Update and fix dependencies related to mac install (#1044)

Addresses part of #1015 ### Dependencies - move jsonargparse and docstring-parser to dependencies to run hl examples without dev - create mujoco-py extra for legacy mujoco envs - updated atari extra - removed atari-py and gym dependencies - added ALE-py, autorom, and shimmy - created robotics extra for HER-DDPG ### Mac specific - only install envpool when not on mac - mujoco-py not working on macOS newer than Monterey (https://github.com/openai/mujoco-py/issues/777) - D4RL also fails due to dependency on mujoco-py (https://github.com/Farama-Foundation/D4RL/issues/232) ### Other - reduced training-num/test-num in example files to a number ≤ 20 (examples with 100 led to too many open files) - rendering for Mujoco envs needs to be fixed on gymnasium side (https://github.com/Farama-Foundation/Gymnasium/issues/749) --------- Co-authored-by: Maximilian Huettenrauch <m.huettenrauch@appliedai.de> Co-authored-by: Michael Panchenko <35432522+MischaPanch@users.noreply.github.com>
2024-02-06 17:06:38 +01:00 · 2024-02-06 17:06:38 +01:00 · 5fe9aea798
commit 5fe9aea798
parent eb0215cf76
15 changed files with 442 additions and 132 deletions
--- a/README.md
+++ b/README.md
@ -96,6 +96,23 @@ You can also install the dev requirements by adding `--with dev` or the extras
 for say mujoco and acceleration by [envpool](https://github.com/sail-sg/envpool)
 by adding `--extras mujoco envpool`

+Available extras are:
+- `atari` (for Atari environments)
+- `box2d` (for Box2D environments)
+- `classic_control` (for classic control (discrete) environments)
+- `mujoco` (for MuJoCo environments)
+- `mujoco-py` (for legacy mujoco-py environments[^1])
+- `pybullet` (for pybullet environments)
+- `robotics` (for gymnasium-robotics environments)
+- `vizdoom` (for ViZDoom environments)
+- `envpool` (for [envpool](https://github.com/sail-sg/envpool/)  integration)
+- `argparse` (in order to be able to run the high level API examples)
+
+[^1]: `mujoco-py` is a legacy package and is not recommended for new projects. 
+It is only included for compatibility with older projects. 
+Also note that there may be compatibility issues with macOS newer than 
+Monterey.
+
 Otherwise, you can install the latest release from PyPI (currently
 far behind the master) with the following command:

@ -216,6 +233,8 @@ We shall apply the deep Q network (DQN) learning algorithm using both APIs.

 ### High-Level API

+The high-level API requires the extra package `argparse` (by adding 
+`--extras argparse`) to be installed.
 To get started, we need some imports.

 ```python
--- a/examples/box2d/acrobot_dualdqn.py
+++ b/examples/box2d/acrobot_dualdqn.py
@ -38,7 +38,7 @@ def get_args() -> argparse.Namespace:
    parser.add_argument("--dueling-q-hidden-sizes", type=int, nargs="*", default=[128, 128])
    parser.add_argument("--dueling-v-hidden-sizes", type=int, nargs="*", default=[128, 128])
    parser.add_argument("--training-num", type=int, default=10)
-    parser.add_argument("--test-num", type=int, default=100)
+    parser.add_argument("--test-num", type=int, default=10)
    parser.add_argument("--logdir", type=str, default="log")
    parser.add_argument("--render", type=float, default=0.0)
    parser.add_argument(
--- a/examples/box2d/bipedal_bdq.py
+++ b/examples/box2d/bipedal_bdq.py
@ -98,10 +98,11 @@ def test_bdq(args: argparse.Namespace = get_args()) -> None:
        device=args.device,
    ).to(args.device)
    optim = torch.optim.Adam(net.parameters(), lr=args.lr)
-    policy: BranchingDQNPolicy = BranchingDQNPolicy(
-        net,
-        optim,
-        args.gamma,
+    policy = BranchingDQNPolicy(
+        model=net,
+        optim=optim,
+        discount_factor=args.gamma,
+        action_space=env.action_space,
        target_update_freq=args.target_update_freq,
    )
    # collector
--- a/examples/box2d/bipedal_hardcore_sac.py
+++ b/examples/box2d/bipedal_hardcore_sac.py
@ -39,7 +39,7 @@ def get_args() -> argparse.Namespace:
    parser.add_argument("--batch-size", type=int, default=128)
    parser.add_argument("--hidden-sizes", type=int, nargs="*", default=[128, 128])
    parser.add_argument("--training-num", type=int, default=10)
-    parser.add_argument("--test-num", type=int, default=100)
+    parser.add_argument("--test-num", type=int, default=10)
    parser.add_argument("--logdir", type=str, default="log")
    parser.add_argument("--render", type=float, default=0.0)
    parser.add_argument("--n-step", type=int, default=4)
--- a/examples/box2d/lunarlander_dqn.py
+++ b/examples/box2d/lunarlander_dqn.py
@ -37,7 +37,7 @@ def get_args() -> argparse.Namespace:
    parser.add_argument("--dueling-q-hidden-sizes", type=int, nargs="*", default=[128, 128])
    parser.add_argument("--dueling-v-hidden-sizes", type=int, nargs="*", default=[128, 128])
    parser.add_argument("--training-num", type=int, default=16)
-    parser.add_argument("--test-num", type=int, default=100)
+    parser.add_argument("--test-num", type=int, default=10)
    parser.add_argument("--logdir", type=str, default="log")
    parser.add_argument("--render", type=float, default=0.0)
    parser.add_argument(
--- a/examples/box2d/mcc_sac.py
+++ b/examples/box2d/mcc_sac.py
@ -39,7 +39,7 @@ def get_args() -> argparse.Namespace:
    parser.add_argument("--batch-size", type=int, default=128)
    parser.add_argument("--hidden-sizes", type=int, nargs="*", default=[128, 128])
    parser.add_argument("--training-num", type=int, default=5)
-    parser.add_argument("--test-num", type=int, default=100)
+    parser.add_argument("--test-num", type=int, default=10)
    parser.add_argument("--logdir", type=str, default="log")
    parser.add_argument("--render", type=float, default=0.0)
    parser.add_argument(
--- a/examples/mujoco/fetch_her_ddpg.py
+++ b/examples/mujoco/fetch_her_ddpg.py
@ -9,7 +9,6 @@ import pprint
 import gymnasium as gym
 import numpy as np
 import torch
-import wandb
 from torch.utils.tensorboard import SummaryWriter


@ -32,7 +31,7 @@ from tianshou.utils.net.continuous import Actor, Critic

 def get_args() -> argparse.Namespace:
    parser = argparse.ArgumentParser()
-    parser.add_argument("--task", type=str, default="FetchReach-v3")
+    parser.add_argument("--task", type=str, default="FetchReach-v2")
    parser.add_argument("--seed", type=int, default=0)
    parser.add_argument("--buffer-size", type=int, default=100000)
    parser.add_argument("--hidden-sizes", type=int, nargs="*", default=[256, 256])
@ -105,8 +104,6 @@ def test_ddpg(args: argparse.Namespace = get_args()) -> None:
            config=args,
            project=args.wandb_project,
        )
-        logger.wandb_run.config.setdefaults(vars(args))
-        args = argparse.Namespace(**wandb.config)
    writer = SummaryWriter(log_path)
    writer.add_text("args", str(args))
    if args.logger == "tensorboard":
--- a/examples/mujoco/mujoco_ppo.py
+++ b/examples/mujoco/mujoco_ppo.py
@ -34,7 +34,7 @@ def get_args() -> argparse.Namespace:
    parser.add_argument("--step-per-collect", type=int, default=2048)
    parser.add_argument("--repeat-per-collect", type=int, default=10)
    parser.add_argument("--batch-size", type=int, default=64)
-    parser.add_argument("--training-num", type=int, default=64)
+    parser.add_argument("--training-num", type=int, default=8)
    parser.add_argument("--test-num", type=int, default=10)
    # ppo special
    parser.add_argument("--rew-norm", type=int, default=True)
--- a/examples/mujoco/mujoco_ppo_hl.py
+++ b/examples/mujoco/mujoco_ppo_hl.py
@ -34,7 +34,7 @@ def main(
    step_per_collect: int = 2048,
    repeat_per_collect: int = 10,
    batch_size: int = 64,
-    training_num: int = 64,
+    training_num: int = 10,
    test_num: int = 10,
    rew_norm: bool = True,
    vf_coef: float = 0.25,
--- a/examples/mujoco/mujoco_reinforce.py
+++ b/examples/mujoco/mujoco_reinforce.py
@ -35,7 +35,7 @@ def get_args() -> argparse.Namespace:
    parser.add_argument("--repeat-per-collect", type=int, default=1)
    # batch-size >> step-per-collect means calculating all data in one singe forward.
    parser.add_argument("--batch-size", type=int, default=None)
-    parser.add_argument("--training-num", type=int, default=64)
+    parser.add_argument("--training-num", type=int, default=10)
    parser.add_argument("--test-num", type=int, default=10)
    # reinforce special
    parser.add_argument("--rew-norm", type=int, default=True)
--- a/examples/mujoco/mujoco_reinforce_hl.py
+++ b/examples/mujoco/mujoco_reinforce_hl.py
@ -31,7 +31,7 @@ def main(
    step_per_collect: int = 2048,
    repeat_per_collect: int = 1,
    batch_size: int | None = None,
-    training_num: int = 64,
+    training_num: int = 10,
    test_num: int = 10,
    rew_norm: bool = True,
    action_bound_method: Literal["clip", "tanh"] = "tanh",
--- a/examples/vizdoom/vizdoom_c51.py
+++ b/examples/vizdoom/vizdoom_c51.py
@ -37,7 +37,7 @@ def get_args() -> argparse.Namespace:
    parser.add_argument("--update-per-step", type=float, default=0.1)
    parser.add_argument("--batch-size", type=int, default=64)
    parser.add_argument("--training-num", type=int, default=10)
-    parser.add_argument("--test-num", type=int, default=100)
+    parser.add_argument("--test-num", type=int, default=10)
    parser.add_argument("--logdir", type=str, default="log")
    parser.add_argument("--render", type=float, default=0.0)
    parser.add_argument(
--- a/examples/vizdoom/vizdoom_ppo.py
+++ b/examples/vizdoom/vizdoom_ppo.py
@ -34,7 +34,7 @@ def get_args() -> argparse.Namespace:
    parser.add_argument("--batch-size", type=int, default=256)
    parser.add_argument("--hidden-size", type=int, default=512)
    parser.add_argument("--training-num", type=int, default=10)
-    parser.add_argument("--test-num", type=int, default=100)
+    parser.add_argument("--test-num", type=int, default=10)
    parser.add_argument("--rew-norm", type=int, default=False)
    parser.add_argument("--vf-coef", type=float, default=0.5)
    parser.add_argument("--ent-coef", type=float, default=0.01)
--- a/poetry.lock
+++ b/poetry.lock
@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.7.0 and should not be changed by hand.

 [[package]]
 name = "absl-py"
@ -50,6 +50,41 @@ files = [
    {file = "alabaster-0.7.13.tar.gz", hash = "sha256:a27a4a084d5e690e16e01e03ad2b2e552c61a65469419b907243193de1a84ae2"},
 ]

+[[package]]
+name = "ale-py"
+version = "0.8.1"
+description = "The Arcade Learning Environment (ALE) - a platform for AI research."
+optional = true
+python-versions = ">=3.7"
+files = [
+    {file = "ale_py-0.8.1-cp310-cp310-macosx_10_15_x86_64.whl", hash = "sha256:b2aa2f69a4169742800615970efe6914fa856e33eaf7fa9133c0e06a617a80e2"},
+    {file = "ale_py-0.8.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:6f2f6b92c8fd6189654979bbf0b305dbe0ecf82176c47f244d8c1cbc36286b89"},
+    {file = "ale_py-0.8.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c9b168eb88c87d0f3e2a778e6c5cdde4ad951d1ca8a6dc3d3679fd45398df7d1"},
+    {file = "ale_py-0.8.1-cp310-cp310-win_amd64.whl", hash = "sha256:5fcc31f495de79ee1d6bfc0f4b7c4619948851e679bbf010035e25f23146a687"},
+    {file = "ale_py-0.8.1-cp311-cp311-macosx_10_15_x86_64.whl", hash = "sha256:0856ca777473ec4ae8a59f3af9580259adb0fd4a47d586a125a440c62e82fc10"},
+    {file = "ale_py-0.8.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f10b1df8774bbe3b00365748b5e0e07cf35f6a703bbaff991bc7b3b2247dccc9"},
+    {file = "ale_py-0.8.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0006d80dfe7745eb5a93444492337203c8bc7eb594a2c24c6a651c5c5b0eaf09"},
+    {file = "ale_py-0.8.1-cp311-cp311-win_amd64.whl", hash = "sha256:9773eea7505484e024beb2fff0f3bfd363db151bdb9799d70995448e196b1ded"},
+    {file = "ale_py-0.8.1-cp37-cp37m-macosx_10_15_x86_64.whl", hash = "sha256:87557db05be0e04130e2ec1bf909d3bb0b0bc034645d4f664e6baa573fe32191"},
+    {file = "ale_py-0.8.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ae2ba24557e0ce541ea3be13b148db2a9cfa730d83537b4cbed5e10449826e51"},
+    {file = "ale_py-0.8.1-cp37-cp37m-win_amd64.whl", hash = "sha256:ade5c32af567629164a6b49378978c728a15dc4db07ad6b679e8832d4fd3ea1f"},
+    {file = "ale_py-0.8.1-cp38-cp38-macosx_10_15_x86_64.whl", hash = "sha256:0ffecb5c956749596030e464827642945162170a132d093c3d4fa2d7e5725c18"},
+    {file = "ale_py-0.8.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:7cd74b7ee0248ef11a086c9764e142e71defd40ec8989a99232bfd2d9e8023be"},
+    {file = "ale_py-0.8.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eadf9f3990b4ff2f9e5ca35889f5e2e95cddd6a353d9d857d9b4601a6e1c4e7c"},
+    {file = "ale_py-0.8.1-cp38-cp38-win_amd64.whl", hash = "sha256:817adf9a3a82c4923c731e634520a5ecf296aca0367f5c69959a96b32119d831"},
+    {file = "ale_py-0.8.1-cp39-cp39-macosx_10_15_x86_64.whl", hash = "sha256:2d9fcfa06c74a613c5419e942ef4d3e0959533f52e94d2d4bda61d07fbfffeee"},
+    {file = "ale_py-0.8.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f278036f9b6066062abcdf0987a0ec5a8e0f22a2c7cfac925e39378d4343d490"},
+    {file = "ale_py-0.8.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b00f74e27815131c1a2791f3d48114363fa2708e19f09ce6b7b614cb14c9d469"},
+    {file = "ale_py-0.8.1-cp39-cp39-win_amd64.whl", hash = "sha256:d49b550a2d9c25b63c343aa680fd81f253a3714cdc0e1835640933ebff1798ff"},
+]
+
+[package.dependencies]
+importlib-resources = "*"
+numpy = "*"
+
+[package.extras]
+test = ["gym (>=0.23,<1.0)", "pytest (>=7.0)"]
+
 [[package]]
 name = "anyio"
 version = "4.0.0"
@ -222,36 +257,6 @@ files = [
    {file = "async_lru-2.0.4-py3-none-any.whl", hash = "sha256:ff02944ce3c288c5be660c42dbcca0742b32c3b279d6dceda655190240b99224"},
 ]

-[[package]]
-name = "atari-py"
-version = "0.2.9"
-description = "Python bindings to Atari games"
-optional = true
-python-versions = "*"
-files = [
-    {file = "atari-py-0.2.9.tar.gz", hash = "sha256:cb1b4355e3e4b628e272de8317e8dceeadeeabb821b33800409e17ffc3095e20"},
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-]
-
-[package.dependencies]
-numpy = "*"
-six = "*"
-
 [[package]]
 name = "attrs"
 version = "23.1.0"
@ -284,6 +289,43 @@ files = [
 [package.dependencies]
 Sphinx = ">=2.2,<8.0"

+[[package]]
+name = "autorom"
+version = "0.4.2"
+description = "Automated installation of Atari ROMs for Gym/ALE-Py"
+optional = true
+python-versions = ">=3.6"
+files = [
+    {file = "AutoROM-0.4.2-py3-none-any.whl", hash = "sha256:719c9d363ef08391fdb7003d70df235b68f36de628d289a946c4a59a3adefa13"},
+    {file = "AutoROM-0.4.2.tar.gz", hash = "sha256:b426a39bc0ee3781c7791f28963a9b2e4385b6421eeaf2f368edc00c761d428a"},
+]
+
+[package.dependencies]
+"AutoROM.accept-rom-license" = {version = "*", optional = true, markers = "extra == \"accept-rom-license\""}
+click = "*"
+requests = "*"
+tqdm = "*"
+
+[package.extras]
+accept-rom-license = ["AutoROM.accept-rom-license"]
+
+[[package]]
+name = "autorom-accept-rom-license"
+version = "0.6.1"
+description = "Automated installation of Atari ROMs for Gym/ALE-Py"
+optional = true
+python-versions = ">=3.7"
+files = [
+    {file = "AutoROM.accept-rom-license-0.6.1.tar.gz", hash = "sha256:0c905a708d634a076f686802f672817d3585259ce3be0bde8713a4fb59e3159e"},
+]
+
+[package.dependencies]
+click = "*"
+requests = "*"
+
+[package.extras]
+tests = ["ale_py", "multi_agent_ale_py"]
+
 [[package]]
 name = "babel"
 version = "2.13.1"
@ -379,6 +421,20 @@ webencodings = "*"
 [package.extras]
 css = ["tinycss2 (>=1.1.0,<1.3)"]

+[[package]]
+name = "box2d-py"
+version = "2.3.5"
+description = "Python Box2D"
+optional = true
+python-versions = "*"
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 version = "0.15"
 description = "Parse Python docstrings in reST, Google and Numpydoc format"
-optional = false
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 python-versions = ">=3.6,<4.0"
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 typing-extensions = "*"

+[[package]]
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+typing_extensions = {version = "*", optional = true, markers = "extra == \"epy\""}
+zipp = {version = "*", optional = true, markers = "extra == \"epath\""}
+
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+ecolab = ["etils[enp]", "etils[epy]", "etils[etree]", "jupyter", "mediapy", "numpy", "packaging", "protobuf"]
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+etree-tf = ["etils[etree]", "tensorflow"]
+lazy-imports = ["etils[ecolab]"]
+
 [[package]]
 name = "executing"
 version = "2.0.1"
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 testing = ["pytest (==7.1.3)", "scipy (==1.7.3)"]
 toy-text = ["pygame (==2.1.3)", "pygame (==2.1.3)"]

+[[package]]
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+version = "1.2.3"
+description = "Robotics environments for the Gymnasium repo."
+optional = true
+python-versions = ">=3.8"
+files = [
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+mujoco = ">=2.3.3"
+numpy = ">=1.21.0"
+PettingZoo = ">=1.23.0"
+
+[package.extras]
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+testing = ["Jinja2 (>=3.0.3)", "PettingZoo (>=1.23.0)", "cython (<3)", "mujoco-py (>=2.1,<2.2)", "pytest (==7.0.1)"]
+
 [[package]]
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 version = "3.10.0"
@ -1638,6 +1754,21 @@ docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker
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+[[package]]
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+version = "6.1.1"
+description = "Read resources from Python packages"
+optional = true
+python-versions = ">=3.8"
+files = [
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+
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@ -1825,7 +1956,7 @@ dev = ["hypothesis"]
 name = "jsonargparse"
 version = "4.27.0"
 description = "Implement minimal boilerplate CLIs derived from type hints and parse from command line, config files and environment variables."
-optional = false
+optional = true
 python-versions = ">=3.7"
 files = [
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 ]

+[[package]]
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+version = "3.1.1"
+description = "MuJoCo Physics Simulator"
+optional = true
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.dependencies]
+absl-py = "*"
+etils = {version = "*", extras = ["epath"]}
+glfw = "*"
+numpy = "*"
+pyopengl = "*"
+
 [[package]]
 name = "mujoco-py"
 version = "2.1.2.14"
@ -3296,7 +3469,7 @@ ptyprocess = ">=0.5"
 name = "pillow"
 version = "10.2.0"
 description = "Python Imaging Library (Fork)"
-optional = false
+optional = true
 python-versions = ">=3.8"
 files = [
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 [package.extras]
 dev = ["aafigure", "matplotlib", "pygame", "pyglet (<2.0.0)", "sphinx", "wheel"]

+[[package]]
+name = "pyopengl"
+version = "3.1.7"
+description = "Standard OpenGL bindings for Python"
+optional = true
+python-versions = "*"
+files = [
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+]
+
 [[package]]
 name = "pytest"
 version = "7.4.3"
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 testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
 testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "packaging (>=23.1)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]

+[[package]]
+name = "shimmy"
+version = "0.2.1"
+description = "API for converting popular non-gymnasium environments to a gymnasium compatible environment."
+optional = true
+python-versions = ">=3.7"
+files = [
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+]
+
+[package.dependencies]
+gymnasium = ">=0.27.0"
+numpy = ">=1.18.0"
+
+[package.extras]
+all = ["ale-py (>=0.8.1,<0.9.0)", "dm-control (>=1.0.10)", "gym (>=0.21)", "h5py (>=3.7.0)", "imageio", "open-spiel (>=1.2)", "pettingzoo (>=1.22)"]
+atari = ["ale-py (>=0.8.1,<0.9.0)"]
+dm-control = ["dm-control (>=1.0.10)", "h5py (>=3.7.0)", "imageio"]
+dm-control-multi-agent = ["dm-control (>=1.0.10)", "pettingzoo (>=1.22)"]
+gym = ["gym (>=0.21)"]
+openspiel = ["open-spiel (>=1.2)", "pettingzoo (>=1.22)"]
+testing = ["autorom[accept-rom-license] (>=0.4.2,<0.5.0)", "pillow (>=9.3.0)", "pytest (==7.1.3)"]
+
 [[package]]
 name = "shortuuid"
 version = "1.0.11"
@ -5376,6 +5583,31 @@ pure-eval = "*"
 [package.extras]
 tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]

+[[package]]
+name = "swig"
+version = "4.2.0"
+description = "SWIG is a software development tool that connects programs written in C and C++ with a variety of high-level programming languages."
+optional = true
+python-versions = "*"
+files = [
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+    {file = "swig-4.2.0-py2.py3-none-win_amd64.whl", hash = "sha256:423daa17c9f9d83cafbfeeb7d7e99ac4c68bf4be8f138de9f7553ea3b57ba51d"},
+    {file = "swig-4.2.0.tar.gz", hash = "sha256:aae1c50f3fcfdcd647dbbfdd49f2f8c416e3e8b573fb33002e8c64318cdab883"},
+]
+
 [[package]]
 name = "sympy"
 version = "1.12"
@ -5751,6 +5983,41 @@ platformdirs = ">=3.9.1,<4"
 docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
 test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]

+[[package]]
+name = "vizdoom"
+version = "1.2.2"
+description = "ViZDoom is Doom-based AI Research Platform for Reinforcement Learning from Raw Visual Information."
+optional = true
+python-versions = "*"
+files = [
+    {file = "vizdoom-1.2.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:3e2f478e1728702f17b828de0e7ee6bf0e2809c1786ce21f69ce00e4a4da82e0"},
+    {file = "vizdoom-1.2.2-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:49180ed13d30109bcd99b38e6b923c5bd74e6bb364add8d46beb5cdf7405fe10"},
+    {file = "vizdoom-1.2.2-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:62b9c3e7f43f0234bf1803994fdbfb1626f320925b645e0257aadc6ef270b984"},
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+    {file = "vizdoom-1.2.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:ef6f0420c8bdf8b5521a219723127ab86e4e7fa242cb5e7779d1c6c9819fea88"},
+    {file = "vizdoom-1.2.2-cp39-cp39-manylinux_2_28_aarch64.whl", hash = "sha256:d32766326a5e5d13c79bfa8146e4be580f3efc83a75be086c197dba40b701e6e"},
+    {file = "vizdoom-1.2.2-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:3c8b9a853c46425dc12b45de639a0a55bd55804b4967127e26b08651caf3cc3f"},
+    {file = "vizdoom-1.2.2-cp39-cp39-win_amd64.whl", hash = "sha256:96d0f6eb046acf1e725adf29f7e83cfb1aea7fb6dd871c18acbb8d327911166d"},
+    {file = "vizdoom-1.2.2.tar.gz", hash = "sha256:21a69bef1131c5d94dea09bc5c96b5a2779775c1f42ade0b57c740eb9d19915b"},
+]
+
+[package.dependencies]
+gymnasium = ">=0.28.0"
+numpy = "*"
+pygame = ">=2.1.3"
+
+[package.extras]
+gym = ["gym (>=0.26.0)", "pygame (>=2.1.3)"]
+test = ["psutil", "pytest"]
+
 [[package]]
 name = "wandb"
 version = "0.12.21"
@ -5900,12 +6167,18 @@ docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.link
 testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]

 [extras]
-atari = ["atari_py", "opencv_python"]
+argparse = ["docstring-parser", "jsonargparse"]
+atari = ["ale-py", "autorom", "opencv_python", "shimmy"]
+box2d = ["box2d_py", "pygame", "swig"]
+classic-control = ["pygame"]
 envpool = ["envpool"]
-mujoco = ["mujoco_py"]
+mujoco = ["imageio", "mujoco"]
+mujoco-py = ["cython", "mujoco-py"]
 pybullet = ["pybullet"]
+robotics = ["gymnasium-robotics"]
+vizdoom = ["vizdoom"]

 [metadata]
 lock-version = "2.0"
 python-versions = "^3.11"
-content-hash = "375a3ce85cefea9ee4ec3dc062bcc3486c8b790768e70cca4d0ac779d0217547"
+content-hash = "a716cd85e29f19839254b0b64c3b5d1c16c1b6f0d9f59a254bbc2b5c06f816ea"
--- a/pyproject.toml
+++ b/pyproject.toml
@ -46,26 +46,46 @@ virtualenv = [
 ]

 # TODO: add versions
-atari_py = { version = "*", optional = true }
-envpool = { version = "^0.8.2", optional = true }
-mujoco_py = { version = "*", optional = true }
+ale-py = { version = "~=0.8.1", optional = true }
+autorom = { version = "~=0.4.2", extras = ["accept-rom-license"], optional = true }
+box2d_py = { version = "2.3.5", optional = true }
+cython = { version = ">=0.27.2", optional = true }
+docstring-parser = { version = "^0.15", optional = true }
+envpool = { version = "^0.8.2", optional = true,  markers = "sys_platform != 'darwin'"}
+gymnasium-robotics = { version = "*", optional = true }
+imageio = { version = ">=2.14.1", optional = true }
+jsonargparse = {version = "^4.24.1", optional = true}
+mujoco = { version = ">=2.1.5", optional = true }
+mujoco-py = { version = ">=2.1,<2.2", optional = true }
 opencv_python = { version = "*", optional = true }
 pybullet = { version = "*", optional = true }
+pygame = { version = ">=2.1.3", optional = true }
+shimmy = { version = ">=0.1.0,<1.0", optional = true }
+swig = { version = "4.*", optional = true }
+vizdoom = { version = "*", optional = true }

+# Atari, box2d, classic-control, and mujoco environments are all optional dependencies of gymnasium.
+# Unfortunately, we cannot have extras relying on (multiple) optionals of other packages due to a poetry issue (see e.g.
+# https://github.com/python-poetry/poetry/issues/7911) and therefore have to maintain our own list of dependencies.
+# This requires attention and monitoring of gymnasium's dependencies and their version numbers!
 [tool.poetry.extras]
-atari = ["atari_py", "opencv-python"]
-mujoco = ["mujoco_py"]
+argparse = ["docstring-parser", "jsonargparse"]
+atari = ["ale-py", "autorom", "opencv-python", "shimmy"]
+box2d = ["box2d-py", "pygame", "swig"]
+classic_control = ["pygame"]
+mujoco = ["mujoco", "imageio"]
+mujoco_py = ["mujoco-py", "cython"]
 pybullet = ["pybullet"]
 envpool = ["envpool"]
+robotics = ["gymnasium-robotics"]
+vizdoom = ["vizdoom"]


 [tool.poetry.group.dev]
 optional = true
 [tool.poetry.group.dev.dependencies]
 black = { version = "^23.7.0", extras = ["jupyter"] }
-docstring-parser = "^0.15"
 jinja2 = "*"
-jsonargparse = "^4.24.1"
 jupyter = "^1.0.0"
 jupyter-book = "^0.15.1"
 mypy = "^1.4.1"