fix(tests): keep aggregate torch op tests active

Author: voltjia

scripts/generate_torch_ops.py

@@ -781,6 +781,9 @@ def _default_call_value(param: Param) -> str:
     if param.aten_type in _NULLOPT_BY_TYPE:
         return _NULLOPT_BY_TYPE[param.aten_type]
 
+    if param.default is not None:
+        return _translate_default(param)
+
     return param.hidden_value()
 
 
@@ -1144,6 +1147,8 @@ def _generate_torch_header(name: str, ops: list[Op]) -> str:
 def _generate_torch_method_source(name: str, op: Op) -> str:
     op_type = _op_cpp_type(name)
     conversion_lines = []
+    out_device_index = f"{op.out_params[0].api_name}.device().index()"
+    conversion_lines.append(f"  const auto device_index = {out_device_index};")
 
     def _optional_aten_type(param: Param) -> str:
         return _NULLOPT_BY_TYPE[param.aten_type].removesuffix("{}")
@@ -1157,7 +1162,7 @@ def _optional_aten_value(schema_param: Param, api_param: Param) -> str:
             return (
                 f"ToAtenTensor<kDev>({data_expr}, {api_name}->shape(), "
                 f"{api_name}->strides(), {api_name}->dtype(), "
-                f"device_index_)"
+                f"device_index)"
             )
 
         if schema_param.aten_type == "Scalar?":
@@ -1211,7 +1216,7 @@ def _append_optional_conversion(schema_param: Param, api_param: Param) -> None:
         conversion_lines.append(
             f"  auto at_{param.name} = ToAtenTensor<kDev>(\n"
             f"      {data_expr}, {api_name}_shape_, {api_name}_strides_,\n"
-            f"      {api_name}_type_, device_index_);"
+            f"      {api_name}_type_, device_index);"
         )
 
     for schema_index, param in enumerate(op.params):

scripts/torch_ops.yaml

@@ -499,6 +499,7 @@
 - _upsample_nearest_exact2d_backward
 - _upsample_nearest_exact3d
 - _upsample_nearest_exact3d_backward
+- add
 - add_
 - argsort
 - bernoulli_
@@ -527,6 +528,7 @@
 - less_equal_
 - lt_
 - masked_fill_
+- mul
 - mul_
 - multiply_
 - ne_

tests/conftest.py

@@ -120,6 +120,9 @@ def skip_op_without_platform_impl(request):
     op_cls = _op_class_from_module(request.node.module)
 
     if op_cls is None:
+        if "op_meta" in params:
+            return
+
         pytest.skip("operator wrapper is not available in this build")
 
     if not hasattr(op_cls, "active_implementation_indices"):

tests/test_generate_torch_ops.py

@@ -165,6 +165,30 @@ def test_existing_base_overload_can_omit_optional_schema_params():
     assert "at::slow_conv3d_out" in source
 
 
+def test_existing_base_overload_can_omit_defaulted_schema_params():
+    module = _load_generator_module()
+    op = module._parse_func(
+        "add.Tensor(Tensor self, Tensor other, *, Scalar alpha=1, "
+        "Tensor(a!) out) -> Tensor(a!)"
+    )
+    signature = [
+        ("const Tensor", "input"),
+        ("const Tensor", "other"),
+        ("Tensor", "out"),
+    ]
+
+    bound = module._bind_base_signature(op, signature)
+
+    assert bound is not None
+
+    source = module._generate_torch_method_source("add", bound)
+
+    assert "double alpha" not in source
+    assert "const auto device_index = out.device().index();" in source
+    assert "device_index_)" not in source
+    assert "at::add_out(at_out, at_self, at_other, 1)" in source
+
+
 def test_existing_base_overload_matches_by_name_when_types_repeat():
     module = _load_generator_module()
     op = module._parse_func(