block_size, block_count * block_size, 0, fetcher);
  std::vector<char> out;
  // Read blocks from the cache, and verify the LRU behavior based on the
  // fetcher calls that the cache makes.
  calls.push_back(0);
  // Cache miss - drains an element from `calls`.
  TF_EXPECT_OK(ReadCache(&cache, "", 0, 1, &out));
  // Cache hit - does not drain an element from `calls`.

}

static bool SetTmpDir(const std::string& tmp_dir_) {
  ModularFileSystemTest::SetTmpDir(tmp_dir_);
  return true;
}

}  // namespace
}  // namespace tensorflow

// Due to the usages of flags for this manual test, we need a special `main` to
// ensure our flags are parsed properly as `testing::InitGoogleTest` silently
// ignores other flags. Furthermore, we need this to ensure that the DSO is

<div align="center">
  <img src="https://www.tensorflow.org/images/tf_logo_horizontal.png">
</div>

[![Python](https://img.shields.io/pypi/pyversions/tensorflow.svg)](https://badge.fury.io/py/tensorflow)
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        ops.
    *   Add `tf.image.psnr`, `tf.image.ssim`, `tf.image.ssim_multiscale`,
        `tf.image.image_gradients`, `tf.image.sobel_edges`.
    *   Add links to https://js.tensorflow.org.
    *   Fix non-uniformity of orthogonal matrices.
    *   Fix bug where multi-image Estimator eval summaries were not displayed
        correctly.

/usr/bin/$VERSION get-pip.py
/usr/bin/$VERSION -m pip install --no-cache-dir --upgrade pip

# Disable the cache dir to save image space, and install packages

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

  # Pulling an already-pulled container image will finish instantly, so
  # repeating the command costs nothing.
  docker pull "$TFCI_DOCKER_IMAGE" || sleep 15
  docker pull "$TFCI_DOCKER_IMAGE" || sleep 15
  docker pull "$TFCI_DOCKER_IMAGE"
fi 

if [[ "$TFCI_DOCKER_REBUILD_ENABLE" == 1 ]]; then
  DOCKER_BUILDKIT=1 docker build --cache-from "$TFCI_DOCKER_IMAGE" -t "$TFCI_DOCKER_IMAGE" $TFCI_DOCKER_REBUILD_ARGS

      liable to You for damages, including any direct, indirect, special,
      incidental, or consequential damages of any character arising as a
      result of this License or out of the use or inability to use the
      Work (including but not limited to damages for loss of goodwill,
      work stoppage, computer failure or malfunction, or any and all
      other commercial damages or losses), even if such Contributor

            echo "No running containers";
          else
            echo "Running container(s) found" && \
            docker stop $running_containers;
          fi
          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

            
            Re-apply the `build and push to gcr.io for staging` label to rebuild and push again. This comment will only be posted once.
      -
        name: Print image digest