SYMBOL INDEX (224 symbols across 33 files)

FILE: adapteacher/checkpoint/detection_checkpoint.py
  class DetectionTSCheckpointer (line 10) | class DetectionTSCheckpointer(DetectionCheckpointer):
    method _load_model (line 11) | def _load_model(self, checkpoint):
    method _load_student_model (line 66) | def _load_student_model(self, checkpoint: Any) -> _IncompatibleKeys:  ...

FILE: adapteacher/config.py
  function add_ateacher_config (line 5) | def add_ateacher_config(cfg):

FILE: adapteacher/data/build.py
  function divide_label_unlabel (line 34) | def divide_label_unlabel(
  function build_detection_semisup_train_loader (line 61) | def build_detection_semisup_train_loader(cfg, mapper=None):
  function build_detection_test_loader (line 118) | def build_detection_test_loader(cfg, dataset_name, mapper=None):
  function build_detection_semisup_train_loader_two_crops (line 148) | def build_detection_semisup_train_loader_two_crops(cfg, mapper=None):
  function build_semisup_batch_data_loader_two_crop (line 222) | def build_semisup_batch_data_loader_two_crop(

FILE: adapteacher/data/common.py
  class MapDatasetTwoCrop (line 6) | class MapDatasetTwoCrop(MapDataset):
    method __getitem__ (line 21) | def __getitem__(self, idx):
  class AspectRatioGroupedDatasetTwoCrop (line 45) | class AspectRatioGroupedDatasetTwoCrop(AspectRatioGroupedDataset):
    method __init__ (line 58) | def __init__(self, dataset, batch_size):
    method __iter__ (line 72) | def __iter__(self):
  class AspectRatioGroupedSemiSupDatasetTwoCrop (line 92) | class AspectRatioGroupedSemiSupDatasetTwoCrop(AspectRatioGroupedDataset):
    method __init__ (line 105) | def __init__(self, dataset, batch_size):
    method __iter__ (line 125) | def __iter__(self):

FILE: adapteacher/data/dataset_mapper.py
  class DatasetMapperTwoCropSeparate (line 14) | class DatasetMapperTwoCropSeparate(DatasetMapper):
    method __init__ (line 35) | def __init__(self, cfg, is_train=True):
    method __call__ (line 73) | def __call__(self, dataset_dict):

FILE: adapteacher/data/datasets/builtin.py
  function register_coco_unlabel (line 31) | def register_coco_unlabel(root):
  function register_coco_unlabel_instances (line 40) | def register_coco_unlabel_instances(name, metadata, json_file, image_root):
  function load_coco_unlabel_json (line 73) | def load_coco_unlabel_json(
  function register_all_cityscapes_foggy (line 124) | def register_all_cityscapes_foggy(root):
  function register_all_clipart (line 156) | def register_all_clipart(root):
  function register_all_water (line 169) | def register_all_water(root):

FILE: adapteacher/data/datasets/cityscapes_foggy.py
  function _get_cityscapes_files (line 28) | def _get_cityscapes_files(image_dir, gt_dir):
  function load_cityscapes_instances (line 59) | def load_cityscapes_instances(image_dir, gt_dir, from_json=True, to_poly...
  function load_cityscapes_semantic (line 102) | def load_cityscapes_semantic(image_dir, gt_dir):
  function _cityscapes_files_to_dict (line 135) | def _cityscapes_files_to_dict(files, from_json, to_polygons):

FILE: adapteacher/data/detection_utils.py
  function build_strong_augmentation (line 9) | def build_strong_augmentation(cfg, is_train):

FILE: adapteacher/data/transforms/augmentation_impl.py
  class GaussianBlur (line 6) | class GaussianBlur:
    method __init__ (line 15) | def __init__(self, sigma=[0.1, 2.0]):
    method __call__ (line 18) | def __call__(self, x):

FILE: adapteacher/engine/hooks.py
  class LossEvalHook (line 10) | class LossEvalHook(HookBase):
    method __init__ (line 11) | def __init__(self, eval_period, model, data_loader, model_output, mode...
    method _do_loss_eval (line 18) | def _do_loss_eval(self):
    method _get_loss (line 56) | def _get_loss(self, data, model):
    method _write_losses (line 73) | def _write_losses(self, metrics_dict):
    method _detect_anomaly (line 92) | def _detect_anomaly(self, losses, loss_dict):
    method after_step (line 100) | def after_step(self):
  function inference_context (line 108) | def inference_context(model):

FILE: adapteacher/engine/probe.py
  class OpenMatchTrainerProbe (line 4) | class OpenMatchTrainerProbe:
    method __init__ (line 5) | def __init__(self, cfg):
    method bbox_stat (line 10) | def bbox_stat(self, unlabel_gt, unlabel_pseudo, name, bbox_stat_list):
    method compute_fp_gtoutlier (line 22) | def compute_fp_gtoutlier(self, unlabel_gt, unlabel_pseudo, name):
    method compute_num_box (line 64) | def compute_num_box(self, unlabel_gt, unlabel_pseudo, name, processed=...
    method compute_ood_acc (line 211) | def compute_ood_acc(self, unlabel_gt, unlabel_pseudo, name, BOX_IOU=0.5):
  function probe (line 292) | def probe(
  function probe_roih_bbox (line 317) | def probe_roih_bbox(proposals_roih, num_cls, name=""):

FILE: adapteacher/engine/trainer.py
  class BaselineTrainer (line 43) | class BaselineTrainer(DefaultTrainer):
    method __init__ (line 44) | def __init__(self, cfg):
    method resume_or_load (line 79) | def resume_or_load(self, resume=True):
    method train_loop (line 105) | def train_loop(self, start_iter: int, max_iter: int):
    method run_step (line 129) | def run_step(self):
    method build_evaluator (line 162) | def build_evaluator(cls, cfg, dataset_name, output_folder=None):
    method build_train_loader (line 187) | def build_train_loader(cls, cfg):
    method build_test_loader (line 191) | def build_test_loader(cls, cfg, dataset_name):
    method build_hooks (line 198) | def build_hooks(self):
    method _write_metrics (line 240) | def _write_metrics(self, metrics_dict: dict):
  class ATeacherTrainer (line 278) | class ATeacherTrainer(DefaultTrainer):
    method __init__ (line 279) | def __init__(self, cfg):
    method resume_or_load (line 325) | def resume_or_load(self, resume=True):
    method build_evaluator (line 352) | def build_evaluator(cls, cfg, dataset_name, output_folder=None):
    method build_train_loader (line 377) | def build_train_loader(cls, cfg):
    method build_lr_scheduler (line 382) | def build_lr_scheduler(cls, cfg, optimizer):
    method train (line 385) | def train(self):
    method train_loop (line 391) | def train_loop(self, start_iter: int, max_iter: int):
    method threshold_bbox (line 415) | def threshold_bbox(self, proposal_bbox_inst, thres=0.7, proposal_type=...
    method process_pseudo_label (line 450) | def process_pseudo_label(
    method remove_label (line 468) | def remove_label(self, label_data):
    method add_label (line 474) | def add_label(self, unlabled_data, label):
    method get_label (line 479) | def get_label(self, label_data):
    method run_step_full_semisup (line 497) | def run_step_full_semisup(self):
    method _write_metrics (line 662) | def _write_metrics(self, metrics_dict: dict):
    method _update_teacher_model (line 701) | def _update_teacher_model(self, keep_rate=0.9996):
    method _copy_main_model (line 722) | def _copy_main_model(self):
    method build_test_loader (line 733) | def build_test_loader(cls, cfg, dataset_name):
    method build_hooks (line 736) | def build_hooks(self):

FILE: adapteacher/evaluation/coco_evaluation.py
  function convert_to_coco_json (line 32) | def convert_to_coco_json(dataset_name, output_file, allow_cached=True):
  class COCOEvaluator (line 67) | class COCOEvaluator(DatasetEvaluator):
    method __init__ (line 80) | def __init__(
    method reset (line 160) | def reset(self):
    method process (line 163) | def process(self, inputs, outputs):
    method evaluate (line 183) | def evaluate(self, img_ids=None):
    method _tasks_from_predictions (line 216) | def _tasks_from_predictions(self, predictions):
    method _eval_predictions (line 228) | def _eval_predictions(self, predictions, img_ids=None):
    method _eval_box_proposals (line 289) | def _eval_box_proposals(self, predictions):
    method _derive_coco_results (line 328) | def _derive_coco_results(self, coco_eval, iou_type, class_names=None):
  function instances_to_coco_json (line 423) | def instances_to_coco_json(instances, img_id):
  function _evaluate_box_proposals (line 487) | def _evaluate_box_proposals(dataset_predictions, coco_api, thresholds=No...
  function _evaluate_predictions_on_coco (line 598) | def _evaluate_predictions_on_coco(

FILE: adapteacher/evaluation/pascal_voc_evaluation.py
  class PascalVOCDetectionEvaluator (line 19) | class PascalVOCDetectionEvaluator(DatasetEvaluator):
    method __init__ (line 30) | def __init__(self, dataset_name, target_classnames=None):
    method reset (line 55) | def reset(self):
    method process (line 58) | def process(self, inputs, outputs):
    method evaluate (line 74) | def evaluate(self):
  function parse_rec (line 143) | def parse_rec(filename):
  function voc_ap (line 166) | def voc_ap(rec, prec, use_07_metric=False):
  function voc_eval (line 198) | def voc_eval(detpath, annopath, imagesetfile, classname, ovthresh=0.5, u...

FILE: adapteacher/modeling/meta_arch/rcnn.py
  class FCDiscriminator_img (line 22) | class FCDiscriminator_img(nn.Module):
    method __init__ (line 23) | def __init__(self, num_classes, ndf1=256, ndf2=128):
    method forward (line 33) | def forward(self, x):
  class GradReverse (line 45) | class GradReverse(torch.autograd.Function):
    method forward (line 47) | def forward(ctx, x):
    method backward (line 51) | def backward(ctx, grad_output):
  function grad_reverse (line 54) | def grad_reverse(x):
  class DAobjTwoStagePseudoLabGeneralizedRCNN (line 60) | class DAobjTwoStagePseudoLabGeneralizedRCNN(GeneralizedRCNN):
    method __init__ (line 63) | def __init__(
    method build_discriminator (line 110) | def build_discriminator(self):
    method from_config (line 114) | def from_config(cls, cfg):
    method preprocess_image_train (line 128) | def preprocess_image_train(self, batched_inputs: List[Dict[str, torch....
    method forward (line 142) | def forward(
    method visualize_training (line 316) | def visualize_training(self, batched_inputs, proposals, branch=""):
  class TwoStagePseudoLabGeneralizedRCNN (line 362) | class TwoStagePseudoLabGeneralizedRCNN(GeneralizedRCNN):
    method forward (line 363) | def forward(

FILE: adapteacher/modeling/meta_arch/ts_ensemble.py
  class EnsembleTSModel (line 6) | class EnsembleTSModel(nn.Module):
    method __init__ (line 7) | def __init__(self, modelTeacher, modelStudent):

FILE: adapteacher/modeling/meta_arch/vgg.py
  function make_layers (line 16) | def make_layers(cfg: List[Union[str, int]], batch_norm: bool = False) ->...
  class vgg_backbone (line 40) | class vgg_backbone(Backbone):
    method __init__ (line 59) | def __init__(self, cfg):
    method forward (line 96) | def forward(self, x):
    method _initialize_weights (line 108) | def _initialize_weights(self) -> None:
  function build_vgg_backbone (line 123) | def build_vgg_backbone(cfg, _):
  function build_vgg_fpn_backbone (line 128) | def build_vgg_fpn_backbone(cfg, _):

FILE: adapteacher/modeling/proposal_generator/rpn.py
  class PseudoLabRPN (line 11) | class PseudoLabRPN(RPN):
    method forward (line 16) | def forward(

FILE: adapteacher/modeling/roi_heads/fast_rcnn.py
  class FastRCNNFocaltLossOutputLayers (line 12) | class FastRCNNFocaltLossOutputLayers(FastRCNNOutputLayers):
    method __init__ (line 13) | def __init__(self, cfg, input_shape):
    method losses (line 17) | def losses(self, predictions, proposals):
  class FastRCNNFocalLoss (line 38) | class FastRCNNFocalLoss(FastRCNNOutputs):
    method __init__ (line 44) | def __init__(
    method losses (line 64) | def losses(self):
    method comput_focal_loss (line 70) | def comput_focal_loss(self):
  class FocalLoss (line 84) | class FocalLoss(nn.Module):
    method __init__ (line 85) | def __init__(
    method forward (line 98) | def forward(self, input, target):

FILE: adapteacher/modeling/roi_heads/roi_heads.py
  class StandardROIHeadsPseudoLab (line 23) | class StandardROIHeadsPseudoLab(StandardROIHeads):
    method _init_box_head (line 25) | def _init_box_head(cls, cfg, input_shape):
    method forward (line 65) | def forward(
    method _forward_box (line 106) | def _forward_box(
    method label_and_sample_proposals (line 141) | def label_and_sample_proposals(

FILE: adapteacher/solver/build.py
  function build_lr_scheduler (line 8) | def build_lr_scheduler(

FILE: adapteacher/solver/lr_scheduler.py
  class WarmupTwoStageMultiStepLR (line 8) | class WarmupTwoStageMultiStepLR(torch.optim.lr_scheduler._LRScheduler):
    method __init__ (line 9) | def __init__(
    method get_lr (line 37) | def get_lr(self) -> List[float]:
    method _compute_values (line 50) | def _compute_values(self) -> List[float]:

FILE: prod_lib/config/defaults.py
  function add_aut_config (line 6) | def add_aut_config(cfg):

FILE: prod_lib/data/builtin.py
  function register_coco_unlabel (line 34) | def register_coco_unlabel():
  function register_coco_unlabel_instances (line 41) | def register_coco_unlabel_instances(name, metadata, json_file, image_root):
  function load_coco_unlabel_json (line 74) | def load_coco_unlabel_json(
  function load_json (line 141) | def load_json(json_file):
  function register_unlabeled (line 149) | def register_unlabeled():
  function register_all_cityscapes_foggy (line 182) | def register_all_cityscapes_foggy():
  function register_all_clipart (line 214) | def register_all_clipart():
  function register_all_water (line 232) | def register_all_water():
  function register_all_clipart_ws (line 246) | def register_all_clipart_ws():

FILE: prod_lib/data/cityscapes_foggy.py
  function _get_cityscapes_files (line 27) | def _get_cityscapes_files(image_dir, gt_dir):
  function load_cityscapes_instances (line 56) | def load_cityscapes_instances(image_dir, gt_dir, from_json=True, to_poly...
  function load_cityscapes_semantic (line 98) | def load_cityscapes_semantic(image_dir, gt_dir):
  function _cityscapes_files_to_dict (line 131) | def _cityscapes_files_to_dict(files, from_json, to_polygons):

FILE: prod_lib/engine/probe.py
  class OpenMatchTrainerProbe (line 6) | class OpenMatchTrainerProbe:
    method __init__ (line 7) | def __init__(self, cfg):
    method bbox_stat (line 12) | def bbox_stat(self, unlabel_gt, unlabel_pseudo, name, bbox_stat_list):
    method compute_fp_gtoutlier (line 24) | def compute_fp_gtoutlier(self, unlabel_gt, unlabel_pseudo, name):
    method compute_num_box (line 66) | def compute_num_box(self, unlabel_gt, unlabel_pseudo, name):
    method compute_ood_acc (line 208) | def compute_ood_acc(self, unlabel_gt, unlabel_pseudo, name, BOX_IOU=0.5):

FILE: prod_lib/engine/trainer.py
  class DAobjTrainer (line 22) | class DAobjTrainer(UnbiasedTeacherTrainer):
    method run_step (line 56) | def run_step(self):
    method burn_in (line 103) | def burn_in(self, label_data_q, label_data_k):
    method teacher_student_learning (line 117) | def teacher_student_learning(
    method weight_losses (line 287) | def weight_losses(self, record_dict):
    method threshold_bbox (line 329) | def threshold_bbox(

FILE: prod_lib/evaluation/coco_evaluation.py
  function convert_to_coco_json (line 32) | def convert_to_coco_json(dataset_name, output_file, allow_cached=True):
  class COCOEvaluator (line 67) | class COCOEvaluator(DatasetEvaluator):
    method __init__ (line 80) | def __init__(
    method reset (line 160) | def reset(self):
    method process (line 163) | def process(self, inputs, outputs):
    method evaluate (line 183) | def evaluate(self, img_ids=None):
    method _tasks_from_predictions (line 216) | def _tasks_from_predictions(self, predictions):
    method _eval_predictions (line 228) | def _eval_predictions(self, predictions, img_ids=None):
    method _eval_box_proposals (line 289) | def _eval_box_proposals(self, predictions):
    method _derive_coco_results (line 328) | def _derive_coco_results(self, coco_eval, iou_type, class_names=None):
  function instances_to_coco_json (line 423) | def instances_to_coco_json(instances, img_id):
  function _evaluate_box_proposals (line 487) | def _evaluate_box_proposals(dataset_predictions, coco_api, thresholds=No...
  function _evaluate_predictions_on_coco (line 598) | def _evaluate_predictions_on_coco(

FILE: prod_lib/evaluation/pascal_voc_evaluation.py
  class PascalVOCDetectionEvaluator (line 19) | class PascalVOCDetectionEvaluator(DatasetEvaluator):
    method __init__ (line 30) | def __init__(self, dataset_name, target_classnames=None):
    method reset (line 55) | def reset(self):
    method process (line 58) | def process(self, inputs, outputs):
    method evaluate (line 74) | def evaluate(self):
  function parse_rec (line 143) | def parse_rec(filename):
  function voc_ap (line 166) | def voc_ap(rec, prec, use_07_metric=False):
  function voc_eval (line 198) | def voc_eval(detpath, annopath, imagesetfile, classname, ovthresh=0.5, u...

FILE: prod_lib/modeling/daobj_rcnn.py
  class FCDiscriminator_img (line 27) | class FCDiscriminator_img(nn.Module):
    method __init__ (line 28) | def __init__(self, num_classes, ndf1=256, ndf2=128):
    method forward (line 38) | def forward(self, x):
  class GradReverse (line 50) | class GradReverse(torch.autograd.Function):
    method forward (line 52) | def forward(ctx, x):
    method backward (line 56) | def backward(ctx, grad_output):
  function grad_reverse (line 59) | def grad_reverse(x):
  class DAobjTwoStagePseudoLabGeneralizedRCNN (line 65) | class DAobjTwoStagePseudoLabGeneralizedRCNN(GeneralizedRCNN):
    method __init__ (line 68) | def __init__(
    method from_config (line 120) | def from_config(cls, cfg):
    method preprocess_image_train (line 134) | def preprocess_image_train(self, batched_inputs: List[Dict[str, torch....
    method forward (line 148) | def forward(
    method visualize_training (line 292) | def visualize_training(self, batched_inputs, proposals, branch=""):

FILE: prod_lib/modeling/vgg.py
  function make_layers (line 18) | def make_layers(cfg: List[Union[str, int]], batch_norm: bool = False) ->...
  class vgg_backbone (line 42) | class vgg_backbone(Backbone):
    method __init__ (line 61) | def __init__(self, cfg):
    method forward (line 98) | def forward(self, x):
    method _initialize_weights (line 110) | def _initialize_weights(self) -> None:
  function build_vgg_backbone (line 125) | def build_vgg_backbone(cfg, _):
  function build_vgg_fpn_backbone (line 130) | def build_vgg_fpn_backbone(cfg, _):

FILE: prod_lib/runner/runner.py
  function _get_tbx_writer (line 66) | def _get_tbx_writer(log_dir):
  class BaseUnbiasedTeacherRunner (line 71) | class BaseUnbiasedTeacherRunner(UnbiasedTeacherRunner):
    method get_default_cfg (line 72) | def get_default_cfg(self):
    method get_evaluator (line 81) | def get_evaluator(cfg, dataset_name, output_folder):
  class DAobjUnbiasedTeacherRunner (line 103) | class DAobjUnbiasedTeacherRunner(BaseUnbiasedTeacherRunner):
    method get_default_cfg (line 104) | def get_default_cfg(self):
    method build_model (line 112) | def build_model(self, cfg, eval_only=False):
    method do_train (line 137) | def do_train(self, cfg, model, resume):

FILE: train_net.py
  function setup (line 22) | def setup(args):
  function main (line 35) | def main(args):