0e49e55d906660e5c9168447c77ebc6d917dda5c,softlearning/replay_pools/utils.py,,get_replay_pool_from_variant,#Any#Any#,19

Before Change


def get_replay_pool_from_variant(variant, env):
    replay_pool_params = variant["replay_pool_params"].copy()

    pool_type = replay_pool_params.pop("type", DEFAULT_REPLAY_POOL)

    pool = POOL_CLASSES[pool_type](
        observation_space=env.observation_space,
        action_space=env.action_space,

After Change



def get_replay_pool_from_variant(variant, env, *args, **kwargs):
    replay_pool_params = variant["replay_pool_params"]
    replay_pool_type = replay_pool_params["type"]
    replay_pool_kwargs = deepcopy(replay_pool_params["kwargs"])

    replay_pool = POOL_CLASSES[replay_pool_type](
        *args,
        observation_space=env.observation_space,
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 5

Instances


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/policies/utils.py
Class Name:
Method Name: get_policy_from_variant


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