Rename to stable-baselines3

.coveragerc

@@ -4,7 +4,7 @@ omit =
     tests/*
     setup.py
     # Require graphical interface
-    torchy_baselines/common/results_plotter.py
+    stable_baselines3/common/results_plotter.py
 
 [report]
 exclude_lines =

.github/ISSUE_TEMPLATE/issue-template.md

@@ -13,7 +13,7 @@ If you are submitting a bug report, please fill in the following details.
 If your issue is related to a custom gym environment, please check it first using:
 
 ```python
-from torchy_baselines.common.env_checker import check_env
+from stable_baselines3.common.env_checker import check_env
 
 env = CustomEnv(arg1, ...)
 # It will check your custom environment and output additional warnings if needed
@@ -30,7 +30,7 @@ Please use the [markdown code blocks](https://help.github.com/en/articles/creati
 for both code and stack traces.
 
 ```python
-from torchy_baselines import ...
+from stable_baselines3 import ...
 
 ```
 

NOTICE

@@ -1,4 +1,4 @@
-Large portion of the code of Torchy-Baselines (in `common/`) were ported from Stable-Baselines, a fork of OpenAI Baselines,
+Large portion of the code of Stable-Baselines3 (in `common/`) were ported from Stable-Baselines, a fork of OpenAI Baselines,
 both licensed under the MIT License:
 
 before the fork (June 2018):

README.md

@@ -2,7 +2,7 @@
 
 [![Build Status](https://travis-ci.com/hill-a/stable-baselines.svg?branch=master)](https://travis-ci.com/hill-a/stable-baselines) [![Documentation Status](https://readthedocs.org/projects/stable-baselines/badge/?version=master)](https://stable-baselines.readthedocs.io/en/master/?badge=master)
 
-# Torchy Baselines
+# Stable Baselines3
 
 PyTorch version of [Stable Baselines](https://github.com/hill-a/stable-baselines), a set of improved implementations of reinforcement learning algorithms.
 
@@ -58,7 +58,7 @@ To cite this repository in publications:
 ```
 @misc{torchy-baselines,
   author = {Raffin, Antonin and Hill, Ashley and Ernestus, Maximilian and Gleave, Adam and Kanervisto, Anssi and Dormann, Noah},
-  title = {Torchy Baselines},
+  title = {Stable Baselines3},
   year = {2019},
   publisher = {GitHub},
   journal = {GitHub repository},

docs/conf.py

@@ -44,19 +44,19 @@ def __getattr__(cls, name):
 sys.modules.update((mod_name, Mock()) for mod_name in MOCK_MODULES)
 
 
-import torchy_baselines
+import stable_baselines3
 
 
 # -- Project information -----------------------------------------------------
 
-project = 'Torchy Baselines'
-copyright = '2020, Torchy Baselines'
-author = 'Torchy Baselines Contributors'
+project = 'Stable Baselines3'
+copyright = '2020, Stable Baselines3'
+author = 'Stable Baselines3 Contributors'
 
 # The short X.Y version
-version = 'master (' + torchy_baselines.__version__ + ' )'
+version = 'master (' + stable_baselines3.__version__ + ' )'
 # The full version, including alpha/beta/rc tags
-release = torchy_baselines.__version__
+release = stable_baselines3.__version__
 
 
 # -- General configuration ---------------------------------------------------
@@ -179,8 +179,8 @@ def setup(app):
 # (source start file, target name, title,
 #  author, documentclass [howto, manual, or own class]).
 latex_documents = [
-    (master_doc, 'TorchyBaselines.tex', 'Torchy Baselines Documentation',
-     'Torchy Baselines Contributors', 'manual'),
+    (master_doc, 'TorchyBaselines.tex', 'Stable Baselines3 Documentation',
+     'Stable Baselines3 Contributors', 'manual'),
 ]
 
 
@@ -189,7 +189,7 @@ def setup(app):
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
 man_pages = [
-    (master_doc, 'torchybaselines', 'Torchy Baselines Documentation',
+    (master_doc, 'torchybaselines', 'Stable Baselines3 Documentation',
      [author], 1)
 ]
 
@@ -200,7 +200,7 @@ def setup(app):
 # (source start file, target name, title, author,
 #  dir menu entry, description, category)
 texinfo_documents = [
-    (master_doc, 'TorchyBaselines', 'Torchy Baselines Documentation',
+    (master_doc, 'TorchyBaselines', 'Stable Baselines3 Documentation',
      author, 'TorchyBaselines', 'One line description of project.',
      'Miscellaneous'),
 ]

docs/guide/quickstart.rst

@@ -12,9 +12,9 @@ Here is a quick example of how to train and run SAC on a Pendulum environment:
 
   import gym
 
-  from torchy_baselines.sac.policies import MlpPolicy
-  from torchy_baselines.common.vec_env import DummyVecEnv
-  from torchy_baselines import SAC
+  from stable_baselines3.sac.policies import MlpPolicy
+  from stable_baselines3.common.vec_env import DummyVecEnv
+  from stable_baselines3 import SAC
 
   env = gym.make('Pendulum-v0')
 
@@ -34,6 +34,6 @@ the policy is registered:
 
 .. code-block:: python
 
-    from torchy_baselines import SAC
+    from stable_baselines3 import SAC
 
     model = SAC('MlpPolicy', 'Pendulum-v0').learn(10000)

docs/guide/vec_envs.rst

@@ -1,6 +1,6 @@
 .. _vec_env:
 
-.. automodule:: torchy_baselines.common.vec_env
+.. automodule:: stable_baselines3.common.vec_env
 
 Vectorized Environments
 =======================

docs/index.rst

@@ -3,10 +3,10 @@
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
-Welcome to Torchy Baselines docs! - Pytorch RL Baselines
+Welcome to Stable Baselines3 docs! - Pytorch RL Baselines
 ========================================================
 
-`Torchy Baselines <https://github.com/hill-a/stable-baselines>`_ is the PyTorch version of `Stable Baselines <https://github.com/hill-a/stable-baselines>`_,
+`Stable Baselines3 <https://github.com/hill-a/stable-baselines>`_ is the PyTorch version of `Stable Baselines <https://github.com/hill-a/stable-baselines>`_,
 a set of improved implementations of reinforcement learning algorithms.
 
 RL Baselines Zoo (collection of pre-trained agents): https://github.com/araffin/rl-baselines-zoo
@@ -41,15 +41,15 @@ RL Baselines zoo also offers a simple interface to train, evaluate agents and do
   misc/changelog
 
 
-Citing Torchy Baselines
+Citing Stable Baselines3
 -----------------------
 To cite this project in publications:
 
 .. code-block:: bibtex
 
     @misc{torchy-baselines,
       author = {Raffin, Antonin and Hill, Ashley and Ernestus, Maximilian and Gleave, Adam and Kanervisto, Anssi and Dormann, Noah},
-      title = {Torchy Baselines},
+      title = {Stable Baselines3},
       year = {2019},
       publisher = {GitHub},
       journal = {GitHub repository},

docs/misc/changelog.rst

@@ -111,7 +111,7 @@ Pre-Release 0.2.0 (2020-02-14)
 
 Breaking Changes:
 ^^^^^^^^^^^^^^^^^
-- Python 2 support was dropped, Torchy Baselines now requires Python 3.6 or above
+- Python 2 support was dropped, Stable Baselines3 now requires Python 3.6 or above
 - Return type of ``evaluation.evaluate_policy()`` has been changed
 - Refactored the replay buffer to avoid transformation between PyTorch and NumPy
 - Created `OffPolicyRLModel` base class
@@ -160,7 +160,7 @@ New Features:
 Maintainers
 -----------
 
-Torchy-Baselines is currently maintained by `Antonin Raffin`_ (aka `@araffin`_).
+Stable-Baselines3 is currently maintained by `Antonin Raffin`_ (aka `@araffin`_).
 
 .. _Antonin Raffin: https://araffin.github.io/
 .. _@araffin: https://github.com/araffin

docs/modules/a2c.rst

@@ -1,6 +1,6 @@
 .. _a2c:
 
-.. automodule:: torchy_baselines.a2c
+.. automodule:: stable_baselines3.a2c
 
 
 A2C
@@ -44,9 +44,9 @@ Train a A2C agent on `CartPole-v1` using 4 processes.
 
   import gym
 
-  from torchy_baselines.common.policies import MlpPolicy
-  from torchy_baselines.common import make_vec_env
-  from torchy_baselines import A2C
+  from stable_baselines3.common.policies import MlpPolicy
+  from stable_baselines3.common import make_vec_env
+  from stable_baselines3 import A2C
 
   # Parallel environments
   env = make_vec_env('CartPole-v1', n_envs=4)

docs/modules/base.rst

@@ -1,6 +1,6 @@
 .. _base_algo:
 
-.. automodule:: torchy_baselines.common.base_class
+.. automodule:: stable_baselines3.common.base_class
 
 
 Base RL Class

docs/modules/ppo.rst

@@ -1,6 +1,6 @@
 .. _ppo2:
 
-.. automodule:: torchy_baselines.ppo
+.. automodule:: stable_baselines3.ppo
 
 PPO
 ===
@@ -53,9 +53,9 @@ Train a PPO agent on `Pendulum-v0` using 4 processes.
 
    import gym
 
-   from torchy_baselines.ppo.policies import MlpPolicy
-   from torchy_baselines.common.vec_env import SubprocVecEnv
-   from torchy_baselines import PPO
+   from stable_baselines3.ppo.policies import MlpPolicy
+   from stable_baselines3.common.vec_env import SubprocVecEnv
+   from stable_baselines3 import PPO
 
    # multiprocess environment
    n_cpu = 4

docs/modules/sac.rst

@@ -1,6 +1,6 @@
 .. _sac:
 
-.. automodule:: torchy_baselines.sac
+.. automodule:: stable_baselines3.sac
 
 
 SAC
@@ -14,7 +14,7 @@ A key feature of SAC, and a major difference with common RL algorithms, is that
 
 .. warning::
 
-  The SAC model does not support ``torchy_baselines.common.policies`` because it uses double q-values
+  The SAC model does not support ``stable_baselines3.common.policies`` because it uses double q-values
   and value estimation, as a result it must use its own policy models (see :ref:`sac_policies`).
 
 
@@ -72,9 +72,9 @@ Example
   import gym
   import numpy as np
 
-  from torchy_baselines.sac.policies import MlpPolicy
-  from torchy_baselines.common.vec_env import DummyVecEnv
-  from torchy_baselines import SAC
+  from stable_baselines3.sac.policies import MlpPolicy
+  from stable_baselines3.common.vec_env import DummyVecEnv
+  from stable_baselines3 import SAC
 
   env = gym.make('Pendulum-v0')
   env = DummyVecEnv([lambda: env])

docs/modules/td3.rst

@@ -1,6 +1,6 @@
 .. _td3:
 
-.. automodule:: torchy_baselines.td3
+.. automodule:: stable_baselines3.td3
 
 
 TD3
@@ -14,7 +14,7 @@ We recommend reading `OpenAI Spinning guide on TD3 <https://spinningup.openai.co
 
 .. warning::
 
-  The TD3 model does not support ``torchy_baselines.common.policies`` because it uses double q-values
+  The TD3 model does not support ``stable_baselines3.common.policies`` because it uses double q-values
   estimation, as a result it must use its own policy models (see :ref:`td3_policies`).
 
 
@@ -64,9 +64,9 @@ Example
 
   import numpy as np
 
-  from torchy_baselines import TD3
-  from torchy_baselines.td3.policies import MlpPolicy
-  from torchy_baselines.common.noise import NormalActionNoise, OrnsteinUhlenbeckActionNoise
+  from stable_baselines3 import TD3
+  from stable_baselines3.td3.policies import MlpPolicy
+  from stable_baselines3.common.noise import NormalActionNoise, OrnsteinUhlenbeckActionNoise
 
   # The noise objects for TD3
   n_actions = env.action_space.shape[-1]

setup.cfg

@@ -18,4 +18,4 @@ filterwarnings =
 		ignore::UserWarning:gym
 
 [pytype]
-inputs = torchy_baselines
+inputs = stable_baselines3

setup.py

@@ -3,13 +3,13 @@
 import subprocess
 from setuptools import setup, find_packages
 
-with open(os.path.join('torchy_baselines', 'version.txt'), 'r') as file_handler:
+with open(os.path.join('stable_baselines3', 'version.txt'), 'r') as file_handler:
     __version__ = file_handler.read()
 
 
-setup(name='torchy_baselines',
+setup(name='stable_baselines3',
       packages=[package for package in find_packages()
-                if package.startswith('torchy_baselines')],
+                if package.startswith('stable_baselines3')],
       install_requires=[
           'gym[classic_control]>=0.11',
           'numpy',

torchy_baselines/__init__.py → stable_baselines3/__init__.py

@@ -1,9 +1,9 @@
 import os
 
-from torchy_baselines.a2c import A2C
-from torchy_baselines.ppo import PPO
-from torchy_baselines.sac import SAC
-from torchy_baselines.td3 import TD3
+from stable_baselines3.a2c import A2C
+from stable_baselines3.ppo import PPO
+from stable_baselines3.sac import SAC
+from stable_baselines3.td3 import TD3
 
 # Read version from file
 version_file = os.path.join(os.path.dirname(__file__), 'version.txt')

stable_baselines3/a2c/__init__.py

@@ -0,0 +1,2 @@
+from stable_baselines3.a2c.a2c import A2C
+from stable_baselines3.ppo.policies import MlpPolicy

torchy_baselines/a2c/a2c.py → stable_baselines3/a2c/a2c.py

@@ -3,11 +3,11 @@
 from gym import spaces
 from typing import Type, Union, Callable, Optional, Dict, Any
 
-from torchy_baselines.common import logger
-from torchy_baselines.common.type_aliases import GymEnv, MaybeCallback
-from torchy_baselines.common.utils import explained_variance
-from torchy_baselines.ppo.policies import PPOPolicy
-from torchy_baselines.ppo.ppo import PPO
+from stable_baselines3.common import logger
+from stable_baselines3.common.type_aliases import GymEnv, MaybeCallback
+from stable_baselines3.common.utils import explained_variance
+from stable_baselines3.ppo.policies import PPOPolicy
+from stable_baselines3.ppo.ppo import PPO
 
 
 class A2C(PPO):

torchy_baselines/common/base_class.py → stable_baselines3/common/base_class.py

@@ -11,17 +11,17 @@
 import torch as th
 import numpy as np
 
-from torchy_baselines.common import logger
-from torchy_baselines.common.policies import BasePolicy, get_policy_from_name
-from torchy_baselines.common.utils import set_random_seed, get_schedule_fn, update_learning_rate, get_device
-from torchy_baselines.common.vec_env import DummyVecEnv, VecEnv, unwrap_vec_normalize, VecNormalize, VecTransposeImage
-from torchy_baselines.common.preprocessing import is_image_space
-from torchy_baselines.common.save_util import data_to_json, json_to_data, recursive_getattr, recursive_setattr
-from torchy_baselines.common.type_aliases import GymEnv, TensorDict, RolloutReturn, MaybeCallback
-from torchy_baselines.common.callbacks import BaseCallback, CallbackList, ConvertCallback, EvalCallback
-from torchy_baselines.common.monitor import Monitor
-from torchy_baselines.common.noise import ActionNoise
-from torchy_baselines.common.buffers import ReplayBuffer
+from stable_baselines3.common import logger
+from stable_baselines3.common.policies import BasePolicy, get_policy_from_name
+from stable_baselines3.common.utils import set_random_seed, get_schedule_fn, update_learning_rate, get_device
+from stable_baselines3.common.vec_env import DummyVecEnv, VecEnv, unwrap_vec_normalize, VecNormalize, VecTransposeImage
+from stable_baselines3.common.preprocessing import is_image_space
+from stable_baselines3.common.save_util import data_to_json, json_to_data, recursive_getattr, recursive_setattr
+from stable_baselines3.common.type_aliases import GymEnv, TensorDict, RolloutReturn, MaybeCallback
+from stable_baselines3.common.callbacks import BaseCallback, CallbackList, ConvertCallback, EvalCallback
+from stable_baselines3.common.monitor import Monitor
+from stable_baselines3.common.noise import ActionNoise
+from stable_baselines3.common.buffers import ReplayBuffer
 
 
 class BaseRLModel(ABC):

torchy_baselines/common/buffers.py → stable_baselines3/common/buffers.py

@@ -4,9 +4,9 @@
 import torch as th
 from gym import spaces
 
-from torchy_baselines.common.vec_env import VecNormalize
-from torchy_baselines.common.type_aliases import RolloutBufferSamples, ReplayBufferSamples
-from torchy_baselines.common.preprocessing import get_action_dim, get_obs_shape
+from stable_baselines3.common.vec_env import VecNormalize
+from stable_baselines3.common.type_aliases import RolloutBufferSamples, ReplayBufferSamples
+from stable_baselines3.common.preprocessing import get_action_dim, get_obs_shape
 
 
 class BaseBuffer(object):