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As support for Intel GPU has been upstreamed, this PR is to make the AMP example doc device-agnostic. Co-authored-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com> Pull Request resolved: https://github.com/pytorch/pytorch/pull/127278 Approved by: https://github.com/dvrogozh, https://github.com/EikanWang, https://github.com/svekars |
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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 | ||
| custom_operators.rst | ||
| ddp.rst | ||
| extending.func.rst | ||
| extending.rst | ||
| faq.rst | ||
| fsdp.rst | ||
| gradcheck.rst | ||
| hip.rst | ||
| large_scale_deployments.rst | ||
| modules.rst | ||
| mps.rst | ||
| multiprocessing.rst | ||
| numerical_accuracy.rst | ||
| randomness.rst | ||
| serialization.rst | ||
| windows.rst | ||
