forked from ROCm/pytorch
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Storage.cpp
495 lines (455 loc) · 15.7 KB
/
Storage.cpp
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
#include <torch/csrc/python_headers.h>
#ifdef _MSC_VER
#include <c10/util/win32-headers.h>
#endif
#include <structmember.h>
#include <ATen/mps/MPSDevice.h>
#include <c10/core/CPUAllocator.h>
#include <libshm.h>
#include <torch/csrc/CudaIPCTypes.h>
#include <torch/csrc/Device.h>
#include <torch/csrc/DynamicTypes.h>
#include <torch/csrc/StorageMethods.h>
#include <torch/csrc/StorageSharing.h>
#include <torch/csrc/THP.h>
#include <torch/csrc/autograd/utils/wrap_outputs.h>
#include <torch/csrc/copy_utils.h>
#include <torch/csrc/utils/python_arg_parser.h>
#include <c10/util/intrusive_ptr.h>
#include <fmt/format.h>
template <>
void THPPointer<c10::StorageImpl>::free() {
if (ptr) {
c10::raw::intrusive_ptr::decref(ptr);
}
}
PyObject* THPStorageClass = nullptr;
PyObject* THPStorage_New(c10::Storage storage) {
PyTypeObject* type = (PyTypeObject*)THPStorageClass;
PyObject* obj = type->tp_alloc(type, 0);
if (obj) {
((THPStorage*)obj)->cdata =
c10::MaybeOwned<c10::Storage>::owned(std::move(storage));
}
return obj;
}
static void THPStorage_subclass_dealloc(PyObject* self) {
THPStorage* _self = (THPStorage*)self;
// Some subclass of StorageBase are GC-tracked objects even
// though the base class is not.
auto* type = Py_TYPE(self);
if (PyType_HasFeature(type, Py_TPFLAGS_HAVE_GC) != 0) {
PyObject_GC_UnTrack(self);
}
_self->cdata.~MaybeOwned<c10::Storage>();
Py_TYPE(_self)->tp_free(self);
}
c10::intrusive_ptr<c10::StorageImpl> make_storage_impl(
c10::StorageImpl::use_byte_size_t use_byte_size,
c10::SymInt size_bytes,
c10::Allocator* allocator,
bool resizable,
c10::optional<int64_t> allocator_opt,
c10::optional<at::Device> device_opt) {
at::OptionalDeviceGuard device_guard;
// This will be non-nullptr only when there is a custom StorageImpl
// constructor for the given device
c10::StorageImplCreateHelper fptr = nullptr;
// For directly passing allocator scenarios, only c10::StorageImpl objects can
// be created. If you need to create a storageimpl object of a subclass, you
// need to pass in the device information.
if (allocator_opt.has_value()) {
allocator = reinterpret_cast<c10::Allocator*>(allocator_opt.value());
} else if (device_opt.has_value()) {
at::Device device = device_opt.value();
// We only need to check this here as this is the only case where we can
// have a device that is not CPU (and thus for which the StorageImpl
// constructor can be overwritten).
fptr = c10::GetStorageImplCreate(device.type());
if (device.type() == at::kCPU) {
allocator = c10::GetDefaultCPUAllocator();
#ifdef USE_CUDA
} else if (device.type() == at::kCUDA) {
at::globalContext().lazyInitCUDA();
allocator = c10::cuda::CUDACachingAllocator::get();
#endif
#ifdef USE_MPS
} else if (device.type() == at::kMPS) {
allocator = at::mps::GetMPSAllocator();
#endif
} else if (device.type() == at::DeviceType::XPU) {
allocator = c10::GetAllocator(device.type());
} else if (device.type() == at::DeviceType::HPU) {
allocator = c10::GetAllocator(device.type());
} else if (device.type() == at::DeviceType::Meta) {
allocator = c10::GetAllocator(device.type());
} else if (device.type() == at::DeviceType::PrivateUse1) {
allocator = c10::GetAllocator(device.type());
} else {
TORCH_CHECK(
false,
THPStorageStr,
"(): Storage device not recognized: ",
device.type());
}
device_guard.reset_device(device);
} else {
allocator = c10::GetDefaultCPUAllocator();
}
if (fptr != nullptr) {
return fptr(use_byte_size, std::move(size_bytes), allocator, resizable);
}
// Create a c10::StorageImpl object.
return c10::make_intrusive<c10::StorageImpl>(
use_byte_size, std::move(size_bytes), allocator, resizable);
}
static PyObject* THPStorage_pynew(
PyTypeObject* type,
PyObject* args,
PyObject* kwargs) {
HANDLE_TH_ERRORS
TORCH_CHECK(
type != &THPStorageType,
"Cannot directly construct StorageBase; subclass it and then construct that");
static torch::PythonArgParser parser({
THPStorageStr "(*, int64_t allocator=None, Device device=None)",
THPStorageStr
"(int64_t size, *, int64_t allocator=None, Device device=None)",
THPStorageStr
"(PyObject* sequence, *, int64_t allocator=None, Device device=None)",
});
torch::ParsedArgs<3> parsed_args;
auto r = parser.parse(args, kwargs, parsed_args);
int64_t allocator_arg_idx = 0;
int64_t device_arg_idx = 1;
if (r.idx > 0) {
allocator_arg_idx = 1;
device_arg_idx = 2;
}
c10::optional<int64_t> allocator_opt = r.toInt64Optional(allocator_arg_idx);
c10::optional<at::Device> device_opt = r.deviceOptional(device_arg_idx);
TORCH_CHECK(
!allocator_opt.has_value() || !device_opt.has_value(),
THPStorageStr,
"(): only one or neither of 'allocator' or 'device' can ",
"be given, but not both");
THPStoragePtr self((THPStorage*)type->tp_alloc(type, 0));
THPUtils_assert(self, "failed to allocate a " THPStorageStr " object");
c10::Allocator* allocator = nullptr;
// torch.Storage(*, ...)
if (r.idx == 0) {
self->cdata = c10::MaybeOwned<c10::Storage>::owned(make_storage_impl(
c10::StorageImpl::use_byte_size_t(),
0,
allocator,
/*resizable=*/true,
allocator_opt,
device_opt));
return (PyObject*)self.release();
// torch.Storage(size, *, ...)
} else if (r.idx == 1) {
int64_t size = r.toInt64(0);
self->cdata = c10::MaybeOwned<c10::Storage>::owned(make_storage_impl(
c10::StorageImpl::use_byte_size_t(),
size,
allocator,
/*resizable=*/true,
allocator_opt,
device_opt));
return (PyObject*)self.release();
// torch.Storage(sequence, *, ...)
} else if (r.idx == 2) {
PyObject* sequence = r.pyobject(0);
Py_ssize_t length = PySequence_Length(sequence);
TORCH_CHECK(
PySequence_Check(sequence),
THPStorageStr,
"(): Expected a sequence type, but got ",
THPUtils_typename(sequence));
TORCH_CHECK(
length >= 0,
THPStorageStr,
"(): Could not obtain the length of sequence of type ",
THPUtils_typename(sequence));
self->cdata = c10::MaybeOwned<c10::Storage>::owned(make_storage_impl(
c10::StorageImpl::use_byte_size_t(),
length,
allocator,
/*resizable=*/true,
allocator_opt,
device_opt));
THPObjectPtr item;
try {
for (Py_ssize_t i = 0; i < length; i++) {
item = PySequence_GetItem(sequence, i);
// NOLINTNEXTLINE(cppcoreguidelines-init-variables)
uint8_t value = THPByteUtils_unpackReal(item.get());
const auto& storage = THPStorage_Unpack(self);
if (allocator == c10::GetDefaultCPUAllocator()) {
static_cast<uint8_t*>(storage.mutable_data())[i] = value;
} else {
// TODO: this might be slow - consider batched updates?
storage_set(storage, i, value);
}
}
} catch (const std::exception& e) {
THPUtils_setError(
THPStorageStr
"(): tried to construct a storage from a sequence (%s), "
"but one of the items was of type %s instead of int",
THPUtils_typename(sequence),
THPUtils_typename(item.get()));
return nullptr;
}
return (PyObject*)self.release();
}
Py_RETURN_NONE;
END_HANDLE_TH_ERRORS
}
static Py_ssize_t THPStorage_length(THPStorage* self) {
HANDLE_TH_ERRORS
return THPStorage_Unpack(self).nbytes();
END_HANDLE_TH_ERRORS_RET(-1)
}
static PyObject* THPStorage_get(THPStorage* self, PyObject* index) {
HANDLE_TH_ERRORS
const auto& storage = THPStorage_Unpack(self);
/* Integer index */
if (THPUtils_checkLong(index)) {
int64_t nindex = THPUtils_unpackLong(index);
if (nindex < 0)
nindex += storage.nbytes();
if (nindex < 0 || nindex >= static_cast<int64_t>(storage.nbytes())) {
PyErr_SetString(
PyExc_IndexError,
fmt::format(
"index {} out of range for storage of size {}",
nindex,
storage.nbytes()));
return nullptr;
}
uint8_t value = storage_get(storage, nindex);
return THPByteUtils_newReal(value);
/* Slice index */
} else if (PySlice_Check(index)) {
// NOLINTNEXTLINE(cppcoreguidelines-init-variables)
Py_ssize_t start, stop, slicelength, step;
int64_t len = storage.nbytes();
if (PySlice_GetIndicesEx(index, len, &start, &stop, &step, &slicelength) !=
0)
return nullptr;
if (step != 1) {
THPUtils_setError(
"Trying to slice with a step of %lld, but only a step of "
"1 is supported",
(long long)step);
return nullptr;
}
const auto& storage = THPStorage_Unpack(self);
auto data = static_cast<uint8_t*>(storage.mutable_data());
at::StorageImpl* old_storage_impl = storage.unsafeGetStorageImpl();
c10::raw::intrusive_ptr::incref(old_storage_impl);
auto new_storage_impl = c10::make_intrusive<at::StorageImpl>(
c10::StorageImpl::use_byte_size_t(),
#ifdef THQUANTIZED
slicelength * sizeof(quantized_t),
#else
slicelength,
#endif
at::DataPtr(
static_cast<void*>(data + start),
old_storage_impl,
[](void* s) {
c10::raw::intrusive_ptr::decref(static_cast<at::StorageImpl*>(s));
},
old_storage_impl->device()),
old_storage_impl->allocator(),
/* resizable */ false);
PyObject* _ret = THPStorage_New(std::move(new_storage_impl));
return _ret;
}
PyErr_Format(
PyExc_TypeError,
"can't index a " THPStorageStr " with %s",
THPUtils_typename(index));
return nullptr;
END_HANDLE_TH_ERRORS
}
static int THPStorage_set(THPStorage* self, PyObject* index, PyObject* value) {
HANDLE_TH_ERRORS
if (!THPByteUtils_checkReal(value)) {
THPUtils_setError(
"can only set storage content with a int types, but got "
"%s instead",
THPUtils_typename(value));
return -1;
}
uint8_t rvalue = THPByteUtils_unpackReal(value);
const auto& storage = THPStorage_Unpack(self);
if (THPUtils_checkLong(index)) {
int64_t nindex = THPUtils_unpackLong(index);
storage_set(storage, nindex, rvalue);
return 0;
} else if (PySlice_Check(index)) {
// NOLINTNEXTLINE(cppcoreguidelines-init-variables)
Py_ssize_t start, stop, slicelength, step;
int64_t len = storage.nbytes();
if (PySlice_GetIndicesEx(index, len, &start, &stop, &step, &slicelength) !=
0)
return -1;
if (step != 1) {
THPUtils_setError(
"Trying to slice with a step of %lld, but only a step of "
"1 is supported",
(long long)step);
return 0;
}
// TODO: check the bounds only once
// TODO: fill?
for (; start < stop; start++)
storage_set(storage, start, rvalue);
return 0;
}
THPUtils_setError(
"can't index a " THPStorageStr " with %s", THPUtils_typename(index));
return -1;
END_HANDLE_TH_ERRORS_RET(-1)
}
static PyMappingMethods THPStorage_mappingmethods = {
(lenfunc)THPStorage_length,
(binaryfunc)THPStorage_get,
(objobjargproc)THPStorage_set};
struct THPStorageMeta {
PyHeapTypeObject base;
};
int THPStorageMetaType_init(PyObject* cls, PyObject* args, PyObject* kwargs);
PyTypeObject THPStorageMetaType = {
PyVarObject_HEAD_INIT(
DEFERRED_ADDRESS(&PyType_Type),
0) "torch._C._StorageMeta", /* tp_name */
sizeof(THPStorageMeta), /* tp_basicsize */
0, /* tp_itemsize */
nullptr, /* tp_dealloc */
0, /* tp_vectorcall_offset */
nullptr, /* tp_getattr */
nullptr, /* tp_setattr */
nullptr, /* tp_reserved */
nullptr, /* tp_repr */
nullptr, /* tp_as_number */
nullptr, /* tp_as_sequence */
nullptr, /* tp_as_mapping */
nullptr, /* tp_hash */
nullptr, /* tp_call */
nullptr, /* tp_str */
nullptr, /* tp_getattro */
nullptr, /* tp_setattro */
nullptr, /* tp_as_buffer */
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, /* tp_flags */
nullptr, /* tp_doc */
nullptr, /* tp_traverse */
nullptr, /* tp_clear */
nullptr, /* tp_richcompare */
0, /* tp_weaklistoffset */
nullptr, /* tp_iter */
nullptr, /* tp_iternext */
nullptr, /* tp_methods */
nullptr, /* tp_members */
nullptr, /* tp_getset */
DEFERRED_ADDRESS(&PyType_Type), /* tp_base */
nullptr, /* tp_dict */
nullptr, /* tp_descr_get */
nullptr, /* tp_descr_set */
0, /* tp_dictoffset */
THPStorageMetaType_init, /* tp_init */
nullptr, /* tp_alloc */
nullptr, /* tp_new */
};
// TODO: implement equality
PyTypeObject THPStorageType = {
PyVarObject_HEAD_INIT(
&THPStorageMetaType,
0) "torch._C.StorageBase", /* tp_name */
sizeof(THPStorage), /* tp_basicsize */
0, /* tp_itemsize */
nullptr, /* tp_dealloc */
0, /* tp_vectorcall_offset */
nullptr, /* tp_getattr */
nullptr, /* tp_setattr */
nullptr, /* tp_reserved */
nullptr, /* tp_repr */
nullptr, /* tp_as_number */
nullptr, /* tp_as_sequence */
&THPStorage_mappingmethods, /* tp_as_mapping */
nullptr, /* tp_hash */
nullptr, /* tp_call */
nullptr, /* tp_str */
nullptr, /* tp_getattro */
nullptr, /* tp_setattro */
nullptr, /* tp_as_buffer */
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, /* tp_flags */
nullptr, /* tp_doc */
nullptr, /* tp_traverse */
nullptr, /* tp_clear */
nullptr, /* tp_richcompare */
0, /* tp_weaklistoffset */
nullptr, /* tp_iter */
nullptr, /* tp_iternext */
nullptr,
/* will be assigned in init */ /* tp_methods */
nullptr,
/* will be assigned in init */ /* tp_members */
nullptr, /* tp_getset */
nullptr, /* tp_base */
nullptr, /* tp_dict */
nullptr, /* tp_descr_get */
nullptr, /* tp_descr_set */
0, /* tp_dictoffset */
nullptr, /* tp_init */
nullptr, /* tp_alloc */
THPStorage_pynew, /* tp_new */
};
int THPStorageMetaType_init(PyObject* cls, PyObject* args, PyObject* kwargs) {
if (PyType_Type.tp_init(cls, args, kwargs) < 0) {
return -1;
}
((PyTypeObject*)cls)->tp_dealloc = (destructor)THPStorage_subclass_dealloc;
return 0;
}
static PyObject* THPStorage_device(THPStorage* self, void* unused) {
HANDLE_TH_ERRORS
return THPDevice_New(THPStorage_Unpack(self).device());
END_HANDLE_TH_ERRORS
}
PyObject* THPStorage_get_cdata(THPStorage* self, void* unused) {
HANDLE_TH_ERRORS
return PyLong_FromVoidPtr(THPStorage_Unpack(self).unsafeGetStorageImpl());
END_HANDLE_TH_ERRORS
}
typedef PyObject* (*getter)(PyObject*, void*);
// NOLINTNEXTLINE(cppcoreguidelines-avoid-c-arrays,modernize-avoid-c-arrays,cppcoreguidelines-avoid-non-const-global-variables)
static struct PyGetSetDef THPStorage_properties[] = {
{"device", (getter)THPStorage_device, nullptr, nullptr, nullptr},
{"_cdata", (getter)THPStorage_get_cdata, nullptr, nullptr, nullptr},
{nullptr}};
bool THPStorage_init(PyObject* module) {
static std::vector<PyMethodDef> methods;
THPUtils_addPyMethodDefs(methods, THPStorage_getMethods());
THPUtils_addPyMethodDefs(methods, THPStorage_getSharingMethods());
THPStorageMetaType.tp_base = &PyType_Type;
if (PyType_Ready(&THPStorageMetaType) < 0)
return false;
Py_INCREF(&THPStorageMetaType);
PyModule_AddObject(module, "_StorageMeta", (PyObject*)&THPStorageMetaType);
THPStorageType.tp_methods = methods.data();
THPStorageType.tp_getset = THPStorage_properties;
if (PyType_Ready(&THPStorageType) < 0)
return false;
Py_INCREF(&THPStorageType);
PyModule_AddObject(module, "StorageBase", (PyObject*)&THPStorageType);
return true;
}
void THPStorage_postInit(PyObject* module) {
THPStorageClass = PyObject_GetAttrString(module, "UntypedStorage");
if (!THPStorageClass)
throw python_error();
}