code: def testGatherAllOverCapacity(self, batch_size):
      spec = specs.TensorSpec([], tf.int64, "action")
      replay_buffer = tf_uniform_replay_buffer.TFUniformReplayBuffer(
          spec, batch_size=batch_size, max_length=10
      )
  
      @common.function(autograph=True)
      def add_data():
          # Each element has its batch index in the 100s place.
          for i in tf.range(15, dtype=tf.int64):
              batch = (
                  tf.range(0, batch_size * 100, 100, dtype=tf.int64) + i
              )
              replay_buffer.add_batch(batch)
  
      expected = [
          list(range(5 + x * 100, 15 + x * 100))
          for x in range(batch_size)
      ]
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
      add_data()
      self.evaluate_last_func_if_graph_mode()
      items = replay_buffer.gather_all()
      items_ = self.evaluate(items)
      self.assertAllClose(expected, items_)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents import specs
  from tf_agents.replay_buffers import tf_uniform_replay_buffer
  from tf_agents.utils import common
  from tf_agents.utils import test_utils
label_desc: Use image node_id 14 for calling the TFUniformReplayBufferTest obj's underlying member method code with example usage: obj.testGatherAllOverCapacity(batch_size) without return types