65f530438eb0e66c396192b4416bce83bf331cf0,ml/rl/test/preprocessing/test_feature_extractor.py,TestTrainingFeatureExtractor,test_create_net_max_q_discrete_action,#TestTrainingFeatureExtractor#,1215

Before Change


            include_possible_actions=True,
            max_num_actions=2,
        )
        expected_input_record = schema.Struct(
            ("state_features", map_schema()),
            ("next_state_features", map_schema()),
            ("action", schema.Scalar()),
            ("next_action", schema.Scalar()),
            ("not_terminal", schema.Scalar()),
            ("possible_actions_mask", schema.List(schema.Scalar())),
            ("possible_next_actions_mask", schema.List(schema.Scalar())),
            ("time_diff", schema.Scalar()),
        )
        expected_output_record = schema.Struct(
            ("state_features", schema.Scalar()),
            ("next_state_features", schema.Scalar()),
            ("action", schema.Scalar()),
            ("next_action", schema.Scalar()),
            ("not_terminal", schema.Scalar()),
            ("time_diff", schema.Scalar()),
            ("possible_actions_mask", schema.Scalar()),
            ("possible_next_actions_mask", schema.Scalar()),
        )
        self.check_create_net_spec(
            extractor, expected_input_record, expected_output_record
        )

After Change


            include_possible_actions=True,
            max_num_actions=2,
        )
        expected_input_record = (
            schema.Struct(
                ("state_features", map_schema()),
                ("next_state_features", map_schema()),
                ("action", schema.Scalar()),
                ("next_action", schema.Scalar()),
                ("possible_actions_mask", schema.List(schema.Scalar())),
                ("possible_next_actions_mask", schema.List(schema.Scalar())),
            )
            + self.pass_through_columns()
        )
        expected_output_record = (
            schema.Struct(
                ("state_features", schema.Scalar()),
                ("next_state_features", schema.Scalar()),
                ("action", schema.Scalar()),
                ("next_action", schema.Scalar()),
                ("possible_actions_mask", schema.Scalar()),
                ("possible_next_actions_mask", schema.Scalar()),
            )
            + self.pass_through_columns()
        )
        self.check_create_net_spec(
            extractor,
            expected_input_record,
            expected_output_record,
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 4

Non-data size: 15

Instances


Project Name: facebookresearch/Horizon
Commit Name: 65f530438eb0e66c396192b4416bce83bf331cf0
Time: 2019-04-04
Author: kittipat@fb.com
File Name: ml/rl/test/preprocessing/test_feature_extractor.py
Class Name: TestTrainingFeatureExtractor
Method Name: test_create_net_max_q_discrete_action


Project Name: facebookresearch/Horizon
Commit Name: 65f530438eb0e66c396192b4416bce83bf331cf0
Time: 2019-04-04
Author: kittipat@fb.com
File Name: ml/rl/test/preprocessing/test_feature_extractor.py
Class Name: TestTrainingFeatureExtractor
Method Name: test_create_net_max_q_discrete_action


Project Name: facebookresearch/Horizon
Commit Name: 65f530438eb0e66c396192b4416bce83bf331cf0
Time: 2019-04-04
Author: kittipat@fb.com
File Name: ml/rl/test/preprocessing/test_feature_extractor.py
Class Name: TestTrainingFeatureExtractor
Method Name: _test_create_net_max_q_parametric_action


Project Name: facebookresearch/Horizon
Commit Name: 65f530438eb0e66c396192b4416bce83bf331cf0
Time: 2019-04-04
Author: kittipat@fb.com
File Name: ml/rl/test/preprocessing/test_feature_extractor.py
Class Name: TestTrainingFeatureExtractor
Method Name: _test_create_net_sarsa_parametric_action


Project Name: facebookresearch/Horizon
Commit Name: 65f530438eb0e66c396192b4416bce83bf331cf0
Time: 2019-04-04
Author: kittipat@fb.com
File Name: ml/rl/test/preprocessing/test_feature_extractor.py
Class Name: TestTrainingFeatureExtractor
Method Name: test_create_net_sarsa_discrete_action