class_docstr: A network that takes global and arm observations and outputs rewards.
  
  This network calculates the dot product of the output of the global and
  per-arm networks and returns them as reward estimates.
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docstr: Initializes an instance of `GlobalAndArmDotProductNetwork`.
  
  The network architecture contains networks for both the global and the arm
  features. The reward estimates will be the dot product of the global and per
  arm outputs.
  
  Args:
    observation_spec: The observation spec for the policy that uses this
      network.
    global_network: The network that takes the global features as input.
    arm_network: The network that takes the arm features as input.
    name: The name of this instance of `GlobalAndArmDotProductNetwork`.
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code: def __init__(
      self,
      observation_spec: types.NestedTensorSpec,
      global_network: types.Network,
      arm_network: types.Network,
      name: Optional[Text] = "GlobalAndArmDotProductNetwork",
  ):
      """Initializes an instance of `GlobalAndArmDotProductNetwork`.
  
      The network architecture contains networks for both the global and the arm
      features. The reward estimates will be the dot product of the global and per
      arm outputs.
  
      Args:
        observation_spec: The observation spec for the policy that uses this
          network.
        global_network: The network that takes the global features as input.
        arm_network: The network that takes the arm features as input.
        name: The name of this instance of `GlobalAndArmDotProductNetwork`.
      """
      super(GlobalAndArmDotProductNetwork, self).__init__(
          input_tensor_spec=observation_spec, state_spec=(), name=name
      )
      self._global_network = global_network
      self._arm_network = arm_network
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import Callable, Optional, Sequence, Text
  import gin
  import numpy
  import tensorflow
  from tf_agents.bandits.specs import utils
  from tf_agents.networks import encoding_network
  from tf_agents.networks import network
  from tf_agents.networks import q_network
  from tf_agents.specs import tensor_spec
  from tf_agents.typing import types
label_desc: Use image node_id 1 to create a new GlobalAndArmDotProductNetwork object from inherited base classes: network with example: obj = GlobalAndArmDotProductNetwork(observation_spec, global_network, arm_network, name)