feat[next]: Extend astype to work with tuples

src/gt4py/next/ffront/fbuiltins.py

@@ -196,7 +196,11 @@ def where(
 
 
 @builtin_function
-def astype(field: Field | gt4py_defs.ScalarT, type_: type, /) -> Field:
+def astype(
+    field: Field | gt4py_defs.ScalarT | Tuple[Field, ...],
+    type_: type,
+    /,
+) -> Field | Tuple[Field, ...]:
     raise NotImplementedError()
 
 

src/gt4py/next/ffront/foast_passes/type_deduction.py

@@ -823,10 +823,12 @@ def _visit_min_over(self, node: foast.Call, **kwargs) -> foast.Call:
         return self._visit_reduction(node, **kwargs)
 
     def _visit_astype(self, node: foast.Call, **kwargs) -> foast.Call:
+        return_type: ts.TupleType | ts.ScalarType | ts.FieldType
         value, new_type = node.args
         assert isinstance(
-            value.type, (ts.FieldType, ts.ScalarType)
+            value.type, (ts.FieldType, ts.ScalarType, ts.TupleType)
         )  # already checked using generic mechanism
+
         if not isinstance(new_type, foast.Name) or new_type.id.upper() not in [
             kind.name for kind in ts.ScalarKind
         ]:
@@ -835,8 +837,11 @@ def _visit_astype(self, node: foast.Call, **kwargs) -> foast.Call:
                 f"Invalid call to `astype`. Second argument must be a scalar type, but got {new_type}.",
             )
 
-        return_type = with_altered_scalar_kind(
-            value.type, getattr(ts.ScalarKind, new_type.id.upper())
+        return_type = type_info.apply_to_primitive_constituents(
+            value.type,
+            lambda primitive_type: with_altered_scalar_kind(
+                primitive_type, getattr(ts.ScalarKind, new_type.id.upper())
+            ),
         )
 
         return foast.Call(

src/gt4py/next/ffront/foast_to_itir.py

@@ -317,12 +317,9 @@ def visit_Call(self, node: foast.Call, **kwargs) -> itir.Expr:
 
     def _visit_astype(self, node: foast.Call, **kwargs) -> itir.FunCall:
         assert len(node.args) == 2 and isinstance(node.args[1], foast.Name)
-        obj, dtype = node.args[0], node.args[1].id
-
-        # TODO check that we test astype that results in a itir.map_ operation
-        return self._map(
-            im.lambda_("it")(im.call("cast_")("it", str(dtype))),
-            obj,
+        obj, new_type = node.args[0], node.args[1].id
+        return self._process_elements(
+            lambda x: im.call("cast_")(x, str(new_type)), obj, obj.type, **kwargs
         )
 
     def _visit_where(self, node: foast.Call, **kwargs) -> itir.FunCall:
@@ -403,6 +400,32 @@ def _map(self, op, *args, **kwargs):
 
         return im.promote_to_lifted_stencil(im.call(op))(*lowered_args)
 
+    def _process_elements(
+        self,
+        process_func: Callable[[itir.Expr], itir.Expr],
+        obj: foast.Expr,
+        current_el_type: ts.TypeSpec,
+        current_el_expr: itir.Expr = im.ref("expr"),
+    ):
+        """Recursively applies a processing function to all primitive constituents of a tuple."""
+        if isinstance(current_el_type, ts.TupleType):
+            # TODO(ninaburg): Refactor to avoid duplicating lowered obj expression for each tuple element.
+            return im.promote_to_lifted_stencil(lambda *elts: im.make_tuple(*elts))(
+                *[
+                    self._process_elements(
+                        process_func,
+                        obj,
+                        current_el_type.types[i],
+                        im.tuple_get(i, current_el_expr),
+                    )
+                    for i in range(len(current_el_type.types))
+                ]
+            )
+        elif type_info.contains_local_field(current_el_type):
+            raise NotImplementedError("Processing fields with local dimension is not implemented.")
+        else:
+            return self._map(im.lambda_("expr")(process_func(current_el_expr)), obj)
+
 
 class FieldOperatorLoweringError(Exception):
     ...

tests/next_tests/integration_tests/feature_tests/ffront_tests/test_execution.py

@@ -325,6 +325,76 @@ def testee(a: cases.IFloatField) -> gtx.Field[[IDim], int64]:
     )
 
 
+@pytest.mark.uses_tuple_returns
+def test_astype_on_tuples(cartesian_case):  # noqa: F811 # fixtures
+    @gtx.field_operator
+    def field_op_returning_a_tuple(
+        a: cases.IFloatField, b: cases.IFloatField
+    ) -> tuple[gtx.Field[[IDim], float], gtx.Field[[IDim], float]]:
+        tup = (a, b)
+        return tup
+
+    @gtx.field_operator
+    def cast_tuple(
+        a: cases.IFloatField,
+        b: cases.IFloatField,
+        a_casted_to_int_outside_of_gt4py: cases.IField,
+        b_casted_to_int_outside_of_gt4py: cases.IField,
+    ) -> tuple[gtx.Field[[IDim], bool], gtx.Field[[IDim], bool]]:
+        result = astype(field_op_returning_a_tuple(a, b), int32)
+        return (
+            result[0] == a_casted_to_int_outside_of_gt4py,
+            result[1] == b_casted_to_int_outside_of_gt4py,
+        )
+
+    @gtx.field_operator
+    def cast_nested_tuple(
+        a: cases.IFloatField,
+        b: cases.IFloatField,
+        a_casted_to_int_outside_of_gt4py: cases.IField,
+        b_casted_to_int_outside_of_gt4py: cases.IField,
+    ) -> tuple[gtx.Field[[IDim], bool], gtx.Field[[IDim], bool], gtx.Field[[IDim], bool]]:
+        result = astype((a, field_op_returning_a_tuple(a, b)), int32)
+        return (
+            result[0] == a_casted_to_int_outside_of_gt4py,
+            result[1][0] == a_casted_to_int_outside_of_gt4py,
+            result[1][1] == b_casted_to_int_outside_of_gt4py,
+        )
+
+    a = cases.allocate(cartesian_case, cast_tuple, "a")()
+    b = cases.allocate(cartesian_case, cast_tuple, "b")()
+    a_casted_to_int_outside_of_gt4py = gtx.np_as_located_field(IDim)(np.asarray(a).astype(int32))
+    b_casted_to_int_outside_of_gt4py = gtx.np_as_located_field(IDim)(np.asarray(b).astype(int32))
+    out_tuple = cases.allocate(cartesian_case, cast_tuple, cases.RETURN)()
+    out_nested_tuple = cases.allocate(cartesian_case, cast_nested_tuple, cases.RETURN)()
+
+    cases.verify(
+        cartesian_case,
+        cast_tuple,
+        a,
+        b,
+        a_casted_to_int_outside_of_gt4py,
+        b_casted_to_int_outside_of_gt4py,
+        out=out_tuple,
+        ref=(np.full_like(a, True, dtype=bool), np.full_like(b, True, dtype=bool)),
+    )
+
+    cases.verify(
+        cartesian_case,
+        cast_nested_tuple,
+        a,
+        b,
+        a_casted_to_int_outside_of_gt4py,
+        b_casted_to_int_outside_of_gt4py,
+        out=out_nested_tuple,
+        ref=(
+            np.full_like(a, True, dtype=bool),
+            np.full_like(a, True, dtype=bool),
+            np.full_like(b, True, dtype=bool),
+        ),
+    )
+
+
 def test_astype_bool_field(cartesian_case):  # noqa: F811 # fixtures
     @gtx.field_operator
     def testee(a: cases.IFloatField) -> gtx.Field[[IDim], bool]:

tests/next_tests/integration_tests/feature_tests/ffront_tests/test_type_deduction.py

@@ -785,8 +785,8 @@ def simple_astype(a: Field[[TDim], float64]):
 
 def test_astype_wrong_value_type():
     def simple_astype(a: Field[[TDim], float64]):
-        # we just use a tuple here but anything that is not a field or scalar works
-        return astype((1, 2), bool)
+        # we just use broadcast here but anything that is not a field, scalar or tuple thereof works
+        return astype(broadcast, bool)
 
     with pytest.raises(errors.DSLError) as exc_info:
         _ = FieldOperatorParser.apply_to_function(simple_astype)