Remove CEMRL

README.md

@@ -11,7 +11,6 @@ NOTE: Python 3.6 is required!
 ## Implemented Algorithms
 
 - A2C
-- CEM-RL (with TD3)
 - PPO
 - SAC
 - TD3

docs/index.rst

@@ -29,7 +29,6 @@ RL Baselines zoo also offers a simple interface to train, evaluate agents and do
 
   modules/base
   modules/a2c
-  modules/cem_rl
   modules/ppo
   modules/sac
   modules/td3

docs/misc/changelog.rst

@@ -9,6 +9,7 @@ Pre-Release 0.4.0a0 (WIP)
 
 Breaking Changes:
 ^^^^^^^^^^^^^^^^^
+- Removed CEMRL
 
 New Features:
 ^^^^^^^^^^^^^

tests/test_callbacks.py

@@ -4,22 +4,17 @@
 import pytest
 import gym
 
-from torchy_baselines import A2C, CEMRL, PPO, SAC, TD3
+from torchy_baselines import A2C, PPO, SAC, TD3
 from torchy_baselines.common.callbacks import (CallbackList, CheckpointCallback, EvalCallback,
                                                EveryNTimesteps, StopTrainingOnRewardThreshold)
 
 
-@pytest.mark.parametrize("model_class", [A2C, CEMRL, PPO, SAC, TD3])
+@pytest.mark.parametrize("model_class", [A2C, PPO, SAC, TD3])
 def test_callbacks(model_class):
     log_folder = './logs/callbacks/'
-    kwargs = {}
-    if model_class == CEMRL:
-        kwargs['pop_size'] = 2
-        kwargs['n_grad'] = 1
-
     # Create RL model
     # Small network for fast test
-    model = model_class('MlpPolicy', 'Pendulum-v0', policy_kwargs=dict(net_arch=[32]), **kwargs)
+    model = model_class('MlpPolicy', 'Pendulum-v0', policy_kwargs=dict(net_arch=[32]))
 
     checkpoint_callback = CheckpointCallback(save_freq=1000, save_path=log_folder)
 

tests/test_predict.py

@@ -1,11 +1,10 @@
 import gym
 import pytest
 
-from torchy_baselines import A2C, CEMRL, PPO, SAC, TD3
+from torchy_baselines import A2C, PPO, SAC, TD3
 from torchy_baselines.common.vec_env import DummyVecEnv
 
 MODEL_LIST = [
-    CEMRL,
     PPO,
     A2C,
     TD3,

tests/test_run.py

@@ -1,7 +1,7 @@
 import numpy as np
 import pytest
 
-from torchy_baselines import A2C, CEMRL, PPO, SAC, TD3
+from torchy_baselines import A2C, PPO, SAC, TD3
 from torchy_baselines.common.noise import NormalActionNoise, OrnsteinUhlenbeckActionNoise
 
 action_noise = NormalActionNoise(np.zeros(1), 0.1 * np.ones(1))
@@ -14,12 +14,6 @@ def test_td3(action_noise):
     model.learn(total_timesteps=1000, eval_freq=500)
 
 
-def test_cemrl():
-    model = CEMRL('MlpPolicy', 'Pendulum-v0', policy_kwargs=dict(net_arch=[16]), pop_size=2, n_grad=1,
-                  learning_starts=100, verbose=1, create_eval_env=True, action_noise=action_noise)
-    model.learn(total_timesteps=1000, eval_freq=500)
-
-
 @pytest.mark.parametrize("model_class", [A2C, PPO])
 @pytest.mark.parametrize("env_id", ['CartPole-v1', 'Pendulum-v0'])
 def test_onpolicy(model_class, env_id):

tests/test_save_load.py

@@ -4,12 +4,11 @@
 import torch as th
 from copy import deepcopy
 
-from torchy_baselines import A2C, CEMRL, PPO, SAC, TD3
+from torchy_baselines import A2C, PPO, SAC, TD3
 from torchy_baselines.common.identity_env import IdentityEnvBox
 from torchy_baselines.common.vec_env import DummyVecEnv
 
 MODEL_LIST = [
-    CEMRL,
     PPO,
     A2C,
     TD3,

tests/test_vec_normalize.py

@@ -4,7 +4,7 @@
 
 from torchy_baselines.common.running_mean_std import RunningMeanStd
 from torchy_baselines.common.vec_env import DummyVecEnv, VecNormalize, VecFrameStack, sync_envs_normalization, unwrap_vec_normalize
-from torchy_baselines import CEMRL, SAC, TD3
+from torchy_baselines import SAC, TD3
 
 ENV_ID = 'Pendulum-v0'
 
@@ -116,7 +116,7 @@ def test_normalize_external():
     assert np.all(norm_rewards < 1)
 
 
-@pytest.mark.parametrize("model_class", [SAC, TD3, CEMRL])
+@pytest.mark.parametrize("model_class", [SAC, TD3])
 def test_offpolicy_normalization(model_class):
     env = DummyVecEnv([make_env])
     env = VecNormalize(env, norm_obs=True, norm_reward=True, clip_obs=10., clip_reward=10.)

torchy_baselines/__init__.py

@@ -1,7 +1,6 @@
 import os
 
 from torchy_baselines.a2c import A2C
-from torchy_baselines.cem_rl import CEMRL
 from torchy_baselines.ppo import PPO
 from torchy_baselines.sac import SAC
 from torchy_baselines.td3 import TD3