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Fix doc "Create Custom Feature Extractor", normalized_images #401

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Fix doc "Create Custom Feature Extractor", normalized_images #401

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5 changes: 3 additions & 2 deletions docs/content/training.md
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@ Although `StableBaselines3` is fully compatible with `Gymnasium`-based environme

```python
class MinigridFeaturesExtractor(BaseFeaturesExtractor):
def __init__(self, observation_space: gym.Space, features_dim: int = 512, normalized_image: bool = False) -> None:
def __init__(self, observation_space: gym.Space, features_dim: int = 512) -> None:
super().__init__(observation_space, features_dim)
n_input_channels = observation_space.shape[0]
self.cnn = nn.Sequential(
Expand Down Expand Up @@ -51,6 +51,7 @@ from stable_baselines3 import PPO
policy_kwargs = dict(
features_extractor_class=MinigridFeaturesExtractor,
features_extractor_kwargs=dict(features_dim=128),
normalize_images=False,
)

env = gym.make("MiniGrid-Empty-16x16-v0", render_mode="rgb_array")
Expand All @@ -64,4 +65,4 @@ By default the observation of Minigrid environments are dictionaries. Since the

## Further Reading

One can also pass dictionary observations to StableBaseline3 policies, for a walkthrough the process of doing so see [here](https://stable-baselines3.readthedocs.io/en/master/guide/custom_policy.html#multiple-inputs-and-dictionary-observations). An implementation utilizing this functionality can be found [here](https://github.com/BolunDai0216/MinigridMiniworldTransfer/blob/main/minigrid_gotoobj_train.py).
One can also pass dictionary observations to StableBaseline3 policies, for a walkthrough the process of doing so see [here](https://stable-baselines3.readthedocs.io/en/master/guide/custom_policy.html#multiple-inputs-and-dictionary-observations). An implementation utilizing this functionality can be found [here](https://github.com/BolunDai0216/MinigridMiniworldTransfer/blob/main/minigrid_gotoobj_train.py).
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