// +k8s:deepcopy-gen=true
// +k8s:openapi-gen=true
message Quantity {
  optional string string = 1;
}

// QuantityValue makes it possible to use a Quantity as value for a command
// line parameter.
//
// +protobuf=true
// +protobuf.embed=string
// +protobuf.options.marshal=false
// +protobuf.options.(gogoproto.goproto_stringer)=false
// +k8s:deepcopy-gen=true
message QuantityValue {

secret can then be passed to Helm using a values file or the `--set` parameter: ``` trustedCertsSecret: "minio-trusted-certs" or --set trustedCertsSecret=minio-trusted-certs ``` ### Create buckets after install Install the chart, specifying the buckets you want to create after install: ```bash helm install --set buckets[0].name=bucket1,buckets[0].policy=none,buckets[0].purge=false minio/minio ``` Description of the configuration parameters used above - - `buckets[].name` - name of the bucket to create,...

secret can then be passed to Helm using a values file or the `--set` parameter: ``` trustedCertsSecret: "minio-trusted-certs" or --set trustedCertsSecret=minio-trusted-certs ``` ### Create buckets after install Install the chart, specifying the buckets you want to create after install: ```bash helm install --set buckets[0].name=bucket1,buckets[0].policy=none,buckets[0].purge=false minio/minio ``` Description of the configuration parameters used above - - `buckets[].name` - name of the bucket to create,...

secret can then be passed to Helm using a values file or the `--set` parameter: ``` trustedCertsSecret: "minio-trusted-certs" or --set trustedCertsSecret=minio-trusted-certs ``` ### Create buckets after install Install the chart, specifying the buckets you want to create after install: ```bash helm install --set buckets[0].name=bucket1,buckets[0].policy=none,buckets[0].purge=false minio/minio ``` Description of the configuration parameters used above - - `buckets[].name` - name of the bucket to create,...

secret can then be passed to Helm using a values file or the `--set` parameter: ``` trustedCertsSecret: "minio-trusted-certs" or --set trustedCertsSecret=minio-trusted-certs ``` ### Create buckets after install Install the chart, specifying the buckets you want to create after install: ```bash helm install --set buckets[0].name=bucket1,buckets[0].policy=none,buckets[0].purge=false minio/minio ``` Description of the configuration parameters used above - - `buckets[].name` - name of the bucket to create,...

  // same controller. For example, you may have different parameters for the
  // same implementing controller. This should be specified as a
  // domain-prefixed path no more than 250 characters in length, e.g.
  // "acme.io/ingress-controller". This field is immutable.
  optional string controller = 1;

  // parameters is a link to a custom resource containing additional

///

`oauth2_scheme` 🔢 👐 `OAuth2PasswordBearer`, ✋️ ⚫️ "🇧🇲".

⚫️ 💪 🤙:

```Python
oauth2_scheme(some, parameters)
```

, ⚫️ 💪 ⚙️ ⏮️ `Depends`.

### ⚙️ ⚫️

🔜 👆 💪 🚶‍♀️ 👈 `oauth2_scheme` 🔗 ⏮️ `Depends`.

```Python hl_lines="10"
{!../../docs_src/security/tutorial001.py!}
```

   * will be returned as the proxied method's return value.
   *
   * <p>Unlike {@link #invoke}, {@code args} will never be null. When the method has no parameter,
   * an empty array is passed in.
   */
  @CheckForNull
  protected abstract Object handleInvocation(Object proxy, Method method, @Nullable Object[] args)
      throws Throwable;

  /**

```Python hl_lines="16-18"
{!../../docs_src/custom_request_and_route/tutorial002.py!}
```

## Benutzerdefinierte `APIRoute`-Klasse in einem Router

Sie können auch den Parameter `route_class` eines `APIRouter` festlegen:

```Python hl_lines="26"
{!../../docs_src/custom_request_and_route/tutorial003.py!}
```

machine across multiple computational devices, including multicore CPUs, general purpose GPUs, and custom-designed ASICs known as Tensor Processing Units (TPUs). This architecture gives flexibility to the application developer, whereas in previous “parameter server” designs the management of shared state is built into the system, TensorFlow enables developers to experiment with novel optimizations and training algorithms. TensorFlow supports a variety of applications, with a focus on training and inference...