Clean up.

Denys88 · Nov 29, 2024 · d78f5a3 · d78f5a3
1 parent db41372
commit d78f5a3
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Showing 4 changed files with 61 additions and 71 deletions.
diff --git a/pyproject.toml b/pyproject.toml
@@ -9,7 +9,7 @@ authors = [
 ]
 
 [tool.poetry.dependencies]
-python = ">=3.7.1,<3.11"
+python = ">=3.7.1,<3.14"
 gym = {version = "^0.23.0", extras = ["classic_control"]}
 tensorboard = "^2.8.0"
 tensorboardX = "^2.5"

diff --git a/rl_games/algos_torch/a2c_continuous.py b/rl_games/algos_torch/a2c_continuous.py
@@ -6,7 +6,7 @@
 from rl_games.common import datasets
 
 from torch import optim
-import torch 
+import torch
 
 
 class A2CAgent(a2c_common.ContinuousA2CBase):
@@ -30,11 +30,11 @@ def __init__(self, base_name, params):
             'actions_num' : self.actions_num,
             'input_shape' : obs_shape,
             'num_seqs' : self.num_actors * self.num_agents,
-            'value_size': self.env_info.get('value_size',1),
+            'value_size': self.env_info.get('value_size', 1),
             'normalize_value' : self.normalize_value,
             'normalize_input': self.normalize_input,
         }
-        
+
         self.model = self.network.build(build_config)
         self.model.to(self.ppo_device)
         self.states = None
@@ -74,7 +74,7 @@ def __init__(self, base_name, params):
     def update_epoch(self):
         self.epoch_num += 1
         return self.epoch_num
-        
+
     def save(self, fn):
         state = self.get_full_state_weights()
         torch_ext.save_checkpoint(fn, state)
@@ -114,7 +114,7 @@ def calc_gradients(self, input_dict):
 
         batch_dict = {
             'is_train': True,
-            'prev_actions': actions_batch, 
+            'prev_actions': actions_batch,
             'obs' : obs_batch,
         }
 
@@ -195,7 +195,7 @@ def train_actor_critic(self, input_dict):
 
     def reg_loss(self, mu):
         if self.bounds_loss_coef is not None:
-            reg_loss = (mu*mu).sum(axis=-1)
+            reg_loss = (mu * mu).sum(axis=-1)
         else:
             reg_loss = 0
         return reg_loss
@@ -209,5 +209,3 @@ def bound_loss(self, mu):
         else:
             b_loss = 0
         return b_loss
-
-
diff --git a/rl_games/common/env_configurations.py b/rl_games/common/env_configurations.py
@@ -10,7 +10,6 @@
 import math
 
 
-
 class HCRewardEnv(gym.RewardWrapper):
     def __init__(self, env):
         gym.RewardWrapper.__init__(self, env)
@@ -34,8 +33,6 @@ def step(self, action):
         return observation, reward, done, info
 
 
-
-
 class DMControlObsWrapper(gym.ObservationWrapper):
     def __init__(self, env):
         gym.RewardWrapper.__init__(self, env)
@@ -96,15 +93,15 @@ def create_myo(**kwargs):
 def create_atari_gym_env(**kwargs):
     #frames = kwargs.pop('frames', 1)
     name = kwargs.pop('name')
-    skip = kwargs.pop('skip',4)
-    episode_life = kwargs.pop('episode_life',True)
+    skip = kwargs.pop('skip', 4)
+    episode_life = kwargs.pop('episode_life', True)
     wrap_impala = kwargs.pop('wrap_impala', False)
-    env = wrappers.make_atari_deepmind(name, skip=skip,episode_life=episode_life, wrap_impala=wrap_impala, **kwargs)
-    return env    
+    env = wrappers.make_atari_deepmind(name, skip=skip, episode_life=episode_life, wrap_impala=wrap_impala, **kwargs)
+    return env
 
 def create_dm_control_env(**kwargs):
     frames = kwargs.pop('frames', 1)
-    name = 'dm2gym:'+ kwargs.pop('name')
+    name = 'dm2gym:' + kwargs.pop('name')
     env = gym.make(name, environment_kwargs=kwargs)
     env = DMControlWrapper(env)
     env = DMControlObsWrapper(env)
@@ -140,11 +137,11 @@ def create_super_mario_env_stage1(name='SuperMarioBrosRandomStage1-v1'):
 
     env = gym_super_mario_bros.make(stage_names[1])
     env = JoypadSpace(env, SIMPLE_MOVEMENT)
-    
+
     env = wrappers.MaxAndSkipEnv(env, skip=4)
     env = wrappers.wrap_deepmind(env, episode_life=False, clip_rewards=False, frame_stack=True, scale=True)
     #env = wrappers.AllowBacktracking(env)
-    
+
     return env
 
 def create_quadrupped_env():
@@ -166,8 +163,7 @@ def create_smac(name, **kwargs):
     has_cv = kwargs.get('central_value', False)
     as_single_agent = kwargs.pop('as_single_agent', False)
     env = SMACEnv(name, **kwargs)
-
-
+
     if frames > 1:
         if has_cv:
             env = wrappers.BatchedFrameStackWithStates(env, frames, transpose=False, flatten=flatten)
@@ -185,7 +181,7 @@ def create_smac_v2(name, **kwargs):
     flatten = kwargs.pop('flatten', True)
     has_cv = kwargs.get('central_value', False)
     env = SMACEnvV2(name, **kwargs)
-    
+
     if frames > 1:
         if has_cv:
             env = wrappers.BatchedFrameStackWithStates(env, frames, transpose=False, flatten=flatten)
@@ -217,15 +213,13 @@ def create_minigrid_env(name, **kwargs):
     import gym_minigrid
     import gym_minigrid.wrappers
 
-
     state_bonus = kwargs.pop('state_bonus', False)
     action_bonus = kwargs.pop('action_bonus', False)
     rgb_fully_obs = kwargs.pop('rgb_fully_obs', False)
     rgb_partial_obs = kwargs.pop('rgb_partial_obs', True)
     view_size = kwargs.pop('view_size', 3)
     env = gym.make(name, **kwargs)
 
-
     if state_bonus:
         env = gym_minigrid.wrappers.StateBonus(env)
     if action_bonus:
@@ -243,7 +237,7 @@ def create_minigrid_env(name, **kwargs):
 
 def create_multiwalker_env(**kwargs):
     from rl_games.envs.multiwalker import MultiWalker
-    env = MultiWalker('', **kwargs) 
+    env = MultiWalker('', **kwargs)
 
     return env
 
@@ -290,87 +284,87 @@ def create_env(name, **kwargs):
         'vecenv_type' : 'RAY'
     },
     'PongNoFrameskip-v4' : {
-        'env_creator' : lambda **kwargs  :  wrappers.make_atari_deepmind('PongNoFrameskip-v4', skip=4),
+        'env_creator' : lambda **kwargs  : wrappers.make_atari_deepmind('PongNoFrameskip-v4', skip=4),
         'vecenv_type' : 'RAY'
     },
     'BreakoutNoFrameskip-v4' : {
-        'env_creator' : lambda  **kwargs :  wrappers.make_atari_deepmind('BreakoutNoFrameskip-v4', skip=4,sticky=False),
+        'env_creator' : lambda  **kwargs : wrappers.make_atari_deepmind('BreakoutNoFrameskip-v4', skip=4, sticky=False),
         'vecenv_type' : 'RAY'
     },
     'MsPacmanNoFrameskip-v4' : {
-        'env_creator' : lambda  **kwargs :  wrappers.make_atari_deepmind('MsPacmanNoFrameskip-v4', skip=4),
+        'env_creator' : lambda  **kwargs : wrappers.make_atari_deepmind('MsPacmanNoFrameskip-v4', skip=4),
         'vecenv_type' : 'RAY'
     },
     'CarRacing-v0' : {
-        'env_creator' : lambda **kwargs  :  wrappers.make_car_racing('CarRacing-v0', skip=4),
+        'env_creator' : lambda **kwargs  : wrappers.make_car_racing('CarRacing-v0', skip=4),
         'vecenv_type' : 'RAY'
     },
     'RoboschoolAnt-v1' : {
         'env_creator' : lambda **kwargs  : create_roboschool_env('RoboschoolAnt-v1'),
         'vecenv_type' : 'RAY'
     },
     'SuperMarioBros-v1' : {
-        'env_creator' : lambda :  create_super_mario_env(),
+        'env_creator' : lambda : create_super_mario_env(),
         'vecenv_type' : 'RAY'
     },
     'SuperMarioBrosRandomStages-v1' : {
-        'env_creator' : lambda :  create_super_mario_env('SuperMarioBrosRandomStages-v1'),
+        'env_creator' : lambda : create_super_mario_env('SuperMarioBrosRandomStages-v1'),
         'vecenv_type' : 'RAY'
     },
     'SuperMarioBrosRandomStage1-v1' : {
-        'env_creator' : lambda **kwargs  :  create_super_mario_env_stage1('SuperMarioBrosRandomStage1-v1'),
+        'env_creator' : lambda **kwargs : create_super_mario_env_stage1('SuperMarioBrosRandomStage1-v1'),
         'vecenv_type' : 'RAY'
     },
     'RoboschoolHalfCheetah-v1' : {
-        'env_creator' : lambda **kwargs  : create_roboschool_env('RoboschoolHalfCheetah-v1'),
+        'env_creator' : lambda **kwargs : create_roboschool_env('RoboschoolHalfCheetah-v1'),
         'vecenv_type' : 'RAY'
     },
     'RoboschoolHumanoid-v1' : {
         'env_creator' : lambda : wrappers.FrameStack(create_roboschool_env('RoboschoolHumanoid-v1'), 1, True),
         'vecenv_type' : 'RAY'
     },
     'LunarLanderContinuous-v2' : {
-        'env_creator' : lambda **kwargs  : gym.make('LunarLanderContinuous-v2'),
+        'env_creator' : lambda **kwargs : gym.make('LunarLanderContinuous-v2'),
         'vecenv_type' : 'RAY'
     },
     'RoboschoolHumanoidFlagrun-v1' : {
-        'env_creator' : lambda **kwargs  : wrappers.FrameStack(create_roboschool_env('RoboschoolHumanoidFlagrun-v1'), 1, True),
+        'env_creator' : lambda **kwargs : wrappers.FrameStack(create_roboschool_env('RoboschoolHumanoidFlagrun-v1'), 1, True),
         'vecenv_type' : 'RAY'
     },
     'BipedalWalker-v3' : {
-        'env_creator' : lambda **kwargs  : create_env('BipedalWalker-v3', **kwargs),
+        'env_creator' : lambda **kwargs : create_env('BipedalWalker-v3', **kwargs),
         'vecenv_type' : 'RAY'
     },
     'BipedalWalkerCnn-v3' : {
-        'env_creator' : lambda **kwargs  : wrappers.FrameStack(HCRewardEnv(gym.make('BipedalWalker-v3')), 4, False),
+        'env_creator' : lambda **kwargs : wrappers.FrameStack(HCRewardEnv(gym.make('BipedalWalker-v3')), 4, False),
         'vecenv_type' : 'RAY'
     },
     'BipedalWalkerHardcore-v3' : {
-        'env_creator' : lambda **kwargs  : gym.make('BipedalWalkerHardcore-v3'),
+        'env_creator' : lambda **kwargs : gym.make('BipedalWalkerHardcore-v3'),
         'vecenv_type' : 'RAY'
     },
     'ReacherPyBulletEnv-v0' : {
-        'env_creator' : lambda **kwargs  : create_roboschool_env('ReacherPyBulletEnv-v0'),
+        'env_creator' : lambda **kwargs : create_roboschool_env('ReacherPyBulletEnv-v0'),
         'vecenv_type' : 'RAY'
     },
     'BipedalWalkerHardcoreCnn-v3' : {
         'env_creator' : lambda : wrappers.FrameStack(gym.make('BipedalWalkerHardcore-v3'), 4, False),
         'vecenv_type' : 'RAY'
     },
     'QuadruppedWalk-v1' : {
-        'env_creator' : lambda **kwargs  : create_quadrupped_env(),
+        'env_creator' : lambda **kwargs : create_quadrupped_env(),
         'vecenv_type' : 'RAY'
     },
     'FlexAnt' : {
-        'env_creator' : lambda **kwargs  : create_flex(FLEX_PATH + '/demo/gym/cfg/ant.yaml'),
+        'env_creator' : lambda **kwargs : create_flex(FLEX_PATH + '/demo/gym/cfg/ant.yaml'),
         'vecenv_type' : 'ISAAC'
     },
     'FlexHumanoid' : {
-        'env_creator' : lambda **kwargs  : create_flex(FLEX_PATH + '/demo/gym/cfg/humanoid.yaml'),
+        'env_creator' : lambda **kwargs : create_flex(FLEX_PATH + '/demo/gym/cfg/humanoid.yaml'),
         'vecenv_type' : 'ISAAC'
     },
     'FlexHumanoidHard' : {
-        'env_creator' : lambda **kwargs  : create_flex(FLEX_PATH + '/demo/gym/cfg/humanoid_hard.yaml'),
+        'env_creator' : lambda **kwargs : create_flex(FLEX_PATH + '/demo/gym/cfg/humanoid_hard.yaml'),
         'vecenv_type' : 'ISAAC'
     },
     'smac' : {
@@ -423,7 +417,7 @@ def create_env(name, **kwargs):
     },
     'brax' : {
         'env_creator': lambda **kwargs: create_brax_env(**kwargs),
-        'vecenv_type': 'BRAX' 
+        'vecenv_type': 'BRAX'
     },
     'envpool': {
         'env_creator': lambda **kwargs: create_envpool(**kwargs),
@@ -439,6 +433,7 @@ def create_env(name, **kwargs):
     },
 }
 
+
 def get_env_info(env):
     result_shapes = {}
     result_shapes['observation_space'] = env.observation_space
@@ -450,16 +445,17 @@ def get_env_info(env):
     '''
     if isinstance(result_shapes['observation_space'], gym.spaces.dict.Dict):
         result_shapes['observation_space'] = observation_space['observations']
-    
+
     if isinstance(result_shapes['observation_space'], dict):
         result_shapes['observation_space'] = observation_space['observations']
         result_shapes['state_space'] = observation_space['states']
     '''
-    if hasattr(env, "value_size"):    
+    if hasattr(env, "value_size"):
         result_shapes['value_size'] = env.value_size
     print(result_shapes)
     return result_shapes
 
+
 def get_obs_and_action_spaces_from_config(config):
     env_config = config.get('env_config', {})
     env = configurations[config['env_name']]['env_creator'](**env_config)
@@ -476,4 +472,4 @@ def register(name, config):
         config (:obj:`dict`): Dictionary with env type and a creator function.
 
     """
-    configurations[name] = config
+    configurations[name] = config
diff --git a/setup.py b/setup.py
@@ -1,9 +1,6 @@
 """Setup script for rl_games"""
 
-import sys
-import os
 import pathlib
-
 from setuptools import setup, find_packages
 # The directory containing this file
 HERE = pathlib.Path(__file__).parent
@@ -16,34 +13,33 @@
       long_description=README,
       long_description_content_type="text/markdown",
       url="https://github.com/Denys88/rl_games",
-      #packages=[package for package in find_packages() if package.startswith('rl_games')],
-      packages = ['.','rl_games','docs'],
-      package_data={'rl_games':['*','*/*','*/*/*'],'docs':['*','*/*','*/*/*'],},
+      packages=['.', 'rl_games', 'docs'],
+      package_data={'rl_games': ['*', '*/*', '*/*/*'], 'docs': ['*', '*/*', '*/*/*'], },
       version='1.6.1',
       author='Denys Makoviichuk, Viktor Makoviichuk',
       author_email='trrrrr97@gmail.com, victor.makoviychuk@gmail.com',
       license="MIT",
       classifiers=[
-            "License :: OSI Approved :: MIT License",
-            "Programming Language :: Python :: 3",
-            "Programming Language :: Python :: 3.7",
-            "Programming Language :: Python :: 3.8",
-            "Programming Language :: Python :: 3.9",
-            "Programming Language :: Python :: 3.10"
+              "License :: OSI Approved :: MIT License",
+              "Programming Language :: Python :: 3",
+              "Programming Language :: Python :: 3.7",
+              "Programming Language :: Python :: 3.8",
+              "Programming Language :: Python :: 3.9",
+              "Programming Language :: Python :: 3.10",
+              "Programming Language :: Python :: 3.11",
+              "Programming Language :: Python :: 3.12",
+              "Programming Language :: Python :: 3.13",
       ],
-      #packages=["rlg"],
       include_package_data=True,
       install_requires=[
-            # this setup is only for pytorch
-            # 
-            'gym>=0.17.2',
-            'torch>=1.7.0',
-            'numpy>=1.16.0',
-            'tensorboard>=1.14.0',
-            'tensorboardX>=1.6',
-            'setproctitle',
-            'psutil',
-            'pyyaml',
-            'watchdog>=2.1.9,<3.0.0',  # for evaluation process
+          'gym>=0.17.2',
+          'torch>=2.0.0',
+          'numpy>=1.16.0',
+          'tensorboard>=1.14.0',
+          'tensorboardX>=1.6',
+          'setproctitle',
+          'psutil',
+          'pyyaml',
+          'watchdog>=2.1.9',  # for evaluation process
       ],
       )