d3rlpy.preprocessing.PixelScaler¶
-
class
d3rlpy.preprocessing.
PixelScaler
[source]¶ Pixel normalization preprocessing.
\[x' = x / 255\]from d3rlpy.dataset import MDPDataset from d3rlpy.algos import CQL dataset = MDPDataset(observations, actions, rewards, terminals) # initialize algorithm with PixelScaler cql = CQL(scaler='pixel') cql.fit(dataset.episodes)
Methods
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fit
(episodes)[source]¶ - Parameters
episodes (List[d3rlpy.dataset.Episode]) –
- Return type
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reverse_transform
(x)[source]¶ Returns reversely transformed observations.
- Parameters
x (torch.Tensor) – normalized observation tensor.
- Returns
unnormalized pixel observation tensor.
- Return type
torch.Tensor
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transform
(x)[source]¶ Returns normalized pixel observations.
- Parameters
x (torch.Tensor) – pixel observation tensor.
- Returns
normalized pixel observation tensor.
- Return type
torch.Tensor
Attributes
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