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  1. README.md

    ```shell
    $ python
    ```
    
    ```python
    >>> import tensorflow as tf
    >>> tf.add(1, 2).numpy()
    3
    >>> hello = tf.constant('Hello, TensorFlow!')
    >>> hello.numpy()
    b'Hello, TensorFlow!'
    ```
    
    For more examples, see the
    [TensorFlow tutorials](https://www.tensorflow.org/tutorials/).
    
    ## Contribution guidelines
    
    **If you want to contribute to TensorFlow, be sure to review the
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  2. ci/official/requirements_updater/README.md

    system-installed Python packages. \
    Instead, an independent Python toolchain is registered, ensuring the right
    dependencies are always used. \
    See https://github.com/bazelbuild/rules_python/ for more details.
    
    ### Specifying the Python version
    
    Note: Only a number of minor Python versions are supported at any given time.
    
    By default, the lowest supported version is used.
    
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  3. ci/official/README.md

    1. Creating a PR and observing the presubmit test results
    2. Running the CI scripts locally, as explained below
    3. **Google employees only**: Google employees can use an internal-only tool
    called "MLCI" that makes testing more convenient: it can execute any full CI job
    against a pending change. Search for "MLCI" internally to find it.
    
    You may invoke a CI script of your choice by following these instructions:
    
    ```bash
    cd tensorflow-git-dir
    
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  4. tensorflow/c/experimental/ops/README.md

    category names correspond to generated source file names, and should be
    consistent with the original source files registering each operator. For example
    since `REGISTER_OP("MatMul")` appears in ***core/math_ops.cc***, the "MatMul"
    operator in the script should be in the "math" category, and it will be
    generated in the output file `c/experimental/ops/math_ops.cc`.
    
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