core/ndstrides: refactoring builtin_fns

nac3core/src/codegen/model/util.rs

@@ -27,14 +27,14 @@ pub fn call_memcpy_model<'ctx, Item: Model<'ctx> + Default, G: CodeGenerator + ?
 
 /// Like [`gen_for_callback_incrementing`] with [`Model`] abstractions.
 /// The [`IntKind`] is automatically inferred.
-pub fn gen_for_model_auto<'ctx, 'a, G, F, I>(
+pub fn gen_for_model_auto<'ctx, 'a, G, F, I, R>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, 'a>,
     start: Int<'ctx, I>,
     stop: Int<'ctx, I>,
     step: Int<'ctx, I>,
     body: F,
-) -> Result<(), String>
+) -> Result<R, String>
 where
     G: CodeGenerator + ?Sized,
     F: FnOnce(
@@ -42,7 +42,7 @@ where
         &mut CodeGenContext<'ctx, 'a>,
         BreakContinueHooks<'ctx>,
         Int<'ctx, I>,
-    ) -> Result<(), String>,
+    ) -> Result<R, String>,
     I: IntKind<'ctx> + Default,
 {
     let int_model = IntModel(I::default());

nac3core/src/codegen/structure/ndarray/mapping.rs

@@ -1,4 +1,3 @@
-use inkwell::values::BasicValueEnum;
 use itertools::Itertools;
 use util::gen_for_model_auto;
 
@@ -19,7 +18,6 @@ pub fn starmap_scalars_array_like<'ctx, 'a, F, G>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, 'a>,
     inputs: &Vec<ScalarOrNDArray<'ctx>>,
-    ret_dtype: Type,
     mapping: F,
 ) -> Result<ScalarOrNDArray<'ctx>, String>
 where
@@ -28,7 +26,7 @@ where
         &mut CodeGenContext<'ctx, 'a>,
         Int<'ctx, SizeT>,
         &Vec<ScalarObject<'ctx>>,
-    ) -> Result<BasicValueEnum<'ctx>, String>,
+    ) -> Result<ScalarObject<'ctx>, String>,
     G: CodeGenerator + ?Sized,
 {
     assert!(!inputs.is_empty());
@@ -44,9 +42,9 @@ where
             // When inputs are all scalars, return a ScalarObject back
 
             let i = sizet_model.const_0(generator, ctx.ctx);
-            let ret = mapping(generator, ctx, i, &scalars)?;
 
-            Ok(ScalarOrNDArray::Scalar(ScalarObject { value: ret, dtype: ret_dtype }))
+            let scalar = mapping(generator, ctx, i, &scalars)?;
+            Ok(ScalarOrNDArray::Scalar(scalar))
         }
         None => {
             // When not all inputs are scalars, promote all non-ndarray inputs
@@ -57,22 +55,12 @@ where
 
             let broadcast_result = broadcast_all_ndarrays(generator, ctx, &ndarrays);
 
-            let mapped_ndarray = NDArrayObject::alloca_uninitialized(
-                generator,
-                ctx,
-                ret_dtype,
-                broadcast_result.ndims,
-                "mapped_ndarray",
-            );
-            mapped_ndarray.copy_shape_from_array(generator, ctx, broadcast_result.shape);
-            mapped_ndarray.create_data(generator, ctx);
-
             let start = sizet_model.const_0(generator, ctx.ctx);
-            let stop = mapped_ndarray.size(generator, ctx);
+            let stop = broadcast_result.ndarrays[0].size(generator, ctx); // They all should have the same `np.size`.
             let step = sizet_model.const_1(generator, ctx.ctx);
 
             // Map element-wise and store results into `mapped_ndarray`.
-            gen_for_model_auto(
+            let mapped_ndarray = gen_for_model_auto(
                 generator,
                 ctx,
                 start,
@@ -89,12 +77,26 @@ where
                         .collect_vec();
 
                     let ret = mapping(generator, ctx, i, &elements)?;
+
+                    // It might look weird but it is perfectly fine putting the allocation codegen
+                    // here within `for`.
+                    // The reason for doing this is to get the `dtype` out of `ret`, which is only
+                    // available after running `mapping`.
+                    let mapped_ndarray = NDArrayObject::alloca_uninitialized(
+                        generator,
+                        ctx,
+                        ret.dtype,
+                        broadcast_result.ndims,
+                        "mapped_ndarray",
+                    );
+                    mapped_ndarray.copy_shape_from_array(generator, ctx, broadcast_result.shape);
+                    mapped_ndarray.create_data(generator, ctx);
+
                     let pret = mapped_ndarray.get_nth_pelement(generator, ctx, i, "pret");
-                    ctx.builder.build_store(pret, ret).unwrap();
-                    Ok(())
+                    ctx.builder.build_store(pret, ret.value).unwrap();
+                    Ok(mapped_ndarray)
                 },
             )?;
-
             Ok(ScalarOrNDArray::NDArray(mapped_ndarray))
         }
     }
@@ -105,7 +107,6 @@ impl<'ctx> ScalarObject<'ctx> {
         &self,
         generator: &mut G,
         ctx: &mut CodeGenContext<'ctx, 'a>,
-        ret_dtype: Type,
         mapping: F,
     ) -> Result<Self, String>
     where
@@ -114,14 +115,13 @@ impl<'ctx> ScalarObject<'ctx> {
             &mut CodeGenContext<'ctx, 'a>,
             Int<'ctx, SizeT>,
             ScalarObject<'ctx>,
-        ) -> Result<BasicValueEnum<'ctx>, String>,
+        ) -> Result<ScalarObject<'ctx>, String>,
         G: CodeGenerator + ?Sized,
     {
         let ScalarOrNDArray::Scalar(ret) = starmap_scalars_array_like(
             generator,
             ctx,
             &vec![ScalarOrNDArray::Scalar(*self)],
-            ret_dtype,
             |generator, ctx, i, scalars| mapping(generator, ctx, i, scalars[0]),
         )?
         else {
@@ -136,7 +136,6 @@ impl<'ctx> NDArrayObject<'ctx> {
         &self,
         generator: &mut G,
         ctx: &mut CodeGenContext<'ctx, 'a>,
-        ret_dtype: Type,
         mapping: F,
     ) -> Result<Self, String>
     where
@@ -145,14 +144,13 @@ impl<'ctx> NDArrayObject<'ctx> {
             &mut CodeGenContext<'ctx, 'a>,
             Int<'ctx, SizeT>,
             ScalarObject<'ctx>,
-        ) -> Result<BasicValueEnum<'ctx>, String>,
+        ) -> Result<ScalarObject<'ctx>, String>,
         G: CodeGenerator + ?Sized,
     {
         let ScalarOrNDArray::NDArray(ret) = starmap_scalars_array_like(
             generator,
             ctx,
             &vec![ScalarOrNDArray::NDArray(*self)],
-            ret_dtype,
             |generator, ctx, i, scalars| mapping(generator, ctx, i, scalars[0]),
         )?
         else {
@@ -176,15 +174,18 @@ impl<'ctx> ScalarOrNDArray<'ctx> {
             &mut CodeGenContext<'ctx, 'a>,
             Int<'ctx, SizeT>,
             ScalarObject<'ctx>,
-        ) -> Result<BasicValueEnum<'ctx>, String>,
+        ) -> Result<ScalarObject<'ctx>, String>,
         G: CodeGenerator + ?Sized,
     {
         match self {
-            ScalarOrNDArray::Scalar(scalar) => {
-                scalar.map(generator, ctx, ret_dtype, mapping).map(ScalarOrNDArray::Scalar)
-            }
+            ScalarOrNDArray::Scalar(scalar) => starmap_scalars_array_like(
+                generator,
+                ctx,
+                &vec![ScalarOrNDArray::Scalar(*scalar)],
+                |generator, ctx, i, scalars| mapping(generator, ctx, i, scalars[0]),
+            ),
             ScalarOrNDArray::NDArray(ndarray) => {
-                ndarray.map(generator, ctx, ret_dtype, mapping).map(ScalarOrNDArray::NDArray)
+                ndarray.map(generator, ctx, mapping).map(ScalarOrNDArray::NDArray)
             }
         }
     }

nac3core/src/toplevel/builtins.rs

@@ -1180,7 +1180,7 @@ impl<'a> BuiltinBuilder<'a> {
                 let ret_elem_ty = size_variant.of_int(&ctx.primitives);
                 let func = match kind {
                     Kind::Ceil => builtin_fns::call_ceil,
-                    Kind::Floor => builtin_fns::call_floor,
+                    Kind::Floor => builtin_fns::call_ceil_or_floor,
                 };
                 Ok(Some(func(generator, ctx, (arg_ty, arg), ret_elem_ty)?))
             }),
@@ -1548,7 +1548,7 @@ impl<'a> BuiltinBuilder<'a> {
 
                 let func = match prim {
                     PrimDef::FunNpCeil => builtin_fns::call_ceil,
-                    PrimDef::FunNpFloor => builtin_fns::call_floor,
+                    PrimDef::FunNpFloor => builtin_fns::call_ceil_or_floor,
                     _ => unreachable!(),
                 };
                 Ok(Some(func(generator, ctx, (arg_ty, arg), ctx.primitives.float)?))

nac3core/src/typecheck/typedef/mod.rs

@@ -336,6 +336,14 @@ impl Unifier {
         self.unification_table.unioned(a, b)
     }
 
+    /// Determine if a type unions with a type in `tys`.
+    pub fn unioned_any<I>(&mut self, a: Type, tys: I) -> bool
+    where
+        I: IntoIterator<Item = Type>,
+    {
+        tys.into_iter().any(|ty| self.unioned(a, ty))
+    }
+
     pub fn from_shared_unifier(unifier: &SharedUnifier) -> Unifier {
         let lock = unifier.lock().unwrap();
         Unifier {