style: uniformize imports

examples/demo_agents/demo_SAC.py

@@ -9,6 +9,7 @@
 import time
 
 import gymnasium as gym
+
 from rlberry.agents.torch.sac import SACAgent
 from rlberry.envs import Pendulum
 from rlberry.manager import AgentManager

examples/demo_agents/video_plot_a2c.py

@@ -11,10 +11,10 @@
 """
 # sphinx_gallery_thumbnail_path = 'thumbnails/video_plot_a2c.jpg'
 
-from rlberry.agents.torch import A2CAgent
-from rlberry.envs.benchmarks.ball_exploration import PBall2D
 from gymnasium.wrappers import TimeLimit
 
+from rlberry.agents.torch import A2CAgent
+from rlberry.envs.benchmarks.ball_exploration import PBall2D
 
 env = PBall2D()
 env = TimeLimit(env, max_episode_steps=256)

examples/demo_agents/video_plot_dqn.py

@@ -20,17 +20,16 @@
 
 # sphinx_gallery_thumbnail_path = 'thumbnails/video_plot_dqn.jpg'
 
-from rlberry.envs import gym_make
+import os
+import shutil
+
+from gymnasium.wrappers.record_video import RecordVideo
 from torch.utils.tensorboard import SummaryWriter
 
 from rlberry.agents.torch.dqn import DQNAgent
+from rlberry.envs import gym_make
 from rlberry.utils.logging import configure_logging
 
-from gymnasium.wrappers.record_video import RecordVideo
-import shutil
-import os
-
-
 configure_logging(level="INFO")
 
 env = gym_make("CartPole-v1", render_mode="rgb_array")

examples/demo_agents/video_plot_mdqn.py

@@ -20,17 +20,16 @@
 
 # sphinx_gallery_thumbnail_path = 'thumbnails/video_plot_dqn.jpg'
 
-from rlberry.envs import gym_make
+import os
+import shutil
+
+from gymnasium.wrappers.record_video import RecordVideo
 from torch.utils.tensorboard import SummaryWriter
 
 from rlberry.agents.torch.dqn import MunchausenDQNAgent
+from rlberry.envs import gym_make
 from rlberry.utils.logging import configure_logging
 
-from gymnasium.wrappers.record_video import RecordVideo
-import shutil
-import os
-
-
 configure_logging(level="INFO")
 
 env = gym_make("CartPole-v1", render_mode="rgb_array")

examples/demo_agents/video_plot_ppo.py

@@ -14,7 +14,6 @@
 from rlberry.agents.torch import PPOAgent
 from rlberry.envs.benchmarks.ball_exploration import PBall2D
 
-
 env = PBall2D()
 n_steps = 3e3
 

examples/demo_agents/video_plot_rs_kernel_ucbvi.py

@@ -11,8 +11,8 @@
 """
 # sphinx_gallery_thumbnail_path = 'thumbnails/video_plot_rs_kernel_ucbvi.jpg'
 
-from rlberry.envs import Acrobot
 from rlberry.agents import RSKernelUCBVIAgent
+from rlberry.envs import Acrobot
 from rlberry.wrappers import RescaleRewardWrapper
 
 env = Acrobot()

examples/demo_bandits/plot_TS_bandit.py

@@ -11,19 +11,19 @@
 """
 
 import numpy as np
-from rlberry.envs.bandits import BernoulliBandit, NormalBandit
+
 from rlberry.agents.bandits import (
     IndexAgent,
     TSAgent,
-    makeBoundedUCBIndex,
-    makeSubgaussianUCBIndex,
     makeBetaPrior,
+    makeBoundedUCBIndex,
     makeGaussianPrior,
+    makeSubgaussianUCBIndex,
 )
+from rlberry.envs.bandits import BernoulliBandit, NormalBandit
 from rlberry.manager import ExperimentManager, plot_writer_data
 from rlberry.wrappers import WriterWrapper
 
-
 # Bernoulli
 
 # Agents definition

examples/demo_bandits/plot_compare_index_bandits.py

@@ -6,11 +6,9 @@
 This script Compare several bandits agents and as a sub-product also shows
 how to use subplots in with `plot_writer_data`
 """
-import numpy as np
 import matplotlib.pyplot as plt
-from rlberry.envs.bandits import BernoulliBandit
-from rlberry.manager import ExperimentManager, plot_writer_data
-from rlberry.wrappers import WriterWrapper
+import numpy as np
+
 from rlberry.agents.bandits import (
     IndexAgent,
     RandomizedAgent,
@@ -22,6 +20,9 @@
     makeETCIndex,
     makeEXP3Index,
 )
+from rlberry.envs.bandits import BernoulliBandit
+from rlberry.manager import ExperimentManager, plot_writer_data
+from rlberry.wrappers import WriterWrapper
 
 # Agents definition
 # sphinx_gallery_thumbnail_number = 2

examples/demo_bandits/plot_exp3_bandit.py

@@ -8,17 +8,17 @@
 """
 
 import numpy as np
-from rlberry.envs.bandits import AdversarialBandit
+
 from rlberry.agents.bandits import (
     RandomizedAgent,
     TSAgent,
-    makeEXP3Index,
     makeBetaPrior,
+    makeEXP3Index,
 )
+from rlberry.envs.bandits import AdversarialBandit
 from rlberry.manager import ExperimentManager, plot_writer_data
 from rlberry.wrappers import WriterWrapper
 
-
 # Agents definition
 
 

examples/demo_bandits/plot_mirror_bandit.py

@@ -12,19 +12,16 @@
 The code is in three parts: definition of environment, definition of agent,
 and finally definition of the experiment.
 """
+import matplotlib.pyplot as plt
 import numpy as np
-
-from rlberry.manager import ExperimentManager, read_writer_data
-from rlberry.envs.interface import Model
-from rlberry.agents.bandits import BanditWithSimplePolicy
-from rlberry.wrappers import WriterWrapper
-import rlberry.spaces as spaces
-
 import requests
-import matplotlib.pyplot as plt
-
 
 import rlberry
+import rlberry.spaces as spaces
+from rlberry.agents.bandits import BanditWithSimplePolicy
+from rlberry.envs.interface import Model
+from rlberry.manager import ExperimentManager, read_writer_data
+from rlberry.wrappers import WriterWrapper
 
 logger = rlberry.logger
 

examples/demo_bandits/plot_ucb_bandit.py

@@ -6,14 +6,14 @@
 This script shows how to define a bandit environment and an UCB Index-based algorithm.
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
-from rlberry.envs.bandits import NormalBandit
+
 from rlberry.agents.bandits import IndexAgent, makeSubgaussianUCBIndex
+from rlberry.envs.bandits import NormalBandit
 from rlberry.manager import ExperimentManager, plot_writer_data
-import matplotlib.pyplot as plt
 from rlberry.wrappers import WriterWrapper
 
-
 # Agents definition
 
 

examples/demo_env/example_atari_atlantis_vectorized_ppo.py

@@ -14,15 +14,16 @@
 # sphinx_gallery_thumbnail_path = 'thumbnails/example_plot_atari_atlantis_vectorized_ppo.jpg'
 
 
-from rlberry.manager import ExperimentManager
+import os
+import shutil
 from datetime import datetime
-from rlberry.agents.torch import PPOAgent
+
 from gymnasium.wrappers.record_video import RecordVideo
-import shutil
-import os
-from rlberry.envs.gym_make import atari_make
-from rlberry.agents.torch.utils.training import model_factory_from_env
 
+from rlberry.agents.torch import PPOAgent
+from rlberry.agents.torch.utils.training import model_factory_from_env
+from rlberry.envs.gym_make import atari_make
+from rlberry.manager import ExperimentManager
 
 initial_time = datetime.now()
 print("-------- init agent --------")

examples/demo_env/example_atari_breakout_vectorized_ppo.py

@@ -14,15 +14,16 @@
 # sphinx_gallery_thumbnail_path = 'thumbnails/example_plot_atari_breakout_vectorized_ppo.jpg'
 
 
-from rlberry.manager import ExperimentManager
+import os
+import shutil
 from datetime import datetime
-from rlberry.agents.torch import PPOAgent
+
 from gymnasium.wrappers.record_video import RecordVideo
-import shutil
-import os
-from rlberry.envs.gym_make import atari_make
-from rlberry.agents.torch.utils.training import model_factory_from_env
 
+from rlberry.agents.torch import PPOAgent
+from rlberry.agents.torch.utils.training import model_factory_from_env
+from rlberry.envs.gym_make import atari_make
+from rlberry.manager import ExperimentManager
 
 initial_time = datetime.now()
 print("-------- init agent --------")

examples/demo_env/video_plot_acrobot.py

@@ -11,8 +11,8 @@
 """
 # sphinx_gallery_thumbnail_path = 'thumbnails/video_plot_acrobot.jpg'
 
-from rlberry.envs import Acrobot
 from rlberry.agents import RSUCBVIAgent
+from rlberry.envs import Acrobot
 from rlberry.wrappers import RescaleRewardWrapper
 
 env = Acrobot()

examples/demo_env/video_plot_apple_gold.py

@@ -9,9 +9,10 @@
    :width: 600
 
 """
+from rlberry.agents.dynprog import ValueIterationAgent
+
 # sphinx_gallery_thumbnail_path = 'thumbnails/video_plot_apple_gold.jpg'
 from rlberry.envs.benchmarks.grid_exploration.apple_gold import AppleGold
-from rlberry.agents.dynprog import ValueIterationAgent
 
 env = AppleGold(reward_free=False, array_observation=False)
 

examples/demo_env/video_plot_atari_freeway.py

@@ -14,14 +14,15 @@
 # sphinx_gallery_thumbnail_path = 'thumbnails/video_plot_atari_freeway.jpg'
 
 
-from rlberry.manager import ExperimentManager
+import os
+import shutil
 from datetime import datetime
-from rlberry.agents.torch.dqn.dqn import DQNAgent
+
 from gymnasium.wrappers.record_video import RecordVideo
-import shutil
-import os
-from rlberry.envs.gym_make import atari_make
 
+from rlberry.agents.torch.dqn.dqn import DQNAgent
+from rlberry.envs.gym_make import atari_make
+from rlberry.manager import ExperimentManager
 
 initial_time = datetime.now()
 print("-------- init agent --------")

examples/demo_env/video_plot_gridworld.py

@@ -15,7 +15,6 @@
 from rlberry.agents.dynprog import ValueIterationAgent
 from rlberry.envs.finite import GridWorld
 
-
 env = GridWorld(7, 10, walls=((2, 2), (3, 3)))
 
 agent = ValueIterationAgent(env, gamma=0.95)

examples/demo_env/video_plot_old_gym_compatibility_wrapper_old_acrobot.py

@@ -11,10 +11,10 @@
 # sphinx_gallery_thumbnail_path = 'thumbnails/video_plot_old_gym_acrobot.jpg'
 
 
-from rlberry.wrappers.tests.old_env.old_acrobot import Old_Acrobot
 from rlberry.agents import RSUCBVIAgent
 from rlberry.wrappers import RescaleRewardWrapper
 from rlberry.wrappers.gym_utils import OldGymCompatibilityWrapper
+from rlberry.wrappers.tests.old_env.old_acrobot import Old_Acrobot
 
 env = Old_Acrobot()
 env = OldGymCompatibilityWrapper(env)

examples/demo_env/video_plot_pball.py

@@ -11,6 +11,7 @@
 # sphinx_gallery_thumbnail_path = 'thumbnails/video_plot_pball.jpg'
 
 import numpy as np
+
 from rlberry.envs.benchmarks.ball_exploration import PBall2D
 
 p = 5

examples/demo_env/video_plot_rooms.py

@@ -10,8 +10,8 @@
 """
 # sphinx_gallery_thumbnail_path = 'thumbnails/video_plot_rooms.jpg'
 
-from rlberry.envs.benchmarks.grid_exploration.nroom import NRoom
 from rlberry.agents.dynprog import ValueIterationAgent
+from rlberry.envs.benchmarks.grid_exploration.nroom import NRoom
 
 env = NRoom(
     nrooms=9,

examples/demo_env/video_plot_springcartpole.py

@@ -13,10 +13,11 @@
 """
 # sphinx_gallery_thumbnail_path = 'thumbnails/video_plot_springcartpole.jpg'
 
-from rlberry.envs.classic_control import SpringCartPole
-from rlberry.agents.torch import DQNAgent
 from gymnasium.wrappers.time_limit import TimeLimit
 
+from rlberry.agents.torch import DQNAgent
+from rlberry.envs.classic_control import SpringCartPole
+
 model_configs = {
     "type": "MultiLayerPerceptron",
     "layer_sizes": (256, 256),

examples/demo_env/video_plot_twinrooms.py

@@ -10,10 +10,10 @@
 """
 # sphinx_gallery_thumbnail_path = 'thumbnails/video_plot_twinrooms.jpg'
 
-from rlberry.envs.benchmarks.generalization.twinrooms import TwinRooms
 from rlberry.agents.mbqvi import MBQVIAgent
-from rlberry.wrappers.discretize_state import DiscretizeStateWrapper
+from rlberry.envs.benchmarks.generalization.twinrooms import TwinRooms
 from rlberry.seeding import Seeder
+from rlberry.wrappers.discretize_state import DiscretizeStateWrapper
 
 seeder = Seeder(123)
 

examples/demo_experiment/run.py

@@ -11,11 +11,9 @@
 $ python examples/demo_examples/demo_experiment/run.py
 """
 
-from rlberry.experiment import load_experiment_results
-from rlberry.experiment import experiment_generator
+from rlberry.experiment import experiment_generator, load_experiment_results
 from rlberry.manager.multiple_managers import MultipleManagers
 
-
 if __name__ == "__main__":
     multimanagers = MultipleManagers(parallelization="thread")
 

examples/demo_network/run_client.py

@@ -3,11 +3,11 @@
  Demo: run_client
  =====================
 """
-from rlberry.network.client import BerryClient
-from rlberry.network import interface
-from rlberry.network.interface import Message, ResourceRequest
 import numpy as np
 
+from rlberry.network import interface
+from rlberry.network.client import BerryClient
+from rlberry.network.interface import Message, ResourceRequest
 
 port = int(input("Select server port: "))
 client = BerryClient(port=port)

examples/demo_network/run_remote_manager.py

@@ -3,15 +3,12 @@
  Demo: run_remote_manager
  =====================
 """
-from rlberry.envs.gym_make import gym_make
-from rlberry.network.client import BerryClient
-from rlberry.network.interface import ResourceRequest
-
 from rlberry.agents.torch import REINFORCEAgent
-
+from rlberry.envs.gym_make import gym_make
 from rlberry.manager import ExperimentManager, MultipleManagers, RemoteExperimentManager
 from rlberry.manager.evaluation import evaluate_agents, plot_writer_data
-
+from rlberry.network.client import BerryClient
+from rlberry.network.interface import ResourceRequest
 
 if __name__ == "__main__":
     port = int(input("Select server port: "))