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#include <torch/csrc/python_headers.h>
#include <torch/csrc/Device.h>
#include <torch/csrc/Dtype.h>
#include <torch/csrc/DynamicTypes.h>
#include <torch/csrc/Exceptions.h>
#include <torch/csrc/Layout.h>
#include <torch/csrc/PythonTypes.h>
#include <torch/csrc/Storage.h>
#include <torch/csrc/autograd/generated/VariableType.h>
#include <torch/csrc/utils/cuda_enabled.h>
#include <torch/csrc/utils/cuda_lazy_init.h>
#include <torch/csrc/utils/object_ptr.h>
#include <ATen/ATen.h>
#include <array>
#include <memory>
#include <sstream>
#include <stdexcept>
#include <string>
#include <unordered_map>
#include <vector>
namespace torch {
namespace {
std::array<THPDtype*, static_cast<int>(at::ScalarType::NumOptions)>
dtype_registry = {};
std::array<THPLayout*, static_cast<int>(at::Layout::NumOptions)>
layout_registry = {};
at::DeprecatedTypeProperties* get_type_properties(
at::DeviceType device_type,
at::ScalarType scalarType) {
at::Backend backend;
if (device_type == at::kCPU) {
backend = at::Backend::CPU;
} else if (device_type == at::kCUDA) {
backend = at::Backend::CUDA;
} else if (device_type == at::kXPU) {
backend = at::Backend::XPU;
} else if (device_type == at::kMPS) {
backend = at::Backend::MPS;
} else if (device_type == at::DeviceType::Meta) {
backend = at::Backend::Undefined;
} else {
TORCH_CHECK(false, "Invalid device for storage: ", device_type);
}
return &at::getDeprecatedTypeProperties(backend, scalarType);
}
} // namespace
void registerDtypeObject(THPDtype* dtype, at::ScalarType scalarType) {
dtype_registry[static_cast<int>(scalarType)] = dtype;
}
void registerLayoutObject(THPLayout* thp_layout, at::Layout layout) {
layout_registry[static_cast<int>(layout)] = thp_layout;
}
THPDtype* getTHPDtype(at::ScalarType scalarType) {
auto dtype = dtype_registry[static_cast<int>(scalarType)];
if (!dtype) {
throw std::invalid_argument("unsupported scalarType");
}
return dtype;
}
THPLayout* getTHPLayout(at::Layout layout) {
auto thp_layout = layout_registry[static_cast<int>(layout)];
if (!thp_layout) {
throw std::invalid_argument("unsupported at::Layout");
}
return thp_layout;
}
PyObject* createPyObject(const at::Storage& storage) {
if (storage.device_type() != at::DeviceType::Meta &&
storage.data() == nullptr && storage.nbytes() != 0) {
TORCH_CHECK_NOT_IMPLEMENTED(
false,
"python bindings to nullptr storage (e.g., from torch.Tensor._make_wrapper_subclass) are currently unsafe and thus disabled. See https://github.com/pytorch/pytorch/issues/61669 for more details");
}
PyTypeObject* type = reinterpret_cast<PyTypeObject*>(THPStorageClass);
auto obj = THPObjectPtr(type->tp_alloc(type, 0));
if (!obj)
throw python_error();
((THPVoidStorage*)obj.get())->cdata =
at::Storage(/* copy */ storage).unsafeReleaseStorageImpl();
return obj.release();
}
PyTypeObject* loadTypedStorageTypeObject() {
PyObject* storage_module = PyImport_ImportModule("torch.storage");
TORCH_INTERNAL_ASSERT(storage_module && PyModule_Check(storage_module));
PyObject* typed_storage_obj =
PyObject_GetAttrString(storage_module, "TypedStorage");
TORCH_INTERNAL_ASSERT(typed_storage_obj && PyType_Check(typed_storage_obj));
return reinterpret_cast<PyTypeObject*>(
PyObject_GetAttrString(storage_module, "TypedStorage"));
}
PyTypeObject* getTypedStorageTypeObject() {
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
static PyTypeObject* typed_storage_type_obj = loadTypedStorageTypeObject();
return typed_storage_type_obj;
}
bool isStorage(PyObject* obj) {
if (PyObject_TypeCheck(obj, getTypedStorageTypeObject())) {
return true;
}
auto obj_type = Py_TYPE(obj);
return obj_type == reinterpret_cast<PyTypeObject*>(THPStorageClass);
}
at::Storage createStorageGetType(
PyObject* obj,
at::ScalarType& scalar_type,
bool& is_typed_storage) {
is_typed_storage = PyObject_TypeCheck(obj, getTypedStorageTypeObject());
PyObject* untyped_storage_obj;
if (is_typed_storage) {
// NOTE: `PyObject_GetAttrString` increments the refcounts to `dtype` and
// `_storage`, so we must decrement them. The refcounts will still stay
// nonzero since the `TypedStorage` maintains a reference.
PyObject* dtype_obj = PyObject_GetAttrString(obj, "dtype");
TORCH_INTERNAL_ASSERT(dtype_obj);
Py_DECREF(dtype_obj);
TORCH_INTERNAL_ASSERT(THPDtype_Check(dtype_obj));
scalar_type = reinterpret_cast<THPDtype*>(dtype_obj)->scalar_type;
untyped_storage_obj = PyObject_GetAttrString(obj, "_storage");
TORCH_INTERNAL_ASSERT(untyped_storage_obj);
Py_DECREF(untyped_storage_obj);
} else {
scalar_type = at::kByte;
untyped_storage_obj = obj;
}
if (Py_TYPE(untyped_storage_obj) !=
reinterpret_cast<PyTypeObject*>(THPStorageClass)) {
throw TypeError("not a storage '%s'", Py_TYPE(obj)->tp_name);
}
c10::StorageImpl* impl = static_cast<c10::StorageImpl*>(
((THPVoidStorage*)untyped_storage_obj)->cdata);
c10::DeviceType device_type = impl->device().type();
auto type_properties = get_type_properties(device_type, at::kByte);
return type_properties->unsafeStorageFromTH(
((THPVoidStorage*)untyped_storage_obj)->cdata, true);
}
at::Storage createStorage(PyObject* obj) {
at::ScalarType scalar_type;
bool is_typed_storage = false;
return createStorageGetType(obj, scalar_type, is_typed_storage);
}
} // namespace torch
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