ModuleNotFoundError: No module named 'baselines'

[amrzv]

Hello.
When running jax_agent_visualizer.ipynb notebook in colab this error is raised on from dopamine.discrete_domains import atari_lib

ModuleNotFoundError                       Traceback (most recent call last)
[<ipython-input-2-c78a96aa2548>](https://localhost:8080/#) in <cell line: 0>()
      1 # @title Imports
----> 2 from dopamine.discrete_domains import atari_lib
      3 from dopamine.jax.agents.dqn import dqn_agent
      4 from dopamine.jax.agents.implicit_quantile import implicit_quantile_agent
      5 from dopamine.jax.agents.quantile import quantile_agent

[/usr/local/lib/python3.11/dist-packages/dopamine/discrete_domains/atari_lib.py](https://localhost:8080/#) in <module>
     43 
     44 import ale_py
---> 45 from baselines.common import atari_wrappers
     46 import cv2
     47 import gin

ModuleNotFoundError: No module named 'baselines'

[krtimisra67]

pip install baseline
(It might not be installed in your system)

[amrzv]

Should it be in the requirements of this project then?

Btw, pip install baselines doesn't work in colab

Collecting baselines
  Using cached baselines-0.1.5.tar.gz (123 kB)
  Preparing metadata (setup.py) ... done
Requirement already satisfied: gym[atari,classic_control,mujoco,robotics] in /usr/local/lib/python3.11/dist-packages (from baselines) (0.25.2)
Requirement already satisfied: scipy in /usr/local/lib/python3.11/dist-packages (from baselines) (1.13.1)
Requirement already satisfied: tqdm in /usr/local/lib/python3.11/dist-packages (from baselines) (4.67.1)
Requirement already satisfied: joblib in /usr/local/lib/python3.11/dist-packages (from baselines) (1.4.2)
Collecting zmq (from baselines)
  Using cached zmq-0.0.0.zip (2.2 kB)
  Preparing metadata (setup.py) ... done
Collecting dill (from baselines)
  Using cached dill-0.3.9-py3-none-any.whl.metadata (10 kB)
Requirement already satisfied: progressbar2 in /usr/local/lib/python3.11/dist-packages (from baselines) (4.5.0)
Collecting mpi4py (from baselines)
  Using cached mpi4py-4.0.2.tar.gz (466 kB)
  Installing build dependencies ... done
  Getting requirements to build wheel ... done
  Installing backend dependencies ... done
  Preparing metadata (pyproject.toml) ... done
Requirement already satisfied: cloudpickle in /usr/local/lib/python3.11/dist-packages (from baselines) (3.1.1)
Requirement already satisfied: tensorflow>=1.4.0 in /usr/local/lib/python3.11/dist-packages (from baselines) (2.18.0)
Requirement already satisfied: click in /usr/local/lib/python3.11/dist-packages (from baselines) (8.1.8)
Requirement already satisfied: absl-py>=1.0.0 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (1.4.0)
Requirement already satisfied: astunparse>=1.6.0 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (1.6.3)
Requirement already satisfied: flatbuffers>=24.3.25 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (25.1.24)
Requirement already satisfied: gast!=0.5.0,!=0.5.1,!=0.5.2,>=0.2.1 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (0.6.0)
Requirement already satisfied: google-pasta>=0.1.1 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (0.2.0)
Requirement already satisfied: libclang>=13.0.0 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (18.1.1)
Requirement already satisfied: opt-einsum>=2.3.2 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (3.4.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (24.2)
Requirement already satisfied: protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<6.0.0dev,>=3.20.3 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (4.25.6)
Requirement already satisfied: requests<3,>=2.21.0 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (2.32.3)
Requirement already satisfied: setuptools in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (75.1.0)
Requirement already satisfied: six>=1.12.0 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (1.17.0)
Requirement already satisfied: termcolor>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (2.5.0)
Requirement already satisfied: typing-extensions>=3.6.6 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (4.12.2)
Requirement already satisfied: wrapt>=1.11.0 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (1.17.2)
Requirement already satisfied: grpcio<2.0,>=1.24.3 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (1.70.0)
Requirement already satisfied: tensorboard<2.19,>=2.18 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (2.18.0)
Requirement already satisfied: keras>=3.5.0 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (3.8.0)
Requirement already satisfied: numpy<2.1.0,>=1.26.0 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (1.26.4)
Requirement already satisfied: h5py>=3.11.0 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (3.12.1)
Requirement already satisfied: ml-dtypes<0.5.0,>=0.4.0 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (0.4.1)
Requirement already satisfied: tensorflow-io-gcs-filesystem>=0.23.1 in /usr/local/lib/python3.11/dist-packages (from tensorflow>=1.4.0->baselines) (0.37.1)
WARNING: gym 0.25.2 does not provide the extra 'robotics'
Requirement already satisfied: gym_notices>=0.0.4 in /usr/local/lib/python3.11/dist-packages (from gym[atari,classic_control,mujoco,robotics]->baselines) (0.0.8)
INFO: pip is looking at multiple versions of gym[atari,classic-control,mujoco,robotics] to determine which version is compatible with other requirements. This could take a while.
Collecting gym[atari,classic_control,mujoco,robotics] (from baselines)
  Downloading gym-0.26.2.tar.gz (721 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 721.7/721.7 kB 15.3 MB/s eta 0:00:00
  Installing build dependencies ... done
  Getting requirements to build wheel ... done
  Preparing metadata (pyproject.toml) ... done
WARNING: gym 0.26.2 does not provide the extra 'robotics'
Collecting ale-py~=0.8.0 (from gym[atari,classic_control,mujoco,robotics]->baselines)
  Downloading ale_py-0.8.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (8.1 kB)
Collecting pygame==2.1.0 (from gym[atari,classic_control,mujoco,robotics]->baselines)
  Downloading pygame-2.1.0.tar.gz (5.8 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 5.8/5.8 MB 71.5 MB/s eta 0:00:00
  error: subprocess-exited-with-error
  
  × python setup.py egg_info did not run successfully.
  │ exit code: 1
  ╰─> See above for output.
  
  note: This error originates from a subprocess, and is likely not a problem with pip.
  Preparing metadata (setup.py) ... error
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details.v

[krtimisra67]

Then try installing pygame before baselines
=> pip install pygame==2.1.0 --no-cache-dir
=> pip install pygame
=>pip install baselines
Also check for system dependencies
For Linux
=>sudo apt update
sudo apt install -y libsdl2-dev libsdl2-image-dev libsdl2-mixer-dev libsdl2-ttf-dev
For windows
=>python3 -m venv myenv
source myenv/bin/activate # On Windows, use "myenv\Scripts\activate"
pip install baselines

[amrzv]

Looks like the problem is in outdated pypi package of baselines, see openai/baselines#693

I was able to install from source pip install git+https://github.com/openai/baselines. However, on from dopamine.replay_memory import circular_replay_buffer getting ModuleNotFoundError

ModuleNotFoundError                       Traceback (most recent call last)
[<ipython-input-3-c78a96aa2548>](https://localhost:8080/#) in <cell line: 0>()
      5 from dopamine.jax.agents.quantile import quantile_agent
      6 from dopamine.jax.agents.rainbow import rainbow_agent
----> 7 from dopamine.replay_memory import circular_replay_buffer
      8 from dopamine.utils import example_viz_lib
      9 import gin

ModuleNotFoundError: No module named 'dopamine.replay_memory'

[krtimisra67]

!pip install --upgrade --no-cache-dir git+https://github.com/google/dopamine.git # Reinstalling dopamine

Restart the runtime after this installation.

Try importing again:

from dopamine.replay_memory import circular_replay_buffer
print("Module imported successfully!")
[I tried on my system as well]

See i tried this but i think there is some issue with the file structure of the installed package or a conflict with other installed libraries.Double-check the output of !pip show dopamine to ensure it's installed and points to the correct location. You may need to examine the package structure to ensure replay_memory and circular_replay_buffer are present in the expected locations.

[amrzv]

Installing both from souce

!pip install git+https://github.com/openai/baselines git+https://github.com/google/dopamine.git

fails
pythonpython
ERROR: Cannot install baselines, baselines==0.1.6, dopamine_rl and tensorflow-probability==0.24.0 because these package versions have conflicting dependencies.

The conflict is caused by:
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.24.0 depends on cloudpickle>=1.3
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.25.0 depends on cloudpickle>=1.3
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.23.0 depends on cloudpickle>=1.3
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.22.1 depends on cloudpickle>=1.3
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.22.0 depends on cloudpickle>=1.3
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.21.0 depends on cloudpickle>=1.3
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.20.1 depends on cloudpickle>=1.3
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.19.0 depends on cloudpickle>=1.3
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.18.0 depends on cloudpickle>=1.3
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.17.0 depends on cloudpickle>=1.3
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.16.0 depends on cloudpickle>=1.3
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.15.0 depends on cloudpickle>=1.3
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.14.1 depends on cloudpickle>=1.3
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.14.0 depends on cloudpickle>=1.3
baselines 0.1.6 depends on cloudpickle
gym 0.15.4 depends on cloudpickle~=1.2.0
gymnasium 1.0.0 depends on cloudpickle>=1.2.0
tensorflow-probability 0.13.0 depends on cloudpickle>=1.3