class_docstr: Multi-head network module.
  
  This takes as input a list of N `network_heads`, and returns another network
  whose output is the stacked outputs of each of these network heads separately
  applied to the module input. The dimension of the output is [..., N].
code: def __init__(self, network_heads: Sequence[TensorTransformation]):
      if not network_heads:
          raise ValueError(
              "Must specify non-empty, non-None critic_network_heads."
          )
      self._network_heads = network_heads
      super().__init__(name="multihead")
  
file_path: acme/acme/tf/networks/multihead.py
imports: from typing import Callable, Union, Sequence
  from acme import types
  import sonnet
  import tensorflow
  import tensorflow_probability
label_desc: Use image node_id 1 to create a new Multihead object from inherited base classes: snt with example: obj = Multihead(network_heads)