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[Exception] [6/N] Remove use of torch::TypeError (#117964)

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Pull Request resolved: https://github.com/pytorch/pytorch/pull/117964
Approved by: https://github.com/albanD
This commit is contained in:
cyy
2024-01-25 03:35:53 +00:00
committed by PyTorch MergeBot
parent 67300a11cb
commit 87335fabae
12 changed files with 191 additions and 170 deletions
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58
torch/csrc/utils/tensor_numpy.cpp
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@ -107,9 +107,7 @@ static std::vector<int64_t> to_aten_shape(int ndim, npy_intp* values) {
static std::vector<int64_t> seq_to_aten_shape(PyObject* py_seq) {
int ndim = PySequence_Length(py_seq);
if (ndim == -1) {
throw TypeError("shape and strides must be sequences");
}
TORCH_CHECK_TYPE(ndim != -1, "shape and strides must be sequences");
auto result = std::vector<int64_t>(ndim);
for (const auto i : c10::irange(ndim)) {
auto item = THPObjectPtr(PySequence_GetItem(py_seq, i));
@ -301,7 +299,8 @@ int aten_to_numpy_dtype(const ScalarType scalar_type) {
case kBool:
return NPY_BOOL;
default:
throw TypeError("Got unsupported ScalarType %s", toString(scalar_type));
TORCH_CHECK_TYPE(
false, "Got unsupported ScalarType ", toString(scalar_type));
}
}
@ -353,10 +352,12 @@ ScalarType numpy_dtype_to_aten(int dtype) {
auto pytype = THPObjectPtr(PyArray_TypeObjectFromType(dtype));
if (!pytype)
throw python_error();
throw TypeError(
"can't convert np.ndarray of type %s. The only supported types are: "
"float64, float32, float16, complex64, complex128, int64, int32, int16, int8, uint64, uint32, uint16, uint8, and bool.",
((PyTypeObject*)pytype.get())->tp_name);
TORCH_CHECK_TYPE(
false,
"can't convert np.ndarray of type ",
((PyTypeObject*)pytype.get())->tp_name,
". The only supported types are: "
"float64, float32, float16, complex64, complex128, int64, int32, int16, int8, uint64, uint32, uint16, uint8, and bool.");
}
bool is_numpy_int(PyObject* obj) {
@ -382,17 +383,15 @@ at::Tensor tensor_from_cuda_array_interface(PyObject* obj) {
THPObjectPtr(PyObject_GetAttrString(obj, "__cuda_array_interface__"));
TORCH_INTERNAL_ASSERT(cuda_dict);
if (!PyDict_Check(cuda_dict.get())) {
throw TypeError("`__cuda_array_interface__` must be a dict");
}
TORCH_CHECK_TYPE(
PyDict_Check(cuda_dict.get()),
"`__cuda_array_interface__` must be a dict");
// Extract the `obj.__cuda_array_interface__['shape']` attribute
std::vector<int64_t> sizes;
{
PyObject* py_shape = PyDict_GetItemString(cuda_dict, "shape");
if (py_shape == nullptr) {
throw TypeError("attribute `shape` must exist");
}
TORCH_CHECK_TYPE(py_shape, "attribute `shape` must exist");
sizes = seq_to_aten_shape(py_shape);
}
@ -403,9 +402,7 @@ at::Tensor tensor_from_cuda_array_interface(PyObject* obj) {
int dtype_size_in_bytes;
{
PyObject* py_typestr = PyDict_GetItemString(cuda_dict, "typestr");
if (py_typestr == nullptr) {
throw TypeError("attribute `typestr` must exist");
}
TORCH_CHECK_TYPE(py_typestr, "attribute `typestr` must exist");
// NOLINTNEXTLINE(cppcoreguidelines-init-variables)
PyArray_Descr* descr;
TORCH_CHECK_VALUE(
@ -420,12 +417,10 @@ at::Tensor tensor_from_cuda_array_interface(PyObject* obj) {
void* data_ptr;
{
PyObject* py_data = PyDict_GetItemString(cuda_dict, "data");
if (py_data == nullptr) {
throw TypeError("attribute `shape` data exist");
}
if (!PyTuple_Check(py_data) || PyTuple_GET_SIZE(py_data) != 2) {
throw TypeError("`data` must be a 2-tuple of (int, bool)");
}
TORCH_CHECK_TYPE(py_data, "attribute `shape` data exist");
TORCH_CHECK_TYPE(
PyTuple_Check(py_data) && PyTuple_GET_SIZE(py_data) == 2,
"`data` must be a 2-tuple of (int, bool)");
data_ptr = PyLong_AsVoidPtr(PyTuple_GET_ITEM(py_data, 0));
if (data_ptr == nullptr && PyErr_Occurred()) {
throw python_error();
@ -434,10 +429,9 @@ at::Tensor tensor_from_cuda_array_interface(PyObject* obj) {
if (read_only == -1) {
throw python_error();
}
if (read_only) {
throw TypeError(
"the read only flag is not supported, should always be False");
}
TORCH_CHECK_TYPE(
!read_only,
"the read only flag is not supported, should always be False");
}
// Extract the `obj.__cuda_array_interface__['strides']` attribute
@ -445,11 +439,11 @@ at::Tensor tensor_from_cuda_array_interface(PyObject* obj) {
{
PyObject* py_strides = PyDict_GetItemString(cuda_dict, "strides");
if (py_strides != nullptr && py_strides != Py_None) {
if (PySequence_Length(py_strides) == -1 ||
static_cast<size_t>(PySequence_Length(py_strides)) != sizes.size()) {
throw TypeError(
"strides must be a sequence of the same length as shape");
}
TORCH_CHECK_TYPE(
PySequence_Length(py_strides) != -1 &&
static_cast<size_t>(PySequence_Length(py_strides)) ==
sizes.size(),
"strides must be a sequence of the same length as shape");
strides = seq_to_aten_shape(py_strides);
// __cuda_array_interface__ strides use bytes. Torch strides use element