@@ -2774,0 +2872,4 @@
+            // Immediately begin iterating through the ndarray
+            ctx.builder.build_unconditional_branch(step_bb).unwrap();
+
+            // ##### Inserting into `step_bb` #####

@@ -1760,0 +1763,4 @@
+        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([self.ndarray_dtype_tvar, self.ndarray_ndims_tvar]);

@@ -2773,1 +2773,4 @@
 }
+
+/// Check if a [`Type`] is an ndarray.
+fn is_type_ndarray(ctx: &mut CodeGenContext<'_, '_>, ty: Type) -> bool {

@@ -2774,0 +2787,4 @@
+/// Helper function to create `np.any()` and `np.all()`.
+///
+/// They are mixed together since they are extremely similar in terms of implementation.
+fn helper_call_numpy_any_all<'ctx, G: CodeGenerator + ?Sized>(

@@ -2774,0 +2790,4 @@
+fn helper_call_numpy_any_all<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    kind: AnyOrAll,

@@ -2774,0 +2811,4 @@
+            /*
+                NOTE: `np.any(<empty ndarray>)` returns true.
+                NOTE: `np.all(<empty ndarray>)` returns false.
+

@@ -2774,0 +2835,4 @@
+            let llvm_i8 = ctx.ctx.i8_type();
+            let llvm_usize = generator.get_size_type(ctx.ctx);
+
+            let current_bb = ctx.builder.get_insert_block().unwrap();

@@ -1987,0 +1990,4 @@
+///
+/// * `ndarray`: The input ndarray [`NDArrayValue`]
+/// * `body_fn`: A lambda containing IR statements that acts on every scalar element within `ndarray`.
+pub fn gen_ndarray_iter_scalar_callback<'ctx, G, BodyFn>(

@@ -462,6 +462,14 @@ pub fn gen_for<G: CodeGenerator>(
     Ok(())
 }
 
+#[derive(Debug, Clone, Copy)]