James Betker 009a1e8404 Add a new diffusion_vocoder that should be trainable faster ... This new one has a "cheating" top layer, that does not feed down into the unet encoder, but does consume the outputs of the unet. This cheater only operates on half of the input, while the rest of the unet operates on the full input. This limits the dimensionality of this last layer, on the assumption that these last layers consume by far the most computation and memory, but do not require the full input context. Losses are only computed on half of the aggregate input.		2022-01-11 17:26:07 -07:00
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byol
classifiers
diffusion
fixup_resnet
flownet2@db2b7899ea
glean
gpt_voice	Add a new diffusion_vocoder that should be trainable faster	2022-01-11 17:26:07 -07:00
lucidrains
optical_flow
segformer
spleeter
srflow
stylegan
switched_conv
tacotron2
vqvae
waveglow
__init__.py
arch_util.py
audio_resnet.py
clip.py
discriminator_vgg_arch.py
feature_arch.py
lightweight_gan.py
ResGen_arch.py
RRDBNet_arch.py
spinenet_arch.py