class_docstr: A class to support adding sharding attributes to Ops.
  
  Use the factory constructors and then call apply_to_tensor:
    Sharding.replicate().apply_to_tensor(tensor)
docstr: Returns a manuall sharding attribute.
  
  This means the op is manually partitioned by the user and XLA will not
  change the shapes.
docstr_tok: ["Returns","a","manuall","sharding","attribute",".","This","means","the","op","is","manually","partitioned","by","the","user","and","XLA","will","not","change","the","shapes","."]
code: def manual(cls):
      """Returns a manuall sharding attribute.
  
      This means the op is manually partitioned by the user and XLA will not
      change the shapes.
      """
      return Sharding(
          proto=xla_data_pb2.OpSharding(
              type=xla_data_pb2.OpSharding.MANUAL
          )
      )
  
imports: import numpy
  from tensorflow.compiler.tf2xla.python import xla
  from local_xla.xla import xla_data_pb2
  from tensorflow.core.framework import attr_value_pb2
label_desc: Use image node_id 3 for calling the Sharding obj's underlying member method code with example usage: obj.manual(cls) and returns: Sharding