code: def _build_module(self, input_layer):
      # Standard classification Network
      self.class_values = self.output = self.dense_layer(
          self.num_actions
      )(input_layer, name="output")
  
      self.output = tf.nn.softmax(self.class_values)
  
      # calculate cross entropy loss
      self.target = tf.placeholder(
          tf.float32, shape=(None, self.num_actions), name="target"
      )
      self.loss = tf.nn.softmax_cross_entropy_with_logits(
          labels=self.target, logits=self.class_values
      )
      tf.losses.add_loss(self.loss)
  
file_path: coach/rl_coach/architectures/tensorflow_components/heads/classification_head.py
imports: import tensorflow
  from rl_coach.architectures.tensorflow_components.layers import Dense
  from rl_coach.architectures.tensorflow_components.heads.head import Head
  from rl_coach.base_parameters import AgentParameters
  from rl_coach.spaces import SpacesDefinition, BoxActionSpace, DiscreteActionSpace
label_desc: Use image node_id 2 for calling the ClassificationHead obj's underlying member method code with example usage: obj._build_module(input_layer) without return types