The following are 7 code examples for showing how to use torch.Device().These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example.
torch.cuda. This package adds support for CUDA tensor types, that implement the same function as CPU tensors, but they utilize GPUs for computation. It is lazily initialized, so you can always import it, and use is_available () to determine if your system supports CUDA.
A torch.device is an object representing the device on which a torch.Tensor is or will be allocated. The torch.device contains a device type ( 'cpu' or 'cuda') …
18.11.2019 · device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") ... # then whenever you get a new Tensor or Module # this won't copy if they are already on the desired device input = data.to(device) model = MyModule(...).to(device) Do note that there is nothing stopping you from adding a .deviceproperty to the models.
torch.device¶ class torch. device ¶ A torch.device is an object representing the device on which a torch.Tensor is or will be allocated. The torch.device contains a device type ('cpu' or 'cuda') and optional device ordinal for the device type.
27.05.2019 · torch.cuda.device_count()will give you the number of available devices, not a device number range(n)will give you all the integers between 0 and n-1 (included). Which are all the valid device numbers. 1 Like bing(Mr. Bing) December 13, 2019, 8:36pm #11 Yes, I am doing the same - device_id = torch.cuda.device_count()
If a given object is not allocated on a GPU, this is a no-op. Parameters. obj (Tensor or Storage) – object allocated on the selected device. torch.cuda.
Arguments: attention_mask: torch.Tensor with 1 indicating tokens to ATTEND to input_shape: tuple, shape of input_ids device: torch.Device, usually self.device Returns: torch.Tensor with dtype of attention_mask.dtype """ # We can provide a self-attention mask of dimensions [batch_size, from_seq_length, to_seq_length] # ourselves in which case we just need to make it broadcastable …
May 27, 2019 · I assumed if I use torch.device("cuda") it makes the device to be a GPU without particularly specifying the device name (0,1,2,3). I would like to make sure if I understand the difference between these two command correctly. torch.device("cuda") # without specifying the cuda device number torch.device("cuda:0") # u...
Nov 19, 2019 · The recommended workflow (as described on PyTorch blog) is to create the device object separately and use that everywhere. Copy-pasting the example from the blog here: # at beginning of the script device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") ...