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Fix typos in .md and .rst files (#88962)
This PR fixes typos `Github` in `.md` and `.rst` files. `Github` -> `GitHub` Pull Request resolved: https://github.com/pytorch/pytorch/pull/88962 Approved by: https://github.com/kit1980
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.github/scripts/README.md
vendored
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.github/scripts/README.md
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@ -3,7 +3,7 @@
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> NOTE: This README contains information for the `.github` directory but cannot be located there because it will overwrite the
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repo README.
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This directory contains workflows and scripts to support our CI infrastructure that runs on Github Actions.
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This directory contains workflows and scripts to support our CI infrastructure that runs on GitHub Actions.
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## Workflows
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@ -281,7 +281,7 @@ need to support these particular versions of software.
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In the event a submodule cannot be fast forwarded and a patch must be applied we can take two different approaches:
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* (preferred) Fork the said repository under the pytorch Github organization, apply the patches we need there, and then switch our submodule to accept our fork.
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* (preferred) Fork the said repository under the pytorch GitHub organization, apply the patches we need there, and then switch our submodule to accept our fork.
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* Get the dependencies maintainers to support a release branch for us
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Editing submodule remotes can be easily done with: (running from the root of the git repository)
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@ -15,4 +15,4 @@ For further information please explore `caffe2/python/trt/test_trt.py` test show
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## Questions and Feedback
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Please use Github issues (https://github.com/pytorch/pytorch/issues) to ask questions, report bugs, and request new features.
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Please use GitHub issues (https://github.com/pytorch/pytorch/issues) to ask questions, report bugs, and request new features.
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@ -138,7 +138,7 @@ A great deal of the tutorials on `pytorch.org <https://pytorch.org/>`__
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come from the community itself and we welcome additional contributions.
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To learn more about how to contribute a new tutorial you can learn more
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here: `PyTorch.org Tutorial Contribution Guide on
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Github <https://github.com/pytorch/tutorials/#contributing>`__
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GitHub <https://github.com/pytorch/tutorials/#contributing>`__
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Improving Documentation & Tutorials
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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@ -157,7 +157,7 @@ Binary Operators
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As you may have seen in the tutorial, :class:`MaskedTensor` also has binary operations implemented with the caveat
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that the masks in the two MaskedTensors must match or else an error will be raised. As noted in the error, if you
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need support for a particular operator or have proposed semantics for how they should behave instead, please open
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an issue on Github. For now, we have decided to go with the most conservative implementation to ensure that users
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an issue on GitHub. For now, we have decided to go with the most conservative implementation to ensure that users
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know exactly what is going on and are being intentional about their decisions with masked semantics.
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The available binary operators are:
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@ -594,7 +594,7 @@ all of the unconvertible ops in one go you can::
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The set is approximated because some ops may be removed during the conversion
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process and don't need to be converted. Some other ops may have partial support
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that will fail conversion with particular inputs, but this should give you a
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general idea of what ops are not supported. Please feel free to open Github Issues
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general idea of what ops are not supported. Please feel free to open GitHub Issues
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for op support requests.
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Frequently Asked Questions
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@ -10,7 +10,7 @@ torch.sparse
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.. warning::
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The PyTorch API of sparse tensors is in beta and may change in the near future.
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We highly welcome feature requests, bug reports and general suggestions as Github issues.
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We highly welcome feature requests, bug reports and general suggestions as GitHub issues.
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Why and when to use sparsity
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++++++++++++++++++++++++++++
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@ -40,7 +40,7 @@ Like many other performance optimization sparse storage formats are not
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always advantageous. When trying sparse formats for your use case
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you might find your execution time to decrease rather than increase.
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Please feel encouraged to open a Github issue if you analytically
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Please feel encouraged to open a GitHub issue if you analytically
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expected to see a stark increase in performance but measured a
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degradation instead. This helps us prioritize the implementation
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of efficient kernels and wider performance optimizations.
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@ -226,7 +226,7 @@ def foo(x, y, z=100):
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return x, y, z
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```
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2. To help understanding the BC/FC breakage changes, here are some FC breaking changes examples. The solution to resolve it is not there yet. If it's desired, please report it in either [PyTorch Forum](https://discuss.pytorch.org/) or [PyTorch Github](https://github.com/pytorch/pytorch). We will prioritize it accordingly.
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2. To help understanding the BC/FC breakage changes, here are some FC breaking changes examples. The solution to resolve it is not there yet. If it's desired, please report it in either [PyTorch Forum](https://discuss.pytorch.org/) or [PyTorch GitHub](https://github.com/pytorch/pytorch). We will prioritize it accordingly.
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- Adding new default argument:
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- Adding a new default argument not RIGHT BEFORE the out arguments which can be 0 or more.
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@ -283,4 +283,4 @@ This concludes our brief introduction to LT. Hopefully, you'll remember the main
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* It's really tricky to produce such graphs without overburdening a user too much. Think, torch.jit.script, torch.jit.trace! Also, think ifs, fors, "Lions, and Tigers, and Bears, Oh My" We digressed.
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Please give LT a try and tell us what you think on Github! We are **eager, not lazy** (haha!) to hear from you!
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Please give LT a try and tell us what you think on GitHub! We are **eager, not lazy** (haha!) to hear from you!
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