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python - Which PyTorch modules are affected by model.eval() and model.train()?

The model.eval() method modifies certain modules (layers) which are required to behave differently during training and inference. Some examples are listed in the docs:

This has [an] effect only on certain modules. See documentations of particular modules for details of their behaviors in training/evaluation mode, if they are affected, e.g. Dropout, BatchNorm, etc.

Is there an exhaustive list of which modules are affected?

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Searching site:https://pytorch.org/docs/stable/generated/torch.nn. "during evaluation" on google, it would appear the following modules are affected:

Base class Modules Criteria
_InstanceNorm InstanceNorm1d
InstanceNorm2d
InstanceNorm3d
track_running_stats=True
_BatchNorm BatchNorm1d
BatchNorm2d
BatchNorm3d
SyncBatchNorm
_DropoutNd Dropout
Dropout2d
Dropout3d
AlphaDropout
FeatureAlphaDropout

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