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---
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name: Bug/Performance issue
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about: Use this template for reporting a bug or a performance issue.
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title: ''
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labels: 'bug'
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assignees: ''
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---
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<!--
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**Dubugging advice**
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[delete this section if it doesn't solve your issue]
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- Add a `--opset` flag with the highest possible opset you can use. Some ops only convert in higher opsets.
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- Try installing the latest tf2onnx from master. Some bug fixes might not have been released to PyPI. Run `pip uninstall tf2onnx` and `pip install git+https://github.com/onnx/tensorflow-onnx`
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- Try installing the latest tf2onnx from main. Some bug fixes might not have been released to PyPI. Run `pip uninstall tf2onnx` and `pip install git+https://github.com/onnx/tensorflow-onnx`
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- If using a saved model, use the Tensorflow `saved_model_cli` to determine the correct `--tag` and `--signature_def` flags to use. If the signature you need is not listed, use the `--concrete_function` flag to index into the model's defined functions.
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- If your model was made in tf1.x, try running tf2onnx in a venv with tensorflow 1.x installed. tf2.x should be able to read tf1 models, but sometimes there are bugs.
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- If your model was made in tf1.x, try running tf2onnx in a venv with tensorflow 1.x installed. tf2.x should be able to read tf1.x models, but sometimes there are bugs.
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-->
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**Describe the bug**
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A clear and concise description of what the bug is.
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<!-- Please describe a clear and concise description of what the bug is. -->
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**Urgency**
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If there are particular important use cases blocked by this or strict project-related timelines, please share more information and dates. If there are no hard deadlines, please specify none.
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<!-- If there are particular important use cases blocked by this or strict project-related timelines, please share more information and dates. If there are no hard deadlines, please specify none. -->
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**System information**
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- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
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- Tensorflow Version:
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- OS Platform and Distribution (e.g., Linux Ubuntu 18.04*):
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- TensorFlow Version:
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- Python version:
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- ONNX version (if applicable, e.g. 1.11*):
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- ONNXRuntime version (if applicable, e.g. 1.11*):
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**To Reproduce**
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Describe steps/code to reproduce the behavior. Please upload/link the model you are trying to convert if possible.
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<!-- Describe steps/code/command to reproduce the behavior. Please upload/link the model you are trying to convert if possible. -->
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**Screenshots**
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If applicable, add screenshots to help explain your problem.
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<!-- If applicable, add screenshots to help explain your problem. -->
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**Additional context**
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Add any other context about the problem here. If the issue is about a particular model, please share the model details as well to facilitate debugging.
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<!-- Add any other context about the problem here. If the issue is about a particular model, please share the model details as well to facilitate debugging. -->
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---
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name: Feature request
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about: Requests for new tf2onnx features
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title: ''
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labels: 'enhancement'
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assignees: ''
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---
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Before submitting your request, please review past submissions to ensure that it is not a duplicate of a known feature request.
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### Describe the feature request
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### Describe scenario use case

.github/ISSUE_TEMPLATE/operators.md

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---
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name: Missing Operator
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about: Operator that does not currently support in tf2onnx.
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title: ''
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labels: 'unsupported ops'
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assignees: ''
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---
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# New Operator
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### Describe the operator
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<!-- Why is this operator necessary? What does it accomplish? -->
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### Do you know this operator be constructed using existing ONNX operators?
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<!-- If so, why not add it as a function? -->
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### Is this operator used by any model currently? Which one?
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### Are you willing to contribute it? (Y/N)
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### Notes
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<!-- Any additional information -->

.github/ISSUE_TEMPLATE/question.md

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---
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name: Question
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about: Ask a question about the tf2onnx.
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title: ''
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labels: 'question'
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assignees: ''
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---
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# Ask a Question
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### Question
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<!-- Explain your question here. -->
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### Further information
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- Is this issue related to a specific model?
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**Model name**: <!-- *e.g. mnist* -->
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**Model opset**: <!-- *e.g. 17* -->
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### Notes
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<!-- Any additional information, code snippets. -->

CONTRIBUTING.md

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4. Make and checkin your changes along with unit tests
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5. git commit your changes
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6. git push origin HEAD
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7. To request merge into master send a pull request from the web ui
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7. To request merge into main send a pull request from the web ui
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https://github.com/onnx/tensorflow-onnx.
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Please see [Coding Conventions and Standards](http://google.github.io/styleguide/pyguide.html)
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# Licensing guidelines
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This project welcomes contributions and suggestions. Most contributions require you to
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agree to a Contributor License Agreement (CLA) declaring that you have the right to,
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and actually do, grant us the rights to use your contribution. For details, visit
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https://cla-assistant.io/onnx/tensorflow-onnx.
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When you submit a pull request, a CLA-bot will automatically determine whether you need
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to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the
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instructions provided by the bot. You will only need to do this once across all repositories using our CLA.
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This project welcomes contributions and suggestions. The contributions require you to
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agree the Developer Certificate of Origin (DCO) declaring that you have the right to,
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and actually do, grant us the rights to use your contribution.
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When you submit a pull request, a DCO-bot will automatically determine whether you need
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to provide a DCO and decorate the PR appropriately.
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You are ready to sign your code by using the `-s` flag during your commits.
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```sh
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git commit -s
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```
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# Code of conduct
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This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).

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