(self)

(self, requires_update_modules)

(self, name)

(self)

(self, name)

(self, message, level='INFO', endwithnewline=True)

(self, message, endwithnewline=True)

(self, seg_logits, seg_targets, losses_cfgs)

(self)

(model, model_cfg)

(self, value, center=1, bound=(0, float('inf')), clip_first_on_zero=True)

(self, seg_losses_log_dict, losses_log_dict, init_losses_log_dict)

(self, block, inplanes, planes, num_blocks, stride=1, dilation=1, contract_dilation=True, use_avg_for_downsamp

(key, data_meta, padding, fill, padding_mode, **kwargs)

(self, grad_scaler=None)

(self, inputs, selected_indices)

(self)

(probabilities, eps=1e-8)

(history_distillation_feats, distillation_feats, reduction='mean', alpha=1., scale_factor=100)

(ckptspath, map_to_cpu=True)

(dirname)

(self, seg_targets, seg_preds)

(dataset, dataloader_cfg)

(self, structure_type, in_channels=3, base_channels=64, stem_channels=64, depth=101, outstride=16, contract_di

(self, structure_type, in_channels=3, base_channels=64, stem_channels=64, depth=101, outstride=16, contract_di

(self, structure_type, in_channels=3, base_channels=64, stem_channels=64, depth=101, outstride=16, contract_di

(self, structure_type, in_channels=3, base_channels=64, stem_channels=64, depth=101, outstride=16, contract_di

(key, data_meta, output_size, **kwargs)

(transform_settings)

(key, data_meta, top, left, height, width, **kwargs)

(self)

(self, history_distillation_feats, distillation_feats, num_known_classes_list=None, dataset_type='VOCDataset',

(task_name, tasks, task_id)

(key, data_meta, **kwargs)

(module, norm_list=None)

(key, data_meta, lambd, **kwargs)

(x, spp_scales=[1, 2, 4])

(fpath)

(key, data_meta, angle, resample, expand, center, **kwargs)

(key, data_meta, output_size, interpolation, **kwargs)

(key, data_meta, top, left, height, width, size, interpolation, **kwargs)

(labels)

(src_path, dst_path)

(self, device=None)

(self, cur_epoch)

(self, cur_epoch)

(key, data_meta, **kwargs)

(self, mode, task_name, task_id, dataset_cfg)

(self, mode, task_name, task_id, dataset_cfg)

(self, reduction='mean', ignore_index=255, scale_factor=1.0, weight=None, label_smoothing=None)

(self)

(self)

(self, x)

(self, mode, dataset_cfg)

(self, seg_logits, seg_targets, losses_cfg)

(self, params, max_norm=35, norm_type=2)

(self)

(seg,features,classes)

(anchor_features, contrast_features, anchor_labels, contrast_labels, P=None, temperature=0.07, scale_factor=1.

(self, state_dict)

(self)

(logits_source, logits_target, seg_targets_mergepseudolabels, prototypes, temperature=3, delta=0.0, history_pr

(self, seg_target, seg_pred)

(history_distillation_feats, distillation_feats, pod_factor=0.01, pod_factor_last_scale=0.0005, spp_scales=[1,

(history_distillation_feats, distillation_feats, reduction='mean', alpha=1., scale_factor=10)

(history_distillation_feats, distillation_feats, num_known_classes_list=None, dataset_type='VOCDataset')

(history_distillation_feats, distillation_feats, num_known_classes_list=None, dataset_type='VOCDataset', spp_s

(dataset, labels, history_labels=None, overlap=True)

(self)

()

(self)

(self)

(self)

(task_name, tasks, task_id)

(self, cur_iter, warmup_cfg, regular_lr)

(self, x)

(self, x)

(self, model, paramwise_cfg, filter_params, optimizer_cfg, params, prefix='')

(self, device=None)

(self, nonlinearity, param=None)

(self)

(self)

(filepath)

(structure_type, pretrained_model_path='', pretrained_weights_table={}, map_to_cpu=True, possible_model_keys=[

(self, cfg_file_path)

()

()

(line)

(fname='requirements.txt', with_version=True)

(self, dataset_cfg, transforms, data_generator)

(decoder_outputs, seg_targets, history_seg_logits, history_decoder_outputs, num_known_classes=None)

(self, name, module)

(self, name, module)

(self)

(self, work_dir='')

(data, savepath)

(ckpts, savepath)

(self, state_dict)

(self)

(self)