryOptic, MemorySetter, OpticValue, Prism};
+
+#[derive(Debug, Clone)]
+pub struct Address<'ctx, AddresseeOptic> {
+    pub addressee_optic: AddresseeOptic,
+    pub address: PointerValue<'ctx>,
+}
+
+impl<'ctx, AddresseeOptic> Address<'ctx, AddresseeOptic> {
+    pub fn cast_to<S: MemoryOptic<'ctx>>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        new_optic: S,
+    ) -> Address<'ctx, S> {
+        let to_ptr_type = new_optic.get_llvm_type(ctx.ctx).ptr_type(AddressSpace::default());
+        let casted_address =
+            ctx.builder.build_pointer_cast(self.address, to_ptr_type, "ptr_casted").unwrap();
+        Address { addressee_optic: new_optic, address: casted_address }
+    }
+
+    pub fn cast_to_opaque(&self) -> OpaqueAddress<'ctx> {
+        OpaqueAddress(self.address)
+    }
+}
+
+impl<'ctx, AddresseeOptic> OpticValue<'ctx> for Address<'ctx, AddresseeOptic> {
+    fn get_llvm_value(&self) -> BasicValueEnum<'ctx> {
+        self.address.as_basic_value_enum()
+    }
+}
+
+#[derive(Debug, Clone)]
+pub struct AddressLens<AddresseeOptic>(pub AddresseeOptic);
+
+impl<'ctx, AddresseeOptic: MemoryOptic<'ctx>> MemoryOptic<'ctx> for AddressLens<AddresseeOptic> {
+    type MemoryValue = Address<'ctx, AddresseeOptic>;
+
+    fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
+        self.0.get_llvm_type(ctx).ptr_type(AddressSpace::default()).as_basic_type_enum()
+    }
+}
+
+impl<'ctx, AddresseeOptic: MemoryOptic<'ctx>> Prism<'ctx> for AddressLens<AddresseeOptic> {
+    fn review<V: AnyValue<'ctx>>(&self, value: V) -> Self::MemoryValue {
+        Address {
+            addressee_optic: self.0.clone(),
+            address: value.as_any_value_enum().into_pointer_value(),
+        }
+    }
+}
+
+impl<'ctx, AddressesOptic: MemoryOptic<'ctx>> MemoryGetter<'ctx> for AddressLens<AddressesOptic> {
+    fn get(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        pointer: PointerValue<'ctx>,
+        name: &str,
+    ) -> Self::MemoryValue {
+        self.review(ctx.builder.build_load(pointer, name).unwrap())
+    }
+}
+
+impl<'ctx, AddressesOptic: MemoryOptic<'ctx>> MemorySetter<'ctx> for AddressLens<AddressesOptic> {
+    fn set(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        pointer: PointerValue<'ctx>,
+        value: &Self::MemoryValue,
+    ) {
+        ctx.builder.build_store(pointer, value.address).unwrap();
+    }
+}
+
+// To make [`Address`] convenient to use
+impl<'ctx, AddresseeOptic: MemoryGetter<'ctx>> Address<'ctx, AddresseeOptic> {
+    pub fn load(&self, ctx: &CodeGenContext<'ctx, '_>, name: &str) -> AddresseeOptic::MemoryValue {
+        self.addressee_optic.get(ctx, self.address, name)
+    }
+}
+
+// To make [`Address`] convenient to use
+impl<'ctx, AddresseeOptic: MemorySetter<'ctx>> Address<'ctx, AddresseeOptic> {
+    pub fn store(&self, ctx: &CodeGenContext<'ctx, '_>, value: &AddresseeOptic::MemoryValue) {
+        self.addressee_optic.set(ctx, self.address, value);
+    }
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct OpaqueAddress<'ctx>(pub PointerValue<'ctx>);
+
+impl<'ctx> OpaqueAddress<'ctx> {
+    pub fn cast_to<AddresseeOptic: MemoryOptic<'ctx>>(
+        &self,
+        ctx: &'ctx CodeGenContext,
+        addressee_optic: AddresseeOptic,
+        name: &str,
+    ) -> Address<'ctx, AddresseeOptic> {
+        let ptr = ctx.builder.build_pointer_cast(
+            self.0,
+            addressee_optic.get_llvm_type(ctx.ctx).ptr_type(AddressSpace::default()),
+            name,
+        );
+        Address { addressee_optic, address: ptr }
+    }
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct OpaqueAddressLens;
+
+impl<'ctx> MemoryOptic<'ctx> for OpaqueAddressLens {
+    type MemoryValue = BasicValueEnum<'ctx>;
+
+    fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
+        ctx.i8_type().ptr_type(AddressSpace::default()).as_basic_type_enum()
+    }
+}
+
+impl<'ctx> OpaqueAddress<'ctx> {
+    pub fn store(&self, ctx: &CodeGenContext<'ctx, '_>, value: BasicValueEnum<'ctx>) {
+    }
+}

nac3core/src/codegen/optics/core.rs

@@ -0,0 +1,51 @@
+use inkwell::{
+    context::Context,
+    types::BasicTypeEnum,
+    values::{AnyValue, BasicValue, BasicValueEnum, PointerValue},
+};
+
+use crate::codegen::CodeGenContext;
+
+use super::address::Address;
+
+// TODO: Write a taxonomy
+
+pub trait OpticValue<'ctx> {
+    fn get_llvm_value(&self) -> BasicValueEnum<'ctx>;
+}
+
+impl<'ctx, T: BasicValue<'ctx>> OpticValue<'ctx> for T {
+    fn get_llvm_value(&self) -> BasicValueEnum<'ctx> {
+        self.as_basic_value_enum()
+    }
+}
+
+// TODO: The interface is unintuitive
+pub trait MemoryOptic<'ctx>: Clone {
+    type MemoryValue: OpticValue<'ctx>;
+
+    fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx>;
+
+    fn alloca(&self, ctx: &CodeGenContext<'ctx, '_>, name: &str) -> Address<'ctx, Self> {
+        let ptr = ctx.builder.build_alloca(self.get_llvm_type(ctx.ctx), name).unwrap();
+        Address { addressee_optic: self.clone(), address: ptr }
+    }
+}
+
+pub trait Prism<'ctx>: MemoryOptic<'ctx> {
+    // TODO: Return error if `review` fails
+    fn review<V: AnyValue<'ctx>>(&self, value: V) -> Self::MemoryValue;
+}
+
+pub trait MemoryGetter<'ctx>: MemoryOptic<'ctx> {
+    fn get(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        pointer: PointerValue<'ctx>,
+        name: &str,
+    ) -> Self::MemoryValue;
+}
+
+pub trait MemorySetter<'ctx>: MemoryOptic<'ctx> {
+    fn set(&self, ctx: &CodeGenContext<'ctx, '_>, pointer: PointerValue<'ctx>, value: &Self::MemoryValue);
+}

nac3core/src/codegen/optics/gep.rs

@@ -0,0 +1,53 @@
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum},
+    values::PointerValue,
+    AddressSpace,
+};
+
+use crate::codegen::CodeGenContext;
+
+use super::{
+    address::Address,
+    core::{MemoryGetter, MemoryOptic},
+};
+
+// ((Memory, Pointer) -> ElementOptic::Value*)
+#[derive(Debug, Clone)]
+pub struct GepGetter<ElementOptic> {
+    /// The LLVM GEP index
+    pub gep_index: u64,
+    /// Element (or field in the context of `struct`s) name. Used for cosmetics.
+    pub name: &'static str,
+    /// The lens to view the actual value after applying this [`FieldLens<T>`]
+    pub element_optic: ElementOptic,
+}
+
+impl<'ctx, ElementOptic: MemoryOptic<'ctx>> MemoryOptic<'ctx> for GepGetter<ElementOptic> {
+    type MemoryValue = Address<'ctx, ElementOptic>;
+
+    fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
+        self.element_optic.get_llvm_type(ctx).ptr_type(AddressSpace::default()).as_basic_type_enum()
+    }
+}
+
+impl<'ctx, ElementOptic: MemoryOptic<'ctx>> MemoryGetter<'ctx> for GepGetter<ElementOptic> {
+    fn get(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        pointer: PointerValue<'ctx>,
+        name: &str,
+    ) -> Self::MemoryValue {
+        let llvm_i32 = ctx.ctx.i32_type(); // TODO: I think I'm not supposed to *just* use i32 for GEP like that
+        let element_ptr = unsafe {
+            ctx.builder
+                .build_in_bounds_gep(
+                    pointer,
+                    &[llvm_i32.const_zero(), llvm_i32.const_int(self.gep_index, false)],
+                    name,
+                )
+                .unwrap()
+        };
+        Address { address: element_ptr, addressee_optic: self.element_optic.clone() }
+    }
+}

nac3core/src/codegen/optics/int.rs

@@ -0,0 +1,66 @@
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum, IntType},
+    values::{AnyValue, BasicValue, IntValue, PointerValue},
+};
+
+use crate::codegen::CodeGenContext;
+
+use super::core::{MemoryGetter, MemorySetter, MemoryOptic, Prism};
+
+// NOTE: I wanted to make Int8Lens, Int16Lens, Int32Lens, with all
+// having the trait IsIntLens, and implement `impl <S: IsIntLens> Optic<S> for T`,
+// but that clashes with StructureOptic!!
+#[derive(Debug, Clone, Copy)]
+pub struct IntLens<'ctx>(pub IntType<'ctx>);
+
+impl<'ctx> IntLens<'ctx> {
+    #[must_use]
+    pub fn int8(ctx: &'ctx Context) -> IntLens<'ctx> {
+        IntLens(ctx.i8_type())
+    }
+
+    #[must_use]
+    pub fn int32(ctx: &'ctx Context) -> IntLens<'ctx> {
+        IntLens(ctx.i32_type())
+    }
+
+    #[must_use]
+    pub fn int64(ctx: &'ctx Context) -> IntLens<'ctx> {
+        IntLens(ctx.i64_type())
+    }
+}
+
+impl<'ctx> MemoryOptic<'ctx> for IntLens<'ctx> {
+    type MemoryValue = IntValue<'ctx>;
+
+    fn get_llvm_type(&self, _ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
+        self.0.as_basic_type_enum()
+    }
+}
+
+impl<'ctx> Prism<'ctx> for IntLens<'ctx> {
+    fn review<V: AnyValue<'ctx>>(&self, value: V) -> Self::MemoryValue {
+        let int = value.as_any_value_enum().into_int_value();
+        debug_assert_eq!(int.get_type().get_bit_width(), self.0.get_bit_width());
+        int
+    }
+}
+
+impl<'ctx> MemoryGetter<'ctx> for IntLens<'ctx> {
+    fn get(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        pointer: PointerValue<'ctx>,
+        name: &str,
+    ) -> Self::MemoryValue {
+        self.review(ctx.builder.build_load(pointer, name).unwrap())
+    }
+}
+
+impl<'ctx> MemorySetter<'ctx> for IntLens<'ctx> {
+    fn set(&self, ctx: &CodeGenContext<'ctx, '_>, pointer: PointerValue<'ctx>, int: &Self::MemoryValue) {
+        debug_assert_eq!(int.get_type().get_bit_width(), self.0.get_bit_width());
+        ctx.builder.build_store(pointer, int.as_basic_value_enum()).unwrap();
+    }
+}

nac3core/src/codegen/optics/ixed.rs

@@ -0,0 +1,65 @@
+use inkwell::values::IntValue;
+
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+use super::address::Address;
+
+// Name inspired by https://hackage.haskell.org/package/lens-5.3.2/docs/Control-Lens-At.html#t:Ixed
+pub trait Ixed<'ctx, ElementOptic> {
+    // TODO: Interface/Method to expose the IntType of index?
+    // or even make index itself parameterized? (probably no)
+
+    fn ix(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        index: IntValue<'ctx>,
+        name: &str,
+    ) -> Address<'ctx, ElementOptic>;
+}
+
+// TODO: Can do interface seggregation
+pub trait BoundedIxed<'ctx, ElementOptic>: Ixed<'ctx, ElementOptic> {
+    fn num_elements(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx>;
+
+    // Check if 0 <= index < self.num_elements()
+    fn ix_bounds_checked<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        index: IntValue<'ctx>,
+        name: &str,
+    ) -> Address<'ctx, ElementOptic> {
+        let num_elements = self.num_elements(ctx);
+        let int_type = num_elements.get_type(); // NOTE: Weird get_type(), see comment under `trait Ixed`
+
+        assert_eq!(int_type.get_bit_width(), index.get_type().get_bit_width()); // Might as well check bit width to catch bugs
+
+        // TODO: SGE or UGE? or make it defined by the implementee?
+
+        // Check `0 <= index`
+        let lower_bounded = ctx
+            .builder
+            .build_int_compare(
+                inkwell::IntPredicate::SLE,
+                int_type.const_zero(),
+                index,
+                "lower_bounded",
+            )
+            .unwrap();
+
+        // Check `index < num_elements`
+        let upper_bounded = ctx
+            .builder
+            .build_int_compare(inkwell::IntPredicate::SLT, index, num_elements, "upper_bounded")
+            .unwrap();
+
+        // Compute `0 <= index && index < num_elements`
+        let bounded = ctx.builder.build_and(lower_bounded, upper_bounded, "bounded").unwrap();
+
+        // Assert `bounded`
+        ctx.make_assert(generator, bounded, "0:IndexError", "nac3core LLVM codegen attempting to access out of bounds array index {0}. Must satisfy 0 <= index < {2}", [Some(index), Some(num_elements), None], ctx.current_loc);
+
+        // ...and finally do indexing
+        self.ix(ctx, index, name)
+    }
+}

nac3core/src/codegen/optics/mod.rs

@@ -0,0 +1,15 @@
+pub mod address;
+pub mod core;
+pub mod gep;
+pub mod int;
+pub mod ixed;
+pub mod slice;
+pub mod structure;
+
+pub use address::*;
+pub use core::*;
+pub use gep::*;
+pub use int::*;
+pub use ixed::*;
+pub use slice::*;
+pub use structure::*;

nac3core/src/codegen/optics/slice.rs

@@ -0,0 +1,36 @@
+use super::{
+    core::MemoryOptic,
+    ixed::{BoundedIxed, Ixed},
+};
+
+use inkwell::values::IntValue;
+
+use crate::codegen::CodeGenContext;
+
+use super::address::Address;
+
+pub struct ArraySlice<'ctx, ElementOptic> {
+    pub num_elements: IntValue<'ctx>,
+    pub base: Address<'ctx, ElementOptic>,
+}
+
+impl<'ctx, ElementOptic: MemoryOptic<'ctx>> Ixed<'ctx, ElementOptic> for ArraySlice<'ctx, ElementOptic> {
+    fn ix(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        index: IntValue<'ctx>,
+        name: &str,
+    ) -> Address<'ctx, ElementOptic> {
+        let element_addr =
+            unsafe { ctx.builder.build_in_bounds_gep(self.base.address, &[index], name).unwrap() };
+        Address { address: element_addr, addressee_optic: self.base.addressee_optic.clone() }
+    }
+}
+
+impl<'ctx, ElementOptic: MemoryOptic<'ctx>> BoundedIxed<'ctx, ElementOptic>
+    for ArraySlice<'ctx, ElementOptic>
+{
+    fn num_elements(&self, _ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.num_elements
+    }
+}

nac3core/src/codegen/optics/structure.rs

@@ -0,0 +1,139 @@
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum},
+    values::{BasicValue, BasicValueEnum, PointerValue, StructValue},
+};
+use itertools::Itertools;
+
+use crate::codegen::CodeGenContext;
+
+use super::{
+    address::Address,
+    core::{MemoryGetter, MemorySetter, MemoryOptic, OpticValue},
+    gep::GepGetter,
+};
+
+pub trait StructureOptic<'ctx>: Clone {
+    // Fields of optics
+    type Fields;
+
+    // TODO: Make it an associated function instead?
+    fn struct_name(&self) -> &'static str;
+
+    fn build_fields(&self, builder: &mut FieldBuilder<'ctx>) -> Self::Fields;
+
+    fn get_fields(&self, ctx: &'ctx Context) -> Self::Fields {
+        let mut builder = FieldBuilder::new(ctx, self.struct_name());
+        self.build_fields(&mut builder)
+    }
+}
+
+pub struct OpticalStructValue<'ctx, StructOptic> {
+    optic: StructOptic,
+    llvm: StructValue<'ctx>,
+}
+
+impl<'ctx, StructOptic> OpticValue<'ctx> for OpticalStructValue<'ctx, StructOptic> {
+    fn get_llvm_value(&self) -> BasicValueEnum<'ctx> {
+        self.llvm.as_basic_value_enum()
+    }
+}
+
+// TODO: check StructType
+impl<'ctx, T: StructureOptic<'ctx>> MemoryOptic<'ctx> for T {
+    type MemoryValue = OpticalStructValue<'ctx, Self>;
+
+    fn get_llvm_type(&self, ctx: &'ctx Context) -> BasicTypeEnum<'ctx> {
+        let mut builder = FieldBuilder::new(ctx, self.struct_name());
+        self.build_fields(&mut builder); // Self::Fields is discarded
+
+        let field_types =
+            builder.fields.iter().map(|field_info| field_info.llvm_type).collect_vec();
+        ctx.struct_type(&field_types, false).as_basic_type_enum()
+    }
+}
+
+impl<'ctx, T: StructureOptic<'ctx>> MemoryGetter<'ctx> for T {
+    fn get(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        pointer: PointerValue<'ctx>,
+        name: &str,
+    ) -> Self::MemoryValue {
+        OpticalStructValue {
+            optic: self.clone(),
+            llvm: ctx.builder.build_load(pointer, name).unwrap().into_struct_value(),
+        }
+    }
+}
+
+impl<'ctx, T: StructureOptic<'ctx>> MemorySetter<'ctx> for T {
+    fn set(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        pointer: PointerValue<'ctx>,
+        value: &Self::MemoryValue,
+    ) {
+        ctx.builder.build_store(pointer, value.llvm).unwrap();
+    }
+}
+
+impl<'ctx, AddresseeOptic: StructureOptic<'ctx>> Address<'ctx, AddresseeOptic> {
+    pub fn focus<GetFieldGepFn, FieldElementOptic: MemoryOptic<'ctx>>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        get_field_gep_fn: GetFieldGepFn,
+    ) -> Address<'ctx, FieldElementOptic>
+    where
+        GetFieldGepFn: FnOnce(&AddresseeOptic::Fields) -> &GepGetter<FieldElementOptic>,
+    {
+        let fields = self.addressee_optic.get_fields(ctx.ctx);
+        let field = get_field_gep_fn(&fields);
+        field.get(ctx, self.address, field.name)
+    }
+}
+
+// Only used by [`FieldBuilder`]
+#[derive(Debug)]
+struct FieldInfo<'ctx> {
+    gep_index: u64,
+    name: &'ctx str,
+    llvm_type: BasicTypeEnum<'ctx>,
+}
+
+#[derive(Debug)]
+pub struct FieldBuilder<'ctx> {
+    pub ctx: &'ctx Context,
+    gep_index_counter: u64,
+    struct_name: &'ctx str,
+    fields: Vec<FieldInfo<'ctx>>,
+}
+
+impl<'ctx> FieldBuilder<'ctx> {
+    #[must_use]
+    pub fn new(ctx: &'ctx Context, struct_name: &'ctx str) -> Self {
+        FieldBuilder { ctx, gep_index_counter: 0, struct_name, fields: Vec::new() }
+    }
+
+    fn next_gep_index(&mut self) -> u64 {
+        let index = self.gep_index_counter;
+        self.gep_index_counter += 1;
+        index
+    }
+
+    pub fn add_field<ElementOptic: MemoryOptic<'ctx>>(
+        &mut self,
+        name: &'static str,
+        element_optic: ElementOptic,
+    ) -> GepGetter<ElementOptic> {
+        let gep_index = self.next_gep_index();
+
+        self.fields.push(FieldInfo {
+            gep_index,
+            name,
+            llvm_type: element_optic.get_llvm_type(self.ctx),
+        });
+
+        GepGetter { gep_index, name, element_optic }
+    }
+}

nac3core/src/lib.rs

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

nac3core/src/toplevel/builtins.rs

@@ -279,8 +279,8 @@ pub fn get_builtins(unifier: &mut Unifier, primitives: &PrimitiveStore) -> Built
         .collect()
 }
 
-fn size_variant_to_int_type(variant: SizeVariant, primitives: &PrimitiveStore) -> Type {
-    match variant {
+fn get_size_variant_of_int(size_variant: SizeVariant, primitives: &PrimitiveStore) -> Type {
+    match size_variant {
         SizeVariant::Bits32 => primitives.int32,
         SizeVariant::Bits64 => primitives.int64,
     }
@@ -502,7 +502,9 @@ impl<'a> BuiltinBuilder<'a> {
 
             PrimDef::FunMin | PrimDef::FunMax => self.build_min_max_function(prim),
 
-            PrimDef::FunNpMin | PrimDef::FunNpMax => self.build_np_min_max_function(prim),
+            PrimDef::FunNpArgmin | PrimDef::FunNpArgmax | PrimDef::FunNpMin | PrimDef::FunNpMax => {
+                self.build_np_max_min_function(prim)
+            }
 
             PrimDef::FunNpMinimum | PrimDef::FunNpMaximum => {
                 self.build_np_minimum_maximum_function(prim)
@@ -953,9 +955,8 @@ impl<'a> BuiltinBuilder<'a> {
                 resolver: None,
                 codegen_callback: Some(Arc::new(GenCall::new(Box::new(
                     |ctx, obj, fun, args, generator| {
-                        todo!()
-                        // gen_ndarray_copy(ctx, &obj, fun, &args, generator)
-                        //     .map(|val| Some(val.as_basic_value_enum()))
+                        gen_ndarray_copy(ctx, &obj, fun, &args, generator)
+                            .map(|val| Some(val.as_basic_value_enum()))
                     },
                 )))),
                 loc: None,
@@ -971,9 +972,8 @@ impl<'a> BuiltinBuilder<'a> {
                 resolver: None,
                 codegen_callback: Some(Arc::new(GenCall::new(Box::new(
                     |ctx, obj, fun, args, generator| {
-                        todo!()
-                        // gen_ndarray_fill(ctx, &obj, fun, &args, generator)?;
-                        // Ok(None)
+                        gen_ndarray_fill(ctx, &obj, fun, &args, generator)?;
+                        Ok(None)
                     },
                 )))),
                 loc: None,
@@ -1053,7 +1053,7 @@ impl<'a> BuiltinBuilder<'a> {
         );
 
         // The size variant of the function determines the size of the returned int.
-        let int_sized = size_variant_to_int_type(size_variant, self.primitives);
+        let int_sized = get_size_variant_of_int(size_variant, self.primitives);
 
         let ndarray_int_sized =
             make_ndarray_ty(self.unifier, self.primitives, Some(int_sized), Some(common_ndim.ty));
@@ -1078,7 +1078,7 @@ impl<'a> BuiltinBuilder<'a> {
                 let arg_ty = fun.0.args[0].ty;
                 let arg = args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
 
-                let ret_elem_ty = size_variant_to_int_type(size_variant, &ctx.primitives);
+                let ret_elem_ty = get_size_variant_of_int(size_variant, &ctx.primitives);
                 Ok(Some(builtin_fns::call_round(generator, ctx, (arg_ty, arg), ret_elem_ty)?))
             }),
         )
@@ -1119,7 +1119,7 @@ impl<'a> BuiltinBuilder<'a> {
             make_ndarray_ty(self.unifier, self.primitives, Some(float), Some(common_ndim.ty));
 
         // The size variant of the function determines the type of int returned
-        let int_sized = size_variant_to_int_type(size_variant, self.primitives);
+        let int_sized = get_size_variant_of_int(size_variant, self.primitives);
         let ndarray_int_sized =
             make_ndarray_ty(self.unifier, self.primitives, Some(int_sized), Some(common_ndim.ty));
 
@@ -1142,7 +1142,7 @@ impl<'a> BuiltinBuilder<'a> {
                 let arg_ty = fun.0.args[0].ty;
                 let arg = args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
 
-                let ret_elem_ty = size_variant_to_int_type(size_variant, &ctx.primitives);
+                let ret_elem_ty = get_size_variant_of_int(size_variant, &ctx.primitives);
                 let func = match kind {
                     Kind::Ceil => builtin_fns::call_ceil,
                     Kind::Floor => builtin_fns::call_floor,
@@ -1193,14 +1193,13 @@ impl<'a> BuiltinBuilder<'a> {
             self.ndarray_float,
             &[(self.ndarray_factory_fn_shape_arg_tvar.ty, "shape")],
             Box::new(move |ctx, obj, fun, args, generator| {
-                todo!()
-                // let func = match prim {
-                //     PrimDef::FunNpNDArray | PrimDef::FunNpEmpty => gen_ndarray_empty,
-                //     PrimDef::FunNpZeros => gen_ndarray_zeros,
-                //     PrimDef::FunNpOnes => gen_ndarray_ones,
-                //     _ => unreachable!(),
-                // };
-                // func(ctx, &obj, fun, &args, generator).map(|val| Some(val.as_basic_value_enum()))
+                let func = match prim {
+                    PrimDef::FunNpNDArray | PrimDef::FunNpEmpty => gen_ndarray_empty,
+                    PrimDef::FunNpZeros => gen_ndarray_zeros,
+                    PrimDef::FunNpOnes => gen_ndarray_ones,
+                    _ => unreachable!(),
+                };
+                func(ctx, &obj, fun, &args, generator).map(|val| Some(val.as_basic_value_enum()))
             }),
         )
     }
@@ -1246,9 +1245,8 @@ impl<'a> BuiltinBuilder<'a> {
                     resolver: None,
                     codegen_callback: Some(Arc::new(GenCall::new(Box::new(
                         |ctx, obj, fun, args, generator| {
-                            todo!()
-                            // gen_ndarray_array(ctx, &obj, fun, &args, generator)
-                            //     .map(|val| Some(val.as_basic_value_enum()))
+                            gen_ndarray_array(ctx, &obj, fun, &args, generator)
+                                .map(|val| Some(val.as_basic_value_enum()))
                         },
                     )))),
                     loc: None,
@@ -1266,9 +1264,8 @@ impl<'a> BuiltinBuilder<'a> {
                     // type variable
                     &[(self.list_int32, "shape"), (tv.ty, "fill_value")],
                     Box::new(move |ctx, obj, fun, args, generator| {
-                        todo!()
-                        // gen_ndarray_full(ctx, &obj, fun, &args, generator)
-                        //     .map(|val| Some(val.as_basic_value_enum()))
+                        gen_ndarray_full(ctx, &obj, fun, &args, generator)
+                            .map(|val| Some(val.as_basic_value_enum()))
                     }),
                 )
             }
@@ -1300,9 +1297,8 @@ impl<'a> BuiltinBuilder<'a> {
                     resolver: None,
                     codegen_callback: Some(Arc::new(GenCall::new(Box::new(
                         |ctx, obj, fun, args, generator| {
-                            todo!()
-                            // gen_ndarray_eye(ctx, &obj, fun, &args, generator)
-                            //     .map(|val| Some(val.as_basic_value_enum()))
+                            gen_ndarray_eye(ctx, &obj, fun, &args, generator)
+                                .map(|val| Some(val.as_basic_value_enum()))
                         },
                     )))),
                     loc: None,
@@ -1315,9 +1311,8 @@ impl<'a> BuiltinBuilder<'a> {
                 self.ndarray_float_2d,
                 &[(int32, "n")],
                 Box::new(|ctx, obj, fun, args, generator| {
-                    todo!()
-                    // gen_ndarray_identity(ctx, &obj, fun, &args, generator)
-                    //     .map(|val| Some(val.as_basic_value_enum()))
+                    gen_ndarray_identity(ctx, &obj, fun, &args, generator)
+                        .map(|val| Some(val.as_basic_value_enum()))
                 }),
             ),
             _ => unreachable!(),
@@ -1554,39 +1549,45 @@ impl<'a> BuiltinBuilder<'a> {
         }
     }
 
-    /// Build the functions `np_min()` and `np_max()`.
-    fn build_np_min_max_function(&mut self, prim: PrimDef) -> TopLevelDef {
-        debug_assert_prim_is_allowed(prim, &[PrimDef::FunNpMin, PrimDef::FunNpMax]);
+    /// Build the functions `np_max()`, `np_min()`, `np_argmax()` and `np_argmin()`
+    /// Calls `call_numpy_max_min` with the function name
+    fn build_np_max_min_function(&mut self, prim: PrimDef) -> TopLevelDef {
+        debug_assert_prim_is_allowed(
+            prim,
+            &[PrimDef::FunNpArgmin, PrimDef::FunNpArgmax, PrimDef::FunNpMin, PrimDef::FunNpMax],
+        );
 
-        let ret_ty = self.unifier.get_fresh_var(Some("R".into()), None);
-        let var_map = self
-            .num_or_ndarray_var_map
-            .clone()
-            .into_iter()
-            .chain(once((ret_ty.id, ret_ty.ty)))
-            .collect::<IndexMap<_, _>>();
+        let (var_map, ret_ty) = match prim {
+            PrimDef::FunNpArgmax | PrimDef::FunNpArgmin => {
+                (self.num_or_ndarray_var_map.clone(), self.primitives.int64)
+            }
+            PrimDef::FunNpMax | PrimDef::FunNpMin => {
+                let ret_ty = self.unifier.get_fresh_var(Some("R".into()), None);
+                let var_map = self
+                    .num_or_ndarray_var_map
+                    .clone()
+                    .into_iter()
+                    .chain(once((ret_ty.id, ret_ty.ty)))
+                    .collect::<IndexMap<_, _>>();
+                (var_map, ret_ty.ty)
+            }
+            _ => unreachable!(),
+        };
 
         create_fn_by_codegen(
             self.unifier,
             &var_map,
             prim.name(),
-            ret_ty.ty,
-            &[(self.float_or_ndarray_ty.ty, "a")],
+            ret_ty,
+            &[(self.num_or_ndarray_ty.ty, "a")],
             Box::new(move |ctx, _, fun, args, generator| {
                 let a_ty = fun.0.args[0].ty;
                 let a = args[0].1.clone().to_basic_value_enum(ctx, generator, a_ty)?;
 
-                let func = match prim {
-                    PrimDef::FunNpMin => builtin_fns::call_numpy_min,
-                    PrimDef::FunNpMax => builtin_fns::call_numpy_max,
-                    _ => unreachable!(),
-                };
-
-                Ok(Some(func(generator, ctx, (a_ty, a))?))
+                Ok(Some(builtin_fns::call_numpy_max_min(generator, ctx, (a_ty, a), prim.name())?))
             }),
         )
     }
-
     /// Build the functions `np_minimum()` and `np_maximum()`.
     fn build_np_minimum_maximum_function(&mut self, prim: PrimDef) -> TopLevelDef {
         debug_assert_prim_is_allowed(prim, &[PrimDef::FunNpMinimum, PrimDef::FunNpMaximum]);

nac3core/src/toplevel/helper.rs

@@ -62,9 +62,11 @@ pub enum PrimDef {
     FunMin,
     FunNpMin,
     FunNpMinimum,
+    FunNpArgmin,
     FunMax,
     FunNpMax,
     FunNpMaximum,
+    FunNpArgmax,
     FunAbs,
     FunNpIsNan,
     FunNpIsInf,
@@ -216,9 +218,11 @@ impl PrimDef {
             PrimDef::FunMin => fun("min", None),
             PrimDef::FunNpMin => fun("np_min", None),
             PrimDef::FunNpMinimum => fun("np_minimum", None),
+            PrimDef::FunNpArgmin => fun("np_argmin", None),
             PrimDef::FunMax => fun("max", None),
             PrimDef::FunNpMax => fun("np_max", None),
             PrimDef::FunNpMaximum => fun("np_maximum", None),
+            PrimDef::FunNpArgmax => fun("np_argmax", None),
             PrimDef::FunAbs => fun("abs", None),
             PrimDef::FunNpIsNan => fun("np_isnan", None),
             PrimDef::FunNpIsInf => fun("np_isinf", None),

nac3core/src/typecheck/type_inferencer/mod.rs

@@ -398,7 +398,10 @@ impl<'a> Fold<()> for Inferencer<'a> {
                 }
                 if let Some(exc) = exc {
                     self.virtual_checks.push((
-                        exc.custom.unwrap(),
+                        match &*self.unifier.get_ty(exc.custom.unwrap()) {
+                            TypeEnum::TFunc(sign) => sign.ret,
+                            _ => exc.custom.unwrap(),
+                        },
                         self.primitives.exception,
                         exc.location,
                     ));

nac3core/src/util.rs

@@ -0,0 +1,6 @@
+/// A helper enum used by [`BuiltinBuilder`]
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+pub enum SizeVariant {
+    Bits32,
+    Bits64,
+}

nac3standalone/demo/interpret_demo.py

@@ -183,8 +183,10 @@ def patch(module):
     module.np_isinf = np.isinf
     module.np_min = np.min
     module.np_minimum = np.minimum
+    module.np_argmin = np.argmin
     module.np_max = np.max
     module.np_maximum = np.maximum
+    module.np_argmax = np.argmax
     module.np_sin = np.sin
     module.np_cos = np.cos
     module.np_exp = np.exp

nac3standalone/demo/src/ndarray.py

@@ -867,6 +867,13 @@ def test_ndarray_minimum_broadcast_rhs_scalar():
     output_ndarray_float_2(min_x_zeros)
     output_ndarray_float_2(min_x_ones)
 
+def test_ndarray_argmin():
+    x = np_array([[1., 2.], [3., 4.]])
+    y = np_argmin(x)
+
+    output_ndarray_float_2(x)
+    output_int64(y)
+
 def test_ndarray_max():
     x = np_identity(2)
     y = np_max(x)
@@ -910,6 +917,13 @@ def test_ndarray_maximum_broadcast_rhs_scalar():
     output_ndarray_float_2(max_x_zeros)
     output_ndarray_float_2(max_x_ones)
 
+def test_ndarray_argmax():
+    x = np_array([[1., 2.], [3., 4.]])
+    y = np_argmax(x)
+
+    output_ndarray_float_2(x)
+    output_int64(y)
+
 def test_ndarray_abs():
     x = np_identity(2)
     y = abs(x)
@@ -1524,11 +1538,13 @@ def run() -> int32:
     test_ndarray_minimum_broadcast()
     test_ndarray_minimum_broadcast_lhs_scalar()
     test_ndarray_minimum_broadcast_rhs_scalar()
+    test_ndarray_argmin()
     test_ndarray_max()
     test_ndarray_maximum()
     test_ndarray_maximum_broadcast()
     test_ndarray_maximum_broadcast_lhs_scalar()
     test_ndarray_maximum_broadcast_rhs_scalar()
+    test_ndarray_argmax()
     test_ndarray_abs()
     test_ndarray_isnan()
     test_ndarray_isinf()

nix/windows/default.nix

@@ -81,7 +81,6 @@ in rec {
     ''
     mkdir -p $out/bin
     ln -s ${llvm-nac3}/bin/clang.exe $out/bin/clang-irrt.exe
-    ln -s ${llvm-nac3}/bin/clang.exe $out/bin/clang-irrt-test.exe
     ln -s ${llvm-nac3}/bin/llvm-as.exe $out/bin/llvm-as-irrt.exe
     '';
   nac3artiq = pkgs.rustPlatform.buildRustPackage {