fi
          docker container prune -f
      - name: Clean repository
        shell: bash
        run: find /home/ubuntu/actions-runner/_work/tensorflow/tensorflow/. -name . -o -prune -exec sudo rm -rf -- {} + || true
      - name: Checkout repository
        uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
      - name: Build binary and run python tests
        shell: bash
        run: |

RUN New-ItemProperty -Path HKLM:\SYSTEM\CurrentControlSet\Control\FileSystem \
        -Name LongPathsEnabled -Value 1 -PropertyType DWORD -Force

# Install Visual C++ Redistributable for Visual Studio 2015-2022.
RUN New-Item -Path "C:/" -Name "TEMP" -ItemType "directory"; \
    Invoke-WebRequest "https://aka.ms/vs/17/release/vc_redist.x64.exe" \
        -OutFile C:/TEMP/vc_redist.x64.exe -UseBasicParsing; \

limitations under the License.
==============================================================================*/
#include "tensorflow/c/experimental/filesystem/plugins/gcs/gcs_helper.h"

#include <stdio.h>

#include <fstream>
#include <string>
#include <utility>

TempFile::TempFile(const std::string& temp_file_name, std::ios::openmode mode)
    : std::fstream(temp_file_name, mode), name_(temp_file_name) {}

limitations under the License.
==============================================================================*/

#include <limits.h>
#include <memory.h>
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <unistd.h>

#ifdef _WIN32
#include <process.h>
#endif

#include "tensorflow/c/c_api.h"
#include "tensorflow/c/c_api_experimental.h"

          docker container prune -f
          docker image prune -af
      - name: Clean repository
        shell: bash
        run: find /home/ubuntu/actions-runner/_work/tensorflow/tensorflow/. -name . -o -prune -exec sudo rm -rf -- {} + || true
      - name: Checkout repository for nightly (skipped for releases)
        if: ${{ github.event_name == 'schedule' }}
        uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1

          fi
          docker container prune -f
      - name: Clean repository
        shell: bash
        run: find /home/ubuntu/actions-runner/_work/tensorflow/tensorflow/. -name . -o -prune -exec sudo rm -rf -- {} + || true
      - name: Checkout repository for nightly (skipped for releases)
        if: ${{ github.event_name == 'schedule' }}
        uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1

*   **Windows users:** Officially-released `tensorflow` Pip packages are now
    built with Visual Studio 2019 version 16.4 in order to take advantage of the
    new `/d2ReducedOptimizeHugeFunctions` compiler flag. To use these new
    packages, you must install "Microsoft Visual C++ Redistributable for Visual
    Studio 2015, 2017 and 2019", available from Microsoft's website

          docker container prune -f
          docker image prune -af
      - name: Clean repository
        shell: bash
        run: find /home/ubuntu/actions-runner/_work/tensorflow/tensorflow/. -name . -o -prune -exec sudo rm -rf -- {} + || true
      - name: Checkout repository for nightly (skipped for releases)
        if: ${{ github.event_name == 'schedule' }}
        uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1

running the `tf.train.Server`.

## Untrusted inputs during training and prediction

TensorFlow supports a wide range of input data formats. For example it can
process images, audio, videos, and text. There are several modules specialized
in taking those formats, modifying them, and/or converting them to intermediate
formats that can be processed by TensorFlow.

# have Bazelisk pre-installed. "TFCI_MACOS_INSTALL_BAZELISK_URL" contains the
# link to the Bazelisk binary which needs to be downloaded.
if [[ "${TFCI_MACOS_INSTALL_BAZELISK_ENABLE}" == 1 ]]; then
  sudo wget --no-verbose -O "/usr/local/bin/bazel" "${TFCI_MACOS_INSTALL_BAZELISK_URL}"
  chmod +x "/usr/local/bin/bazel"
fi

# "TFCI_MACOS_UPGRADE_PYENV_ENABLE" is used to decide if we need to upgrade the