code: def testClear(self):
      batch_size = 1
      spec = self._data_spec()
      replay_buffer = tf_uniform_replay_buffer.TFUniformReplayBuffer(
          spec, batch_size=batch_size, max_length=10
      )
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
  
      initial_id = self.evaluate(replay_buffer._get_last_id())
      empty_items = self.evaluate(replay_buffer.gather_all())
  
      values, _ = self.evaluate(
          _get_add_op(spec, replay_buffer, batch_size)
      )
      sample, _ = self.evaluate(
          replay_buffer.get_next(sample_batch_size=3)
      )
      tf.nest.map_structure(
          lambda x, y: self._assertContains([x], list(y)),
          values,
          sample,
      )
      self.assertNotEqual(
          initial_id, self.evaluate(replay_buffer._get_last_id())
      )
  
      self.evaluate(replay_buffer.clear())
      self.assertEqual(
          initial_id, self.evaluate(replay_buffer._get_last_id())
      )
  
      def check_np_arrays_everything_equal(x, y):
          np.testing.assert_equal(x, y)
          self.assertEqual(x.dtype, y.dtype)
  
      tf.nest.map_structure(
          check_np_arrays_everything_equal,
          empty_items,
          self.evaluate(replay_buffer.gather_all()),
      )
  
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 8 for calling the TFUniformReplayBufferTest obj's underlying member method code with example usage: obj.testClear() without return types