"five", 5,
            "six", 6,
            "seven", 7,
            "eight", 8),
        "one",
        1,
        "two",
        2,
        "three",
        3,
        "four",
        4,
        "five",
        5,
        "six",
        6,
        "seven",
        7,
        "eight",
        8);
    assertMapEquals(
        ImmutableMap.of(
            "one", 1,

```
$ 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

   * perform better than its longhand equivalent, but should not perform worse.
   *
   * @since 12.0
   */
  HashCode hashInt(int input);

  /**
   * Shortcut for {@code newHasher().putLong(input).hash()}; returns the hash code for the given
   * {@code long} value, interpreted in little-endian byte order. The implementation <i>might</i>

- Nightly builds:
  - [Linux CPU-only](https://storage.googleapis.com/tensorflow-nightly/github/tensorflow/lib_package/libtensorflow-cpu-linux-x86_64.tar.gz)
  - [Linux GPU](https://storage.googleapis.com/tensorflow-nightly/github/tensorflow/lib_package/libtensorflow-gpu-linux-x86_64.tar.gz)

This includes, for example:

* Email notifications sent after performing an action:
    * As connecting to an email server and sending an email tends to be "slow" (several seconds), you can return the response right away and send the email notification in the background.
* Processing data:

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

    triggerName = "ReadyforNightly",
    vcsRootId = gradlePromotionBranches
) {
    init {
        id("Promotion_Nightly")
        name = "Nightly Snapshot"
        description = "Promotes the latest successful changes on '${branch.branchName}' from Ready for Nightly as a new nightly snapshot"

        triggers {
            branch.nightlyPromotionTriggerHour?.let { triggerHour ->
                schedule {

     Each Contributor represents that the Contributor believes its Contributions
     are its original creation(s) or it has sufficient rights to grant the
     rights to its Contributions conveyed by this License.

2.6. Fair Use

     This License is not intended to limit any rights You have under applicable
     copyright doctrines of fair use, fair dealing, or other equivalents.

2.7. Conditions