let summary = "Creates a dataset that fuses mapping with batching.";

  let description = [{
Creates a dataset that applies `f` to the outputs of `input_dataset` and then
batches `batch_size` of them.

Unlike a "MapDataset", which applies `f` sequentially, this dataset invokes up
to `batch_size * num_parallel_batches` copies of `f` in parallel.
  }];

  let arguments = (ins

            "description": "Level is SELinux level label that applies to the container.",
            "type": "string"
          },
          "role": {
            "description": "Role is a SELinux role label that applies to the container.",
            "type": "string"
          },
          "type": {
            "description": "Type is a SELinux type label that applies to the container.",
            "type": "string"

#f8f9fa;\n  --dark: #343a40;\n  --breakpoint-xs: 0;\n  --breakpoint-sm: 576px;\n  --breakpoint-md: 768px;\n  --breakpoint-lg: 992px;\n  --breakpoint-xl: 1200px;\n  --font-family-sans-serif: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Roboto, \"Helvetica Neue\", Arial, \"Noto Sans\", sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\", \"Noto Color Emoji\";\n  --font-family-monospace: SFMono-Regular, Menlo, Monaco, Consolas, \"Liberation Mono\", \"Courier New\", monosp...

#f8f9fa;\n  --dark: #343a40;\n  --breakpoint-xs: 0;\n  --breakpoint-sm: 576px;\n  --breakpoint-md: 768px;\n  --breakpoint-lg: 992px;\n  --breakpoint-xl: 1200px;\n  --font-family-sans-serif: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Roboto, \"Helvetica Neue\", Arial, \"Noto Sans\", sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\", \"Noto Color Emoji\";\n  --font-family-monospace: SFMono-Regular, Menlo, Monaco, Consolas, \"Liberation Mono\", \"Courier New\", monosp...

        most cases and defaults to `verbose=2` when used with
        `ParameterServerStrategy` or with interactive logging disabled.
    *   Argument `jit_compile` in `Model.compile()` now applies to
        `Model.evaluate()` and `Model.predict()`. Setting `jit_compile=True` in
        `compile()` compiles the model's training, evaluation, and inference
        steps to [XLA](https://www.tensorflow.org/xla). Note that

fc107;--danger:#dc3545;--light:#f8f9fa;--dark:#343a40;--breakpoint-xs:0;--breakpoint-sm:576px;--breakpoint-md:768px;--breakpoint-lg:992px;--breakpoint-xl:1200px;--font-family-sans-serif:"Source Sans Pro",-apple-system,BlinkMacSystemFont,"Segoe UI",Roboto,"Helvetica Neue",Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";--font-family-monospace:SFMono-Regular,Menlo,Monaco,Consolas,"Liberation Mono","Courier New",monospace}*,::after,::before{box-sizing:border-box}html{font-fa...

                              properties:
                                applicationProtocols:
                                  description: Applies only to sidecars.
                                  type: string
                                destinationPort:
                                  description: The destination_port value used by

The seccomp (secure computing mode) support for Kubernetes has graduated to General Availability (GA). This feature can be used to increase the workload security by restricting the system calls for a Pod (applies to all containers) or single containers.

Technically this means that a first class `seccompProfile` field has been added to the Pod and Container `securityContext` objects:

```yaml
securityContext:

                              properties:
                                applicationProtocols:
                                  description: Applies only to sidecars.
                                  type: string
                                destinationPort:
                                  description: The destination_port value used by

        "description": "ManagedFieldsEntry is a workflow-id, a FieldSet and the group version of the resource that the fieldset applies to.",
        "properties": {
          "apiVersion": {