streaming compression due to its stability and performance.

This algorithm is specifically optimized for machine generated content.
Write throughput is typically at least 500MB/s per CPU core,
and scales with the number of available CPU cores.
Decompression speed is typically at least 1GB/s.

This means that in cases where raw IO is below these numbers
compression will not only reduce disk usage but also help increase system throughput.

```bash
tensorflow/tools/ci_build/ci_build.sh CPU tensorflow/tools/ci_build/ci_sanity.sh
```

This will catch most license, Python coding style and BUILD file issues that
may exist in your changes.

#### Running unit tests

There are two ways to run TensorFlow unit tests.

1.  Using tools and libraries installed directly on your system.

    Refer to the

mkdir -p ~/.gradle/init.d && cp -v $WORKSPACE/.ci/init.gradle ~/.gradle/init.d
if [ "$(uname -m)" = "arm64" ] || [ "$(uname -m)" = "aarch64" ]; then
   MAX_WORKERS=16
elif [ -f /proc/cpuinfo ]; then
   MAX_WORKERS=`grep '^cpu\scores' /proc/cpuinfo  | uniq | sed 's/\s\+//g' |  cut -d':' -f 2`
else
   if [[ "$OSTYPE" == "darwin"* ]]; then
      MAX_WORKERS=`sysctl -n hw.physicalcpu | sed 's/\s\+//g'`
   else
      echo "Unsupported OS Type: $OSTYPE"

        append(buf, "open", () -> processProbe.getOpenFileDescriptorCount()).append(',');
        append(buf, "max", () -> processProbe.getMaxFileDescriptorCount());
        buf.append("},");
        buf.append("\"cpu\":{");
        append(buf, "percent", () -> processProbe.getProcessCpuPercent()).append(',');
        append(buf, "total", () -> processProbe.getProcessCpuTotalTime());
        buf.append("},");

TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=macos_arm64
TFCI_BUILD_PIP_PACKAGE_WHEEL_NAME_ARG="--repo_env=WHEEL_NAME=tensorflow"
TFCI_INDEX_HTML_ENABLE=1
TFCI_LIB_SUFFIX="-cpu-darwin-arm64"
TFCI_MACOS_BAZEL_TEST_DIR_ENABLE=1
TFCI_MACOS_BAZEL_TEST_DIR_PATH="/Volumes/BuildData/bazel_output"
TFCI_OUTPUT_DIR=build_output
TFCI_WHL_BAZEL_TEST_ENABLE=1
TFCI_WHL_SIZE_LIMIT=245M

        this.delayMillisForWaitingNewUrl = delayMillisForWaitingNewUrl;
    }

    /**
     * Delays the crawler while waiting for new URLs to be available.
     * This method calibrates CPU load, checks crawler status, applies
     * interval control rules, and then calls the parent implementation.
     * All operations are wrapped in exception handling to ensure robustness
     * in test and production environments.

      }
    };

    public abstract Queue<Integer> create(Comparator<Integer> comparator);
  }

  /**
   * Does a CPU intensive operation on Integer and returns a BigInteger Used to implement an
   * ordering that spends a lot of cpu.
   */
  static class ExpensiveComputation implements Function<Integer, BigInteger> {
    @Override
    public BigInteger apply(Integer from) {

      }
    };

    public abstract Queue<Integer> create(Comparator<Integer> comparator);
  }

  /**
   * Does a CPU intensive operation on Integer and returns a BigInteger Used to implement an
   * ordering that spends a lot of cpu.
   */
  static class ExpensiveComputation implements Function<Integer, BigInteger> {
    @Override
    public BigInteger apply(Integer from) {

  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  ASSERT_EQ(2, TFE_TensorDebugInfoOnDeviceNumDims(debug_info));
  // Shape is the same for CPU tensors.
  EXPECT_EQ(3, TFE_TensorDebugInfoOnDeviceDim(debug_info, 0));
  EXPECT_EQ(2, TFE_TensorDebugInfoOnDeviceDim(debug_info, 1));

  TFE_DeleteTensorDebugInfo(debug_info);
  TFE_DeleteTensorHandle(h);

concurrency:
  group: ${{ github.workflow }}-${{ github.head_ref || github.ref }}
  # Don't cancel in-progress jobs for master branches.
  cancel-in-progress: ${{ github.ref != 'master' }}

jobs:
  #build-and-test-linux-x86-cpu:
  #  uses: ./.github/workflows/build-reusable.yml
  #  with:
  #    runner: 'linux-x86-n2-16'
  #    tfci: 'py313,linux_x86,rbe'

  #build-and-test-linux-x86-cuda:
  #  uses: ./.github/workflows/build-reusable.yml