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#ifndef TH_GENERIC_FILE
#define TH_GENERIC_FILE "torch/csrc/generic/serialization.cpp"
#else
#ifdef THC_GENERIC_FILE
#include <c10/cuda/CUDAGuard.h>
#endif
// save_save is necessary since the old eager format saved storages as
// [size + data], but the v1.5 eager format removes this since size is saved in
// the filesize.
template <class io>
void THPStorage_(writeFileRaw)(THWStorage *self, io fd, bool save_size)
{
#ifdef THC_GENERIC_FILE
c10::cuda::CUDAGuard guard(self->device());
#endif
scalar_t *data;
int64_t size_bytes = self->nbytes();
int64_t numel = size_bytes / sizeof(scalar_t);
#ifndef THC_GENERIC_FILE
data = THWStorage_(data)(LIBRARY_STATE self);
#else
std::unique_ptr<char[]> cpu_data(new char[size_bytes]);
data = (scalar_t*)cpu_data.get();
THCudaCheck(cudaMemcpy(
data,
THWStorage_(data)(LIBRARY_STATE self),
size_bytes,
cudaMemcpyDeviceToHost));
#endif
if (save_size) {
if (torch::utils::THP_nativeByteOrder() ==
torch::utils::THPByteOrder::THP_LITTLE_ENDIAN)
doWrite(fd, &numel, sizeof(int64_t));
else {
int64_t nsize; // convert big endian cpu to little endian storage
torch::utils::THP_encodeInt64Buffer(
(uint8_t*)&nsize,
(const int64_t*)&numel,
torch::utils::THPByteOrder::THP_LITTLE_ENDIAN,
1);
doWrite(fd, &nsize, sizeof(int64_t));
}
}
// fast track for bytes and little endian
if (sizeof(scalar_t) == 1 ||
torch::utils::THP_nativeByteOrder() ==
torch::utils::THPByteOrder::THP_LITTLE_ENDIAN) {
doWrite(fd, data, size_bytes);
} else {
int64_t buffer_size = std::min(numel, (int64_t)5000);
std::unique_ptr<uint8_t[]> le_buffer(new uint8_t[buffer_size * sizeof(scalar_t)]);
for (int64_t i = 0; i < numel; i += buffer_size) {
size_t to_convert = std::min(numel - i, buffer_size);
if (sizeof(scalar_t) == 2) {
torch::utils::THP_encodeInt16Buffer(
(uint8_t*)le_buffer.get(),
(const int16_t*)data + i,
torch::utils::THPByteOrder::THP_LITTLE_ENDIAN,
to_convert);
} else if (sizeof(scalar_t) == 4) {
torch::utils::THP_encodeInt32Buffer(
(uint8_t*)le_buffer.get(),
(const int32_t*)data + i,
torch::utils::THPByteOrder::THP_LITTLE_ENDIAN,
to_convert);
} else if (sizeof(scalar_t) == 8) {
torch::utils::THP_encodeInt64Buffer(
(uint8_t*)le_buffer.get(),
(const int64_t*)data + i,
torch::utils::THPByteOrder::THP_LITTLE_ENDIAN,
to_convert);
}
doWrite(fd, le_buffer.get(), to_convert * sizeof(scalar_t));
}
}
}
template void THPStorage_(writeFileRaw<int>)(THWStorage *self, int fd, bool save_size);
template void THPStorage_(writeFileRaw<PyObject*>)(THWStorage *self, PyObject* fd, bool save_size);
template <class io>
THWStorage * THPStorage_(readFileRaw)(io file, THWStorage *_storage)
{
#ifdef THC_GENERIC_FILE
c10::cuda::OptionalCUDAGuard guard;
if (_storage != nullptr) {
guard.set_device(_storage->device());
}
#endif
scalar_t *data;
int64_t size;
doRead(file, &size, sizeof(int64_t));
if (torch::utils::THP_nativeByteOrder() ==
torch::utils::THPByteOrder::THP_BIG_ENDIAN) {
int64_t nsize; // convert little endian storage to big endian cpu
nsize = size;
torch::utils::THP_decodeInt64Buffer(
&size, (const uint8_t*)&nsize, torch::utils::THP_nativeByteOrder(), 1);
}
THWStoragePtr storage;
if (_storage == nullptr) {
storage = THWStorage_(newWithSize)(LIBRARY_STATE size);
} else {
int64_t _storage_numel = _storage->nbytes() / sizeof(scalar_t);
THPUtils_assert(
_storage_numel == size,
"storage has wrong size: expected %ld got %ld",
size,
_storage_numel);
storage = _storage;
}
#ifndef THC_GENERIC_FILE
data = THWStorage_(data)(LIBRARY_STATE storage);
#else
std::unique_ptr<char[]> cpu_data(new char[size * sizeof(scalar_t)]);
data = (scalar_t*)cpu_data.get();
#endif
// fast track for bytes and little endian
if (sizeof(scalar_t) == 1 ||
torch::utils::THP_nativeByteOrder() ==
torch::utils::THPByteOrder::THP_LITTLE_ENDIAN) {
doRead(file, data, storage->nbytes());
} else {
int64_t buffer_size = std::min(size, (int64_t)5000);
std::unique_ptr<uint8_t[]> le_buffer(new uint8_t[buffer_size * sizeof(scalar_t)]);
for (int64_t i = 0; i < size; i += buffer_size) {
size_t to_convert = std::min(size - i, buffer_size);
doRead(file, le_buffer.get(), sizeof(scalar_t) * to_convert);
if (sizeof(scalar_t) == 2) {
torch::utils::THP_decodeInt16Buffer(
(int16_t*)data + i,
le_buffer.get(),
torch::utils::THP_nativeByteOrder(),
to_convert);
} else if (sizeof(scalar_t) == 4) {
torch::utils::THP_decodeInt32Buffer(
(int32_t*)data + i,
le_buffer.get(),
torch::utils::THP_nativeByteOrder(),
to_convert);
} else if (sizeof(scalar_t) == 8) {
torch::utils::THP_decodeInt64Buffer(
(int64_t*)data + i,
le_buffer.get(),
torch::utils::THP_nativeByteOrder(),
to_convert);
}
}
}
#ifdef THC_GENERIC_FILE
THCudaCheck(cudaMemcpy(THWStorage_(data)(LIBRARY_STATE storage), data, size * sizeof(scalar_t), cudaMemcpyHostToDevice));
#endif
return storage.release();
}
template THWStorage* THPStorage_(readFileRaw<int>)(int fd, THWStorage* storage);
template THWStorage* THPStorage_(readFileRaw<PyObject*>)(PyObject* fd, THWStorage* storage);
#endif
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