* All models updated with revised foward_features / forward_head interface * Vision transformer and MLP based models consistently output sequence from forward_features (pooling or token selection considered part of 'head') * WIP param grouping interface to allow consistent grouping of parameters for layer-wise decay across all model types * Add gradient checkpointing support to a significant % of models, especially popular architectures * Formatting and interface consistency improvements across models * layer-wise LR decay impl part of optimizer factory w/ scale support in scheduler * Poolformer and Volo architectures added |
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.. | ||
parsers | ||
__init__.py | ||
auto_augment.py | ||
config.py | ||
constants.py | ||
dataset.py | ||
dataset_factory.py | ||
distributed_sampler.py | ||
loader.py | ||
mixup.py | ||
random_erasing.py | ||
real_labels.py | ||
tf_preprocessing.py | ||
transforms.py | ||
transforms_factory.py |