returns `f(inputs)`, where `f`'s body is placed and partitioned.
  }];

  let description = [{
Asynchronously executes a function, potentially across multiple devices but
within a single process. The kernel places and partitions a given function's
underlying graph, and executes each of the partitioned subgraphs as a function.
  }];

  let arguments = (ins

* Add an option `disable_eager_executer_streaming_enqueue` to `tensorflow.ConfigProto.Experimental` to control the eager runtime's behavior around parallel remote function invocations; when set to `True`, the eager runtime will be allowed to execute multiple function invocations in parallel.

* `tf.constant_initializer`

                - required:
                  - exec
                properties:
                  exec:
                    description: Health is determined by how the command that is executed
                      exited.
                    properties:
                      command:
                        description: Command to run.
                        items:

              "type": "string"
            },
            "type": "array",
            "x-kubernetes-list-type": "atomic"
          },
          "command": {

                - required:
                  - exec
                properties:
                  exec:
                    description: Health is determined by how the command that is executed
                      exited.
                    properties:
                      command:
                        description: Command to run.
                        items:

                        properties:
                          filters:
                            description: |-
                              Filters defined at this level MUST be executed if and only if the
                              request is being forwarded to the backend defined here.


                              Support: Implementation-specific (For broader support of filters, use the