SYMBOL INDEX (815 symbols across 112 files) FILE: unetr_pp/evaluation/add_mean_dice_to_json.py function foreground_mean (line 21) | def foreground_mean(filename): function run_in_folder (line 42) | def run_in_folder(folder): FILE: unetr_pp/evaluation/collect_results_files.py function crawl_and_copy (line 20) | def crawl_and_copy(current_folder, out_folder, prefix="fabian_", suffix=... FILE: unetr_pp/evaluation/evaluator.py class Evaluator (line 30) | class Evaluator: method __init__ (line 60) | def __init__(self, method set_test (line 99) | def set_test(self, test): method set_reference (line 104) | def set_reference(self, reference): method set_labels (line 109) | def set_labels(self, labels): method construct_labels (line 125) | def construct_labels(self): method set_metrics (line 137) | def set_metrics(self, metrics): method add_metric (line 147) | def add_metric(self, metric): method evaluate (line 152) | def evaluate(self, test=None, reference=None, advanced=False, **metric... method to_dict (line 227) | def to_dict(self): method to_array (line 233) | def to_array(self): method to_pandas (line 254) | def to_pandas(self): class NiftiEvaluator (line 269) | class NiftiEvaluator(Evaluator): method __init__ (line 271) | def __init__(self, *args, **kwargs): method set_test (line 277) | def set_test(self, test): method set_reference (line 287) | def set_reference(self, reference): method evaluate (line 297) | def evaluate(self, test=None, reference=None, voxel_spacing=None, **me... function run_evaluation (line 306) | def run_evaluation(args): function aggregate_scores (line 321) | def aggregate_scores(test_ref_pairs, function aggregate_scores_for_experiment (line 403) | def aggregate_scores_for_experiment(score_file, function evaluate_folder (line 446) | def evaluate_folder(folder_with_gts: str, folder_with_predictions: str, ... function nnformer_evaluate_folder (line 464) | def nnformer_evaluate_folder(): FILE: unetr_pp/evaluation/metrics.py function assert_shape (line 19) | def assert_shape(test, reference): class ConfusionMatrix (line 25) | class ConfusionMatrix: method __init__ (line 27) | def __init__(self, test=None, reference=None): method set_test (line 41) | def set_test(self, test): method set_reference (line 46) | def set_reference(self, reference): method reset (line 51) | def reset(self): method compute (line 63) | def compute(self): method get_matrix (line 80) | def get_matrix(self): method get_size (line 89) | def get_size(self): method get_existence (line 95) | def get_existence(self): function dice (line 105) | def dice(test=None, reference=None, confusion_matrix=None, nan_for_nonex... function jaccard (line 123) | def jaccard(test=None, reference=None, confusion_matrix=None, nan_for_no... function precision (line 141) | def precision(test=None, reference=None, confusion_matrix=None, nan_for_... function sensitivity (line 159) | def sensitivity(test=None, reference=None, confusion_matrix=None, nan_fo... function recall (line 177) | def recall(test=None, reference=None, confusion_matrix=None, nan_for_non... function specificity (line 183) | def specificity(test=None, reference=None, confusion_matrix=None, nan_fo... function accuracy (line 201) | def accuracy(test=None, reference=None, confusion_matrix=None, **kwargs): function fscore (line 212) | def fscore(test=None, reference=None, confusion_matrix=None, nan_for_non... function false_positive_rate (line 222) | def false_positive_rate(test=None, reference=None, confusion_matrix=None... function false_omission_rate (line 228) | def false_omission_rate(test=None, reference=None, confusion_matrix=None... function false_negative_rate (line 246) | def false_negative_rate(test=None, reference=None, confusion_matrix=None... function true_negative_rate (line 252) | def true_negative_rate(test=None, reference=None, confusion_matrix=None,... function false_discovery_rate (line 258) | def false_discovery_rate(test=None, reference=None, confusion_matrix=Non... function negative_predictive_value (line 264) | def negative_predictive_value(test=None, reference=None, confusion_matri... function total_positives_test (line 270) | def total_positives_test(test=None, reference=None, confusion_matrix=Non... function total_negatives_test (line 281) | def total_negatives_test(test=None, reference=None, confusion_matrix=Non... function total_positives_reference (line 292) | def total_positives_reference(test=None, reference=None, confusion_matri... function total_negatives_reference (line 303) | def total_negatives_reference(test=None, reference=None, confusion_matri... function hausdorff_distance (line 314) | def hausdorff_distance(test=None, reference=None, confusion_matrix=None,... function hausdorff_distance_95 (line 332) | def hausdorff_distance_95(test=None, reference=None, confusion_matrix=No... function avg_surface_distance (line 350) | def avg_surface_distance(test=None, reference=None, confusion_matrix=Non... function avg_surface_distance_symmetric (line 368) | def avg_surface_distance_symmetric(test=None, reference=None, confusion_... FILE: unetr_pp/evaluation/model_selection/ensemble.py function merge (line 26) | def merge(args): function ensemble (line 39) | def ensemble(training_output_folder1, training_output_folder2, output_fo... FILE: unetr_pp/evaluation/model_selection/figure_out_what_to_submit.py function find_task_name (line 29) | def find_task_name(folder, task_id): function get_mean_foreground_dice (line 36) | def get_mean_foreground_dice(json_file): function get_foreground_mean (line 41) | def get_foreground_mean(results): function main (line 47) | def main(): FILE: unetr_pp/evaluation/model_selection/summarize_results_in_one_json.py function summarize (line 22) | def summarize(tasks, models=('2d', '3d_lowres', '3d_fullres', '3d_cascad... function summarize2 (line 101) | def summarize2(task_ids, models=('2d', '3d_lowres', '3d_fullres', '3d_ca... function foreground_mean2 (line 203) | def foreground_mean2(filename): FILE: unetr_pp/evaluation/model_selection/summarize_results_with_plans.py function list_to_string (line 23) | def list_to_string(l, delim=","): function write_plans_to_file (line 30) | def write_plans_to_file(f, plans_file, stage=0, do_linebreak_at_end=True... FILE: unetr_pp/evaluation/region_based_evaluation.py function get_brats_regions (line 12) | def get_brats_regions(): function get_KiTS_regions (line 26) | def get_KiTS_regions(): function create_region_from_mask (line 34) | def create_region_from_mask(mask, join_labels: tuple): function evaluate_case (line 41) | def evaluate_case(file_pred: str, file_gt: str, regions): function evaluate_regions (line 53) | def evaluate_regions(folder_predicted: str, folder_gt: str, regions: dic... FILE: unetr_pp/evaluation/surface_dice.py function normalized_surface_dice (line 20) | def normalized_surface_dice(a: np.ndarray, b: np.ndarray, threshold: flo... FILE: unetr_pp/experiment_planning/DatasetAnalyzer.py class DatasetAnalyzer (line 27) | class DatasetAnalyzer(object): method __init__ (line 28) | def __init__(self, folder_with_cropped_data, overwrite=True, num_proce... method load_properties_of_cropped (line 45) | def load_properties_of_cropped(self, case_identifier): method _check_if_all_in_one_region (line 51) | def _check_if_all_in_one_region(seg, regions): method _collect_class_and_region_sizes (line 65) | def _collect_class_and_region_sizes(seg, all_classes, vol_per_voxel): method _get_unique_labels (line 76) | def _get_unique_labels(self, patient_identifier): method _load_seg_analyze_classes (line 81) | def _load_seg_analyze_classes(self, patient_identifier, all_classes): method get_classes (line 109) | def get_classes(self): method analyse_segmentations (line 113) | def analyse_segmentations(self): method get_sizes_and_spacings_after_cropping (line 134) | def get_sizes_and_spacings_after_cropping(self): method get_modalities (line 145) | def get_modalities(self): method get_size_reduction_by_cropping (line 151) | def get_size_reduction_by_cropping(self): method _get_voxels_in_foreground (line 161) | def _get_voxels_in_foreground(self, patient_identifier, modality_id): method _compute_stats (line 169) | def _compute_stats(voxels): method collect_intensity_properties (line 181) | def collect_intensity_properties(self, num_modalities): method analyze_dataset (line 225) | def analyze_dataset(self, collect_intensityproperties=True): FILE: unetr_pp/experiment_planning/alternative_experiment_planning/experiment_planner_baseline_3DUNet_v21_11GB.py class ExperimentPlanner3D_v21_11GB (line 25) | class ExperimentPlanner3D_v21_11GB(ExperimentPlanner3D_v21): method __init__ (line 29) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_properties_for_stage (line 35) | def get_properties_for_stage(self, current_spacing, original_spacing, ... FILE: unetr_pp/experiment_planning/alternative_experiment_planning/experiment_planner_baseline_3DUNet_v21_16GB.py class ExperimentPlanner3D_v21_16GB (line 25) | class ExperimentPlanner3D_v21_16GB(ExperimentPlanner3D_v21): method __init__ (line 29) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_properties_for_stage (line 35) | def get_properties_for_stage(self, current_spacing, original_spacing, ... FILE: unetr_pp/experiment_planning/alternative_experiment_planning/experiment_planner_baseline_3DUNet_v21_32GB.py class ExperimentPlanner3D_v21_32GB (line 25) | class ExperimentPlanner3D_v21_32GB(ExperimentPlanner3D_v21): method __init__ (line 29) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_properties_for_stage (line 35) | def get_properties_for_stage(self, current_spacing, original_spacing, ... FILE: unetr_pp/experiment_planning/alternative_experiment_planning/experiment_planner_baseline_3DUNet_v21_3convperstage.py class ExperimentPlanner3D_v21_3cps (line 25) | class ExperimentPlanner3D_v21_3cps(ExperimentPlanner3D_v21): method __init__ (line 32) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method run_preprocessing (line 39) | def run_preprocessing(self, num_threads): FILE: unetr_pp/experiment_planning/alternative_experiment_planning/experiment_planner_baseline_3DUNet_v22.py class ExperimentPlanner3D_v22 (line 21) | class ExperimentPlanner3D_v22(ExperimentPlanner3D_v21): method __init__ (line 24) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_target_spacing (line 30) | def get_target_spacing(self): FILE: unetr_pp/experiment_planning/alternative_experiment_planning/experiment_planner_baseline_3DUNet_v23.py class ExperimentPlanner3D_v23 (line 20) | class ExperimentPlanner3D_v23(ExperimentPlanner3D_v21): method __init__ (line 23) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): FILE: unetr_pp/experiment_planning/alternative_experiment_planning/experiment_planner_residual_3DUNet_v21.py class ExperimentPlanner3DFabiansResUNet_v21 (line 26) | class ExperimentPlanner3DFabiansResUNet_v21(ExperimentPlanner3D_v21): method __init__ (line 27) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_properties_for_stage (line 33) | def get_properties_for_stage(self, current_spacing, original_spacing, ... method run_preprocessing (line 124) | def run_preprocessing(self, num_threads): FILE: unetr_pp/experiment_planning/alternative_experiment_planning/normalization/experiment_planner_2DUNet_v21_RGB_scaleto_0_1.py class ExperimentPlanner2D_v21_RGB_scaleTo_0_1 (line 20) | class ExperimentPlanner2D_v21_RGB_scaleTo_0_1(ExperimentPlanner2D_v21): method __init__ (line 24) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): FILE: unetr_pp/experiment_planning/alternative_experiment_planning/normalization/experiment_planner_3DUNet_CT2.py class ExperimentPlannerCT2 (line 22) | class ExperimentPlannerCT2(ExperimentPlanner): method __init__ (line 30) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method determine_normalization_scheme (line 35) | def determine_normalization_scheme(self): FILE: unetr_pp/experiment_planning/alternative_experiment_planning/normalization/experiment_planner_3DUNet_nonCT.py class ExperimentPlannernonCT (line 22) | class ExperimentPlannernonCT(ExperimentPlanner): method __init__ (line 27) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method determine_normalization_scheme (line 32) | def determine_normalization_scheme(self): FILE: unetr_pp/experiment_planning/alternative_experiment_planning/patch_size/experiment_planner_3DUNet_isotropic_in_mm.py class ExperimentPlannerIso (line 25) | class ExperimentPlannerIso(ExperimentPlanner): method __init__ (line 32) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_properties_for_stage (line 37) | def get_properties_for_stage(self, current_spacing, original_spacing, ... FILE: unetr_pp/experiment_planning/alternative_experiment_planning/patch_size/experiment_planner_3DUNet_isotropic_in_voxels.py class ExperimentPlanner3D_IsoPatchesInVoxels (line 25) | class ExperimentPlanner3D_IsoPatchesInVoxels(ExperimentPlanner): method __init__ (line 33) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_properties_for_stage (line 38) | def get_properties_for_stage(self, current_spacing, original_spacing, ... FILE: unetr_pp/experiment_planning/alternative_experiment_planning/pooling_and_convs/experiment_planner_baseline_3DUNet_allConv3x3.py class ExperimentPlannerAllConv3x3 (line 24) | class ExperimentPlannerAllConv3x3(ExperimentPlanner): method __init__ (line 25) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_properties_for_stage (line 30) | def get_properties_for_stage(self, current_spacing, original_spacing, ... method run_preprocessing (line 136) | def run_preprocessing(self, num_threads): FILE: unetr_pp/experiment_planning/alternative_experiment_planning/pooling_and_convs/experiment_planner_baseline_3DUNet_poolBasedOnSpacing.py class ExperimentPlannerPoolBasedOnSpacing (line 24) | class ExperimentPlannerPoolBasedOnSpacing(ExperimentPlanner): method __init__ (line 25) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_properties_for_stage (line 31) | def get_properties_for_stage(self, current_spacing, original_spacing, ... FILE: unetr_pp/experiment_planning/alternative_experiment_planning/target_spacing/experiment_planner_baseline_3DUNet_targetSpacingForAnisoAxis.py class ExperimentPlannerTargetSpacingForAnisoAxis (line 20) | class ExperimentPlannerTargetSpacingForAnisoAxis(ExperimentPlanner): method __init__ (line 21) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_target_spacing (line 27) | def get_target_spacing(self): FILE: unetr_pp/experiment_planning/alternative_experiment_planning/target_spacing/experiment_planner_baseline_3DUNet_v21_customTargetSpacing_2x2x2.py class ExperimentPlanner3D_v21_customTargetSpacing_2x2x2 (line 20) | class ExperimentPlanner3D_v21_customTargetSpacing_2x2x2(ExperimentPlanne... method __init__ (line 21) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_target_spacing (line 30) | def get_target_spacing(self): FILE: unetr_pp/experiment_planning/alternative_experiment_planning/target_spacing/experiment_planner_baseline_3DUNet_v21_noResampling.py class ExperimentPlanner3D_v21_noResampling (line 23) | class ExperimentPlanner3D_v21_noResampling(ExperimentPlanner3D_v21): method __init__ (line 24) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method plan_experiment (line 31) | def plan_experiment(self): class ExperimentPlanner3D_v21_noResampling_16GB (line 121) | class ExperimentPlanner3D_v21_noResampling_16GB(ExperimentPlanner3D_v21_... method __init__ (line 122) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method plan_experiment (line 129) | def plan_experiment(self): FILE: unetr_pp/experiment_planning/common_utils.py function split_4d_nifti (line 23) | def split_4d_nifti(filename, output_folder): function get_pool_and_conv_props_poolLateV2 (line 50) | def get_pool_and_conv_props_poolLateV2(patch_size, min_feature_map_size,... function get_pool_and_conv_props (line 89) | def get_pool_and_conv_props(spacing, patch_size, min_feature_map_size, m... function get_pool_and_conv_props_v2 (line 157) | def get_pool_and_conv_props_v2(spacing, patch_size, min_feature_map_size... function get_shape_must_be_divisible_by (line 232) | def get_shape_must_be_divisible_by(net_numpool_per_axis): function pad_shape (line 236) | def pad_shape(shape, must_be_divisible_by): function get_network_numpool (line 257) | def get_network_numpool(patch_size, maxpool_cap=999, min_feature_map_siz... FILE: unetr_pp/experiment_planning/experiment_planner_baseline_2DUNet.py class ExperimentPlanner2D (line 32) | class ExperimentPlanner2D(ExperimentPlanner): method __init__ (line 33) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_properties_for_stage (line 45) | def get_properties_for_stage(self, current_spacing, original_spacing, ... method plan_experiment (line 90) | def plan_experiment(self): FILE: unetr_pp/experiment_planning/experiment_planner_baseline_2DUNet_v21.py class ExperimentPlanner2D_v21 (line 23) | class ExperimentPlanner2D_v21(ExperimentPlanner2D): method __init__ (line 24) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_properties_for_stage (line 31) | def get_properties_for_stage(self, current_spacing, original_spacing, ... FILE: unetr_pp/experiment_planning/experiment_planner_baseline_3DUNet.py class ExperimentPlanner (line 32) | class ExperimentPlanner(object): method __init__ (line 33) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_target_spacing (line 66) | def get_target_spacing(self): method save_my_plans (line 81) | def save_my_plans(self): method load_my_plans (line 85) | def load_my_plans(self): method determine_postprocessing (line 94) | def determine_postprocessing(self): method get_properties_for_stage (line 144) | def get_properties_for_stage(self, current_spacing, original_spacing, ... method plan_experiment (line 247) | def plan_experiment(self): method determine_normalization_scheme (line 359) | def determine_normalization_scheme(self): method save_properties_of_cropped (line 371) | def save_properties_of_cropped(self, case_identifier, properties): method load_properties_of_cropped (line 375) | def load_properties_of_cropped(self, case_identifier): method determine_whether_to_use_mask_for_norm (line 380) | def determine_whether_to_use_mask_for_norm(self): method write_normalization_scheme_to_patients (line 411) | def write_normalization_scheme_to_patients(self): method run_preprocessing (line 422) | def run_preprocessing(self, num_threads): FILE: unetr_pp/experiment_planning/experiment_planner_baseline_3DUNet_v21.py class ExperimentPlanner3D_v21 (line 24) | class ExperimentPlanner3D_v21(ExperimentPlanner): method __init__ (line 31) | def __init__(self, folder_with_cropped_data, preprocessed_output_folder): method get_target_spacing (line 38) | def get_target_spacing(self): method get_properties_for_stage (line 83) | def get_properties_for_stage(self, current_spacing, original_spacing, ... FILE: unetr_pp/experiment_planning/nnFormer_convert_decathlon_task.py function crawl_and_remove_hidden_from_decathlon (line 20) | def crawl_and_remove_hidden_from_decathlon(folder): function main (line 41) | def main(): FILE: unetr_pp/experiment_planning/nnFormer_plan_and_preprocess.py function main (line 27) | def main(): FILE: unetr_pp/experiment_planning/summarize_plans.py function summarize_plans (line 20) | def summarize_plans(file): function write_plans_to_file (line 37) | def write_plans_to_file(f, plans_file): FILE: unetr_pp/experiment_planning/utils.py function split_4d (line 31) | def split_4d(input_folder, num_processes=default_num_threads, overwrite_... function create_lists_from_splitted_dataset (line 82) | def create_lists_from_splitted_dataset(base_folder_splitted): function create_lists_from_splitted_dataset_folder (line 100) | def create_lists_from_splitted_dataset_folder(folder): function get_caseIDs_from_splitted_dataset_folder (line 113) | def get_caseIDs_from_splitted_dataset_folder(folder): function crop (line 122) | def crop(task_string, override=False, num_threads=default_num_threads): function analyze_dataset (line 138) | def analyze_dataset(task_string, override=False, collect_intensityproper... function plan_and_preprocess (line 144) | def plan_and_preprocess(task_string, processes_lowres=default_num_thread... function add_classes_in_slice_info (line 190) | def add_classes_in_slice_info(args): FILE: unetr_pp/inference/predict.py function preprocess_save_to_queue (line 37) | def preprocess_save_to_queue(preprocess_fn, q, list_of_lists, output_fil... function preprocess_multithreaded (line 95) | def preprocess_multithreaded(trainer, list_of_lists, output_files, num_p... function predict_cases (line 133) | def predict_cases(model, list_of_lists, output_filenames, folds, save_np... function predict_cases_fast (line 289) | def predict_cases_fast(model, list_of_lists, output_filenames, folds, nu... function predict_cases_fastest (line 427) | def predict_cases_fastest(model, list_of_lists, output_filenames, folds,... function check_input_folder_and_return_caseIDs (line 543) | def check_input_folder_and_return_caseIDs(input_folder, expected_num_mod... function predict_from_folder (line 579) | def predict_from_folder(model: str, input_folder: str, output_folder: st... FILE: unetr_pp/inference/predict_simple.py function main (line 27) | def main(): FILE: unetr_pp/inference/segmentation_export.py function save_segmentation_nifti_from_softmax (line 27) | def save_segmentation_nifti_from_softmax(segmentation_softmax: Union[str... function save_segmentation_nifti (line 158) | def save_segmentation_nifti(segmentation, out_fname, dct, order=1, force... FILE: unetr_pp/inference_acdc.py function read_nii (line 11) | def read_nii(path): function dice (line 16) | def dice(pred, label): function process_label (line 22) | def process_label(label): function hd (line 42) | def hd(pred,gt): function test (line 55) | def test(fold): FILE: unetr_pp/inference_synapse.py function read_nii (line 8) | def read_nii(path): function dice (line 11) | def dice(pred, label): function hd (line 16) | def hd(pred,gt): function process_label (line 23) | def process_label(label): function test (line 35) | def test(fold): FILE: unetr_pp/inference_tumor.py function read_nii (line 8) | def read_nii(path): function new_dice (line 11) | def new_dice(pred,label): function dice (line 17) | def dice(pred, label): function hd (line 23) | def hd(pred,gt): function process_label (line 30) | def process_label(label): function test (line 41) | def test(fold): FILE: unetr_pp/network_architecture/acdc/model_components.py class UnetrPPEncoder (line 13) | class UnetrPPEncoder(nn.Module): method __init__ (line 14) | def __init__(self, input_size=[16 * 40 * 40, 8 * 20 * 20, 4 * 10 * 10,... method _init_weights (line 45) | def _init_weights(self, m): method forward_features (line 54) | def forward_features(self, x): method forward (line 70) | def forward(self, x): class UnetrUpBlock (line 75) | class UnetrUpBlock(nn.Module): method __init__ (line 76) | def __init__( method _init_weights (line 133) | def _init_weights(self, m): method forward (line 142) | def forward(self, inp, skip): FILE: unetr_pp/network_architecture/acdc/transformerblock.py class TransformerBlock (line 6) | class TransformerBlock(nn.Module): method __init__ (line 12) | def __init__( method forward (line 54) | def forward(self, x): class EPA (line 69) | class EPA(nn.Module): method __init__ (line 74) | def __init__(self, input_size, hidden_size, proj_size, num_heads=4, qk... method forward (line 93) | def forward(self, x): method no_weight_decay (line 135) | def no_weight_decay(self): FILE: unetr_pp/network_architecture/acdc/unetr_pp_acdc.py class UNETR_PP (line 8) | class UNETR_PP(SegmentationNetwork): method __init__ (line 13) | def __init__( method proj_feat (line 113) | def proj_feat(self, x, hidden_size, feat_size): method forward (line 118) | def forward(self, x_in): FILE: unetr_pp/network_architecture/dynunet_block.py class UnetResBlock (line 12) | class UnetResBlock(nn.Module): method __init__ (line 30) | def __init__( method forward (line 67) | def forward(self, inp): class UnetBasicBlock (line 83) | class UnetBasicBlock(nn.Module): method __init__ (line 101) | def __init__( method forward (line 129) | def forward(self, inp): class UnetUpBlock (line 139) | class UnetUpBlock(nn.Module): method __init__ (line 159) | def __init__( method forward (line 196) | def forward(self, inp, skip): class UnetOutBlock (line 204) | class UnetOutBlock(nn.Module): method __init__ (line 205) | def __init__( method forward (line 213) | def forward(self, inp): function get_conv_layer (line 217) | def get_conv_layer( function get_padding (line 251) | def get_padding( function get_output_padding (line 265) | def get_output_padding( FILE: unetr_pp/network_architecture/generic_UNet.py class ConvDropoutNormNonlin (line 26) | class ConvDropoutNormNonlin(nn.Module): method __init__ (line 31) | def __init__(self, input_channels, output_channels, method forward (line 64) | def forward(self, x): class ConvDropoutNonlinNorm (line 71) | class ConvDropoutNonlinNorm(ConvDropoutNormNonlin): method forward (line 72) | def forward(self, x): class StackedConvLayers (line 79) | class StackedConvLayers(nn.Module): method __init__ (line 80) | def __init__(self, input_feature_channels, output_feature_channels, nu... method forward (line 141) | def forward(self, x): function print_module_training_status (line 145) | def print_module_training_status(module): class Upsample (line 154) | class Upsample(nn.Module): method __init__ (line 155) | def __init__(self, size=None, scale_factor=None, mode='nearest', align... method forward (line 162) | def forward(self, x): class Generic_UNet (line 167) | class Generic_UNet(SegmentationNetwork): method __init__ (line 184) | def __init__(self, input_channels, base_num_features, num_classes, num... method forward (line 388) | def forward(self, x): method compute_approx_vram_consumption (line 417) | def compute_approx_vram_consumption(patch_size, num_pool_per_axis, bas... FILE: unetr_pp/network_architecture/initialization.py class InitWeights_He (line 19) | class InitWeights_He(object): method __init__ (line 20) | def __init__(self, neg_slope=1e-2): method __call__ (line 23) | def __call__(self, module): class InitWeights_XavierUniform (line 30) | class InitWeights_XavierUniform(object): method __init__ (line 31) | def __init__(self, gain=1): method __call__ (line 34) | def __call__(self, module): FILE: unetr_pp/network_architecture/layers.py class LayerNorm (line 7) | class LayerNorm(nn.Module): method __init__ (line 8) | def __init__(self, normalized_shape, eps=1e-6, data_format="channels_l... method forward (line 18) | def forward(self, x): class PositionalEncodingFourier (line 29) | class PositionalEncodingFourier(nn.Module): method __init__ (line 30) | def __init__(self, hidden_dim=32, dim=768, temperature=10000): method forward (line 38) | def forward(self, B, H, W): FILE: unetr_pp/network_architecture/lung/model_components.py class UnetrPPEncoder (line 15) | class UnetrPPEncoder(nn.Module): method __init__ (line 16) | def __init__(self, input_size=[32*48*48, 16 * 24 * 24, 8 * 12 * 12, 4*... method _init_weights (line 49) | def _init_weights(self, m): method forward_features (line 58) | def forward_features(self, x): method forward (line 74) | def forward(self, x): class UnetrUpBlock (line 79) | class UnetrUpBlock(nn.Module): method __init__ (line 80) | def __init__( method _init_weights (line 137) | def _init_weights(self, m): method forward (line 146) | def forward(self, inp, skip): FILE: unetr_pp/network_architecture/lung/transformerblock.py class TransformerBlock (line 6) | class TransformerBlock(nn.Module): method __init__ (line 12) | def __init__( method forward (line 55) | def forward(self, x): class EPA (line 72) | class EPA(nn.Module): method __init__ (line 77) | def __init__(self, input_size, hidden_size, proj_size, num_heads=4, qk... method forward (line 96) | def forward(self, x): method no_weight_decay (line 139) | def no_weight_decay(self): FILE: unetr_pp/network_architecture/lung/unetr_pp_lung.py class UNETR_PP (line 8) | class UNETR_PP(SegmentationNetwork): method __init__ (line 13) | def __init__( method proj_feat (line 113) | def proj_feat(self, x, hidden_size, feat_size): method forward (line 118) | def forward(self, x_in): FILE: unetr_pp/network_architecture/neural_network.py class NeuralNetwork (line 28) | class NeuralNetwork(nn.Module): method __init__ (line 29) | def __init__(self): method get_device (line 32) | def get_device(self): method set_device (line 38) | def set_device(self, device): method forward (line 44) | def forward(self, x): class SegmentationNetwork (line 48) | class SegmentationNetwork(NeuralNetwork): method __init__ (line 49) | def __init__(self): method predict_3D (line 73) | def predict_3D(self, x: np.ndarray, do_mirroring: bool, mirror_axes: T... method predict_2D (line 168) | def predict_2D(self, x, do_mirroring: bool, mirror_axes: tuple = (0, 1... method _get_gaussian (line 251) | def _get_gaussian(patch_size, sigma_scale=1. / 8) -> np.ndarray: method _compute_steps_for_sliding_window (line 267) | def _compute_steps_for_sliding_window(patch_size: Tuple[int, ...], ima... method _internal_predict_3D_3Dconv_tiled (line 292) | def _internal_predict_3D_3Dconv_tiled(self, x: np.ndarray, step_size: ... method _internal_predict_2D_2Dconv (line 430) | def _internal_predict_2D_2Dconv(self, x: np.ndarray, min_size: Tuple[i... method _internal_predict_3D_3Dconv (line 466) | def _internal_predict_3D_3Dconv(self, x: np.ndarray, min_size: Tuple[i... method _internal_maybe_mirror_and_pred_3D (line 502) | def _internal_maybe_mirror_and_pred_3D(self, x: Union[np.ndarray, torc... method _internal_maybe_mirror_and_pred_2D (line 561) | def _internal_maybe_mirror_and_pred_2D(self, x: Union[np.ndarray, torc... method _internal_predict_2D_2Dconv_tiled (line 604) | def _internal_predict_2D_2Dconv_tiled(self, x: np.ndarray, step_size: ... method _internal_predict_3D_2Dconv (line 736) | def _internal_predict_3D_2Dconv(self, x: np.ndarray, min_size: Tuple[i... method predict_3D_pseudo3D_2Dconv (line 754) | def predict_3D_pseudo3D_2Dconv(self, x: np.ndarray, min_size: Tuple[in... method _internal_predict_3D_2Dconv_tiled (line 786) | def _internal_predict_3D_2Dconv_tiled(self, x: np.ndarray, patch_size:... FILE: unetr_pp/network_architecture/synapse/model_components.py class UnetrPPEncoder (line 13) | class UnetrPPEncoder(nn.Module): method __init__ (line 14) | def __init__(self, input_size=[32 * 32 * 32, 16 * 16 * 16, 8 * 8 * 8, ... method _init_weights (line 43) | def _init_weights(self, m): method forward_features (line 52) | def forward_features(self, x): method forward (line 68) | def forward(self, x): class UnetrUpBlock (line 73) | class UnetrUpBlock(nn.Module): method __init__ (line 74) | def __init__( method _init_weights (line 129) | def _init_weights(self, m): method forward (line 138) | def forward(self, inp, skip): FILE: unetr_pp/network_architecture/synapse/transformerblock.py class TransformerBlock (line 6) | class TransformerBlock(nn.Module): method __init__ (line 12) | def __init__( method forward (line 52) | def forward(self, x): class EPA (line 68) | class EPA(nn.Module): method __init__ (line 73) | def __init__(self, input_size, hidden_size, proj_size, num_heads=4, qk... method forward (line 93) | def forward(self, x): method no_weight_decay (line 135) | def no_weight_decay(self): FILE: unetr_pp/network_architecture/synapse/unetr_pp_synapse.py class UNETR_PP (line 8) | class UNETR_PP(SegmentationNetwork): method __init__ (line 14) | def __init__( method proj_feat (line 128) | def proj_feat(self, x, hidden_size, feat_size): method forward (line 133) | def forward(self, x_in): FILE: unetr_pp/network_architecture/tumor/model_components.py class UnetrPPEncoder (line 13) | class UnetrPPEncoder(nn.Module): method __init__ (line 14) | def __init__(self, input_size=[32 * 32 * 32, 16 * 16 * 16, 8 * 8 * 8, ... method _init_weights (line 45) | def _init_weights(self, m): method forward_features (line 54) | def forward_features(self, x): method forward (line 70) | def forward(self, x): class UnetrUpBlock (line 75) | class UnetrUpBlock(nn.Module): method __init__ (line 76) | def __init__( method _init_weights (line 133) | def _init_weights(self, m): method forward (line 142) | def forward(self, inp, skip): FILE: unetr_pp/network_architecture/tumor/transformerblock.py class TransformerBlock (line 7) | class TransformerBlock(nn.Module): method __init__ (line 13) | def __init__( method forward (line 53) | def forward(self, x): function init_ (line 69) | def init_(tensor): class EPA (line 76) | class EPA(nn.Module): method __init__ (line 81) | def __init__(self, input_size, hidden_size, proj_size, num_heads=4, qk... method forward (line 98) | def forward(self, x): method no_weight_decay (line 129) | def no_weight_decay(self): FILE: unetr_pp/network_architecture/tumor/unetr_pp_tumor.py class UNETR_PP (line 8) | class UNETR_PP(SegmentationNetwork): method __init__ (line 13) | def __init__( method proj_feat (line 113) | def proj_feat(self, x, hidden_size, feat_size): method forward (line 118) | def forward(self, x_in): FILE: unetr_pp/postprocessing/connected_components.py function load_remove_save (line 30) | def load_remove_save(input_file: str, output_file: str, for_which_classe... function remove_all_but_the_largest_connected_component (line 48) | def remove_all_but_the_largest_connected_component(image: np.ndarray, fo... function load_postprocessing (line 108) | def load_postprocessing(json_file): function determine_postprocessing (line 122) | def determine_postprocessing(base, gt_labels_folder, raw_subfolder_name=... function apply_postprocessing_to_folder (line 400) | def apply_postprocessing_to_folder(input_folder: str, output_folder: str... FILE: unetr_pp/postprocessing/consolidate_all_for_paper.py function get_datasets (line 19) | def get_datasets(): function get_commands (line 44) | def get_commands(configurations, regular_trainer="nnFormerTrainerV2", ca... FILE: unetr_pp/postprocessing/consolidate_postprocessing.py function collect_cv_niftis (line 25) | def collect_cv_niftis(cv_folder: str, output_folder: str, validation_fol... function consolidate_folds (line 43) | def consolidate_folds(output_folder_base, validation_folder_name: str = ... FILE: unetr_pp/postprocessing/consolidate_postprocessing_simple.py function main (line 23) | def main(): FILE: unetr_pp/preprocessing/cropping.py function create_nonzero_mask (line 23) | def create_nonzero_mask(data): function get_bbox_from_mask (line 34) | def get_bbox_from_mask(mask, outside_value=0): function crop_to_bbox (line 45) | def crop_to_bbox(image, bbox): function get_case_identifier (line 51) | def get_case_identifier(case): function get_case_identifier_from_npz (line 56) | def get_case_identifier_from_npz(case): function load_case_from_list_of_files (line 61) | def load_case_from_list_of_files(data_files, seg_file=None): function crop_to_nonzero (line 84) | def crop_to_nonzero(data, seg=None, nonzero_label=-1): function get_patient_identifiers_from_cropped_files (line 119) | def get_patient_identifiers_from_cropped_files(folder): class ImageCropper (line 123) | class ImageCropper(object): method __init__ (line 124) | def __init__(self, num_threads, output_folder=None): method crop (line 139) | def crop(data, properties, seg=None): method crop_from_list_of_files (line 153) | def crop_from_list_of_files(data_files, seg_file=None): method load_crop_save (line 157) | def load_crop_save(self, case, case_identifier, overwrite_existing=Fal... method get_list_of_cropped_files (line 175) | def get_list_of_cropped_files(self): method get_patient_identifiers_from_cropped_files (line 178) | def get_patient_identifiers_from_cropped_files(self): method run_cropping (line 181) | def run_cropping(self, list_of_files, overwrite_existing=False, output... method load_properties (line 209) | def load_properties(self, case_identifier): method save_properties (line 214) | def save_properties(self, case_identifier, properties): FILE: unetr_pp/preprocessing/custom_preprocessors/preprocessor_scale_RGB_to_0_1.py class GenericPreprocessor_scale_uint8_to_0_1 (line 19) | class GenericPreprocessor_scale_uint8_to_0_1(PreprocessorFor2D): method resample_and_normalize (line 27) | def resample_and_normalize(self, data, target_spacing, properties, seg... FILE: unetr_pp/preprocessing/preprocessing.py function get_do_separate_z (line 28) | def get_do_separate_z(spacing, anisotropy_threshold=RESAMPLING_SEPARATE_... function get_lowres_axis (line 33) | def get_lowres_axis(new_spacing): function resample_patient (line 38) | def resample_patient(data, seg, original_spacing, target_spacing, order_... function resample_data_or_seg (line 112) | def resample_data_or_seg(data, new_shape, is_seg, axis=None, order=3, do... class GenericPreprocessor (line 204) | class GenericPreprocessor(object): method __init__ (line 205) | def __init__(self, normalization_scheme_per_modality, use_nonzero_mask... method load_cropped (line 220) | def load_cropped(cropped_output_dir, case_identifier): method resample_and_normalize (line 228) | def resample_and_normalize(self, data, target_spacing, properties, seg... method preprocess_test_case (line 308) | def preprocess_test_case(self, data_files, target_spacing, seg_file=No... method _run_internal (line 318) | def _run_internal(self, target_spacing, case_identifier, output_folder... method run (line 356) | def run(self, target_spacings, input_folder_with_cropped_npz, output_f... class Preprocessor3DDifferentResampling (line 397) | class Preprocessor3DDifferentResampling(GenericPreprocessor): method resample_and_normalize (line 398) | def resample_and_normalize(self, data, target_spacing, properties, seg... class Preprocessor3DBetterResampling (line 479) | class Preprocessor3DBetterResampling(GenericPreprocessor): method resample_and_normalize (line 485) | def resample_and_normalize(self, data, target_spacing, properties, seg... class PreprocessorFor2D (line 573) | class PreprocessorFor2D(GenericPreprocessor): method __init__ (line 574) | def __init__(self, normalization_scheme_per_modality, use_nonzero_mask... method run (line 578) | def run(self, target_spacings, input_folder_with_cropped_npz, output_f... method resample_and_normalize (line 606) | def resample_and_normalize(self, data, target_spacing, properties, seg... class PreprocessorFor3D_NoResampling (line 674) | class PreprocessorFor3D_NoResampling(GenericPreprocessor): method resample_and_normalize (line 675) | def resample_and_normalize(self, data, target_spacing, properties, seg... class PreprocessorFor2D_noNormalization (line 754) | class PreprocessorFor2D_noNormalization(GenericPreprocessor): method resample_and_normalize (line 755) | def resample_and_normalize(self, data, target_spacing, properties, seg... FILE: unetr_pp/preprocessing/sanity_checks.py function verify_all_same_orientation (line 25) | def verify_all_same_orientation(folder): function verify_same_geometry (line 45) | def verify_same_geometry(img_1: sitk.Image, img_2: sitk.Image): function verify_contains_only_expected_labels (line 79) | def verify_contains_only_expected_labels(itk_img: str, valid_labels: (tu... function verify_dataset_integrity (line 90) | def verify_dataset_integrity(folder): function reorient_to_RAS (line 237) | def reorient_to_RAS(img_fname: str, output_fname: str = None): FILE: unetr_pp/run/default_configuration.py function get_configuration_from_output_folder (line 25) | def get_configuration_from_output_folder(folder): function get_default_configuration (line 36) | def get_default_configuration(network, task, network_trainer, plans_iden... FILE: unetr_pp/run/run_training.py function main (line 38) | def main(): FILE: unetr_pp/training/cascade_stuff/predict_next_stage.py function resample_and_save (line 31) | def resample_and_save(predicted, target_shape, output_file, force_separa... function predict_next_stage (line 46) | def predict_next_stage(trainer, stage_to_be_predicted_folder): FILE: unetr_pp/training/data_augmentation/custom_transforms.py class RemoveKeyTransform (line 19) | class RemoveKeyTransform(AbstractTransform): method __init__ (line 20) | def __init__(self, key_to_remove): method __call__ (line 23) | def __call__(self, **data_dict): class MaskTransform (line 28) | class MaskTransform(AbstractTransform): method __init__ (line 29) | def __init__(self, dct_for_where_it_was_used, mask_idx_in_seg=1, set_o... method __call__ (line 46) | def __call__(self, **data_dict): function convert_3d_to_2d_generator (line 60) | def convert_3d_to_2d_generator(data_dict): function convert_2d_to_3d_generator (line 70) | def convert_2d_to_3d_generator(data_dict): class Convert3DTo2DTransform (line 80) | class Convert3DTo2DTransform(AbstractTransform): method __init__ (line 81) | def __init__(self): method __call__ (line 84) | def __call__(self, **data_dict): class Convert2DTo3DTransform (line 88) | class Convert2DTo3DTransform(AbstractTransform): method __init__ (line 89) | def __init__(self): method __call__ (line 92) | def __call__(self, **data_dict): class ConvertSegmentationToRegionsTransform (line 96) | class ConvertSegmentationToRegionsTransform(AbstractTransform): method __init__ (line 97) | def __init__(self, regions: dict, seg_key: str = "seg", output_key: st... method __call__ (line 110) | def __call__(self, **data_dict): FILE: unetr_pp/training/data_augmentation/data_augmentation_insaneDA.py function get_insaneDA_augmentation (line 37) | def get_insaneDA_augmentation(dataloader_train, dataloader_val, patch_si... FILE: unetr_pp/training/data_augmentation/data_augmentation_insaneDA2.py function get_insaneDA_augmentation2 (line 38) | def get_insaneDA_augmentation2(dataloader_train, dataloader_val, patch_s... FILE: unetr_pp/training/data_augmentation/data_augmentation_moreDA.py function get_moreDA_augmentation (line 37) | def get_moreDA_augmentation(dataloader_train, dataloader_val, patch_size... FILE: unetr_pp/training/data_augmentation/data_augmentation_noDA.py function get_no_augmentation (line 28) | def get_no_augmentation(dataloader_train, dataloader_val, params=default... FILE: unetr_pp/training/data_augmentation/default_data_augmentation.py function get_patch_size (line 107) | def get_patch_size(final_patch_size, rot_x, rot_y, rot_z, scale_range): function get_default_augmentation (line 130) | def get_default_augmentation(dataloader_train, dataloader_val, patch_siz... FILE: unetr_pp/training/data_augmentation/downsampling.py class DownsampleSegForDSTransform3 (line 23) | class DownsampleSegForDSTransform3(AbstractTransform): method __init__ (line 34) | def __init__(self, ds_scales=(1, 0.5, 0.25), input_key="seg", output_k... method __call__ (line 40) | def __call__(self, **data_dict): function downsample_seg_for_ds_transform3 (line 45) | def downsample_seg_for_ds_transform3(seg, ds_scales=((1, 1, 1), (0.5, 0.... class DownsampleSegForDSTransform2 (line 70) | class DownsampleSegForDSTransform2(AbstractTransform): method __init__ (line 74) | def __init__(self, ds_scales=(1, 0.5, 0.25), order=0, cval=0, input_ke... method __call__ (line 82) | def __call__(self, **data_dict): function downsample_seg_for_ds_transform2 (line 88) | def downsample_seg_for_ds_transform2(seg, ds_scales=((1, 1, 1), (0.5, 0.... FILE: unetr_pp/training/data_augmentation/pyramid_augmentations.py class RemoveRandomConnectedComponentFromOneHotEncodingTransform (line 22) | class RemoveRandomConnectedComponentFromOneHotEncodingTransform(Abstract... method __init__ (line 23) | def __init__(self, channel_idx, key="data", p_per_sample=0.2, fill_wit... method __call__ (line 39) | def __call__(self, **data_dict): class MoveSegAsOneHotToData (line 70) | class MoveSegAsOneHotToData(AbstractTransform): method __init__ (line 71) | def __init__(self, channel_id, all_seg_labels, key_origin="seg", key_t... method __call__ (line 78) | def __call__(self, **data_dict): class ApplyRandomBinaryOperatorTransform (line 95) | class ApplyRandomBinaryOperatorTransform(AbstractTransform): method __init__ (line 96) | def __init__(self, channel_idx, p_per_sample=0.3, any_of_these=(binary... method __call__ (line 111) | def __call__(self, **data_dict): class ApplyRandomBinaryOperatorTransform2 (line 138) | class ApplyRandomBinaryOperatorTransform2(AbstractTransform): method __init__ (line 139) | def __init__(self, channel_idx, p_per_sample=0.3, p_per_label=0.3, any... method __call__ (line 164) | def __call__(self, **data_dict): FILE: unetr_pp/training/dataloading/dataset_loading.py function get_case_identifiers (line 26) | def get_case_identifiers(folder): function get_case_identifiers_from_raw_folder (line 31) | def get_case_identifiers_from_raw_folder(folder): function convert_to_npy (line 37) | def convert_to_npy(args): function save_as_npz (line 48) | def save_as_npz(args): function unpack_dataset (line 58) | def unpack_dataset(folder, threads=default_num_threads, key="data"): function pack_dataset (line 73) | def pack_dataset(folder, threads=default_num_threads, key="data"): function delete_npy (line 81) | def delete_npy(folder): function load_dataset (line 89) | def load_dataset(folder, num_cases_properties_loading_threshold=1000): function crop_2D_image_force_fg (line 113) | def crop_2D_image_force_fg(img, crop_size, valid_voxels): class DataLoader3D (line 155) | class DataLoader3D(SlimDataLoaderBase): method __init__ (line 156) | def __init__(self, data, patch_size, final_patch_size, batch_size, has... method get_do_oversample (line 204) | def get_do_oversample(self, batch_idx): method determine_shapes (line 207) | def determine_shapes(self): method generate_train_batch (line 223) | def generate_train_batch(self): class DataLoader2D (line 382) | class DataLoader2D(SlimDataLoaderBase): method __init__ (line 383) | def __init__(self, data, patch_size, final_patch_size, batch_size, ove... method determine_shapes (line 429) | def determine_shapes(self): method get_do_oversample (line 442) | def get_do_oversample(self, batch_idx): method generate_train_batch (line 445) | def generate_train_batch(self): FILE: unetr_pp/training/learning_rate/poly_lr.py function poly_lr (line 16) | def poly_lr(epoch, max_epochs, initial_lr, exponent=0.9): FILE: unetr_pp/training/loss_functions/TopK_loss.py class TopKLoss (line 20) | class TopKLoss(RobustCrossEntropyLoss): method __init__ (line 24) | def __init__(self, weight=None, ignore_index=-100, k=10): method forward (line 28) | def forward(self, inp, target): FILE: unetr_pp/training/loss_functions/crossentropy.py class RobustCrossEntropyLoss (line 4) | class RobustCrossEntropyLoss(nn.CrossEntropyLoss): method forward (line 8) | def forward(self, input: Tensor, target: Tensor) -> Tensor: FILE: unetr_pp/training/loss_functions/deep_supervision.py class MultipleOutputLoss2 (line 19) | class MultipleOutputLoss2(nn.Module): method __init__ (line 20) | def __init__(self, loss, weight_factors=None): method forward (line 31) | def forward(self, x, y): FILE: unetr_pp/training/loss_functions/dice_loss.py class GDL (line 25) | class GDL(nn.Module): method __init__ (line 26) | def __init__(self, apply_nonlin=None, batch_dice=False, do_bg=True, sm... method forward (line 40) | def forward(self, x, y, loss_mask=None): function get_tp_fp_fn_tn (line 100) | def get_tp_fp_fn_tn(net_output, gt, axes=None, mask=None, square=False): class SoftDiceLoss (line 158) | class SoftDiceLoss(nn.Module): method __init__ (line 159) | def __init__(self, apply_nonlin=None, batch_dice=False, do_bg=True, sm... method forward (line 169) | def forward(self, x, y, loss_mask=None): class MCCLoss (line 197) | class MCCLoss(nn.Module): method __init__ (line 198) | def __init__(self, apply_nonlin=None, batch_mcc=False, do_bg=True, smo... method forward (line 212) | def forward(self, x, y, loss_mask=None): class SoftDiceLossSquared (line 245) | class SoftDiceLossSquared(nn.Module): method __init__ (line 246) | def __init__(self, apply_nonlin=None, batch_dice=False, do_bg=True, sm... method forward (line 257) | def forward(self, x, y, loss_mask=None): class DC_and_CE_loss (line 304) | class DC_and_CE_loss(nn.Module): method __init__ (line 305) | def __init__(self, soft_dice_kwargs, ce_kwargs, aggregate="sum", squar... method forward (line 333) | def forward(self, net_output, target): class DC_and_BCE_loss (line 364) | class DC_and_BCE_loss(nn.Module): method __init__ (line 365) | def __init__(self, bce_kwargs, soft_dice_kwargs, aggregate="sum"): method forward (line 380) | def forward(self, net_output, target): class GDL_and_CE_loss (line 392) | class GDL_and_CE_loss(nn.Module): method __init__ (line 393) | def __init__(self, gdl_dice_kwargs, ce_kwargs, aggregate="sum"): method forward (line 399) | def forward(self, net_output, target): class DC_and_topk_loss (line 409) | class DC_and_topk_loss(nn.Module): method __init__ (line 410) | def __init__(self, soft_dice_kwargs, ce_kwargs, aggregate="sum", squar... method forward (line 419) | def forward(self, net_output, target): FILE: unetr_pp/training/model_restore.py function recursive_find_python_class (line 22) | def recursive_find_python_class(folder, trainer_name, current_module): function restore_model (line 43) | def restore_model(pkl_file, checkpoint=None, train=False, fp16=None,fold... function load_best_model_for_inference (line 112) | def load_best_model_for_inference(folder): function load_model_and_checkpoint_files (line 118) | def load_model_and_checkpoint_files(folder, folds=None, mixed_precision=... FILE: unetr_pp/training/network_training/Trainer_acdc.py class Trainer_acdc (line 48) | class Trainer_acdc(NetworkTrainer_acdc): method __init__ (line 49) | def __init__(self, plans_file, fold, output_folder=None, dataset_direc... method update_fold (line 134) | def update_fold(self, fold): method setup_DA_params (line 153) | def setup_DA_params(self): method initialize (line 189) | def initialize(self, training=True, force_load_plans=False): method initialize_network (line 234) | def initialize_network(self): method initialize_optimizer_and_scheduler (line 267) | def initialize_optimizer_and_scheduler(self): method plot_network_architecture (line 276) | def plot_network_architecture(self): method save_debug_information (line 299) | def save_debug_information(self): method run_training (line 317) | def run_training(self): method load_plans_file (line 321) | def load_plans_file(self): method process_plans (line 328) | def process_plans(self, plans): method load_dataset (line 396) | def load_dataset(self): method get_basic_generators (line 399) | def get_basic_generators(self): method preprocess_patient (line 419) | def preprocess_patient(self, input_files): method preprocess_predict_nifti (line 447) | def preprocess_predict_nifti(self, input_files: List[str], output_file... method predict_preprocessed_data_return_seg_and_softmax (line 485) | def predict_preprocessed_data_return_seg_and_softmax(self, data: np.nd... method validate (line 528) | def validate(self, do_mirroring: bool = True, use_sliding_window: bool... method run_online_evaluation (line 685) | def run_online_evaluation(self, output, target): method finish_online_evaluation (line 709) | def finish_online_evaluation(self): method save_checkpoint (line 728) | def save_checkpoint(self, fname, save_optimizer=True): FILE: unetr_pp/training/network_training/Trainer_lung.py class Trainer_lung (line 49) | class Trainer_lung(NetworkTrainer_lung): method __init__ (line 50) | def __init__(self, plans_file, fold, output_folder=None, dataset_direc... method update_fold (line 135) | def update_fold(self, fold): method setup_DA_params (line 154) | def setup_DA_params(self): method initialize (line 190) | def initialize(self, training=True, force_load_plans=False): method initialize_network (line 235) | def initialize_network(self): method initialize_optimizer_and_scheduler (line 268) | def initialize_optimizer_and_scheduler(self): method plot_network_architecture (line 277) | def plot_network_architecture(self): method save_debug_information (line 300) | def save_debug_information(self): method run_training (line 318) | def run_training(self): method load_plans_file (line 322) | def load_plans_file(self): method process_plans (line 329) | def process_plans(self, plans): method load_dataset (line 397) | def load_dataset(self): method get_basic_generators (line 400) | def get_basic_generators(self): method preprocess_patient (line 420) | def preprocess_patient(self, input_files): method preprocess_predict_nifti (line 448) | def preprocess_predict_nifti(self, input_files: List[str], output_file... method predict_preprocessed_data_return_seg_and_softmax (line 486) | def predict_preprocessed_data_return_seg_and_softmax(self, data: np.nd... method validate (line 529) | def validate(self, do_mirroring: bool = True, use_sliding_window: bool... method run_online_evaluation (line 686) | def run_online_evaluation(self, output, target): method finish_online_evaluation (line 710) | def finish_online_evaluation(self): method save_checkpoint (line 729) | def save_checkpoint(self, fname, save_optimizer=True): FILE: unetr_pp/training/network_training/Trainer_synapse.py class Trainer_synapse (line 49) | class Trainer_synapse(NetworkTrainer_synapse): method __init__ (line 50) | def __init__(self, plans_file, fold, output_folder=None, dataset_direc... method update_fold (line 135) | def update_fold(self, fold): method setup_DA_params (line 154) | def setup_DA_params(self): method initialize (line 190) | def initialize(self, training=True, force_load_plans=False): method initialize_network (line 235) | def initialize_network(self): method initialize_optimizer_and_scheduler (line 268) | def initialize_optimizer_and_scheduler(self): method plot_network_architecture (line 277) | def plot_network_architecture(self): method save_debug_information (line 300) | def save_debug_information(self): method run_training (line 318) | def run_training(self): method load_plans_file (line 322) | def load_plans_file(self): method process_plans (line 329) | def process_plans(self, plans): method load_dataset (line 397) | def load_dataset(self): method get_basic_generators (line 400) | def get_basic_generators(self): method preprocess_patient (line 420) | def preprocess_patient(self, input_files): method preprocess_predict_nifti (line 448) | def preprocess_predict_nifti(self, input_files: List[str], output_file... method predict_preprocessed_data_return_seg_and_softmax (line 486) | def predict_preprocessed_data_return_seg_and_softmax(self, data: np.nd... method validate (line 529) | def validate(self, do_mirroring: bool = True, use_sliding_window: bool... method run_online_evaluation (line 693) | def run_online_evaluation(self, output, target): method finish_online_evaluation (line 724) | def finish_online_evaluation(self): method save_checkpoint (line 743) | def save_checkpoint(self, fname, save_optimizer=True): FILE: unetr_pp/training/network_training/Trainer_tumor.py class Trainer_tumor (line 49) | class Trainer_tumor(NetworkTrainer_tumor): method __init__ (line 50) | def __init__(self, plans_file, fold, output_folder=None, dataset_direc... method update_fold (line 134) | def update_fold(self, fold): method setup_DA_params (line 153) | def setup_DA_params(self): method initialize (line 189) | def initialize(self, training=True, force_load_plans=False): method initialize_network (line 234) | def initialize_network(self): method initialize_optimizer_and_scheduler (line 267) | def initialize_optimizer_and_scheduler(self): method plot_network_architecture (line 276) | def plot_network_architecture(self): method save_debug_information (line 299) | def save_debug_information(self): method run_training (line 317) | def run_training(self): method load_plans_file (line 321) | def load_plans_file(self): method process_plans (line 329) | def process_plans(self, plans): method load_dataset (line 397) | def load_dataset(self): method get_basic_generators (line 400) | def get_basic_generators(self): method preprocess_patient (line 420) | def preprocess_patient(self, input_files): method preprocess_predict_nifti (line 448) | def preprocess_predict_nifti(self, input_files: List[str], output_file... method predict_preprocessed_data_return_seg_and_softmax (line 486) | def predict_preprocessed_data_return_seg_and_softmax(self, data: np.nd... method validate (line 529) | def validate(self, do_mirroring: bool = True, use_sliding_window: bool... method run_online_evaluation (line 693) | def run_online_evaluation(self, output, target): method finish_online_evaluation (line 717) | def finish_online_evaluation(self): method save_checkpoint (line 736) | def save_checkpoint(self, fname, save_optimizer=True): FILE: unetr_pp/training/network_training/network_trainer_acdc.py class NetworkTrainer_acdc (line 42) | class NetworkTrainer_acdc(object): method __init__ (line 43) | def __init__(self, deterministic=True, fp16=False): method initialize (line 130) | def initialize(self, training=True): method load_dataset (line 146) | def load_dataset(self): method do_split (line 149) | def do_split(self): method plot_progress (line 187) | def plot_progress(self): method print_to_log_file (line 248) | def print_to_log_file(self, *args, also_print_to_console=True, add_tim... method save_checkpoint (line 282) | def save_checkpoint(self, fname, save_optimizer=True): method load_best_checkpoint (line 314) | def load_best_checkpoint(self, train=True): method load_latest_checkpoint (line 324) | def load_latest_checkpoint(self, train=True): method load_final_checkpoint (line 333) | def load_final_checkpoint(self, train=False): method load_checkpoint (line 339) | def load_checkpoint(self, fname, train=True): method initialize_network (line 348) | def initialize_network(self): method initialize_optimizer_and_scheduler (line 356) | def initialize_optimizer_and_scheduler(self): method load_checkpoint_ram (line 363) | def load_checkpoint_ram(self, checkpoint, train=True): method _maybe_init_amp (line 427) | def _maybe_init_amp(self): method plot_network_architecture (line 431) | def plot_network_architecture(self): method run_training (line 439) | def run_training(self): method maybe_update_lr (line 529) | def maybe_update_lr(self): method maybe_save_checkpoint (line 542) | def maybe_save_checkpoint(self): method update_eval_criterion_MA (line 554) | def update_eval_criterion_MA(self): method manage_patience (line 580) | def manage_patience(self): method on_epoch_end (line 633) | def on_epoch_end(self): method update_train_loss_MA (line 648) | def update_train_loss_MA(self): method run_iteration (line 655) | def run_iteration(self, data_generator, do_backprop=True, run_online_e... method run_online_evaluation (line 695) | def run_online_evaluation(self, *args, **kwargs): method finish_online_evaluation (line 704) | def finish_online_evaluation(self): method validate (line 712) | def validate(self, *args, **kwargs): method find_lr (line 715) | def find_lr(self, num_iters=1000, init_value=1e-6, final_value=10., be... FILE: unetr_pp/training/network_training/network_trainer_lung.py class NetworkTrainer_lung (line 42) | class NetworkTrainer_lung(object): method __init__ (line 43) | def __init__(self, deterministic=True, fp16=False): method initialize (line 130) | def initialize(self, training=True): method load_dataset (line 146) | def load_dataset(self): method do_split (line 149) | def do_split(self): method plot_progress (line 187) | def plot_progress(self): method print_to_log_file (line 248) | def print_to_log_file(self, *args, also_print_to_console=True, add_tim... method save_checkpoint (line 282) | def save_checkpoint(self, fname, save_optimizer=True): method load_best_checkpoint (line 314) | def load_best_checkpoint(self, train=True): method load_latest_checkpoint (line 324) | def load_latest_checkpoint(self, train=True): method load_final_checkpoint (line 333) | def load_final_checkpoint(self, train=False): method load_checkpoint (line 339) | def load_checkpoint(self, fname, train=True): method initialize_network (line 348) | def initialize_network(self): method initialize_optimizer_and_scheduler (line 356) | def initialize_optimizer_and_scheduler(self): method load_checkpoint_ram (line 363) | def load_checkpoint_ram(self, checkpoint, train=True): method _maybe_init_amp (line 427) | def _maybe_init_amp(self): method plot_network_architecture (line 431) | def plot_network_architecture(self): method run_training (line 439) | def run_training(self): method maybe_update_lr (line 529) | def maybe_update_lr(self): method maybe_save_checkpoint (line 542) | def maybe_save_checkpoint(self): method update_eval_criterion_MA (line 554) | def update_eval_criterion_MA(self): method manage_patience (line 580) | def manage_patience(self): method on_epoch_end (line 633) | def on_epoch_end(self): method update_train_loss_MA (line 648) | def update_train_loss_MA(self): method run_iteration (line 655) | def run_iteration(self, data_generator, do_backprop=True, run_online_e... method run_online_evaluation (line 695) | def run_online_evaluation(self, *args, **kwargs): method finish_online_evaluation (line 704) | def finish_online_evaluation(self): method validate (line 712) | def validate(self, *args, **kwargs): method find_lr (line 715) | def find_lr(self, num_iters=1000, init_value=1e-6, final_value=10., be... FILE: unetr_pp/training/network_training/network_trainer_synapse.py class NetworkTrainer_synapse (line 43) | class NetworkTrainer_synapse(object): method __init__ (line 44) | def __init__(self, deterministic=True, fp16=False): method initialize (line 131) | def initialize(self, training=True): method load_dataset (line 147) | def load_dataset(self): method do_split (line 150) | def do_split(self): method plot_progress (line 188) | def plot_progress(self): method print_to_log_file (line 249) | def print_to_log_file(self, *args, also_print_to_console=True, add_tim... method save_checkpoint (line 283) | def save_checkpoint(self, fname, save_optimizer=True): method load_best_checkpoint (line 315) | def load_best_checkpoint(self, train=True): method load_latest_checkpoint (line 325) | def load_latest_checkpoint(self, train=True): method load_final_checkpoint (line 334) | def load_final_checkpoint(self, train=False): method load_checkpoint (line 340) | def load_checkpoint(self, fname, train=True): method initialize_network (line 349) | def initialize_network(self): method initialize_optimizer_and_scheduler (line 357) | def initialize_optimizer_and_scheduler(self): method load_checkpoint_ram (line 364) | def load_checkpoint_ram(self, checkpoint, train=True): method _maybe_init_amp (line 428) | def _maybe_init_amp(self): method plot_network_architecture (line 432) | def plot_network_architecture(self): method run_training (line 440) | def run_training(self): method maybe_update_lr (line 530) | def maybe_update_lr(self): method maybe_save_checkpoint (line 543) | def maybe_save_checkpoint(self): method update_eval_criterion_MA (line 555) | def update_eval_criterion_MA(self): method manage_patience (line 581) | def manage_patience(self): method on_epoch_end (line 634) | def on_epoch_end(self): method update_train_loss_MA (line 649) | def update_train_loss_MA(self): method run_iteration (line 656) | def run_iteration(self, data_generator, do_backprop=True, run_online_e... method run_online_evaluation (line 696) | def run_online_evaluation(self, *args, **kwargs): method finish_online_evaluation (line 705) | def finish_online_evaluation(self): method validate (line 713) | def validate(self, *args, **kwargs): method find_lr (line 716) | def find_lr(self, num_iters=1000, init_value=1e-6, final_value=10., be... FILE: unetr_pp/training/network_training/network_trainer_tumor.py class NetworkTrainer_tumor (line 42) | class NetworkTrainer_tumor(object): method __init__ (line 43) | def __init__(self, deterministic=True, fp16=False): method initialize (line 129) | def initialize(self, training=True): method load_dataset (line 141) | def load_dataset(self): method do_split (line 144) | def do_split(self): method plot_progress (line 182) | def plot_progress(self): method print_to_log_file (line 238) | def print_to_log_file(self, *args, also_print_to_console=True, add_tim... method save_checkpoint (line 272) | def save_checkpoint(self, fname, save_optimizer=True): method load_best_checkpoint (line 304) | def load_best_checkpoint(self, train=True): method load_latest_checkpoint (line 314) | def load_latest_checkpoint(self, train=True): method load_final_checkpoint (line 323) | def load_final_checkpoint(self, train=False): method load_checkpoint (line 329) | def load_checkpoint(self, fname, train=True): method initialize_network (line 338) | def initialize_network(self): method initialize_optimizer_and_scheduler (line 346) | def initialize_optimizer_and_scheduler(self): method load_checkpoint_ram (line 353) | def load_checkpoint_ram(self, checkpoint, train=True): method _maybe_init_amp (line 417) | def _maybe_init_amp(self): method plot_network_architecture (line 421) | def plot_network_architecture(self): method run_training (line 429) | def run_training(self): method maybe_update_lr (line 519) | def maybe_update_lr(self): method maybe_save_checkpoint (line 532) | def maybe_save_checkpoint(self): method update_eval_criterion_MA (line 544) | def update_eval_criterion_MA(self): method manage_patience (line 570) | def manage_patience(self): method on_epoch_end (line 623) | def on_epoch_end(self): method update_train_loss_MA (line 638) | def update_train_loss_MA(self): method run_iteration (line 645) | def run_iteration(self, data_generator, do_backprop=True, run_online_e... method run_online_evaluation (line 685) | def run_online_evaluation(self, *args, **kwargs): method finish_online_evaluation (line 694) | def finish_online_evaluation(self): method validate (line 702) | def validate(self, *args, **kwargs): method find_lr (line 705) | def find_lr(self, num_iters=1000, init_value=1e-6, final_value=10., be... FILE: unetr_pp/training/network_training/unetr_pp_trainer_acdc.py class unetr_pp_trainer_acdc (line 40) | class unetr_pp_trainer_acdc(Trainer_acdc): method __init__ (line 45) | def __init__(self, plans_file, fold, output_folder=None, dataset_direc... method initialize (line 76) | def initialize(self, training=True, force_load_plans=False): method initialize_network (line 159) | def initialize_network(self): method initialize_optimizer_and_scheduler (line 193) | def initialize_optimizer_and_scheduler(self): method run_online_evaluation (line 199) | def run_online_evaluation(self, output, target): method validate (line 215) | def validate(self, do_mirroring: bool = True, use_sliding_window: bool... method predict_preprocessed_data_return_seg_and_softmax (line 233) | def predict_preprocessed_data_return_seg_and_softmax(self, data: np.nd... method run_iteration (line 257) | def run_iteration(self, data_generator, do_backprop=True, run_online_e... method do_split (line 309) | def do_split(self): method setup_DA_params (line 431) | def setup_DA_params(self): method maybe_update_lr (line 485) | def maybe_update_lr(self, epoch=None): method on_epoch_end (line 502) | def on_epoch_end(self): method run_training (line 522) | def run_training(self): FILE: unetr_pp/training/network_training/unetr_pp_trainer_lung.py class unetr_pp_trainer_lung (line 40) | class unetr_pp_trainer_lung(Trainer_lung): method __init__ (line 45) | def __init__(self, plans_file, fold, output_folder=None, dataset_direc... method initialize (line 77) | def initialize(self, training=True, force_load_plans=False): method initialize_network (line 160) | def initialize_network(self): method initialize_optimizer_and_scheduler (line 194) | def initialize_optimizer_and_scheduler(self): method run_online_evaluation (line 200) | def run_online_evaluation(self, output, target): method validate (line 216) | def validate(self, do_mirroring: bool = True, use_sliding_window: bool... method predict_preprocessed_data_return_seg_and_softmax (line 234) | def predict_preprocessed_data_return_seg_and_softmax(self, data: np.nd... method run_iteration (line 258) | def run_iteration(self, data_generator, do_backprop=True, run_online_e... method do_split (line 311) | def do_split(self): method setup_DA_params (line 391) | def setup_DA_params(self): method maybe_update_lr (line 445) | def maybe_update_lr(self, epoch=None): method on_epoch_end (line 462) | def on_epoch_end(self): method run_training (line 482) | def run_training(self): FILE: unetr_pp/training/network_training/unetr_pp_trainer_synapse.py class unetr_pp_trainer_synapse (line 40) | class unetr_pp_trainer_synapse(Trainer_synapse): method __init__ (line 45) | def __init__(self, plans_file, fold, output_folder=None, dataset_direc... method initialize (line 70) | def initialize(self, training=True, force_load_plans=False): method initialize_network (line 150) | def initialize_network(self): method initialize_optimizer_and_scheduler (line 185) | def initialize_optimizer_and_scheduler(self): method run_online_evaluation (line 191) | def run_online_evaluation(self, output, target): method validate (line 207) | def validate(self, do_mirroring: bool = True, use_sliding_window: bool... method predict_preprocessed_data_return_seg_and_softmax (line 225) | def predict_preprocessed_data_return_seg_and_softmax(self, data: np.nd... method run_iteration (line 249) | def run_iteration(self, data_generator, do_backprop=True, run_online_e... method do_split (line 301) | def do_split(self): method setup_DA_params (line 373) | def setup_DA_params(self): method maybe_update_lr (line 427) | def maybe_update_lr(self, epoch=None): method on_epoch_end (line 444) | def on_epoch_end(self): method run_training (line 464) | def run_training(self): FILE: unetr_pp/training/network_training/unetr_pp_trainer_tumor.py class unetr_pp_trainer_tumor (line 40) | class unetr_pp_trainer_tumor(Trainer_tumor): method __init__ (line 45) | def __init__(self, plans_file, fold, output_folder=None, dataset_direc... method initialize (line 78) | def initialize(self, training=True, force_load_plans=False): method initialize_network (line 158) | def initialize_network(self): method initialize_optimizer_and_scheduler (line 193) | def initialize_optimizer_and_scheduler(self): method run_online_evaluation (line 199) | def run_online_evaluation(self, output, target): method validate (line 215) | def validate(self, do_mirroring: bool = True, use_sliding_window: bool... method predict_preprocessed_data_return_seg_and_softmax (line 233) | def predict_preprocessed_data_return_seg_and_softmax(self, data: np.nd... method run_iteration (line 257) | def run_iteration(self, data_generator, do_backprop=True, run_online_e... method do_split (line 309) | def do_split(self): method setup_DA_params (line 468) | def setup_DA_params(self): method maybe_update_lr (line 522) | def maybe_update_lr(self, epoch=None): method on_epoch_end (line 539) | def on_epoch_end(self): method run_training (line 559) | def run_training(self): FILE: unetr_pp/training/optimizer/ranger.py class Ranger (line 11) | class Ranger(Optimizer): method __init__ (line 13) | def __init__(self, params, lr=1e-3, alpha=0.5, k=6, N_sma_threshhold=5... method __setstate__ (line 64) | def __setstate__(self, state): method step (line 68) | def step(self, closure=None): FILE: unetr_pp/utilities/distributed.py function print_if_rank0 (line 22) | def print_if_rank0(*args): class awesome_allgather_function (line 27) | class awesome_allgather_function(autograd.Function): method forward (line 29) | def forward(ctx, input): method backward (line 39) | def backward(ctx, grad_output): FILE: unetr_pp/utilities/file_conversions.py function convert_2d_image_to_nifti (line 8) | def convert_2d_image_to_nifti(input_filename: str, output_filename_trunc... function convert_3d_tiff_to_nifti (line 63) | def convert_3d_tiff_to_nifti(filenames: List[str], output_name: str, spa... function convert_2d_segmentation_nifti_to_img (line 99) | def convert_2d_segmentation_nifti_to_img(nifti_file: str, output_filenam... function convert_3d_segmentation_nifti_to_tiff (line 109) | def convert_3d_segmentation_nifti_to_tiff(nifti_file: str, output_filena... FILE: unetr_pp/utilities/file_endings.py function remove_trailing_slash (line 19) | def remove_trailing_slash(filename: str): function maybe_add_0000_to_all_niigz (line 25) | def maybe_add_0000_to_all_niigz(folder): FILE: unetr_pp/utilities/folder_names.py function get_output_folder_name (line 20) | def get_output_folder_name(model: str, task: str = None, trainer: str = ... FILE: unetr_pp/utilities/one_hot_encoding.py function to_one_hot (line 18) | def to_one_hot(seg, all_seg_labels=None): FILE: unetr_pp/utilities/overlay_plots.py function hex_to_rgb (line 41) | def hex_to_rgb(hex: str): function generate_overlay (line 46) | def generate_overlay(input_image: np.ndarray, segmentation: np.ndarray, ... function plot_overlay (line 89) | def plot_overlay(image_file: str, segmentation_file: str, output_file: s... function plot_overlay_preprocessed (line 108) | def plot_overlay_preprocessed(case_file: str, output_file: str, overlay_... function multiprocessing_plot_overlay (line 127) | def multiprocessing_plot_overlay(list_of_image_files, list_of_seg_files,... function multiprocessing_plot_overlay_preprocessed (line 138) | def multiprocessing_plot_overlay_preprocessed(list_of_case_files, list_o... function generate_overlays_for_task (line 150) | def generate_overlays_for_task(task_name_or_id, output_folder, num_proce... function entry_point_generate_overlay (line 191) | def entry_point_generate_overlay(): FILE: unetr_pp/utilities/random_stuff.py class no_op (line 16) | class no_op(object): method __enter__ (line 17) | def __enter__(self): method __exit__ (line 20) | def __exit__(self, *args): FILE: unetr_pp/utilities/recursive_delete_npz.py function recursive_delete_npz (line 21) | def recursive_delete_npz(current_directory: str): FILE: unetr_pp/utilities/recursive_rename_taskXX_to_taskXXX.py function recursive_rename (line 20) | def recursive_rename(folder): FILE: unetr_pp/utilities/sitk_stuff.py function copy_geometry (line 19) | def copy_geometry(image: sitk.Image, ref: sitk.Image): FILE: unetr_pp/utilities/task_name_id_conversion.py function convert_id_to_task_name (line 21) | def convert_id_to_task_name(task_id: int): function convert_task_name_to_id (line 64) | def convert_task_name_to_id(task_name: str): FILE: unetr_pp/utilities/tensor_utilities.py function sum_tensor (line 20) | def sum_tensor(inp, axes, keepdim=False): function mean_tensor (line 31) | def mean_tensor(inp, axes, keepdim=False): function flip (line 42) | def flip(x, dim): FILE: unetr_pp/utilities/to_torch.py function maybe_to_torch (line 18) | def maybe_to_torch(d): function to_cuda (line 26) | def to_cuda(data, non_blocking=True, gpu_id=0):