[Bug]: if learning_rate function uses special types, they can cause torch.load to fail when weights_only=True

[markscsmith]

🐛 Bug

When using the model save/load function, using certain types in a learning_rate function will cause the model.load to require weights_only=False because they are not an allowed safe unpickle type.

To Reproduce

from stable_baselines3 import PPO
import numpy as np
path = "ppo_pendulum.zip"
PPO("MlpPolicy", "Pendulum-v1", learning_rate=lambda _: np.sin(1.0)).save(path)       
PPO.load(path) # 💥

Relevant log output / Error message

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/mscs/OneFiveOne/venv/lib/python3.10/site-packages/stable_baselines3/common/base_class.py", line 680, in load
    data, params, pytorch_variables = load_from_zip_file(
  File "/home/mscs/OneFiveOne/venv/lib/python3.10/site-packages/stable_baselines3/common/save_util.py", line 450, in load_from_zip_file
    th_object = th.load(file_content, map_location=device, weights_only=True)
  File "/home/mscs/OneFiveOne/venv/lib/python3.10/site-packages/torch/serialization.py", line 1024, in load
    raise pickle.UnpicklingError(UNSAFE_MESSAGE + str(e)) from None
_pickle.UnpicklingError: Weights only load failed. Re-running `torch.load` with `weights_only` set to `False` will likely succeed, but it can result in arbitrary code execution.Do it only if you get the file from a trusted source. WeightsUnpickler error: Unsupported class numpy.core.multiarray.scalar

System Info

(venv) mscs@hush:~/OneFiveOne$ python -c 'import stable_baselines3 as sb3; sb3.get_system_info()'
2024-04-18 21:09:04.412040: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
- OS: Linux-6.5.0-27-generic-x86_64-with-glibc2.35 # 28~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Mar 15 10:51:06 UTC 2
- Python: 3.10.12
- Stable-Baselines3: 2.3.0
- PyTorch: 2.4.0.dev20240417+rocm6.0
- GPU Enabled: True
- Numpy: 1.26.4
- Cloudpickle: 3.0.0
- Gymnasium: 0.29.1
- OpenAI Gym: 0.26.2

Checklist

• My issue does not relate to a custom gym environment. (Use the custom gym env template instead)
• I have checked that there is no similar issue in the repo
• I have read the documentation
• I have provided a minimal and working example to reproduce the bug
• I've used the markdown code blocks for both code and stack traces.

[markscsmith]

See #1852 for details on the upstream reason in pytorch this is needed

[araffin]

For reference, this is not a bug per se (the return type of a lr schedule should be float, not np.ndarray) but it is annoying for users/error message should be improved anyway.

[markscsmith]

Oh! My bad! Should I recategorize as enhancement? Thank you for being so patient with my noob mistakes :)

[araffin]

Oh! My bad! Should I recategorize as enhancement? Thank you for being so patient with my noob mistakes :)

this is fine, no worry, I just wanted to comment in case someone else finds the issue.