code: def testGetAddAppendMultiple(self):
      spec = self.default_specs()
      replay_table = episodic_table.EpisodicTable(spec, capacity=4)
  
      batch_size = 2
      input_values = self.np_values(spec, batch_size)
      expected_values = self.np_values(spec)
      empty_values = self.np_values(spec, 0)
      tensors = tf.nest.map_structure(
          lambda x: tf.convert_to_tensor(value=x, dtype=tf.float32),
          input_values,
      )
  
      # Pull out the first entry in the batch, and add an outer
      # dimension to represent a single time step that we'll append.
      tensors_batch0 = tf.nest.map_structure(
          lambda x: tf.expand_dims(x[0, ...], 0), tensors
      )
  
      # We will append tensors_batch0 to row 0, which contains x[0].
      expected_appended_values = tf.nest.map_structure(
          lambda x: np.stack((x[0], x[0])), input_values
      )
  
      # batch_size == 2, so add [0, 1]
      write_op = replay_table.add([0, 1], tensors)
      append_op_0 = lambda: replay_table.append(0, tensors_batch0)
  
      values_0 = lambda: replay_table.get_episode_values(0)
      values_1 = lambda: replay_table.get_episode_values(1)
      values_2 = lambda: replay_table.get_episode_values(2)
      self.evaluate(tf.compat.v1.global_variables_initializer())
      self.evaluate(write_op)
      tf.nest.map_structure(
          self.assertAllClose,
          expected_values,
          self.evaluate(values_0()),
      )
      tf.nest.map_structure(
          self.assertAllClose,
          expected_values,
          self.evaluate(values_1()),
      )
      tf.nest.map_structure(
          self.assertAllClose, empty_values, self.evaluate(values_2())
      )
  
      self.evaluate(append_op_0())
      tf.nest.map_structure(
          self.assertAllClose,
          expected_appended_values,
          self.evaluate(values_0()),
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import numpy
  import tensorflow
  from tf_agents import specs
  from tf_agents.replay_buffers import episodic_table
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 6 for calling the EpisodicTableTest obj's underlying member method code with example usage: obj.testGetAddAppendMultiple() without return types