# %% from siim_isic_melanoma_classification import ( io, util, task, transforms as my_transforms, ) from siim_isic_melanoma_classification.config import get_config from siim_isic_melanoma_classification.net import EfficientNetB5MLP # %% config = get_config() # %% util.initialize(config) if util.is_kaggle(): import kaggle_timm_pretrained kaggle_timm_pretrained.patch() # %% train_transform = transforms.Compose([ transforms.RandomResizedCrop(size=config.image_size, scale=(0.8, 1.0)), transforms.RandomHorizontalFlip(), transforms.RandomVerticalFlip(), my_transforms.Microscope(p=0.5), transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]), ])
Classifier, ) # %% from category_encoders import TargetEncoder # %% config = get_config() # %% logger = get_logger() logger.log_hyperparams(config.__dict__) # %% util.initialize(config) if util.is_kaggle(): import kaggle_timm_pretrained kaggle_timm_pretrained.patch() # %% train_transform = transforms.Compose([ transforms.RandomResizedCrop(size=config.image_size, scale=(0.8, 1.0)), transforms.RandomHorizontalFlip(), transforms.RandomVerticalFlip(), my_transforms.Microscope(p=0.5), transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]), ]) test_transform = transforms.Compose([