class_docstr: An extension of Rainbow to perform implicit quantile regression.
docstr: Builds an Implicit Quantile ConvNet.
  
  Args:
    name: str, this name is passed to the tf.keras.Model and used to create
      variable scope under the hood by the tf.keras.Model.
  Returns:
    network: tf.keras.Model, the network instantiated by the Keras model.
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code: def _create_network(self, name):
      r"""Builds an Implicit Quantile ConvNet.
  
      Args:
        name: str, this name is passed to the tf.keras.Model and used to create
          variable scope under the hood by the tf.keras.Model.
      Returns:
        network: tf.keras.Model, the network instantiated by the Keras model.
      """
      network = self.network(
          self.num_actions, self.quantile_embedding_dim, name=name
      )
      return network
  
file_path: dopamine/dopamine/agents/implicit_quantile/implicit_quantile_agent.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from dopamine.agents.rainbow import rainbow_agent
  from dopamine.discrete_domains import atari_lib
  import gin.tf
  import tensorflow
label_desc: Use image node_id 2 for calling the ImplicitQuantileAgent obj's underlying member method code with example usage: obj._create_network(name) and returns: network