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Fix classmethod override argument passing. #47114

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Fix classmethod override argument passing. #47114

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912d8ae
Fix classmethod override argument passing.
hameerabbasi Oct 30, 2020
e0ffce1
Fix copypasta typo.
hameerabbasi Nov 2, 2020
178b1c5
Merge branch 'master' into fix-overrides-classmethods
ezyang Nov 3, 2020
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7 changes: 7 additions & 0 deletions test/test_overrides.py
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Expand Up @@ -822,5 +822,12 @@ def test_gradcheck(self):
})


class TestGradNewOnesOverride(TestCase):
""" Regression test for gh-47069 """
def test_newones(self):
t = torch.tensor([1, 2]).as_subclass(SubTensor2)
n = t.new_ones((1, 2))
self.assertEqual(type(n), SubTensor2)

if __name__ == '__main__':
unittest.main()
36 changes: 18 additions & 18 deletions tools/autograd/templates/python_variable_methods.cpp
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Expand Up @@ -50,7 +50,7 @@ static PyObject * THPVariable__is_view(PyObject *self, PyObject* args)
{
HANDLE_TH_ERRORS
if (check_has_torch_function(self)) {
return handle_torch_function(self, "_is_view");
return handle_torch_function(self, "_is_view", args);
}
auto& self_ = reinterpret_cast<THPVariable*>(self)->cdata;
if (self_.is_view()) {
Expand Down Expand Up @@ -154,7 +154,7 @@ static PyObject * THPVariable_get_device(PyObject* self_, PyObject* args)
{
HANDLE_TH_ERRORS
if (check_has_torch_function(self_)) {
return handle_torch_function(self_, "get_device");
return handle_torch_function(self_, "get_device", args, nullptr);
}
auto& self = reinterpret_cast<THPVariable*>(self_)->cdata;
return wrap(self.get_device());
Expand All @@ -165,7 +165,7 @@ static PyObject * THPVariable_has_names(PyObject* self_, PyObject* args)
{
HANDLE_TH_ERRORS
if (check_has_torch_function(self_)) {
return handle_torch_function(self_, "has_names");
return handle_torch_function(self_, "has_names", args);
}
auto& self = reinterpret_cast<THPVariable*>(self_)->cdata;
return wrap(self.has_names());
Expand All @@ -177,7 +177,7 @@ static PyObject * THPVariable_data_ptr(PyObject* self_, PyObject* args)
{
HANDLE_TH_ERRORS
if (check_has_torch_function(self_)) {
return handle_torch_function(self_, "data_ptr");
return handle_torch_function(self_, "data_ptr", args);
}
auto& self = reinterpret_cast<THPVariable*>(self_)->cdata;
return wrap(self.data_ptr());
Expand All @@ -201,7 +201,7 @@ static PyObject * THPVariable_dim(PyObject* self, PyObject* args)
{
HANDLE_TH_ERRORS
if (check_has_torch_function(self)) {
return handle_torch_function(self, "dim");
return handle_torch_function(self, "dim", args);
}
auto& self_ = reinterpret_cast<THPVariable*>(self)->cdata;
return THPUtils_packInt64(self_.dim());
Expand All @@ -213,7 +213,7 @@ static PyObject * THPVariable_numel(PyObject* self, PyObject* args)
{
HANDLE_TH_ERRORS
if (check_has_torch_function(self)) {
return handle_torch_function(self, "numel");
return handle_torch_function(self, "numel", args);
}
auto& self_ = reinterpret_cast<THPVariable*>(self)->cdata;
return THPUtils_packInt64(self_.numel());
Expand Down Expand Up @@ -327,7 +327,7 @@ static bool dispatch_to_Bool(const Tensor & self) {
static PyObject * THPVariable_float_scalar(PyObject* self, PyObject* args) {
HANDLE_TH_ERRORS
if (check_has_torch_function(self)) {
return handle_torch_function(self, "__float__");
return handle_torch_function(self, "__float__", args);
}
jit::tracer::warn("Converting a tensor to a Python float", jit::tracer::WARN_PYTHON_DATAFLOW);
auto& self_ = reinterpret_cast<THPVariable*>(self)->cdata;
Expand All @@ -338,7 +338,7 @@ static PyObject * THPVariable_float_scalar(PyObject* self, PyObject* args) {
static PyObject * THPVariable_complex_scalar(PyObject* self, PyObject* args) {
HANDLE_TH_ERRORS
if (check_has_torch_function(self)) {
return handle_torch_function(self, "__complex__");
return handle_torch_function(self, "__complex__", args);
}
jit::tracer::warn("Converting a tensor to a Python complex", jit::tracer::WARN_PYTHON_DATAFLOW);
auto& self_ = reinterpret_cast<THPVariable*>(self)->cdata;
Expand All @@ -349,7 +349,7 @@ static PyObject * THPVariable_complex_scalar(PyObject* self, PyObject* args) {
static PyObject * THPVariable_integral_scalar(PyObject* self, PyObject* args) {
HANDLE_TH_ERRORS
if (check_has_torch_function(self)) {
return handle_torch_function(self, "__int__");
return handle_torch_function(self, "__int__", args);
}
jit::tracer::warn("Converting a tensor to a Python integer", jit::tracer::WARN_PYTHON_DATAFLOW);
auto& self_ = reinterpret_cast<THPVariable*>(self)->cdata;
Expand All @@ -368,7 +368,7 @@ static PyObject * THPVariable_integral_scalar(PyObject* self, PyObject* args) {
static PyObject * THPVariable_index_scalar(PyObject* self, PyObject* args) {
HANDLE_TH_ERRORS
if (check_has_torch_function(self)) {
return handle_torch_function(self, "__index__");
return handle_torch_function(self, "__index__", args);
}
jit::tracer::warn("Converting a tensor to a Python index", jit::tracer::WARN_PYTHON_DATAFLOW);
auto& self_ = reinterpret_cast<THPVariable*>(self)->cdata;
Expand All @@ -390,7 +390,7 @@ static Tensor dispatch_invert(const Tensor & self) {
static PyObject * THPVariable_invert(PyObject* self, PyObject* args) {
HANDLE_TH_ERRORS
if (check_has_torch_function(self)) {
return handle_torch_function(self, "__invert__");
return handle_torch_function(self, "__invert__", args);
}
auto& self_ = reinterpret_cast<THPVariable*>(self)->cdata;
if (!isIntegralType(self_.scalar_type(), /*includeBool=*/true)) {
Expand Down Expand Up @@ -685,7 +685,7 @@ static PyObject * THPVariable_element_size(PyObject* self, PyObject* args)
{
HANDLE_TH_ERRORS
if (check_has_torch_function(self)) {
return handle_torch_function(self, "element_size");
return handle_torch_function(self, "element_size", args);
}
auto& self_ = reinterpret_cast<THPVariable*>(self)->cdata;
return THPUtils_packInt64(self_.element_size());
Expand Down Expand Up @@ -763,7 +763,7 @@ static PyObject * THPVariable_item(PyObject* self, PyObject* args)
{
HANDLE_TH_ERRORS
if (check_has_torch_function(self)) {
return handle_torch_function(self, "item");
return handle_torch_function(self, "item", args);
}
jit::tracer::warn("Converting a tensor to a Python number", jit::tracer::WARN_PYTHON_DATAFLOW);
auto& self_ = reinterpret_cast<THPVariable*>(self)->cdata;
Expand Down Expand Up @@ -832,7 +832,7 @@ static PyObject * THPVariable_new(PyObject* self, PyObject* args, PyObject* kwar
{
HANDLE_TH_ERRORS
if (check_has_torch_function(self)) {
return handle_torch_function(self, "new");
return handle_torch_function(self, "new", args, kwargs);
}
auto& self_ = reinterpret_cast<THPVariable*>(self)->cdata;
OptionalDeviceGuard device_guard(device_of(self_));
Expand All @@ -844,7 +844,7 @@ static PyObject * THPVariable_new_ones(PyObject* self, PyObject* args, PyObject*
{
HANDLE_TH_ERRORS
if (check_has_torch_function(self)) {
return handle_torch_function(self, "new_ones");
return handle_torch_function(self, "new_ones", args, kwargs);
}
auto& self_ = reinterpret_cast<THPVariable*>(self)->cdata;
OptionalDeviceGuard device_guard(device_of(self_));
Expand All @@ -856,7 +856,7 @@ static PyObject * THPVariable_new_tensor(PyObject* self, PyObject* args, PyObjec
{
HANDLE_TH_ERRORS
if (check_has_torch_function(self)) {
return handle_torch_function(self, "new_tensor");
return handle_torch_function(self, "new_tensor", args, kwargs);
}
auto& self_ = reinterpret_cast<THPVariable*>(self)->cdata;
OptionalDeviceGuard device_guard(device_of(self_));
Expand Down Expand Up @@ -935,7 +935,7 @@ static PyObject * THPVariable_tolist(PyObject* self, PyObject* args)
{
HANDLE_TH_ERRORS
if (check_has_torch_function(self)) {
return handle_torch_function(self, "tolist");
return handle_torch_function(self, "tolist", args);
}
jit::tracer::warn("Converting a tensor to a Python list", jit::tracer::WARN_PYTHON_DATAFLOW);
auto self_ = reinterpret_cast<THPVariable*>(self)->cdata;
Expand Down Expand Up @@ -1004,7 +1004,7 @@ static PyObject * THPVariable_type(PyObject* self, PyObject* args, PyObject* kwa
static PyObject * THPVariable_bool_scalar(PyObject* self, PyObject* args) {
if (check_has_torch_function(self)) {
HANDLE_TH_ERRORS
return handle_torch_function(self, "__bool__");
return handle_torch_function(self, "__bool__", args);
END_HANDLE_TH_ERRORS
}
jit::tracer::warn("Converting a tensor to a Python boolean", jit::tracer::WARN_PYTHON_DATAFLOW);
Expand Down
10 changes: 5 additions & 5 deletions torch/csrc/utils/python_arg_parser.cpp
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Expand Up @@ -139,7 +139,7 @@ FunctionParameter::FunctionParameter(const std::string& fmt, bool keyword_only)
auto handle_torch_function_getter(THPVariable* self, const std::string& property_name) -> PyObject* {
py::object torch_api = PyObject_FastGetAttrString(THPVariableClass, (char*)property_name.c_str());
std::string module_name = "torch.Tensor." + property_name;
return handle_torch_function((PyObject *)self, "__get__", nullptr, torch_api.ptr(), module_name);
return handle_torch_function((PyObject *)self, "__get__", nullptr, nullptr, torch_api.ptr(), module_name);
}

auto handle_torch_function_setter(THPVariable* self, const std::string& property_name, PyObject* value) -> int {
Expand All @@ -148,10 +148,10 @@ auto handle_torch_function_setter(THPVariable* self, const std::string& property
if (value != nullptr)
{
py::tuple args_ = py::make_tuple(py::handle(value));
handle_torch_function((PyObject *)self, "__set__", args_.ptr(), torch_api.ptr(), module_name);
handle_torch_function((PyObject *)self, "__set__", args_.ptr(), nullptr, torch_api.ptr(), module_name);
}
else {
handle_torch_function((PyObject *)self, "__delete__", nullptr, torch_api.ptr(), module_name);
handle_torch_function((PyObject *)self, "__delete__", nullptr, nullptr, torch_api.ptr(), module_name);
}
return 0;
}
Expand All @@ -175,13 +175,13 @@ auto combine_self_args(PyObject *self, PyObject *args) -> py::tuple {
return args_;
}

auto handle_torch_function(PyObject* self, const std::string& func_name, PyObject* args, PyObject* torch_api, const std::string& module_name) -> PyObject* {
auto handle_torch_function(PyObject* self, const std::string& func_name, PyObject* args, PyObject* kwargs, PyObject* torch_api, const std::string& module_name) -> PyObject* {
py::object torch_api_function = PyObject_FastGetAttrString(torch_api, (char*)func_name.c_str());
TORCH_INTERNAL_ASSERT(torch_api_function.ptr() != nullptr, "torch API function must exist");
py::tuple args_ = combine_self_args(self, args);
py::tuple py_types = py::make_tuple(py::handle(PyObject_Type(self)));
py::object torch_function = PyObject_FastGetAttrString(self, "__torch_function__");
py::object ret = py::reinterpret_steal<py::object>(PyObject_CallFunctionObjArgs(torch_function.ptr(), torch_api_function.ptr(), py_types.ptr(), args_.ptr(), NULL));
py::object ret = py::reinterpret_steal<py::object>(PyObject_CallFunctionObjArgs(torch_function.ptr(), torch_api_function.ptr(), py_types.ptr(), args_.ptr(), kwargs));
if (ret.ptr() == nullptr) {
// if an exception occurred in a user's implementation of
// __torch_function__, throw it
Expand Down
4 changes: 2 additions & 2 deletions torch/csrc/utils/python_arg_parser.h
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Expand Up @@ -820,8 +820,8 @@ auto handle_torch_function(PythonArgs &r, PyObject* self, PyObject* args, PyObje
// Used for functions which needs to parse python args.
auto handle_torch_function(PythonArgs &r, PyObject* args, PyObject* kwargs, PyObject* torch_api, const char* module_name) -> PyObject*;

// Used for functions that accept no keyword arguments and have no argument parsing
auto handle_torch_function(PyObject* self, const std::string& func_name, PyObject* args=nullptr, PyObject* torch_api=THPVariableClass, const std::string& module_name="torch.Tensor") -> PyObject*;
// Used for functions that have no argument parsing.
auto handle_torch_function(PyObject* self, const std::string& func_name, PyObject* args=nullptr, PyObject* kwargs=nullptr, PyObject* torch_api=THPVariableClass, const std::string& module_name="torch.Tensor") -> PyObject*;

// Used for functions created in C++, e.g., C++ custom op, which doesn't use PythonArgParser to get overloaded_args.
auto handle_torch_function_no_python_arg_parser(const std::vector<py::handle> &overloaded_args, PyObject* args, PyObject* kwargs, const char* func_name, PyObject* torch_api_function, const char* module_name) -> PyObject*;
Expand Down