cuda¶

Documentation¶

class treetensor.torch.Tensor(data, *args, constraint=None, **kwargs)[source]¶

cuda(*args, **kwargs)[source]¶

Returns a copy of this tree tensor in CUDA memory.

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

Torch Version Related

This documentation is based on torch.Tensor.cuda in torch v1.9.0+cu102. Its arguments’ arrangements depend on the version of pytorch you installed.

If some arguments listed here are not working properly, please check your pytorch’s version with the following command and find its documentation.

python -c 'import torch;print(torch.__version__)'

The arguments and keyword arguments supported in torch v1.9.0+cu102 is listed below.

Description From Torch v1.9.0+cu102¶

class torch.Tensor¶

cuda(device=None, non_blocking=False, memory_format=torch.preserve_format) → Tensor ¶

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.

Args:

device (torch.device): The destination GPU device.: Defaults to the current CUDA device.
non_blocking (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. Default: False.
memory_format (torch.memory_format, optional): the desired memory format of: returned Tensor. Default: torch.preserve_format.