&arrived, &executed, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

  // Create a variable handle placed on the custom device.
  std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> op(
      TFE_NewOp(context.get(), "VarHandleOp", status.get()), TFE_DeleteOp);

Angenommen, Ihre Datei heißt `myapp.py`.

Wenn Sie sie mit folgendem Befehl ausführen:

<div class="termy">

```console
$ python myapp.py
```

</div>

dann hat in Ihrer Datei die interne Variable `__name__`, die von Python automatisch erstellt wird, als Wert den String `"__main__"`.

Daher wird der Abschnitt:

```Python
    uvicorn.run(app, host="0.0.0.0", port=8000)
```

ausgeführt.

---

  bool HasTensor(const std::string& name) const;
  const std::string DebugString() const;

  // Returns a map from variable names to their shapes.  Slices of a partitioned
  // tensor are combined into a single entry.
  const TensorSliceReader::VarToShapeMap& GetVariableToShapeMap() const;

  // Returns a map from variable names to their data types.  Slices of a
  // partitioned tensor are combined into a single entry.

      if (values.hasAnyNonFinite()) {
        assertWithMessage("population covariance of %s", values).that(populationCovariance).isNaN();
        assertWithMessage("population covariance by addAll(PairedStats) of %s", values)
            .that(populationCovarianceByAddAllPartitionedPairedStats)
            .isNaN();
      } else {
        assertWithMessage("population covariance of %s", values)
            .that(populationCovariance)

  """Set boolean action_env variable.

  Ask user if query_item will be enabled. Default is used if no input is given.
  Set environment variable and write to .bazelrc.

  Args:
    environ_cp: copy of the os.environ.
    var_name: string for name of environment variable, e.g. "TF_NEED_CUDA".
    query_item: string for feature related to the variable, e.g. "CUDA for
      Nvidia GPUs".

       * Refer [windows setup guide](https://www.tensorflow.org/install/gpu#windows_setup).
     * If you have above configuration and using _**Ubuntu/Linux**_ platform -
       * Try adding the CUDA, CUPTI, and cuDNN installation directories to the $LD_LIBRARY_PATH environment variable.
       * Refer [linux setup guide](https://www.tensorflow.org/install/gpu#linux_setup).

        WITH_CONFIG // configuration provided via StaticJAASConfiguration
    }

    private JAASAuthenticator buildAuthenticator(SubjectVariant variant) {
        switch (variant) {
        case DEFAULT_WITH_PS: {
            JAASAuthenticator a = new JAASAuthenticator();
            // Provide a preset Subject so the getSubject() path uses the (serviceName, ps, this) constructor

#### More details { #more-details }

Let's say your file is named `myapp.py`.

If you run it with:

<div class="termy">

```console
$ python myapp.py
```

</div>

then the internal variable `__name__` in your file, created automatically by Python, will have as value the string `"__main__"`.

So, the section:

```Python
    uvicorn.run(app, host="0.0.0.0", port=8000)
```

will run.

---

	errSFTPLDAPNotEnabled     = errors.New("ldap authentication is not enabled")
)

// if the sftp parameter --trusted-user-ca-key is set, then
// the final form of the key file will be set as this variable.
var globalSFTPTrustedCAPubkey ssh.PublicKey

// https://cs.opensource.google/go/x/crypto/+/refs/tags/v0.22.0:ssh/common.go;l=46
// preferredKexAlgos specifies the default preference for key-exchange

 * It supports both regular deployment and Docker container environments.
 *
 */
public class ResourceUtil {
    /** Environment variable name for overriding the configuration path */
    private static final String FESS_OVERRIDE_CONF_PATH = "FESS_OVERRIDE_CONF_PATH";

    /** Environment variable name for specifying the application type */
    private static final String FESS_APP_TYPE = "FESS_APP_TYPE";