layers
The following can be imported like this (using AbsLoss as an example):
from pytorch_adapt.layers import AbsLoss
Direct module members¶
- AbsLoss
- AdaBNModel
- AdaptiveBatchNorm2d
- AdaptiveFeatureNorm
- BNMLoss
- BatchSpectralLoss
- CORALLoss
- ConcatSoftmax
- ConfidenceWeights
- DiversityLoss
- DoNothingOptimizer
- EntropyLoss
- EntropyWeights
- GeneralMCDLoss
- GradientReversal
- ISTLoss
- L2PreservedDropout
- MCCLoss
- MCDLoss
- MMDBatchedLoss
- MMDLoss
- MaxNormalizer
- MeanDistLoss
- MinMaxNormalizer
- ModelWithBridge
- MultipleModels
- NLLLoss
- NeighborhoodAggregation
- NoNormalizer
- PlusResidual
- PopulationBatchNorm2d
- RandomizedDotProduct
- SilhouetteScore
- SlicedWasserstein
- StochasticLinear
- SufficientAccuracy
- SumNormalizer
- SymNetsCategoryLoss
- SymNetsCategoryLossListInput
- SymNetsDomainLoss
- SymNetsEntropyLoss
- SymNetsEntropyLossListInput
- UniformDistributionLoss
- VATLoss