ProjectionInImmediateArgumentToSupertypeImpl(
            firDiagnostic as KtPsiDiagnostic,
            token,
        )
    }
    add(FirErrors.INCONSISTENT_TYPE_PARAMETER_VALUES) { firDiagnostic ->
        InconsistentTypeParameterValuesImpl(
            firSymbolBuilder.classifierBuilder.buildTypeParameterSymbol(firDiagnostic.a),

    dispatch to logical ops. This brings them more in line with Python and NumPy
    behavior.
*   Adds `tf.SparseTensor.with_values`. This returns a new SparseTensor with the
    same sparsity pattern, but with new provided values. It is similar to the
    `with_values` function of `RaggedTensor`.
*   Adds `StatelessCase` op, and uses it if none of case branches has stateful
    ops.

            testJvmVendorParameter,
            JvmVendor.openjdk.name,
            display = ParameterDisplay.PROMPT,
            description = "Java vendor to run the test with",
            options = JvmVendor.values().map { it.displayName to it.name }
        )
        text(
            testTaskOptionsParameterName,
            "",
            display = ParameterDisplay.PROMPT,
            allowEmpty = true,

        leftOperandPsi: KtExpression
    ): KtPartiallyAppliedFunctionSymbol<KtFunctionSymbol>? {
        // The new value is a call to the appropriate operator function.
        val operationCall = fir.rValue as? FirFunctionCall ?: getInitializerOfReferencedLocalVariable(fir.rValue) ?: return null
        return operationCall.toPartiallyAppliedSymbol(leftOperandPsi)
    }

    ```Python hl_lines="80-83"
    {!> ../../../docs_src/security/tutorial003.py!}
    ```

#### About `**user_dict`

`UserInDB(**user_dict)` means:

*Pass the keys and values of the `user_dict` directly as key-value arguments, equivalent to:*

```Python
UserInDB(
    username = user_dict["username"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],

"istiod{{- if not (eq .Values.revision "") }}-{{ .Values.revision }}{{- end }}" successfully installed!

To learn more about the release, try:
  $ helm status {{ .Release.Name }} -n {{ .Release.Namespace }}
  $ helm get all {{ .Release.Name }} -n {{ .Release.Namespace }}

Next steps:
{{- if (eq .Values.profile "ambient") }}
  * Get started with ambient: https://istio.io/latest/docs/ops/ambient/getting-started/

Common examples of CPU bound operations are things that require complex math processing.

For example:

* **Audio** or **image processing**.
* **Computer vision**: an image is composed of millions of pixels, each pixel has 3 values / colors, processing that normally requires computing something on those pixels, all at the same time.

    'full_name': None,
}
```

#### Unwrapping a `dict`

If we take a `dict` like `user_dict` and pass it to a function (or class) with `**user_dict`, Python will "unwrap" it. It will pass the keys and values of the `user_dict` directly as key-value arguments.

So, continuing with the `user_dict` from above, writing:

```Python
UserInDB(**user_dict)
```

would result in something equivalent to:

```Python
UserInDB(

    "name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

!!! info
    `**second_user_data` means:

    Pass the keys and values of the `second_user_data` dict directly as key-value arguments, equivalent to: `User(id=4, name="Mary", joined="2018-11-30")`

### Editor support

    ignoreIoExceptions {
      shutdown(connectionCode)
    }

    var streamsToClose: Array<Http2Stream>? = null
    this.withLock {
      if (streams.isNotEmpty()) {
        streamsToClose = streams.values.toTypedArray()
        streams.clear()
      }
    }

    streamsToClose?.forEach { stream ->
      ignoreIoExceptions {
        stream.close(streamCode, cause)
      }
    }