PyTorch Adapt
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KevinMusgrave/pytorch-adapt
PyTorch Adapt
KevinMusgrave/pytorch-adapt
Overview
Getting started
Papers implemented
Papers implemented
Unsupervised Domain Adaptation
Validators
Documentation
Documentation
adapters
adapters
adabn
adda
aligner
base_adapter
classifier
dann
gan
mcd
symnets
utils
containers
containers
base_container
key_enforcer
lr_schedulers
misc
models
multiple_containers
optimizers
datasets
datasets
base_dataset
combined_source_and_target
concat_dataset
dataloader_creator
domainnet
mnistm
office31
officehome
pseudo_labeled_dataset
source_dataset
target_dataset
frameworks
frameworks
ignite
ignite
loggers
loggers
ignite_record_keeper_logger
checkpoint_utils
ignite
lightning
lightning
lightning
hooks
hooks
adabn
adda
aligners
atdoc
base
cdan
classification
conditions
dann
domain
domain_confusion
features
gan
gvb
mcd
optimizer
reducers
rtn
symnets
utils
vada
validate
inference
inference
inference
layers
layers
abs_loss
adaptive_feature_norm
batch_spectral_loss
bnm_loss
concat_softmax
confidence_weights
coral_loss
diversity_loss
do_nothing_optimizer
entropy_loss
entropy_weights
gradient_reversal
ist_loss
mcc_loss
mcd_loss
mmd_loss
model_with_bridge
multiple_models
neighborhood_aggregation
nll_loss
plus_residual
randomized_dot_product
silhouette_score
sliced_wasserstein
stochastic_linear
sufficient_accuracy
uniform_distribution_loss
vat_loss
meta_validators
meta_validators
forward_only_validator
reverse_validator
models
models
classifier
discriminator
mnist
pretrained
transforms
utils
validators
validators
accuracy_validator
base_validator
bnm_validator
deep_embedded_validator
diversity_validator
entropy_validator
error_validator
im_validator
multiple_validators
score_history
snd_validator
torchmetrics_validator
weighters
weighters
base_weighter
mean_weighter
sum_weighter
frameworks