fix pre-commit

cleanrl/dqn.py

@@ -53,7 +53,7 @@ class Args:
     """the replay memory buffer size"""
     gamma: float = 0.99
     """the discount factor gamma"""
-    tau: float = 1.
+    tau: float = 1.0
     """the target network update rate"""
     target_network_frequency: int = 500
     """the timesteps it takes to update the target network"""

cleanrl/dqn_atari.py

@@ -60,7 +60,7 @@ class Args:
     """the replay memory buffer size"""
     gamma: float = 0.99
     """the discount factor gamma"""
-    tau: float = 1.
+    tau: float = 1.0
     """the target network update rate"""
     target_network_frequency: int = 1000
     """the timesteps it takes to update the target network"""

cleanrl/ppg_procgen.py

@@ -85,8 +85,6 @@ class Args:
     n_aux_grad_accum: int = 1
     """the number of gradient accumulation in mini batch"""
 
-
-
     # to be filled in runtime
     batch_size: int = 0
     """the batch size (computed in runtime)"""
@@ -283,7 +281,6 @@ def get_pi(self, x):
     start_time = time.time()
     next_obs = torch.Tensor(envs.reset()).to(device)
     next_done = torch.zeros(args.num_envs).to(device)
-
 
     for phase in range(1, args.num_phases + 1):
 
@@ -397,7 +394,7 @@ def get_pi(self, x):
                     optimizer.step()
 
                 if args.target_kl is not None and approx_kl > args.target_kl:
-                        break
+                    break
 
             y_pred, y_true = b_values.cpu().numpy(), b_returns.cpu().numpy()
             var_y = np.var(y_true)

cleanrl/qdagger_dqn_atari_jax_impalacnn.py

@@ -1,10 +1,8 @@
 # docs and experiment results can be found at https://docs.cleanrl.dev/rl-algorithms/qdagger/#qdagger_dqn_atari_jax_impalacnnpy
-import argparse
 import os
 import random
 import time
 from collections import deque
-from distutils.util import strtobool
 from typing import Sequence
 
 os.environ[