core: implement ndarray_iter_elem_impl and np.any() & np.all()

nac3core/src/codegen/builtin_fns.rs

@@ -725,7 +725,7 @@ pub fn call_numpy_min<'ctx, G: CodeGenerator + ?Sized>(
                 ctx,
                 llvm_usize.const_int(1, false),
                 (n_sz, false),
-                |generator, ctx, idx| {
+                |generator, ctx, _, idx| {
                     let elem = unsafe { n.data().get_unchecked(ctx, generator, &idx, None) };
 
                     let accumulator = ctx.builder.build_load(accumulator_addr, "").unwrap();
@@ -941,7 +941,7 @@ pub fn call_numpy_max<'ctx, G: CodeGenerator + ?Sized>(
                 ctx,
                 llvm_usize.const_int(1, false),
                 (n_sz, false),
-                |generator, ctx, idx| {
+                |generator, ctx, _, idx| {
                     let elem = unsafe { n.data().get_unchecked(ctx, generator, &idx, None) };
 
                     let accumulator = ctx.builder.build_load(accumulator_addr, "").unwrap();

nac3core/src/codegen/classes.rs

@@ -1706,7 +1706,7 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
             ctx,
             llvm_usize.const_zero(),
             (len, false),
-            |generator, ctx, i| {
+            |generator, ctx, _, i| {
                 let (dim_idx, dim_sz) = unsafe {
                     (
                         indices.get_unchecked(ctx, generator, &i, None).into_int_value(),

nac3core/src/codegen/irrt/mod.rs

@@ -802,7 +802,7 @@ pub fn call_ndarray_calc_broadcast<'ctx, G: CodeGenerator + ?Sized>(
         ctx,
         llvm_usize.const_zero(),
         (min_ndims, false),
-        |generator, ctx, idx| {
+        |generator, ctx, _, idx| {
             let idx = ctx.builder.build_int_sub(min_ndims, idx, "").unwrap();
             let (lhs_dim_sz, rhs_dim_sz) = unsafe {
                 (

nac3core/src/codegen/numpy.rs

@@ -7,12 +7,11 @@ use crate::{
         },
         expr::gen_binop_expr_with_values,
         irrt::{
-            calculate_len_for_slice_range, call_ndarray_calc_broadcast,
+            self, calculate_len_for_slice_range, call_ndarray_calc_broadcast,
             call_ndarray_calc_broadcast_index, call_ndarray_calc_nd_indices,
             call_ndarray_calc_size,
         },
-        llvm_intrinsics,
+        llvm_intrinsics::{self, call_memcpy_generic},
-        llvm_intrinsics::call_memcpy_generic,
         stmt::{gen_for_callback_incrementing, gen_for_range_callback, gen_if_else_expr_callback},
         CodeGenContext, CodeGenerator,
     },
@@ -32,6 +31,8 @@ use inkwell::{
 };
 use nac3parser::ast::{Operator, StrRef};
 
+use super::{builtin_fns::call_bool, stmt::BreakContinueHooks};
+
 /// Creates an uninitialized `NDArray` instance.
 fn create_ndarray_uninitialized<'ctx, G: CodeGenerator + ?Sized>(
     generator: &mut G,
@@ -86,7 +87,7 @@ where
         ctx,
         llvm_usize.const_zero(),
         (shape_len, false),
-        |generator, ctx, i| {
+        |generator, ctx, _, i| {
             let shape_dim = shape_data_fn(generator, ctx, shape, i)?;
             debug_assert!(shape_dim.get_type().get_bit_width() <= llvm_usize.get_bit_width());
 
@@ -131,7 +132,7 @@ where
         ctx,
         llvm_usize.const_zero(),
         (shape_len, false),
-        |generator, ctx, i| {
+        |generator, ctx, _, i| {
             let shape_dim = shape_data_fn(generator, ctx, shape, i)?;
             debug_assert!(shape_dim.get_type().get_bit_width() <= llvm_usize.get_bit_width());
             let shape_dim = ctx.builder.build_int_z_extend(shape_dim, llvm_usize, "").unwrap();
@@ -334,7 +335,7 @@ where
         ctx,
         llvm_usize.const_zero(),
         (ndarray_num_elems, false),
-        |generator, ctx, i| {
+        |generator, ctx, _, i| {
             let elem = unsafe { ndarray.data().ptr_offset_unchecked(ctx, generator, &i, None) };
 
             let value = value_fn(generator, ctx, i)?;
@@ -1193,7 +1194,7 @@ pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
             ctx,
             llvm_usize.const_int(slices.len() as u64, false),
             (this.load_ndims(ctx), false),
-            |generator, ctx, idx| {
+            |generator, ctx, _, idx| {
                 unsafe {
                     let dim_sz = this.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None);
                     ndarray.dim_sizes().set_typed_unchecked(ctx, generator, &idx, dim_sz);
@@ -1366,6 +1367,46 @@ where
     Ok(ndarray)
 }
 
+/// LLVM-typed implementation for iterating through all elements within an `ndarray`.
+///
+/// * `ndarray`: The input [`NDArrayValue`] to iterate through.
+/// * `body`: A lambda containing IR statements that acts on every element within `ndarray`.
+/// It may also implement short-circuiting logic by branching with [`BreakContinueHooks`].
+pub fn ndarray_iter_elem_impl<'ctx, G, BodyFn>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+    body: BodyFn,
+) -> Result<(), String>
+where
+    G: CodeGenerator + ?Sized,
+    BodyFn: FnOnce(
+        &mut G,
+        &mut CodeGenContext<'ctx, '_>,
+        BreakContinueHooks,
+        BasicValueEnum<'ctx>,
+    ) -> Result<(), String>,
+{
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+
+    let ndarray_size =
+        irrt::call_ndarray_calc_size(generator, ctx, &ndarray.dim_sizes(), (None, None));
+
+    gen_for_callback_incrementing(
+        generator,
+        ctx,
+        llvm_usize.const_int(0, false),
+        (ndarray_size, false),
+        |generator, ctx, hooks, idx| {
+            let scalar = unsafe { ndarray.data().get_unchecked(ctx, generator, &idx, None) };
+            body(generator, ctx, hooks, scalar)
+        },
+        llvm_usize.const_int(1, false),
+    )?;
+
+    Ok(())
+}
+
 /// LLVM-typed implementation for computing matrix multiplication between two 2D `ndarray`s.
 ///
 /// * `elem_ty` - The element type of the `NDArray`.
@@ -1597,7 +1638,7 @@ pub fn ndarray_matmul_2d<'ctx, G: CodeGenerator>(
             ctx,
             llvm_i32.const_zero(),
             (common_dim, false),
-            |generator, ctx, i| {
+            |generator, ctx, _, i| {
                 let i = ctx.builder.build_int_truncate(i, llvm_i32, "").unwrap();
 
                 let ab_idx = generator.gen_array_var_alloc(
@@ -1984,3 +2025,136 @@ pub fn gen_ndarray_fill<'ctx>(
 
     Ok(())
 }
+
+/// Used by [`call_ndarray_any_all_impl`]
+#[derive(Debug, Clone, Copy)]
+enum AnyOrAll {
+    /// The numpy function `np.any()`
+    IsAny,
+    /// The numpy function `np.all()`
+    IsAll,
+}
+
+/// Helper function to create `np.any()` and `np.all()`.
+///
+/// Returns a boolean result in the form of an `i8` [`IntValue`].
+///
+/// They are mixed together since they are extremely similar in terms of implementation.
+fn call_ndarray_any_all_impl<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    kind: AnyOrAll,
+    elem_ty: Type,
+    ndarray: NDArrayValue<'ctx>,
+) -> Result<IntValue<'ctx>, String> {
+    /*
+        NOTE: `np.any(<empty ndarray>)` returns false.
+        NOTE: `np.all(<empty ndarray>)` returns true.
+
+        Here is the reference C code of what the implemented LLVM of `np.any()` is essentially doing.
+        ```c
+        // np.any(ndarray)
+        const int8 neutral = 0;
+        const int8 on_hit = 1;
+
+        int8 has_true = neutral;
+        for (size_t index = 0; index < ndarray.size; index++) {
+            Element *elem = ndarray.get(index);
+            bool elem_is_truthy = call_bool(*elem);
+            if (elem_is_truthy) {
+                has_true = on_hit;
+                break; // Short-circuiting for performance
+            }
+        }
+        ```
+    */
+
+    // Name of the function. Used here for creating LLVM labels and names.
+    let fn_name = match kind {
+        AnyOrAll::IsAny => "np_any",
+        AnyOrAll::IsAll => "np_all",
+    };
+
+    let llvm_i8 = ctx.ctx.i8_type();
+
+    let (neutral, on_hit) = match kind {
+        AnyOrAll::IsAny => (0, 1),
+        AnyOrAll::IsAll => (1, 0),
+    };
+
+    // The result of `np.any()`/`np.all()`
+    let result_ptr =
+        ctx.builder.build_alloca(llvm_i8, format!("{fn_name}.result").as_str()).unwrap();
+    ctx.builder.build_store(result_ptr, llvm_i8.const_int(neutral, false)).unwrap();
+
+    ndarray_iter_elem_impl(generator, ctx, ndarray, |generator, ctx, hooks, elem| {
+        // The basic block to go to when...
+        //    - np.any() sees a `true`, then `result` is set from `false` to `true` and short-circuit.
+        //    - np.all() sees a `false`, then `result` is set from `true` to `false` and short-circuit.
+        let on_hit_bb =
+            ctx.ctx.insert_basic_block_after(hooks.break_bb, format!("{fn_name}.on_hit").as_str());
+
+        let elem_is_truthy = call_bool(generator, ctx, (elem_ty, elem)).unwrap().into_int_value();
+        let (on_true, on_false) = match kind {
+            AnyOrAll::IsAny => (on_hit_bb, hooks.continue_bb),
+            AnyOrAll::IsAll => (hooks.continue_bb, on_hit_bb),
+        };
+        ctx.builder.build_conditional_branch(elem_is_truthy, on_true, on_false).unwrap();
+
+        // Begin inserting into `on_hit_bb`
+        ctx.builder.position_at_end(on_hit_bb);
+        ctx.builder.build_store(result_ptr, llvm_i8.const_int(on_hit, false)).unwrap();
+        ctx.builder.build_unconditional_branch(hooks.break_bb).unwrap();
+
+        Ok(())
+    })?;
+
+    // Load `result` and return it
+    let result = ctx.builder.build_load(result_ptr, "result").unwrap();
+    Ok(result.into_int_value())
+}
+
+/// Helper function to generate LLVM IR for `np.any()` and `np.all()`.
+fn gen_ndarray_any_all_helper<'ctx>(
+    kind: AnyOrAll,
+    context: &mut CodeGenContext<'ctx, '_>,
+    obj: &Option<(Type, ValueEnum<'ctx>)>,
+    fun: (&FunSignature, DefinitionId),
+    args: &[(Option<StrRef>, ValueEnum<'ctx>)],
+    generator: &mut dyn CodeGenerator,
+) -> Result<IntValue<'ctx>, String> {
+    assert!(obj.is_none());
+    assert_eq!(args.len(), 1);
+
+    let llvm_usize = generator.get_size_type(context.ctx);
+
+    let in_ty = fun.0.args[0].ty;
+    let (elem_ty, _) = unpack_ndarray_var_tys(&mut context.unifier, in_ty);
+    let in_arg = args[0].1.clone().to_basic_value_enum(context, generator, elem_ty)?;
+
+    let ndarray = NDArrayValue::from_ptr_val(in_arg.into_pointer_value(), llvm_usize, None);
+
+    call_ndarray_any_all_impl(generator, context, kind, elem_ty, ndarray)
+}
+
+/// Generates LLVM IR for `np.any()`.
+pub fn gen_ndarray_any<'ctx>(
+    context: &mut CodeGenContext<'ctx, '_>,
+    obj: &Option<(Type, ValueEnum<'ctx>)>,
+    fun: (&FunSignature, DefinitionId),
+    args: &[(Option<StrRef>, ValueEnum<'ctx>)],
+    generator: &mut dyn CodeGenerator,
+) -> Result<IntValue<'ctx>, String> {
+    gen_ndarray_any_all_helper(AnyOrAll::IsAny, context, obj, fun, args, generator)
+}
+
+/// Generates LLVM IR for `np.all()`.
+pub fn gen_ndarray_all<'ctx>(
+    context: &mut CodeGenContext<'ctx, '_>,
+    obj: &Option<(Type, ValueEnum<'ctx>)>,
+    fun: (&FunSignature, DefinitionId),
+    args: &[(Option<StrRef>, ValueEnum<'ctx>)],
+    generator: &mut dyn CodeGenerator,
+) -> Result<IntValue<'ctx>, String> {
+    gen_ndarray_any_all_helper(AnyOrAll::IsAll, context, obj, fun, args, generator)
+}

nac3core/src/codegen/stmt.rs

@@ -462,6 +462,14 @@ pub fn gen_for<G: CodeGenerator>(
     Ok(())
 }
 
+#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
+pub struct BreakContinueHooks<'ctx> {
+    /// [`BasicBlock`] to branch to for `break`-ing out of the loop.
+    pub break_bb: BasicBlock<'ctx>,
+    /// [`BasicBlock`] to branch to for `continue`-ing to the next iteration in the loop.
+    pub continue_bb: BasicBlock<'ctx>,
+}
+
 /// Generates a C-style `for` construct using lambdas, similar to the following C code:
 ///
 /// ```c
@@ -489,7 +497,8 @@ where
     I: Clone,
     InitFn: FnOnce(&mut G, &mut CodeGenContext<'ctx, 'a>) -> Result<I, String>,
     CondFn: FnOnce(&mut G, &mut CodeGenContext<'ctx, 'a>, I) -> Result<IntValue<'ctx>, String>,
-    BodyFn: FnOnce(&mut G, &mut CodeGenContext<'ctx, 'a>, I) -> Result<(), String>,
+    BodyFn:
+        FnOnce(&mut G, &mut CodeGenContext<'ctx, 'a>, BreakContinueHooks, I) -> Result<(), String>,
     UpdateFn: FnOnce(&mut G, &mut CodeGenContext<'ctx, 'a>, I) -> Result<(), String>,
 {
     let current_bb = ctx.builder.get_insert_block().unwrap();
@@ -520,7 +529,8 @@ where
     }
 
     ctx.builder.position_at_end(body_bb);
-    body(generator, ctx, loop_var.clone())?;
+    let hooks = BreakContinueHooks { break_bb: cont_bb, continue_bb: update_bb };
+    body(generator, ctx, hooks, loop_var.clone())?;
     if !ctx.is_terminated() {
         ctx.builder.build_unconditional_branch(update_bb).unwrap();
     }
@@ -562,7 +572,12 @@ pub fn gen_for_callback_incrementing<'ctx, 'a, G, BodyFn>(
 ) -> Result<(), String>
 where
     G: CodeGenerator + ?Sized,
-    BodyFn: FnOnce(&mut G, &mut CodeGenContext<'ctx, 'a>, IntValue<'ctx>) -> Result<(), String>,
+    BodyFn: FnOnce(
+        &mut G,
+        &mut CodeGenContext<'ctx, 'a>,
+        BreakContinueHooks,
+        IntValue<'ctx>,
+    ) -> Result<(), String>,
 {
     let init_val_t = init_val.get_type();
 
@@ -584,10 +599,10 @@ where
 
             Ok(ctx.builder.build_int_compare(cmp_op, i, max_val, "").unwrap())
         },
-        |generator, ctx, i_addr| {
+        |generator, ctx, hooks, i_addr| {
             let i = ctx.builder.build_load(i_addr, "").map(BasicValueEnum::into_int_value).unwrap();
 
-            body(generator, ctx, i)
+            body(generator, ctx, hooks, i)
         },
         |_, ctx, i_addr| {
             let i = ctx.builder.build_load(i_addr, "").map(BasicValueEnum::into_int_value).unwrap();
@@ -698,7 +713,7 @@ where
 
             Ok(cond)
         },
-        |generator, ctx, (i_addr, _)| {
+        |generator, ctx, _, (i_addr, _)| {
             let i = ctx.builder.build_load(i_addr, "").map(BasicValueEnum::into_int_value).unwrap();
 
             body_fn(generator, ctx, i)

nac3core/src/toplevel/builtins.rs

@@ -497,6 +497,8 @@ impl<'a> BuiltinBuilder<'a> {
 
             PrimDef::FunNpIsNan | PrimDef::FunNpIsInf => self.build_np_float_to_bool_function(prim),
 
+            PrimDef::FunNpAny | PrimDef::FunNpAll => self.build_np_any_all_function(prim),
+
             PrimDef::FunNpSin
             | PrimDef::FunNpCos
             | PrimDef::FunNpTan
@@ -1757,6 +1759,24 @@ impl<'a> BuiltinBuilder<'a> {
         }
     }
 
+    fn build_np_any_all_function(&mut self, prim: PrimDef) -> TopLevelDef {
+        debug_assert_prim_is_allowed(prim, &[PrimDef::FunNpAny, PrimDef::FunNpAll]);
+        let param_ty = &[(self.ndarray_num_ty, "a")];
+        let ret_ty = self.primitives.bool;
+        let var_map = &into_var_map([]);
+        let codegen_callback: Box<GenCallCallback> =
+            Box::new(move |ctx, obj, fun, args, generator| {
+                let func = match prim {
+                    PrimDef::FunNpAny => gen_ndarray_any,
+                    PrimDef::FunNpAll => gen_ndarray_all,
+                    _ => unreachable!(),
+                };
+                func(ctx, &obj, fun, &args, generator).map(|val| Some(val.as_basic_value_enum()))
+            });
+
+        create_fn_by_codegen(self.unifier, var_map, prim.name(), ret_ty, param_ty, codegen_callback)
+    }
+
     fn create_method(prim: PrimDef, method_ty: Type) -> (StrRef, Type, DefinitionId) {
         (prim.simple_name().into(), method_ty, prim.id())
     }

nac3core/src/toplevel/helper.rs

@@ -100,6 +100,8 @@ pub enum PrimDef {
     FunNpHypot,
     FunNpNextAfter,
     FunSome,
+    FunNpAny,
+    FunNpAll,
 }
 
 /// Associated details of a [`PrimDef`]
@@ -251,6 +253,8 @@ impl PrimDef {
             PrimDef::FunNpHypot => fun("np_hypot", None),
             PrimDef::FunNpNextAfter => fun("np_nextafter", None),
             PrimDef::FunSome => fun("Some", None),
+            PrimDef::FunNpAny => fun("np_any", None),
+            PrimDef::FunNpAll => fun("np_all", None),
         }
     }
 }

nac3standalone/demo/interpret_demo.py

@@ -226,6 +226,8 @@ def patch(module):
     module.np_full = np.full
     module.np_eye = np.eye
     module.np_identity = np.identity
+    module.np_any = np.any
+    module.np_all = np.all
 
 def file_import(filename, prefix="file_import_"):
     filename = pathlib.Path(filename)

nac3standalone/demo/src/ndarray.py

@@ -1388,6 +1388,48 @@ def test_ndarray_nextafter_broadcast_rhs_scalar():
     output_ndarray_float_2(nextafter_x_zeros)
     output_ndarray_float_2(nextafter_x_ones)
 
+def test_ndarray_any():
+    x1 = np_identity(5)
+    y1 = np_any(x1)
+    output_ndarray_float_2(x1)
+    output_bool(y1)
+
+    x2 = np_identity(1)
+    y2 = np_any(x2)
+    output_ndarray_float_2(x2)
+    output_bool(y2)
+
+    x3 = np_array([[1.0, 2.0], [3.0, 4.0]])
+    y3 = np_any(x3)
+    output_ndarray_float_2(x3)
+    output_bool(y3)
+
+    x4 = np_zeros([3, 5])
+    y4 = np_any(x4)
+    output_ndarray_float_2(x4)
+    output_bool(y4)
+
+def test_ndarray_all():
+    x1 = np_identity(5)
+    y1 = np_all(x1)
+    output_ndarray_float_2(x1)
+    output_bool(y1)
+
+    x2 = np_identity(1)
+    y2 = np_all(x2)
+    output_ndarray_float_2(x2)
+    output_bool(y2)
+
+    x3 = np_array([[1.0, 2.0], [3.0, 4.0]])
+    y3 = np_all(x3)
+    output_ndarray_float_2(x3)
+    output_bool(y3)
+
+    x4 = np_zeros([3, 5])
+    y4 = np_all(x4)
+    output_ndarray_float_2(x4)
+    output_bool(y4)
+
 def run() -> int32:
     test_ndarray_ctor()
     test_ndarray_empty()
@@ -1565,4 +1607,7 @@ def run() -> int32:
     test_ndarray_nextafter_broadcast_lhs_scalar()
     test_ndarray_nextafter_broadcast_rhs_scalar()
 
+    test_ndarray_any()
+    test_ndarray_all()
+
     return 0