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[Doc] Update docs. (DeepRec-AI#120)
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CODEOWNERS

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CODE_OF_CONDUCT.md

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# TensorFlow Code of Conduct
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# DeepRec Code of Conduct
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In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, nationality, personal appearance, race, religion, or sexual identity and orientation.
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In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to make participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, nationality, personal appearance, race, religion, or sexual identity and orientation.
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## Our Standards
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* Conduct which could reasonably be considered inappropriate for the forum in
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which it occurs.
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All TensorFlow forums and spaces are meant for professional interactions, and any behavior which could reasonably be considered inappropriate in a professional setting is unacceptable.
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All DeepRec forums and spaces are meant for professional interactions, and any behavior which could reasonably be considered inappropriate in a professional setting is unacceptable.
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## Our Responsibilities
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## Scope
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This Code of Conduct applies to all content on tensorflow.org, TensorFlow’s GitHub organization, or any other official TensorFlow web presence allowing for community interactions, as well as at all official TensorFlow events, whether offline or online.
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This Code of Conduct applies to all content on DeepRec’s GitHub organization, or any other official DeepRec web presence allowing for community interactions, as well as at all official DeepRec events, whether offline or online.
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The Code of Conduct also applies within project spaces and in public spaces whenever an individual is representing TensorFlow or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account, or acting as an appointed or de facto representative at an online or offline event.
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The Code of Conduct also applies within project spaces and in public spaces whenever an individual is representing DeepRec or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account, or acting as an appointed or de facto representative at an online or offline event.
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## Conflict Resolution
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## Reporting Violations
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Violations of the Code of Conduct can be reported to TensorFlow’s Project
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Stewards, Edd Wilder-James ([email protected]) and Thea Lamkin
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([email protected]). The Project Steward will determine whether the Code of
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Conduct was violated, and will issue an appropriate sanction, possibly including
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a written warning or expulsion from the project, project sponsored spaces, or
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project forums. We ask that you make a good-faith effort to resolve your
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conflict via the conflict resolution policy before submitting a report.
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Violations of the Code of Conduct can be reported to DeepRec’s Project Stewards, Liu Tongxuan ([email protected]). The Project Steward will determine whether the Code of Conduct was violated, and will issue an appropriate sanction, possibly including a written warning or expulsion from the project, project sponsored spaces, or project forums. We ask that you make a good-faith effort to resolve your conflict via the conflict resolution policy before submitting a report.
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Violations of the Code of Conduct can occur in any setting, even those unrelated to the project. We will only consider complaints about conduct that has occurred within one year of the report.
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CONTRIBUTING.md

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- Read [contributing guidelines](CONTRIBUTING.md).
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- Read [Code of Conduct](CODE_OF_CONDUCT.md).
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- Ensure you have signed the [Contributor License Agreement (CLA)](https://cla.developers.google.com/).
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- Check if my changes are consistent with the [guidelines](https://github.com/tensorflow/tensorflow/blob/master/CONTRIBUTING.md#general-guidelines-and-philosophy-for-contribution).
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- Changes are consistent with the [Coding Style](https://github.com/tensorflow/tensorflow/blob/master/CONTRIBUTING.md#c-coding-style).
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- Run [Unit Tests](https://github.com/tensorflow/tensorflow/blob/master/CONTRIBUTING.md#running-unit-tests).
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- Ensure you have signed the [Contributor License Agreement (CLA)](https://cla-assistant.io/alibaba/DeepRec).
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- Check if my changes are consistent with the [guidelines](https://github.com/alibaba/DeepRec/blob/main/CONTRIBUTING.md#general-guidelines-and-philosophy-for-contribution).
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- Changes are consistent with the [Coding Style](https://github.com/alibaba/DeepRec/blob/main/CONTRIBUTING.md#c-coding-style).
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- Run [Unit Tests](https://github.com/alibaba/DeepRec/blob/main/CONTRIBUTING.md#running-unit-tests).
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## How to become a contributor and submit your own code
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Please fill out either the individual or corporate Contributor License Agreement (CLA).
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* If you are an individual writing original source code and you're sure you own the intellectual property, then you'll need to sign an [individual CLA](https://code.google.com/legal/individual-cla-v1.0.html).
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* If you work for a company that wants to allow you to contribute your work, then you'll need to sign a [corporate CLA](https://code.google.com/legal/corporate-cla-v1.0.html).
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* If you are an individual writing original source code and you're sure you own the intellectual property, then you'll need to sign an [individual CLA](https://cla-assistant.io/alibaba/DeepRec).
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* If you work for a company that wants to allow you to contribute your work, then you'll need to sign a [corporate CLA](https://cla-assistant.io/alibaba/DeepRec).
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Follow either of the two links above to access the appropriate CLA and instructions for how to sign and return it. Once we receive it, we'll be able to accept your pull requests.
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***NOTE***: Only original source code from you and other people that have signed the CLA can be accepted into the main repository.
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### Contributing code
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If you have improvements to TensorFlow, send us your pull requests! For those
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If you have improvements to DeepRec, send us your pull requests! For those
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just getting started, Github has a
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[how to](https://help.github.com/articles/using-pull-requests/).
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TensorFlow team members will be assigned to review your pull requests. Once the
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pull requests are approved and pass continuous integration checks, a TensorFlow
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DeepRec team members will be assigned to review your pull requests. Once the
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pull requests are approved and pass continuous integration checks, a DeepRec
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team member will apply `ready to pull` label to your change. This means we are
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working on getting your pull request submitted to our internal repository. After
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the change has been submitted internally, your pull request will be merged
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automatically on GitHub.
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If you want to contribute, start working through the TensorFlow codebase,
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If you want to contribute, start working through the DeepRec codebase,
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navigate to the
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[Github "issues" tab](https://github.com/tensorflow/tensorflow/issues) and start
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[Github "issues" tab](https://github.com/alibaba/DeepRec/issues) and start
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looking through interesting issues. If you are not sure of where to start, then
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start by trying one of the smaller/easier issues here i.e.
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[issues with the "good first issue" label](https://github.com/tensorflow/tensorflow/labels/good%20first%20issue)
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[issues with the "good first issue" label](https://github.com/alibaba/DeepRec/labels/good%20first%20issue)
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and then take a look at the
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[issues with the "contributions welcome" label](https://github.com/tensorflow/tensorflow/labels/stat%3Acontributions%20welcome).
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[issues with the "contributions welcome" label](https://github.com/alibaba/DeepRec/labels/stat%3Acontributions%20welcome).
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These are issues that we believe are particularly well suited for outside
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contributions, often because we probably won't get to them right now. If you
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decide to start on an issue, leave a comment so that other people know that
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### Contribution guidelines and standards
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Before sending your pull request for
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[review](https://github.com/tensorflow/tensorflow/pulls),
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[review](https://github.com/alibaba/DeepRec/pulls),
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make sure your changes are consistent with the guidelines and follow the
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TensorFlow coding style.
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DeepRec coding style.
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#### General guidelines and philosophy for contribution
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changes to lower the maintenance cost.
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* Bug fixes also generally require unit tests, because the presence of bugs
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* Keep API compatibility in mind when you change code in core TensorFlow,
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* Keep API compatibility in mind when you change code in core DeepRec,
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e.g., code in
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[tensorflow/core](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/core)
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[core](https://github.com/alibaba/DeepRec/tree/main/tensorflow/core)
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and
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[tensorflow/python](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/python).
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TensorFlow has reached version 1 and hence cannot make
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[python](https://github.com/alibaba/DeepRec/tree/main/tensorflow/python).
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DeepRec has reached version 1 and hence cannot make
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non-backward-compatible API changes without a major release. Reviewers of
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your pull request will comment on any API compatibility issues.
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* When you contribute a new feature to TensorFlow, the maintenance burden is
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(by default) transferred to the TensorFlow team. This means that the benefit
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* When you contribute a new feature to DeepRec, the maintenance burden is
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(by default) transferred to the DeepRec team. This means that the benefit
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* Full new features (e.g., a new op implementing a cutting-edge algorithm)
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* [C/C++ license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/op.cc#L1)
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* [Python license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/nn.py#L1)
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* [Java license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/java/src/main/java/org/tensorflow/Graph.java#L1)
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* [Go license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/go/operation.go#L1)
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* [Bash license example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/ci_build/ci_sanity.sh#L2)
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* [C/C++ license example](https://github.com/alibaba/DeepRec/blob/main/tensorflow/core/framework/op.cc#L1)
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* [Python license example](https://github.com/alibaba/DeepRec/blob/main/tensorflow/python/ops/nn.py#L1)
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* [Java license example](https://github.com/alibaba/DeepRec/blob/main/tensorflow/java/src/main/java/org/tensorflow/Graph.java#L1)
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* [Go license example](https://github.com/alibaba/DeepRec/blob/main/tensorflow/go/operation.go#L1)
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* [Bash license example](https://github.com/alibaba/DeepRec/blob/main/tensorflow/tools/ci_build/ci_sanity.sh#L2)
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* [HTML license example](https://github.com/tensorflow/tensorboard/blob/master/tensorboard/components/tf_backend/tf-backend.html#L2)
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* [JavaScript/TypeScript license example](https://github.com/tensorflow/tensorboard/blob/master/tensorboard/components/tf_backend/backend.ts#L1)
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Bazel BUILD files also need to include a license section, e.g.,
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[BUILD example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/BUILD#L61).
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[BUILD example](https://github.com/alibaba/DeepRec/blob/main/tensorflow/core/BUILD#L61).
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Changes to TensorFlow C++ code should conform to
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Changes to DeepRec C++ code should conform to
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[Google C++ Style Guide](https://google.github.io/styleguide/cppguide.html).
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Use `clang-tidy` to check your C/C++ changes. To install `clang-tidy` on ubuntu:16.04, do:
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Use `clang-tidy` to check your C/C++ changes. To install `clang-tidy` on ubuntu:18.04, do:
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Changes to DeepRec Python code should conform to
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[Google Python Style Guide](https://github.com/google/styleguide/blob/gh-pages/pyguide.md)
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retrieve DeepRec's custom style definition:
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wget -O /tmp/pylintrc https://raw.githubusercontent.com/alibaba/DeepRec/main/tensorflow/tools/ci_build/pylintrc
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#### Running unit tests
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There are two ways to run DeepRec unit tests.
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[CPU-only developer Dockerfile](https://github.com/alibaba/DeepRec/blob/main/tensorflow/tools/dockerfiles/dockerfiles/devel-cpu.Dockerfile)
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[GPU developer Dockerfile](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/dockerfiles/dockerfiles/devel-gpu.Dockerfile)
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[GPU developer Dockerfile](https://github.com/alibaba/DeepRec/blob/main/tensorflow/tools/dockerfiles/dockerfiles/devel-gpu.Dockerfile)
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Docker images e.g.,
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[devel](registry.cn-shanghai.aliyuncs.com/pai-dlc-share/deeprec-developer:deeprec-dev-cpu-py36-ubuntu18.04) and [devel-gpu](registry.cn-shanghai.aliyuncs.com/pai-dlc-share/deeprec-developer:deeprec-dev-gpu-py36-cu110-ubuntu18.04) for
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development to avoid installing the packages directly on your system (in
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which case remember to change directory from `/root` to `/tensorflow` once
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you get into the running container so `bazel` can find the `tensorflow`
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which case remember to change directory from `/root` to `/DeepRec` once
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you get into the running container so `bazel` can find the `DeepRec`
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2. Using Docker and DeepRec's CI scripts.
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[TensorFlow Builds](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/tools/ci_build)
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[DeepRec Builds](https://github.com/alibaba/DeepRec/tree/main/cibuild)
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for details.

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