returns f(inputs), where f's body is placed and partitioned.
tf.raw_ops.PartitionedCall(
    args,
    Tout,
    f,
    config='',
    config_proto='',
    executor_type='',
    name=None
)
  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.
| Args | |
|---|---|
| args | A list of Tensorobjects. A list of input tensors. | 
| Tout | A list of tf.DTypes. A list of output types. | 
| f | A function decorated with @Defun. A function that takes 'args', a list of tensors, and returns 'output', another list of tensors. Input and output types are specified by 'Tin' and 'Tout'. The function body of f will be placed and partitioned across devices, setting this op apart from the regular Call op. | 
| config | An optional string. Defaults to"". | 
| config_proto | An optional string. Defaults to"". | 
| executor_type | An optional string. Defaults to"". | 
| name | A name for the operation (optional). | 
| Returns | |
|---|---|
| A list of Tensorobjects of typeTout. | 
    © 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
    https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/raw_ops/PartitionedCall