class_docstr: Tests for TFRecordObserver class and dataset/spec file functions.
class_docstr_tok: ["Tests","for","TFRecordObserver","class","and","dataset\/spec","file","functions","."]
code: def setUp(self):
      super(TFRecordsUtilsTest, self).setUp()
      tf.compat.v1.enable_resource_variables()
      # Create a simple mock tensor data spec for testing
      # Spec has a batch dimmension of 1 to simulate environment samples
      self.simple_data_spec = SimpleSpec(
          step_type=tf.TensorSpec(
              shape=(1), dtype=tf.int32, name="step_type"
          ),
          value=tf.TensorSpec(
              shape=(1, 2), dtype=tf.float64, name="value"
          ),
      )
      self.dataset_path = os.path.join(
          self.get_temp_dir(), "test_tfrecord_dataset.tfrecord"
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import os
  import numpy
  import tensorflow
  from tf_agents.drivers import dynamic_step_driver
  from tf_agents.drivers import py_driver
  from tf_agents.drivers import test_utils
  from tf_agents.drivers import tf_driver
  from tf_agents.environments import tf_py_environment
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import trajectory
  from tf_agents.utils import common
  from tf_agents.utils import eager_utils
  from tf_agents.utils import example_encoding_dataset
  from tf_agents.utils import test_utils
label_desc: Use image node_id 1 for calling the TFRecordsUtilsTest obj's underlying member method code with example usage: obj.setUp() without return types