export TF_WHEEL=$(find /tf/pkg -iname "*.whl")
    fi
}

teardown_file() {
    rm -rf /tf/venv
}

@test "Wheel is manylinux2014 (manylinux_2_17) compliant" {
    python3 -m auditwheel show "$TF_WHEEL" > audit.txt
    grep --quiet -zoP 'is consistent with the following platform tag:\n"manylinux_2_17_(aarch|x86_)64"\.' audit.txt
}

@test "Wheel conforms to upstream size limitations" {

    git config --system protocol.file.allow always

    # Note that you could generate a list of all the affected targets with e.g.:
    # bazel query $(paste -sd "+" $BATS_FILE_TMPDIR/changed_files) --keep_going
    # Only shows Added, Changed, Modified, Renamed, and Type-changed files
    if [[ "$(git rev-parse --abbrev-ref HEAD)" == "pull_branch" ]]; then
        # TF's CI runs 'git fetch origin "pull/PR#/merge:pull_branch"'

FROM mcr.microsoft.com/dotnet/framework/sdk:4.8-windowsservercore-ltsc2019

# Set default powershell policy for this script (ProgressPreference='SilentlyContinue' makes
# downloads with Invoke-WebRequest not show the progress bar and is MUCH faster).
SHELL ["powershell.exe", "-ExecutionPolicy", "Bypass", "-Command", "$ErrorActionPreference='Stop'; $ProgressPreference='SilentlyContinue'; $VerbosePreference = 'Continue';"]

    [guidelines](#general-guidelines-and-philosophy-for-contribution).
-   Changes are consistent with the [Coding Style](#c-coding-style).
-   Run the [unit tests](#running-unit-tests).

## How to become a contributor and submit your own code

![Screen Shot 2022-08-30 at 7 27 04 PM](https://user-images.githubusercontent.com/42785357/187579207-9924eb32-da31-47bb-99f9-d8bf1aa238ad.png)

### Typical Pull Request Workflow -

**1. New PR**

```

To specify the file via a Bazel command argument, use the following:

```
--repo_env=REQUIREMENTS_FILE_NAME=my_requirements.in
```

### How to run the updater

```
bash updater.sh
```

## How to add a new Python version

Note: Updating the
[rules-python](https://github.com/bazelbuild/rules_python/releases) version may
be required before going through the steps below. This is due to the new Python

2)  Reference [TensorFlow Lite Model Colab](https://colab.research.google.com/gist/ymodak/0dfeb28255e189c5c48d9093f296e9a8/tensorflow-lite-debugger-colab.ipynb): Demonstrate how to convert your TF model to a TF Lite model (with quantization, if used) and run TFLite Inference (if possible).

```

-   Different Python versions
-   Linux, MacOS, and Windows machines (these pool definitions are internal)
-   x86 and arm64
-   CPU-only, or with NVIDIA CUDA support (Linux only), or with TPUs

## How to Test Your Changes to TensorFlow

You may check how your changes will affect TensorFlow by:

1. Creating a PR and observing the presubmit test results
2. Running the CI scripts locally, as explained below

        `tf.Variable`s.
    *   Add NUMA-aware MapAndBatch dataset.
    *   Deprecate `tf.data.Dataset.make_one_shot_iterator()` in V1, removed it
        from V2, and added tf.compat.v1.data.make_one_shot_iterator()`.
    *   Deprecate `tf.data.Dataset.make_initializable_iterator()` in V1, removed
        it from V2, and added `tf.compat.v1.data.make_initializable_iterator()`.

    how we can reproduce your findings. For memory corruption triggerable in
    TensorFlow models, please demonstrate an exploit against one of Alphabet's
    models in <https://tfhub.dev/>
  - An explanation of who can exploit this vulnerability, and what they gain
    when doing so. Write an attack scenario that demonstrates how your issue

    visibility = ["//visibility:public"],
)

# Sometimes Bazel reports darwin_x86_64 as "darwin" and sometimes as
# "darwin_x86_64". The former shows up when building on a Mac x86_64 host for a Mac x86_64 target.
# The latter shows up when cross-compiling for Mac x86_64 from a Mac ARM machine and in internal
# Google builds.
config_setting(
    name = "macos_x86_64_default",
    constraint_values = if_google(