lit_sb3.modules.feature_extractors.nature_cnn

source module lit_sb3.modules.feature_extractors.nature_cnn

Classes

• NatureCNN — CNN from DQN Nature paper.

source class NatureCNN(observation_space: gym.Space, features_dim: int = 512, normalized_image: bool = False)

Bases : BaseFeaturesExtractor

CNN from DQN Nature paper.

Mnih, Volodymyr, et al.
"Human-level control through deep reinforcement learning."
Nature 518.7540 (2015): 529-533.

Parameters

• observation_space : gym.Space — The observation space of the environment

• features_dim : int — Number of features extracted. This corresponds to the number of unit for the last layer.

• normalized_image : bool — Whether to assume that the image is already normalized or not (this disables dtype and bounds checks): when True, it only checks that the space is a Box and has 3 dimensions. Otherwise, it checks that it has expected dtype (uint8) and bounds (values in [0, 255]).

Attributes

• features_dim : int — The number of features that the extractor outputs.

Methods

• forward

source method NatureCNN.forward(observations: torch.Tensor) → torch.Tensor