SYMBOL INDEX (1687 symbols across 165 files)

FILE: reference_code/GSNet-release/demo/demo.py
  function setup_cfg (line 20) | def setup_cfg(args):
  function get_parser (line 34) | def get_parser():

FILE: reference_code/GSNet-release/demo/predictor.py
  class VisualizationDemo (line 20) | class VisualizationDemo(object):
    method __init__ (line 21) | def __init__(self, cfg, instance_mode=ColorMode.IMAGE, parallel=False):
    method run_on_image (line 42) | def run_on_image(self, image, save_name):
    method _frame_from_video (line 138) | def _frame_from_video(self, video):
    method run_on_video (line 146) | def run_on_video(self, video):
  class AsyncPredictor (line 202) | class AsyncPredictor:
    class _StopToken (line 209) | class _StopToken:
    class _PredictWorker (line 212) | class _PredictWorker(mp.Process):
      method __init__ (line 213) | def __init__(self, cfg, task_queue, result_queue):
      method run (line 219) | def run(self):
    method __init__ (line 230) | def __init__(self, cfg, num_gpus: int = 1):
    method put (line 257) | def put(self, image):
    method get (line 261) | def get(self):
    method __len__ (line 277) | def __len__(self):
    method __call__ (line 280) | def __call__(self, image):
    method shutdown (line 284) | def shutdown(self):
    method default_buffer_size (line 289) | def default_buffer_size(self):

FILE: reference_code/GSNet-release/detectron2/checkpoint/c2_model_loading.py
  function convert_basic_c2_names (line 12) | def convert_basic_c2_names(original_keys):
  function convert_c2_detectron_names (line 68) | def convert_c2_detectron_names(weights):
  function align_and_update_state_dicts (line 211) | def align_and_update_state_dicts(model_state_dict, ckpt_state_dict, c2_c...

FILE: reference_code/GSNet-release/detectron2/checkpoint/catalog.py
  class ModelCatalog (line 6) | class ModelCatalog(object):
    method get (line 55) | def get(name):
    method _get_c2_imagenet_pretrained (line 63) | def _get_c2_imagenet_pretrained(name):
    method _get_c2_detectron_baseline (line 71) | def _get_c2_detectron_baseline(name):
  class ModelCatalogHandler (line 92) | class ModelCatalogHandler(PathHandler):
    method _get_supported_prefixes (line 99) | def _get_supported_prefixes(self):
    method _get_local_path (line 102) | def _get_local_path(self, path):
    method _open (line 108) | def _open(self, path, mode="r", **kwargs):
  class Detectron2Handler (line 112) | class Detectron2Handler(PathHandler):
    method _get_supported_prefixes (line 120) | def _get_supported_prefixes(self):
    method _get_local_path (line 123) | def _get_local_path(self, path):
    method _open (line 127) | def _open(self, path, mode="r", **kwargs):

FILE: reference_code/GSNet-release/detectron2/checkpoint/detection_checkpoint.py
  class DetectionCheckpointer (line 11) | class DetectionCheckpointer(Checkpointer):
    method __init__ (line 17) | def __init__(self, model, save_dir="", *, save_to_disk=None, **checkpo...
    method _load_file (line 26) | def _load_file(self, filename):
    method _load_model (line 47) | def _load_model(self, checkpoint):

FILE: reference_code/GSNet-release/detectron2/config/compat.py
  function upgrade_config (line 33) | def upgrade_config(cfg: CN, to_version: Optional[int] = None) -> CN:
  function downgrade_config (line 55) | def downgrade_config(cfg: CN, to_version: int) -> CN:
  function guess_version (line 82) | def guess_version(cfg: CN, filename: str) -> int:
  function _rename (line 116) | def _rename(cfg: CN, old: str, new: str) -> None:
  class _RenameConverter (line 146) | class _RenameConverter:
    method upgrade (line 154) | def upgrade(cls, cfg: CN) -> None:
    method downgrade (line 159) | def downgrade(cls, cfg: CN) -> None:
  class ConverterV1 (line 164) | class ConverterV1(_RenameConverter):
  class ConverterV2 (line 168) | class ConverterV2(_RenameConverter):
    method upgrade (line 204) | def upgrade(cls, cfg: CN) -> None:
    method downgrade (line 222) | def downgrade(cls, cfg: CN) -> None:

FILE: reference_code/GSNet-release/detectron2/config/config.py
  class CfgNode (line 8) | class CfgNode(_CfgNode):
    method merge_from_file (line 21) | def merge_from_file(self, cfg_filename: str, allow_unsafe: bool = True...
    method dump (line 63) | def dump(self, *args, **kwargs):
  function get_cfg (line 75) | def get_cfg() -> CfgNode:
  function set_global_cfg (line 87) | def set_global_cfg(cfg: CfgNode) -> None:

FILE: reference_code/GSNet-release/detectron2/data/build.py
  function filter_images_with_only_crowd_annotations (line 38) | def filter_images_with_only_crowd_annotations(dataset_dicts):
  function filter_images_with_few_keypoints (line 69) | def filter_images_with_few_keypoints(dataset_dicts, min_keypoints_per_im...
  function load_proposals_into_dataset (line 103) | def load_proposals_into_dataset(dataset_dicts, proposal_file):
  function _quantize (line 157) | def _quantize(x, bin_edges):
  function print_instances_class_histogram (line 164) | def print_instances_class_histogram(dataset_dicts, class_names):
  function get_detection_dataset_dicts (line 211) | def get_detection_dataset_dicts(
  function build_detection_train_loader (line 266) | def build_detection_train_loader(cfg, mapper=None):
  function build_detection_test_loader (line 353) | def build_detection_test_loader(cfg, dataset_name, mapper=None):
  function trivial_batch_collator (line 399) | def trivial_batch_collator(batch):
  function worker_init_reset_seed (line 406) | def worker_init_reset_seed(worker_id):

FILE: reference_code/GSNet-release/detectron2/data/catalog.py
  class DatasetCatalog (line 12) | class DatasetCatalog(object):
    method register (line 31) | def register(name, func):
    method get (line 44) | def get(name):
    method list (line 65) | def list() -> List[str]:
    method clear (line 75) | def clear():
  class Metadata (line 82) | class Metadata(types.SimpleNamespace):
    method __getattr__ (line 108) | def __getattr__(self, key):
    method __setattr__ (line 123) | def __setattr__(self, key, val):
    method as_dict (line 143) | def as_dict(self):
    method set (line 150) | def set(self, **kwargs):
    method get (line 158) | def get(self, key, default=None):
  class MetadataCatalog (line 169) | class MetadataCatalog:
    method get (line 184) | def get(name):
    method list (line 215) | def list():

FILE: reference_code/GSNet-release/detectron2/data/common.py
  class MapDataset (line 14) | class MapDataset(data.Dataset):
    method __init__ (line 26) | def __init__(self, dataset, map_func):
    method __len__ (line 33) | def __len__(self):
    method __getitem__ (line 36) | def __getitem__(self, idx):
  class DatasetFromList (line 60) | class DatasetFromList(data.Dataset):
    method __init__ (line 65) | def __init__(self, lst: list, copy: bool = True, serialize: bool = True):
    method __len__ (line 97) | def __len__(self):
    method __getitem__ (line 103) | def __getitem__(self, idx):
  class AspectRatioGroupedDataset (line 115) | class AspectRatioGroupedDataset(data.IterableDataset):
    method __init__ (line 126) | def __init__(self, dataset, batch_size):
    method __iter__ (line 139) | def __iter__(self):

FILE: reference_code/GSNet-release/detectron2/data/dataset_mapper.py
  class DatasetMapper (line 19) | class DatasetMapper:
    method __init__ (line 36) | def __init__(self, cfg, is_train=True):
    method __call__ (line 68) | def __call__(self, dataset_dict):

FILE: reference_code/GSNet-release/detectron2/data/datasets/builtin.py
  function register_all_coco (line 109) | def register_all_coco(root):
  function register_all_lvis (line 155) | def register_all_lvis(root):
  function register_all_cityscapes (line 177) | def register_all_cityscapes(root):
  function register_all_pascal_voc (line 204) | def register_all_pascal_voc(root):

FILE: reference_code/GSNet-release/detectron2/data/datasets/builtin_meta.py
  function _get_coco_instances_meta (line 191) | def _get_coco_instances_meta():
  function _get_coco_panoptic_separated_meta (line 206) | def _get_coco_panoptic_separated_meta():
  function _get_builtin_metadata (line 239) | def _get_builtin_metadata(dataset_name):

FILE: reference_code/GSNet-release/detectron2/data/datasets/cityscapes.py
  function get_cityscapes_files (line 28) | def get_cityscapes_files(image_dir, gt_dir):
  function load_cityscapes_instances (line 54) | def load_cityscapes_instances(image_dir, gt_dir, from_json=True, to_poly...
  function load_cityscapes_semantic (line 96) | def load_cityscapes_semantic(image_dir, gt_dir):
  function cityscapes_files_to_dict (line 132) | def cityscapes_files_to_dict(files, from_json, to_polygons):

FILE: reference_code/GSNet-release/detectron2/data/datasets/coco.py
  function load_coco_json_eval (line 27) | def load_coco_json_eval(json_file, image_root, dataset_name=None, extra_...
  function load_coco_json (line 198) | def load_coco_json(json_file, image_root, dataset_name=None, extra_annot...
  function load_sem_seg (line 374) | def load_sem_seg(gt_root, image_root, gt_ext="png", image_ext="jpg"):
  function convert_to_coco_dict (line 450) | def convert_to_coco_dict(dataset_name):
  function convert_to_coco_json (line 578) | def convert_to_coco_json(dataset_name, output_file, allow_cached=True):

FILE: reference_code/GSNet-release/detectron2/data/datasets/lvis.py
  function register_lvis_instances (line 23) | def register_lvis_instances(name, metadata, json_file, image_root):
  function load_lvis_json (line 39) | def load_lvis_json(json_file, image_root, dataset_name=None):
  function get_lvis_instances_meta (line 148) | def get_lvis_instances_meta(dataset_name):
  function _get_lvis_instances_meta_v0_5 (line 168) | def _get_lvis_instances_meta_v0_5():

FILE: reference_code/GSNet-release/detectron2/data/datasets/pascal_voc.py
  function load_voc_instances (line 24) | def load_voc_instances(dirname: str, split: str):
  function register_pascal_voc (line 76) | def register_pascal_voc(name, dirname, split, year):

FILE: reference_code/GSNet-release/detectron2/data/datasets/process_dataset.py
  function bb_intersection_over_union (line 35) | def bb_intersection_over_union(boxA, boxB):
  function load_coco_json (line 54) | def load_coco_json(json_file, image_root, dataset_name=None, extra_annot...
  function load_sem_seg (line 321) | def load_sem_seg(gt_root, image_root, gt_ext="png", image_ext="jpg"):
  function convert_to_coco_dict (line 397) | def convert_to_coco_dict(dataset_dicts, dataset_name):
  function convert_to_coco_json (line 530) | def convert_to_coco_json(dataset_name, output_file, allow_cached=True):

FILE: reference_code/GSNet-release/detectron2/data/datasets/process_dataset_occ.py
  function bb_intersection_over_union (line 30) | def bb_intersection_over_union(boxA, boxB):
  function load_coco_json (line 49) | def load_coco_json(json_file, image_root, dataset_name=None, extra_annot...
  function load_sem_seg (line 234) | def load_sem_seg(gt_root, image_root, gt_ext="png", image_ext="jpg"):
  function convert_to_coco_dict (line 310) | def convert_to_coco_dict(dataset_dicts, dataset_name):
  function convert_to_coco_json (line 437) | def convert_to_coco_json(dataset_name, output_file, allow_cached=True):

FILE: reference_code/GSNet-release/detectron2/data/datasets/register_coco.py
  function register_coco_instances (line 15) | def register_coco_instances(name, metadata, json_file, image_root):
  function register_coco_panoptic_separated (line 46) | def register_coco_panoptic_separated(
  function merge_to_panoptic (line 107) | def merge_to_panoptic(detection_dicts, sem_seg_dicts):

FILE: reference_code/GSNet-release/detectron2/data/detection_utils.py
  class SizeMismatchError (line 30) | class SizeMismatchError(ValueError):
  function read_image (line 36) | def read_image(file_name, format=None):
  function check_image_size (line 82) | def check_image_size(dataset_dict, image):
  function transform_proposals (line 107) | def transform_proposals(dataset_dict, image_shape, transforms, min_box_s...
  function transform_instance_annotations (line 149) | def transform_instance_annotations(
  function transform_keypoint_annotations (line 226) | def transform_keypoint_annotations(keypoints, transforms, image_size, ke...
  function annotations_to_instances (line 261) | def annotations_to_instances(annos, image_size, mask_format="polygon"):
  function annotations_to_instances_rotated (line 339) | def annotations_to_instances_rotated(annos, image_size):
  function filter_empty_instances (line 368) | def filter_empty_instances(instances, by_box=True, by_mask=True):
  function create_keypoint_hflip_indices (line 397) | def create_keypoint_hflip_indices(dataset_names):
  function gen_crop_transform_with_instance (line 419) | def gen_crop_transform_with_instance(crop_size, image_size, instance):
  function check_metadata_consistency (line 449) | def check_metadata_consistency(key, dataset_names):
  function build_transform_gen (line 478) | def build_transform_gen(cfg, is_train):

FILE: reference_code/GSNet-release/detectron2/data/samplers/distributed_sampler.py
  class TrainingSampler (line 12) | class TrainingSampler(Sampler):
    method __init__ (line 24) | def __init__(self, size: int, shuffle: bool = True, seed: Optional[int...
    method __iter__ (line 43) | def __iter__(self):
    method _infinite_indices (line 47) | def _infinite_indices(self):
  class RepeatFactorTrainingSampler (line 57) | class RepeatFactorTrainingSampler(Sampler):
    method __init__ (line 69) | def __init__(self, dataset_dicts, repeat_thresh, shuffle=True, seed=No...
    method _get_repeat_factors (line 93) | def _get_repeat_factors(self, dataset_dicts, repeat_thresh):
    method _get_epoch_indices (line 131) | def _get_epoch_indices(self, generator):
    method __iter__ (line 154) | def __iter__(self):
    method _infinite_indices (line 158) | def _infinite_indices(self):
  class InferenceSampler (line 172) | class InferenceSampler(Sampler):
    method __init__ (line 180) | def __init__(self, size: int):
    method __iter__ (line 195) | def __iter__(self):
    method __len__ (line 198) | def __len__(self):

FILE: reference_code/GSNet-release/detectron2/data/samplers/grouped_batch_sampler.py
  class GroupedBatchSampler (line 6) | class GroupedBatchSampler(BatchSampler):
    method __init__ (line 14) | def __init__(self, sampler, group_ids, batch_size):
    method __iter__ (line 37) | def __iter__(self):
    method __len__ (line 46) | def __len__(self):

FILE: reference_code/GSNet-release/detectron2/data/transforms/transform.py
  class ExtentTransform (line 12) | class ExtentTransform(Transform):
    method __init__ (line 22) | def __init__(self, src_rect, output_size, interp=Image.LINEAR, fill=0):
    method apply_image (line 33) | def apply_image(self, img, interp=None):
    method apply_coords (line 44) | def apply_coords(self, coords):
    method apply_segmentation (line 58) | def apply_segmentation(self, segmentation):
  class ResizeTransform (line 63) | class ResizeTransform(Transform):
    method __init__ (line 68) | def __init__(self, h, w, new_h, new_w, interp):
    method apply_image (line 79) | def apply_image(self, img, interp=None):
    method apply_coords (line 87) | def apply_coords(self, coords):
    method apply_segmentation (line 92) | def apply_segmentation(self, segmentation):
  function HFlip_rotated_box (line 97) | def HFlip_rotated_box(transform, rotated_boxes):
  function Resize_rotated_box (line 113) | def Resize_rotated_box(transform, rotated_boxes):

FILE: reference_code/GSNet-release/detectron2/data/transforms/transform_gen.py
  function check_dtype (line 38) | def check_dtype(img):
  class TransformGen (line 50) | class TransformGen(metaclass=ABCMeta):
    method _init (line 66) | def _init(self, params=None):
    method get_transform (line 73) | def get_transform(self, img):
    method _rand_range (line 76) | def _rand_range(self, low=1.0, high=None, size=None):
    method __repr__ (line 86) | def __repr__(self):
  class RandomFlip (line 115) | class RandomFlip(TransformGen):
    method __init__ (line 120) | def __init__(self, prob=0.5, *, horizontal=True, vertical=False):
    method get_transform (line 135) | def get_transform(self, img):
  class Resize (line 147) | class Resize(TransformGen):
    method __init__ (line 150) | def __init__(self, shape, interp=Image.BILINEAR):
    method get_transform (line 161) | def get_transform(self, img):
  class ResizeShortestEdge (line 169) | class ResizeShortestEdge(TransformGen):
    method __init__ (line 175) | def __init__(
    method get_transform (line 194) | def get_transform(self, img):
  class RandomCrop (line 221) | class RandomCrop(TransformGen):
    method __init__ (line 226) | def __init__(self, crop_type: str, crop_size):
    method get_transform (line 238) | def get_transform(self, img):
    method get_crop_size (line 246) | def get_crop_size(self, image_size):
  class RandomExtent (line 268) | class RandomExtent(TransformGen):
    method __init__ (line 277) | def __init__(self, scale_range, shift_range):
    method get_transform (line 290) | def get_transform(self, img):
  class RandomContrast (line 313) | class RandomContrast(TransformGen):
    method __init__ (line 325) | def __init__(self, intensity_min, intensity_max):
    method get_transform (line 334) | def get_transform(self, img):
  class RandomBrightness (line 339) | class RandomBrightness(TransformGen):
    method __init__ (line 351) | def __init__(self, intensity_min, intensity_max):
    method get_transform (line 360) | def get_transform(self, img):
  class RandomSaturation (line 365) | class RandomSaturation(TransformGen):
    method __init__ (line 377) | def __init__(self, intensity_min, intensity_max):
    method get_transform (line 386) | def get_transform(self, img):
  class RandomLighting (line 393) | class RandomLighting(TransformGen):
    method __init__ (line 401) | def __init__(self, scale):
    method get_transform (line 413) | def get_transform(self, img):
  function apply_transform_gens (line 421) | def apply_transform_gens(transform_gens, img):

FILE: reference_code/GSNet-release/detectron2/engine/defaults.py
  function default_argument_parser (line 48) | def default_argument_parser():
  function default_setup (line 83) | def default_setup(cfg, args):
  class DefaultPredictor (line 132) | class DefaultPredictor:
    method __init__ (line 155) | def __init__(self, cfg):
    method __call__ (line 171) | def __call__(self, original_image):
  class DefaultTrainer (line 194) | class DefaultTrainer(SimpleTrainer):
    method __init__ (line 236) | def __init__(self, cfg):
    method resume_or_load (line 272) | def resume_or_load(self, resume=True):
    method build_hooks (line 292) | def build_hooks(self):
    method build_writers (line 340) | def build_writers(self):
    method train (line 370) | def train(self):
    method build_model (line 383) | def build_model(cls, cfg):
    method build_optimizer (line 397) | def build_optimizer(cls, cfg, model):
    method build_lr_scheduler (line 408) | def build_lr_scheduler(cls, cfg, optimizer):
    method build_train_loader (line 416) | def build_train_loader(cls, cfg):
    method build_test_loader (line 427) | def build_test_loader(cls, cfg, dataset_name):
    method build_evaluator (line 438) | def build_evaluator(cls, cfg, dataset_name):
    method test (line 451) | def test(cls, cfg, model, evaluators=None):

FILE: reference_code/GSNet-release/detectron2/engine/hooks.py
  class CallbackHook (line 40) | class CallbackHook(HookBase):
    method __init__ (line 45) | def __init__(self, *, before_train=None, after_train=None, before_step...
    method before_train (line 54) | def before_train(self):
    method after_train (line 58) | def after_train(self):
    method before_step (line 66) | def before_step(self):
    method after_step (line 70) | def after_step(self):
  class IterationTimer (line 75) | class IterationTimer(HookBase):
    method __init__ (line 87) | def __init__(self, warmup_iter=3):
    method before_train (line 96) | def before_train(self):
    method after_train (line 101) | def after_train(self):
    method before_step (line 127) | def before_step(self):
    method after_step (line 131) | def after_step(self):
  class PeriodicWriter (line 144) | class PeriodicWriter(HookBase):
    method __init__ (line 151) | def __init__(self, writers, period=20):
    method after_step (line 162) | def after_step(self):
    method after_train (line 169) | def after_train(self):
  class PeriodicCheckpointer (line 174) | class PeriodicCheckpointer(_PeriodicCheckpointer, HookBase):
    method before_train (line 185) | def before_train(self):
    method after_step (line 188) | def after_step(self):
  class LRScheduler (line 193) | class LRScheduler(HookBase):
    method __init__ (line 199) | def __init__(self, optimizer, scheduler):
    method after_step (line 227) | def after_step(self):
  class AutogradProfiler (line 233) | class AutogradProfiler(HookBase):
    method __init__ (line 258) | def __init__(self, enable_predicate, output_dir, *, use_cuda=True):
    method before_step (line 271) | def before_step(self):
    method after_step (line 278) | def after_step(self):
  class EvalHook (line 298) | class EvalHook(HookBase):
    method __init__ (line 305) | def __init__(self, eval_period, eval_function):
    method _do_eval (line 321) | def _do_eval(self):
    method after_step (line 344) | def after_step(self):
    method after_train (line 352) | def after_train(self):
  class PreciseBN (line 360) | class PreciseBN(HookBase):
    method __init__ (line 370) | def __init__(self, period, model, data_loader, num_iter):
    method after_step (line 399) | def after_step(self):
    method update_stats (line 405) | def update_stats(self):

FILE: reference_code/GSNet-release/detectron2/engine/launch.py
  function _find_free_port (line 12) | def _find_free_port():
  function launch (line 24) | def launch(main_func, num_gpus_per_machine, num_machines=1, machine_rank...
  function _distributed_worker (line 55) | def _distributed_worker(

FILE: reference_code/GSNet-release/detectron2/engine/train_loop.py
  class HookBase (line 16) | class HookBase:
    method before_train (line 51) | def before_train(self):
    method after_train (line 57) | def after_train(self):
    method before_step (line 63) | def before_step(self):
    method after_step (line 69) | def after_step(self):
  class TrainerBase (line 76) | class TrainerBase:
    method __init__ (line 95) | def __init__(self):
    method register_hooks (line 98) | def register_hooks(self, hooks):
    method train (line 116) | def train(self, start_iter: int, max_iter: int):
    method before_train (line 137) | def before_train(self):
    method after_train (line 141) | def after_train(self):
    method before_step (line 145) | def before_step(self):
    method after_step (line 149) | def after_step(self):
    method run_step (line 155) | def run_step(self):
  class SimpleTrainer (line 159) | class SimpleTrainer(TrainerBase):
    method __init__ (line 174) | def __init__(self, model, data_loader, optimizer):
    method run_step (line 197) | def run_step(self):
    method _detect_anomaly (line 233) | def _detect_anomaly(self, losses, loss_dict):
    method _write_metrics (line 241) | def _write_metrics(self, metrics_dict: dict):

FILE: reference_code/GSNet-release/detectron2/evaluation/cityscapes_evaluation.py
  class CityscapesEvaluator (line 17) | class CityscapesEvaluator(DatasetEvaluator):
    method __init__ (line 27) | def __init__(self, dataset_name):
    method reset (line 38) | def reset(self):
    method process (line 50) | def process(self, inputs, outputs):
    method evaluate (line 74) | def evaluate(self):

FILE: reference_code/GSNet-release/detectron2/evaluation/coco_evaluation.py
  class COCOEvaluator (line 28) | class COCOEvaluator(DatasetEvaluator):
    method __init__ (line 34) | def __init__(self, dataset_name, cfg, distributed, output_dir=None):
    method reset (line 83) | def reset(self):
    method _tasks_from_config (line 86) | def _tasks_from_config(self, cfg):
    method process (line 98) | def process(self, inputs, outputs):
    method evaluate (line 118) | def evaluate(self):
    method _eval_predictions (line 147) | def _eval_predictions(self, tasks, predictions):
    method _eval_box_proposals (line 203) | def _eval_box_proposals(self, predictions):
    method _derive_coco_results (line 242) | def _derive_coco_results(self, coco_eval, iou_type, class_names=None):
  function instances_to_coco_json (line 311) | def instances_to_coco_json(instances, img_id):
  function _evaluate_box_proposals (line 380) | def _evaluate_box_proposals(dataset_predictions, coco_api, thresholds=No...
  function _evaluate_predictions_on_coco (line 491) | def _evaluate_predictions_on_coco(coco_gt, coco_results, iou_type, kpt_o...

FILE: reference_code/GSNet-release/detectron2/evaluation/evaluator.py
  class DatasetEvaluator (line 13) | class DatasetEvaluator:
    method reset (line 24) | def reset(self):
    method process (line 31) | def process(self, input, output):
    method evaluate (line 41) | def evaluate(self):
  class DatasetEvaluators (line 57) | class DatasetEvaluators(DatasetEvaluator):
    method __init__ (line 58) | def __init__(self, evaluators):
    method reset (line 62) | def reset(self):
    method process (line 66) | def process(self, input, output):
    method evaluate (line 70) | def evaluate(self):
  function inference_on_dataset (line 83) | def inference_on_dataset(model, data_loader, evaluator):
  function inference_context (line 169) | def inference_context(model):

FILE: reference_code/GSNet-release/detectron2/evaluation/lvis_evaluation.py
  class LVISEvaluator (line 21) | class LVISEvaluator(DatasetEvaluator):
    method __init__ (line 27) | def __init__(self, dataset_name, cfg, distributed, output_dir=None):
    method reset (line 54) | def reset(self):
    method _tasks_from_config (line 57) | def _tasks_from_config(self, cfg):
    method process (line 67) | def process(self, inputs, outputs):
    method evaluate (line 86) | def evaluate(self):
    method _eval_predictions (line 115) | def _eval_predictions(self, tasks, predictions):
    method _eval_box_proposals (line 157) | def _eval_box_proposals(self, predictions):
  function _evaluate_box_proposals (line 199) | def _evaluate_box_proposals(dataset_predictions, lvis_api, thresholds=No...
  function _evaluate_predictions_on_lvis (line 308) | def _evaluate_predictions_on_lvis(lvis_gt, lvis_results, iou_type, class...

FILE: reference_code/GSNet-release/detectron2/evaluation/panoptic_evaluation.py
  class COCOPanopticEvaluator (line 22) | class COCOPanopticEvaluator(DatasetEvaluator):
    method __init__ (line 30) | def __init__(self, dataset_name, output_dir):
    method reset (line 46) | def reset(self):
    method _convert_category_id (line 49) | def _convert_category_id(self, segment_info):
    method process (line 64) | def process(self, inputs, outputs):
    method evaluate (line 85) | def evaluate(self):
  function _print_panoptic_results (line 136) | def _print_panoptic_results(pq_res):

FILE: reference_code/GSNet-release/detectron2/evaluation/pascal_voc_evaluation.py
  class PascalVOCDetectionEvaluator (line 20) | class PascalVOCDetectionEvaluator(DatasetEvaluator):
    method __init__ (line 30) | def __init__(self, dataset_name):
    method reset (line 45) | def reset(self):
    method process (line 48) | def process(self, inputs, outputs):
    method evaluate (line 64) | def evaluate(self):
  function parse_rec (line 126) | def parse_rec(filename):
  function voc_ap (line 149) | def voc_ap(rec, prec, use_07_metric=False):
  function voc_eval (line 181) | def voc_eval(detpath, annopath, imagesetfile, classname, ovthresh=0.5, u...

FILE: reference_code/GSNet-release/detectron2/evaluation/rotated_coco_evaluation.py
  class RotatedCOCOeval (line 14) | class RotatedCOCOeval(COCOeval):
    method is_rotated (line 16) | def is_rotated(box_list):
    method boxlist_to_tensor (line 33) | def boxlist_to_tensor(boxlist, output_box_dim):
    method compute_iou_dt_gt (line 56) | def compute_iou_dt_gt(self, dt, gt, is_crowd):
    method computeIoU (line 67) | def computeIoU(self, imgId, catId):
  class RotatedCOCOEvaluator (line 96) | class RotatedCOCOEvaluator(COCOEvaluator):
    method process (line 103) | def process(self, inputs, outputs):
    method instances_to_json (line 123) | def instances_to_json(self, instances, img_id):
    method _eval_predictions (line 147) | def _eval_predictions(self, tasks, predictions):
    method _evaluate_predictions_on_coco (line 188) | def _evaluate_predictions_on_coco(self, coco_gt, coco_results):

FILE: reference_code/GSNet-release/detectron2/evaluation/sem_seg_evaluation.py
  class SemSegEvaluator (line 19) | class SemSegEvaluator(DatasetEvaluator):
    method __init__ (line 24) | def __init__(self, dataset_name, distributed, num_classes, ignore_labe...
    method reset (line 58) | def reset(self):
    method process (line 62) | def process(self, inputs, outputs):
    method evaluate (line 86) | def evaluate(self):
    method encode_json_sem_seg (line 143) | def encode_json_sem_seg(self, sem_seg, input_file_name):

FILE: reference_code/GSNet-release/detectron2/evaluation/testing.py
  function print_csv_format (line 10) | def print_csv_format(results):
  function verify_results (line 28) | def verify_results(cfg, results):
  function flatten_results_dict (line 61) | def flatten_results_dict(results):

FILE: reference_code/GSNet-release/detectron2/export/api.py
  function add_export_config (line 17) | def add_export_config(cfg):
  function export_caffe2_model (line 34) | def export_caffe2_model(cfg, model, inputs):
  class Caffe2Model (line 58) | class Caffe2Model(nn.Module):
    method __init__ (line 59) | def __init__(self, predict_net, init_net):
    method predict_net (line 67) | def predict_net(self):
    method init_net (line 75) | def init_net(self):
    method save_protobuf (line 84) | def save_protobuf(self, output_dir):
    method save_graph (line 102) | def save_graph(self, output_file, inputs=None):
    method load_protobuf (line 124) | def load_protobuf(dir):
    method __call__ (line 144) | def __call__(self, inputs):

FILE: reference_code/GSNet-release/detectron2/export/c10.py
  class Boxes4or5 (line 21) | class Boxes4or5(Boxes):
    method __init__ (line 27) | def __init__(self, tensor):
  class InstancesList (line 35) | class InstancesList(object):
    method __init__ (line 45) | def __init__(self, im_info, indices, extra_fields=None):
    method get_fields (line 55) | def get_fields(self):
    method has (line 69) | def has(self, name):
    method set (line 72) | def set(self, name, value):
    method __setattr__ (line 80) | def __setattr__(self, name, val):
    method __getattr__ (line 86) | def __getattr__(self, name):
    method __len__ (line 91) | def __len__(self):
    method flatten (line 94) | def flatten(self):
    method to_d2_instances_list (line 104) | def to_d2_instances_list(instances_list):
  class Caffe2Compatible (line 144) | class Caffe2Compatible(object):
    method _get_tensor_mode (line 145) | def _get_tensor_mode(self):
    method _set_tensor_mode (line 148) | def _set_tensor_mode(self, v):
  class Caffe2RPN (line 157) | class Caffe2RPN(Caffe2Compatible, rpn.RPN):
    method forward (line 158) | def forward(self, images, features, gt_instances=None):
    method c2_postprocess (line 248) | def c2_postprocess(im_info, rpn_rois, rpn_roi_probs, tensor_mode):
  class Caffe2ROIPooler (line 264) | class Caffe2ROIPooler(Caffe2Compatible, poolers.ROIPooler):
    method c2_preprocess (line 266) | def c2_preprocess(box_lists):
    method forward (line 276) | def forward(self, x, box_lists):
  class Caffe2FastRCNNOutputsInference (line 331) | class Caffe2FastRCNNOutputsInference:
    method __init__ (line 332) | def __init__(self, tensor_mode):
    method __call__ (line 335) | def __call__(self, fastrcnn_outputs, score_thresh, nms_thresh, topk_pe...
  class Caffe2MaskRCNNInference (line 449) | class Caffe2MaskRCNNInference:
    method __call__ (line 450) | def __call__(self, pred_mask_logits, pred_instances):
  class Caffe2KeypointRCNNInference (line 461) | class Caffe2KeypointRCNNInference:
    method __init__ (line 462) | def __init__(self, use_heatmap_max_keypoint):
    method __call__ (line 465) | def __call__(self, pred_keypoint_logits, pred_instances):

FILE: reference_code/GSNet-release/detectron2/export/caffe2_export.py
  function _export_via_onnx (line 26) | def _export_via_onnx(model, inputs):
  function _op_stats (line 59) | def _op_stats(net_def):
  function export_caffe2_detection_model (line 68) | def export_caffe2_detection_model(model: torch.nn.Module, tensor_inputs:...
  function run_and_save_graph (line 101) | def run_and_save_graph(predict_net, init_net, tensor_inputs, graph_save_...

FILE: reference_code/GSNet-release/detectron2/export/caffe2_inference.py
  class ProtobufModel (line 15) | class ProtobufModel(torch.nn.Module):
    method __init__ (line 22) | def __init__(self, predict_net, init_net):
    method forward (line 39) | def forward(self, inputs_dict):
  class ProtobufDetectionModel (line 67) | class ProtobufDetectionModel(torch.nn.Module):
    method __init__ (line 73) | def __init__(self, predict_net, init_net, *, convert_outputs=None):
    method _convert_inputs (line 92) | def _convert_inputs(self, batched_inputs):
    method forward (line 99) | def forward(self, batched_inputs):

FILE: reference_code/GSNet-release/detectron2/export/caffe2_modeling.py
  function _is_valid_model_output_blob (line 30) | def _is_valid_model_output_blob(blob):
  function assemble_rcnn_outputs_by_name (line 34) | def assemble_rcnn_outputs_by_name(image_sizes, tensor_outputs, force_mas...
  function _cast_to_f32 (line 99) | def _cast_to_f32(f64):
  function set_caffe2_compatible_tensor_mode (line 103) | def set_caffe2_compatible_tensor_mode(model, enable=True):
  function convert_batched_inputs_to_c2_format (line 111) | def convert_batched_inputs_to_c2_format(batched_inputs, size_divisibilit...
  class Caffe2MetaArch (line 139) | class Caffe2MetaArch(Caffe2Compatible, torch.nn.Module):
    method __init__ (line 146) | def __init__(self, cfg, torch_model):
    method get_caffe2_inputs (line 158) | def get_caffe2_inputs(self, batched_inputs):
    method encode_additional_info (line 182) | def encode_additional_info(self, predict_net, init_net):
    method forward (line 188) | def forward(self, inputs):
    method _caffe2_preprocess_image (line 203) | def _caffe2_preprocess_image(self, inputs):
    method get_outputs_converter (line 220) | def get_outputs_converter(predict_net, init_net):
  class Caffe2GeneralizedRCNN (line 248) | class Caffe2GeneralizedRCNN(Caffe2MetaArch):
    method __init__ (line 249) | def __init__(self, cfg, torch_model):
    method encode_additional_info (line 256) | def encode_additional_info(self, predict_net, init_net):
    method forward (line 262) | def forward(self, inputs):
    method get_outputs_converter (line 273) | def get_outputs_converter(predict_net, init_net):
  class Caffe2PanopticFPN (line 282) | class Caffe2PanopticFPN(Caffe2MetaArch):
    method __init__ (line 283) | def __init__(self, cfg, torch_model):
    method forward (line 291) | def forward(self, inputs):
    method encode_additional_info (line 306) | def encode_additional_info(self, predict_net, init_net):
    method get_outputs_converter (line 333) | def get_outputs_converter(predict_net, init_net):
  class Caffe2RetinaNet (line 374) | class Caffe2RetinaNet(Caffe2MetaArch):
    method __init__ (line 375) | def __init__(self, cfg, torch_model):
    method forward (line 380) | def forward(self, inputs):
    method encode_additional_info (line 401) | def encode_additional_info(self, predict_net, init_net):
    method _encode_anchor_generator_cfg (line 429) | def _encode_anchor_generator_cfg(self, predict_net):
    method get_outputs_converter (line 439) | def get_outputs_converter(predict_net, init_net):

FILE: reference_code/GSNet-release/detectron2/export/patcher.py
  class GenericMixin (line 22) | class GenericMixin(object):
  class Caffe2CompatibleConverter (line 26) | class Caffe2CompatibleConverter(object):
    method __init__ (line 32) | def __init__(self, replaceCls):
    method create_from (line 35) | def create_from(self, module):
  function patch (line 57) | def patch(model, target, updater, *args, **kwargs):
  function patch_generalized_rcnn (line 70) | def patch_generalized_rcnn(model):
  function mock_fastrcnn_outputs_inference (line 79) | def mock_fastrcnn_outputs_inference(tensor_mode, check=True):
  function mock_mask_rcnn_inference (line 92) | def mock_mask_rcnn_inference(tensor_mode, patched_module, check=True):
  function mock_keypoint_rcnn_inference (line 102) | def mock_keypoint_rcnn_inference(tensor_mode, patched_module, use_heatma...
  class ROIHeadsPatcher (line 112) | class ROIHeadsPatcher:
    method __init__ (line 113) | def __init__(self, cfg, heads):
    method mock_roi_heads (line 119) | def mock_roi_heads(self, tensor_mode=True):

FILE: reference_code/GSNet-release/detectron2/export/shared.py
  function to_device (line 25) | def to_device(t, device_str):
  function BilinearInterpolation (line 37) | def BilinearInterpolation(tensor_in, up_scale):
  function onnx_compatibale_interpolate (line 71) | def onnx_compatibale_interpolate(
  function mock_torch_nn_functional_interpolate (line 105) | def mock_torch_nn_functional_interpolate():
  class ScopedWS (line 118) | class ScopedWS(object):
    method __init__ (line 119) | def __init__(self, ws_name, is_reset, is_cleanup=False):
    method __enter__ (line 125) | def __enter__(self):
    method __exit__ (line 134) | def __exit__(self, *args):
  function fetch_any_blob (line 141) | def fetch_any_blob(name):
  function get_pb_arg (line 156) | def get_pb_arg(pb, arg_name):
  function get_pb_arg_valf (line 163) | def get_pb_arg_valf(pb, arg_name, default_val):
  function get_pb_arg_floats (line 168) | def get_pb_arg_floats(pb, arg_name, default_val):
  function get_pb_arg_ints (line 173) | def get_pb_arg_ints(pb, arg_name, default_val):
  function get_pb_arg_vali (line 178) | def get_pb_arg_vali(pb, arg_name, default_val):
  function get_pb_arg_vals (line 183) | def get_pb_arg_vals(pb, arg_name, default_val):
  function get_pb_arg_valstrings (line 188) | def get_pb_arg_valstrings(pb, arg_name, default_val):
  function check_set_pb_arg (line 193) | def check_set_pb_arg(pb, arg_name, arg_attr, arg_value, allow_override=F...
  function _create_const_fill_op_from_numpy (line 211) | def _create_const_fill_op_from_numpy(name, tensor, device_option=None):
  function _create_const_fill_op_from_c2_int8_tensor (line 232) | def _create_const_fill_op_from_c2_int8_tensor(name, int8_tensor):
  function create_const_fill_op (line 254) | def create_const_fill_op(
  function construct_init_net_from_params (line 276) | def construct_init_net_from_params(
  function get_params_from_init_net (line 297) | def get_params_from_init_net(init_net: caffe2_pb2.NetDef) -> Dict[str, A...
  function remove_reshape_for_fc (line 306) | def remove_reshape_for_fc(predict_net, params):
  function _modify_blob_names (line 379) | def _modify_blob_names(ops, blob_rename_f):
  function _rename_blob (line 395) | def _rename_blob(name, blob_sizes, blob_ranges):
  function save_graph (line 411) | def save_graph(net, file_name, graph_name="net", op_only=True, blob_size...
  function save_graph_base (line 416) | def save_graph_base(net, file_name, graph_name="net", op_only=True, blob...
  function group_norm_replace_aten_with_caffe2 (line 451) | def group_norm_replace_aten_with_caffe2(predict_net: caffe2_pb2.NetDef):
  function alias (line 480) | def alias(x, name, is_backward=False):
  function fuse_alias_placeholder (line 487) | def fuse_alias_placeholder(predict_net, init_net):
  class IllegalGraphTransformError (line 515) | class IllegalGraphTransformError(ValueError):
  function _rename_versioned_blob_in_proto (line 519) | def _rename_versioned_blob_in_proto(
  function rename_op_input (line 550) | def rename_op_input(
  function rename_op_output (line 617) | def rename_op_output(predict_net: caffe2_pb2.NetDef, op_id: int, output_...
  function get_sub_graph_external_input_output (line 638) | def get_sub_graph_external_input_output(
  function get_producer_map (line 670) | def get_producer_map(ssa):
  function get_consumer_map (line 683) | def get_consumer_map(ssa):
  class DiGraph (line 696) | class DiGraph:
    method __init__ (line 699) | def __init__(self):
    method add_edge (line 703) | def add_edge(self, u, v):
    method get_all_paths (line 709) | def get_all_paths(self, s, d):
    method from_ssa (line 730) | def from_ssa(ssa):
  function _get_dependency_chain (line 739) | def _get_dependency_chain(ssa, versioned_target, versioned_source):
  function identify_reshape_sub_graph (line 767) | def identify_reshape_sub_graph(predict_net: caffe2_pb2.NetDef,) -> List[...

FILE: reference_code/GSNet-release/detectron2/layers/batch_norm.py
  class FrozenBatchNorm2d (line 14) | class FrozenBatchNorm2d(nn.Module):
    method __init__ (line 36) | def __init__(self, num_features, eps=1e-5):
    method forward (line 45) | def forward(self, x):
    method _load_from_state_dict (line 67) | def _load_from_state_dict(
    method __repr__ (line 90) | def __repr__(self):
    method convert_frozen_batchnorm (line 94) | def convert_frozen_batchnorm(cls, module):
  function get_norm (line 127) | def get_norm(norm, out_channels):
  class AllReduce (line 148) | class AllReduce(Function):
    method forward (line 150) | def forward(ctx, input):
    method backward (line 158) | def backward(ctx, grad_output):
  class NaiveSyncBatchNorm (line 163) | class NaiveSyncBatchNorm(BatchNorm2d):
    method forward (line 174) | def forward(self, input):

FILE: reference_code/GSNet-release/detectron2/layers/boundary.py
  function get_contour_interior (line 17) | def get_contour_interior(mask, bold=False):
  function get_center (line 33) | def get_center(mask):
  function get_instances_contour_interior (line 43) | def get_instances_contour_interior(instances_mask):

FILE: reference_code/GSNet-release/detectron2/layers/csrc/ROIAlign/ROIAlign.h
  function namespace (line 5) | namespace detectron2 {

FILE: reference_code/GSNet-release/detectron2/layers/csrc/ROIAlign/ROIAlign_cpu.cpp
  type PreCalc (line 9) | struct PreCalc {
  function pre_calc_for_bilinear_interpolate (line 21) | void pre_calc_for_bilinear_interpolate(
  function ROIAlignForward (line 117) | void ROIAlignForward(
  function bilinear_interpolate_gradient (line 221) | void bilinear_interpolate_gradient(
  function add (line 282) | inline void add(T* address, const T& val) {
  function ROIAlignBackward (line 287) | void ROIAlignBackward(
  type detectron2 (line 398) | namespace detectron2 {
    function ROIAlign_forward_cpu (line 400) | at::Tensor ROIAlign_forward_cpu(
    function ROIAlign_backward_cpu (line 447) | at::Tensor ROIAlign_backward_cpu(

FILE: reference_code/GSNet-release/detectron2/layers/csrc/ROIAlignRotated/ROIAlignRotated.h
  function namespace (line 5) | namespace detectron2 {

FILE: reference_code/GSNet-release/detectron2/layers/csrc/ROIAlignRotated/ROIAlignRotated_cpu.cpp
  type detectron2 (line 12) | namespace detectron2 {
    type PreCalc (line 16) | struct PreCalc {
    function pre_calc_for_bilinear_interpolate (line 28) | void pre_calc_for_bilinear_interpolate(
    function bilinear_interpolate_gradient (line 132) | void bilinear_interpolate_gradient(
    function add (line 195) | inline void add(T* address, const T& val) {
    function ROIAlignRotatedForward (line 202) | void ROIAlignRotatedForward(
    function ROIAlignRotatedBackward (line 313) | void ROIAlignRotatedBackward(
    function ROIAlignRotated_forward_cpu (line 417) | at::Tensor ROIAlignRotated_forward_cpu(
    function ROIAlignRotated_backward_cpu (line 464) | at::Tensor ROIAlignRotated_backward_cpu(

FILE: reference_code/GSNet-release/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated.h
  function namespace (line 5) | namespace detectron2 {

FILE: reference_code/GSNet-release/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated_cpu.cpp
  type detectron2 (line 5) | namespace detectron2 {
    function box_iou_rotated_cpu_kernel (line 8) | void box_iou_rotated_cpu_kernel(
    function box_iou_rotated_cpu (line 31) | at::Tensor box_iou_rotated_cpu(

FILE: reference_code/GSNet-release/detectron2/layers/csrc/box_iou_rotated/box_iou_rotated_utils.h
  function namespace (line 17) | namespace detectron2 {

FILE: reference_code/GSNet-release/detectron2/layers/csrc/deformable/deform_conv.h
  function namespace (line 5) | namespace detectron2 {

FILE: reference_code/GSNet-release/detectron2/layers/csrc/nms_rotated/nms_rotated.h
  function namespace (line 5) | namespace detectron2 {

FILE: reference_code/GSNet-release/detectron2/layers/csrc/nms_rotated/nms_rotated_cpu.cpp
  type detectron2 (line 5) | namespace detectron2 {
    function nms_rotated_cpu_kernel (line 8) | at::Tensor nms_rotated_cpu_kernel(
    function nms_rotated_cpu (line 61) | at::Tensor nms_rotated_cpu(

FILE: reference_code/GSNet-release/detectron2/layers/csrc/vision.cpp
  type detectron2 (line 10) | namespace detectron2 {
    function get_cuda_version (line 16) | std::string get_cuda_version() {
    function get_compiler_version (line 37) | std::string get_compiler_version() {
    function PYBIND11_MODULE (line 63) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: reference_code/GSNet-release/detectron2/layers/deform_conv.py
  class _DeformConv (line 15) | class _DeformConv(Function):
    method forward (line 17) | def forward(
    method backward (line 77) | def backward(ctx, grad_output):
    method _output_size (line 138) | def _output_size(input, weight, padding, dilation, stride):
    method _cal_im2col_step (line 157) | def _cal_im2col_step(input_size, default_size):
  class _ModulatedDeformConv (line 179) | class _ModulatedDeformConv(Function):
    method forward (line 181) | def forward(
    method backward (line 238) | def backward(ctx, grad_output):
    method _infer_shape (line 290) | def _infer_shape(ctx, input, weight):
  class DeformConv (line 308) | class DeformConv(nn.Module):
    method __init__ (line 309) | def __init__(
    method forward (line 361) | def forward(self, x, offset):
    method extra_repr (line 392) | def extra_repr(self):
  class ModulatedDeformConv (line 405) | class ModulatedDeformConv(nn.Module):
    method __init__ (line 406) | def __init__(
    method forward (line 455) | def forward(self, x, offset, mask):
    method extra_repr (line 484) | def extra_repr(self):

FILE: reference_code/GSNet-release/detectron2/layers/iou_loss.py
  class IOULoss (line 7) | class IOULoss(nn.Module):
    method __init__ (line 8) | def __init__(self, loss_type="iou"):
    method forward (line 12) | def forward(self, pred, target, weight=None):

FILE: reference_code/GSNet-release/detectron2/layers/mask_ops.py
  function _do_paste_mask (line 16) | def _do_paste_mask(masks, boxes, img_h, img_w, skip_empty=True):
  function paste_masks_in_image (line 67) | def paste_masks_in_image(masks, boxes, image_shape, threshold=0.5):
  function paste_mask_in_image_old (line 136) | def paste_mask_in_image_old(mask, box, img_h, img_w, threshold):
  function pad_masks (line 200) | def pad_masks(masks, padding):
  function scale_boxes (line 218) | def scale_boxes(boxes, scale):

FILE: reference_code/GSNet-release/detectron2/layers/misc.py
  class AddCoords (line 17) | class AddCoords(nn.Module):
    method __init__ (line 19) | def __init__(self, with_r=False):
    method forward (line 23) | def forward(self, input_tensor):
  class CoordConv (line 54) | class CoordConv(nn.Module):
    method __init__ (line 56) | def __init__(self, in_channels, out_channels, with_r=False, **kwargs):
    method forward (line 64) | def forward(self, x):
  class _NewEmptyTensorOp (line 70) | class _NewEmptyTensorOp(torch.autograd.Function):
    method forward (line 72) | def forward(ctx, x, new_shape):
    method backward (line 77) | def backward(ctx, grad):
  class Conv2d (line 82) | class Conv2d(torch.nn.Conv2d):
    method forward (line 83) | def forward(self, x):
  class ConvTranspose2d (line 98) | class ConvTranspose2d(torch.nn.ConvTranspose2d):
    method forward (line 99) | def forward(self, x):
  class BatchNorm2d (line 119) | class BatchNorm2d(torch.nn.BatchNorm2d):
    method forward (line 120) | def forward(self, x):
  function interpolate (line 128) | def interpolate(
  class DFConv2d (line 166) | class DFConv2d(torch.nn.Module):
    method __init__ (line 168) | def __init__(
    method forward (line 225) | def forward(self, x):

FILE: reference_code/GSNet-release/detectron2/layers/nms.py
  function batched_nms (line 9) | def batched_nms(boxes, scores, idxs, iou_threshold):
  function nms_rotated (line 31) | def nms_rotated(boxes, scores, iou_threshold):
  function batched_nms_rotated (line 99) | def batched_nms_rotated(boxes, scores, idxs, iou_threshold):

FILE: reference_code/GSNet-release/detectron2/layers/roi_align.py
  class _ROIAlign (line 10) | class _ROIAlign(Function):
    method forward (line 12) | def forward(ctx, input, roi, output_size, spatial_scale, sampling_rati...
    method backward (line 26) | def backward(ctx, grad_output):
  class ROIAlign (line 51) | class ROIAlign(nn.Module):
    method __init__ (line 52) | def __init__(self, output_size, spatial_scale, sampling_ratio, aligned...
    method forward (line 87) | def forward(self, input, rois):
    method __repr__ (line 98) | def __repr__(self):

FILE: reference_code/GSNet-release/detectron2/layers/roi_align_rotated.py
  class _ROIAlignRotated (line 10) | class _ROIAlignRotated(Function):
    method forward (line 12) | def forward(ctx, input, roi, output_size, spatial_scale, sampling_ratio):
    method backward (line 25) | def backward(ctx, grad_output):
  class ROIAlignRotated (line 49) | class ROIAlignRotated(nn.Module):
    method __init__ (line 50) | def __init__(self, output_size, spatial_scale, sampling_ratio):
    method forward (line 70) | def forward(self, input, rois):
    method __repr__ (line 82) | def __repr__(self):

FILE: reference_code/GSNet-release/detectron2/layers/rotated_boxes.py
  function pairwise_iou_rotated (line 8) | def pairwise_iou_rotated(boxes1, boxes2):

FILE: reference_code/GSNet-release/detectron2/layers/scale.py
  class Scale (line 5) | class Scale(nn.Module):
    method __init__ (line 6) | def __init__(self, init_value=1.0):
    method forward (line 10) | def forward(self, input):

FILE: reference_code/GSNet-release/detectron2/layers/shape_spec.py
  class ShapeSpec (line 6) | class ShapeSpec(namedtuple("_ShapeSpec", ["channels", "height", "width",...
    method __new__ (line 19) | def __new__(cls, *, channels=None, height=None, width=None, stride=None):

FILE: reference_code/GSNet-release/detectron2/layers/wrappers.py
  function cat (line 16) | def cat(tensors, dim=0):
  class _NewEmptyTensorOp (line 26) | class _NewEmptyTensorOp(torch.autograd.Function):
    method forward (line 28) | def forward(ctx, x, new_shape):
    method backward (line 33) | def backward(ctx, grad):
  class Conv2d (line 38) | class Conv2d(torch.nn.Conv2d):
    method __init__ (line 43) | def __init__(self, *args, **kwargs):
    method forward (line 60) | def forward(self, x):
  class ConvTranspose2d (line 75) | class ConvTranspose2d(torch.nn.ConvTranspose2d):
    method forward (line 80) | def forward(self, x):
  class BatchNorm2d (line 107) | class BatchNorm2d(torch.nn.BatchNorm2d):
    method forward (line 112) | def forward(self, x):
  function interpolate (line 120) | def interpolate(input, size=None, scale_factor=None, mode="nearest", ali...

FILE: reference_code/GSNet-release/detectron2/modeling/anchor_generator.py
  class BufferList (line 20) | class BufferList(nn.Module):
    method __init__ (line 25) | def __init__(self, buffers=None):
    method extend (line 30) | def extend(self, buffers):
    method __len__ (line 36) | def __len__(self):
    method __iter__ (line 39) | def __iter__(self):
  function _create_grid_offsets (line 43) | def _create_grid_offsets(size, stride, offset, device):
  class DefaultAnchorGenerator (line 59) | class DefaultAnchorGenerator(nn.Module):
    method __init__ (line 64) | def __init__(self, cfg, input_shape: List[ShapeSpec]):
    method _calculate_anchors (line 91) | def _calculate_anchors(self, sizes, aspect_ratios):
    method box_dim (line 109) | def box_dim(self):
    method num_cell_anchors (line 117) | def num_cell_anchors(self):
    method grid_anchors (line 130) | def grid_anchors(self, grid_sizes):
    method generate_cell_anchors (line 140) | def generate_cell_anchors(self, sizes=(32, 64, 128, 256, 512), aspect_...
    method forward (line 179) | def forward(self, features):
  class RotatedAnchorGenerator (line 202) | class RotatedAnchorGenerator(nn.Module):
    method __init__ (line 207) | def __init__(self, cfg, input_shape: List[ShapeSpec]):
    method _calculate_anchors (line 223) | def _calculate_anchors(self, sizes, aspect_ratios, angles, feature_str...
    method box_dim (line 265) | def box_dim(self):
    method num_cell_anchors (line 273) | def num_cell_anchors(self):
    method grid_anchors (line 287) | def grid_anchors(self, grid_sizes):
    method generate_cell_anchors (line 298) | def generate_cell_anchors(
    method forward (line 337) | def forward(self, features):
  function build_anchor_generator (line 360) | def build_anchor_generator(cfg, input_shape):

FILE: reference_code/GSNet-release/detectron2/modeling/backbone/backbone.py
  class Backbone (line 10) | class Backbone(nn.Module, metaclass=ABCMeta):
    method __init__ (line 15) | def __init__(self):
    method forward (line 22) | def forward(self):
    method size_divisibility (line 32) | def size_divisibility(self):
    method output_shape (line 42) | def output_shape(self):

FILE: reference_code/GSNet-release/detectron2/modeling/backbone/build.py
  function build_backbone (line 20) | def build_backbone(cfg, input_shape=None):

FILE: reference_code/GSNet-release/detectron2/modeling/backbone/fpn.py
  class FPN (line 16) | class FPN(Backbone):
    method __init__ (line 22) | def __init__(
    method size_divisibility (line 106) | def size_divisibility(self):
    method forward (line 109) | def forward(self, x):
    method output_shape (line 146) | def output_shape(self):
  function _assert_strides_are_log2_contiguous (line 155) | def _assert_strides_are_log2_contiguous(strides):
  class LastLevelMaxPool (line 165) | class LastLevelMaxPool(nn.Module):
    method __init__ (line 171) | def __init__(self):
    method forward (line 176) | def forward(self, x):
  class LastLevelP6P7 (line 180) | class LastLevelP6P7(nn.Module):
    method __init__ (line 186) | def __init__(self, in_channels, out_channels):
    method forward (line 195) | def forward(self, p5):
  function build_resnet_fpn_backbone (line 202) | def build_resnet_fpn_backbone(cfg, input_shape: ShapeSpec):
  function build_retinanet_resnet_fpn_backbone (line 225) | def build_retinanet_resnet_fpn_backbone(cfg, input_shape: ShapeSpec):

FILE: reference_code/GSNet-release/detectron2/modeling/backbone/pafpn.py
  class FPN (line 16) | class FPN(Backbone):
    method __init__ (line 22) | def __init__(
    method size_divisibility (line 139) | def size_divisibility(self):
    method forward (line 142) | def forward(self, x):
    method output_shape (line 191) | def output_shape(self):
  function _assert_strides_are_log2_contiguous (line 200) | def _assert_strides_are_log2_contiguous(strides):
  class LastLevelMaxPool (line 210) | class LastLevelMaxPool(nn.Module):
    method __init__ (line 216) | def __init__(self):
    method forward (line 221) | def forward(self, x):
  class LastLevelP6P7 (line 225) | class LastLevelP6P7(nn.Module):
    method __init__ (line 231) | def __init__(self, in_channels, out_channels):
    method forward (line 240) | def forward(self, p5):
  function build_resnet_fpn_backbone (line 247) | def build_resnet_fpn_backbone(cfg, input_shape: ShapeSpec):
  function build_retinanet_resnet_fpn_backbone (line 270) | def build_retinanet_resnet_fpn_backbone(cfg, input_shape: ShapeSpec):

FILE: reference_code/GSNet-release/detectron2/modeling/backbone/resnet.py
  class ResNetBlockBase (line 31) | class ResNetBlockBase(nn.Module):
    method __init__ (line 32) | def __init__(self, in_channels, out_channels, stride):
    method freeze (line 46) | def freeze(self):
  class BottleneckBlock (line 53) | class BottleneckBlock(ResNetBlockBase):
    method __init__ (line 54) | def __init__(
    method forward (line 138) | def forward(self, x):
  class DeformBottleneckBlock (line 157) | class DeformBottleneckBlock(ResNetBlockBase):
    method __init__ (line 158) | def __init__(
    method forward (line 245) | def forward(self, x):
  function make_stage (line 272) | def make_stage(block_class, num_blocks, first_stride, **kwargs):
  class BasicStem (line 292) | class BasicStem(nn.Module):
    method __init__ (line 293) | def __init__(self, in_channels=3, out_channels=64, norm="BN"):
    method forward (line 312) | def forward(self, x):
    method out_channels (line 319) | def out_channels(self):
    method stride (line 323) | def stride(self):
  class ResNet (line 327) | class ResNet(Backbone):
    method __init__ (line 328) | def __init__(self, stem, stages, num_classes=None, out_features=None):
    method forward (line 379) | def forward(self, x):
    method output_shape (line 395) | def output_shape(self):
  function build_resnet_backbone (line 405) | def build_resnet_backbone(cfg, input_shape):

FILE: reference_code/GSNet-release/detectron2/modeling/box_regression.py
  class Box2BoxTransform (line 14) | class Box2BoxTransform(object):
    method __init__ (line 21) | def __init__(self, weights, scale_clamp=_DEFAULT_SCALE_CLAMP):
    method get_deltas (line 34) | def get_deltas(self, src_boxes, target_boxes):
    method apply_deltas (line 71) | def apply_deltas(self, deltas, boxes):
  class Box2BoxTransformRotated (line 112) | class Box2BoxTransformRotated(object):
    method __init__ (line 121) | def __init__(self, weights, scale_clamp=_DEFAULT_SCALE_CLAMP):
    method get_deltas (line 133) | def get_deltas(self, src_boxes, target_boxes):
    method apply_deltas (line 171) | def apply_deltas(self, deltas, boxes):

FILE: reference_code/GSNet-release/detectron2/modeling/matcher.py
  class Matcher (line 5) | class Matcher(object):
    method __init__ (line 21) | def __init__(self, thresholds, labels, allow_low_quality_matches=False):
    method __call__ (line 55) | def __call__(self, match_quality_matrix):
    method set_low_quality_matches_ (line 99) | def set_low_quality_matches_(self, match_labels, match_quality_matrix):

FILE: reference_code/GSNet-release/detectron2/modeling/meta_arch/build.py
  function build_model (line 13) | def build_model(cfg):

FILE: reference_code/GSNet-release/detectron2/modeling/meta_arch/fcos.py
  function select_foreground_proposals (line 31) | def select_foreground_proposals(train_part, proposals, bg_label):
  class FCOS (line 70) | class FCOS(nn.Module):
    method __init__ (line 75) | def __init__(self, cfg):
    method forward (line 138) | def forward(self, batched_inputs, c_iter, max_iter):
    method _forward_train (line 187) | def _forward_train(self, features_list, locations, box_cls, box_regres...
    method _forward_test (line 211) | def _forward_test(self, features, locations, box_cls, box_regression, ...
    method _forward_mask (line 224) | def _forward_mask(self, features, instances):
    method label_and_sample_proposals (line 258) | def label_and_sample_proposals(self, proposals, targets):
    method _sample_proposals (line 340) | def _sample_proposals(self, matched_idxs, matched_labels, gt_classes):
    method _postprocess (line 378) | def _postprocess(instances, batched_inputs, image_sizes):
    method compute_locations (line 393) | def compute_locations(self, features):
    method compute_locations_per_level (line 404) | def compute_locations_per_level(self, h, w, stride, device):
    method preprocess_image (line 419) | def preprocess_image(self, batched_inputs):
  class FCOSHead (line 429) | class FCOSHead(nn.Module):
    method __init__ (line 430) | def __init__(self, cfg, in_channels):
    method forward (line 508) | def forward(self, x):

FILE: reference_code/GSNet-release/detectron2/modeling/meta_arch/inference_fcos.py
  function permute_to_N_HW_K (line 11) | def permute_to_N_HW_K(tensor, K):
  class FCOSPostProcessor (line 23) | class FCOSPostProcessor(torch.nn.Module):
    method __init__ (line 28) | def __init__(
    method forward_for_single_image (line 57) | def forward_for_single_image(
    method forward (line 132) | def forward(self, locations, box_cls, box_regression, centerness, batc...
  function make_fcos_postprocessor (line 163) | def make_fcos_postprocessor(config): #, is_train):

FILE: reference_code/GSNet-release/detectron2/modeling/meta_arch/loss_fcos.py
  function get_num_gpus (line 17) | def get_num_gpus():
  function reduce_sum (line 21) | def reduce_sum(tensor):
  class FCOSLossComputation (line 30) | class FCOSLossComputation(object):
    method __init__ (line 35) | def __init__(self, cfg):
    method get_sample_region (line 52) | def get_sample_region(self, gt, strides, num_points_per, gt_xs, gt_ys,...
    method prepare_targets (line 99) | def prepare_targets(self, points, targets):
    method compute_targets_for_locations (line 145) | def compute_targets_for_locations(self, locations, targets, object_siz...
    method compute_centerness_targets (line 199) | def compute_centerness_targets(self, reg_targets):
    method __call__ (line 206) | def __call__(self, locations, box_cls, box_regression, centerness, tar...
  function make_fcos_loss_evaluator (line 286) | def make_fcos_loss_evaluator(cfg):

FILE: reference_code/GSNet-release/detectron2/modeling/meta_arch/panoptic_fpn.py
  class PanopticFPN (line 20) | class PanopticFPN(nn.Module):
    method __init__ (line 25) | def __init__(self, cfg):
    method forward (line 50) | def forward(self, batched_inputs):
  function combine_semantic_and_instance_outputs (line 131) | def combine_semantic_and_instance_outputs(

FILE: reference_code/GSNet-release/detectron2/modeling/meta_arch/rcnn.py
  class GeneralizedRCNN (line 22) | class GeneralizedRCNN(nn.Module):
    method __init__ (line 30) | def __init__(self, cfg):
    method visualize_training (line 47) | def visualize_training(self, batched_inputs, proposals):
    method forward (line 82) | def forward(self, batched_inputs, curr_iter, total_iters):
    method inference (line 140) | def inference(self, batched_inputs, detected_instances=None, do_postpr...
    method preprocess_image (line 182) | def preprocess_image(self, batched_inputs):
    method _postprocess (line 192) | def _postprocess(instances, batched_inputs, image_sizes):
  class ProposalNetwork (line 209) | class ProposalNetwork(nn.Module):
    method __init__ (line 210) | def __init__(self, cfg):
    method forward (line 222) | def forward(self, batched_inputs):

FILE: reference_code/GSNet-release/detectron2/modeling/meta_arch/retinanet.py
  function permute_to_N_HWA_K (line 23) | def permute_to_N_HWA_K(tensor, K):
  function permute_all_cls_and_box_to_N_HWA_K_and_concat (line 35) | def permute_all_cls_and_box_to_N_HWA_K_and_concat(box_cls, box_delta, nu...
  class RetinaNet (line 57) | class RetinaNet(nn.Module):
    method __init__ (line 62) | def __init__(self, cfg):
    method forward (line 101) | def forward(self, batched_inputs):
    method losses (line 150) | def losses(self, gt_classes, gt_anchors_deltas, pred_class_logits, pre...
    method get_ground_truth (line 200) | def get_ground_truth(self, anchors, targets):
    method inference (line 258) | def inference(self, box_cls, box_delta, anchors, image_sizes):
    method inference_single_image (line 287) | def inference_single_image(self, box_cls, box_delta, anchors, image_si...
    method preprocess_image (line 349) | def preprocess_image(self, batched_inputs):
  class RetinaNetHead (line 359) | class RetinaNetHead(nn.Module):
    method __init__ (line 365) | def __init__(self, cfg, input_shape: List[ShapeSpec]):
    method forward (line 409) | def forward(self, features):

FILE: reference_code/GSNet-release/detectron2/modeling/meta_arch/semantic_seg.py
  class SemanticSegmentor (line 28) | class SemanticSegmentor(nn.Module):
    method __init__ (line 33) | def __init__(self, cfg):
    method forward (line 47) | def forward(self, batched_inputs):
  function build_sem_seg_head (line 93) | def build_sem_seg_head(cfg, input_shape):
  class SemSegFPNHead (line 102) | class SemSegFPNHead(nn.Module):
    method __init__ (line 109) | def __init__(self, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward (line 153) | def forward(self, features, targets=None):

FILE: reference_code/GSNet-release/detectron2/modeling/poolers.py
  function assign_boxes_to_levels (line 13) | def assign_boxes_to_levels(box_lists, min_level, max_level, canonical_bo...
  function convert_boxes_to_pooler_format (line 47) | def convert_boxes_to_pooler_format(box_lists):
  class ROIPooler (line 84) | class ROIPooler(nn.Module):
    method __init__ (line 90) | def __init__(
    method forward (line 180) | def forward(self, x, box_lists):

FILE: reference_code/GSNet-release/detectron2/modeling/postprocessing.py
  function detector_postprocess (line 8) | def detector_postprocess(results, output_height, output_width, mask_thre...
  function sem_seg_postprocess (line 55) | def sem_seg_postprocess(result, img_size, output_height, output_width):

FILE: reference_code/GSNet-release/detectron2/modeling/proposal_generator/build.py
  function build_proposal_generator (line 15) | def build_proposal_generator(cfg, input_shape):

FILE: reference_code/GSNet-release/detectron2/modeling/proposal_generator/proposal_utils.py
  function add_ground_truth_to_proposals (line 8) | def add_ground_truth_to_proposals(gt_boxes, proposals):
  function add_ground_truth_to_proposals_single_image (line 34) | def add_ground_truth_to_proposals_single_image(gt_boxes, proposals):

FILE: reference_code/GSNet-release/detectron2/modeling/proposal_generator/rpn.py
  function build_rpn_head (line 26) | def build_rpn_head(cfg, input_shape):
  class StandardRPNHead (line 35) | class StandardRPNHead(nn.Module):
    method __init__ (line 43) | def __init__(self, cfg, input_shape: List[ShapeSpec]):
    method forward (line 74) | def forward(self, features):
  class RPN (line 89) | class RPN(nn.Module):
    method __init__ (line 94) | def __init__(self, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward (line 127) | def forward(self, images, features, gt_instances=None):

FILE: reference_code/GSNet-release/detectron2/modeling/proposal_generator/rpn_outputs.py
  function find_top_rpn_proposals (line 52) | def find_top_rpn_proposals(
  function rpn_losses (line 154) | def rpn_losses(
  class RPNOutputs (line 193) | class RPNOutputs(object):
    method __init__ (line 194) | def __init__(
    method _get_ground_truth (line 250) | def _get_ground_truth(self):
    method losses (line 297) | def losses(self):
    method predict_proposals (line 399) | def predict_proposals(self):
    method predict_objectness_logits (line 428) | def predict_objectness_logits(self):

FILE: reference_code/GSNet-release/detectron2/modeling/proposal_generator/rrpn.py
  class RRPN (line 17) | class RRPN(RPN):
    method __init__ (line 26) | def __init__(self, cfg, input_shape: Dict[str, ShapeSpec]):
    method forward (line 30) | def forward(self, images, features, gt_instances=None):

FILE: reference_code/GSNet-release/detectron2/modeling/proposal_generator/rrpn_outputs.py
  function find_top_rrpn_proposals (line 41) | def find_top_rrpn_proposals(
  class RRPNOutputs (line 143) | class RRPNOutputs(RPNOutputs):
    method __init__ (line 144) | def __init__(
    method _get_ground_truth (line 200) | def _get_ground_truth(self):

FILE: reference_code/GSNet-release/detectron2/modeling/roi_heads/box_head.py
  class FastRCNNConvFCHead (line 20) | class FastRCNNConvFCHead(nn.Module):
    method __init__ (line 26) | def __init__(self, cfg, input_shape: ShapeSpec):
    method forward (line 73) | def forward(self, x):
    method output_size (line 84) | def output_size(self):
  function build_box_head (line 88) | def build_box_head(cfg, input_shape):

FILE: reference_code/GSNet-release/detectron2/modeling/roi_heads/cascade_rcnn.py
  class _ScaleGradient (line 18) | class _ScaleGradient(Function):
    method forward (line 20) | def forward(ctx, input, scale):
    method backward (line 25) | def backward(ctx, grad_output):
  class CascadeROIHeads (line 30) | class CascadeROIHeads(StandardROIHeads):
    method _init_box_head (line 31) | def _init_box_head(self, cfg):
    method forward (line 83) | def forward(self, images, features, proposals, targets=None):
    method _forward_box (line 101) | def _forward_box(self, features, proposals, targets=None):
    method _match_and_label_boxes (line 144) | def _match_and_label_boxes(self, proposals, stage, targets):
    method _run_stage (line 193) | def _run_stage(self, features, proposals, stage):
    method _create_proposals_from_boxes (line 222) | def _create_proposals_from_boxes(self, boxes, image_sizes):

FILE: reference_code/GSNet-release/detectron2/modeling/roi_heads/fast_rcnn.py
  function fast_rcnn_inference (line 41) | def fast_rcnn_inference(boxes, scores, image_shapes, score_thresh, nms_t...
  function fast_rcnn_inference_single_image (line 76) | def fast_rcnn_inference_single_image(
  class FastRCNNOutputs (line 121) | class FastRCNNOutputs(object):
    method __init__ (line 126) | def __init__(
    method _log_accuracy (line 168) | def _log_accuracy(self):
    method softmax_cross_entropy_loss (line 191) | def softmax_cross_entropy_loss(self):
    method smooth_l1_loss (line 202) | def smooth_l1_loss(self):
    method losses (line 258) | def losses(self):
    method predict_boxes (line 271) | def predict_boxes(self):
    method predict_probs (line 287) | def predict_probs(self):
    method inference (line 297) | def inference(self, score_thresh, nms_thresh, topk_per_image):
  class FastRCNNOutputLayers (line 316) | class FastRCNNOutputLayers(nn.Module):
    method __init__ (line 323) | def __init__(self, input_size, num_classes, cls_agnostic_bbox_reg, box...
    method forward (line 349) | def forward(self, x):

FILE: reference_code/GSNet-release/detectron2/modeling/roi_heads/keypoint_head.py
  function build_keypoint_head (line 21) | def build_keypoint_head(cfg, input_shape):
  function keypoint_rcnn_loss (line 29) | def keypoint_rcnn_loss(pred_keypoint_logits, instances, normalizer):
  function keypoint_rcnn_inference (line 114) | def keypoint_rcnn_inference(pred_keypoint_logits, pred_instances):
  class KRCNNConvDeconvUpsampleHead (line 149) | class KRCNNConvDeconvUpsampleHead(nn.Module):
    method __init__ (line 155) | def __init__(self, cfg, input_shape: ShapeSpec):
    method forward (line 194) | def forward(self, x):

FILE: reference_code/GSNet-release/detectron2/modeling/roi_heads/mask_head.py
  function mask_rcnn_loss (line 25) | def mask_rcnn_loss(pred_mask_logits, instances):
  function mask_rcnn_inference (line 105) | def mask_rcnn_inference(pred_mask_logits, pred_instances):
  class MaskRCNNConvUpsampleHead (line 148) | class MaskRCNNConvUpsampleHead(nn.Module):
    method __init__ (line 153) | def __init__(self, cfg, input_shape: ShapeSpec):
    method forward (line 206) | def forward(self, x):
  function build_mask_head (line 218) | def build_mask_head(cfg, input_shape):

FILE: reference_code/GSNet-release/detectron2/modeling/roi_heads/roi_heads.py
  function smooth_l1_loss (line 41) | def smooth_l1_loss(pred, targets, beta=2.8):
  function euler_angles_to_rotation_matrix (line 64) | def euler_angles_to_rotation_matrix(car_rotation, is_dir=False):
  function build_roi_heads (line 91) | def build_roi_heads(cfg, input_shape):
  function select_foreground_proposals (line 99) | def select_foreground_proposals(proposals, bg_label):
  function select_proposals_with_visible_keypoints (line 129) | def select_proposals_with_visible_keypoints(proposals):
  class ROIHeads (line 174) | class ROIHeads(torch.nn.Module):
    method __init__ (line 184) | def __init__(self, cfg, input_shape: Dict[str, ShapeSpec]):
    method _sample_proposals (line 212) | def _sample_proposals(self, matched_idxs, matched_labels, gt_classes):
    method label_and_sample_proposals (line 250) | def label_and_sample_proposals(self, proposals, targets):
    method forward (line 335) | def forward(self, images, features, proposals, targets=None):
  class StandardROIHeads (line 366) | class StandardROIHeads(ROIHeads):
    method __init__ (line 378) | def __init__(self, cfg, input_shape):
    method _init_box_head (line 386) | def _init_box_head(self, cfg):
    method _init_mask_head (line 417) | def _init_mask_head(self, cfg):
    method _init_keypoint_head (line 440) | def _init_keypoint_head(self, cfg):
    method _init_3d_head (line 465) | def _init_3d_head(self, cfg):
    method _init_3d_mesh (line 524) | def _init_3d_mesh(self, cfg):
    method forward (line 552) | def forward(self, images, features, proposals, curr_iter, targets=None):
    method forward_with_given_boxes (line 571) | def forward_with_given_boxes(self, features, instances):
    method _forward_box (line 597) | def _forward_box(self, features, proposals):
    method _forward_mask (line 646) | def _forward_mask(self, features, instances):
    method _forward_keypoint (line 671) | def _forward_keypoint(self, features, instances):
    method _forward_3d_pose_inference (line 698) | def _forward_3d_pose_inference(self, roi_feature, box_pos, keypoint_po...

FILE: reference_code/GSNet-release/detectron2/modeling/roi_heads/rotated_fast_rcnn.py
  function fast_rcnn_inference_rotated (line 46) | def fast_rcnn_inference_rotated(
  function fast_rcnn_inference_single_image_rotated (line 83) | def fast_rcnn_inference_single_image_rotated(
  class RotatedFastRCNNOutputs (line 129) | class RotatedFastRCNNOutputs(FastRCNNOutputs):
    method inference (line 134) | def inference(self, score_thresh, nms_thresh, topk_per_image):
  class RROIHeads (line 154) | class RROIHeads(StandardROIHeads):
    method __init__ (line 160) | def __init__(self, cfg, input_shape: Dict[str, ShapeSpec]):
    method _init_box_head (line 169) | def _init_box_head(self, cfg):
    method label_and_sample_proposals (line 204) | def label_and_sample_proposals(self, proposals, targets):
    method _forward_box (line 265) | def _forward_box(self, features, proposals):

FILE: reference_code/GSNet-release/detectron2/modeling/sampling.py
  function subsample_labels (line 7) | def subsample_labels(labels, num_samples, positive_fraction, bg_label):

FILE: reference_code/GSNet-release/detectron2/modeling/test_time_augmentation.py
  class DatasetMapperTTA (line 21) | class DatasetMapperTTA:
    method __init__ (line 30) | def __init__(self, cfg):
    method __call__ (line 36) | def __call__(self, dataset_dict):
  class GeneralizedRCNNWithTTA (line 70) | class GeneralizedRCNNWithTTA(nn.Module):
    method __init__ (line 76) | def __init__(self, cfg, model, tta_mapper=None, batch_size=3):
    method _turn_off_roi_head (line 106) | def _turn_off_roi_head(self, attr):
    method _batch_inference (line 127) | def _batch_inference(self, batched_inputs, detected_instances=None, do...
    method __call__ (line 153) | def __call__(self, batched_inputs):
    method _inference_one_image (line 159) | def _inference_one_image(self, input):

FILE: reference_code/GSNet-release/detectron2/solver/build.py
  function build_optimizer (line 10) | def build_optimizer(cfg: CfgNode, model: torch.nn.Module) -> torch.optim...
  function build_lr_scheduler (line 34) | def build_lr_scheduler(

FILE: reference_code/GSNet-release/detectron2/solver/lr_scheduler.py
  class WarmupMultiStepLR (line 16) | class WarmupMultiStepLR(torch.optim.lr_scheduler._LRScheduler):
    method __init__ (line 17) | def __init__(
    method get_lr (line 38) | def get_lr(self) -> List[float]:
    method _compute_values (line 47) | def _compute_values(self) -> List[float]:
  class WarmupCosineLR (line 52) | class WarmupCosineLR(torch.optim.lr_scheduler._LRScheduler):
    method __init__ (line 53) | def __init__(
    method get_lr (line 68) | def get_lr(self) -> List[float]:
    method _compute_values (line 85) | def _compute_values(self) -> List[float]:
  function _get_warmup_factor_at_iter (line 90) | def _get_warmup_factor_at_iter(

FILE: reference_code/GSNet-release/detectron2/structures/boxes.py
  class BoxMode (line 14) | class BoxMode(Enum):
    method convert (line 36) | def convert(box: _RawBoxType, from_mode: "BoxMode", to_mode: "BoxMode"...
  class Boxes (line 118) | class Boxes:
    method __init__ (line 132) | def __init__(self, tensor: torch.Tensor):
    method clone (line 145) | def clone(self) -> "Boxes":
    method to (line 154) | def to(self, device: str) -> "Boxes":
    method area (line 157) | def area(self) -> torch.Tensor:
    method clip (line 168) | def clip(self, box_size: BoxSizeType) -> None:
    method nonempty (line 183) | def nonempty(self, threshold: int = 0) -> torch.Tensor:
    method __getitem__ (line 199) | def __getitem__(self, item: Union[int, slice, torch.BoolTensor]) -> "B...
    method __len__ (line 219) | def __len__(self) -> int:
    method __repr__ (line 222) | def __repr__(self) -> str:
    method inside_box (line 225) | def inside_box(self, box_size: BoxSizeType, boundary_threshold: int = ...
    method get_centers (line 244) | def get_centers(self) -> torch.Tensor:
    method scale (line 251) | def scale(self, scale_x: float, scale_y: float) -> None:
    method cat (line 259) | def cat(boxes_list: List["Boxes"]) -> "Boxes":
    method device (line 277) | def device(self) -> torch.device:
    method __iter__ (line 280) | def __iter__(self) -> Iterator[torch.Tensor]:
  function pairwise_iou (line 289) | def pairwise_iou(boxes1: Boxes, boxes2: Boxes) -> torch.Tensor:
  function matched_boxlist_iou (line 324) | def matched_boxlist_iou(boxes1: Boxes, boxes2: Boxes) -> torch.Tensor:

FILE: reference_code/GSNet-release/detectron2/structures/image_list.py
  class ImageList (line 8) | class ImageList(object):
    method __init__ (line 19) | def __init__(self, tensor: torch.Tensor, image_sizes: List[Tuple[int, ...
    method __len__ (line 28) | def __len__(self) -> int:
    method __getitem__ (line 31) | def __getitem__(self, idx: Union[int, slice]) -> torch.Tensor:
    method to (line 41) | def to(self, *args: Any, **kwargs: Any) -> "ImageList":
    method device (line 46) | def device(self) -> torch.device:
    method from_tensors (line 50) | def from_tensors(

FILE: reference_code/GSNet-release/detectron2/structures/instances.py
  class Instances (line 9) | class Instances:
    method __init__ (line 35) | def __init__(self, image_size: Tuple[int, int], **kwargs: Any):
    method image_size (line 47) | def image_size(self) -> Tuple[int, int]:
    method __setattr__ (line 54) | def __setattr__(self, name: str, val: Any) -> None:
    method __getattr__ (line 60) | def __getattr__(self, name: str) -> Any:
    method set (line 65) | def set(self, name: str, value: Any) -> None:
    method has (line 78) | def has(self, name: str) -> bool:
    method remove (line 85) | def remove(self, name: str) -> None:
    method get (line 91) | def get(self, name: str) -> Any:
    method get_fields (line 97) | def get_fields(self) -> Dict[str, Any]:
    method to (line 107) | def to(self, device: str) -> "Instances":
    method __getitem__ (line 119) | def __getitem__(self, item: Union[int, slice, torch.BoolTensor]) -> "I...
    method __len__ (line 133) | def __len__(self) -> int:
    method __iter__ (line 138) | def __iter__(self):
    method cat (line 142) | def cat(instance_lists: List["Instances"]) -> "Instances":
    method __str__ (line 173) | def __str__(self) -> str:
    method __repr__ (line 181) | def __repr__(self) -> str:

FILE: reference_code/GSNet-release/detectron2/structures/keypoints.py
  class Keypoints (line 9) | class Keypoints:
    method __init__ (line 21) | def __init__(self, keypoints: Union[torch.Tensor, np.ndarray, List[Lis...
    method __len__ (line 33) | def __len__(self) -> int:
    method to (line 36) | def to(self, *args: Any, **kwargs: Any) -> "Keypoints":
    method device (line 40) | def device(self) -> torch.device:
    method to_heatmap (line 43) | def to_heatmap(self, boxes: torch.Tensor, heatmap_size: int) -> torch....
    method __getitem__ (line 57) | def __getitem__(self, item: Union[int, slice, torch.BoolTensor]) -> "K...
    method __repr__ (line 75) | def __repr__(self) -> str:
  function _keypoints_to_heatmap (line 82) | def _keypoints_to_heatmap(
  function heatmaps_to_keypoints (line 142) | def heatmaps_to_keypoints(maps: torch.Tensor, rois: torch.Tensor) -> tor...

FILE: reference_code/GSNet-release/detectron2/structures/masks.py
  function polygon_area (line 15) | def polygon_area(x, y):
  function polygons_to_bitmask (line 21) | def polygons_to_bitmask(polygons: List[np.ndarray], height: int, width: ...
  function rasterize_polygons_within_box (line 36) | def rasterize_polygons_within_box(
  class BitMasks (line 89) | class BitMasks:
    method __init__ (line 98) | def __init__(self, tensor: Union[torch.Tensor, np.ndarray]):
    method to (line 109) | def to(self, device: str) -> "BitMasks":
    method device (line 113) | def device(self) -> torch.device:
    method __getitem__ (line 116) | def __getitem__(self, item: Union[int, slice, torch.BoolTensor]) -> "B...
    method __iter__ (line 139) | def __iter__(self) -> torch.Tensor:
    method __repr__ (line 142) | def __repr__(self) -> str:
    method __len__ (line 147) | def __len__(self) -> int:
    method nonempty (line 150) | def nonempty(self) -> torch.Tensor:
    method from_polygon_masks (line 161) | def from_polygon_masks(
    method crop_and_resize (line 174) | def crop_and_resize(self, boxes: torch.Tensor, mask_size: int) -> torc...
    method get_bounding_boxes (line 207) | def get_bounding_boxes(self) -> None:
    method cat (line 212) | def cat(bitmasks_list: List["BitMasks"]) -> "BitMasks":
  class PolygonMasks (line 230) | class PolygonMasks:
    method __init__ (line 238) | def __init__(self, polygons: List[List[Union[torch.Tensor, np.ndarray]...
    method to (line 279) | def to(self, *args: Any, **kwargs: Any) -> "PolygonMasks":
    method device (line 283) | def device(self) -> torch.device:
    method get_bounding_boxes (line 286) | def get_bounding_boxes(self) -> Boxes:
    method nonempty (line 303) | def nonempty(self) -> torch.Tensor:
    method __getitem__ (line 314) | def __getitem__(self, item: Union[int, slice, List[int], torch.BoolTen...
    method __iter__ (line 344) | def __iter__(self) -> Iterator[List[torch.Tensor]]:
    method __repr__ (line 352) | def __repr__(self) -> str:
    method __len__ (line 357) | def __len__(self) -> int:
    method crop_and_resize (line 360) | def crop_and_resize(self, boxes: torch.Tensor, mask_size: int) -> torc...
    method area (line 392) | def area(self):
    method cat (line 412) | def cat(polymasks_list: List["PolygonMasks"]) -> "PolygonMasks":

FILE: reference_code/GSNet-release/detectron2/structures/rotated_boxes.py
  class RotatedBoxes (line 12) | class RotatedBoxes(Boxes):
    method __init__ (line 21) | def __init__(self, tensor: torch.Tensor):
    method clone (line 222) | def clone(self) -> "RotatedBoxes":
    method to (line 231) | def to(self, device: str) -> "RotatedBoxes":
    method area (line 234) | def area(self) -> torch.Tensor:
    method normalize_angles (line 245) | def normalize_angles(self) -> None:
    method clip (line 251) | def clip(self, box_size: Boxes.BoxSizeType, clip_angle_threshold: floa...
    method nonempty (line 301) | def nonempty(self, threshold: int = 0) -> torch.Tensor:
    method __getitem__ (line 316) | def __getitem__(self, item: Union[int, slice, torch.BoolTensor]) -> "R...
    method __len__ (line 339) | def __len__(self) -> int:
    method __repr__ (line 342) | def __repr__(self) -> str:
    method inside_box (line 345) | def inside_box(self, box_size: Boxes.BoxSizeType, boundary_threshold: ...
    method get_centers (line 382) | def get_centers(self) -> torch.Tensor:
    method scale (line 389) | def scale(self, scale_x: float, scale_y: float) -> None:
    method cat (line 455) | def cat(boxes_list: List["RotatedBoxes"]) -> "RotatedBoxes":  # type: ...
    method device (line 473) | def device(self) -> str:
    method __iter__ (line 476) | def __iter__(self) -> Iterator[torch.Tensor]:
  function pairwise_iou (line 483) | def pairwise_iou(boxes1: RotatedBoxes, boxes2: RotatedBoxes) -> None:

FILE: reference_code/GSNet-release/detectron2/utils/collect_env.py
  function collect_torch_env (line 15) | def collect_torch_env():
  function get_env_module (line 27) | def get_env_module():
  function collect_env_info (line 32) | def collect_env_info():

FILE: reference_code/GSNet-release/detectron2/utils/colormap.py
  function colormap (line 95) | def colormap(rgb=False, maximum=255):
  function random_color (line 111) | def random_color(rgb=False, maximum=255):

FILE: reference_code/GSNet-release/detectron2/utils/comm.py
  function get_world_size (line 21) | def get_world_size() -> int:
  function get_rank (line 29) | def get_rank() -> int:
  function get_local_rank (line 37) | def get_local_rank() -> int:
  function get_local_size (line 50) | def get_local_size() -> int:
  function is_main_process (line 63) | def is_main_process() -> bool:
  function synchronize (line 67) | def synchronize():
  function _get_global_gloo_group (line 83) | def _get_global_gloo_group():
  function _serialize_to_tensor (line 94) | def _serialize_to_tensor(data, group):
  function _pad_to_largest_tensor (line 112) | def _pad_to_largest_tensor(tensor, group):
  function all_gather (line 139) | def all_gather(data, group=None):
  function gather (line 177) | def gather(data, dst=0, group=None):
  function shared_random_seed (line 220) | def shared_random_seed():
  function reduce_dict (line 234) | def reduce_dict(input_dict, average=True):

FILE: reference_code/GSNet-release/detectron2/utils/env.py
  function seed_all_rng (line 15) | def seed_all_rng(seed=None):
  function _import_file (line 36) | def _import_file(module_name, file_path, make_importable=False):
  function _configure_libraries (line 45) | def _configure_libraries():
  function setup_environment (line 70) | def setup_environment():
  function setup_custom_environment (line 92) | def setup_custom_environment(custom_module):

FILE: reference_code/GSNet-release/detectron2/utils/events.py
  function get_event_storage (line 15) | def get_event_storage():
  class EventWriter (line 27) | class EventWriter:
    method write (line 32) | def write(self):
    method close (line 35) | def close(self):
  class JSONWriter (line 39) | class JSONWriter(EventWriter):
    method __init__ (line 85) | def __init__(self, json_file, window_size=20):
    method write (line 95) | def write(self):
    method close (line 106) | def close(self):
  class TensorboardXWriter (line 110) | class TensorboardXWriter(EventWriter):
    method __init__ (line 115) | def __init__(self, log_dir: str, window_size: int = 20, **kwargs):
    method write (line 128) | def write(self):
    method close (line 138) | def close(self):
  class CommonMetricPrinter (line 143) | class CommonMetricPrinter(EventWriter):
    method __init__ (line 151) | def __init__(self, max_iter):
    method write (line 160) | def write(self):
  class EventStorage (line 209) | class EventStorage:
    method __init__ (line 216) | def __init__(self, start_iter=0):
    method put_image (line 228) | def put_image(self, img_name, img_tensor):
    method clear_images (line 242) | def clear_images(self):
    method put_scalar (line 249) | def put_scalar(self, name, value, smoothing_hint=True):
    method put_scalars (line 276) | def put_scalars(self, *, smoothing_hint=True, **kwargs):
    method history (line 287) | def history(self, name):
    method histories (line 297) | def histories(self):
    method latest (line 304) | def latest(self):
    method latest_with_smoothing_hint (line 311) | def latest_with_smoothing_hint(self, window_size=20):
    method smoothing_hints (line 325) | def smoothing_hints(self):
    method step (line 333) | def step(self):
    method vis_data (line 344) | def vis_data(self):
    method iter (line 348) | def iter(self):
    method iteration (line 352) | def iteration(self):
    method __enter__ (line 356) | def __enter__(self):
    method __exit__ (line 360) | def __exit__(self, exc_type, exc_val, exc_tb):
    method name_scope (line 365) | def name_scope(self, name):

FILE: reference_code/GSNet-release/detectron2/utils/logger.py
  class _ColorfulFormatter (line 13) | class _ColorfulFormatter(logging.Formatter):
    method __init__ (line 14) | def __init__(self, *args, **kwargs):
    method formatMessage (line 21) | def formatMessage(self, record):
  function setup_logger (line 34) | def setup_logger(
  function _cached_log_stream (line 95) | def _cached_log_stream(filename):
  function _find_caller (line 106) | def _find_caller():
  function log_first_n (line 127) | def log_first_n(lvl, msg, n=1, *, name=None, key="caller"):
  function log_every_n (line 162) | def log_every_n(lvl, msg, n=1, *, name=None):
  function log_every_n_seconds (line 178) | def log_every_n_seconds(lvl, msg, n=1, *, name=None):
  function create_small_table (line 196) | def create_small_table(small_dict):

FILE: reference_code/GSNet-release/detectron2/utils/memory.py
  function _ignore_torch_cuda_oom (line 12) | def _ignore_torch_cuda_oom():
  function retry_if_cuda_oom (line 26) | def retry_if_cuda_oom(func):

FILE: reference_code/GSNet-release/detectron2/utils/serialize.py
  class PicklableWrapper (line 5) | class PicklableWrapper(object):
    method __init__ (line 15) | def __init__(self, obj):
    method __reduce__ (line 18) | def __reduce__(self):
    method __call__ (line 22) | def __call__(self, *args, **kwargs):
    method __getattr__ (line 25) | def __getattr__(self, attr):

FILE: reference_code/GSNet-release/detectron2/utils/video_visualizer.py
  class _DetectedInstance (line 15) | class _DetectedInstance:
    method __init__ (line 31) | def __init__(self, label, bbox, mask_rle, color, ttl):
  class VideoVisualizer (line 39) | class VideoVisualizer:
    method __init__ (line 40) | def __init__(self, metadata, instance_mode=ColorMode.IMAGE):
    method draw_instance_predictions (line 53) | def draw_instance_predictions(self, frame, predictions):
    method draw_sem_seg (line 112) | def draw_sem_seg(self, frame, sem_seg, area_threshold=None):
    method draw_panoptic_seg_predictions (line 124) | def draw_panoptic_seg_predictions(
    method _assign_colors (line 180) | def _assign_colors(self, instances):

FILE: reference_code/GSNet-release/detectron2/utils/visualizer.py
  class ColorMode (line 34) | class ColorMode(Enum):
  class GenericMask (line 51) | class GenericMask:
    method __init__ (line 59) | def __init__(self, mask_or_polygons, height, width):
    method mask (line 88) | def mask(self):
    method polygons (line 94) | def polygons(self):
    method has_holes (line 100) | def has_holes(self):
    method mask_to_polygons (line 108) | def mask_to_polygons(self, mask):
    method polygons_to_mask (line 124) | def polygons_to_mask(self, polygons):
    method area (line 129) | def area(self):
    method bbox (line 132) | def bbox(self):
  class _PanopticPrediction (line 141) | class _PanopticPrediction:
    method __init__ (line 142) | def __init__(self, panoptic_seg, segments_info):
    method non_empty_mask (line 155) | def non_empty_mask(self):
    method semantic_masks (line 171) | def semantic_masks(self):
    method instance_masks (line 179) | def instance_masks(self):
  function _create_text_labels (line 189) | def _create_text_labels(classes, scores, class_names):
  class VisImage (line 210) | class VisImage:
    method __init__ (line 211) | def __init__(self, img, scale=1.0):
    method _setup_figure (line 222) | def _setup_figure(self, img):
    method save (line 249) | def save(self, filepath):
    method get_image (line 263) | def get_image(self):
  class Visualizer (line 310) | class Visualizer:
    method __init__ (line 311) | def __init__(self, img_rgb, metadata, scale=1.0, instance_mode=ColorMo...
    method draw_instance_predictions (line 332) | def draw_instance_predictions(self, predictions):
    method draw_sem_seg (line 382) | def draw_sem_seg(self, sem_seg, area_threshold=None, alpha=0.8):
    method draw_panoptic_seg_predictions (line 417) | def draw_panoptic_seg_predictions(
    method draw_dataset_dict (line 477) | def draw_dataset_dict(self, dic):
    method overlay_instances (line 518) | def overlay_instances(
    method overlay_rotated_instances (line 656) | def overlay_rotated_instances(self, boxes=None, labels=None, assigned_...
    method draw_and_connect_keypoints (line 695) | def draw_and_connect_keypoints(self, keypoints):
    method draw_text (line 762) | def draw_text(
    method draw_box (line 809) | def draw_box(self, box_coord, alpha=0.5, edge_color="g", line_style="-"):
    method draw_rotated_box_with_label (line 843) | def draw_rotated_box_with_label(
    method draw_circle (line 896) | def draw_circle(self, circle_coord, color, radius=3):
    method draw_line (line 914) | def draw_line(self, x_data, y_data, color, linestyle="-", linewidth=No...
    method draw_binary_mask (line 945) | def draw_binary_mask(
    method draw_polygon (line 1005) | def draw_polygon(self, segment, color, edge_color=None, alpha=0.5):
    method _jitter (line 1041) | def _jitter(self, color):
    method _create_grayscale_image (line 1060) | def _create_grayscale_image(self, mask=None):
    method _change_color_brightness (line 1071) | def _change_color_brightness(self, color, brightness_factor):
    method _convert_boxes (line 1096) | def _convert_boxes(self, boxes):
    method _convert_masks (line 1105) | def _convert_masks(self, masks_or_polygons):
    method _convert_keypoints (line 1128) | def _convert_keypoints(self, keypoints):
    method get_output (line 1134) | def get_output(self):

FILE: reference_code/GSNet-release/pytorch_toolbelt/inference/functional.py
  function torch_none (line 7) | def torch_none(x: Tensor):
  function torch_rot90_ (line 11) | def torch_rot90_(x: Tensor):
  function torch_rot90 (line 15) | def torch_rot90(x: Tensor):
  function torch_rot180 (line 19) | def torch_rot180(x: Tensor):
  function torch_rot270 (line 23) | def torch_rot270(x: Tensor):
  function torch_flipud (line 27) | def torch_flipud(x: Tensor):
  function torch_fliplr (line 36) | def torch_fliplr(x: Tensor):
  function torch_transpose (line 45) | def torch_transpose(x: Tensor):
  function torch_transpose_ (line 49) | def torch_transpose_(x: Tensor):
  function torch_transpose2 (line 53) | def torch_transpose2(x: Tensor):
  function pad_image_tensor (line 57) | def pad_image_tensor(image_tensor: Tensor, pad_size: int = 32):
  function unpad_image_tensor (line 104) | def unpad_image_tensor(image_tensor, pad):
  function unpad_xyxy_bboxes (line 110) | def unpad_xyxy_bboxes(bboxes_tensor: torch.Tensor, pad, dim=-1):

FILE: reference_code/GSNet-release/pytorch_toolbelt/inference/tiles.py
  function compute_pyramid_patch_weight_loss (line 12) | def compute_pyramid_patch_weight_loss(width, height) -> np.ndarray:
  class ImageSlicer (line 45) | class ImageSlicer:
    method __init__ (line 50) | def __init__(
    method split (line 163) | def split(self, image, border_type=cv2.BORDER_CONSTANT, value=0):
    method cut_patch (line 192) | def cut_patch(
    method target_shape (line 221) | def target_shape(self):
    method merge (line 228) | def merge(self, tiles: List[np.ndarray], dtype=np.float32):
    method crop_to_orignal_size (line 255) | def crop_to_orignal_size(self, image):
    method _mean (line 266) | def _mean(self, tile_size):
    method _pyramid (line 269) | def _pyramid(self, tile_size):
  class CudaTileMerger (line 274) | class CudaTileMerger:
    method __init__ (line 279) | def __init__(self, image_shape, channels, weight):
    method integrate_batch (line 294) | def integrate_batch(self, batch: torch.Tensor, crop_coords):
    method merge (line 309) | def merge(self) -> torch.Tensor:

FILE: reference_code/GSNet-release/pytorch_toolbelt/inference/tta.py
  function fliplr_image2label (line 26) | def fliplr_image2label(model: nn.Module, image: Tensor) -> Tensor:
  function fivecrop_image2label (line 39) | def fivecrop_image2label(model: nn.Module, image: Tensor, crop_size: Tup...
  function tencrop_image2label (line 93) | def tencrop_image2label(model: nn.Module, image: Tensor, crop_size: Tupl...
  function fliplr_image2mask (line 153) | def fliplr_image2mask(model: nn.Module, image: Tensor) -> Tensor:
  function d4_image2label (line 168) | def d4_image2label(model: nn.Module, image: Tensor) -> Tensor:
  function d4_image2mask (line 192) | def d4_image2mask(model: nn.Module, image: Tensor) -> Tensor:
  class TTAWrapper (line 224) | class TTAWrapper(nn.Module):
    method __init__ (line 225) | def __init__(self, model: nn.Module, tta_function, **kwargs):
    method forward (line 230) | def forward(self, *input):
  class MultiscaleTTAWrapper (line 234) | class MultiscaleTTAWrapper(nn.Module):
    method __init__ (line 239) | def __init__(self, model: nn.Module, scale_levels: List[float]):
    method forward (line 252) | def forward(self, input: Tensor) -> Tensor:

FILE: reference_code/GSNet-release/pytorch_toolbelt/losses/dice.py
  class DiceLoss (line 18) | class DiceLoss(_Loss):
    method __init__ (line 24) | def __init__(
    method forward (line 57) | def forward(self, y_pred: Tensor, y_true: Tensor) -> Tensor:

FILE: reference_code/GSNet-release/pytorch_toolbelt/losses/focal.py
  class BinaryFocalLoss (line 10) | class BinaryFocalLoss(_Loss):
    method __init__ (line 11) | def __init__(
    method forward (line 45) | def forward(self, label_input, label_target):
  class FocalLoss (line 61) | class FocalLoss(_Loss):
    method __init__ (line 62) | def __init__(self, alpha=0.5, gamma=2, ignore_index=None):
    method forward (line 75) | def forward(self, label_input, label_target):

FILE: reference_code/GSNet-release/pytorch_toolbelt/losses/functional.py
  function focal_loss_with_logits (line 16) | def focal_loss_with_logits(
  function reduced_focal_loss (line 81) | def reduced_focal_loss(
  function soft_jaccard_score (line 93) | def soft_jaccard_score(
  function soft_dice_score (line 125) | def soft_dice_score(
  function tversky_score (line 153) | def tversky_score(y_pred: torch.Tensor, y_true: torch.Tensor, alpha, smo...
  function wing_loss (line 169) | def wing_loss(

FILE: reference_code/GSNet-release/pytorch_toolbelt/losses/jaccard.py
  class JaccardLoss (line 18) | class JaccardLoss(_Loss):
    method __init__ (line 24) | def __init__(
    method forward (line 57) | def forward(self, y_pred: Tensor, y_true: Tensor) -> Tensor:

FILE: reference_code/GSNet-release/pytorch_toolbelt/losses/joint_loss.py
  class WeightedLoss (line 6) | class WeightedLoss(_Loss):
    method __init__ (line 11) | def __init__(self, loss, weight=1.0):
    method forward (line 16) | def forward(self, *input):
  class JointLoss (line 20) | class JointLoss(_Loss):
    method __init__ (line 21) | def __init__(self, first, second, first_weight=1.0, second_weight=1.0):
    method forward (line 26) | def forward(self, *input):

FILE: reference_code/GSNet-release/pytorch_toolbelt/losses/lovasz.py
  function _lovasz_grad (line 21) | def _lovasz_grad(gt_sorted):
  function _lovasz_hinge (line 35) | def _lovasz_hinge(logits, labels, per_image=True, ignore=None):
  function _lovasz_hinge_flat (line 55) | def _lovasz_hinge_flat(logits, labels):
  function _flatten_binary_scores (line 75) | def _flatten_binary_scores(scores, labels, ignore=None):
  function _lovasz_softmax (line 92) | def _lovasz_softmax(probas, labels, classes="present", per_image=False, ...
  function _lovasz_softmax_flat (line 117) | def _lovasz_softmax_flat(probas, labels, classes="present"):
  function _flatten_probas (line 148) | def _flatten_probas(probas, labels, ignore=None):
  function isnan (line 167) | def isnan(x):
  function mean (line 171) | def mean(values, ignore_nan=False, empty=0):
  class BinaryLovaszLoss (line 191) | class BinaryLovaszLoss(_Loss):
    method __init__ (line 192) | def __init__(self, per_image=False, ignore=None):
    method forward (line 197) | def forward(self, logits, target):
  class LovaszLoss (line 203) | class LovaszLoss(_Loss):
    method __init__ (line 204) | def __init__(self, per_image=False, ignore=None):
    method forward (line 209) | def forward(self, logits, target):

FILE: reference_code/GSNet-release/pytorch_toolbelt/losses/other_losses.py
  class BceLoss (line 9) | class BceLoss(_Loss):
    method __init__ (line 10) | def __init__(self, pos_weight=None):
    method forward (line 14) | def forward(self, logits, target):
  class TverskyLoss (line 22) | class TverskyLoss(_Loss):
    method __init__ (line 23) | def __init__(
    method forward (line 39) | def forward(self, y_pred: Tensor, y_true: Tensor) -> Tensor:
  class FocalTverskyLoss (line 77) | class FocalTverskyLoss(_Loss):
    method __init__ (line 78) | def __init__(
    method forward (line 94) | def forward(self, y_pred: Tensor, y_true: Tensor) -> Tensor:

FILE: reference_code/GSNet-release/pytorch_toolbelt/losses/wing_loss.py
  class WingLoss (line 8) | class WingLoss(_Loss):
    method __init__ (line 9) | def __init__(self, width=5, curvature=0.5, reduction="mean"):
    method forward (line 14) | def forward(self, prediction, target):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/abn.py
  class ABN (line 22) | class ABN(nn.Module):
    method __init__ (line 27) | def __init__(
    method reset_parameters (line 69) | def reset_parameters(self):
    method forward (line 76) | def forward(self, x):
    method __repr__ (line 109) | def __repr__(self):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/activations.py
  function swish (line 37) | def swish(x):
  function hard_sigmoid (line 41) | def hard_sigmoid(x, inplace=False):
  function hard_swish (line 45) | def hard_swish(x, inplace=False):
  class HardSigmoid (line 49) | class HardSigmoid(nn.Module):
    method __init__ (line 50) | def __init__(self, inplace=False):
    method forward (line 54) | def forward(self, x):
  class Swish (line 58) | class Swish(nn.Module):
    method __init__ (line 59) | def __init__(self, inplace=False):
    method forward (line 62) | def forward(self, x):
  class HardSwish (line 66) | class HardSwish(nn.Module):
    method __init__ (line 67) | def __init__(self, inplace=False):
    method forward (line 71) | def forward(self, x):
  function get_activation_module (line 75) | def get_activation_module(activation_name: str, **kwargs) -> nn.Module:

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/agn.py
  class AGN (line 23) | class AGN(nn.Module):
    method __init__ (line 28) | def __init__(
    method reset_parameters (line 67) | def reset_parameters(self):
    method forward (line 71) | def forward(self, x):
    method __repr__ (line 95) | def __repr__(self):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/backbone/efficient_net.py
  function round_filters (line 15) | def round_filters(filters, width_coefficient, depth_divisor, min_depth):
  function round_repeats (line 29) | def round_repeats(repeats: int, depth_multiplier):
  function drop_connect (line 38) | def drop_connect(inputs, p, training):
  class EfficientNetBlockArgs (line 55) | class EfficientNetBlockArgs:
    method __init__ (line 56) | def __init__(
    method scale (line 83) | def scale(
  class MBConvBlock (line 105) | class MBConvBlock(nn.Module):
    method __init__ (line 115) | def __init__(self, block_args: EfficientNetBlockArgs, abn_block: ABN, ...
    method reset_parameters (line 164) | def reset_parameters(self):
    method forward (line 178) | def forward(self, inputs, drop_connect_rate=None):
  function get_default_efficientnet_params (line 209) | def get_default_efficientnet_params(dropout=0.2, **kwargs):
  class EfficientNet (line 291) | class EfficientNet(nn.Module):
    method __init__ (line 301) | def __init__(
    method forward (line 376) | def forward(self, inputs):
  function efficient_net_b0 (line 404) | def efficient_net_b0(num_classes: int, **kwargs):
  function efficient_net_b1 (line 410) | def efficient_net_b1(num_classes: int, **kwargs):
  function efficient_net_b2 (line 416) | def efficient_net_b2(num_classes: int, **kwargs):
  function efficient_net_b3 (line 422) | def efficient_net_b3(num_classes: int, **kwargs):
  function efficient_net_b4 (line 428) | def efficient_net_b4(num_classes: int, **kwargs):
  function efficient_net_b5 (line 434) | def efficient_net_b5(num_classes: int, **kwargs):
  function efficient_net_b6 (line 440) | def efficient_net_b6(num_classes: int, **kwargs):
  function efficient_net_b7 (line 446) | def efficient_net_b7(num_classes: int, **kwargs):
  function test_efficient_net (line 452) | def test_efficient_net():
  function test_efficient_net_group_norm (line 480) | def test_efficient_net_group_norm():

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/backbone/inceptionv4.py
  class BasicConv2d (line 37) | class BasicConv2d(nn.Module):
    method __init__ (line 38) | def __init__(self, in_planes, out_planes, kernel_size, stride, padding...
    method forward (line 56) | def forward(self, x):
  class Mixed_3a (line 63) | class Mixed_3a(nn.Module):
    method __init__ (line 64) | def __init__(self):
    method forward (line 69) | def forward(self, x):
  class Mixed_4a (line 76) | class Mixed_4a(nn.Module):
    method __init__ (line 77) | def __init__(self):
    method forward (line 92) | def forward(self, x):
  class Mixed_5a (line 99) | class Mixed_5a(nn.Module):
    method __init__ (line 100) | def __init__(self):
    method forward (line 105) | def forward(self, x):
  class Inception_A (line 112) | class Inception_A(nn.Module):
    method __init__ (line 113) | def __init__(self):
    method forward (line 133) | def forward(self, x):
  class Reduction_A (line 142) | class Reduction_A(nn.Module):
    method __init__ (line 143) | def __init__(self):
    method forward (line 155) | def forward(self, x):
  class Inception_B (line 163) | class Inception_B(nn.Module):
    method __init__ (line 164) | def __init__(self):
    method forward (line 193) | def forward(self, x):
  class Reduction_B (line 202) | class Reduction_B(nn.Module):
    method __init__ (line 203) | def __init__(self):
    method forward (line 222) | def forward(self, x):
  class Inception_C (line 230) | class Inception_C(nn.Module):
    method __init__ (line 231) | def __init__(self):
    method forward (line 263) | def forward(self, x):
  class InceptionV4 (line 284) | class InceptionV4(nn.Module):
    method __init__ (line 285) | def __init__(self, num_classes=1001):
    method logits (line 319) | def logits(self, features):
    method forward (line 327) | def forward(self, input):
  function inceptionv4 (line 333) | def inceptionv4(num_classes=1000, pretrained="imagenet"):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/backbone/mobilenet.py
  function conv_bn (line 9) | def conv_bn(inp, oup, stride, activation: nn.Module):
  function conv_1x1_bn (line 17) | def conv_1x1_bn(inp, oup, activation: nn.Module):
  class InvertedResidual (line 25) | class InvertedResidual(nn.Module):
    method __init__ (line 26) | def __init__(self, inp, oup, stride, expand_ratio, activation: nn.Modu...
    method forward (line 63) | def forward(self, x):
  class MobileNetV2 (line 70) | class MobileNetV2(nn.Module):
    method __init__ (line 71) | def __init__(
    method forward (line 141) | def forward(self, x):
    method _initialize_weights (line 156) | def _initialize_weights(self):
  function test (line 172) | def test():

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/backbone/mobilenetv3.py
  function _make_divisible (line 14) | def _make_divisible(v, divisor, min_value=None):
  class SqEx (line 34) | class SqEx(nn.Module):
    method __init__ (line 39) | def __init__(self, n_features, reduction=4):
    method forward (line 54) | def forward(self, x):
  class LinearBottleneck (line 62) | class LinearBottleneck(nn.Module):
    method __init__ (line 63) | def __init__(
    method forward (line 115) | def forward(self, x):
  class LastBlockLarge (line 140) | class LastBlockLarge(nn.Module):
    method __init__ (line 141) | def __init__(self, inplanes, num_classes, expplanes1, expplanes2):
    method forward (line 160) | def forward(self, x):
  class LastBlockSmall (line 177) | class LastBlockSmall(nn.Module):
    method __init__ (line 178) | def __init__(self, inplanes, num_classes, expplanes1, expplanes2):
    method forward (line 201) | def forward(self, x):
  class MobileNetV3 (line 219) | class MobileNetV3(nn.Module):
    method __init__ (line 223) | def __init__(
    method _make_bottlenecks (line 318) | def _make_bottlenecks(self):
    method forward (line 352) | def forward(self, x):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/backbone/senet.py
  class SEModule (line 92) | class SEModule(nn.Module):
    method __init__ (line 93) | def __init__(self, channels, reduction):
    method forward (line 101) | def forward(self, x):
  class Bottleneck (line 111) | class Bottleneck(nn.Module):
    method forward (line 116) | def forward(self, x):
  class SEBottleneck (line 139) | class SEBottleneck(Bottleneck):
    method __init__ (line 146) | def __init__(self, inplanes, planes, groups, reduction, stride=1, down...
  class SEResNetBottleneck (line 168) | class SEResNetBottleneck(Bottleneck):
    method __init__ (line 177) | def __init__(self, inplanes, planes, groups, reduction, stride=1, down...
  class SEResNeXtBottleneck (line 195) | class SEResNeXtBottleneck(Bottleneck):
    method __init__ (line 202) | def __init__(
  class SENet (line 234) | class SENet(nn.Module):
    method __init__ (line 235) | def __init__(
    method _make_layer (line 363) | def _make_layer(
    method features (line 398) | def features(self, x):
    method logits (line 406) | def logits(self, x):
    method forward (line 414) | def forward(self, x):
  function initialize_pretrained_model (line 420) | def initialize_pretrained_model(model, num_classes, settings):
  function senet154 (line 434) | def senet154(num_classes=1000, pretrained="imagenet"):
  function se_resnet50 (line 449) | def se_resnet50(num_classes=1000, pretrained="imagenet"):
  function se_resnet101 (line 468) | def se_resnet101(num_classes=1000, pretrained="imagenet"):
  function se_resnet152 (line 487) | def se_resnet152(num_classes=1000, pretrained="imagenet"):
  function se_resnext50_32x4d (line 506) | def se_resnext50_32x4d(num_classes=1000, pretrained="imagenet"):
  function se_resnext101_32x4d (line 525) | def se_resnext101_32x4d(num_classes=1000, pretrained="imagenet"):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/backbone/wider_resnet.py
  class IdentityResidualBlock (line 12) | class IdentityResidualBlock(nn.Module):
    method __init__ (line 13) | def __init__(
    method forward (line 130) | def forward(self, x):
  class WiderResNet (line 144) | class WiderResNet(nn.Module):
    method __init__ (line 145) | def __init__(self, structure, norm_act=ABN, classes=0):
    method forward (line 216) | def forward(self, img):
  class WiderResNetA2 (line 232) | class WiderResNetA2(nn.Module):
    method __init__ (line 233) | def __init__(self, structure, norm_act=ABN, classes=0, dilation=False):
    method forward (line 332) | def forward(self, img):
  function wider_resnet_16 (line 348) | def wider_resnet_16(num_classes=0, norm_act=ABN):
  function wider_resnet_20 (line 354) | def wider_resnet_20(num_classes=0, norm_act=ABN):
  function wider_resnet_38 (line 360) | def wider_resnet_38(num_classes=0, norm_act=ABN):
  function wider_resnet_16_a2 (line 366) | def wider_resnet_16_a2(num_classes=0, norm_act=ABN):
  function wider_resnet_20_a2 (line 372) | def wider_resnet_20_a2(num_classes=0, norm_act=ABN):
  function wider_resnet_38_a2 (line 378) | def wider_resnet_38_a2(num_classes=0, norm_act=ABN):
  function test_wider_resnet (line 384) | def test_wider_resnet():

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/coord_conv.py
  function append_coords (line 9) | def append_coords(input_tensor, with_r=False):
  class AddCoords (line 49) | class AddCoords(nn.Module):
    method __init__ (line 50) | def __init__(self, with_r=False):
    method forward (line 54) | def forward(self, input_tensor):
  class CoordConv (line 62) | class CoordConv(nn.Module):
    method __init__ (line 63) | def __init__(self, in_channels, out_channels, with_r=False, **kwargs):
    method forward (line 71) | def forward(self, x):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/decoders.py
  class DecoderModule (line 7) | class DecoderModule(nn.Module):
    method __init__ (line 8) | def __init__(self):
    method forward (line 11) | def forward(self, features):
    method set_trainable (line 14) | def set_trainable(self, trainable):
  class UNetDecoder (line 19) | class UNetDecoder(DecoderModule):
    method __init__ (line 20) | def __init__(
    method forward (line 50) | def forward(self, features):
  class FPNDecoder (line 63) | class FPNDecoder(DecoderModule):
    method __init__ (line 64) | def __init__(
    method forward (line 132) | def forward(self, features):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/dropblock.py
  class DropBlock2D (line 6) | class DropBlock2D(nn.Module):
    method __init__ (line 22) | def __init__(self, drop_prob, block_size):
    method forward (line 28) | def forward(self, x):
    method _compute_block_mask (line 54) | def _compute_block_mask(self, mask):
    method _compute_gamma (line 72) | def _compute_gamma(self, x):
  class DropBlock3D (line 76) | class DropBlock3D(DropBlock2D):
    method __init__ (line 92) | def __init__(self, drop_prob, block_size):
    method forward (line 95) | def forward(self, x):
    method _compute_block_mask (line 122) | def _compute_block_mask(self, mask):
    method _compute_gamma (line 137) | def _compute_gamma(self, x):
  class DropBlockScheduled (line 141) | class DropBlockScheduled(nn.Module):
    method __init__ (line 142) | def __init__(self, dropblock, start_value, stop_value, nr_steps, start...
    method forward (line 150) | def forward(self, x):
    method step (line 155) | def step(self):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/dsconv.py
  class DepthwiseSeparableConv2d (line 6) | class DepthwiseSeparableConv2d(nn.Module):
    method __init__ (line 7) | def __init__(
    method forward (line 33) | def forward(self, x):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/encoders.py
  function _take (line 93) | def _take(elements, indexes):
  class EncoderModule (line 97) | class EncoderModule(nn.Module):
    method __init__ (line 98) | def __init__(self, channels: List[int], strides: List[int],
    method forward (line 108) | def forward(self, x):
    method output_strides (line 119) | def output_strides(self) -> List[int]:
    method output_filters (line 123) | def output_filters(self) -> List[int]:
    method encoder_layers (line 127) | def encoder_layers(self):
    method set_trainable (line 130) | def set_trainable(self, trainable):
  class ResnetEncoder (line 135) | class ResnetEncoder(EncoderModule):
    method __init__ (line 136) | def __init__(self, resnet, filters, strides, layers=None):
    method encoder_layers (line 155) | def encoder_layers(self):
    method forward (line 159) | def forward(self, x):
  class Resnet18Encoder (line 175) | class Resnet18Encoder(ResnetEncoder):
    method __init__ (line 176) | def __init__(self, pretrained=True, layers=None):
  class Resnet34Encoder (line 185) | class Resnet34Encoder(ResnetEncoder):
    method __init__ (line 186) | def __init__(self, pretrained=True, layers=None):
  class Resnet50Encoder (line 195) | class Resnet50Encoder(ResnetEncoder):
    method __init__ (line 196) | def __init__(self, pretrained=True, layers=None):
  class Resnet101Encoder (line 205) | class Resnet101Encoder(ResnetEncoder):
    method __init__ (line 206) | def __init__(self, pretrained=True, layers=None):
  class Resnet152Encoder (line 215) | class Resnet152Encoder(ResnetEncoder):
    method __init__ (line 216) | def __init__(self, pretrained=True, layers=None):
  class SEResnetEncoder (line 225) | class SEResnetEncoder(EncoderModule):
    method __init__ (line 230) | def __init__(self, seresnet: SENet, channels, strides, layers=None):
    method encoder_layers (line 248) | def encoder_layers(self):
    method output_strides (line 253) | def output_strides(self):
    method output_filters (line 257) | def output_filters(self):
    method forward (line 260) | def forward(self, x):
  class SEResnet50Encoder (line 276) | class SEResnet50Encoder(SEResnetEncoder):
    method __init__ (line 277) | def __init__(self, pretrained=True, layers=None):
  class SEResnet101Encoder (line 283) | class SEResnet101Encoder(SEResnetEncoder):
    method __init__ (line 284) | def __init__(self, pretrained=True, layers=None):
  class SEResnet152Encoder (line 290) | class SEResnet152Encoder(SEResnetEncoder):
    method __init__ (line 291) | def __init__(self, pretrained=True, layers=None):
  class SENet154Encoder (line 297) | class SENet154Encoder(SEResnetEncoder):
    method __init__ (line 298) | def __init__(self, pretrained=True, layers=None):
  class SEResNeXt50Encoder (line 304) | class SEResNeXt50Encoder(SEResnetEncoder):
    method __init__ (line 305) | def __init__(self, pretrained=True, layers=None):
  class SEResNeXt101Encoder (line 312) | class SEResNeXt101Encoder(SEResnetEncoder):
    method __init__ (line 313) | def __init__(self, pretrained=True, layers=None):
  class SqueezenetEncoder (line 320) | class SqueezenetEncoder(EncoderModule):
    method __init__ (line 321) | def __init__(self, pretrained=True, layers=[1, 2, 3]):
    method encoder_layers (line 367) | def encoder_layers(self):
  class MobilenetV2Encoder (line 371) | class MobilenetV2Encoder(EncoderModule):
    method __init__ (line 372) | def __init__(self, layers=[2, 3, 5, 7], activation="relu6"):
    method encoder_layers (line 389) | def encoder_layers(self):
  class MobilenetV3Encoder (line 402) | class MobilenetV3Encoder(EncoderModule):
    method __init__ (line 403) | def __init__(
    method forward (line 426) | def forward(self, x):
    method encoder_layers (line 452) | def encoder_layers(self):
  class WiderResnetEncoder (line 457) | class WiderResnetEncoder(EncoderModule):
    method __init__ (line 458) | def __init__(self, structure: List[int], layers: List[int], norm_act=A...
    method encoder_layers (line 480) | def encoder_layers(self):
    method forward (line 491) | def forward(self, input):
  class WiderResnet16Encoder (line 519) | class WiderResnet16Encoder(WiderResnetEncoder):
    method __init__ (line 520) | def __init__(self, layers=None):
  class WiderResnet20Encoder (line 526) | class WiderResnet20Encoder(WiderResnetEncoder):
    method __init__ (line 527) | def __init__(self, layers=None):
  class WiderResnet38Encoder (line 533) | class WiderResnet38Encoder(WiderResnetEncoder):
    method __init__ (line 534) | def __init__(self, layers=None):
  class WiderResnetA2Encoder (line 540) | class WiderResnetA2Encoder(EncoderModule):
    method __init__ (line 541) | def __init__(self, structure: List[int], layers: List[int], norm_act=A...
    method encoder_layers (line 561) | def encoder_layers(self):
    method forward (line 572) | def forward(self, input):
  class WiderResnet16A2Encoder (line 600) | class WiderResnet16A2Encoder(WiderResnetA2Encoder):
    method __init__ (line 601) | def __init__(self, layers=None):
  class WiderResnet20A2Encoder (line 607) | class WiderResnet20A2Encoder(WiderResnetA2Encoder):
    method __init__ (line 608) | def __init__(self, layers=None):
  class WiderResnet38A2Encoder (line 614) | class WiderResnet38A2Encoder(WiderResnetA2Encoder):
    method __init__ (line 615) | def __init__(self, layers=None):
  class DenseNetEncoder (line 621) | class DenseNetEncoder(EncoderModule):
    method __init__ (line 622) | def __init__(
    method encoder_layers (line 668) | def encoder_layers(self):
    method output_strides (line 673) | def output_strides(self):
    method output_filters (line 677) | def output_filters(self):
    method forward (line 680) | def forward(self, x):
  class DenseNet121Encoder (line 699) | class DenseNet121Encoder(DenseNetEncoder):
    method __init__ (line 700) | def __init__(
  class DenseNet161Encoder (line 711) | class DenseNet161Encoder(DenseNetEncoder):
    method __init__ (line 712) | def __init__(
  class DenseNet169Encoder (line 723) | class DenseNet169Encoder(DenseNetEncoder):
    method __init__ (line 724) | def __init__(
  class DenseNet201Encoder (line 735) | class DenseNet201Encoder(DenseNetEncoder):
    method __init__ (line 736) | def __init__(
  class EfficientNetEncoder (line 747) | class EfficientNetEncoder(EncoderModule):
    method __init__ (line 748) | def __init__(self, efficientnet, filters, strides, layers):
    method encoder_layers (line 765) | def encoder_layers(self):
    method forward (line 776) | def forward(self, x):
  class EfficientNetB0Encoder (line 789) | class EfficientNetB0Encoder(EfficientNetEncoder):
    method __init__ (line 790) | def __init__(self, layers=None, **kwargs):
  class EfficientNetB1Encoder (line 799) | class EfficientNetB1Encoder(EfficientNetEncoder):
    method __init__ (line 800) | def __init__(self, layers=None, **kwargs):
  class EfficientNetB2Encoder (line 809) | class EfficientNetB2Encoder(EfficientNetEncoder):
    method __init__ (line 810) | def __init__(self, layers=None, **kwargs):
  class EfficientNetB3Encoder (line 819) | class EfficientNetB3Encoder(EfficientNetEncoder):
    method __init__ (line 820) | def __init__(self, layers=None, **kwargs):
  class EfficientNetB4Encoder (line 829) | class EfficientNetB4Encoder(EfficientNetEncoder):
    method __init__ (line 830) | def __init__(self, layers=None, **kwargs):
  class EfficientNetB5Encoder (line 839) | class EfficientNetB5Encoder(EfficientNetEncoder):
    method __init__ (line 840) | def __init__(self, layers=None, **kwargs):
  class EfficientNetB6Encoder (line 849) | class EfficientNetB6Encoder(EfficientNetEncoder):
    method __init__ (line 850) | def __init__(self, layers=None, **kwargs):
  class EfficientNetB7Encoder (line 859) | class EfficientNetB7Encoder(EfficientNetEncoder):
    method __init__ (line 860) | def __init__(self, layers=None, **kwargs):
  class InceptionV4Encoder (line 869) | class InceptionV4Encoder(EncoderModule):
    method __init__ (line 870) | def __init__(self, pretrained=True, layers=None, **kwargs):
    method forward (line 888) | def forward(self, x):
    method encoder_layers (line 900) | def encoder_layers(self):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/fpn.py
  class FPNBottleneckBlock (line 18) | class FPNBottleneckBlock(nn.Module):
    method __init__ (line 19) | def __init__(self, input_channels, output_channels):
    method forward (line 23) | def forward(self, x):
  class FPNBottleneckBlockBN (line 28) | class FPNBottleneckBlockBN(nn.Module):
    method __init__ (line 29) | def __init__(self, input_channels, output_channels):
    method forward (line 36) | def forward(self, x):
  class FPNPredictionBlock (line 41) | class FPNPredictionBlock(nn.Module):
    method __init__ (line 42) | def __init__(self, input_channels, output_channels, mode="nearest"):
    method forward (line 51) | def forward(self, x, y=None):
  class UpsampleAdd (line 64) | class UpsampleAdd(nn.Module):
    method __init__ (line 69) | def __init__(
    method forward (line 77) | def forward(self, x, y=None):
  class UpsampleAddConv (line 99) | class UpsampleAddConv(nn.Module):
    method __init__ (line 105) | def __init__(
    method forward (line 114) | def forward(self, x, y=None):
  class FPNFuse (line 137) | class FPNFuse(nn.Module):
    method __init__ (line 138) | def __init__(self, mode="bilinear", align_corners=False):
    method forward (line 143) | def forward(self, features):
  class FPNFuseSum (line 157) | class FPNFuseSum(nn.Module):
    method __init__ (line 160) | def __init__(self, mode="bilinear", align_corners=False):
    method forward (line 165) | def forward(self, features):
  class HFF (line 177) | class HFF(nn.Module):
    method __init__ (line 185) | def __init__(
    method forward (line 194) | def forward(self, features):
    method _upsample (line 210) | def _upsample(self, x, output_size=None):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/identity.py
  class Identity (line 6) | class Identity(nn.Module):
    method __init__ (line 9) | def __init__(self, *args, **kwargs):
    method forward (line 12) | def forward(self, x):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/pooling.py
  class GlobalAvgPool2d (line 17) | class GlobalAvgPool2d(nn.Module):
    method __init__ (line 18) | def __init__(self, flatten=False):
    method forward (line 23) | def forward(self, x):
  class GlobalMaxPool2d (line 30) | class GlobalMaxPool2d(nn.Module):
    method __init__ (line 31) | def __init__(self, flatten=False):
    method forward (line 36) | def forward(self, x):
  class GWAP (line 43) | class GWAP(nn.Module):
    method __init__ (line 48) | def __init__(self, features):
    method fscore (line 52) | def fscore(self, x):
    method norm (line 57) | def norm(self, x: torch.Tensor):
    method forward (line 60) | def forward(self, x):
  class RMSPool (line 69) | class RMSPool(nn.Module):
    method __init__ (line 74) | def __init__(self):
    method forward (line 78) | def forward(self, x):
  class MILCustomPoolingModule (line 84) | class MILCustomPoolingModule(nn.Module):
    method __init__ (line 85) | def __init__(self, in_channels, out_channels, reduction=4):
    method forward (line 96) | def forward(self, x):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/scse.py
  class ChannelGate2d (line 20) | class ChannelGate2d(nn.Module):
    method __init__ (line 25) | def __init__(self, channels):
    method forward (line 29) | def forward(self, x: Tensor):
  class SpatialGate2d (line 36) | class SpatialGate2d(nn.Module):
    method __init__ (line 41) | def __init__(self, channels, reduction=None, squeeze_channels=None):
    method reset_parameters (line 65) | def reset_parameters(self):
    method forward (line 69) | def forward(self, x: Tensor):
  class ChannelSpatialGate2d (line 80) | class ChannelSpatialGate2d(nn.Module):
    method __init__ (line 85) | def __init__(self, channels, reduction=4):
    method forward (line 90) | def forward(self, x):
  class SpatialGate2dV2 (line 94) | class SpatialGate2dV2(nn.Module):
    method __init__ (line 99) | def __init__(self, channels, reduction=4):
    method forward (line 108) | def forward(self, x: Tensor):
  class ChannelSpatialGate2dV2 (line 119) | class ChannelSpatialGate2dV2(nn.Module):
    method __init__ (line 120) | def __init__(self, channels, reduction=4):
    method forward (line 125) | def forward(self, x):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/srm.py
  class SRMLayer (line 5) | class SRMLayer(nn.Module):
    method __init__ (line 11) | def __init__(self, channels: int):
    method forward (line 20) | def forward(self, x):

FILE: reference_code/GSNet-release/pytorch_toolbelt/modules/unet.py
  class UnetEncoderBlock (line 10) | class UnetEncoderBlock(nn.Module):
    method __init__ (line 11) | def __init__(
    method forward (line 42) | def forward(self, x):
  class UnetCentralBlock (line 50) | class UnetCentralBlock(nn.Module):
    method __init__ (line 51) | def __init__(
    method forward (line 70) | def forward(self, x):
  class UnetDecoderBlock (line 78) | class UnetDecoderBlock(nn.Module):
    method __init__ (line 82) | def __init__(
    method forward (line 119) | def forward(self, x, enc):

FILE: reference_code/GSNet-release/pytorch_toolbelt/optimization/functional.py
  function get_lr_decay_parameters (line 1) | def get_lr_decay_parameters(parameters, learning_rate, groups: dict):

FILE: reference_code/GSNet-release/pytorch_toolbelt/optimization/lr_schedules.py
  function set_learning_rate (line 8) | def set_learning_rate(optimizer, lr):
  class OnceCycleLR (line 13) | class OnceCycleLR(_LRScheduler):
    method __init__ (line 14) | def __init__(self, optimizer, epochs, min_lr_factor=0.05, max_lr=1.0):
    method get_lr (line 24) | def get_lr(self):
  class CosineAnnealingLRWithDecay (line 30) | class CosineAnnealingLRWithDecay(_LRScheduler):
    method __init__ (line 56) | def __init__(self, optimizer, T_max, gamma, eta_min=0, last_epoch=-1):
    method get_lr (line 62) | def get_lr(self):

FILE: reference_code/GSNet-release/pytorch_toolbelt/utils/catalyst/criterions.py
  class LPRegularizationCallback (line 10) | class LPRegularizationCallback(CriterionCallback):
    method __init__ (line 15) | def __init__(
    method get_multiplier (line 49) | def get_multiplier(self, training_progress, schedule, start, end):
    method on_loader_start (line 67) | def on_loader_start(self, state: RunnerState):
    method on_epoch_start (line 74) | def on_epoch_start(self, state: RunnerState):
    method on_batch_end (line 80) | def on_batch_end(self, state: RunnerState):

FILE: reference_code/GSNet-release/pytorch_toolbelt/utils/catalyst/metrics.py
  function pixel_accuracy (line 30) | def pixel_accuracy(outputs: torch.Tensor, targets: torch.Tensor, ignore_...
  class PixelAccuracyCallback (line 48) | class PixelAccuracyCallback(MetricCallback):
    method __init__ (line 52) | def __init__(
  class ConfusionMatrixCallback (line 74) | class ConfusionMatrixCallback(Callback):
    method __init__ (line 80) | def __init__(
    method on_loader_start (line 104) | def on_loader_start(self, state):
    method on_batch_end (line 108) | def on_batch_end(self, state: RunnerState):
    method on_loader_end (line 122) | def on_loader_end(self, state):
  class MacroF1Callback (line 147) | class MacroF1Callback(Callback):
    method __init__ (line 152) | def __init__(
    method on_batch_end (line 176) | def on_batch_end(self, state: RunnerState):
    method on_loader_start (line 197) | def on_loader_start(self, state):
    method on_loader_end (line 201) | def on_loader_end(self, state):
  function binary_dice_iou_score (line 210) | def binary_dice_iou_score(
  function multiclass_dice_iou_score (line 254) | def multiclass_dice_iou_score(
  function multilabel_dice_iou_score (line 284) | def multilabel_dice_iou_score(
  class IoUMetricsCallback (line 313) | class IoUMetricsCallback(Callback):
    method __init__ (line 319) | def __init__(
    method on_loader_start (line 387) | def on_loader_start(self, state):
    method on_batch_end (line 391) | def on_batch_end(self, state: RunnerState):
    method on_loader_end (line 407) | def on_loader_end(self, state):

FILE: reference_code/GSNet-release/pytorch_toolbelt/utils/catalyst/visualization.py
  function get_tensorboard_logger (line 23) | def get_tensorboard_logger(state: RunnerState) -> SummaryWriter:
  class ShowPolarBatchesCallback (line 30) | class ShowPolarBatchesCallback(Callback):
    method __init__ (line 35) | def __init__(
    method to_cpu (line 76) | def to_cpu(self, data):
    method on_loader_start (line 87) | def on_loader_start(self, state):
    method on_batch_end (line 96) | def on_batch_end(self, state: RunnerState):
    method on_loader_end (line 114) | def on_loader_end(self, state: RunnerState) -> None:
    method _log_samples (line 125) | def _log_samples(self, samples, name, logger, step):
  function draw_binary_segmentation_predictions (line 143) | def draw_binary_segmentation_predictions(
  function draw_semantic_segmentation_predictions (line 196) | def draw_semantic_segmentation_predictions(

FILE: reference_code/GSNet-release/pytorch_toolbelt/utils/dataset_utils.py
  class ImageMaskDataset (line 12) | class ImageMaskDataset(Dataset):
    method __init__ (line 13) | def __init__(
    method __len__ (line 42) | def __len__(self):
    method __getitem__ (line 45) | def __getitem__(self, index):
  class TiledSingleImageDataset (line 58) | class TiledSingleImageDataset(Dataset):
    method __init__ (line 59) | def __init__(
    method _get_image (line 104) | def _get_image(self, index):
    method _get_mask (line 112) | def _get_mask(self, index):
    method __len__ (line 120) | def __len__(self):
    method __getitem__ (line 123) | def __getitem__(self, index):
  class TiledImageMaskDataset (line 135) | class TiledImageMaskDataset(ConcatDataset):
    method __init__ (line 136) | def __init__(

FILE: reference_code/GSNet-release/pytorch_toolbelt/utils/fs.py
  function has_image_ext (line 12) | def has_image_ext(fname: str) -> bool:
  function find_in_dir (line 17) | def find_in_dir(dirname: str):
  function find_images_in_dir (line 21) | def find_images_in_dir(dirname: str):
  function find_in_dir_glob (line 25) | def find_in_dir_glob(dirname: str, recursive=False):
  function id_from_fname (line 30) | def id_from_fname(fname: str):
  function change_extension (line 34) | def change_extension(fname: str, new_ext: str):
  function auto_file (line 38) | def auto_file(filename: str, where: str = ".") -> str:
  function read_rgb_image (line 67) | def read_rgb_image(fname: str) -> np.ndarray:
  function read_image_as_is (line 83) | def read_image_as_is(fname: str) -> np.ndarray:

FILE: reference_code/GSNet-release/pytorch_toolbelt/utils/namesgenerator.py
  function get_random_name (line 567) | def get_random_name(sep="_"):

FILE: reference_code/GSNet-release/pytorch_toolbelt/utils/random.py
  function set_manual_seed (line 10) | def set_manual_seed(seed):
  function get_rng_state (line 19) | def get_rng_state() -> dict:
  function set_rng_state (line 27) | def set_rng_state(rng_state: dict):
  function get_random_name (line 50) | def get_random_name() -> str:

FILE: reference_code/GSNet-release/pytorch_toolbelt/utils/rle.py
  function rle_encode (line 6) | def rle_encode(mask: np.ndarray):
  function rle_to_string (line 27) | def rle_to_string(runs) -> str:
  function rle_decode (line 31) | def rle_decode(rle_str, shape, dtype) -> np.ndarray:

FILE: reference_code/GSNet-release/pytorch_toolbelt/utils/torch_utils.py
  function set_trainable (line 13) | def set_trainable(module: nn.Module, trainable=True, freeze_bn=True):
  function freeze_bn (line 39) | def freeze_bn(module: nn.Module):
  function logit (line 46) | def logit(x: torch.Tensor, eps=1e-5):
  function count_parameters (line 51) | def count_parameters(model: nn.Module) -> Tuple[int, int]:
  function to_numpy (line 62) | def to_numpy(x) -> np.ndarray:
  function to_tensor (line 78) | def to_tensor(x, dtype=None) -> torch.Tensor:
  function tensor_from_rgb_image (line 98) | def tensor_from_rgb_image(image: np.ndarray) -> torch.Tensor:
  function tensor_from_mask_image (line 105) | def tensor_from_mask_image(mask: np.ndarray) -> torch.Tensor:
  function rgb_image_from_tensor (line 111) | def rgb_image_from_tensor(
  function maybe_cuda (line 121) | def maybe_cuda(x):
  function get_optimizable_parameters (line 127) | def get_optimizable_parameters(model: nn.Module):
  function transfer_weights (line 136) | def transfer_weights(model: nn.Module, model_state_dict: collections.Ord...

FILE: reference_code/GSNet-release/pytorch_toolbelt/utils/visualization.py
  function plot_confusion_matrix (line 9) | def plot_confusion_matrix(
  function render_figure_to_tensor (line 67) | def render_figure_to_tensor(figure):

FILE: reference_code/GSNet-release/setup.py
  function get_version (line 17) | def get_version():
  function get_extensions (line 39) | def get_extensions():
  function get_model_zoo_configs (line 86) | def get_model_zoo_configs() -> List[str]:

FILE: reference_code/roi_heads.py
  function smooth_l1_loss (line 41) | def smooth_l1_loss(pred, targets, beta=2.8):
  function euler_angles_to_rotation_matrix (line 64) | def euler_angles_to_rotation_matrix(car_rotation, is_dir=False):
  function build_roi_heads (line 91) | def build_roi_heads(cfg, input_shape):
  function select_foreground_proposals (line 99) | def select_foreground_proposals(proposals, bg_label):
  function select_proposals_with_visible_keypoints (line 129) | def select_proposals_with_visible_keypoints(proposals):
  class ROIHeads (line 174) | class ROIHeads(torch.nn.Module):
    method __init__ (line 184) | def __init__(self, cfg, input_shape: Dict[str, ShapeSpec]):
    method _sample_proposals (line 212) | def _sample_proposals(self, matched_idxs, matched_labels, gt_classes):
    method label_and_sample_proposals (line 250) | def label_and_sample_proposals(self, proposals, targets):
    method forward (line 335) | def forward(self, images, features, proposals, targets=None):
  class StandardROIHeads (line 366) | class StandardROIHeads(ROIHeads):
    method __init__ (line 378) | def __init__(self, cfg, input_shape):
    method _init_box_head (line 386) | def _init_box_head(self, cfg):
    method _init_mask_head (line 417) | def _init_mask_head(self, cfg):
    method _init_keypoint_head (line 440) | def _init_keypoint_head(self, cfg):
    method _init_3d_head (line 465) | def _init_3d_head(self, cfg):
    method _init_3d_mesh (line 524) | def _init_3d_mesh(self, cfg):
    method forward (line 552) | def forward(self, images, features, proposals, curr_iter, targets=None):
    method forward_with_given_boxes (line 571) | def forward_with_given_boxes(self, features, instances):
    method _forward_box (line 597) | def _forward_box(self, features, proposals):
    method _forward_mask (line 646) | def _forward_mask(self, features, instances):
    method _forward_keypoint (line 671) | def _forward_keypoint(self, features, instances):
    method _forward_3d_pose_inference (line 698) | def _forward_3d_pose_inference(self, roi_feature, box_pos, keypoint_po...