Reinforcement Learning
stable-baselines3
deep-reinforcement-learning
agricultural-ai
weather-modelling
curriculum-learning
edge-ai
Instructions to use DHDRL/monsoon-rl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use DHDRL/monsoon-rl with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="DHDRL/monsoon-rl", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Update train_curriculum.py
Browse files- train_curriculum.py +4 -1
train_curriculum.py
CHANGED
|
@@ -352,7 +352,10 @@ class DynaCallback(BaseCallback):
|
|
| 352 |
return True # safe: missing locals, skip silently
|
| 353 |
|
| 354 |
if hasattr(obs_now, "numpy"):
|
| 355 |
-
|
|
|
|
|
|
|
|
|
|
| 356 |
else:
|
| 357 |
obs_now_np = obs_now
|
| 358 |
|
|
|
|
| 352 |
return True # safe: missing locals, skip silently
|
| 353 |
|
| 354 |
if hasattr(obs_now, "numpy"):
|
| 355 |
+
if hasattr(obs_now, "items"):
|
| 356 |
+
obs_now_np = {k: v.cpu().numpy() for k, v in obs_now.items()}
|
| 357 |
+
else:
|
| 358 |
+
obs_now_np = {"_raw": obs_now.cpu().numpy()}
|
| 359 |
else:
|
| 360 |
obs_now_np = obs_now
|
| 361 |
|