def METHOD_NAME(
    display_name: str,
    dataset: Output[VertexDataset],
    location: Optional[str] = 'us-central1',
    data_item_labels: Optional[dict] = {},
    gcs_source: Optional[str] = None,
    import_schema_uri: Optional[str] = None,
    labels: Optional[dict] = {},
    encryption_spec_key_name: Optional[str] = None,
    project: str = _placeholders.PROJECT_ID_PLACEHOLDER,
):
  # fmt: off
  """Creates a new video [Dataset](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.datasets) and optionally imports data into Dataset when
  `source` and `import_schema_uri` are passed.
  Args:
      display_name: The user-defined name of the Dataset.
          The name can be up to 128 characters long and can be consist
          of any UTF-8 characters.
      gcs_source:
          Google Cloud Storage URI(-s) to the
          input file(s). May contain wildcards. For more
          information on wildcards, see
          https://cloud.google.com/storage/docs/gsutil/addlhelp/WildcardNames.
          For example, `"gs://bucket/file.csv"` or `["gs://bucket/file1.csv", "gs://bucket/file2.csv"]`.
      import_schema_uri: Points to a YAML file stored on Google Cloud
          Storage describing the import format. Validation will be
          done against the schema. The schema is defined as an
          [OpenAPI 3.0.2 Schema
          Object](https://tinyurl.com/y538mdwt).
      data_item_labels: Labels that will be applied to newly imported DataItems. If
          an identical DataItem as one being imported already exists
          in the Dataset, then these labels will be appended to these
          of the already existing one, and if labels with identical
          key is imported before, the old label value will be
          overwritten. If two DataItems are identical in the same
          import data operation, the labels will be combined and if
          key collision happens in this case, one of the values will
          be picked randomly. Two DataItems are considered identical
          if their content bytes are identical (e.g. image bytes or
          pdf bytes). These labels will be overridden by Annotation
          labels specified inside index file refenced by
          `import_schema_uri`,
      location: Optional location to retrieve Dataset from.
      labels: Labels with user-defined metadata to organize your Tensorboards.
          Label keys and values can be no longer than 64 characters
          (Unicode codepoints), can only contain lowercase letters, numeric
          characters, underscores and dashes. International characters are allowed.
          No more than 64 user labels can be associated with one Tensorboard
          (System labels are excluded).
          See https://goo.gl/xmQnxf for more information and examples of labels.
          System reserved label keys are prefixed with "aiplatform.googleapis.com/"
          and are immutable.
      encryption_spec_key_name: The Cloud KMS resource identifier of the customer
          managed encryption key used to protect the Dataset. Has the
          form:
          `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`.
          The key needs to be in the same region as where the compute
          resource is created.
          If set, this Dataset and all sub-resources of this Dataset will be secured by this key.
          Overrides `encryption_spec_key_name` set in `aiplatform.init`.
      project: Project to retrieve Dataset from. Defaults to the project in which the PipelineJob is run.
  Returns:
      dataset: Instantiated representation of the managed video Datasetresource.
  """
  # fmt: on
  return dsl.ContainerSpec(
      image=_image.GCPC_IMAGE_TAG,
      command=[
          'python3',
          '-m',
          'google_cloud_pipeline_components.container.v1.aiplatform.remote_runner',
          '--cls_name',
          'VideoDataset',
          '--method_name',
          'create',
      ],
      args=[
          '--method.project',
          project,
          '--method.location',
          location,
          '--method.display_name',
          display_name,
          '--method.data_item_labels',
          data_item_labels,
          dsl.IfPresentPlaceholder(
              input_name='gcs_source', then=['--method.gcs_source', gcs_source]
          ),
          dsl.IfPresentPlaceholder(
              input_name='import_schema_uri',
              then=['--method.import_schema_uri', import_schema_uri],
          ),
          '--method.labels',
          labels,
          dsl.IfPresentPlaceholder(
              input_name='encryption_spec_key_name',
              then=[
                  '--method.encryption_spec_key_name',
                  encryption_spec_key_name,
              ],
          ),
          '--executor_input',
          '{{$}}',
          '--resource_name_output_artifact_uri',
          dataset.uri,
      ],
  )