torch.Storage¶

A torch.Storage is a contiguous, one-dimensional array of a single data type.

Every torch.Tensor has a corresponding storage of the same data type.

class torch.FloatStorage[source]¶

byte()¶: Casts this storage to byte type

char()¶: Casts this storage to char type

clone()¶: Returns a copy of this storage

copy_()¶

cpu()¶: Returns a CPU copy of this storage if it’s not already on the CPU

cuda(device=None, async=False)¶

Returns a copy of this object in CUDA memory.

If this object is already in CUDA memory and on the correct device, then no copy is performed and the original object is returned.

Parameters:	device (int) – The destination GPU id. Defaults to the current device. async (bool) – If True and the source is in pinned memory, the copy will be asynchronous with respect to the host. Otherwise, the argument has no effect.

data_ptr()¶

double()¶: Casts this storage to double type

element_size()¶

fill_()¶

float()¶: Casts this storage to float type

from_buffer()¶

half()¶: Casts this storage to half type

int()¶: Casts this storage to int type

is_cuda = False¶

is_pinned()¶

is_shared()¶

is_sparse = False¶

long()¶: Casts this storage to long type

new()¶

pin_memory()¶: Copies the storage to pinned memory, if it’s not already pinned.

resize_()¶

share_memory_()¶

Moves the storage to shared memory.

This is a no-op for storages already in shared memory and for CUDA storages, which do not need to be moved for sharing across processes. Storages in shared memory cannot be resized.

Returns: self

short()¶: Casts this storage to short type

size()¶

tolist()¶: Returns a list containing the elements of this storage

type(new_type=None, async=False)¶

Casts this object to the specified type.

If this is already of the correct type, no copy is performed and the original object is returned.

Parameters:	new_type (type or string) – The desired type async (bool) – If True, and the source is in pinned memory and destination is on the GPU or vice versa, the copy is performed asynchronously with respect to the host. Otherwise, the argument has no effect.