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core/typecheck: Inferencer allow heterogenerous assignemnt

This commit is contained in:
lyken 2024-07-30 16:15:16 +08:00
parent e4f6adb1ec
commit 3d8240259c
1 changed files with 55 additions and 1 deletions
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56
nac3core/src/typecheck/type_inferencer/mod.rs
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@ -389,7 +389,7 @@ impl<'a> Fold<()> for Inferencer<'a> {
}
ast::StmtKind::Assign { targets, value, .. } => {
for target in targets {
self.unify(target.custom.unwrap(), value.custom.unwrap(), &target.location)?;
self.fold_assign(target, value)?;
}
}
ast::StmtKind::Raise { exc, cause, .. } => {
@ -2159,4 +2159,58 @@ impl<'a> Inferencer<'a> {
self.constrain(body.custom.unwrap(), orelse.custom.unwrap(), &body.location)?;
Ok(body.custom.unwrap())
}
fn fold_assign(
&mut self,
target: &ast::Expr<Option<Type>>,
value: &ast::Expr<Option<Type>>,
) -> Result<(), HashSet<String>> {
let target_ty = target.custom.unwrap();
let value_ty = value.custom.unwrap();
match (&target.node, &*self.unifier.get_ty(target_ty)) {
(ExprKind::Subscript { .. }, TypeEnum::TObj { obj_id: target_obj_id, .. })
if *target_obj_id == self.primitives.ndarray.obj_id(self.unifier).unwrap() =>
{
// Pattern match expressions like `my_ndarray[slices] = value`.
// TODO: `(my_ndarray[slices1], my_ndarray[slices2]) = (value1, value2)` are not supported for now.
// Suppose `my_ndarray` has type `ndarray[target_dtype, ndims]`
// value's type could be one of the following:
// Case 1. `target_dtype`
// Case 2. `ndarray[target_dtype, ?]`
// Case 3. list, tuple, iterables (TODO: NOT IMPLEMENTED)
let (target_dtype, _) = unpack_ndarray_var_tys(self.unifier, target_ty);
// Typecheck `value_ty`
match &*self.unifier.get_ty(value_ty) {
TypeEnum::TObj { obj_id: value_obj_id, .. }
if *value_obj_id
== self.primitives.ndarray.obj_id(self.unifier).unwrap() =>
{
// Case 2
// - `dtype` of `target_ty` and `value_ty` must unify.
// - `ndims` of `value_ty` is ignored.
let (value_dtype, _) = unpack_ndarray_var_tys(self.unifier, value_ty);
self.unify(target_dtype, value_dtype, &target.location)?;
}
_ => {
// If `value_ty` is not an ndarray, simply typecheck as through it has to be Case 1.
self.unify(target_dtype, value_ty, &target.location)?;
}
}
}
_ => {
// To handle
// - variable assignments `target = value`
// - and attribute assignments `target.my_attr = value`
//
// For these cases in nac3core, types of LHS and RHS must unify
self.unify(target_ty, value_ty, &target.location)?;
}
}
Ok(())
}
}