Index _ | B | C | D | E | F | G | L | M | P | S | T | U | W _ __init__() (experiments.tvn.TypicalVariationNormalizer method) (models.simclr_vanilla.SimCLRModel method) (models.simclr_vanilla.SimCLRProjectionHead method) (models.simclr_vanilla.SimCLRVanillaDataset method) (models.simclr_ws.LARS method) (models.simclr_ws.SimCLRDataset method) (models.simclr_ws.SimCLRModel method) (models.simclr_ws.SimCLRProjectionHead method) (models.wsdino_resnet.BBBC021WeakLabelDataset method) (models.wsdino_resnet.DINOProjectionHead method) (models.wsdino_resnet.MultiCropTransform method) B BBBC021WeakLabelDataset (class in models.wsdino_resnet) C components_ (experiments.tvn.TypicalVariationNormalizer attribute) contrastive_loss() (in module models.simclr_ws) contrastive_loss_vanilla() (in module models.simclr_vanilla) contrastive_loss_vanilla_compound_aware() (in module models.simclr_vanilla) create_feature_extractor() (in module models.load_model) D data.pybbbc_loader module dino_loss() (in module models.wsdino_resnet) DINOProjectionHead (class in models.wsdino_resnet) download_bbbc021() (in module data.pybbbc_loader) E eps (experiments.tvn.TypicalVariationNormalizer attribute) evaluate_model() (in module evaluation.evaluator) evaluation module evaluation.evaluator module evaluation.extractor module evaluation.visualization.visualize_embeddings module experiments module experiments.tvn module extract_moa_features() (in module evaluation.extractor) F fit() (experiments.tvn.TypicalVariationNormalizer method) forward() (models.simclr_vanilla.SimCLRModel method) (models.simclr_vanilla.SimCLRProjectionHead method) (models.simclr_ws.SimCLRModel method) (models.simclr_ws.SimCLRProjectionHead method) (models.wsdino_resnet.DINOProjectionHead method) G get_resnet50() (in module models.wsdino_resnet) L LARS (class in models.simclr_ws) load_model_features() (in module evaluation.visualization.visualize_embeddings) load_pretrained_model() (in module models.load_model) load_pretrained_model_from_weights() (in module models.load_model) load_pretrained_resnet50() (in module models.load_model) M mean_ (experiments.tvn.TypicalVariationNormalizer attribute) models module models.load_model module models.simclr_vanilla module models.simclr_ws module models.wsdino_resnet module module data.pybbbc_loader evaluation evaluation.evaluator evaluation.extractor evaluation.visualization.visualize_embeddings experiments experiments.tvn models models.load_model models.simclr_vanilla models.simclr_ws models.wsdino_resnet training training.simclr_vanilla_train training.simclr_ws_train training.wsdino_resnet_train MultiCropTransform (class in models.wsdino_resnet) P plot_accuracy_vs_image_count() (in module evaluation.visualization.visualize_embeddings) plot_tsne_comparison() (in module evaluation.visualization.visualize_embeddings) plot_umap_comparison() (in module evaluation.visualization.visualize_embeddings) preprocess_bbbc021() (in module data.pybbbc_loader) S SimCLRDataset (class in models.simclr_ws) SimCLRModel (class in models.simclr_vanilla) (class in models.simclr_ws) SimCLRProjectionHead (class in models.simclr_vanilla) (class in models.simclr_ws) SimCLRVanillaDataset (class in models.simclr_vanilla) step() (models.simclr_ws.LARS method) T train_simclr() (in module training.simclr_ws_train) train_simclr_vanilla() (in module training.simclr_vanilla_train) train_wsdino() (in module training.wsdino_resnet_train) training module training.simclr_vanilla_train module training.simclr_ws_train module training.wsdino_resnet_train module transform() (experiments.tvn.TypicalVariationNormalizer method) TypicalVariationNormalizer (class in experiments.tvn) U update_teacher() (in module models.wsdino_resnet) W whiten (experiments.tvn.TypicalVariationNormalizer attribute)