name: TensorFlow Lite Other Issue description: Use this template to report any
issue in TensorFlow Lite that is not about Converters, Play Services or Ops
body: - type: dropdown id: issue-type attributes: label: Issue Type description:
What type of issue would you like to report? multiple: false options: - Bug -
Build/Install - Performance - Support - Feature Request - Documentation Feature
Request - Documentation Bug - Others validations: required: true - type:

Note: Only a number of minor Python versions are supported at any given time.

By default, the lowest supported version is used.

To set a different version, use the `TF_PYTHON_VERSION` environment variable,
e.g.

```
export TF_PYTHON_VERSION=3.11
```

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

```
--repo_env=TF_PYTHON_VERSION=3.11
```

## Requirements updater

#      compilers, etc. can cause undefined behavior such as build failures
#      or tests passing incorrectly.
#    - Automatic LLVM updates are known to extend build time even with
#      the cache; this is unavoidable.
export TFCI=py311,linux_x86,public_cache,disk_cache

# Recommended: Configure Docker. (Linux only)
#
#   TF uses hub.docker.com/r/tensorflow/build containers for CI,

    bazel by doing as follows:

    ```bash
    export flags="--config=opt -k"
    ```

    If the tests are to be run on the GPU, add CUDA paths to LD_LIBRARY_PATH and
    add the `cuda` option flag

    ```bash
    export LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH"
    export flags="--config=opt --config=cuda -k"
    ```

outside of the safe formats, etc.) are not treated as vulnerabilities..

### Reporting process

Please use [Google Bug Hunters reporting form](https://g.co/vulnz) to report
security vulnerabilities. Please include the following information along with
your report:

  - A descriptive title
  - Your name and affiliation (if any).
  - A description of the technical details of the vulnerabilities.

*   `tf.estimator`:
    *   `Estimator`s now use custom savers included in `EstimatorSpec` scaffolds
        for saving SavedModels during export.
    *   `EstimatorSpec` will now add a default prediction output for export if
        no `export_output` is provided, eliminating the need to explicitly
        include a `PredictOutput` object in the `model_fn` for simple use-cases.

# -------------------------------------------

# TensorFlow uses several libraries that may also be used by applications
# linking against the C and C++ APIs (such as libjpeg).  When we create
# the shared library, only export the core TF API functions to avoid
# causing library conflicts (e.g., those reported in github issue 1924).
# On Linux, tell the linker (-Wl,<option>) to use a version script that
# excludes all but a subset of function names.

# Do not print anything if this is not being used interactively
[ -z "$PS1" ] && return

# Set up attractive prompt
export PS1="\[\e[31m\]tf-docker\[\e[m\] \[\e[33m\]\w\[\e[m\] > "
export TERM=xterm-256color
alias grep="grep --color=auto"
alias ls="ls --color=auto"
# Fix nvidia-docker

# Suite of verification tests for the SINGLE TensorFlow wheel in /tf/pkg
# or whatever path is set as $TF_WHEEL.

setup_file() {
    cd /tf/pkg
    if [[ -z "$TF_WHEEL" ]]; then
        export TF_WHEEL=$(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