# LLVM/Clang: https://apt.llvm.org/
apt-key adv --fetch-keys https://apt.llvm.org/llvm-snapshot.gpg.key

# Set up custom sources
cat >/etc/apt/sources.list.d/custom.list <<SOURCES
# More Python versions: Deadsnakes
deb http://ppa.launchpad.net/deadsnakes/ppa/ubuntu focal main
deb-src http://ppa.launchpad.net/deadsnakes/ppa/ubuntu focal main

# LLVM/Clang 17 repository

build --linkopt="-Wl,--undefined-version"

# Prevent double-compilation of some TF code, ref. b/183279666 (internal)
# > TF's gen_api_init_files has a genrule to run the core TensorFlow code
# > on the host machine. If we don't have --distinct_host_configuration=false,
# > the core TensorFlow code will be built once for the host and once for the
# > target platform.

```
(You can paste links or attach files by dragging & dropping them below)
- Provide links to your updated versions of the above two colab notebooks.
- Provide links to your TensorFlow model and (optionally) TensorFlow Lite Model.
```

#### Option B: Paste your code here or provide a link to a custom end-to-end colab

```

fi

# Note: the profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling

#
# Builds a devtoolset cross-compiler targeting manylinux2014 (glibc 2.17 / libstdc++ 4.8).

VERSION="$1"
TARGET="$2"

case "${VERSION}" in
devtoolset-9)
  LIBSTDCXX_VERSION="6.0.28"
  LIBSTDCXX_ABI="new"
  ;;
devtoolset-10)
  LIBSTDCXX_VERSION="6.0.28"
  LIBSTDCXX_ABI="new"
  ;;
*)
  echo "Usage: $0 {devtoolset-9|devtoolset-10} <target-directory> <arch>"

      - name: Build binary and run python tests on nightly for all python versions
        shell: bash
        run: |
          is_nightly=0 && tf_project_name='tf_ci_ext' && ${{ github.event_name == 'schedule' }} && is_nightly=1 && tf_project_name='tf_nightly_ci_ext'
          CI_DOCKER_BUILD_EXTRA_PARAMS="--build-arg py_major_minor_version=${{ matrix.pyver }} --build-arg is_nightly=${is_nightly} --build-arg tf_project_name=${tf_project_name}" \

   
   **1. Installing **TensorFlow-GPU** (TF) prebuilt binaries**
   
   
   Make sure you are using compatible TF and CUDA versions.
   Please refer following TF version and CUDA version compatibility table.
   
   | TF  | CUDA |
   
   | :-------------: | :-------------: |
   
   | 2.5.0  | 11.2 |
   
   | 2.4.0  | 11.0 |
   
   | 2.1.0 - 2.3.0  | 10.1 |

source "${BASH_SOURCE%/*}/utilities/setup.sh"

# Update the version numbers for Nightly only, then fetch the version numbers
# for choosing the final directory name. This adds "-devYYYYMMDD" to the end of
# the version string (.devYYYYMMDD for Python; see pypi.org/project/tf-nightly)
if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then
  tfrun python3 tensorflow/tools/ci_build/update_version.py --nightly
fi
source ci/official/utilities/get_versions.sh

}

void TF_GraphVersions(TF_Graph* graph, TF_Buffer* output_version_def,
                      TF_Status* status) {
  VersionDef versions;
  {
    mutex_lock l(graph->mu);
    versions = graph->graph.versions();
  }
  status->status = MessageToBuffer(versions, output_version_def);
}

TF_ImportGraphDefOptions* TF_NewImportGraphDefOptions() {

# the Python version set in "TFCI_PYTHON_VERSION" and use it as default.
# We enable this in the nightly and release builds because before uploading the
# wheels, we install them in a virtual environment and run some smoke tests on
# it. TFCI Mac VMs only have one Python version installed so we need to install
# the other versions manually.
if [[ "${TFCI_MACOS_PYENV_INSTALL_ENABLE}" == 1 ]]; then