9caa24c58689c1d6f3d982f623ceab8f78e7362d,examples/mujoco_all_diayn.py,,run_experiment,#Any#,128

Before Change


        hidden_layer_sizes=[M, M],
    )

    vf = NNVFunction(
        observation_shape=aug_env_spec.observation_space.shape,
        hidden_layer_sizes=[M, M],
    )

    policy = GMMPolicy(
        observation_shape=aug_env_spec.observation_space.shape,
        action_shape=aug_env_spec.action_space.shape,

After Change


    Q = create_feedforward_Q_function(
        variant, aug_obs_space, env.action_space)
    V = create_feedforward_V_function(
        variant["V_params"], aug_obs_space)

    policy = GMMPolicy(
        observation_shape=aug_obs_space.shape,
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 5

Instances


Project Name: rail-berkeley/softlearning
Commit Name: 9caa24c58689c1d6f3d982f623ceab8f78e7362d
Time: 2018-10-20
Author: hartikainen@berkeley.edu
File Name: examples/mujoco_all_diayn.py
Class Name:
Method Name: run_experiment


Project Name: rail-berkeley/softlearning
Commit Name: 9caa24c58689c1d6f3d982f623ceab8f78e7362d
Time: 2018-10-20
Author: hartikainen@berkeley.edu
File Name: examples/multigoal_sac.py
Class Name:
Method Name: run_experiment


Project Name: rail-berkeley/softlearning
Commit Name: 9caa24c58689c1d6f3d982f623ceab8f78e7362d
Time: 2018-10-20
Author: hartikainen@berkeley.edu
File Name: examples/mujoco_all_diayn_finetune.py
Class Name:
Method Name: run_experiment