```
 pip install tensorflow-cpu
```

To update TensorFlow to the latest version, add the `--upgrade` flag to the
commands above.

*Nightly binaries are available for testing using the
[tf-nightly](https://pypi.python.org/pypi/tf-nightly) and
[tf-nightly-cpu](https://pypi.python.org/pypi/tf-nightly-cpu) packages on PyPI.*

#### *Try your first TensorFlow program*

```shell
$ python
```

```python

        assertEquals(
            listOf(
                "SanityCheck",
                "Nightly Snapshot",
                "Nightly Snapshot (from QuickFeedback)",
                "Nightly Snapshot (from QuickFeedback) - Check Ready",
                "Nightly Snapshot (from QuickFeedback) - Upload",
                "Nightly Snapshot (from QuickFeedback) - Promote",
                "Publish Branch Snapshot (from Quick Feedback)",

    ```

    This will run it using your installed version of TensorFlow. To be sure
    you're running the same code that you're testing:

    *   Use an up to date [tf-nightly](https://pypi.org/project/tf-nightly/)
        `pip install -U tf-nightly`
    *   Rebase your pull request onto a recent pull from
        [TensorFlow's](https://github.com/tensorflow/tensorflow) master branch.

    PULL_REQUEST_FEEDBACK("Pull Request Feedback", "Run various functional tests", "PullRequestFeedback"),
    READY_FOR_NIGHTLY(
        "Ready for Nightly",
        "Rerun tests in different environments / 3rd party components",
        "ReadyforNightly",
    ),
    READY_FOR_RELEASE("Ready for Release", "Once a day: Rerun tests in more environments", "ReadyforRelease"),

  /**
   * Adds the given values to the dataset.
   *
   * @param values a series of values, which will be converted to {@code double} values (this may
   *     cause loss of precision for longs of magnitude over 2^53 (slightly over 9e15))
   */
  public void addAll(long... values) {
    for (long value : values) {
      add(value);
    }
  }

  /**

 * [application interceptor][OkHttpClient.interceptors] or as a [OkHttpClient.networkInterceptors].
 *
 * The format of the logs created by this class should not be considered stable and may
 * change slightly between releases. If you need a stable logging format, use your own interceptor.
 */
class HttpLoggingInterceptor
  @JvmOverloads
  constructor(
    private val logger: Logger = Logger.DEFAULT,
  ) : Interceptor {

            score -= 20;

        // Adjust based on interface capabilities
        score += localInterface.getScore() / 100;
        score += remoteInterface.getScore() / 100;

        // Prefer primary channel slightly
        if (isPrimary)
            score += 10;

        // Penalize channels with many pending operations
        score -= (int) getRequestsPending();

        return Math.max(0, score);
    }

    // up exactly as many bits as can be represented in the significand (24 for float, 53 for
    // double). That final 0 should be rounded up to 1 because the remaining bits make that number
    // slightly nearer.
    long floatConversionTest = 0xfffffe8000000002L;
    long doubleConversionTest = 0xfffffffffffff402L;

    for (long i = -3; i <= 3; i++) {
      testLongsBuilder
          .add(i)

   *
   * @param values a series of values, which will be converted to {@code double} values (this may
   *     cause loss of precision for longs of magnitude over 2^53 (slightly over 9e15))
   */
  public static Stats of(long... values) {
    StatsAccumulator accumulator = new StatsAccumulator();
    accumulator.addAll(values);
    return accumulator.snapshot();
  }

  /**

   *
   * <p><b>Performance note:</b> When feasible, {@code initialCapacity} should be the exact number
   * of values that will be added, if that knowledge is readily available. It is better to guess a
   * value slightly too high than slightly too low. If the value is not exact, the {@link
   * ImmutableLongArray} that is built will very likely occupy more memory than strictly necessary;
   * to trim memory usage, build using {@code builder.build().trimmed()}.