James Betker df1046c318 New arch: SwitchedResidualGenerator_arch ... The concept here is to use switching to split the generator into two functions: interpretation and transformation. Transformation is done at the pixel level by relatively simple conv layers, while interpretation is computed at various levels by far more complicated conv stacks. The two are merged using the switching mechanism. This architecture is far less computationally intensive that RRDB.		2020-06-16 11:23:50 -06:00
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archs	New arch: SwitchedResidualGenerator_arch	2020-06-16 11:23:50 -06:00
__init__.py	Implement downsample GAN	2020-04-24 00:00:46 -06:00
base_model.py	Introduce (untested) colab mode	2020-06-01 15:09:52 -06:00
loss.py	mmsr	2019-08-23 21:42:47 +08:00
lr_scheduler.py	Enable forced learning rates	2020-06-07 16:56:05 -06:00
networks.py	New arch: SwitchedResidualGenerator_arch	2020-06-16 11:23:50 -06:00
SR_model.py	Allow validating in batches, remove val size limit	2020-06-02 08:41:22 -06:00
SRGAN_model.py	Add GPU mem tracing module	2020-06-14 11:02:54 -06:00