IDDM v1.1.4

[chairc]

What's Changed

• Add PLMS sampler; Add PLMS sample initializer. by @chairc in Add PLMS sampler; Add PLMS sample initializer. #51
• Removed forced checking of samplers, now free choice of sample generation; Add output image format; Add choices.py; Modify the choices attribute in parsers. by @chairc in Removed forced checking of samplers, now free choice of sample generation; Add output image format; Add choices.py; Modify the choices attribute in parsers. #52
• Update README.md by @chairc in Update README.md #53
• Add version.py. by @chairc in Add version.py. #54
• Add --save_model_interval_epochs parameter. Save model interval and save it every X epochs. by @chairc in Add --save_model_interval_epochs parameter. Save model interval and save it every X epochs. #55
• Modify the mean, std and random resized crop settings in torchvision.transforms.Compose; Modify the choices in parser and adjust the order of parts. by @chairc in Modify the mean, std and random resized crop settings in torchvision.transforms.Compose; Modify the choices in parser and adjust the order of parts. #56
• Fix: Fix unable to load unconditional model. by @chairc in Fix: Fix unable to load unconditional model. #57
• Modify the config in repository structure; Added "--noise_schedule" training parameters, this method is a model noise adding method. by @chairc in Modify the config in repository structure; Added "--noise_schedule" training parameters, this method is a model noise adding method. #59
• Added unetv2.py, replace nn.Upsample with nn.ConvTranspose2d; Add DDIM code comments; Fix the problem that bool in parser cannot be correctly recognized by the console. by @chairc in Added unetv2.py, replace nn.Upsample with nn.ConvTranspose2d; Add DDIM code comments; Fix the problem that bool in parser cannot be correctly recognized by the console. #61
• Modify the get_dataset; Add check.py; Add classes_initializer function by @chairc in Modify the get_dataset; Add check.py; Add classes_initializer function #62

Weights

• celebahq-120-weight.pt: Trained on a dataset of 30,000 people face, and image size is 120
• animate-ganyu-120-weight.pt: Trained on a dataset of 500 animate ganyu face, and image size is 120
• neu-120-weight.pt: Trained on a dataset of 1,800 defect, and image size is 120

Full Changelog: v1.1.3...v1.1.4