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Summary: Doc update intended to clarify and expand our current serialization behavior, including explaining the difference between torch.save/torch.load, torch.nn.Module.state_dict/torch.nn.Module.load_state_dict, and torch.jit.save/torch.jit.load. Also explains, for the time, when historic serialized Torchscript behavior is preserved and our recommendation for preserving behavior (using the same PyTorch version to consume a model as produced it). Pull Request resolved: https://github.com/pytorch/pytorch/pull/41395 Reviewed By: ngimel Differential Revision: D22560538 Pulled By: mruberry fbshipit-source-id: dbc2f1bb92ab61ff2eca4888febc21f7dda76ba1 |
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| .. | ||
| amp_examples.rst | ||
| autograd.rst | ||
| broadcasting.rst | ||
| cpu_threading_runtimes.svg | ||
| cpu_threading_torchscript_inference.rst | ||
| cpu_threading_torchscript_inference.svg | ||
| cuda.rst | ||
| ddp.rst | ||
| extending.rst | ||
| faq.rst | ||
| large_scale_deployments.rst | ||
| multiprocessing.rst | ||
| randomness.rst | ||
| serialization.rst | ||
| windows.rst | ||
