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.
12.08.2019 · This OP is missing in the PyTorch binaries for Windows, since (if I'm not mistaken) Windows does not support (some) distributed setups. Therefore I've built PyTorch from source, manually disabling the distributed option, so that I can run into the same errors.
Resets the “peak” stats tracked by the CUDA memory allocator. See memory_stats() for details. Peak stats correspond to the “peak” key in each individual stat ...
I tried to run the code in the Quick Start. When I got to this step, optimizer = torch.optim.Adam(task.parameters(), lr=1e-3) solver = core.Engine(task, train_set, valid_set, test_set, optimizer, b...
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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.