text: # coding=utf-8
  # Copyright 2021 The TensorFlow Datasets Authors.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  """D4Rl Halfcheetah dataset from Mujoco."""
  
  from tensorflow_datasets.d4rl.d4rl_mujoco_halfcheetah import d4rl_mujoco_halfcheetah
  import tensorflow_datasets.public_api as tfds
  
  
  class D4rlMujocoHalfcheetahTest(tfds.testing.DatasetBuilderTestCase):
    """Tests for halfcheetah datasets."""
    DATASET_CLASS = d4rl_mujoco_halfcheetah.D4rlMujocoHalfcheetah
    SPLITS = {
        'train': 2,  # Number of fake train example
    }
    SKIP_TF1_GRAPH_MODE = True
  
    DL_EXTRACT_RESULT = {'file_path': 'halfcheetah_medium.hdf5'}
    DL_DOWNLOAD_RESULT = {'file_path': 'halfcheetah_medium.hdf5'}
  
    BUILDER_CONFIG_NAMES_TO_TEST = ['v0-medium']
  
  
  class D4rlMujocoHalfcheetahInfosTest(tfds.testing.DatasetBuilderTestCase):
    """Tests for halfcheetah datasets with step metadata."""
    DATASET_CLASS = d4rl_mujoco_halfcheetah.D4rlMujocoHalfcheetah
    SPLITS = {
        'train': 2,  # Number of fake train example
    }
    SKIP_TF1_GRAPH_MODE = True
  
    DL_EXTRACT_RESULT = {'file_path': 'halfcheetah_random-v1.hdf5'}
    DL_DOWNLOAD_RESULT = {'file_path': 'halfcheetah_random-v1.hdf5'}
  
    BUILDER_CONFIG_NAMES_TO_TEST = ['v1-random']
  
  
  class D4rlMujocoHalfcheetahReplayTest(tfds.testing.DatasetBuilderTestCase):
    """Tests for halfcheetah datasets with replay.
  
    These datasets have the following special features:
      * Contain step metadata.
      * Contain two fields of episode metadata.
      * Use float64 types (instead of float32)
      * Rewards are stored with shape (1,) instead of scalar
  
    """
    DATASET_CLASS = d4rl_mujoco_halfcheetah.D4rlMujocoHalfcheetah
    SPLITS = {
        'train': 2,  # Number of fake train example
    }
    SKIP_TF1_GRAPH_MODE = True
  
    DL_EXTRACT_RESULT = {'file_path': 'halfcheetah_medium_replay-v1.hdf5'}
    DL_DOWNLOAD_RESULT = {'file_path': 'halfcheetah_medium_replay-v1.hdf5'}
  
    BUILDER_CONFIG_NAMES_TO_TEST = ['v1-medium-replay']
  
  
  class D4rlMujocoHalfcheetahMetadataTest(tfds.testing.DatasetBuilderTestCase):
    """Tests for halfcheetah datasets with all the metadata fields."""
    DATASET_CLASS = d4rl_mujoco_halfcheetah.D4rlMujocoHalfcheetah
    SPLITS = {
        'train': 2,  # Number of fake train example
    }
    SKIP_TF1_GRAPH_MODE = True
  
    DL_EXTRACT_RESULT = {'file_path': 'halfcheetah_medium-v2.hdf5'}
    DL_DOWNLOAD_RESULT = {'file_path': 'halfcheetah_medium-v2.hdf5'}
  
    BUILDER_CONFIG_NAMES_TO_TEST = ['v2-medium']
  
  
  if __name__ == '__main__':
    tfds.testing.test_main()
  