0e49e55d906660e5c9168447c77ebc6d917dda5c,softlearning/value_functions/utils.py,,get_V_function_from_variant,#Any#Any#,29

Before Change




def get_V_function_from_variant(variant, env):
    V_params = variant["V_params"].copy()

    observation_shape = env.active_observation_shape

    input_shapes = (observation_shape, )

After Change




def get_V_function_from_variant(variant, env, *args, **kwargs):
    V_params = variant["V_params"]
    V_type = V_params["type"]
    V_kwargs = deepcopy(V_params["kwargs"])

    input_shapes = (env.active_observation_shape, )

    return VALUE_FUNCTIONS[V_type](
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 6

Instances


Project Name: rail-berkeley/softlearning
Commit Name: 0e49e55d906660e5c9168447c77ebc6d917dda5c
Time: 2018-10-22
Author: hartikainen@berkeley.edu
File Name: softlearning/value_functions/utils.py
Class Name:
Method Name: get_V_function_from_variant


Project Name: rail-berkeley/softlearning
Commit Name: 0e49e55d906660e5c9168447c77ebc6d917dda5c
Time: 2018-10-22
Author: hartikainen@berkeley.edu
File Name: softlearning/replay_pools/utils.py
Class Name:
Method Name: get_replay_pool_from_variant


Project Name: rail-berkeley/softlearning
Commit Name: 0e49e55d906660e5c9168447c77ebc6d917dda5c
Time: 2018-10-22
Author: hartikainen@berkeley.edu
File Name: softlearning/value_functions/utils.py
Class Name:
Method Name: get_Q_function_from_variant