6f3a917e94edf2b96e4c151d698495799be5c9de,tf_agents/agents/sac/sac_agent.py,SacAgent,alpha_loss,#SacAgent#Any#Any#,534

Before Change

      else:
        alpha_loss = (tf.exp(self._log_alpha) * entropy_diff)

      if nest_utils.is_batched_nested_tensors(
          time_steps, self.time_step_spec, num_outer_dims=2):
        // Sum over the time dimension.
        alpha_loss = tf.reduce_sum(input_tensor=alpha_loss, axis=1)
      else:
        alpha_loss = tf.expand_dims(alpha_loss, 0)

      agg_loss = common.aggregate_losses(
          per_example_loss=alpha_loss, sample_weight=weights)
      alpha_loss = agg_loss.total_loss

After Change

      unused_actions, log_pi = self._actions_and_log_probs(time_steps)
      entropy_diff = tf.stop_gradient(-log_pi - self._target_entropy)
      if self._use_log_alpha_in_alpha_loss:
        alpha_loss = (self._log_alpha * entropy_diff)
      else:
        alpha_loss = (tf.exp(self._log_alpha) * entropy_diff)

      if alpha_loss.shape.rank > 1:
        // Sum over the time dimension.
        alpha_loss = tf.reduce_sum(
            alpha_loss, axis=range(1, alpha_loss.shape.rank))

      agg_loss = common.aggregate_losses(
          per_example_loss=alpha_loss, sample_weight=weights)
      alpha_loss = agg_loss.total_loss

Instances