code: def testDeterministicAsDatasetNumStepsGreaterThanMaxLengthFails(self):
      spec = specs.TensorSpec([], tf.int32, "action")
      replay_buffer = tf_uniform_replay_buffer.TFUniformReplayBuffer(
          spec,
          batch_size=2,
          max_length=3,
          # If this isn't turned on, then the batching works fine.
          dataset_drop_remainder=True,
      )
      with self.assertRaisesRegexp(
          ValueError, "ALL data will be dropped"
      ):
          replay_buffer.as_dataset(
              single_deterministic_pass=True, num_steps=4
          )
  
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 25 for calling the TFUniformReplayBufferTest obj's underlying member method code with example usage: obj.testDeterministicAsDatasetNumStepsGreaterThanMaxLengthFails() without return types