try {
                            final SmbTransportImpl transport = tf.getTransportPool()
                                    .getSmbTransport(tf, dr.getServer(), 0, false,
                                            !tf.getCredentials().isAnonymous() && tf.getConfig().isSigningEnabled()
                                                    && tf.getConfig().isIpcSigningEnforced())

        # to tag names on gcr.io/tensorflow-sigs/build.
        # TF 2.9
        map sigbuild-r2.9 2.9-python3.9
        map sigbuild-r2.9-python3.8 2.9-python3.8
        map sigbuild-r2.9-python3.9 2.9-python3.9
        map sigbuild-r2.9-python3.10 2.9-python3.10
        # TF 2.10
        map sigbuild-r2.10 2.10-python3.9
        map sigbuild-r2.10-python3.8 2.10-python3.8

    *   Added a new boolean argument `allow_fast_lookup` to `tf.nn.embedding_lookup_sparse` and `tf.nn.safe_embedding_lookup_sparse`, which enables a simplified and typically faster lookup procedure.

*   `tf.data`

    *   `tf.data.Dataset.zip` now supports Python-style zipping, i.e. `Dataset.zip(a, b, c)`.

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
>>> import tensorflow as tf
>>> tf.add(1, 2).numpy()
3
>>> hello = tf.constant('Hello, TensorFlow!')
>>> hello.numpy()
b'Hello, TensorFlow!'

        final UniAddress dc = new UniAddress(addr);
        try (SmbTransportInternal trans = tf.getTransportPool()
                .getSmbTransport(tf, dc, 0, false, tf.hasDefaultCredentials() && tf.getConfig().isIpcSigningEnforced())
                .unwrap(SmbTransportInternal.class)) {
            if (!tf.hasDefaultCredentials()) {

typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch
keras-nightly ~= 3.10.0.dev
tb-nightly ~= 2.20.0.a

    public byte[] getChallenge(final CIFSContext tf, final Address dc) throws SmbException {
        return getChallenge(tf, dc, 0);
    }

    @Override
    public byte[] getChallenge(final CIFSContext tf, final Address dc, final int port) throws SmbException {
        try (SmbTransportInternal trans = tf.getTransportPool()

#     monolithic:       Build all TF C++ code into a single shared object.
#     dynamic_kernels:  Try to link all kernels dynamically (experimental).
#     dbg:              Build with debug info
#
# TF version options;
#     v2: Build TF v2
#
# Feature and Third party library support options:
#     xla:          Build TF with XLA
#     tpu:          Build TF with TPU support
#     cuda:         Build with CUDA support.

     * @param tf the CIFS context
     * @param domain the domain name to check
     * @return whether the given domain is trusted
     * @throws CIFSException if the operation fails
     */
    boolean isTrustedDomain(CIFSContext tf, String domain) throws CIFSException;

    /**
     * Get a connection to the domain controller for a given domain
     *
     * @param tf the CIFS context

typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch
keras-nightly ~= 3.10.0.dev
tb-nightly ~= 2.20.0.a