SYMBOL INDEX (259 symbols across 19 files) FILE: nn/data/datasets.py class BaseDataset (line 20) | class BaseDataset(Dataset): method __init__ (line 26) | def __init__(self, root_dir, start_config={'data_folders': []}, gt_cac... method save_to_wandb (line 84) | def save_to_wandb(self, experiment): method update_transform (line 90) | def update_transform(self, transform): method __len__ (line 95) | def __len__(self): method __getitem__ (line 99) | def __getitem__(self, idx): method update_config (line 120) | def update_config(self, in_config): method _drop_cache (line 134) | def _drop_cache(self): method _renew_cache (line 139) | def _renew_cache(self): method indices_by_data_folder (line 148) | def indices_by_data_folder(self, index_list): method subsets_per_datafolder (line 167) | def subsets_per_datafolder(self, index_list=None): method random_split_by_dataset (line 180) | def random_split_by_dataset(self, valid_per_type, test_per_type=0, spl... method split_from_dict (line 246) | def split_from_dict(self, split_dict, with_breakdown=False): method save_prediction_batch (line 286) | def save_prediction_batch(self, *args, **kwargs): method standardize (line 290) | def standardize(self, training=None): method _clean_datapoint_list (line 301) | def _clean_datapoint_list(self, datapoints_names, dataset_folder): method _get_sample_info (line 306) | def _get_sample_info(self, datapoint_name): method _estimate_data_shape (line 328) | def _estimate_data_shape(self): method _update_on_config_change (line 336) | def _update_on_config_change(self): class GarmentBaseDataset (line 341) | class GarmentBaseDataset(BaseDataset): method __init__ (line 344) | def __init__(self, root_dir, start_config={'data_folders': []}, gt_cac... method save_to_wandb (line 407) | def save_to_wandb(self, experiment): method _clean_datapoint_list (line 433) | def _clean_datapoint_list(self, datapoints_names, dataset_folder): method filter_by_params (line 474) | def filter_by_params(self, filter_file, dataset_folder, datapoint_names): method template_name (line 502) | def template_name(self, datapoint_name): method _read_pattern (line 506) | def _read_pattern(self, datapoint_name, folder_elements, method _unpad (line 524) | def _unpad(self, element, tolerance=1.e-5): method _get_distribution_stats (line 534) | def _get_distribution_stats(self, input_batch, padded=False): method _get_norm_stats (line 549) | def _get_norm_stats(self, input_batch, padded=False): class Garment3DPatternFullDataset (line 571) | class Garment3DPatternFullDataset(GarmentBaseDataset): method __init__ (line 576) | def __init__(self, root_dir, start_config={'data_folders': []}, gt_cac... method standardize (line 596) | def standardize(self, training=None): method save_prediction_batch (line 657) | def save_prediction_batch( method _pred_to_pattern (line 731) | def _pred_to_pattern(self, prediction, dataname): method _get_sample_info (line 770) | def _get_sample_info(self, datapoint_name): method _get_pattern_ground_truth (line 803) | def _get_pattern_ground_truth(self, datapoint_name, folder_elements): method _sample_points (line 822) | def _sample_points(self, datapoint_name, folder_elements): method sample_mesh_points (line 846) | def sample_mesh_points(num_points, verts, faces): method _point_classes_from_mesh (line 863) | def _point_classes_from_mesh(self, points, verts, datapoint_name, fold... method _empty_panels_mask (line 907) | def _empty_panels_mask(self, num_edges): method tags_to_stitches (line 917) | def tags_to_stitches(stitch_tags, free_edges_score): method free_edges_mask (line 971) | def free_edges_mask(pattern, stitches, num_stitches): class GarmentStitchPairsDataset (line 985) | class GarmentStitchPairsDataset(GarmentBaseDataset): method __init__ (line 989) | def __init__( method standardize (line 1018) | def standardize(self, training=None): method save_prediction_batch (line 1051) | def save_prediction_batch( method _get_sample_info (line 1097) | def _get_sample_info(self, datapoint_name): method _clean_datapoint_list (line 1134) | def _clean_datapoint_list(self, datapoints_names, dataset_folder): FILE: nn/data/panel_classes.py class PanelClasses (line 8) | class PanelClasses(): method __init__ (line 10) | def __init__(self, classes_file): method __len__ (line 26) | def __len__(self): method class_idx (line 29) | def class_idx(self, template, panel): method class_name (line 36) | def class_name(self, idx): method map (line 39) | def map(self, template_name, panel_list): FILE: nn/data/pattern_converter.py class EmptyPanelError (line 19) | class EmptyPanelError(Exception): class InvalidPatternDefError (line 22) | class InvalidPatternDefError(Exception): method __init__ (line 27) | def __init__(self, pattern_name='', message=''): class NNSewingPattern (line 35) | class NNSewingPattern(VisPattern): method __init__ (line 39) | def __init__(self, pattern_file=None, view_ids=False, panel_classifier... method pattern_as_tensors (line 48) | def pattern_as_tensors( method pattern_from_tensors (line 118) | def pattern_from_tensors( method panel_as_numeric (line 189) | def panel_as_numeric(self, panel_name, pad_to_len=None): method panel_from_numeric (line 228) | def panel_from_numeric(self, panel_name, edge_sequence, rotation=None,... method stitches_as_tags (line 290) | def stitches_as_tags(self, panel_order=None, pad_to_len=None): method stitches_as_3D_pairs (line 321) | def stitches_as_3D_pairs(self, stitch_pairs_num=None, non_stitch_pairs... method stitches_from_pair_classifier (line 411) | def stitches_from_pair_classifier(self, model, data_stats): method all_edge_pairs (line 458) | def all_edge_pairs(self, device='cpu'): method _stitches_as_set (line 501) | def _stitches_as_set(self): method _edge_dict (line 510) | def _edge_dict(self, vstart, vend, curvature): method _3D_edges_per_panel (line 517) | def _3D_edges_per_panel(self, randomize_direction=False): method _stitch_entry (line 554) | def _stitch_entry(self, panel_1, edge_1, panel_2, edge_2, score=None): method _empty_panel (line 569) | def _empty_panel(self, max_edge_num): method panel_order (line 575) | def panel_order(self, force_update=False, pad_to_len=None): FILE: nn/data/transforms.py function _dict_to_tensors (line 6) | def _dict_to_tensors(dict_obj): # helper class SampleToTensor (line 28) | class SampleToTensor(object): method __call__ (line 31) | def __call__(self, sample): class FeatureStandartization (line 35) | class FeatureStandartization(): method __init__ (line 37) | def __init__(self, shift, scale): method __call__ (line 41) | def __call__(self, sample): class GTtandartization (line 52) | class GTtandartization(): method __init__ (line 57) | def __init__(self, shift, scale): method __call__ (line 63) | def __call__(self, sample): FILE: nn/data/utils.py class BalancedBatchSampler (line 16) | class BalancedBatchSampler(): method __init__ (line 19) | def __init__(self, ids_by_type, batch_size=10, drop_last=True): method __iter__ (line 54) | def __iter__(self): method __len__ (line 91) | def __len__(self): function sample_points_from_meshes (line 96) | def sample_points_from_meshes(mesh_paths, data_config): function save_garments_prediction (line 110) | def save_garments_prediction(predictions, save_to, data_config=None, dat... FILE: nn/data/wrapper.py class DatasetWrapper (line 16) | class DatasetWrapper(object): method __init__ (line 20) | def __init__(self, in_dataset, known_split=None, batch_size=None, shuf... method get_loader (line 55) | def get_loader(self, data_section='full'): method new_loaders (line 63) | def new_loaders(self, batch_size=None, shuffle_train=True): method _loaders_dict (line 105) | def _loaders_dict(self, subsets_dict, batch_size, shuffle=False): method new_split (line 113) | def new_split(self, valid, test=None, random_seed=None): method load_split (line 122) | def load_split(self, split_info=None, batch_size=None): method print_subset_stats (line 175) | def print_subset_stats(self, subset_breakdown_dict, total_len, subset_... method save_to_wandb (line 190) | def save_to_wandb(self, experiment): method standardize_data (line 206) | def standardize_data(self): method predict (line 211) | def predict(self, model, save_to, dir_tag='pred', sections=['test'], s... FILE: nn/evaluation_scripts/noise_levels.py function get_values_from_args (line 22) | def get_values_from_args(): FILE: nn/evaluation_scripts/on_test_set.py function get_values_from_args (line 23) | def get_values_from_args(): FILE: nn/evaluation_scripts/predict_per_example.py function get_values_from_args (line 32) | def get_values_from_args(): function sample_points_obj (line 85) | def sample_points_obj(filename, num_points): function load_points (line 103) | def load_points(filename): FILE: nn/experiment.py class ExperimentWrappper (line 17) | class ExperimentWrappper(object): method __init__ (line 26) | def __init__(self, config, wandb_username='', no_sync=False): method init_run (line 47) | def init_run(self, config={}): method stop (line 68) | def stop(self): method full_name (line 75) | def full_name(self): method last_epoch (line 85) | def last_epoch(self): method data_info (line 92) | def data_info(self): method last_best_validation_loss (line 126) | def last_best_validation_loss(self): method NN_config (line 133) | def NN_config(self): method add_statistic (line 138) | def add_statistic(self, tag, info, log=''): method add_config (line 163) | def add_config(self, tag, info): method add_artifact (line 170) | def add_artifact(self, path, name, type): method is_finished (line 195) | def is_finished(self): method load_dataset (line 203) | def load_dataset(self, data_root, eval_config={}, unseen=False, batch_... method load_model (line 227) | def load_model(self, data_config=None): method prediction (line 243) | def prediction(self, save_to, model, datawrapper, dir_tag='pred', nick... method checkpoint_filename (line 258) | def checkpoint_filename(self, check_id=None): method artifactname (line 263) | def artifactname(self, tag, with_version=True, version=None, custom_al... method final_filename (line 273) | def final_filename(self): method cloud_path (line 277) | def cloud_path(self): method local_wandb_path (line 285) | def local_wandb_path(self): method local_artifact_path (line 290) | def local_artifact_path(self): method get_checkpoint_file (line 298) | def get_checkpoint_file(self, to_path=None, version=None, device=None): method get_best_model (line 311) | def get_best_model(self, to_path=None, device=None): method save_checkpoint (line 337) | def save_checkpoint(self, state, aliases=[], wait_for_upload=False): method get_file (line 362) | def get_file(self, filename, to_path='.'): method _load_artifact (line 369) | def _load_artifact(self, artifact_name, to_path=None): method _run_object (line 380) | def _run_object(self): method _run_config (line 385) | def _run_config(self): method _wait_for_upload (line 393) | def _wait_for_upload(self, artifact_name, max_attempts=10): method _load_model_from_file (line 410) | def _load_model_from_file(self, file, device=None): FILE: nn/metrics/composed_loss.py class ComposedLoss (line 11) | class ComposedLoss(): method __init__ (line 14) | def __init__(self, data_config, in_config={}): method __call__ (line 39) | def __call__(self, preds, ground_truth, names=None, epoch=1000): method eval (line 69) | def eval(self): method train (line 73) | def train(self, mode=True): method _main_losses (line 76) | def _main_losses(self, preds, ground_truth, gt_num_edges, epoch): method _main_quality_metrics (line 92) | def _main_quality_metrics(self, preds, ground_truth, gt_num_edges, nam... method _prec_recall (line 112) | def _prec_recall(self, preds, ground_truth, target_label): class ComposedPatternLoss (line 129) | class ComposedPatternLoss(): method __init__ (line 134) | def __init__(self, data_config, in_config={}): method __call__ (line 222) | def __call__(self, preds, ground_truth, names=None, epoch=1000): method eval (line 286) | def eval(self): method train (line 290) | def train(self, mode=True): method _main_losses (line 294) | def _main_losses(self, preds, ground_truth, gt_num_edges): method _stitch_losses (line 336) | def _stitch_losses(self, preds, ground_truth, gt_num_edges): method _main_quality_metrics (line 365) | def _main_quality_metrics(self, preds, ground_truth, gt_num_edges, nam... method _stitch_quality_metrics (line 400) | def _stitch_quality_metrics(self, preds, ground_truth, gt_num_edges, n... method _gt_order_match (line 429) | def _gt_order_match(self, preds, ground_truth): method _panel_order_match (line 530) | def _panel_order_match(self, pred_features, gt_features): method _feature_permute (line 573) | def _feature_permute(pattern_features, permutation): method _stitch_after_permute (line 592) | def _stitch_after_permute(stitches, stitches_num, permutation, max_pan... method _rotate_gt (line 621) | def _rotate_gt(self, preds, ground_truth, gt_num_edges, epoch): method _batch_edge_order_match (line 656) | def _batch_edge_order_match(predicted_panels, gt_panels, gt_num_edges): method _panel_egde_match (line 687) | def _panel_egde_match(pred_panel, gt_panel, num_edges): method _per_panel_shift (line 706) | def _per_panel_shift(panel_features, per_panel_leading_edges, panel_nu... method _gt_stitches_shift (line 727) | def _gt_stitches_shift( method _rotate_edges (line 758) | def _rotate_edges(panel, num_edges): FILE: nn/metrics/eval_utils.py function eval_metrics (line 12) | def eval_metrics(model, data_wrapper, section='test'): function _eval_metrics_per_loader (line 35) | def _eval_metrics_per_loader(model, loss, loader, device): function eval_pad_vector (line 80) | def eval_pad_vector(data_stats={}): FILE: nn/metrics/losses.py class PanelLoopLoss (line 8) | class PanelLoopLoss(): method __init__ (line 11) | def __init__(self, max_edges_in_panel, data_stats={}): method __call__ (line 19) | def __call__(self, predicted_panels, gt_panel_num_edges=None): class PatternStitchLoss (line 54) | class PatternStitchLoss(): method __init__ (line 60) | def __init__(self, triplet_margin=0.1, use_hardnet=True): method __call__ (line 65) | def __call__(self, stitch_tags, gt_stitches, gt_stitches_nums): method extended_triplet_neg_loss (line 114) | def extended_triplet_neg_loss(self, total_tags, gt_stitches_nums): method HardNet_neg_loss (line 150) | def HardNet_neg_loss(self, total_tags, gt_stitches_nums): FILE: nn/metrics/metrics.py class PatternStitchPrecisionRecall (line 13) | class PatternStitchPrecisionRecall(): method __init__ (line 18) | def __init__(self, data_stats=None): method __call__ (line 24) | def __call__( method on_loader (line 81) | def on_loader(self, data_loader, model): class NumbersInPanelsAccuracies (line 95) | class NumbersInPanelsAccuracies(): method __init__ (line 99) | def __init__(self, max_edges_in_panel, data_stats=None): method __call__ (line 110) | def __call__(self, predicted_outlines, gt_num_edges, gt_panel_nums, pa... class PanelVertsL2 (line 185) | class PanelVertsL2(): method __init__ (line 191) | def __init__(self, max_edges_in_panel, data_stats={}): method __call__ (line 203) | def __call__(self, predicted_outlines, gt_outlines, gt_num_edges, corr... method _to_verts (line 259) | def _to_verts(self, panel_edges): class UniversalL2 (line 284) | class UniversalL2(): method __init__ (line 288) | def __init__(self, data_stats={}): method __call__ (line 296) | def __call__(self, predicted, gt, correct_mask=None): FILE: nn/net_blocks.py class _SetAbstractionModule (line 10) | class _SetAbstractionModule(nn.Module): method __init__ (line 12) | def __init__(self, ratio, conv_radius, per_point_nn): method forward (line 18) | def forward(self, features, pos, batch): class _GlobalSetAbstractionModule (line 28) | class _GlobalSetAbstractionModule(nn.Module): method __init__ (line 30) | def __init__(self, per_point_net): method forward (line 34) | def forward(self, features, pos, batch): function MLP (line 43) | def MLP(channels, batch_norm=True): class PointNetPlusPlus (line 50) | class PointNetPlusPlus(nn.Module): method __init__ (line 56) | def __init__(self, out_size, config={}): method forward (line 71) | def forward(self, positions): class EdgeConvFeatures (line 93) | class EdgeConvFeatures(nn.Module): method __init__ (line 95) | def __init__(self, out_size, config={}): method forward (line 160) | def forward(self, positions, global_pool=True): class DynamicASAPool (line 194) | class DynamicASAPool(nn.Module): method __init__ (line 201) | def __init__(self, feature_size, k=10, pool_ratio=0.5): method forward (line 207) | def forward(self, node_features, batch): class EdgeConvPoolingFeatures (line 221) | class EdgeConvPoolingFeatures(nn.Module): method __init__ (line 224) | def __init__(self, out_size, config={}): method forward (line 246) | def forward(self, positions): class MLPDecoder (line 273) | class MLPDecoder(nn.Module): method __init__ (line 277) | def __init__( method forward (line 289) | def forward(self, batch_enc, *args): function _init_tenzor (line 302) | def _init_tenzor(*shape, device='cpu', init_type=''): function _init_weights (line 318) | def _init_weights(module, init_type=''): class LSTMEncoderModule (line 336) | class LSTMEncoderModule(nn.Module): method __init__ (line 338) | def __init__(self, elem_len, encoding_size, n_layers, dropout=0, custo... method forward (line 350) | def forward(self, batch_sequence): class LSTMDecoderModule (line 363) | class LSTMDecoderModule(nn.Module): method __init__ (line 365) | def __init__(self, encoding_size, hidden_size, out_elem_size, n_layers... method forward (line 382) | def forward(self, batch_enc, out_len): class LSTMDoubleReverseDecoderModule (line 405) | class LSTMDoubleReverseDecoderModule(nn.Module): method __init__ (line 408) | def __init__(self, encoding_size, hidden_size, out_elem_size, n_layers... method forward (line 429) | def forward(self, batch_enc, out_len): class GRUDecoderModule (line 457) | class GRUDecoderModule(nn.Module): method __init__ (line 459) | def __init__(self, encoding_size, hidden_size, out_elem_size, n_layers... method forward (line 477) | def forward(self, batch_enc, out_len): FILE: nn/nets.py class BaseModule (line 11) | class BaseModule(nn.Module): method __init__ (line 13) | def __init__(self): method loss (line 21) | def loss(self, preds, ground_truth, **kwargs): method train (line 29) | def train(self, mode=True): method eval (line 34) | def eval(self): class GarmentFullPattern3D (line 41) | class GarmentFullPattern3D(BaseModule): method __init__ (line 49) | def __init__(self, data_config, config={}, in_loss_config={}): method forward_encode (line 132) | def forward_encode(self, positions_batch): method forward_pattern_decode (line 138) | def forward_pattern_decode(self, garment_encodings): method forward_panel_decode (line 148) | def forward_panel_decode(self, flat_panel_encodings, batch_size): method forward_decode (line 171) | def forward_decode(self, garment_encodings): method forward (line 179) | def forward(self, positions_batch, **kwargs): class GarmentSegmentPattern3D (line 187) | class GarmentSegmentPattern3D(GarmentFullPattern3D): method __init__ (line 192) | def __init__(self, data_config, config={}, in_loss_config={}): method forward_panel_enc_from_3d (line 238) | def forward_panel_enc_from_3d(self, positions_batch): method forward (line 285) | def forward(self, positions_batch, **kwargs): class StitchOnEdge3DPairs (line 303) | class StitchOnEdge3DPairs(BaseModule): method __init__ (line 311) | def __init__(self, data_config, config={}, in_loss_config={}): method forward (line 343) | def forward(self, pairs_batch, **kwargs): FILE: nn/train.py function get_values_from_args (line 20) | def get_values_from_args(): function get_old_data_config (line 34) | def get_old_data_config(in_config): function merge_repos (line 65) | def merge_repos(root, repos): FILE: nn/trainer.py class Trainer (line 13) | class Trainer(): method __init__ (line 14) | def __init__( method init_randomizer (line 31) | def init_randomizer(self, random_seed=None): method use_dataset (line 46) | def use_dataset(self, dataset, split_info): method fit (line 57) | def fit(self, model): method _fit_loop (line 83) | def _fit_loop(self, model, train_loader, valid_loader, start_epoch=0): method _start_experiment (line 140) | def _start_experiment(self, model): method _add_optimizer (line 162) | def _add_optimizer(self, model): method _add_scheduler (line 174) | def _add_scheduler(self, steps_per_epoch): method _restore_run (line 187) | def _restore_run(self, model): method _early_stopping (line 215) | def _early_stopping(self, last_loss, last_tracking_loss, last_lr): method _log_an_image (line 243) | def _log_an_image(self, model, loader, epoch, log_step): method _save_checkpoint (line 275) | def _save_checkpoint(self, model, epoch, best=False): FILE: nn/utility_scripts/param_filter_test.py function isAllowed (line 10) | def isAllowed(pattern, param_filter):