class_docstr: Task for policy evaluation.
class_docstr_tok: ["Task","for","policy","evaluation","."]
code: def _eval_batch(self, trajectory_batch, shape_only=False):
      advantages = self._train_task.calculate_advantages(
          trajectory_batch, shape_only=shape_only
      )
      (
          observations,
          actions,
          mask,
      ) = self._train_task.trim_and_mask_batch(
          trajectory_batch, advantages
      )
      return (observations, actions, advantages, mask)
  
file_path: trax/trax/rl/policy_tasks.py
imports: import numpy
  from trax import layers
  from trax.fastmath import numpy
  from trax.rl import distributions
  from trax.supervised import training
label_desc: Use image node_id 2 for calling the PolicyEvalTask obj's underlying member method code with example usage: obj._eval_batch(trajectory_batch, shape_only) and returns: observations,  actions,  advantages,  mask