code: def tanh_squash_to_spec(inputs, spec):
      """Maps inputs with arbitrary range to range defined by spec using `tanh`."""
      means = (spec.maximum + spec.minimum) / 2.0
      magnitudes = (spec.maximum - spec.minimum) / 2.0
  
      return means + magnitudes * tf.tanh(inputs)
  
file_path: agents/tf_agents/networks/normal_projection_network.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import sys
  import gin
  import tensorflow
  import tensorflow_probability
  from tf_agents.distributions import utils
  from tf_agents.keras_layers import bias_layer
  from tf_agents.networks import network
  from tf_agents.networks import utils
  from tf_agents.specs import distribution_spec
  from tf_agents.specs import tensor_spec
label_desc: Use image node_id 1 for calling a global function with example usage: tanh_squash_to_spec(inputs, spec) and returns: unknown