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EspeholtResidualEncoder

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EspeholtResidualEncoder(
   observation_space: gym.Space, feature_dim: int = 0, net_arch: List[int] = [16, 32,
   32]
)

ResNet-like encoder for processing image-based observations. Proposed by Espeholt L, Soyer H, Munos R, et al. Impala: Scalable distributed deep-rl with importance weighted actor-learner architectures[C]//International conference on machine learning. PMLR, 2018: 1407-1416. Target task: Atari games and Procgen games.

Args

  • observation_space (gym.Space) : Observation space.
  • feature_dim (int) : Number of features extracted.
  • net_arch (List) : Architecture of the network. It represents the out channels of each residual layer. The length of this list is the number of residual layers.

Returns

ResNet-like encoder instance.

Methods:

.forward

source 

.forward(
   obs: th.Tensor
)

Forward method implementation.

Args

  • obs (th.Tensor) : Observation tensor.

Returns

Encoded observation tensor.