```
$ pip install tensorflow-cpu
```

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

*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)", "Release - Milestone", "Release - Release Candidate", "Release - Final", "Nightly Documentation"),
            model.buildTypes.map { it.name }

absl-py==2.1.0 \
    --hash=sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308 \
    --hash=sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \
    --hash=sha256:95c30d87a6c2cf89aa628b87398466840f0ad8652f88eb173125a6df8533fb8d \
    --hash=sha256:fb503b9e2fdd05609fbf557b916b4a7824171203701660f0c55bbf5a7a68713e
    # via -r requirements.in

absl-py==2.1.0 \
    --hash=sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308 \
    --hash=sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \
    --hash=sha256:95c30d87a6c2cf89aa628b87398466840f0ad8652f88eb173125a6df8533fb8d \
    --hash=sha256:fb503b9e2fdd05609fbf557b916b4a7824171203701660f0c55bbf5a7a68713e
    # via -r requirements.in

absl-py==2.1.0 \
    --hash=sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308 \
    --hash=sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \
    --hash=sha256:95c30d87a6c2cf89aa628b87398466840f0ad8652f88eb173125a6df8533fb8d \
    --hash=sha256:fb503b9e2fdd05609fbf557b916b4a7824171203701660f0c55bbf5a7a68713e
    # via -r requirements.in

absl-py==2.1.0 \
    --hash=sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308 \
    --hash=sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \
    --hash=sha256:95c30d87a6c2cf89aa628b87398466840f0ad8652f88eb173125a6df8533fb8d \
    --hash=sha256:fb503b9e2fdd05609fbf557b916b4a7824171203701660f0c55bbf5a7a68713e
    # via -r requirements.in

    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"),

    ```

    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.

   *
   * <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()}.

    // 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)