Index _ | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W _ __call__() (mipcandy.inference.Predictor method) (mipcandy.training.Trainer method) __entry__() (in module mipcandy.__entry__) __getitem__() (mipcandy.data.dataset._AbstractDataset method) (mipcandy.data.dataset.SupervisedDataset method) (mipcandy.data.dataset.UnsupervisedDataset method) (mipcandy.data.inspection.InspectionAnnotations method) (mipcandy.evaluation.EvalResult method) __LABEL_COLORMAP (in module mipcandy.data.visualization) __len__() (mipcandy.data.dataset.BinarizedDataset method) (mipcandy.data.dataset.ComposeDataset method) (mipcandy.data.dataset.SupervisedDataset method) (mipcandy.data.dataset.UnsupervisedDataset method) (mipcandy.data.inspection.InspectionAnnotations method) (mipcandy.evaluation.EvalResult method) __str__() (mipcandy.profiler._LineBreak method) (mipcandy.profiler.ProfilerFrame method) (mipcandy.sanity_check.SanityCheckResult method) (mipcandy.training.Trainer method) _AbstractDataset (class in mipcandy.data.dataset) _allocate_experiment_folder() (mipcandy.training.Trainer method) _args_check() (in module mipcandy.metrics) _build_toolbox() (mipcandy.training.Trainer method) _c_p() (mipcandy.common.module.preprocess.Pad static method) _c_t() (mipcandy.common.module.preprocess.Pad static method) _conv_block() (in module mipcandy.common.module.conv) _create_subset() (mipcandy.data.dataset.NNUNetDataset static method) _DEFAULT_SECRETS_PATH (in module mipcandy.config) _DEFAULT_SETTINGS_PATH (in module mipcandy.config) _DIR (in module mipcandy.config) _evaluate_dataset() (mipcandy.evaluation.Evaluator method) _forward() (mipcandy.common.optim.loss.DiceBCELossWithLogits method) (mipcandy.common.optim.loss.DiceCELossWithLogits method) _get_shapes() (mipcandy.data.inspection.InspectionAnnotations method) _interp() (mipcandy.common.optim.lr_scheduler.AbsoluteLinearLR method) (mipcandy.common.optim.lr_scheduler.PolyLRScheduler method) _lazy_load_padding_module() (mipcandy.layer.WithPaddingModule method) _LineBreak (class in mipcandy.profiler) _lists_to_tuples() (in module mipcandy.data.inspection) _load() (in module mipcandy.config) _nd() (mipcandy.data.dataset.SupervisedDataset method) _predict() (mipcandy.inference.Predictor method) _save() (in module mipcandy.config) (mipcandy.profiler.Profiler method) _save_preview() (mipcandy.presets.segmentation.SegmentationTrainer method) _select() (mipcandy.evaluation.EvalResult method) _str_indices_to_int_indices() (in module mipcandy.data.inspection) _visualize3d_with_pyvista() (in module mipcandy.data.visualization) A AbsoluteLinearLR (class in mipcandy.common.optim.lr_scheduler) AbstractConvBlock (class in mipcandy.common.module.conv) aggregate_orthographic_views() (in module mipcandy.data.geometric) allocate_experiment_folder() (mipcandy.training.Trainer method) annotations() (mipcandy.data.inspection.InspectionAnnotations method) apply_non_linearity() (mipcandy.presets.segmentation.SegmentationTrainer method) assemble() (mipcandy.layer.LayerT method) auto_convert() (in module mipcandy.data.convertion) auto_device() (in module mipcandy.layer) B background() (mipcandy.data.inspection.InspectionAnnotations method) backward() (mipcandy.presets.segmentation.SegmentationTrainer method) (mipcandy.training.Trainer method) batch_int_divide() (in module mipcandy.layer) batch_int_multiply() (in module mipcandy.layer) bbox_from_indices() (in module mipcandy.data.inspection) best_score (mipcandy.training.TrainerTracker attribute) BinarizedDataset (class in mipcandy.data.dataset) binary_dice() (in module mipcandy.metrics) build_criterion() (mipcandy.presets.segmentation.SegmentationTrainer method) (mipcandy.training.Trainer method) build_ema() (mipcandy.presets.segmentation.SegmentationTrainer method) (mipcandy.training.Trainer method) build_network() (mipcandy.layer.WithNetwork method) build_network_from_checkpoint() (mipcandy.layer.WithNetwork method) build_optimizer() (mipcandy.presets.segmentation.SegmentationTrainer method) (mipcandy.training.Trainer method) build_padding_module() (mipcandy.layer.WithPaddingModule method) build_restoring_module() (mipcandy.layer.WithPaddingModule method) build_scheduler() (mipcandy.presets.segmentation.SegmentationTrainer method) (mipcandy.training.Trainer method) build_toolbox() (mipcandy.training.Trainer method) C center_of_foreground() (mipcandy.data.inspection.InspectionAnnotation method) center_of_foregrounds() (mipcandy.data.inspection.InspectionAnnotations method) center_of_foregrounds_offsets() (mipcandy.data.inspection.InspectionAnnotations method) class_bboxes (mipcandy.data.inspection.InspectionAnnotation attribute) class_counts (mipcandy.data.inspection.InspectionAnnotation attribute) class_ids (mipcandy.data.inspection.InspectionAnnotation attribute) class_locations (mipcandy.data.inspection.InspectionAnnotation attribute) class_percentages() (mipcandy.presets.segmentation.SegmentationTrainer method) ColorizeLabel (class in mipcandy.common.module.preprocess) compile_model() (mipcandy.layer.WithNetwork static method) ComposeDataset (class in mipcandy.data.dataset) config() (in module mipcandy.run) console() (mipcandy.training.Trainer method) construct_new() (mipcandy.data.dataset.BinarizedDataset method) (mipcandy.data.dataset.MergedDataset method) (mipcandy.data.dataset.NNUNetDataset method) (mipcandy.data.dataset.SupervisedDataset method) (mipcandy.data.inspection.RandomROIDataset method) (mipcandy.data.inspection.ROIDataset method) continue_training() (mipcandy.training.Trainer method) ConvBlock2d (in module mipcandy.common.module.conv) ConvBlock3d (in module mipcandy.common.module.conv) convert_ids_to_logits() (in module mipcandy.data.convertion) convert_idx() (mipcandy.data.inspection.RandomROIDataset method) convert_logits_to_ids() (in module mipcandy.data.convertion) copy() (mipcandy.layer.LayerT method) cpu (mipcandy.profiler.ProfilerFrame attribute) create_hybrid_frontend() (in module mipcandy.frontend.prototype) criterion (mipcandy.training.TrainerToolbox attribute) crop() (in module mipcandy.data.geometric) crop_and_pad() (in module mipcandy.data.inspection) crop_foreground() (mipcandy.data.inspection.InspectionAnnotations method) crop_roi() (mipcandy.data.inspection.InspectionAnnotations method) CTNormalize (class in mipcandy.common.module.preprocess) D D (in module mipcandy.data.dataset) dataloader() (mipcandy.training.Trainer method) dataset() (mipcandy.data.inspection.InspectionAnnotations method) DatasetFromMemory (class in mipcandy.data.dataset) deep_supervision (mipcandy.presets.segmentation.SegmentationTrainer attribute) deep_supervision_scales (mipcandy.presets.segmentation.SegmentationTrainer attribute) deep_supervision_weights (mipcandy.presets.segmentation.SegmentationTrainer attribute) DeepSupervisionWrapper (class in mipcandy.presets.segmentation) device() (mipcandy.layer.HasDevice method) dice_similarity_coefficient() (in module mipcandy.metrics) DiceBCELossWithLogits (class in mipcandy.common.optim.loss) DiceCELossWithLogits (class in mipcandy.common.optim.loss) do_load() (mipcandy.data.dataset.Loader static method) (mipcandy.data.dataset.TensorLoader static method) do_reduction() (in module mipcandy.metrics) download_dataset() (in module mipcandy.data.download) dump_allocated_tensors() (in module mipcandy.data.io) E ema (mipcandy.training.TrainerToolbox attribute) empty_cache() (in module mipcandy.data.io) (mipcandy.training.Trainer method) ensure_num_dimensions() (in module mipcandy.data.geometric) epoch (mipcandy.training.TrainerTracker attribute) etc() (mipcandy.training.Trainer method) EvalCase (class in mipcandy.evaluation) EvalResult (class in mipcandy.evaluation) evaluate() (mipcandy.evaluation.Evaluator method) evaluate_dataset() (mipcandy.evaluation.Evaluator method) Evaluator (class in mipcandy.evaluation) experiment_folder() (mipcandy.training.Trainer method) experiment_id() (mipcandy.training.Trainer method) export() (mipcandy.profiler._LineBreak method) (mipcandy.profiler.ProfilerFrame method) F fast_load() (in module mipcandy.data.io) fast_save() (in module mipcandy.data.io) filename (mipcandy.evaluation.EvalCase attribute) filter_train_params() (mipcandy.training.Trainer static method) FocalBCEWithLogits (class in mipcandy.common.optim.loss) fold() (mipcandy.data.dataset.BinarizedDataset method) (mipcandy.data.dataset.SupervisedDataset method) folder() (mipcandy.data.dataset.NNUNetDataset method) foreground_bbox (mipcandy.data.inspection.InspectionAnnotation attribute) foreground_heatmap() (mipcandy.data.inspection.InspectionAnnotations method) foreground_shape() (mipcandy.data.inspection.InspectionAnnotation method) foreground_shapes() (mipcandy.data.inspection.InspectionAnnotations method) format_bbox() (in module mipcandy.data.inspection) format_class_percentages() (mipcandy.presets.segmentation.SegmentationTrainer static method) forward() (mipcandy.common.module.conv.AbstractConvBlock method) (mipcandy.common.module.conv.WSConv2d method) (mipcandy.common.module.conv.WSConv3d method) (mipcandy.common.module.preprocess.ColorizeLabel method) (mipcandy.common.module.preprocess.CTNormalize method) (mipcandy.common.module.preprocess.Normalize method) (mipcandy.common.module.preprocess.Pad2d method) (mipcandy.common.module.preprocess.Pad3d method) (mipcandy.common.module.preprocess.PadTo method) (mipcandy.common.module.preprocess.Restore2d method) (mipcandy.common.module.preprocess.Restore3d method) (mipcandy.common.optim.loss.DiceBCELossWithLogits method) (mipcandy.common.optim.loss.DiceCELossWithLogits method) (mipcandy.common.optim.loss.FocalBCEWithLogits method) (mipcandy.data.transform.JointTransform method) (mipcandy.data.transform.MONAITransform method) (mipcandy.presets.segmentation.DeepSupervisionWrapper method) Frontend (class in mipcandy.frontend.prototype) frontend() (mipcandy.training.Trainer method) G get_cpu_usage() (mipcandy.profiler.Profiler static method) get_example_input() (mipcandy.training.Trainer method) get_gpu_mem_usage() (mipcandy.profiler.Profiler method) get_gpu_usage() (mipcandy.profiler.Profiler static method) get_lr() (mipcandy.common.optim.lr_scheduler.AbsoluteLinearLR method) (mipcandy.common.optim.lr_scheduler.PolyLRScheduler method) get_mem_usage() (mipcandy.profiler.Profiler method) get_padding_module() (mipcandy.layer.WithPaddingModule method) get_restoring_module() (mipcandy.layer.WithPaddingModule method) get_total_gpu_mem() (mipcandy.profiler.Profiler static method) get_total_mem() (mipcandy.profiler.Profiler static method) gpu (mipcandy.profiler.ProfilerFrame attribute) gpu_mem (mipcandy.profiler.ProfilerFrame attribute) H HasDevice (class in mipcandy.layer) I image (mipcandy.evaluation.EvalCase attribute) image() (mipcandy.data.dataset.SupervisedDataset method) include_background (mipcandy.presets.segmentation.SegmentationTrainer attribute) init_experiment() (mipcandy.training.Trainer method) initialized() (mipcandy.training.Trainer method) inspect() (in module mipcandy.data.inspection) InspectionAnnotation (class in mipcandy.data.inspection) InspectionAnnotations (class in mipcandy.data.inspection) intensity_stats() (mipcandy.data.inspection.InspectionAnnotations method) J JointTransform (class in mipcandy.data.transform) K KFPicker (class in mipcandy.data.dataset) L label (mipcandy.evaluation.EvalCase attribute) label() (mipcandy.data.dataset.SupervisedDataset method) layer_stats (mipcandy.sanity_check.SanityCheckResult attribute) LayerT (class in mipcandy.layer) lazy_load_model() (mipcandy.inference.Predictor method) line_break() (mipcandy.profiler.Profiler method) load() (mipcandy.data.dataset._AbstractDataset method) (mipcandy.data.dataset.ComposeDataset method) (mipcandy.data.dataset.DatasetFromMemory method) (mipcandy.data.dataset.SimpleDataset method) (mipcandy.data.dataset.SupervisedDataset method) (mipcandy.data.inspection.RandomROIDataset method) (mipcandy.data.inspection.ROIDataset method) load_checkpoint() (mipcandy.layer.WithCheckpoint method) (mipcandy.layer.WithNetwork method) load_image() (in module mipcandy.data.io) (mipcandy.data.dataset.BinarizedDataset method) (mipcandy.data.dataset.MergedDataset method) (mipcandy.data.dataset.NNUNetDataset method) (mipcandy.data.dataset.SupervisedDataset method) (mipcandy.data.inspection.ROIDataset method) load_inspection_annotations() (in module mipcandy.data.inspection) load_label() (mipcandy.data.dataset.BinarizedDataset method) (mipcandy.data.dataset.MergedDataset method) (mipcandy.data.dataset.NNUNetDataset method) (mipcandy.data.dataset.SupervisedDataset method) (mipcandy.data.inspection.ROIDataset method) load_metrics() (mipcandy.training.Trainer method) load_model() (mipcandy.layer.WithNetwork method) load_secrets() (in module mipcandy.config) load_settings() (in module mipcandy.config) load_state_orb() (mipcandy.training.Trainer method) load_toolbox() (mipcandy.training.Trainer method) load_tracker() (mipcandy.training.Trainer method) load_training_arguments() (mipcandy.training.Trainer method) Loader (class in mipcandy.data.dataset) log() (mipcandy.training.Trainer method) logitfy_no_grad() (mipcandy.common.optim.loss.SegmentationLoss method) Loss (class in mipcandy.common.optim.loss) M max() (mipcandy.evaluation.EvalResult method) max_n() (mipcandy.evaluation.EvalResult method) mem (mipcandy.profiler.ProfilerFrame attribute) MergedDataset (class in mipcandy.data.dataset) metrics (mipcandy.evaluation.EvalCase attribute) metrics() (mipcandy.training.Trainer method) min() (mipcandy.evaluation.EvalResult method) min_n() (mipcandy.evaluation.EvalResult method) mipcandy module mipcandy.__entry__ module mipcandy.__main__ module mipcandy.common module mipcandy.common.module module mipcandy.common.module.conv module mipcandy.common.module.preprocess module mipcandy.common.numpy module mipcandy.common.numpy.regressions module mipcandy.common.optim module mipcandy.common.optim.loss module mipcandy.common.optim.lr_scheduler module mipcandy.config module mipcandy.data module mipcandy.data.convertion module mipcandy.data.dataset module mipcandy.data.download module mipcandy.data.geometric module mipcandy.data.inspection module mipcandy.data.io module mipcandy.data.transform module mipcandy.data.visualization module mipcandy.evaluation module mipcandy.frontend module mipcandy.frontend.notion_fe module mipcandy.frontend.prototype module mipcandy.frontend.wandb_fe module mipcandy.inference module mipcandy.layer module mipcandy.metrics module mipcandy.presets module mipcandy.presets.segmentation module mipcandy.profiler module mipcandy.run module mipcandy.sanity_check module mipcandy.training module mipcandy.types module model (mipcandy.training.TrainerToolbox attribute) model_complexity_info() (in module mipcandy.sanity_check) module mipcandy mipcandy.__entry__ mipcandy.__main__ mipcandy.common mipcandy.common.module mipcandy.common.module.conv mipcandy.common.module.preprocess mipcandy.common.numpy mipcandy.common.numpy.regressions mipcandy.common.optim mipcandy.common.optim.loss mipcandy.common.optim.lr_scheduler mipcandy.config mipcandy.data mipcandy.data.convertion mipcandy.data.dataset mipcandy.data.download mipcandy.data.geometric mipcandy.data.inspection mipcandy.data.io mipcandy.data.transform mipcandy.data.visualization mipcandy.evaluation mipcandy.frontend mipcandy.frontend.notion_fe mipcandy.frontend.prototype mipcandy.frontend.wandb_fe mipcandy.inference mipcandy.layer mipcandy.metrics mipcandy.presets mipcandy.presets.segmentation mipcandy.profiler mipcandy.run mipcandy.sanity_check mipcandy.training mipcandy.types MONAITransform (class in mipcandy.data.transform) N new_experiment() (mipcandy.frontend.notion_fe.NotionFrontend method) NNUNetDataset (class in mipcandy.data.dataset) Normalize (class in mipcandy.common.module.preprocess) NotionFrontend (class in mipcandy.frontend.notion_fe) num_classes (mipcandy.presets.segmentation.SegmentationTrainer attribute) num_macs (mipcandy.sanity_check.SanityCheckResult attribute) num_params (mipcandy.sanity_check.SanityCheckResult attribute) num_trainable_params() (in module mipcandy.sanity_check) O on_experiment_completed() (mipcandy.frontend.notion_fe.NotionFrontend method) (mipcandy.frontend.prototype.Frontend method) on_experiment_created() (mipcandy.frontend.notion_fe.NotionFrontend method) (mipcandy.frontend.prototype.Frontend method) on_experiment_interrupted() (mipcandy.frontend.notion_fe.NotionFrontend method) (mipcandy.frontend.prototype.Frontend method) on_experiment_updated() (mipcandy.frontend.notion_fe.NotionFrontend method) (mipcandy.frontend.prototype.Frontend method) optimizer (mipcandy.training.TrainerToolbox attribute) OrderedKFPicker (class in mipcandy.data.dataset) orthographic_views() (in module mipcandy.data.geometric) output (mipcandy.evaluation.EvalCase attribute) (mipcandy.sanity_check.SanityCheckResult attribute) overlay() (in module mipcandy.data.visualization) oversample_foreground() (mipcandy.data.inspection.RandomROIDataset method) P Pad (class in mipcandy.common.module.preprocess) Pad2d (class in mipcandy.common.module.preprocess) Pad3d (class in mipcandy.common.module.preprocess) padded_shape() (mipcandy.common.module.preprocess.Pad2d method) (mipcandy.common.module.preprocess.Pad3d method) paddings() (mipcandy.common.module.preprocess.Pad2d method) (mipcandy.common.module.preprocess.Pad3d method) PadTo (class in mipcandy.common.module.preprocess) parse_inspection_annotation() (in module mipcandy.data.inspection) parse_predictant() (in module mipcandy.inference) PathBasedSupervisedDataset (class in mipcandy.data.dataset) PathBasedUnsupervisedDataset (class in mipcandy.data.dataset) paths() (mipcandy.data.dataset.PathBasedSupervisedDataset method) (mipcandy.data.dataset.PathBasedUnsupervisedDataset method) pick() (mipcandy.data.dataset.KFPicker static method) (mipcandy.data.dataset.OrderedKFPicker static method) (mipcandy.data.dataset.RandomKFPicker static method) PolyLRScheduler (class in mipcandy.common.optim.lr_scheduler) predict() (mipcandy.inference.Predictor method) predict_and_evaluate() (mipcandy.evaluation.Evaluator method) predict_image() (mipcandy.inference.Predictor method) predict_maximum_validation_score() (mipcandy.training.Trainer method) predict_to_files() (mipcandy.inference.Predictor method) Predictor (class in mipcandy.inference) preload() (mipcandy.data.dataset.SupervisedDataset method) prepare_deep_supervision_targets() (mipcandy.presets.segmentation.SegmentationTrainer static method) Profiler (class in mipcandy.profiler) ProfilerFrame (class in mipcandy.profiler) Q query_database() (mipcandy.frontend.notion_fe.NotionFrontend method) quotient_bounds() (in module mipcandy.common.numpy.regressions) quotient_derivative() (in module mipcandy.common.numpy.regressions) quotient_regression() (in module mipcandy.common.numpy.regressions) R random_roi() (mipcandy.data.inspection.RandomROIDataset method) RandomKFPicker (class in mipcandy.data.dataset) RandomROIDataset (class in mipcandy.data.inspection) record() (mipcandy.profiler.Profiler method) (mipcandy.training.Trainer method) record_all() (mipcandy.training.Trainer method) record_allocated_tensors() (mipcandy.profiler.Profiler method) record_profiler() (mipcandy.training.Trainer method) record_profiler_allocated_tensors() (mipcandy.training.Trainer method) record_profiler_linebreak() (mipcandy.training.Trainer method) recover_from() (mipcandy.training.Trainer method) recovery() (mipcandy.training.Trainer method) require_nonempty_secret() (mipcandy.frontend.prototype.Frontend method) resample_to_isotropic() (in module mipcandy.data.io) Restore2d (class in mipcandy.common.module.preprocess) Restore3d (class in mipcandy.common.module.preprocess) retrieve_database() (mipcandy.frontend.notion_fe.NotionFrontend method) reverse_paddings() (in module mipcandy.common.module.preprocess) roi() (mipcandy.data.inspection.InspectionAnnotations method) roi_shape() (mipcandy.data.inspection.InspectionAnnotations method) (mipcandy.data.inspection.RandomROIDataset method) ROIDataset (class in mipcandy.data.inspection) S sanity_check() (in module mipcandy.sanity_check) (mipcandy.training.Trainer method) SanityCheckResult (class in mipcandy.sanity_check) save() (mipcandy.data.dataset.NNUNetDataset method) (mipcandy.data.inspection.InspectionAnnotations method) save_checkpoint() (mipcandy.layer.WithCheckpoint method) (mipcandy.layer.WithNetwork method) save_everything_for_recovery() (mipcandy.training.Trainer method) save_image() (in module mipcandy.data.io) save_metric_curve() (mipcandy.training.Trainer method) save_metric_curve_combo() (mipcandy.training.Trainer method) save_metric_curves() (mipcandy.training.Trainer method) save_metrics() (mipcandy.training.Trainer method) save_model() (mipcandy.layer.WithNetwork method) save_paths() (mipcandy.data.dataset.PathBasedSupervisedDataset method) (mipcandy.data.dataset.PathBasedUnsupervisedDataset method) save_prediction() (mipcandy.inference.Predictor static method) save_predictions() (mipcandy.inference.Predictor method) save_preview() (mipcandy.presets.segmentation.SegmentationTrainer method) (mipcandy.training.Trainer method) save_progress() (mipcandy.training.Trainer method) save_secrets() (in module mipcandy.config) save_settings() (in module mipcandy.config) scheduler (mipcandy.training.TrainerToolbox attribute) SegmentationLoss (class in mipcandy.common.optim.loss) SegmentationTrainer (class in mipcandy.presets.segmentation) select_experiment() (mipcandy.frontend.notion_fe.NotionFrontend method) set_frontend() (mipcandy.training.Trainer method) set_roi_shape() (mipcandy.data.inspection.InspectionAnnotations method) set_seed() (mipcandy.training.Trainer method) set_transform() (mipcandy.data.dataset.SupervisedDataset method) (mipcandy.data.dataset.UnsupervisedDataset method) shape (mipcandy.data.inspection.InspectionAnnotation attribute) shapes() (mipcandy.data.inspection.InspectionAnnotations method) show_metrics() (mipcandy.training.Trainer method) show_metrics_per_case() (mipcandy.training.Trainer method) SimpleDataset (class in mipcandy.data.dataset) soft_dice() (in module mipcandy.metrics) spacing (mipcandy.data.inspection.InspectionAnnotation attribute) stack (mipcandy.profiler.ProfilerFrame attribute) statistical_foreground_shape() (mipcandy.data.inspection.InspectionAnnotations method) statistical_shape() (mipcandy.data.inspection.InspectionAnnotations method) SupervisedDataset (class in mipcandy.data.dataset) T T (in module mipcandy.data.dataset) TensorLoader (class in mipcandy.data.dataset) tracker() (mipcandy.training.Trainer method) train() (mipcandy.training.Trainer method) train_batch() (mipcandy.training.Trainer method) train_epoch() (mipcandy.training.Trainer method) train_with_settings() (mipcandy.training.Trainer method) Trainer (class in mipcandy.training) trainer_folder() (mipcandy.training.Trainer method) trainer_variant() (mipcandy.training.Trainer method) TrainerToolbox (class in mipcandy.training) TrainerTracker (class in mipcandy.training) transform() (mipcandy.data.dataset.SupervisedDataset method) (mipcandy.data.dataset.UnsupervisedDataset method) try_append() (in module mipcandy.training) try_append_all() (in module mipcandy.training) U UnsupervisedDataset (class in mipcandy.data.dataset) update() (mipcandy.layer.LayerT method) update_experiment() (mipcandy.frontend.notion_fe.NotionFrontend method) V validate() (mipcandy.training.Trainer method) validate_case() (mipcandy.presets.segmentation.SegmentationTrainer method) (mipcandy.training.Trainer method) validation_dataloader() (mipcandy.training.Trainer method) validation_mode (mipcandy.common.optim.loss.Loss property) visualize2d() (in module mipcandy.data.visualization) visualize3d() (in module mipcandy.data.visualization) W WithCheckpoint (class in mipcandy.layer) WithNetwork (class in mipcandy.layer) WithPaddingModule (class in mipcandy.layer) worst_case (mipcandy.training.TrainerTracker attribute) WSConv2d (class in mipcandy.common.module.conv) WSConv3d (class in mipcandy.common.module.conv)
