tf.raw_ops.PartitionedCall
    
    
      
    
    
      
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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. | 
  
  
 
  
    
    
      
       
    
    
  
  
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  Last updated 2023-10-06 UTC.
  
  
  
    
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