code: def entropy_y_x(logits):
      """Entropy term to add to VAT with entropy minimization.
  
      Args:
        logits: A Tensor containing the predicted logits for a batch of samples.
  
      Returns:
        The entropy minimization loss.
      """
      p = tf.nn.softmax(logits)
      return tf.reduce_mean(
          tf.nn.softmax_cross_entropy_with_logits_v2(
              labels=p, logits=logits
          )
      )
  
imports: import tensorflow
label_desc: Use image node_id 6 for calling a global function with example usage: entropy_y_x(logits) and returns: tf