Pads images such that dimensions are divisible by 8

r""" ConvNeXt Block. There are two equivalent implementations: (1) DwConv -> LayerNorm (channels_first) -> 1x1 Conv -> GELU -> 1x1 Conv; all in (N

GSA: using a key to summarize the information for a group to be efficient.

GSA: using a key to summarize the information for a group to be efficient.

GSA: using a key to summarize the information for a group to be efficient.

GSA: using a key to summarize the information for a group to be efficient.

Latent cost tokens attend to different group

Latent cost tokens attend to different group

r""" LayerNorm that supports two data formats: channels_last (default) or channels_first. The ordering of the dimensions in the inputs. channels_

LSA: self attention within a group

LSA: self attention within a group

LSA: self attention within a group

Image to Patch Embedding

Chromatic augmentation: https://github.com/lmb-freiburg/flownet2/blob/master/src/caffe/layers/data_augmentation_layer.cu

Composes several co_transforms together. For example: >>> co_transforms.Compose([ >>> co_transforms.CenterCrop(10), >>> co_tr

GSA: using a key to summarize the information for a group to be efficient.

Pads images such that dimensions are divisible by 8

This is a sinusoidal position encoding that generalized to 2-dimensional images

This is a sinusoidal position encoding that generalized to 2-dimensional images

Chromatic Eigen Augmentation: https://github.com/lmb-freiburg/flownet2/blob/master/src/caffe/layers/data_augmentation_layer.cu

This is a sinusoidal position encoding that generalized to 2-dimensional images