SYMBOL INDEX (4564 symbols across 391 files)

FILE: GLIP/maskrcnn_benchmark/config/paths_catalog.py
  function try_to_find (line 7) | def try_to_find(file, return_dir=False, search_path=['./DATASET', './OUT...
  class DatasetCatalog (line 30) | class DatasetCatalog(object):
    method set (line 210) | def set(name, info):
    method get (line 214) | def get(name):
  class ModelCatalog (line 392) | class ModelCatalog(object):
    method get (line 416) | def get(name):
    method get_c2_imagenet_pretrained (line 424) | def get_c2_imagenet_pretrained(name):
    method get_c2_detectron_12_2017_baselines (line 432) | def get_c2_detectron_12_2017_baselines(name):

FILE: GLIP/maskrcnn_benchmark/csrc/cpu/ROIAlign_cpu.cpp
  type PreCalc (line 6) | struct PreCalc {
  function pre_calc_for_bilinear_interpolate (line 18) | void pre_calc_for_bilinear_interpolate(
  function ROIAlignForward_cpu_kernel (line 114) | void ROIAlignForward_cpu_kernel(
  function ROIAlign_forward_cpu (line 221) | at::Tensor ROIAlign_forward_cpu(const at::Tensor& input,

FILE: GLIP/maskrcnn_benchmark/csrc/cpu/nms_cpu.cpp
  function nms_cpu_kernel (line 6) | at::Tensor nms_cpu_kernel(const at::Tensor& dets,
  function nms_cpu (line 67) | at::Tensor nms_cpu(const at::Tensor& dets,

FILE: GLIP/maskrcnn_benchmark/csrc/cpu/soft_nms.cpp
  function soft_nms_cpu_kernel (line 6) | std::pair<at::Tensor, at::Tensor> soft_nms_cpu_kernel(const at::Tensor& ...
  function soft_nms_cpu (line 108) | std::pair<at::Tensor, at::Tensor> soft_nms_cpu(const at::Tensor& dets,

FILE: GLIP/maskrcnn_benchmark/csrc/deform_conv.h
  function deform_conv_forward (line 11) | int deform_conv_forward(
  function deform_conv_backward_input (line 45) | int deform_conv_backward_input(
  function deform_conv_backward_parameters (line 80) | int deform_conv_backward_parameters(
  function modulated_deform_conv_forward (line 115) | void modulated_deform_conv_forward(
  function modulated_deform_conv_backward (line 152) | void modulated_deform_conv_backward(

FILE: GLIP/maskrcnn_benchmark/csrc/deform_pool.h
  function deform_psroi_pooling_forward (line 11) | void deform_psroi_pooling_forward(
  function deform_psroi_pooling_backward (line 41) | void deform_psroi_pooling_backward(

FILE: GLIP/maskrcnn_benchmark/csrc/ml_nms.h
  function threshold (line 13) | float threshold) {

FILE: GLIP/maskrcnn_benchmark/csrc/vision.cpp
  function PYBIND11_MODULE (line 10) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: GLIP/maskrcnn_benchmark/data/build.py
  function build_dataset (line 21) | def build_dataset(cfg, dataset_list, transforms, dataset_catalog, is_tra...
  function build_dataset_by_group (line 124) | def build_dataset_by_group(dataset_list, transforms, dataset_catalog, is...
  function make_data_sampler (line 196) | def make_data_sampler(dataset, shuffle, distributed, num_replicas=None, ...
  function _quantize (line 207) | def _quantize(x, bins):
  function _compute_aspect_ratios (line 214) | def _compute_aspect_ratios(dataset):
  function make_batch_data_sampler (line 223) | def make_batch_data_sampler(
  function make_data_loader (line 244) | def make_data_loader(cfg, is_train=True, is_distributed=False, num_repli...

FILE: GLIP/maskrcnn_benchmark/data/collate_batch.py
  class BatchCollator (line 6) | class BatchCollator(object):
    method __init__ (line 13) | def __init__(self, size_divisible=0):
    method __call__ (line 16) | def __call__(self, batch):
  class BBoxAugCollator (line 70) | class BBoxAugCollator(object):
    method __call__ (line 77) | def __call__(self, batch):

FILE: GLIP/maskrcnn_benchmark/data/datasets/background.py
  class Background (line 11) | class Background(data.Dataset):
    method __init__ (line 21) | def __init__(self, ann_file, root, remove_images_without_annotations=N...
    method __getitem__ (line 28) | def __getitem__(self, index):
    method __len__ (line 48) | def __len__(self):
    method get_img_info (line 51) | def get_img_info(self, index):

FILE: GLIP/maskrcnn_benchmark/data/datasets/box_label_loader.py
  class LabelLoader (line 12) | class LabelLoader(object):
    method __init__ (line 13) | def __init__(self, labelmap, extra_fields=(), filter_duplicate_relatio...
    method __call__ (line 24) | def __call__(self, annotations, img_size, remove_empty=False, load_fie...
    method get_box_mask (line 60) | def get_box_mask(self, rect, img_size):
    method add_masks (line 72) | def add_masks(self, annotations, img_size):
    method add_classes (line 86) | def add_classes(self, annotations):
    method add_confidences (line 93) | def add_confidences(self, annotations):
    method add_attributes (line 102) | def add_attributes(self, annotations):
    method add_features (line 110) | def add_features(self, annotations):
    method add_scores_all (line 116) | def add_scores_all(self, annotations):
    method add_boxes_all (line 122) | def add_boxes_all(self, annotations):
    method relation_loader (line 128) | def relation_loader(self, relation_annos, target):
  class BoxLabelLoader (line 154) | class BoxLabelLoader(object):
    method __init__ (line 155) | def __init__(self, labelmap, extra_fields=(), ignore_attrs=(),
    method __call__ (line 165) | def __call__(self, annotations, img_size, remove_empty=True):
    method add_classes_with_ignore (line 197) | def add_classes_with_ignore(self, annotations):
    method add_masks (line 209) | def add_masks(self, annotations, img_size):
    method get_box_mask (line 223) | def get_box_mask(self, rect, img_size):
    method add_confidences (line 235) | def add_confidences(self, annotations):
    method add_attributes (line 246) | def add_attributes(self, annotations):

FILE: GLIP/maskrcnn_benchmark/data/datasets/caption.py
  class CaptionTSV (line 14) | class CaptionTSV(TSVYamlDataset):
    method __init__ (line 15) | def __init__(self,
    method __len__ (line 66) | def __len__(self):
    method pack_caption (line 69) | def pack_caption(self, positive_caption, negative_captions, original_t...
    method __get_negative_captions__ (line 108) | def __get_negative_captions__(self, idx, negative_size=7):
    method __getitem__ (line 117) | def __getitem__(self, idx):
    method convert_anno_from_v2_to_v1 (line 252) | def convert_anno_from_v2_to_v1(self, anno):
    method get_raw_image (line 270) | def get_raw_image(self, idx):
    method get_img_id (line 274) | def get_img_id(self, idx):

FILE: GLIP/maskrcnn_benchmark/data/datasets/coco.py
  function _count_visible_keypoints (line 20) | def _count_visible_keypoints(anno):
  function _has_only_empty_bbox (line 24) | def _has_only_empty_bbox(anno):
  function has_valid_annotation (line 28) | def has_valid_annotation(anno):
  function pil_loader (line 46) | def pil_loader(path, retry=5):
  function rgb2id (line 58) | def rgb2id(color):
  class CocoDetection (line 66) | class CocoDetection(data.Dataset):
    method __init__ (line 78) | def __init__(self, root, annFile, transform=None, target_transform=None):
    method __getitem__ (line 86) | def __getitem__(self, index, return_meta=False):
    method __len__ (line 116) | def __len__(self):
    method __repr__ (line 119) | def __repr__(self):
  class COCODataset (line 130) | class COCODataset(CocoDetection):
    method __init__ (line 131) | def __init__(self, ann_file, root, remove_images_without_annotations, ...
    method categories (line 190) | def categories(self, no_background=True):
    method __getitem__ (line 198) | def __getitem__(self, idx):
    method get_img_info (line 265) | def get_img_info(self, index):

FILE: GLIP/maskrcnn_benchmark/data/datasets/coco_dt.py
  class CocoDetectionTSV (line 19) | class CocoDetectionTSV(ODTSVDataset):
    method __init__ (line 20) | def __init__(self,
    method __len__ (line 75) | def __len__(self):
    method categories (line 78) | def categories(self, no_background=True):
    method __getitem__ (line 87) | def __getitem__(self, idx):
    method get_raw_image (line 142) | def get_raw_image(self, idx):
    method get_img_id (line 146) | def get_img_id(self, idx):

FILE: GLIP/maskrcnn_benchmark/data/datasets/concat_dataset.py
  class ConcatDataset (line 7) | class ConcatDataset(_ConcatDataset):
    method get_idxs (line 13) | def get_idxs(self, idx):
    method get_img_info (line 21) | def get_img_info(self, idx):

FILE: GLIP/maskrcnn_benchmark/data/datasets/custom_distributed_sampler.py
  class DistributedSamplerChunkByNode (line 12) | class DistributedSamplerChunkByNode(torch.utils.data.Sampler):
    method __init__ (line 14) | def __init__(self,
    method __iter__ (line 98) | def __iter__(self):
    method generate_indices_within_range_with_rank (line 130) | def generate_indices_within_range_with_rank(self, seed, epoch, process...
    method __len__ (line 173) | def __len__(self) -> int:
    method set_epoch (line 176) | def set_epoch(self, epoch: int) -> None:

FILE: GLIP/maskrcnn_benchmark/data/datasets/duplicate_dataset.py
  function create_duplicate_dataset (line 11) | def create_duplicate_dataset(DatasetBaseClass):

FILE: GLIP/maskrcnn_benchmark/data/datasets/evaluation/__init__.py
  function evaluate (line 10) | def evaluate(dataset, predictions, output_folder, **kwargs):
  function evaluate_mdetr (line 39) | def evaluate_mdetr(dataset, predictions, output_folder, cfg):

FILE: GLIP/maskrcnn_benchmark/data/datasets/evaluation/box_aug.py
  function im_detect_bbox_aug (line 12) | def im_detect_bbox_aug(model, images, device, captions=None, positive_ma...
  function im_detect_bbox (line 65) | def im_detect_bbox(model, images, target_scale, target_max_size, device,
  function im_detect_bbox_hflip (line 94) | def im_detect_bbox_hflip(model, images, target_scale, target_max_size, d...
  function im_detect_bbox_scale (line 129) | def im_detect_bbox_scale(model, images, target_scale, target_max_size, d...
  function remove_boxes (line 150) | def remove_boxes(boxlist_ts, min_scale, max_scale):
  function merge_result_from_multi_scales (line 166) | def merge_result_from_multi_scales(boxlists):
  function boxlist_nms (line 209) | def boxlist_nms(boxlist, thresh, max_proposals=-1, score_field="scores",...
  function bbox_vote (line 241) | def bbox_vote(boxes, scores, vote_thresh):
  function soft_bbox_vote (line 290) | def soft_bbox_vote(boxes, scores, vote_thresh):

FILE: GLIP/maskrcnn_benchmark/data/datasets/evaluation/coco/__init__.py
  function coco_evaluation (line 4) | def coco_evaluation(

FILE: GLIP/maskrcnn_benchmark/data/datasets/evaluation/coco/coco_eval.py
  function do_coco_evaluation (line 16) | def do_coco_evaluation(
  function prepare_for_tsv_detection (line 86) | def prepare_for_tsv_detection(predictions, dataset):
  function prepare_for_coco_detection (line 129) | def prepare_for_coco_detection(predictions, dataset):
  function prepare_for_coco_segmentation (line 160) | def prepare_for_coco_segmentation(predictions, dataset):
  function prepare_for_coco_keypoint (line 214) | def prepare_for_coco_keypoint(predictions, dataset):
  function evaluate_box_proposals (line 246) | def evaluate_box_proposals(
  function evaluate_predictions_on_coco (line 375) | def evaluate_predictions_on_coco(
  function summarize_per_category (line 400) | def summarize_per_category(coco_eval, csv_output=None):
  function filter_valid_keypoints (line 459) | def filter_valid_keypoints(coco_gt, coco_dt):
  class COCOResults (line 467) | class COCOResults(object):
    method __init__ (line 484) | def __init__(self, *iou_types):
    method update (line 494) | def update(self, coco_eval):
    method __repr__ (line 507) | def __repr__(self):
  function check_expected_results (line 512) | def check_expected_results(results, expected_results, sigma_tol):

FILE: GLIP/maskrcnn_benchmark/data/datasets/evaluation/flickr/flickr_eval.py
  function get_sentence_data (line 21) | def get_sentence_data(filename) -> List[Dict[str, Any]]:
  function get_annotations (line 89) | def get_annotations(filename) -> Dict[str, Union[int, List[str], Dict[st...
  function box_area (line 152) | def box_area(boxes: np.array) -> np.array:
  function _box_inter_union (line 171) | def _box_inter_union(boxes1: np.array, boxes2: np.array) -> Tuple[np.arr...
  function box_iou (line 186) | def box_iou(boxes1: np.array, boxes2: np.array) -> np.array:
  function _merge_boxes (line 207) | def _merge_boxes(boxes: List[List[int]]) -> List[List[int]]:
  class RecallTracker (line 220) | class RecallTracker:
    method __init__ (line 223) | def __init__(self, topk: Sequence[int]):
    method add_positive (line 232) | def add_positive(self, k: int, category: str):
    method add_negative (line 239) | def add_negative(self, k: int, category: str):
    method report (line 245) | def report(self) -> Dict[int, Dict[str, float]]:
  class Flickr30kEntitiesRecallEvaluator (line 258) | class Flickr30kEntitiesRecallEvaluator:
    method __init__ (line 259) | def __init__(
    method evaluate (line 323) | def evaluate(self, predictions: List[Dict]):
  class FlickrEvaluator (line 393) | class FlickrEvaluator(object):
    method __init__ (line 394) | def __init__(
    method accumulate (line 410) | def accumulate(self):
    method update (line 413) | def update(self, predictions):
    method synchronize_between_processes (line 416) | def synchronize_between_processes(self):
    method summarize (line 420) | def summarize(self):

FILE: GLIP/maskrcnn_benchmark/data/datasets/evaluation/lvis/lvis.py
  function _isArrayLike (line 14) | def _isArrayLike(obj):
  class LVIS (line 18) | class LVIS:
    method __init__ (line 19) | def __init__(self, annotation_path=None):
    method _load_json (line 41) | def _load_json(self, path):
    method _create_index (line 45) | def _create_index(self):
    method get_ann_ids (line 70) | def get_ann_ids(self, img_ids=None, cat_ids=None, area_rng=None):
    method get_cat_ids (line 106) | def get_cat_ids(self):
    method get_img_ids (line 113) | def get_img_ids(self):
    method _load_helper (line 120) | def _load_helper(self, _dict, ids):
    method load_anns (line 128) | def load_anns(self, ids=None):
    method load_cats (line 137) | def load_cats(self, ids):
    method load_imgs (line 147) | def load_imgs(self, ids):
    method download (line 156) | def download(self, save_dir, img_ids=None):
    method ann_to_rle (line 174) | def ann_to_rle(self, ann):
    method ann_to_mask (line 197) | def ann_to_mask(self, ann):

FILE: GLIP/maskrcnn_benchmark/data/datasets/evaluation/lvis/lvis_eval.py
  function merge (line 21) | def merge(img_ids, eval_imgs):
  class Params (line 51) | class Params:
    method __init__ (line 52) | def __init__(self, iou_type):
  class LVISResults (line 78) | class LVISResults(LVIS):
    method __init__ (line 79) | def __init__(self, lvis_gt, results, max_dets=300):
    method limit_dets_per_image (line 136) | def limit_dets_per_image(self, anns, max_dets):
    method get_top_results (line 149) | def get_top_results(self, img_id, score_thrs):
  class LVISEval (line 155) | class LVISEval:
    method __init__ (line 156) | def __init__(self, lvis_gt, lvis_dt=None, iou_type="segm"):
    method _to_mask (line 195) | def _to_mask(self, anns, lvis):
    method _prepare (line 200) | def _prepare(self):
    method _prepare_freq_group (line 244) | def _prepare_freq_group(self):
    method evaluate (line 252) | def evaluate(self):
    method _get_gt_dt (line 279) | def _get_gt_dt(self, img_id, cat_id):
    method compute_iou (line 292) | def compute_iou(self, img_id, cat_id):
    method evaluate_img (line 318) | def evaluate_img(self, img_id, cat_id, area_rng):
    method accumulate (line 412) | def accumulate(self):
    method _summarize (line 525) | def _summarize(self, summary_type, iou_thr=None, area_rng="all", freq_...
    method summarize (line 550) | def summarize(self):
    method run (line 587) | def run(self):
    method print_results (line 593) | def print_results(self):
    method get_results (line 625) | def get_results(self):
  class LvisEvaluator (line 636) | class LvisEvaluator(object):
    method __init__ (line 637) | def __init__(self, lvis_gt, iou_types):
    method update (line 650) | def update(self, predictions):
    method synchronize_between_processes (line 669) | def synchronize_between_processes(self):
    method accumulate (line 674) | def accumulate(self):
    method summarize (line 678) | def summarize(self):
    method prepare (line 683) | def prepare(self, predictions, iou_type):
    method prepare_for_lvis_detection (line 693) | def prepare_for_lvis_detection(self, predictions):
    method prepare_for_lvis_segmentation (line 717) | def prepare_for_lvis_segmentation(self, predictions):
  function _merge_lists (line 752) | def _merge_lists(listA, listB, maxN, key):
  class LvisEvaluatorFixedAP (line 766) | class LvisEvaluatorFixedAP(object):
    method __init__ (line 767) | def __init__(self, gt: LVIS, topk=10000, fixed_ap=True):
    method update (line 775) | def update(self, predictions):
    method synchronize_between_processes (line 796) | def synchronize_between_processes(self):
    method prepare (line 806) | def prepare(self, predictions):
    method summarize (line 830) | def summarize(self):
    method _summarize_standard (line 839) | def _summarize_standard(self):
    method _summarize_fixed (line 845) | def _summarize_fixed(self):
  class LvisDumper (line 874) | class LvisDumper(object):
    method __init__ (line 875) | def __init__(self, topk=10000, fixed_ap=True, out_path="lvis_eval"):
    method update (line 886) | def update(self, predictions):
    method synchronize_between_processes (line 907) | def synchronize_between_processes(self):
    method prepare (line 917) | def prepare(self, predictions):
    method summarize (line 941) | def summarize(self):
    method _summarize_standard (line 950) | def _summarize_standard(self):
    method _summarize_fixed (line 958) | def _summarize_fixed(self):
  function convert_to_xywh (line 984) | def convert_to_xywh(boxes):
  function create_common_lvis_eval (line 989) | def create_common_lvis_eval(lvis_eval, img_ids, eval_imgs):
  function lvis_evaluation (line 997) | def lvis_evaluation():

FILE: GLIP/maskrcnn_benchmark/data/datasets/evaluation/od_to_grounding/__init__.py
  function od_to_grounding_evaluation (line 4) | def od_to_grounding_evaluation(

FILE: GLIP/maskrcnn_benchmark/data/datasets/evaluation/od_to_grounding/od_eval.py
  function do_od_evaluation (line 16) | def do_od_evaluation(
  function prepare_for_tsv_detection (line 86) | def prepare_for_tsv_detection(predictions, dataset):
  function prepare_for_coco_detection (line 129) | def prepare_for_coco_detection(predictions, dataset):
  function prepare_for_coco_segmentation (line 160) | def prepare_for_coco_segmentation(predictions, dataset):
  function prepare_for_coco_keypoint (line 214) | def prepare_for_coco_keypoint(predictions, dataset):
  function evaluate_box_proposals (line 246) | def evaluate_box_proposals(
  function evaluate_predictions_on_coco (line 375) | def evaluate_predictions_on_coco(
  function summarize_per_category (line 400) | def summarize_per_category(coco_eval, csv_output=None):
  function filter_valid_keypoints (line 459) | def filter_valid_keypoints(coco_gt, coco_dt):
  class COCOResults (line 467) | class COCOResults(object):
    method __init__ (line 484) | def __init__(self, *iou_types):
    method update (line 494) | def update(self, coco_eval):
    method __repr__ (line 507) | def __repr__(self):
  function check_expected_results (line 512) | def check_expected_results(results, expected_results, sigma_tol):

FILE: GLIP/maskrcnn_benchmark/data/datasets/evaluation/vg/__init__.py
  function vg_evaluation (line 6) | def vg_evaluation(dataset, predictions, output_folder, box_only, eval_at...

FILE: GLIP/maskrcnn_benchmark/data/datasets/evaluation/vg/vg_eval.py
  function evaluate_box_proposals (line 14) | def evaluate_box_proposals(
  class VGResults (line 130) | class VGResults(object):
    method __init__ (line 137) | def __init__(self, iou_type, value):
  function do_vg_evaluation (line 145) | def do_vg_evaluation(dataset, predictions, output_folder, box_only, eval...
  function eval_detection_voc (line 253) | def eval_detection_voc(pred_boxlists, gt_boxlists, classes, iou_thresh=0...
  function calc_detection_voc_prec_rec (line 326) | def calc_detection_voc_prec_rec(pred_boxlists, gt_boxlists, classindex, ...
  function voc_ap (line 450) | def voc_ap(rec, prec, use_07_metric=False):
  function calc_detection_voc_ap (line 484) | def calc_detection_voc_ap(prec, rec, use_07_metric=False):
  function evaluate_box_proposals_for_relation (line 544) | def evaluate_box_proposals_for_relation(

FILE: GLIP/maskrcnn_benchmark/data/datasets/evaluation/voc/__init__.py
  function voc_evaluation (line 6) | def voc_evaluation(dataset, predictions, output_folder, box_only, **_):

FILE: GLIP/maskrcnn_benchmark/data/datasets/evaluation/voc/voc_eval.py
  function do_voc_evaluation (line 12) | def do_voc_evaluation(dataset, predictions, output_folder, logger):
  function eval_detection_voc (line 48) | def eval_detection_voc(pred_boxlists, gt_boxlists, iou_thresh=0.5, use_0...
  function calc_detection_voc_prec_rec (line 68) | def calc_detection_voc_prec_rec(gt_boxlists, pred_boxlists, iou_thresh=0...
  function calc_detection_voc_ap (line 160) | def calc_detection_voc_ap(prec, rec, use_07_metric=False):

FILE: GLIP/maskrcnn_benchmark/data/datasets/flickr.py
  class FlickrDataset (line 7) | class FlickrDataset(ModulatedDataset):

FILE: GLIP/maskrcnn_benchmark/data/datasets/gqa.py
  class GQADataset (line 10) | class GQADataset(ModulatedDataset):
  class GQAQuestionAnswering (line 14) | class GQAQuestionAnswering(torchvision.datasets.CocoDetection):
    method __init__ (line 15) | def __init__(self, img_folder, ann_file, transforms, return_masks, ret...
    method __getitem__ (line 25) | def __getitem__(self, idx):

FILE: GLIP/maskrcnn_benchmark/data/datasets/imagenet.py
  function pil_loader (line 8) | def pil_loader(path):
  class ImageNet (line 14) | class ImageNet(data.Dataset):
    method __init__ (line 24) | def __init__(self, ann_file, root, remove_images_without_annotations=N...
    method select_class (line 42) | def select_class(self, cls):
    method __getitem__ (line 47) | def __getitem__(self, index):
    method __len__ (line 62) | def __len__(self):

FILE: GLIP/maskrcnn_benchmark/data/datasets/list_dataset.py
  class ListDataset (line 11) | class ListDataset(object):
    method __init__ (line 12) | def __init__(self, image_lists, transforms=None):
    method __getitem__ (line 16) | def __getitem__(self, item):
    method __len__ (line 28) | def __len__(self):
    method get_img_info (line 31) | def get_img_info(self, item):

FILE: GLIP/maskrcnn_benchmark/data/datasets/lvis.py
  function _isArrayLike (line 16) | def _isArrayLike(obj):
  class LVIS (line 20) | class LVIS:
    method __init__ (line 21) | def __init__(self, annotation_path=None):
    method _load_json (line 43) | def _load_json(self, path):
    method _create_index (line 47) | def _create_index(self):
    method get_ann_ids (line 72) | def get_ann_ids(self, img_ids=None, cat_ids=None, area_rng=None):
    method get_cat_ids (line 108) | def get_cat_ids(self):
    method get_img_ids (line 115) | def get_img_ids(self):
    method _load_helper (line 122) | def _load_helper(self, _dict, ids):
    method load_anns (line 130) | def load_anns(self, ids=None):
    method load_cats (line 139) | def load_cats(self, ids):
    method load_imgs (line 149) | def load_imgs(self, ids):
    method download (line 158) | def download(self, save_dir, img_ids=None):
    method ann_to_rle (line 176) | def ann_to_rle(self, ann):
    method ann_to_mask (line 199) | def ann_to_mask(self, ann):
  class LvisDetectionBase (line 211) | class LvisDetectionBase(torchvision.datasets.VisionDataset):
    method __init__ (line 212) | def __init__(self, root, annFile, transform=None, target_transform=Non...
    method __getitem__ (line 217) | def __getitem__(self, index):
    method __len__ (line 238) | def __len__(self):
  class LvisDetection (line 242) | class LvisDetection(LvisDetectionBase):
    method __init__ (line 243) | def __init__(self, img_folder, ann_file, transforms, return_masks=Fals...
    method __getitem__ (line 249) | def __getitem__(self, idx):
    method get_raw_image (line 258) | def get_raw_image(self, idx):
    method categories (line 262) | def categories(self):

FILE: GLIP/maskrcnn_benchmark/data/datasets/mixed.py
  class CustomCocoDetection (line 15) | class CustomCocoDetection(VisionDataset):
    method __init__ (line 31) | def __init__(
    method __getitem__ (line 60) | def __getitem__(self, index):
    method __len__ (line 84) | def __len__(self):
  class MixedDataset (line 88) | class MixedDataset(CustomCocoDetection):
    method __init__ (line 91) | def __init__(self,
    method __getitem__ (line 111) | def __getitem__(self, idx):
    method get_img_info (line 142) | def get_img_info(self, index):

FILE: GLIP/maskrcnn_benchmark/data/datasets/mixup.py
  class MixupDetection (line 8) | class MixupDetection(data.Dataset):
    method __init__ (line 21) | def __init__(self, dataset, mixup=None, preproc=None, *args):
    method set_mixup (line 28) | def set_mixup(self, mixup=None, *args):
    method __len__ (line 41) | def __len__(self):
    method __getitem__ (line 45) | def __getitem__(self, idx):
    method pull_item (line 86) | def pull_item(self, idx):

FILE: GLIP/maskrcnn_benchmark/data/datasets/modulated_coco.py
  class CocoGrounding (line 22) | class CocoGrounding(torchvision.datasets.CocoDetection):
    method __init__ (line 23) | def __init__(self,
    method categories (line 116) | def categories(self, no_background=True):
    method get_box_mask (line 125) | def get_box_mask(self, rect, img_size, mode="poly"):
    method __getitem__ (line 130) | def __getitem__(self, idx):
    method get_img_info (line 232) | def get_img_info(self, index):
  class ModulatedDataset (line 238) | class ModulatedDataset(torchvision.datasets.CocoDetection):
    method __init__ (line 239) | def __init__(self,
    method __getitem__ (line 273) | def __getitem__(self, idx):
    method get_img_info (line 327) | def get_img_info(self, index):
  class CocoDetection (line 333) | class CocoDetection(data.Dataset):
    method __init__ (line 345) | def __init__(self, root, annFile, transform=None, target_transform=None):
    method __getitem__ (line 353) | def __getitem__(self, index, return_meta=False):
    method __len__ (line 383) | def __len__(self):
    method __repr__ (line 386) | def __repr__(self):
  class ConvertCocoPolysToMask (line 397) | class ConvertCocoPolysToMask(object):
    method __init__ (line 398) | def __init__(self, return_masks=False, return_tokens=False, tokenizer=...
    method get_box_mask (line 404) | def get_box_mask(self, rect, img_size, mode="poly"):
    method __call__ (line 409) | def __call__(self, image, target, ignore_box_screen=False, box_format=...
  function create_greenlight_map (line 523) | def create_greenlight_map(tok_list, tokenized):
  function create_positive_map_for_od_labels (line 561) | def create_positive_map_for_od_labels(tokenized, label_to_positions):
  function convert_coco_poly_to_mask (line 598) | def convert_coco_poly_to_mask(segmentations, height, width):
  function create_positive_map (line 615) | def create_positive_map(tokenized, tokens_positive):
  function pil_loader (line 645) | def pil_loader(path, retry=5):

FILE: GLIP/maskrcnn_benchmark/data/datasets/object365.py
  class Object365DetectionTSV (line 7) | class Object365DetectionTSV(CocoDetectionTSV):

FILE: GLIP/maskrcnn_benchmark/data/datasets/od_to_grounding.py
  function clean_name (line 9) | def clean_name(name):
  function sanity_check_target_after_processing (line 16) | def sanity_check_target_after_processing(target):
  function convert_od_to_grounding_simple (line 20) | def convert_od_to_grounding_simple(
  function check_for_positive_overflow (line 104) | def check_for_positive_overflow(target, ind_to_class, tokenizer, max_seq...
  function convert_object_detection_to_grounding_optimized_for_od (line 149) | def convert_object_detection_to_grounding_optimized_for_od(
  function generate_control_options_given_probabilities (line 336) | def generate_control_options_given_probabilities(

FILE: GLIP/maskrcnn_benchmark/data/datasets/phrasecut.py
  class PhrasecutDetection (line 7) | class PhrasecutDetection(ModulatedDataset):

FILE: GLIP/maskrcnn_benchmark/data/datasets/pseudo_data.py
  class PseudoData (line 15) | class PseudoData(TSVYamlDataset):
    method __init__ (line 16) | def __init__(self,
    method __len__ (line 72) | def __len__(self):
    method check_for_overlap (line 76) | def check_for_overlap(range1, range2):
    method divert_boxes (line 81) | def divert_boxes(self, anno):
    method __getitem__ (line 107) | def __getitem__(self, idx):
    method convert_anno_from_yiling_to_ours (line 202) | def convert_anno_from_yiling_to_ours(self, anno):
    method get_raw_image (line 219) | def get_raw_image(self, idx):
    method get_img_id (line 223) | def get_img_id(self, idx):

FILE: GLIP/maskrcnn_benchmark/data/datasets/refexp.py
  class RefExpDataset (line 14) | class RefExpDataset(ModulatedDataset):
  class RefExpEvaluator (line 18) | class RefExpEvaluator(object):
    method __init__ (line 19) | def __init__(self, refexp_gt, iou_types, k=(1, 5, 10), thresh_iou=0.5):
    method accumulate (line 29) | def accumulate(self):
    method update (line 32) | def update(self, predictions):
    method synchronize_between_processes (line 35) | def synchronize_between_processes(self):
    method summarize (line 42) | def summarize(self):

FILE: GLIP/maskrcnn_benchmark/data/datasets/tsv.py
  function load_linelist_file (line 16) | def load_linelist_file(linelist_file):
  function img_from_base64 (line 25) | def img_from_base64(imagestring):
  function load_from_yaml_file (line 33) | def load_from_yaml_file(yaml_file):
  function find_file_path_in_yaml (line 38) | def find_file_path_in_yaml(fname, root):
  function create_lineidx (line 50) | def create_lineidx(filein, idxout):
  function read_to_character (line 62) | def read_to_character(fp, c):
  class TSVFile (line 75) | class TSVFile(object):
    method __init__ (line 76) | def __init__(self, tsv_file, generate_lineidx=False):
    method __del__ (line 88) | def __del__(self):
    method __str__ (line 92) | def __str__(self):
    method __repr__ (line 95) | def __repr__(self):
    method num_rows (line 98) | def num_rows(self):
    method seek (line 102) | def seek(self, idx):
    method seek_first_column (line 113) | def seek_first_column(self, idx):
    method get_key (line 120) | def get_key(self, idx):
    method __getitem__ (line 123) | def __getitem__(self, index):
    method __len__ (line 126) | def __len__(self):
    method _ensure_lineidx_loaded (line 129) | def _ensure_lineidx_loaded(self):
    method _ensure_tsv_opened (line 135) | def _ensure_tsv_opened(self):
  class CompositeTSVFile (line 146) | class CompositeTSVFile():
    method __init__ (line 147) | def __init__(self, file_list, seq_file, root='.'):
    method get_key (line 159) | def get_key(self, index):
    method num_rows (line 164) | def num_rows(self):
    method __getitem__ (line 167) | def __getitem__(self, index):
    method __len__ (line 171) | def __len__(self):
    method initialize (line 174) | def initialize(self):
  function load_list_file (line 190) | def load_list_file(fname):
  class TSVDataset (line 199) | class TSVDataset(object):
    method __init__ (line 200) | def __init__(self, img_file, label_file=None, hw_file=None,
    method __len__ (line 226) | def __len__(self):
    method __getitem__ (line 235) | def __getitem__(self, idx):
    method get_line_no (line 250) | def get_line_no(self, idx):
    method get_image (line 253) | def get_image(self, idx):
    method get_annotations (line 266) | def get_annotations(self, idx):
    method get_target_from_annotations (line 275) | def get_target_from_annotations(self, annotations, img_size, idx):
    method apply_transforms (line 280) | def apply_transforms(self, image, target=None):
    method get_img_info (line 285) | def get_img_info(self, idx):
    method get_img_key (line 309) | def get_img_key(self, idx):
  class TSVYamlDataset (line 326) | class TSVYamlDataset(TSVDataset):
    method __init__ (line 330) | def __init__(self, yaml_file, root=None, replace_clean_label=False):
  class ODTSVDataset (line 354) | class ODTSVDataset(TSVYamlDataset):
    method __init__ (line 359) | def __init__(self, yaml_file, extra_fields=(), transforms=None,
    method get_target_from_annotations (line 411) | def get_target_from_annotations(self, annotations, img_size, idx):
    method apply_transforms (line 417) | def apply_transforms(self, img, target=None):

FILE: GLIP/maskrcnn_benchmark/data/datasets/vg.py
  class VGDetectionTSV (line 14) | class VGDetectionTSV(CocoDetectionTSV):
  function sort_key_by_val (line 18) | def sort_key_by_val(dic):
  function bbox_overlaps (line 23) | def bbox_overlaps(anchors, gt_boxes):
  function _box_filter (line 59) | def _box_filter(boxes, must_overlap=False):
  class VGTSVDataset (line 78) | class VGTSVDataset(TSVYamlDataset):
    method __init__ (line 83) | def __init__(self, yaml_file, extra_fields=None, transforms=None,
    method _get_freq_prior (line 167) | def _get_freq_prior(self, must_overlap=False):
    method relation_loader (line 204) | def relation_loader(self, relation_triplets, target):
    method get_target_from_annotations (line 228) | def get_target_from_annotations(self, annotations, img_size, idx):
    method get_groundtruth (line 241) | def get_groundtruth(self, idx, call=False):
    method apply_transforms (line 255) | def apply_transforms(self, img, target=None):
    method map_class_id_to_class_name (line 260) | def map_class_id_to_class_name(self, class_id):
    method map_attribute_id_to_attribute_name (line 263) | def map_attribute_id_to_attribute_name(self, attribute_id):
    method map_relation_id_to_relation_name (line 266) | def map_relation_id_to_relation_name(self, relation_id):

FILE: GLIP/maskrcnn_benchmark/data/datasets/voc.py
  class PascalVOCDataset (line 17) | class PascalVOCDataset(torch.utils.data.Dataset):
    method __init__ (line 43) | def __init__(self, data_dir, split, use_difficult=False, transforms=No...
    method __getitem__ (line 61) | def __getitem__(self, index):
    method __len__ (line 73) | def __len__(self):
    method get_groundtruth (line 76) | def get_groundtruth(self, index):
    method _preprocess_annotation (line 87) | def _preprocess_annotation(self, target):
    method get_img_info (line 126) | def get_img_info(self, index):
    method map_class_id_to_class_name (line 133) | def map_class_id_to_class_name(self, class_id):

FILE: GLIP/maskrcnn_benchmark/data/samplers/distributed.py
  class DistributedSampler (line 12) | class DistributedSampler(Sampler):
    method __init__ (line 27) | def __init__(self, dataset, num_replicas=None, rank=None, shuffle=True...
    method __iter__ (line 45) | def __iter__(self):
    method __len__ (line 68) | def __len__(self):
    method set_epoch (line 71) | def set_epoch(self, epoch):

FILE: GLIP/maskrcnn_benchmark/data/samplers/grouped_batch_sampler.py
  class GroupedBatchSampler (line 9) | class GroupedBatchSampler(BatchSampler):
    method __init__ (line 24) | def __init__(self, sampler, group_ids, batch_size, drop_uneven=False):
    method _prepare_batches (line 40) | def _prepare_batches(self):
    method __iter__ (line 102) | def __iter__(self):
    method __len__ (line 111) | def __len__(self):

FILE: GLIP/maskrcnn_benchmark/data/samplers/iteration_based_batch_sampler.py
  class IterationBasedBatchSampler (line 5) | class IterationBasedBatchSampler(BatchSampler):
    method __init__ (line 11) | def __init__(self, batch_sampler, num_iterations, start_iter=0):
    method __iter__ (line 16) | def __iter__(self):
    method __len__ (line 30) | def __len__(self):

FILE: GLIP/maskrcnn_benchmark/data/transforms/build.py
  function build_transforms (line 5) | def build_transforms(cfg, is_train=True):

FILE: GLIP/maskrcnn_benchmark/data/transforms/transforms.py
  function matrix_iou (line 12) | def matrix_iou(a, b, relative=False):
  class RACompose (line 29) | class RACompose(object):
    method __init__ (line 30) | def __init__(self, pre_transforms, rand_transforms, post_transforms, c...
    method __call__ (line 36) | def __call__(self, image, target):
    method __repr__ (line 47) | def __repr__(self):
  class Compose (line 64) | class Compose(object):
    method __init__ (line 65) | def __init__(self, transforms):
    method __call__ (line 68) | def __call__(self, image, target=None):
    method __repr__ (line 75) | def __repr__(self):
  class Resize (line 84) | class Resize(object):
    method __init__ (line 85) | def __init__(self, min_size, max_size, restrict=False):
    method get_size (line 93) | def get_size(self, image_size):
    method __call__ (line 117) | def __call__(self, image, target):
  class RandomHorizontalFlip (line 130) | class RandomHorizontalFlip(object):
    method __init__ (line 131) | def __init__(self, prob=0.5):
    method __call__ (line 134) | def __call__(self, image, target):
  class RandomVerticalFlip (line 145) | class RandomVerticalFlip(object):
    method __init__ (line 146) | def __init__(self, prob=0.5):
    method __call__ (line 149) | def __call__(self, image, target):
  class ToTensor (line 158) | class ToTensor(object):
    method __call__ (line 159) | def __call__(self, image, target):
  class Normalize (line 163) | class Normalize(object):
    method __init__ (line 164) | def __init__(self, mean, std, format='rgb'):
    method __call__ (line 169) | def __call__(self, image, target):
  class ColorJitter (line 178) | class ColorJitter(object):
    method __init__ (line 179) | def __init__(self,
    method __call__ (line 191) | def __call__(self, image, target):
  class RandomCrop (line 196) | class RandomCrop(object):
    method __init__ (line 197) | def __init__(self, prob=0.5, min_ious=(0.1, 0.3, 0.5, 0.7, 0.9), min_c...
    method __call__ (line 203) | def __call__(self, img, target):
  class RandomAffine (line 254) | class RandomAffine(object):
    method __init__ (line 255) | def __init__(self, prob=0.5, degrees=(-10, 10), translate=(.1, .1), sc...
    method __call__ (line 264) | def __call__(self, img, targets=None):
  class RandomErasing (line 332) | class RandomErasing:
    method __init__ (line 333) | def __init__(self, prob=0.5, era_l=0.02, era_h=1/3, min_aspect=0.3,
    method _get_pixels (line 346) | def _get_pixels(self, patch_size):
    method __call__ (line 354) | def __call__(self, image, target):

FILE: GLIP/maskrcnn_benchmark/engine/alter_trainer.py
  function reduce_loss_dict (line 13) | def reduce_loss_dict(all_loss_dict):
  function do_train (line 44) | def do_train(

FILE: GLIP/maskrcnn_benchmark/engine/evolution.py
  function gather_candidates (line 25) | def gather_candidates(all_candidates):
  function gather_stats (line 31) | def gather_stats(all_candidates):
  function compute_on_dataset (line 39) | def compute_on_dataset(model, rngs, data_loader, device=cfg.MODEL.DEVICE):
  function bn_statistic (line 54) | def bn_statistic(model, rngs, data_loader, device=cfg.MODEL.DEVICE, max_...
  function inference (line 73) | def inference(
  function fitness (line 109) | def fitness(cfg, model, rngs, val_loaders):
  class EvolutionTrainer (line 129) | class EvolutionTrainer(object):
    method __init__ (line 130) | def __init__(self, cfg, model, flops_limit=None, is_distributed=True):
    method save_checkpoint (line 155) | def save_checkpoint(self):
    method load_checkpoint (line 168) | def load_checkpoint(self):
    method legal (line 179) | def legal(self, cand):
    method update_top_k (line 195) | def update_top_k(self, candidates, *, k, key, reverse=False):
    method eval_candidates (line 203) | def eval_candidates(self, train_loader, val_loader):
    method stack_random_cand (line 221) | def stack_random_cand(self, random_func, *, batchsize=10):
    method random_can (line 227) | def random_can(self, num):
    method get_mutation (line 242) | def get_mutation(self, k, mutation_num, m_prob):
    method get_crossover (line 268) | def get_crossover(self, k, crossover_num):
    method train (line 292) | def train(self, train_loader, val_loader):
    method save_candidates (line 319) | def save_candidates(self, cand, template):

FILE: GLIP/maskrcnn_benchmark/engine/inference.py
  function inference_default (line 20) | def inference_default(
  function clean_name (line 85) | def clean_name(name):
  function create_one_hot_dict (line 92) | def create_one_hot_dict(labels, no_minus_one_for_one_hot = False):
  function create_positive_dict (line 111) | def create_positive_dict(tokenized, tokens_positive, labels):
  function chunks (line 146) | def chunks(lst, n):
  function create_queries_and_maps_from_dataset (line 159) | def create_queries_and_maps_from_dataset(dataset, cfg):
  function create_queries_and_maps (line 192) | def create_queries_and_maps(labels, label_list, additional_labels = None...
  function create_positive_map_label_to_token_from_positive_map (line 262) | def create_positive_map_label_to_token_from_positive_map(positive_map, p...
  function _accumulate_predictions_from_multiple_gpus (line 270) | def _accumulate_predictions_from_multiple_gpus(predictions_per_gpu):
  function resize_box (line 291) | def resize_box(output, targets):
  function flickr_post_process (line 299) | def flickr_post_process(output, targets, positive_map_label_to_token, pl...
  function build_flickr_evaluator (line 317) | def build_flickr_evaluator(cfg):
  function build_lvis_evaluator (line 324) | def build_lvis_evaluator(ann_file, fixed_ap=True):
  function write_lvis_results (line 331) | def write_lvis_results(results, output_file_name):
  function write_flickr_results (line 345) | def write_flickr_results(results, output_file_name):
  function inference (line 360) | def inference(

FILE: GLIP/maskrcnn_benchmark/engine/predictor.py
  class COCODemo (line 19) | class COCODemo(object):
    method __init__ (line 105) | def __init__(
    method build_transform (line 139) | def build_transform(self):
    method inference (line 169) | def inference(self, image, debug=False):
    method run_on_opencv_image (line 187) | def run_on_opencv_image(self, image):
    method compute_prediction (line 212) | def compute_prediction(self, original_image):
    method select_top_predictions (line 258) | def select_top_predictions(self, predictions):
    method compute_colors_for_labels (line 297) | def compute_colors_for_labels(self, labels):
    method overlay_boxes (line 305) | def overlay_boxes(self, image, predictions):
    method overlay_scores (line 327) | def overlay_scores(self, image, predictions):
    method overlay_cboxes (line 348) | def overlay_cboxes(self, image, predictions):
    method overlay_centers (line 370) | def overlay_centers(self, image, predictions):
    method overlay_count (line 388) | def overlay_count(self, image, predictions):
    method overlay_mask (line 405) | def overlay_mask(self, image, predictions):
    method overlay_keypoints (line 431) | def overlay_keypoints(self, image, predictions):
    method create_mask_montage (line 441) | def create_mask_montage(self, image, predictions):
    method overlay_class_names (line 477) | def overlay_class_names(self, image, predictions, names=None):
  function vis_keypoints (line 505) | def vis_keypoints(img, kps, kp_thresh=0, alpha=0.7, names=None, connecti...

FILE: GLIP/maskrcnn_benchmark/engine/predictor_glip.py
  class GLIPDemo (line 29) | class GLIPDemo(object):
    method __init__ (line 30) | def __init__(self,
    method build_transform (line 61) | def build_transform(self):
    method build_tokenizer (line 91) | def build_tokenizer(self):
    method run_ner (line 106) | def run_ner(self, caption):
    method inference (line 130) | def inference(self, original_image, original_caption, thresh=None):
    method inference_batch (line 138) | def inference_batch(self, original_image_list, original_caption, thres...
    method run_on_web_image (line 148) | def run_on_web_image(self, original_image, original_caption, thresh=0.5):
    method compute_prediction (line 162) | def compute_prediction(self, original_image, original_caption):
    method compute_prediction_batch (line 208) | def compute_prediction_batch(self, original_image_list, original_capti...
    method _post_process_fixed_thresh (line 255) | def _post_process_fixed_thresh(self, predictions):
    method _post_process (line 273) | def _post_process(self, predictions, threshold=0.5):
    method compute_colors_for_labels (line 291) | def compute_colors_for_labels(self, labels):
    method overlay_boxes (line 299) | def overlay_boxes(self, image, predictions):
    method overlay_scores (line 313) | def overlay_scores(self, image, predictions):
    method overlay_entity_names (line 326) | def overlay_entity_names(self, image, predictions, names=None):
    method overlay_mask (line 352) | def overlay_mask(self, image, predictions):
    method create_mask_montage (line 373) | def create_mask_montage(self, image, predictions):
  function create_positive_map_label_to_token_from_positive_map (line 402) | def create_positive_map_label_to_token_from_positive_map(positive_map, p...
  function create_positive_map (line 409) | def create_positive_map(tokenized, tokens_positive):
  function find_noun_phrases (line 445) | def find_noun_phrases(caption: str) -> List[str]:
  function remove_punctuation (line 462) | def remove_punctuation(text: str) -> str:

FILE: GLIP/maskrcnn_benchmark/engine/singlepath_trainer.py
  function reduce_loss_dict (line 13) | def reduce_loss_dict(loss_dict):
  function do_train (line 38) | def do_train(

FILE: GLIP/maskrcnn_benchmark/engine/stage_trainer.py
  function reduce_loss_dict (line 13) | def reduce_loss_dict(all_loss_dict):
  function do_train (line 44) | def do_train(

FILE: GLIP/maskrcnn_benchmark/engine/trainer.py
  function reduce_loss_dict (line 20) | def reduce_loss_dict(loss_dict):
  function do_train (line 45) | def do_train(

FILE: GLIP/maskrcnn_benchmark/layers/batch_norm.py
  class FrozenBatchNorm2d (line 9) | class FrozenBatchNorm2d(nn.Module):
    method __init__ (line 15) | def __init__(self, n):
    method forward (line 22) | def forward(self, x):
  class AllReduce (line 30) | class AllReduce(Function):
    method forward (line 32) | def forward(ctx, input):
    method backward (line 40) | def backward(ctx, grad_output):
  class NaiveSyncBatchNorm2d (line 45) | class NaiveSyncBatchNorm2d(nn.BatchNorm2d):
    method __init__ (line 73) | def __init__(self, *args, stats_mode="", **kwargs):
    method forward (line 78) | def forward(self, input):

FILE: GLIP/maskrcnn_benchmark/layers/deform_conv.py
  class DeformConvFunction (line 12) | class DeformConvFunction(Function):
    method forward (line 15) | def forward(
    method backward (line 75) | def backward(ctx, grad_output):
    method _output_size (line 137) | def _output_size(input, weight, padding, dilation, stride):
  class ModulatedDeformConvFunction (line 152) | class ModulatedDeformConvFunction(Function):
    method forward (line 155) | def forward(
    method backward (line 209) | def backward(ctx, grad_output):
    method _infer_shape (line 251) | def _infer_shape(ctx, input, weight):
  class DeformConv (line 267) | class DeformConv(nn.Module):
    method __init__ (line 269) | def __init__(
    method reset_parameters (line 306) | def reset_parameters(self):
    method forward (line 314) | def forward(self, input, offset):
    method __repr__ (line 319) | def __repr__(self):
  class ModulatedDeformConv (line 333) | class ModulatedDeformConv(nn.Module):
    method __init__ (line 335) | def __init__(
    method reset_parameters (line 369) | def reset_parameters(self):
    method forward (line 379) | def forward(self, input, offset, mask):
    method __repr__ (line 384) | def __repr__(self):
  class ModulatedDeformConvPack (line 398) | class ModulatedDeformConvPack(ModulatedDeformConv):
    method __init__ (line 400) | def __init__(self,
    method init_offset (line 424) | def init_offset(self):
    method forward (line 429) | def forward(self, input):

FILE: GLIP/maskrcnn_benchmark/layers/deform_pool.py
  function add_conv (line 7) | def add_conv(in_ch, out_ch, ksize, stride, leaky=True):
  class upsample (line 31) | class upsample(nn.Module):
    method __init__ (line 34) | def __init__(self, size=None, scale_factor=None, mode='nearest', align...
    method forward (line 42) | def forward(self, input):
    method extra_repr (line 45) | def extra_repr(self):
  class SPPLayer (line 53) | class SPPLayer(nn.Module):
    method __init__ (line 54) | def __init__(self):
    method forward (line 57) | def forward(self, x):
  class DropBlock (line 65) | class DropBlock(nn.Module):
    method __init__ (line 66) | def __init__(self, block_size=7, keep_prob=0.9):
    method reset (line 75) | def reset(self, block_size, keep_prob):
    method calculate_gamma (line 83) | def calculate_gamma(self, x):
    method forward (line 87) | def forward(self, x):
  class resblock (line 109) | class resblock(nn.Module):
    method __init__ (line 118) | def __init__(self, ch, nblocks=1, shortcut=True):
    method forward (line 129) | def forward(self, x):
  class RFBblock (line 138) | class RFBblock(nn.Module):
    method __init__ (line 139) | def __init__(self,in_ch,residual=False):
    method forward (line 161) | def forward(self,x):
  class FeatureAdaption (line 172) | class FeatureAdaption(nn.Module):
    method __init__ (line 173) | def __init__(self, in_ch, out_ch, n_anchors, rfb=False, sep=False):
    method forward (line 187) | def forward(self, input, wh_pred):
  class ASFFmobile (line 200) | class ASFFmobile(nn.Module):
    method __init__ (line 201) | def __init__(self, level, rfb=False, vis=False):
    method forward (line 229) | def forward(self, x_level_0, x_level_1, x_level_2):
  class ASFF (line 268) | class ASFF(nn.Module):
    method __init__ (line 269) | def __init__(self, level, rfb=False, vis=False):
    method forward (line 296) | def forward(self, x_level_0, x_level_1, x_level_2):
  function make_divisible (line 333) | def make_divisible(v, divisor, min_value=None):
  class ConvBNReLU (line 353) | class ConvBNReLU(nn.Sequential):
    method __init__ (line 354) | def __init__(self, in_planes, out_planes, kernel_size=3, stride=1, gro...
  function add_sepconv (line 362) | def add_sepconv(in_ch, out_ch, ksize, stride):
  class InvertedResidual (line 376) | class InvertedResidual(nn.Module):
    method __init__ (line 377) | def __init__(self, inp, oup, stride, expand_ratio):
    method forward (line 398) | def forward(self, x):
  class ressepblock (line 404) | class ressepblock(nn.Module):
    method __init__ (line 405) | def __init__(self, ch, out_ch, in_ch=None, shortcut=True):
    method forward (line 416) | def forward(self, x):

FILE: GLIP/maskrcnn_benchmark/layers/dropblock.py
  class DropBlock2D (line 6) | class DropBlock2D(nn.Module):
    method __init__ (line 27) | def __init__(self, drop_prob, block_size):
    method forward (line 33) | def forward(self, x):
    method _compute_block_mask (line 62) | def _compute_block_mask(self, mask):
    method _compute_gamma (line 75) | def _compute_gamma(self, x):
  class DropBlock3D (line 79) | class DropBlock3D(DropBlock2D):
    method __init__ (line 100) | def __init__(self, drop_prob, block_size):
    method forward (line 103) | def forward(self, x):
    method _compute_block_mask (line 132) | def _compute_block_mask(self, mask):
    method _compute_gamma (line 145) | def _compute_gamma(self, x):

FILE: GLIP/maskrcnn_benchmark/layers/dyhead.py
  class Conv3x3Norm (line 9) | class Conv3x3Norm(torch.nn.Module):
    method __init__ (line 10) | def __init__(self,
    method forward (line 28) | def forward(self, input, **kwargs):
  class DyConv (line 35) | class DyConv(nn.Module):
    method __init__ (line 36) | def __init__(self,
    method init_weights (line 72) | def init_weights(self):
    method forward (line 85) | def forward(self, x):
  class DyHead (line 122) | class DyHead(nn.Module):
    method __init__ (line 123) | def __init__(self, cfg, in_channels):
    method forward (line 149) | def forward(self, x):

FILE: GLIP/maskrcnn_benchmark/layers/dyrelu.py
  function _make_divisible (line 5) | def _make_divisible(v, divisor, min_value=None):
  class swish (line 15) | class swish(nn.Module):
    method forward (line 16) | def forward(self, x):
  class h_swish (line 20) | class h_swish(nn.Module):
    method __init__ (line 21) | def __init__(self, inplace=False):
    method forward (line 25) | def forward(self, x):
  class h_sigmoid (line 29) | class h_sigmoid(nn.Module):
    method __init__ (line 30) | def __init__(self, inplace=True, h_max=1):
    method forward (line 35) | def forward(self, x):
  class DYReLU (line 39) | class DYReLU(nn.Module):
    method __init__ (line 40) | def __init__(self, inp, oup, reduction=4, lambda_a=1.0, K2=True, use_b...
    method forward (line 78) | def forward(self, x):

FILE: GLIP/maskrcnn_benchmark/layers/evonorm.py
  class EvoNorm2d (line 5) | class EvoNorm2d(nn.Module):
    method __init__ (line 8) | def __init__(self, num_features, eps=1e-5, nonlinearity=True, group=32):
    method reset_parameters (line 23) | def reset_parameters(self):
    method group_std (line 29) | def group_std(self, x, groups=32):
    method forward (line 35) | def forward(self, x):

FILE: GLIP/maskrcnn_benchmark/layers/iou_loss.py
  class IOULoss (line 5) | class IOULoss(nn.Module):
    method __init__ (line 6) | def __init__(self, loss_type="iou"):
    method forward (line 10) | def forward(self, pred, target, weight=None):
  class IOUWHLoss (line 52) | class IOUWHLoss(nn.Module):  # used for anchor guiding
    method __init__ (line 53) | def __init__(self, reduction='none'):
    method forward (line 57) | def forward(self, pred, target):

FILE: GLIP/maskrcnn_benchmark/layers/misc.py
  class _NewEmptyTensorOp (line 17) | class _NewEmptyTensorOp(torch.autograd.Function):
    method forward (line 19) | def forward(ctx, x, new_shape):
    method backward (line 24) | def backward(ctx, grad):
  class Conv2d (line 29) | class Conv2d(torch.nn.Conv2d):
    method forward (line 30) | def forward(self, x):
  class ConvTranspose2d (line 45) | class ConvTranspose2d(torch.nn.ConvTranspose2d):
    method forward (line 46) | def forward(self, x):
  class BatchNorm2d (line 66) | class BatchNorm2d(torch.nn.BatchNorm2d):
    method forward (line 67) | def forward(self, x):
  function interpolate (line 75) | def interpolate(
  class Scale (line 113) | class Scale(torch.nn.Module):
    method __init__ (line 114) | def __init__(self, init_value=1.0):
    method forward (line 118) | def forward(self, input):
  class DFConv2d (line 122) | class DFConv2d(torch.nn.Module):
    method __init__ (line 124) | def __init__(
    method forward (line 181) | def forward(self, x):

FILE: GLIP/maskrcnn_benchmark/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_ratio):
    method backward (line 25) | 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):
    method forward (line 58) | def forward(self, input, rois):
    method __repr__ (line 63) | def __repr__(self):
  class ROIAlignV2 (line 71) | class ROIAlignV2(nn.Module):
    method __init__ (line 72) | def __init__(self, output_size, spatial_scale, sampling_ratio):
    method forward (line 78) | def forward(self, input, rois):
    method __repr__ (line 83) | def __repr__(self):

FILE: GLIP/maskrcnn_benchmark/layers/roi_pool.py
  class _ROIPool (line 11) | class _ROIPool(Function):
    method forward (line 13) | def forward(ctx, input, roi, output_size, spatial_scale):
    method backward (line 25) | def backward(ctx, grad_output):
  class ROIPool (line 49) | class ROIPool(nn.Module):
    method __init__ (line 50) | def __init__(self, output_size, spatial_scale):
    method forward (line 55) | def forward(self, input, rois):
    method __repr__ (line 58) | def __repr__(self):

FILE: GLIP/maskrcnn_benchmark/layers/se.py
  class SELayer (line 4) | class SELayer(nn.Module):
    method __init__ (line 5) | def __init__(self, channel, reduction=16):
    method forward (line 15) | def forward(self, x):
  class SEBlock (line 22) | class SEBlock(nn.Module):
    method __init__ (line 23) | def __init__(self, channels, reduction=16,
    method forward (line 41) | def forward(self, x):

FILE: GLIP/maskrcnn_benchmark/layers/set_loss.py
  function box_area (line 10) | def box_area(boxes):
  function box_iou (line 15) | def box_iou(boxes1, boxes2):
  function generalized_box_iou (line 31) | def generalized_box_iou(boxes1, boxes2):
  function dice_loss (line 55) | def dice_loss(inputs, targets, num_boxes):
  function sigmoid_focal_loss (line 73) | def sigmoid_focal_loss(inputs: torch.Tensor, targets: torch.Tensor, alph...
  class HungarianMatcher (line 115) | class HungarianMatcher(nn.Module):
    method __init__ (line 123) | def __init__(self, cost_class: float = 1, cost_bbox: float = 1, cost_g...
    method forward (line 145) | def forward(self, outputs, targets):
  class SetCriterion (line 217) | class SetCriterion(nn.Module):
    method __init__ (line 223) | def __init__(self, num_classes, matcher, weight_dict, eos_coef, losses,
    method loss_labels (line 248) | def loss_labels(self, outputs, targets, indices, num_boxes, log=False):
    method loss_boxes (line 283) | def loss_boxes(self, outputs, targets, indices, num_boxes):
    method _get_src_permutation_idx (line 306) | def _get_src_permutation_idx(self, indices):
    method _get_tgt_permutation_idx (line 312) | def _get_tgt_permutation_idx(self, indices):
    method get_loss (line 318) | def get_loss(self, loss, outputs, targets, indices, num_boxes, **kwargs):
    method forward (line 327) | def forward(self, outputs, targets, *argrs, **kwargs):

FILE: GLIP/maskrcnn_benchmark/layers/sigmoid_focal_loss.py
  class _SigmoidFocalLoss (line 11) | class _SigmoidFocalLoss(Function):
    method forward (line 13) | def forward(ctx, logits, targets, gamma, alpha):
    method backward (line 27) | def backward(ctx, d_loss):
  function sigmoid_focal_loss_cpu (line 42) | def sigmoid_focal_loss_cpu(logits, targets, gamma, alpha):
  class SigmoidFocalLoss (line 55) | class SigmoidFocalLoss(nn.Module):
    method __init__ (line 56) | def __init__(self, gamma, alpha):
    method forward (line 61) | def forward(self, logits, targets):
    method __repr__ (line 70) | def __repr__(self):
  function token_sigmoid_softmax_focal_loss (line 78) | def token_sigmoid_softmax_focal_loss(pred_logits, targets, alpha, gamma,...
  function token_sigmoid_binary_focal_loss_v2 (line 110) | def token_sigmoid_binary_focal_loss_v2(pred_logits, targets, alpha, gamm...
  function token_sigmoid_binary_focal_loss (line 130) | def token_sigmoid_binary_focal_loss(pred_logits, targets, alpha, gamma, ...
  class TokenSigmoidFocalLoss (line 174) | class TokenSigmoidFocalLoss(nn.Module):
    method __init__ (line 175) | def __init__(self, alpha, gamma):
    method forward (line 180) | def forward(self, logits, targets, text_masks=None, version="binary", ...
    method __repr__ (line 192) | def __repr__(self):

FILE: GLIP/maskrcnn_benchmark/layers/smooth_l1_loss.py
  function smooth_l1_loss (line 6) | def smooth_l1_loss(input, target, beta=1. / 9, size_average=True):

FILE: GLIP/maskrcnn_benchmark/modeling/backbone/__init__.py
  function build_resnet_backbone (line 23) | def build_resnet_backbone(cfg):
  function build_resnet_c5_backbone (line 31) | def build_resnet_c5_backbone(cfg):
  function build_retinanet_swint_fpn_backbone (line 38) | def build_retinanet_swint_fpn_backbone(cfg):
  function build_swint_fpn_backbone (line 84) | def build_swint_fpn_backbone(cfg):
  function build_retinanet_cvt_fpn_backbone (line 128) | def build_retinanet_cvt_fpn_backbone(cfg):
  function build_eff_fpn_p6p7_backbone (line 170) | def build_eff_fpn_p6p7_backbone(cfg):
  function build_eff_fpn_p6p7_backbone (line 199) | def build_eff_fpn_p6p7_backbone(cfg):
  function build_efficientdet_backbone (line 220) | def build_efficientdet_backbone(cfg):
  function build_backbone (line 234) | def build_backbone(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/backbone/bifpn.py
  class BiFPN (line 7) | class BiFPN(nn.Module):
    method __init__ (line 8) | def __init__(self, in_channels_list, out_channels, first_time=False, e...
    method forward (line 120) | def forward(self, inputs):
    method _forward_fast_attention (line 151) | def _forward_fast_attention(self, inputs):
    method _forward (line 225) | def _forward(self, inputs):

FILE: GLIP/maskrcnn_benchmark/modeling/backbone/blocks.py
  class stem (line 5) | class stem(nn.Module):
    method __init__ (line 8) | def __init__(self, conv, inplanes, planes, stride=1, norm_layer=nn.Bat...
    method forward (line 15) | def forward(self, x):
  class basic (line 23) | class basic(nn.Module):
    method __init__ (line 27) | def __init__(self, conv, inplanes, planes, stride=1, midplanes=None, n...
    method forward (line 43) | def forward(self, x):
  class bottleneck (line 62) | class bottleneck(nn.Module):
    method __init__ (line 66) | def __init__(self, conv, inplanes, planes, stride=1, midplanes=None, n...
    method forward (line 84) | def forward(self, x):
  class invert (line 107) | class invert(nn.Module):
    method __init__ (line 108) | def __init__(self, conv, inp, oup, stride=1, expand_ratio=1, norm_laye...
    method forward (line 141) | def forward(self, x):
  function channel_shuffle (line 154) | def channel_shuffle(x, groups):
  class shuffle (line 165) | class shuffle(nn.Module):
    method __init__ (line 169) | def __init__(self, conv, inplanes, outplanes, stride=1, midplanes=None...
    method forward (line 201) | def forward(self, x):
  class shufflex (line 212) | class shufflex(nn.Module):
    method __init__ (line 216) | def __init__(self, conv, inplanes, outplanes, stride=1, midplanes=None...
    method forward (line 258) | def forward(self, x):

FILE: GLIP/maskrcnn_benchmark/modeling/backbone/efficientdet.py
  class MaxPool2dStaticSamePadding (line 32) | class MaxPool2dStaticSamePadding(nn.Module):
    method __init__ (line 38) | def __init__(self, kernel_size, stride):
    method forward (line 59) | def forward(self, x):
  class Conv2dStaticSamePadding (line 84) | class Conv2dStaticSamePadding(nn.Module):
    method __init__ (line 90) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, b...
    method forward (line 124) | def forward(self, x):
  class SeparableConvBlock (line 149) | class SeparableConvBlock(nn.Module):
    method __init__ (line 154) | def __init__(self, in_channels, out_channels=None, norm=True, activati...
    method forward (line 177) | def forward(self, x):
  class BiFPN (line 190) | class BiFPN(nn.Module):
    method __init__ (line 195) | def __init__(self, num_channels, conv_channels, first_time=False,
    method forward (line 297) | def forward(self, inputs):
    method _forward_fast_attention (line 327) | def _forward_fast_attention(self, inputs):
    method _forward (line 433) | def _forward(self, inputs):
  class Regressor (line 484) | class Regressor(nn.Module):
    method __init__ (line 489) | def __init__(self, in_channels, num_anchors, num_layers, onnx_export=F...
    method forward (line 502) | def forward(self, inputs):
  class SwishImplementation (line 519) | class SwishImplementation(torch.autograd.Function):
    method forward (line 521) | def forward(ctx, i):
    method backward (line 527) | def backward(ctx, grad_output):
  class MemoryEfficientSwish (line 532) | class MemoryEfficientSwish(nn.Module):
    method forward (line 533) | def forward(self, x):
  class Swish (line 538) | class Swish(nn.Module):
    method forward (line 539) | def forward(self, x):
  class Classifier (line 542) | class Classifier(nn.Module):
    method __init__ (line 547) | def __init__(self, in_channels, num_anchors, num_classes, num_layers,
    method forward (line 567) | def forward(self, inputs):
  class Conv2dDynamicSamePadding (line 588) | class Conv2dDynamicSamePadding(nn.Conv2d):
    method __init__ (line 591) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, d...
    method forward (line 596) | def forward(self, x):
  function get_same_padding_conv2d (line 609) | def get_same_padding_conv2d(image_size=None):
  function round_filters (line 619) | def round_filters(filters, global_params):
  function round_repeats (line 633) | def round_repeats(repeats, global_params):
  function drop_connect (line 640) | def drop_connect(inputs, p, training):
  class MBConvBlock (line 651) | class MBConvBlock(nn.Module):
    method __init__ (line 663) | def __init__(self, block_args, global_params):
    method forward (line 703) | def forward(self, inputs, drop_connect_rate=None):
    method set_swish (line 740) | def set_swish(self, memory_efficient=True):
  class BlockDecoder (line 744) | class BlockDecoder(object):
    method _decode_block_string (line 748) | def _decode_block_string(block_string):
    method _encode_block_string (line 775) | def _encode_block_string(block):
    method decode (line 792) | def decode(string_list):
    method encode (line 806) | def encode(blocks_args):
  function efficientnet (line 818) | def efficientnet(width_coefficient=None, depth_coefficient=None, dropout...
  function efficientnet_params (line 847) | def efficientnet_params(model_name):
  function get_model_params (line 865) | def get_model_params(model_name, override_params):
  function load_pretrained_weights (line 902) | def load_pretrained_weights(model, model_name, load_fc=True, advprop=Fal...
  class EfficientNet (line 919) | class EfficientNet(nn.Module):
    method __init__ (line 932) | def __init__(self, blocks_args=None, global_params=None):
    method set_swish (line 982) | def set_swish(self, memory_efficient=True):
    method extract_features (line 988) | def extract_features(self, inputs):
    method forward (line 1005) | def forward(self, inputs):
    method from_name (line 1019) | def from_name(cls, model_name, override_params=None):
    method from_pretrained (line 1025) | def from_pretrained(cls, model_name, load_weights=True, advprop=True, ...
    method get_image_size (line 1036) | def get_image_size(cls, model_name):
    method _check_model_name_is_valid (line 1042) | def _check_model_name_is_valid(cls, model_name):
  class EfficientNetD (line 1048) | class EfficientNetD(nn.Module):
    method __init__ (line 1053) | def __init__(self, compound_coef, load_weights=False):
    method forward (line 1063) | def forward(self, x):
  class Anchors (line 1087) | class Anchors(nn.Module):
    method __init__ (line 1092) | def __init__(self, anchor_scale=4., pyramid_levels=None, **kwargs):
    method forward (line 1108) | def forward(self, image, dtype=torch.float32, features=None):
    method get_key (line 1190) | def get_key(self, hint, image_shape):
  class EffNetFPN (line 1193) | class EffNetFPN(nn.Module):
    method __init__ (line 1194) | def __init__(self, compound_coef=0, start_from=3):
    method forward (line 1216) | def forward(self, inputs):
  class EfficientDetBackbone (line 1229) | class EfficientDetBackbone(nn.Module):
    method __init__ (line 1256) | def __init__(self, num_classes=80, compound_coef=0, load_weights=False,
    method freeze_bn (line 1293) | def freeze_bn(self):
    method forward (line 1298) | def forward(self, inputs):
    method init_backbone (line 1310) | def init_backbone(self, path):
  function init_weights (line 1318) | def init_weights(model):
  function calc_iou (line 1328) | def calc_iou(a, b):
  class BBoxTransform (line 1344) | class BBoxTransform(nn.Module):
    method forward (line 1345) | def forward(self, anchors, regression):
  class ClipBoxes (line 1377) | class ClipBoxes(nn.Module):
    method __init__ (line 1379) | def __init__(self):
    method forward (line 1382) | def forward(self, boxes, img):
  function postprocess2 (line 1393) | def postprocess2(x, anchors, regression, classification,
  function postprocess (line 1450) | def postprocess(x, anchors, regression, classification, regressBoxes, cl...
  function display (line 1490) | def display(preds, imgs, obj_list, imshow=True, imwrite=False):
  function calculate_focal_loss2 (line 1510) | def calculate_focal_loss2(classification, target_list, alpha, gamma):
  function calculate_focal_loss (line 1515) | def calculate_focal_loss(classification, targets, alpha, gamma):
  function calculate_giou (line 1534) | def calculate_giou(pred, gt):
  class FocalLoss (line 1556) | class FocalLoss(nn.Module):
    method __init__ (line 1557) | def __init__(self, alpha=0.25, gamma=2., cls_loss_type='FL', smooth_bc...
    method forward (line 1602) | def forward(self, classifications, regressions, anchor_info, annotatio...
  class ModelWithLoss (line 1761) | class ModelWithLoss(nn.Module):
    method __init__ (line 1762) | def __init__(self, model, criterion):
    method forward (line 1767) | def forward(self, *args):
  class TorchVisionNMS (line 1776) | class TorchVisionNMS(nn.Module):
    method __init__ (line 1777) | def __init__(self, iou_threshold):
    method forward (line 1781) | def forward(self, box, prob):
  class PostProcess (line 1785) | class PostProcess(nn.Module):
    method __init__ (line 1786) | def __init__(self, iou_threshold):
    method forward (line 1790) | def forward(self, x, anchors, regression,
  class InferenceModel (line 1846) | class InferenceModel(nn.Module):
    method __init__ (line 1847) | def __init__(self, model):
    method forward (line 1859) | def forward(self, sample):

FILE: GLIP/maskrcnn_benchmark/modeling/backbone/efficientnet.py
  function round_channels (line 17) | def round_channels(channels,
  function calc_tf_padding (line 40) | def calc_tf_padding(x,
  class ConvBlock (line 71) | class ConvBlock(nn.Module):
    method __init__ (line 100) | def __init__(self,
    method forward (line 136) | def forward(self, x):
  function conv1x1_block (line 147) | def conv1x1_block(in_channels,
  function conv3x3_block (line 193) | def conv3x3_block(in_channels,
  function dwconv3x3_block (line 243) | def dwconv3x3_block(in_channels,
  function dwconv5x5_block (line 287) | def dwconv5x5_block(in_channels,
  class EffiDwsConvUnit (line 331) | class EffiDwsConvUnit(nn.Module):
    method __init__ (line 351) | def __init__(self,
    method forward (line 378) | def forward(self, x):
  class EffiInvResUnit (line 391) | class EffiInvResUnit(nn.Module):
    method __init__ (line 416) | def __init__(self,
    method forward (line 458) | def forward(self, x):
  class EffiInitBlock (line 473) | class EffiInitBlock(nn.Module):
    method __init__ (line 491) | def __init__(self,
    method forward (line 508) | def forward(self, x):
  class EfficientNet (line 515) | class EfficientNet(nn.Module):
    method __init__ (line 547) | def __init__(self,
    method _freeze_backbone (line 608) | def _freeze_backbone(self, freeze_at):
    method forward (line 616) | def forward(self, x):
  function get_efficientnet (line 625) | def get_efficientnet(cfg, version, tf_mode = True, bn_eps=1e-5, **kwargs):

FILE: GLIP/maskrcnn_benchmark/modeling/backbone/fbnet.py
  function _py2_round (line 23) | def _py2_round(x):
  function _get_divisible_by (line 27) | def _get_divisible_by(num, divisible_by, min_val):
  class Identity (line 34) | class Identity(nn.Module):
    method __init__ (line 35) | def __init__(self, C_in, C_out, stride):
    method forward (line 52) | def forward(self, x):
  class CascadeConv3x3 (line 60) | class CascadeConv3x3(nn.Sequential):
    method __init__ (line 61) | def __init__(self, C_in, C_out, stride):
    method forward (line 73) | def forward(self, x):
  class Shift (line 80) | class Shift(nn.Module):
    method __init__ (line 81) | def __init__(self, C, kernel_size, stride, padding):
    method forward (line 108) | def forward(self, x):
  class ShiftBlock5x5 (line 134) | class ShiftBlock5x5(nn.Sequential):
    method __init__ (line 135) | def __init__(self, C_in, C_out, expansion, stride):
    method forward (line 154) | def forward(self, x):
  class ChannelShuffle (line 161) | class ChannelShuffle(nn.Module):
    method __init__ (line 162) | def __init__(self, groups):
    method forward (line 166) | def forward(self, x):
  class ConvBNRelu (line 181) | class ConvBNRelu(nn.Sequential):
    method __init__ (line 182) | def __init__(
  class SEModule (line 240) | class SEModule(nn.Module):
    method __init__ (line 243) | def __init__(self, C):
    method forward (line 253) | def forward(self, x):
  class Upsample (line 257) | class Upsample(nn.Module):
    method __init__ (line 258) | def __init__(self, scale_factor, mode, align_corners=None):
    method forward (line 264) | def forward(self, x):
  function _get_upsample_op (line 271) | def _get_upsample_op(stride):
  class IRFBlock (line 288) | class IRFBlock(nn.Module):
    method __init__ (line 289) | def __init__(
    method forward (line 392) | def forward(self, x):

FILE: GLIP/maskrcnn_benchmark/modeling/backbone/fpn.py
  class FPN (line 6) | class FPN(nn.Module):
    method __init__ (line 13) | def __init__(
    method forward (line 59) | def forward(self, x):
  class LastLevelMaxPool (line 132) | class LastLevelMaxPool(nn.Module):
    method forward (line 133) | def forward(self, x):
  class LastLevelP6P7 (line 137) | class LastLevelP6P7(nn.Module):
    method __init__ (line 141) | def __init__(self, in_channels, out_channels):
    method forward (line 150) | def forward(self, c5, p5):
  class SPPLayer (line 157) | class SPPLayer(nn.Module):
    method __init__ (line 158) | def __init__(self):
    method forward (line 161) | def forward(self, x):

FILE: GLIP/maskrcnn_benchmark/modeling/backbone/mixer.py
  class MixedOperationRandom (line 4) | class MixedOperationRandom(nn.Module):
    method __init__ (line 5) | def __init__(self, search_ops):
    method forward (line 10) | def forward(self, x, x_path=None):

FILE: GLIP/maskrcnn_benchmark/modeling/backbone/ops.py
  function conv7x7 (line 7) | def conv7x7(in_planes, out_planes, stride=1, groups=1, dilation=1):
  function conv5x5 (line 13) | def conv5x5(in_planes, out_planes, stride=1, groups=1, dilation=1):
  function conv3x3 (line 19) | def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
  function conv1x1 (line 25) | def conv1x1(in_planes, out_planes, stride=1):
  function maxpool (line 30) | def maxpool(**kwargs):
  function avgpool (line 34) | def avgpool(**kwargs):
  function dropout (line 37) | def dropout(prob):

FILE: GLIP/maskrcnn_benchmark/modeling/backbone/resnet.py
  class ResNet (line 81) | class ResNet(nn.Module):
    method __init__ (line 82) | def __init__(self, cfg):
    method _freeze_backbone (line 159) | def _freeze_backbone(self, freeze_at):
    method forward (line 170) | def forward(self, x):
  class ResNetHead (line 180) | class ResNetHead(nn.Module):
    method __init__ (line 181) | def __init__(
    method forward (line 226) | def forward(self, x):
  function _make_stage (line 232) | def _make_stage(
  class Bottleneck (line 278) | class Bottleneck(nn.Module):
    method __init__ (line 279) | def __init__(
    method forward (line 382) | def forward(self, x):
  class BaseStem (line 408) | class BaseStem(nn.Module):
    method __init__ (line 409) | def __init__(self, cfg, norm_func):
    method forward (line 435) | def forward(self, x):
  class BottleneckWithFixedBatchNorm (line 451) | class BottleneckWithFixedBatchNorm(Bottleneck):
    method __init__ (line 452) | def __init__(
  class StemWithFixedBatchNorm (line 478) | class StemWithFixedBatchNorm(BaseStem):
    method __init__ (line 479) | def __init__(self, cfg):
  class BottleneckWithBatchNorm (line 485) | class BottleneckWithBatchNorm(Bottleneck):
    method __init__ (line 486) | def __init__(
  class StemWithBatchNorm (line 512) | class StemWithBatchNorm(BaseStem):
    method __init__ (line 513) | def __init__(self, cfg):
  class BottleneckWithNaiveSyncBatchNorm (line 519) | class BottleneckWithNaiveSyncBatchNorm(Bottleneck):
    method __init__ (line 520) | def __init__(
  class StemWithNaiveSyncBatchNorm (line 546) | class StemWithNaiveSyncBatchNorm(BaseStem):
    method __init__ (line 547) | def __init__(self, cfg):
  class BottleneckWithSyncBatchNorm (line 553) | class BottleneckWithSyncBatchNorm(Bottleneck):
    method __init__ (line 554) | def __init__(
  class StemWithSyncBatchNorm (line 580) | class StemWithSyncBatchNorm(BaseStem):
    method __init__ (line 581) | def __init__(self, cfg):
  class BottleneckWithGN (line 587) | class BottleneckWithGN(Bottleneck):
    method __init__ (line 588) | def __init__(
  class StemWithGN (line 614) | class StemWithGN(BaseStem):
    method __init__ (line 615) | def __init__(self, cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/backbone/swint.py
  class Mlp (line 13) | class Mlp(nn.Module):
    method __init__ (line 16) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 25) | def forward(self, x):
  function window_partition (line 34) | def window_partition(x, window_size):
  function window_reverse (line 48) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 64) | class WindowAttention(nn.Module):
    method __init__ (line 77) | def __init__(self, dim, window_size, num_heads, qkv_bias=True, qk_scal...
    method forward (line 111) | def forward(self, x, mask=None):
  class SwinTransformerBlock (line 145) | class SwinTransformerBlock(nn.Module):
    method __init__ (line 162) | def __init__(self, dim, num_heads, window_size=7, shift_size=0,
    method forward (line 186) | def forward(self, x, mask_matrix):
  class PatchMerging (line 245) | class PatchMerging(nn.Module):
    method __init__ (line 252) | def __init__(self, dim, norm_layer=nn.LayerNorm):
    method forward (line 258) | def forward(self, x, H, W):
  class BasicLayer (line 287) | class BasicLayer(nn.Module):
    method __init__ (line 305) | def __init__(self,
    method forward (line 347) | def forward(self, x, H, W):
  class PatchEmbed (line 389) | class PatchEmbed(nn.Module):
    method __init__ (line 398) | def __init__(self, patch_size=4, in_chans=3, embed_dim=96, norm_layer=...
    method forward (line 412) | def forward(self, x):
  class SwinTransformer (line 431) | class SwinTransformer(nn.Module):
    method __init__ (line 459) | def __init__(self,
    method _freeze_stages (line 556) | def _freeze_stages(self):
    method init_weights (line 573) | def init_weights(self, pretrained=None):
    method forward (line 591) | def forward(self, x):
    method train (line 617) | def train(self, mode=True):
  function build_swint_backbone (line 623) | def build_swint_backbone(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/backbone/swint_v2.py
  class Mlp (line 14) | class Mlp(nn.Module):
    method __init__ (line 17) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 26) | def forward(self, x):
  function window_partition (line 35) | def window_partition(x, window_size):
  function window_reverse (line 49) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 65) | class WindowAttention(nn.Module):
    method __init__ (line 78) | def __init__(self, dim, window_size, num_heads, qkv_bias=True, qk_scal...
    method forward (line 112) | def forward(self, x, mask=None):
  class SwinTransformerBlock (line 146) | class SwinTransformerBlock(nn.Module):
    method __init__ (line 163) | def __init__(self, dim, num_heads, window_size=7, shift_size=0,
    method forward (line 194) | def forward(self, x, mask_matrix):
  class PatchMerging (line 253) | class PatchMerging(nn.Module):
    method __init__ (line 260) | def __init__(self, dim, norm_layer=nn.LayerNorm):
    method forward (line 266) | def forward(self, x, H, W):
  class BasicLayer (line 295) | class BasicLayer(nn.Module):
    method __init__ (line 313) | def __init__(self,
    method forward (line 358) | def forward(self, x, H, W):
  class ConvEmbed (line 442) | class ConvEmbed(nn.Module):
    method __init__ (line 446) | def __init__(
    method forward (line 467) | def forward(self, x, H=None, W=None):
  class SwinTransformer (line 499) | class SwinTransformer(nn.Module):
    method __init__ (line 527) | def __init__(self,
    method _freeze_stages (line 635) | def _freeze_stages(self):
    method init_weights (line 652) | def init_weights(self, pretrained=None):
    method forward (line 670) | def forward(self, x):
    method train (line 697) | def train(self, mode=True):
  function build_swint_backbone (line 703) | def build_swint_backbone(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/backbone/swint_v2_vl.py
  class Mlp (line 15) | class Mlp(nn.Module):
    method __init__ (line 18) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 27) | def forward(self, x):
  function window_partition (line 36) | def window_partition(x, window_size):
  function window_reverse (line 50) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 66) | class WindowAttention(nn.Module):
    method __init__ (line 79) | def __init__(self, dim, window_size, num_heads, qkv_bias=True, qk_scal...
    method forward (line 125) | def forward(self, x, mask=None, x_text=None, mask_text=None):
  class SwinTransformerBlock (line 215) | class SwinTransformerBlock(nn.Module):
    method __init__ (line 232) | def __init__(self, dim, num_heads, window_size=7, shift_size=0,
    method forward (line 276) | def forward(self, x, mask_matrix, x_text, mask_text):
  class PatchMerging (line 347) | class PatchMerging(nn.Module):
    method __init__ (line 354) | def __init__(self, dim, norm_layer=nn.LayerNorm):
    method forward (line 360) | def forward(self, x, H, W):
  class BasicLayer (line 389) | class BasicLayer(nn.Module):
    method __init__ (line 407) | def __init__(self,
    method forward (line 456) | def forward(self, x, H, W, x_text=None, mask_text=None):
  class ConvEmbed (line 542) | class ConvEmbed(nn.Module):
    method __init__ (line 546) | def __init__(
    method forward (line 567) | def forward(self, x, H=None, W=None):
  class SwinTransformer (line 599) | class SwinTransformer(nn.Module):
    method __init__ (line 627) | def __init__(self,
    method _freeze_stages (line 744) | def _freeze_stages(self):
    method init_weights (line 761) | def init_weights(self, pretrained=None):
    method forward (line 779) | def forward(self, inputs):
    method train (line 822) | def train(self, mode=True):
  function build_swint_backbone (line 828) | def build_swint_backbone(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/backbone/swint_vl.py
  class Mlp (line 14) | class Mlp(nn.Module):
    method __init__ (line 17) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 26) | def forward(self, x):
  function window_partition (line 35) | def window_partition(x, window_size):
  function window_reverse (line 49) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 65) | class WindowAttention(nn.Module):
    method __init__ (line 78) | def __init__(self, dim, window_size, num_heads, qkv_bias=True, qk_scal...
    method forward (line 124) | def forward(self, x, mask=None, x_text=None, mask_text=None):
  class SwinTransformerBlock (line 214) | class SwinTransformerBlock(nn.Module):
    method __init__ (line 231) | def __init__(self, dim, num_heads, window_size=7, shift_size=0,
    method forward (line 264) | def forward(self, x, mask_matrix, x_text, mask_text):
  class PatchMerging (line 335) | class PatchMerging(nn.Module):
    method __init__ (line 342) | def __init__(self, dim, norm_layer=nn.LayerNorm):
    method forward (line 348) | def forward(self, x, H, W):
  class BasicLayer (line 377) | class BasicLayer(nn.Module):
    method __init__ (line 395) | def __init__(self,
    method forward (line 441) | def forward(self, x, H, W, x_text=None, mask_text=None):
  class PatchEmbed (line 485) | class PatchEmbed(nn.Module):
    method __init__ (line 494) | def __init__(self, patch_size=4, in_chans=3, embed_dim=96, norm_layer=...
    method forward (line 508) | def forward(self, x):
  class SwinTransformer (line 527) | class SwinTransformer(nn.Module):
    method __init__ (line 555) | def __init__(self,
    method _freeze_stages (line 661) | def _freeze_stages(self):
    method init_weights (line 678) | def init_weights(self, pretrained=None):
    method forward (line 696) | def forward(self, inputs):
    method train (line 739) | def train(self, mode=True):
  function build_swint_backbone (line 745) | def build_swint_backbone(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/balanced_positive_negative_sampler.py
  class BalancedPositiveNegativeSampler (line 5) | class BalancedPositiveNegativeSampler(object):
    method __init__ (line 10) | def __init__(self, batch_size_per_image, positive_fraction):
    method __call__ (line 19) | def __call__(self, matched_idxs):

FILE: GLIP/maskrcnn_benchmark/modeling/box_coder.py
  class BoxCoder (line 7) | class BoxCoder(object):
    method __init__ (line 13) | def __init__(self, weights, bbox_xform_clip=math.log(1000. / 16)):
    method encode (line 22) | def encode(self, reference_boxes, proposals):
    method decode (line 52) | def decode(self, rel_codes, boxes):

FILE: GLIP/maskrcnn_benchmark/modeling/detector/__init__.py
  function build_detection_model (line 9) | def build_detection_model(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/detector/generalized_rcnn.py
  class GeneralizedRCNN (line 17) | class GeneralizedRCNN(nn.Module):
    method __init__ (line 27) | def __init__(self, cfg):
    method train (line 45) | def train(self, mode=True):
    method forward (line 70) | def forward(self, images, targets=None):

FILE: GLIP/maskrcnn_benchmark/modeling/detector/generalized_vl_rcnn.py
  function random_word (line 26) | def random_word(input_ids, mask_token_id, vocabs, padding_token_id, gree...
  class GeneralizedVLRCNN (line 63) | class GeneralizedVLRCNN(nn.Module):
    method __init__ (line 73) | def __init__(self, cfg):
    method train (line 129) | def train(self, mode=True):
    method forward (line 170) | def forward(self,

FILE: GLIP/maskrcnn_benchmark/modeling/language_backbone/backbone.py
  function build_bert_backbone (line 13) | def build_bert_backbone(cfg):
  function build_bert_backbone (line 20) | def build_bert_backbone(cfg):
  function build_rnn_backbone (line 27) | def build_rnn_backbone(cfg):
  function build_clip_backbone (line 34) | def build_clip_backbone(cfg):
  function build_backbone (line 40) | def build_backbone(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/language_backbone/bert_model.py
  class BertEncoder (line 10) | class BertEncoder(nn.Module):
    method __init__ (line 11) | def __init__(self, cfg):
    method forward (line 32) | def forward(self, x):

FILE: GLIP/maskrcnn_benchmark/modeling/language_backbone/build.py
  function build_tokenizer (line 4) | def build_tokenizer(tokenizer_name):

FILE: GLIP/maskrcnn_benchmark/modeling/language_backbone/clip_model.py
  class LayerNorm (line 16) | class LayerNorm(nn.Module):
    method __init__ (line 17) | def __init__(self, hidden_size, eps=1e-12):
    method forward (line 25) | def forward(self, x):
  class QuickGELU (line 34) | class QuickGELU(nn.Module):
    method forward (line 35) | def forward(self, x: torch.Tensor):
  class ResidualAttentionBlock (line 39) | class ResidualAttentionBlock(nn.Module):
    method __init__ (line 40) | def __init__(self,
    method attention (line 58) | def attention(self, x: torch.Tensor, key_padding_mask: torch.Tensor = ...
    method forward (line 63) | def forward(self, x: torch.Tensor, key_padding_mask: torch.Tensor = No...
  class CLIPTransformer (line 69) | class CLIPTransformer(nn.Module):
    method __init__ (line 70) | def __init__(self, cfg):
    method build_attention_mask (line 113) | def build_attention_mask(self):
    method _init_weights (line 121) | def _init_weights(self, m):
    method resize_pos_embed_1d (line 129) | def resize_pos_embed_1d(self, posemb, shape_new):
    method init_weights (line 140) | def init_weights(self, pretrained="", pretrained_layers=[], verbose=Fa...
    method no_weight_decay (line 165) | def no_weight_decay(self):
    method forward (line 171) | def forward(self, text):

FILE: GLIP/maskrcnn_benchmark/modeling/language_backbone/hfpt_tokenizer.py
  class HFPTTokenizer (line 7) | class HFPTTokenizer(object):
    method __init__ (line 8) | def __init__(self, pt_name=None):
    method get_eot_token (line 36) | def get_eot_token(self):
    method get_sot_token (line 39) | def get_sot_token(self):
    method get_eot_token_list (line 42) | def get_eot_token_list(self):
    method get_sot_token_list (line 45) | def get_sot_token_list(self):
    method get_tokenizer_obj (line 48) | def get_tokenizer_obj(self):
    method check_added_tokens (line 53) | def check_added_tokens(self):
    method tokenize (line 56) | def tokenize(self, texts: Union[str, List[str]], context_length: int =...
    method get_vocab_size (line 95) | def get_vocab_size(self):
    method __call__ (line 98) | def __call__(self, texts: Union[str, List[str]], context_length: int =...

FILE: GLIP/maskrcnn_benchmark/modeling/language_backbone/rnn_model.py
  class RNNEnoder (line 7) | class RNNEnoder(nn.Module):
    method __init__ (line 8) | def __init__(self, cfg):
    method forward (line 36) | def forward(self, input, mask=None):
    method encode (line 49) | def encode(self, input_labels):
    method sort_inputs (line 103) | def sort_inputs(self, input_labels):  # sort input labels by descending

FILE: GLIP/maskrcnn_benchmark/modeling/language_backbone/simple_tokenizer.py
  function default_bpe (line 14) | def default_bpe():
  function bytes_to_unicode (line 19) | def bytes_to_unicode():
  function get_pairs (line 41) | def get_pairs(word):
  function basic_clean (line 53) | def basic_clean(text):
  function whitespace_clean (line 59) | def whitespace_clean(text):
  class SimpleTokenizer (line 65) | class SimpleTokenizer(object):
    method __init__ (line 66) | def __init__(self, bpe_path: str = default_bpe()):
    method bpe (line 85) | def bpe(self, token):
    method encode (line 126) | def encode(self, text):
    method decode (line 134) | def decode(self, tokens):
    method get_vocab_size (line 139) | def get_vocab_size(self):
    method get_eot_token (line 142) | def get_eot_token(self):
    method get_sot_token (line 145) | def get_sot_token(self):
    method check_added_tokens (line 148) | def check_added_tokens(self):
    method get_tokenizer_obj (line 151) | def get_tokenizer_obj(self):
    method tokenize (line 154) | def tokenize(self, texts: Union[str, List[str]], context_length: int =...
    method __call__ (line 172) | def __call__(self, texts: Union[str, List[str]], context_length: int =...

FILE: GLIP/maskrcnn_benchmark/modeling/language_backbone/word_utils.py
  class Dictionary (line 15) | class Dictionary(object):
    method __init__ (line 16) | def __init__(self):
    method add_word (line 20) | def add_word(self, word):
    method __len__ (line 26) | def __len__(self):
    method __getitem__ (line 29) | def __getitem__(self, a):
    method __contains__ (line 39) | def __contains__(self, word):
  class Corpus (line 43) | class Corpus(object):
    method __init__ (line 44) | def __init__(self):
    method set_max_len (line 47) | def set_max_len(self, value):
    method load_file (line 50) | def load_file(self, filename):
    method add_to_corpus (line 58) | def add_to_corpus(self, line):
    method tokenize (line 67) | def tokenize(self, line, max_len=20):
    method __len__ (line 99) | def __len__(self):

FILE: GLIP/maskrcnn_benchmark/modeling/make_layers.py
  function get_group_gn (line 14) | def get_group_gn(dim, dim_per_gp, num_groups):
  function group_norm (line 31) | def group_norm(out_channels, affine=True, divisor=1):
  function make_conv3x3 (line 44) | def make_conv3x3(
  function make_fc (line 80) | def make_fc(dim_in, hidden_dim, use_gn=False):
  function conv_with_kaiming_uniform (line 95) | def conv_with_kaiming_uniform(use_gn=False, use_relu=False, use_dyrelu=F...

FILE: GLIP/maskrcnn_benchmark/modeling/matcher.py
  class Matcher (line 5) | class Matcher(object):
    method __init__ (line 23) | def __init__(self, high_threshold, low_threshold, allow_low_quality_ma...
    method __call__ (line 42) | def __call__(self, match_quality_matrix):
    method set_low_quality_matches_ (line 86) | def set_low_quality_matches_(self, matches, all_matches, match_quality...

FILE: GLIP/maskrcnn_benchmark/modeling/poolers.py
  class LevelMapper (line 11) | class LevelMapper(object):
    method __init__ (line 16) | def __init__(self, k_min, k_max, canonical_scale=224, canonical_level=...
    method __call__ (line 31) | def __call__(self, boxlists):
  class Pooler (line 45) | class Pooler(nn.Module):
    method __init__ (line 55) | def __init__(self, output_size, scales, sampling_ratio, use_v2=False):
    method convert_to_roi_format (line 82) | def convert_to_roi_format(self, boxes):
    method forward (line 95) | def forward(self, x, boxes):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/__init__.py
  class CombinedROIHeads (line 9) | class CombinedROIHeads(torch.nn.ModuleDict):
    method __init__ (line 15) | def __init__(self, cfg, heads):
    method forward (line 23) | def forward(self, features, proposals, targets=None, language_dict_fea...
  function build_roi_heads (line 64) | def build_roi_heads(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/box_head/box_head.py
  class ROIBoxHead (line 11) | class ROIBoxHead(torch.nn.Module):
    method __init__ (line 16) | def __init__(self, cfg):
    method forward (line 25) | def forward(self, features, proposals, targets=None):
  function build_roi_box_head (line 69) | def build_roi_box_head(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/box_head/inference.py
  class PostProcessor (line 12) | class PostProcessor(nn.Module):
    method __init__ (line 19) | def __init__(
    method forward (line 38) | def forward(self, x, boxes):
    method prepare_boxlist (line 87) | def prepare_boxlist(self, boxes, scores, image_shape, extra_field={}):
    method filter_results (line 108) | def filter_results(self, boxlist, num_classes):
  function make_roi_box_post_processor (line 164) | def make_roi_box_post_processor(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/box_head/loss.py
  class FastRCNNLossComputation (line 15) | class FastRCNNLossComputation(object):
    method __init__ (line 21) | def __init__(self, proposal_matcher, fg_bg_sampler, box_coder):
    method match_targets_to_proposals (line 32) | def match_targets_to_proposals(self, proposal, target):
    method prepare_targets (line 54) | def prepare_targets(self, proposals, targets):
    method subsample (line 86) | def subsample(self, proposals, targets):
    method __call__ (line 123) | def __call__(self, class_logits, box_regression):
  function make_roi_box_loss_evaluator (line 171) | def make_roi_box_loss_evaluator(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/box_head/roi_box_feature_extractors.py
  class LightheadFeatureExtractor (line 15) | class LightheadFeatureExtractor(nn.Module):
    method __init__ (line 16) | def __init__(self, cfg):
    method forward (line 46) | def forward(self, x, proposals):
  class ResNet50Conv5ROIFeatureExtractor (line 66) | class ResNet50Conv5ROIFeatureExtractor(nn.Module):
    method __init__ (line 67) | def __init__(self, config):
    method forward (line 94) | def forward(self, x, proposals):
  class FPN2MLPFeatureExtractor (line 101) | class FPN2MLPFeatureExtractor(nn.Module):
    method __init__ (line 106) | def __init__(self, cfg):
    method forward (line 124) | def forward(self, x, proposals):
  class FPNXconv1fcFeatureExtractor (line 135) | class FPNXconv1fcFeatureExtractor(nn.Module):
    method __init__ (line 140) | def __init__(self, cfg):
    method forward (line 189) | def forward(self, x, proposals):
  function make_roi_box_feature_extractor (line 197) | def make_roi_box_feature_extractor(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/box_head/roi_box_predictors.py
  class FastRCNNPredictor (line 5) | class FastRCNNPredictor(nn.Module):
    method __init__ (line 6) | def __init__(self, config, pretrained=None):
    method forward (line 25) | def forward(self, x):
  class FPNPredictor (line 33) | class FPNPredictor(nn.Module):
    method __init__ (line 34) | def __init__(self, cfg):
    method forward (line 47) | def forward(self, x):
  function make_roi_box_predictor (line 60) | def make_roi_box_predictor(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/keypoint_head/inference.py
  class KeypointPostProcessor (line 10) | class KeypointPostProcessor(nn.Module):
    method __init__ (line 11) | def __init__(self, keypointer=None):
    method forward (line 15) | def forward(self, x, boxes):
  function heatmaps_to_keypoints (line 40) | def heatmaps_to_keypoints(maps, rois):
  class Keypointer (line 97) | class Keypointer(object):
    method __init__ (line 103) | def __init__(self, padding=0):
    method __call__ (line 106) | def __call__(self, masks, boxes):
  function make_roi_keypoint_post_processor (line 118) | def make_roi_keypoint_post_processor(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/keypoint_head/keypoint_head.py
  class ROIKeypointHead (line 9) | class ROIKeypointHead(torch.nn.Module):
    method __init__ (line 10) | def __init__(self, cfg):
    method forward (line 18) | def forward(self, features, proposals, targets=None):
  function build_roi_keypoint_head (line 49) | def build_roi_keypoint_head(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/keypoint_head/loss.py
  function project_keypoints_to_heatmap (line 17) | def project_keypoints_to_heatmap(keypoints, proposals, discretization_si...
  function cat_boxlist_with_keypoints (line 24) | def cat_boxlist_with_keypoints(boxlists):
  function _within_box (line 39) | def _within_box(points, boxes):
  class KeypointRCNNLossComputation (line 54) | class KeypointRCNNLossComputation(object):
    method __init__ (line 55) | def __init__(self, proposal_matcher, fg_bg_sampler, discretization_size):
    method match_targets_to_proposals (line 66) | def match_targets_to_proposals(self, proposal, target):
    method prepare_targets (line 79) | def prepare_targets(self, proposals, targets):
    method subsample (line 111) | def subsample(self, proposals, targets):
    method __call__ (line 145) | def __call__(self, proposals, keypoint_logits):
  function make_roi_keypoint_loss_evaluator (line 172) | def make_roi_keypoint_loss_evaluator(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/keypoint_head/roi_keypoint_feature_extractors.py
  class KeypointRCNNFeatureExtractor (line 10) | class KeypointRCNNFeatureExtractor(nn.Module):
    method __init__ (line 11) | def __init__(self, cfg):
    method forward (line 37) | def forward(self, x, proposals):
  class KeypointRCNNFeature2XZoomExtractor (line 43) | class KeypointRCNNFeature2XZoomExtractor(nn.Module):
    method __init__ (line 44) | def __init__(self, cfg):
    method forward (line 79) | def forward(self, x, proposals):
  function make_roi_keypoint_feature_extractor (line 92) | def make_roi_keypoint_feature_extractor(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/keypoint_head/roi_keypoint_predictors.py
  class KeypointRCNNPredictor (line 7) | class KeypointRCNNPredictor(nn.Module):
    method __init__ (line 8) | def __init__(self, cfg):
    method forward (line 26) | def forward(self, x):
  function make_roi_keypoint_predictor (line 37) | def make_roi_keypoint_predictor(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/mask_head/hourglass.py
  class Residual (line 6) | class Residual(nn.Module):
    method __init__ (line 7) | def __init__(self, inp_dim, out_dim, use_gn=False):
    method forward (line 22) | def forward(self, x):
  class Hourglass (line 41) | class Hourglass(nn.Module):
    method __init__ (line 42) | def __init__(self, n, f, gn=False, increase=0):
    method forward (line 58) | def forward(self, x):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/mask_head/inference.py
  function convert_mask_grounding_to_od_logits (line 10) | def convert_mask_grounding_to_od_logits(logits, positive_map_label_to_to...
  class MaskPostProcessor (line 20) | class MaskPostProcessor(nn.Module):
    method __init__ (line 31) | def __init__(self, masker=None, mdetr_style_aggregate_class_num=None, ...
    method forward (line 37) | def forward(self, x, boxes, positive_map_label_to_token=None):
  class MaskPostProcessorCOCOFormat (line 81) | class MaskPostProcessorCOCOFormat(MaskPostProcessor):
    method forward (line 88) | def forward(self, x, boxes, positive_map_label_to_token=None, vl_versi...
  function expand_boxes (line 108) | def expand_boxes(boxes, scale):
  function expand_masks (line 125) | def expand_masks(mask, padding):
  function paste_mask_in_image (line 135) | def paste_mask_in_image(mask, box, im_h, im_w, thresh=0.5, padding=1):
  class Masker (line 174) | class Masker(object):
    method __init__ (line 180) | def __init__(self, threshold=0.5, padding=1):
    method forward_single_image (line 184) | def forward_single_image(self, masks, boxes):
    method __call__ (line 197) | def __call__(self, masks, boxes):
  function make_roi_mask_post_processor (line 214) | def make_roi_mask_post_processor(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/mask_head/loss.py
  function project_masks_on_boxes (line 11) | def project_masks_on_boxes(segmentation_masks, proposals, discretization...
  class MaskRCNNLossComputation (line 47) | class MaskRCNNLossComputation(object):
    method __init__ (line 48) | def __init__(self, proposal_matcher, discretization_size, vl_version=F...
    method match_targets_to_proposals (line 58) | def match_targets_to_proposals(self, proposal, target):
    method prepare_targets (line 74) | def prepare_targets(self, proposals, targets):
    method __call__ (line 123) | def __call__(self, proposals, mask_logits, targets):
  function make_roi_mask_loss_evaluator (line 167) | def make_roi_mask_loss_evaluator(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/mask_head/mask_head.py
  function keep_only_positive_boxes (line 13) | def keep_only_positive_boxes(boxes):
  class ROIMaskHead (line 36) | class ROIMaskHead(torch.nn.Module):
    method __init__ (line 37) | def __init__(self, cfg):
    method forward (line 45) | def forward(self, features, proposals, targets=None,
  function build_roi_mask_head (line 87) | def build_roi_mask_head(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/mask_head/roi_mask_feature_extractors.py
  class MaskRCNNFPNFeatureExtractor (line 13) | class MaskRCNNFPNFeatureExtractor(nn.Module):
    method __init__ (line 18) | def __init__(self, cfg):
    method forward (line 53) | def forward(self, x, proposals):
  class HourglassFPNFeatureExtractor (line 62) | class HourglassFPNFeatureExtractor(nn.Module):
    method __init__ (line 67) | def __init__(self, cfg):
    method forward (line 99) | def forward(self, x, proposals):
  function make_roi_mask_feature_extractor (line 115) | def make_roi_mask_feature_extractor(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/roi_heads/mask_head/roi_mask_predictors.py
  class MaskRCNNC4Predictor (line 11) | class MaskRCNNC4Predictor(nn.Module):
    method __init__ (line 12) | def __init__(self, cfg):
    method forward (line 38) | def forward(self, x):
  class VLMaskRCNNC4Predictor (line 43) | class VLMaskRCNNC4Predictor(nn.Module):
    method __init__ (line 44) | def __init__(self, cfg):
    method forward (line 75) | def forward(self, x, language_dict_features):
  function make_roi_mask_predictor (line 109) | def make_roi_mask_predictor(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/rpn/__init__.py
  function build_rpn (line 19) | def build_rpn(cfg):

FILE: GLIP/maskrcnn_benchmark/modeling/rpn/anchor_generator.py
  class BufferList (line 12) | class BufferList(nn.Module):
    method __init__ (line 17) | def __init__(self, buffers=None):
    method extend (line 22) | def extend(self, buffers):
    method __len__ (line 28) | def __len__(self):
    method __iter__ (line 31) | def __iter__(self):
  class AnchorGenerator (line 35) | class AnchorGenerator(nn.Module):
    method __init__ (line 41) | def __init__(
    method num_anchors_per_location (line 70) | def num_anchors_per_location(self):
    method grid_anchors (line 73) | def grid_anchors(self, grid_sizes):
    method add_visibility_to (line 97) | def add_visibility_to(self, boxlist):
    method forward (line 112) | def forward(self, image_list, feature_maps):
  function make_anchor_generator (line 139) | def make_anchor_generator(config):
  function make_anchor_generator_complex (line 157) | def make_anchor_generator_complex(config):
  class CenterAnchorGenerator (line 184) | class CenterAnchorGenerator(nn.Module):
    method __init__ (line 190) | def __init__(
    method add_visibility_to (line 208) | def add_visibility_to(self, boxlist):
    method forward (line 223) | def forward(self, centers, image_sizes, feature_maps):
  function make_center_anchor_generator (line 276) | def make_center_anchor_generator(config):
  function generate_anchors (line 356) | def generate_anchors(
  function _generate_anchors (line 370) | def _generate_anchors(base_size, scales, aspect_ratios):
  function _whctrs (line 382) | def _whctrs(anchor):
  function _mkanchors (line 391) | def _mkanchors(ws, hs, x_ctr, y_ctr):
  function _ratio_enum (line 408) | def _ratio_enum(anchor, ratios):
  function _scale_enum (line 419) | def _scale_enum(anchor, scales):

FILE: GLIP/maskrcnn_benchmark/modeling/rpn/atss.py
  class BoxCoder (line 14) | class BoxCoder(object):
    method __init__ (line 16) | def __init__(self, cfg):
    method encode (line 19) | def encode(self, gt_boxes, anchors):
    method decode (line 41) | def decode(self, preds, anchors):
  class ATSSHead (line 75) | class ATSSHead(torch.nn.Module):
    method __init__ (line 76) | def __init__(self, cfg):
    method forward (line 171) | def forward(self, x):
  class ATSSModule (line 188) | class ATSSModule(torch.nn.Module):
    method __init__ (line 190) | def __init__(self, cfg):
    method forward (line 200) | def forward(self, images, features, targets=None):
    method _forward_train (line 209) | def _forward_train(self, box_cls, box_regression, centerness, targets,...
    method _forward_test (line 231) | def _forward_test(self, box_cls, box_regression, centerness, anchors):

FILE: GLIP/maskrcnn_benchmark/modeling/rpn/dyhead.py
  class h_sigmoid (line 16) | class h_sigmoid(nn.Module):
    method __init__ (line 17) | def __init__(self, inplace=True, h_max=1):
    method forward (line 22) | def forward(self, x):
  class BoxCoder (line 26) | class BoxCoder(object):
    method __init__ (line 28) | def __init__(self, cfg):
    method encode (line 31) | def encode(self, gt_boxes, anchors):
    method decode (line 52) | def decode(self, preds, anchors):
  class Conv3x3Norm (line 85) | class Conv3x3Norm(torch.nn.Module):
    method __init__ (line 86) | def __init__(self,
    method forward (line 122) | def forward(self, input, **kwargs):
  class DyConv (line 129) | class DyConv(torch.nn.Module):
    method __init__ (line 130) | def __init__(self,
    method init_weights (line 166) | def init_weights(self):
    method forward (line 179) | def forward(self, x):
  class DyHead (line 217) | class DyHead(torch.nn.Module):
    method __init__ (line 218) | def __init__(self, cfg):
    method extract_feature (line 286) | def extract_feature(self, x):
    method forward (line 293) | def forward(self, x):
  class DyHeadModule (line 327) | class DyHeadModule(torch.nn.Module):
    method __init__ (line 329) | def __init__(self, cfg):
    method forward (line 339) | def forward(self, images, features, targets=None):
    method _forward_train (line 348) | def _forward_train(self, box_cls, box_regression, centerness, targets,...
    method _forward_test (line 375) | def _forward_test(self, box_cls, box_regression, centerness, anchors):

FILE: GLIP/maskrcnn_benchmark/modeling/rpn/fcos.py
  class FCOSHead (line 14) | class FCOSHead(torch.nn.Module):
    method __init__ (line 15) | def __init__(self, cfg):
    method forward (line 100) | def forward(self, x):
  class FCOSModule (line 126) | class FCOSModule(torch.nn.Module):
    method __init__ (line 132) | def __init__(self, cfg):
    method forward (line 152) | def forward(self, images, features, targets=None):
    method _forward_train (line 180) | def _forward_train(self, locations, box_cls, box_regression, centernes...
    method _forward_test (line 199) | def _forward_test(self, locations, box_cls, box_regression, centerness...
    method compute_locations (line 208) | def compute_locations(self, features):
    method compute_locations_per_level (line 219) | def compute_locations_per_level(self, h, w, stride, device):

FILE: GLIP/maskrcnn_benchmark/modeling/rpn/inference.py
  class RPNPostProcessor (line 16) | class RPNPostProcessor(torch.nn.Module):
    method __init__ (line 22) | def __init__(
    method add_gt_proposals (line 56) | def add_gt_proposals(self, proposals, targets):
    method forward_for_single_feature_map (line 79) | def forward_for_single_feature_map(self, anchors, objectness, box_regr...
    method forward (line 133) | def forward(self, anchors, objectness, box_regression, targets=None):
    method select_over_all_levels (line 162) | def select_over_all_levels(self, boxlists):
  function make_rpn_postprocessor (line 192) | def make_rpn_postprocessor(config, rpn_box_coder, is_train):
  class RetinaPostProcessor (line 217) | class RetinaPostProcessor(torch.nn.Module):
    method __init__ (line 223) | def __init__(
    method forward_for_single_feature_map (line 255) | def forward_for_single_feature_map(self, anchors, box_cls, box_regress...
    method select_over_all_levels (line 325) | def select_over_all_levels(self, boxlists):
    method forward (line 370) | def forward(self, anchors, objectness, box_regression, targets=None):
  function make_retina_postprocessor (line 394) | def make_retina_postprocessor(config, rpn_box_coder, is_train):
  class FCOSPostProcessor (line 414) | class FCOSPostProcessor(torch.nn.Module):
    method __init__ (line 420) | def __init__(
    method forward_for_single_feature_map (line 449) | def forward_for_single_feature_map(
    method forward (line 517) | def forward(self, locations, box_cls, box_regression, centerness, imag...
    method select_over_all_levels (line 547) | def select_over_all_levels(self, boxlists):
  function make_fcos_postprocessor (line 569) | def make_fcos_postprocessor(config, is_train=False):
  class ATSSPostProcessor (line 592) | class ATSSPostProcessor(torch.nn.Module):
    method __init__ (line 593) | def __init__(
    method forward_for_single_feature_map (line 620) | def forward_for_single_feature_map(self, box_regression, centerness, a...
    method forward (line 713) | def forward(self, box_regression, centerness, anchors,
    method select_over_all_levels (line 747) | def select_over_all_levels(self, boxlists):
  function convert_grounding_to_od_logits (line 771) | def convert_grounding_to_od_logits(logits, box_cls, positive_map, score_...
  function convert_grounding_to_od_logits_v2 (line 792) | def convert_grounding_to_od_logits_v2(logits, num_class, positive_map, s...
  function make_atss_postprocessor (line 825) | def make_atss_postprocessor(config, box_coder, is_train=False):

FILE: GLIP/maskrcnn_benchmark/modeling/rpn/loss.py
  class RPNLossComputation (line 28) | class RPNLossComputation(object):
    method __init__ (line 33) | def __init__(self, proposal_matcher, fg_bg_sampler, box_coder):
    method match_targets_to_anchors (line 45) | def match_targets_to_anchors(self, anchor, target):
    method prepare_targets (line 64) | def prepare_targets(self, anchors, targets):
    method __call__ (line 95) | def __call__(self, anchors, objectness, box_regression, targets):
  class FocalLossComputation (line 156) | class FocalLossComputation(object):
    method __init__ (line 161) | def __init__(self, proposal_matcher, box_coder,
    method match_targets_to_anchors (line 180) | def match_targets_to_anchors(self, anchor, target, copied_fields=[]):
    method prepare_targets (line 194) | def prepare_targets(self, anchors, targets):
    method __call__ (line 230) | def __call__(self, anchors, box_cls, box_regression, targets):
  class FCOSLossComputation (line 270) | class FCOSLossComputation(object):
    method __init__ (line 275) | def __init__(self, cfg):
    method get_sample_region (line 291) | def get_sample_region(self, gt, strides, num_points_per, gt_xs, gt_ys,...
    method prepare_targets (line 338) | def prepare_targets(self, points, targets):
    method compute_targets_for_locations (line 384) | def compute_targets_for_locations(self, locations, targets, object_siz...
    method compute_centerness_targets (line 443) | def compute_centerness_targets(self, reg_targets):
    method __call__ (line 451) | def __call__(self, locations, box_cls, box_regression, centerness, tar...
  class ATSSLossComputation (line 518) | class ATSSLossComputation(torch.nn.Module):
    method __init__ (line 520) | def __init__(self, cfg, box_coder):
    method NllSoftMaxLoss (line 582) | def NllSoftMaxLoss(self, logits, target):
    method ContrastiveAlignLoss (line 587) | def ContrastiveAlignLoss(self, logits, positive_map):
    method GIoULoss (line 610) | def GIoULoss(self, pred, target, anchor, weight=None):
    method prepare_targets (line 653) | def prepare_targets(self, targets, anchors, tokenized=None, positive_m...
    method compute_centerness_targets (line 832) | def compute_centerness_targets(self, reg_targets, anchors):
    method __call__ (line 848) | def __call__(self, box_cls, box_regression, centerness, targets, anchors,
  function generate_anchor_labels (line 1202) | def generate_anchor_labels(matched_targets):
  function make_focal_loss_evaluator (line 1207) | def make_focal_loss_evaluator(cfg, box_coder):
  function make_rpn_loss_evaluator (line 1229) | def make_rpn_loss_evaluator(cfg, box_coder):
  function make_fcos_loss_evaluator (line 1244) | def make_fcos_loss_evaluator(cfg):
  function make_atss_loss_evaluator (line 1249) | def make_atss_loss_evaluator(cfg, box_coder):

FILE: GLIP/maskrcnn_benchmark/modeling/rpn/modeling_bert.py
  function clamp_values (line 34) | def clamp_values(vector, min_val = -50000, max_val = 50000):
  class BertSelfAttention (line 39) | class BertSelfAttention(nn.Module):
    method __init__ (line 40) | def __init__(self, config, clamp_min_for_underflow=False, clamp_max_fo...
    method transpose_for_scores (line 66) | def transpose_for_scores(self, x):
    method forward (line 71) | def forward(
  class BertSelfOutput (line 179) | class BertSelfOutput(nn.Module):
    method __init__ (line 180) | def __init__(self, config):
    method forward (line 186) | def forward(self, hidden_states, input_tensor):
  class BertAttention (line 193) | class BertAttention(nn.Module):
    method __init__ (line 194) | def __init__(self, config, clamp_min_for_underflow=False, clamp_max_fo...
    method prune_heads (line 200) | def prune_heads(self, heads):
    method forward (line 218) | def forward(
  class BertIntermediate (line 242) | class BertIntermediate(nn.Module):
    method __init__ (line 243) | def __init__(self, config):
    method forward (line 251) | def forward(self, hidden_states):
  class BertOutput (line 259) | class BertOutput(nn.Module):
    method __init__ (line 260) | def __init__(self, config):
    method forward (line 266) | def forward(self, hidden_states, input_tensor):

FILE: GLIP/maskrcnn_benchmark/modeling/rpn/retina.py
  class RetinaNetHead (line 15) | class RetinaNetHead(torch.nn.Module):
    method __init__ (line 20) | def __init__(self, cfg):
    method forward (line 84) | def forward(self, x):
  class RetinaNetModule (line 93) | class RetinaNetModule(torch.nn.Module):
    method __init__ (line 99) | def __init__(self, cfg):
    method forward (line 118) | def forward(self, images, features, targets=None):
    method _forward_train (line 141) | def _forward_train(self, anchors, box_cls, box_regression, targets):
    method _forward_test (line 152) | def _forward_test(self, anchors, box_cls, box_regression):

FILE: GLIP/maskrcnn_benchmark/modeling/rpn/rpn.py
  class mRPNHead (line 14) | class mRPNHead(nn.Module):
    method __init__ (line 19) | def __init__(self, cfg, in_channels, num_anchors):
    method forward (line 36) | def forward(self, x):
  class RPNHead (line 47) | class RPNHead(nn.Module):
    method __init__ (line 52) | def __init__(self, cfg, in_channels, num_anchors):
    method forward (line 72) | def forward(self, x):
  class RPNModule (line 82) | class RPNModule(torch.nn.Module):
    method __init__ (line 88) | def __init__(self, cfg):
    method forward (line 114) | def forward(self, images, features, targets=None):
    method _forward_train (line 137) | def _forward_train(self, anchors, objectness, rpn_box_regression, targ...
    method _forward_test (line 160) | def _forward_test(self, anchors, objectness, rpn_box_regression):

FILE: GLIP/maskrcnn_benchmark/modeling/rpn/transformer.py
  function _get_clones (line 9) | def _get_clones(module, N):
  function _get_activation_fn (line 13) | def _get_activation_fn(activation):
  class TransformerEncoderLayer (line 24) | class TransformerEncoderLayer(nn.Module):
    method __init__ (line 25) | def __init__(self, d_model, nhead, dim_feedforward=2048, dropout=0.1,
    method forward (line 42) | def forward(self, src,

FILE: GLIP/maskrcnn_benchmark/modeling/rpn/vldyhead.py
  class h_sigmoid (line 28) | class h_sigmoid(nn.Module):
    method __init__ (line 29) | def __init__(self, inplace=True, h_max=1):
    method forward (line 34) | def forward(self, x):
  class BoxCoder (line 38) | class BoxCoder(object):
    method __init__ (line 40) | def __init__(self, cfg):
    method encode (line 43) | def encode(self, gt_boxes, anchors):
    method decode (line 64) | def decode(self, preds, anchors):
  class Conv3x3Norm (line 97) | class Conv3x3Norm(torch.nn.Module):
    method __init__ (line 98) | def __init__(self,
    method forward (line 134) | def forward(self, input, **kwargs):
  class DyConv (line 141) | class DyConv(torch.nn.Module):
    method __init__ (line 142) | def __init__(self,
    method init_weights (line 178) | def init_weights(self):
    method forward (line 191) | def forward(self, inputs):
  class BertEncoderLayer (line 236) | class BertEncoderLayer(BertPreTrainedModel):
    method __init__ (line 237) | def __init__(self, config,  clamp_min_for_underflow = False, clamp_max...
    method forward (line 250) | def forward(self, inputs):
    method feed_forward_chunk (line 284) | def feed_forward_chunk(self, attention_output):
  class CLIPTransformerLayer (line 290) | class CLIPTransformerLayer(nn.Module):
    method __init__ (line 291) | def __init__(self, config):
    method _init_weights (line 310) | def _init_weights(self, m):
    method attention (line 318) | def attention(self, x: torch.Tensor, key_padding_mask: torch.Tensor = ...
    method forward (line 323) | def forward(self, inputs):
  class DummyLayer (line 342) | class DummyLayer(nn.Module):
    method __init__ (line 343) | def __init__(self):
    method forward (line 346) | def forward(self, inputs):
  class VLFuse (line 350) | class VLFuse(torch.nn.Module):
    method __init__ (line 355) | def __init__(self, cfg):
    method init_configs (line 423) | def init_configs(self, cfg):
    method forward (line 447) | def forward(self, x):
  class VLDyHead (line 560) | class VLDyHead(torch.nn.Module):
    method __init__ (line 561) | def __init__(self, cfg):
    method forward (line 731) | def forward(self, x, language_dict_features=None, embedding=None, swin...
  class VLDyHeadModule (line 862) | class VLDyHeadModule(torch.nn.Module):
    method __init__ (line 864) | def __init__(self, cfg):
    method forward (line 892) | def forward(self, images, features, targets=None,
    method _forward_train (line 950) | def _forward_train(self, box_cls, box_regression, centerness, targets,...
    method _forward_test (line 1022) | def _forward_test(self, box_regression, centerness, anchors,

FILE: GLIP/maskrcnn_benchmark/modeling/utils.py
  function cat (line 9) | def cat(tensors, dim=0):
  function permute_and_flatten (line 19) | def permute_and_flatten(layer, N, A, C, H, W):
  function concat_box_prediction_layers (line 26) | def concat_box_prediction_layers(box_regression, box_cls=None, token_log...
  function round_channels (line 75) | def round_channels(channels, divisor=8):

FILE: GLIP/maskrcnn_benchmark/solver/build.py
  function make_optimizer (line 8) | def make_optimizer(cfg, model):
  function make_lr_scheduler (line 58) | def make_lr_scheduler(cfg, optimizer):

FILE: GLIP/maskrcnn_benchmark/solver/lr_scheduler.py
  class WarmupMultiStepLR (line 11) | class WarmupMultiStepLR(torch.optim.lr_scheduler._LRScheduler):
    method __init__ (line 12) | def __init__(
    method get_lr (line 40) | def get_lr(self):
  class WarmupCosineAnnealingLR (line 56) | class WarmupCosineAnnealingLR(torch.optim.lr_scheduler._LRScheduler):
    method __init__ (line 57) | def __init__(
    method get_lr (line 82) | def get_lr(self):
  class WarmupReduceLROnPlateau (line 104) | class WarmupReduceLROnPlateau(torch.optim.lr_scheduler.ReduceLROnPlateau):
    method __init__ (line 105) | def __init__(
    method step (line 140) | def step(self, metrics=None):

FILE: GLIP/maskrcnn_benchmark/structures/bounding_box.py
  class BoxList (line 9) | class BoxList(object):
    method __init__ (line 19) | def __init__(self, bbox, image_size, mode="xyxy"):
    method _jit_unwrap (line 43) | def _jit_unwrap(self):
    method _jit_wrap (line 48) | def _jit_wrap(self, input_stream):
    method add_field (line 57) | def add_field(self, field, field_data):
    method get_field (line 60) | def get_field(self, field):
    method has_field (line 63) | def has_field(self, field):
    method fields (line 66) | def fields(self):
    method _copy_extra_fields (line 69) | def _copy_extra_fields(self, bbox):
    method convert (line 73) | def convert(self, mode):
    method _split_into_xyxy (line 94) | def _split_into_xyxy(self):
    method resize (line 110) | def resize(self, size, *args, **kwargs):
    method transpose (line 148) | def transpose(self, method):
    method crop (line 186) | def crop(self, box):
    method to (line 213) | def to(self, device):
    method __getitem__ (line 221) | def __getitem__(self, item):
    method __len__ (line 227) | def __len__(self):
    method clip_to_image (line 230) | def clip_to_image(self, remove_empty=True):
    method area (line 243) | def area(self):
    method copy_with_fields (line 256) | def copy_with_fields(self, fields):
    method __repr__ (line 264) | def __repr__(self):
    method concate_box_list (line 273) | def concate_box_list(list_of_boxes):
  function _onnx_clip_boxes_to_image (line 287) | def _onnx_clip_boxes_to_image(boxes, size):

FILE: GLIP/maskrcnn_benchmark/structures/boxlist_ops.py
  function boxlist_nms (line 10) | def boxlist_nms(boxlist, nms_thresh, max_proposals=-1, score_field="scor...
  function boxlist_ml_nms (line 35) | def boxlist_ml_nms(boxlist, nms_thresh, max_proposals=-1,
  function remove_small_boxes (line 78) | def remove_small_boxes(boxlist, min_size):
  function boxlist_iou (line 97) | def boxlist_iou(boxlist1, boxlist2):
  function _cat (line 136) | def _cat(tensors, dim=0):
  function cat_boxlist (line 148) | def cat_boxlist(bboxes):
  function getUnionBBox (line 177) | def getUnionBBox(aBB, bBB, margin = 10):

FILE: GLIP/maskrcnn_benchmark/structures/image_list.py
  class ImageList (line 7) | class ImageList(object):
    method __init__ (line 15) | def __init__(self, tensors, image_sizes):
    method to (line 24) | def to(self, *args, **kwargs):
  function to_image_list (line 29) | def to_image_list(tensors, size_divisible=0):

FILE: GLIP/maskrcnn_benchmark/structures/keypoint.py
  class Keypoints (line 9) | class Keypoints(object):
    method __init__ (line 10) | def __init__(self, keypoints, size, mode=None):
    method crop (line 27) | def crop(self, box):
    method resize (line 30) | def resize(self, size, *args, **kwargs):
    method transpose (line 41) | def transpose(self, method):
    method to (line 62) | def to(self, *args, **kwargs):
    method __getitem__ (line 70) | def __getitem__(self, item):
    method add_field (line 76) | def add_field(self, field, field_data):
    method get_field (line 79) | def get_field(self, field):
    method __repr__ (line 82) | def __repr__(self):
  class PersonKeypoints (line 90) | class PersonKeypoints(Keypoints):
    method __init__ (line 121) | def __init__(self, *args, **kwargs):
    method to_coco_format (line 133) | def to_coco_format(self):
    method _create_flip_indices (line 144) | def _create_flip_indices(self, names, flip_map):
    method _kp_connections (line 152) | def _kp_connections(self, keypoints):
  function keypoints_to_heat_map (line 178) | def keypoints_to_heat_map(keypoints, rois, heatmap_size):

FILE: GLIP/maskrcnn_benchmark/structures/segmentation_mask.py
  class Mask (line 11) | class Mask(object):
    method __init__ (line 18) | def __init__(self, masks, size, mode):
    method transpose (line 23) | def transpose(self, method):
    method crop (line 41) | def crop(self, box):
    method resize (line 47) | def resize(self, size, *args, **kwargs):
  class Polygons (line 51) | class Polygons(object):
    method __init__ (line 58) | def __init__(self, polygons, size, mode):
    method transpose (line 69) | def transpose(self, method):
    method crop (line 92) | def crop(self, box):
    method resize (line 108) | def resize(self, size, *args, **kwargs):
    method convert (line 125) | def convert(self, mode):
    method __repr__ (line 137) | def __repr__(self):
  class SegmentationMask (line 146) | class SegmentationMask(object):
    method __init__ (line 151) | def __init__(self, polygons, size, mode=None):
    method transpose (line 165) | def transpose(self, method):
    method crop (line 176) | def crop(self, box):
    method resize (line 183) | def resize(self, size, *args, **kwargs):
    method to (line 189) | def to(self, *args, **kwargs):
    method __getitem__ (line 192) | def __getitem__(self, item):
    method __iter__ (line 206) | def __iter__(self):
    method __repr__ (line 209) | def __repr__(self):

FILE: GLIP/maskrcnn_benchmark/utils/amp.py
  function nullcontext (line 4) | def nullcontext(enter_result=None, **kwargs):

FILE: GLIP/maskrcnn_benchmark/utils/big_model_loading.py
  function tf2th (line 8) | def tf2th(conv_weights):
  function _rename_conv_weights_for_deformable_conv_layers (line 15) | def _rename_conv_weights_for_deformable_conv_layers(state_dict, cfg):
  function load_big_format (line 47) | def load_big_format(cfg, f):

FILE: GLIP/maskrcnn_benchmark/utils/c2_model_loading.py
  function _rename_basic_resnet_weights (line 12) | def _rename_basic_resnet_weights(layer_keys):
  function _rename_fpn_weights (line 64) | def _rename_fpn_weights(layer_keys, stage_names):
  function _rename_weights_for_resnet (line 84) | def _rename_weights_for_resnet(weights, stage_names):
  function _load_c2_pickled_weights (line 135) | def _load_c2_pickled_weights(file_path):
  function _rename_conv_weights_for_deformable_conv_layers (line 148) | def _rename_conv_weights_for_deformable_conv_layers(state_dict, cfg):
  function load_resnet_c2_format (line 193) | def load_resnet_c2_format(cfg, f):
  function load_c2_format (line 206) | def load_c2_format(cfg, f):

FILE: GLIP/maskrcnn_benchmark/utils/checkpoint.py
  class Checkpointer (line 15) | class Checkpointer(object):
    method __init__ (line 16) | def __init__(
    method save (line 34) | def save(self, name, **kwargs):
    method load (line 59) | def load(self, f=None, force=False, keyword="model", skip_optimizer =F...
    method has_checkpoint (line 93) | def has_checkpoint(self):
    method get_checkpoint_file (line 97) | def get_checkpoint_file(self):
    method tag_last_checkpoint (line 109) | def tag_last_checkpoint(self, last_filename):
    method _load_file (line 114) | def _load_file(self, f):
    method _load_model (line 117) | def _load_model(self, checkpoint, keyword="model"):
  class DetectronCheckpointer (line 121) | class DetectronCheckpointer(Checkpointer):
    method __init__ (line 122) | def __init__(
    method _load_file (line 137) | def _load_file(self, f):

FILE: GLIP/maskrcnn_benchmark/utils/collect_env.py
  function get_pil_version (line 7) | def get_pil_version():
  function collect_env_info (line 11) | def collect_env_info():

FILE: GLIP/maskrcnn_benchmark/utils/comm.py
  function get_world_size (line 15) | def get_world_size():
  function get_rank (line 23) | def get_rank():
  function is_main_process (line 31) | def is_main_process():
  function synchronize (line 35) | def synchronize():
  function all_gather (line 50) | def all_gather(data):
  function reduce_dict (line 93) | def reduce_dict(input_dict, average=True):
  function broadcast_data (line 122) | def broadcast_data(data):
  function reduce_sum (line 137) | def reduce_sum(tensor):
  function shared_random_seed (line 146) | def shared_random_seed():

FILE: GLIP/maskrcnn_benchmark/utils/cv2_util.py
  function findContours (line 8) | def findContours(*args, **kwargs):

FILE: GLIP/maskrcnn_benchmark/utils/dist.py
  function _get_global_gloo_group (line 20) | def _get_global_gloo_group():
  function all_gather (line 32) | def all_gather(data):
  function reduce_dict (line 92) | def reduce_dict(input_dict, average=True):
  function setup_for_distributed (line 119) | def setup_for_distributed(is_master):
  function is_dist_avail_and_initialized (line 135) | def is_dist_avail_and_initialized():
  function get_world_size (line 147) | def get_world_size():
  function get_rank (line 157) | def get_rank():
  function get_local_rank (line 167) | def get_local_rank() -> int:
  function get_local_size (line 180) | def get_local_size() -> int:
  function is_main_process (line 193) | def is_main_process():
  function save_on_master (line 198) | def save_on_master(*args, **kwargs):
  function init_distributed_mode (line 204) | def init_distributed_mode(args):

FILE: GLIP/maskrcnn_benchmark/utils/ema.py
  class ModelEma (line 6) | class ModelEma:
    method __init__ (line 7) | def __init__(self, model, decay=0.9999, device=''):
    method load_checkpoint (line 18) | def load_checkpoint(self, checkpoint):
    method state_dict (line 33) | def state_dict(self):
    method update (line 36) | def update(self, model):

FILE: GLIP/maskrcnn_benchmark/utils/env.py
  function setup_environment (line 7) | def setup_environment():
  function setup_custom_environment (line 20) | def setup_custom_environment(custom_module_path):

FILE: GLIP/maskrcnn_benchmark/utils/flops.py
  function profile (line 15) | def profile(model, input_size, custom_ops={}, device="cpu", verbose=Fals...
  function count_conv2d (line 79) | def count_conv2d(m, x, y):
  function count_convtranspose2d (line 100) | def count_convtranspose2d(m, x, y):
  function count_bn (line 123) | def count_bn(m, x, y):
  function count_relu (line 131) | def count_relu(m, x, y):
  function count_softmax (line 138) | def count_softmax(m, x, y):
  function count_maxpool (line 148) | def count_maxpool(m, x, y):
  function count_adap_maxpool (line 155) | def count_adap_maxpool(m, x, y):
  function count_avgpool (line 163) | def count_avgpool(m, x, y):
  function count_adap_avgpool (line 172) | def count_adap_avgpool(m, x, y):
  function count_linear (line 182) | def count_linear(m, x, y):
  function count_LastLevelMaxPool (line 191) | def count_LastLevelMaxPool(m, x, y):
  function count_ROIAlign (line 197) | def count_ROIAlign(m, x, y):

FILE: GLIP/maskrcnn_benchmark/utils/fuse_helper.py
  class BertPredictionHeadTransform (line 10) | class BertPredictionHeadTransform(nn.Module):
    method __init__ (line 11) | def __init__(self, config):
    method forward (line 20) | def forward(self, hidden_states):
  class BertLMPredictionHead (line 27) | class BertLMPredictionHead(nn.Module):
    method __init__ (line 28) | def __init__(self, config):
    method forward (line 41) | def forward(self, hidden_states):
  class FeatureResizer (line 46) | class FeatureResizer(nn.Module):
    method __init__ (line 52) | def __init__(self, input_feat_size, output_feat_size, dropout, do_ln=T...
    method forward (line 60) | def forward(self, encoder_features):
  function _make_conv (line 68) | def _make_conv(input_dim, output_dim, k, stride=1):
  function _make_mlp (line 77) | def _make_mlp(input_dim, output_dim, drop):
  function _make_coord (line 87) | def _make_coord(batch, height, width):
  function l1norm (line 106) | def l1norm(X, dim, eps=1e-8):
  function l2norm (line 114) | def l2norm(X, dim, eps=1e-8):
  function func_attention (line 122) | def func_attention(query, context, smooth=1, raw_feature_norm="softmax",...
  class BiMultiHeadAttention (line 171) | class BiMultiHeadAttention(nn.Module):
    method __init__ (line 172) | def __init__(self, v_dim, l_dim, embed_dim, num_heads, dropout=0.1, cf...
    method _shape (line 201) | def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
    method _reset_parameters (line 204) | def _reset_parameters(self):
    method forward (line 218) | def forward(self, v, l, attention_mask_l=None):
  class BiAttentionBlock (line 307) | class BiAttentionBlock(nn.Module):
    method __init__ (line 308) | def __init__(self, v_dim, l_dim, embed_dim, num_heads, hidden_dim=None...
    method forward (line 335) | def forward(self, v, l, attention_mask_l=None, dummy_tensor=None):
  class BiAttentionBlockForCheckpoint (line 344) | class BiAttentionBlockForCheckpoint(nn.Module):
    method __init__ (line 345) | def __init__(self, v_dim, l_dim, embed_dim, num_heads, hidden_dim=None...
    method forward (line 377) | def forward(self, q0, q1, q2, q3, q4, l, attention_mask_l=None, dummy_...
    method single_attention_call (line 419) | def single_attention_call(self, v, l, attention_mask_l=None, dummy_ten...
  class MultiHeadAttention (line 430) | class MultiHeadAttention(nn.Module):
    method __init__ (line 435) | def __init__(self, q_dim, k_dim, embed_dim, num_heads, dropout=0.1,
    method _shape (line 460) | def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
    method _reset_parameters (line 463) | def _reset_parameters(self):
    method forward (line 473) | def forward(self, q, k, v, attention_mask=None, return_attention=False):
  class AttentionMLP (line 543) | class AttentionMLP(nn.Module):
    method __init__ (line 544) | def __init__(self, q_dim, hidden_dim, dropout=0.1):
    method forward (line 552) | def forward(self, hidden_states):
  class AttentionT2I (line 559) | class AttentionT2I(nn.Module):
    method __init__ (line 560) | def __init__(self, q_dim, k_dim, embed_dim, num_heads, hidden_dim=None...
    method forward (line 591) | def forward(self, q0, q1, q2, q3, q4, k, v, attention_mask, dummy_arg=...

FILE: GLIP/maskrcnn_benchmark/utils/imports.py
  function import_file (line 11) | def import_file(module_name, file_path, make_importable=False):
  function import_file (line 21) | def import_file(module_name, file_path, make_importable=None):

FILE: GLIP/maskrcnn_benchmark/utils/logger.py
  function setup_logger (line 7) | def setup_logger(name, save_dir, distributed_rank):

FILE: GLIP/maskrcnn_benchmark/utils/mdetr_dist.py
  function _get_global_gloo_group (line 21) | def _get_global_gloo_group():
  function all_gather (line 32) | def all_gather(data):
  function reduce_dict (line 92) | def reduce_dict(input_dict, average=True):
  function setup_for_distributed (line 119) | def setup_for_distributed(is_master):
  function is_dist_avail_and_initialized (line 135) | def is_dist_avail_and_initialized():
  function get_world_size (line 147) | def get_world_size():
  function get_rank (line 157) | def get_rank():
  function get_local_rank (line 167) | def get_local_rank() -> int:
  function get_local_size (line 180) | def get_local_size() -> int:
  function is_main_process (line 193) | def is_main_process():
  function save_on_master (line 198) | def save_on_master(*args, **kwargs):
  function init_distributed_mode (line 204) | def init_distributed_mode(args):

FILE: GLIP/maskrcnn_benchmark/utils/metric_logger.py
  class SmoothedValue (line 11) | class SmoothedValue(object):
    method __init__ (line 16) | def __init__(self, window_size=20):
    method update (line 22) | def update(self, value):
    method median (line 31) | def median(self):
    method avg (line 36) | def avg(self):
    method global_avg (line 41) | def global_avg(self):
  class AverageMeter (line 45) | class AverageMeter(object):
    method __init__ (line 48) | def __init__(self):
    method reset (line 51) | def reset(self):
    method update (line 57) | def update(self, val, n=1):
  class MetricLogger (line 64) | class MetricLogger(object):
    method __init__ (line 65) | def __init__(self, delimiter="\t"):
    method update (line 69) | def update(self, **kwargs):
    method __getattr__ (line 76) | def __getattr__(self, attr):
    method __str__ (line 84) | def __str__(self):
  class TensorboardLogger (line 94) | class TensorboardLogger(MetricLogger):
    method __init__ (line 95) | def __init__(self,
    method _get_tensorboard_writer (line 105) | def _get_tensorboard_writer(log_dir):
    method update (line 121) | def update(self, **kwargs):

FILE: GLIP/maskrcnn_benchmark/utils/miscellaneous.py
  function mkdir (line 6) | def mkdir(path):
  function save_config (line 14) | def save_config(cfg, path):

FILE: GLIP/maskrcnn_benchmark/utils/model_serialization.py
  function resize_2d (line 9) | def resize_2d(posemb, shape_new):
  function align_and_update_state_dicts (line 20) | def align_and_update_state_dicts(model_state_dict, loaded_state_dict, re...
  function strip_prefix_if_present (line 103) | def strip_prefix_if_present(state_dict, prefix):
  function load_state_dict (line 112) | def load_state_dict(model, loaded_state_dict):
  function _group_checkpoint_keys (line 123) | def _group_checkpoint_keys(keys):
  function _group_to_str (line 143) | def _group_to_str(group):

FILE: GLIP/maskrcnn_benchmark/utils/model_zoo.py
  function cache_url (line 20) | def cache_url(url, model_dir='model', progress=True):

FILE: GLIP/maskrcnn_benchmark/utils/pretrain_model_loading.py
  function _remove_bn_statics (line 7) | def _remove_bn_statics(state_dict):
  function _rename_conv_weights_for_deformable_conv_layers (line 17) | def _rename_conv_weights_for_deformable_conv_layers(state_dict, cfg):
  function load_pretrain_format (line 44) | def load_pretrain_format(cfg, f):

FILE: GLIP/maskrcnn_benchmark/utils/registry.py
  function _register_generic (line 4) | def _register_generic(module_dict, module_name, module):
  class Registry (line 9) | class Registry(dict):
    method __init__ (line 31) | def __init__(self, *args, **kwargs):
    method register (line 34) | def register(self, module_name, module=None):

FILE: GLIP/maskrcnn_benchmark/utils/shallow_contrastive_loss_helper.py
  function normalized_positive_map (line 5) | def normalized_positive_map(positive_map):
  function pad_tensor_given_dim_length (line 13) | def pad_tensor_given_dim_length(tensor, dim, length, padding_value=0, ba...
  function pad_random_negative_tensor_given_length (line 23) | def pad_random_negative_tensor_given_length(positive_tensor, negative_pa...
  function gather_tensors (line 28) | def gather_tensors(tensor):
  function convert_to_roi_format (line 53) | def convert_to_roi_format(boxes):

FILE: GLIP/maskrcnn_benchmark/utils/stats.py
  function get_model_complexity_info (line 18) | def get_model_complexity_info(model, input_res,
  function flops_to_string (line 58) | def flops_to_string(flops, units='GMac', precision=2):
  function params_to_string (line 79) | def params_to_string(params_num, units=None, precision=2):
  function accumulate_flops (line 96) | def accumulate_flops(self):
  function print_model_with_flops (line 106) | def print_model_with_flops(model, total_flops, total_params, units='GMac',
  function get_model_parameters_number (line 150) | def get_model_parameters_number(model):
  function add_flops_counting_methods (line 155) | def add_flops_counting_methods(net_main_module):
  function compute_average_flops_cost (line 169) | def compute_average_flops_cost(self):
  function start_flops_count (line 191) | def start_flops_count(self, **kwargs):
  function stop_flops_count (line 233) | def stop_flops_count(self):
  function reset_flops_count (line 246) | def reset_flops_count(self):
  function empty_flops_counter_hook (line 259) | def empty_flops_counter_hook(module, input, output):
  function upsample_flops_counter_hook (line 263) | def upsample_flops_counter_hook(module, input, output):
  function relu_flops_counter_hook (line 272) | def relu_flops_counter_hook(module, input, output):
  function linear_flops_counter_hook (line 277) | def linear_flops_counter_hook(module, input, output):
  function pool_flops_counter_hook (line 285) | def pool_flops_counter_hook(module, input, output):
  function bn_flops_counter_hook (line 290) | def bn_flops_counter_hook(module, input, output):
  function conv_flops_counter_hook (line 299) | def conv_flops_counter_hook(conv_module, input, output):
  function batch_counter_hook (line 330) | def batch_counter_hook(module, input, output):
  function rnn_flops (line 343) | def rnn_flops(flops, rnn_module, w_ih, w_hh, input_size):
  function rnn_flops_counter_hook (line 368) | def rnn_flops_counter_hook(rnn_module, input, output):
  function rnn_cell_flops_counter_hook (line 401) | def rnn_cell_flops_counter_hook(rnn_cell_module, input, output):
  function add_batch_counter_variables_or_reset (line 418) | def add_batch_counter_variables_or_reset(module):
  function add_batch_counter_hook_function (line 423) | def add_batch_counter_hook_function(module):
  function remove_batch_counter_hook_function (line 431) | def remove_batch_counter_hook_function(module):
  function add_flops_counter_variable_or_reset (line 437) | def add_flops_counter_variable_or_reset(module):
  function is_supported_instance (line 499) | def is_supported_instance(module):
  function remove_flops_counter_hook_function (line 506) | def remove_flops_counter_hook_function(module):

FILE: GLIP/setup.py
  function get_extensions (line 17) | def get_extensions():

FILE: GLIP/tools/cityscapes/convert_cityscapes_to_coco.py
  function parse_args (line 38) | def parse_args():
  function convert_coco_stuff_mat (line 53) | def convert_coco_stuff_mat(data_dir, out_dir):
  function getLabelID (line 94) | def getLabelID(self, instID):
  function convert_cityscapes_instance_only (line 101) | def convert_cityscapes_instance_only(

FILE: GLIP/tools/cityscapes/instances2dict_with_polygons.py
  function instances2dict_with_polygons (line 19) | def instances2dict_with_polygons(imageFileList, verbose=False):
  function main (line 72) | def main(argv):

FILE: GLIP/tools/eval_all.py
  function main (line 25) | def main():

FILE: GLIP/tools/finetune.py
  function removekey (line 35) | def removekey(d, prefix):
  function train (line 47) | def train(cfg, local_rank, distributed, zero_shot, skip_optimizer_resume...
  function test (line 177) | def test(cfg, model, distributed, verbose=False):
  function tuning_highlevel_override (line 215) | def tuning_highlevel_override(cfg,):
  function report_freeze_options (line 262) | def report_freeze_options(cfg):
  function main (line 271) | def main():

FILE: GLIP/tools/test_grounding_net.py
  function init_distributed_mode (line 31) | def init_distributed_mode(args):
  function setup_for_distributed (line 58) | def setup_for_distributed(is_master):
  function main (line 73) | def main():

FILE: GLIP/tools/test_net.py
  function run_test (line 22) | def run_test(cfg, model, distributed, log_dir):
  function main (line 57) | def main():

FILE: GLIP/tools/train_net.py
  function train (line 34) | def train(cfg, local_rank, distributed, use_tensorboard=False,):
  function setup_for_distributed (line 145) | def setup_for_distributed(is_master):
  function main (line 159) | def main():

FILE: GroundingDINO/demo/gradio_app.py
  function load_model_hf (line 42) | def load_model_hf(model_config_path, repo_id, filename, device='cpu'):
  function image_transform_grounding (line 54) | def image_transform_grounding(init_image):
  function image_transform_grounding_for_vis (line 63) | def image_transform_grounding_for_vis(init_image):
  function run_grounding (line 72) | def run_grounding(input_image, grounding_caption, box_threshold, text_th...

FILE: GroundingDINO/demo/inference_on_a_image.py
  function plot_boxes_to_image (line 16) | def plot_boxes_to_image(image_pil, tgt):
  function load_image (line 57) | def load_image(image_path):
  function load_model (line 72) | def load_model(model_config_path, model_checkpoint_path, cpu_only=False):
  function get_grounding_output (line 83) | def get_grounding_output(model, image, caption, box_threshold, text_thre...

FILE: GroundingDINO/groundingdino/datasets/transforms.py
  function crop (line 17) | def crop(image, target, region):
  function hflip (line 68) | def hflip(image, target):
  function resize (line 87) | def resize(image, target, size, max_size=None):
  function pad (line 149) | def pad(image, target, padding):
  class ResizeDebug (line 162) | class ResizeDebug(object):
    method __init__ (line 163) | def __init__(self, size):
    method __call__ (line 166) | def __call__(self, img, target):
  class RandomCrop (line 170) | class RandomCrop(object):
    method __init__ (line 171) | def __init__(self, size):
    method __call__ (line 174) | def __call__(self, img, target):
  class RandomSizeCrop (line 179) | class RandomSizeCrop(object):
    method __init__ (line 180) | def __init__(self, min_size: int, max_size: int, respect_boxes: bool =...
    method __call__ (line 187) | def __call__(self, img: PIL.Image.Image, target: dict):
  class CenterCrop (line 204) | class CenterCrop(object):
    method __init__ (line 205) | def __init__(self, size):
    method __call__ (line 208) | def __call__(self, img, target):
  class RandomHorizontalFlip (line 216) | class RandomHorizontalFlip(object):
    method __init__ (line 217) | def __init__(self, p=0.5):
    method __call__ (line 220) | def __call__(self, img, target):
  class RandomResize (line 226) | class RandomResize(object):
    method __init__ (line 227) | def __init__(self, sizes, max_size=None):
    method __call__ (line 232) | def __call__(self, img, target=None):
  class RandomPad (line 237) | class RandomPad(object):
    method __init__ (line 238) | def __init__(self, max_pad):
    method __call__ (line 241) | def __call__(self, img, target):
  class RandomSelect (line 247) | class RandomSelect(object):
    method __init__ (line 253) | def __init__(self, transforms1, transforms2, p=0.5):
    method __call__ (line 258) | def __call__(self, img, target):
  class ToTensor (line 264) | class ToTensor(object):
    method __call__ (line 265) | def __call__(self, img, target):
  class RandomErasing (line 269) | class RandomErasing(object):
    method __init__ (line 270) | def __init__(self, *args, **kwargs):
    method __call__ (line 273) | def __call__(self, img, target):
  class Normalize (line 277) | class Normalize(object):
    method __init__ (line 278) | def __init__(self, mean, std):
    method __call__ (line 282) | def __call__(self, image, target=None):
  class Compose (line 296) | class Compose(object):
    method __init__ (line 297) | def __init__(self, transforms):
    method __call__ (line 300) | def __call__(self, image, target):
    method __repr__ (line 305) | def __repr__(self):

FILE: GroundingDINO/groundingdino/models/GroundingDINO/backbone/backbone.py
  class FrozenBatchNorm2d (line 33) | class FrozenBatchNorm2d(torch.nn.Module):
    method __init__ (line 42) | def __init__(self, n):
    method _load_from_state_dict (line 49) | def _load_from_state_dict(
    method forward (line 60) | def forward(self, x):
  class BackboneBase (line 73) | class BackboneBase(nn.Module):
    method __init__ (line 74) | def __init__(
    method forward (line 107) | def forward(self, tensor_list: NestedTensor):
  class Backbone (line 119) | class Backbone(BackboneBase):
    method __init__ (line 122) | def __init__(
  class Joiner (line 146) | class Joiner(nn.Sequential):
    method __init__ (line 147) | def __init__(self, backbone, position_embedding):
    method forward (line 150) | def forward(self, tensor_list: NestedTensor):
  function build_backbone (line 162) | def build_backbone(args):

FILE: GroundingDINO/groundingdino/models/GroundingDINO/backbone/position_encoding.py
  class PositionEmbeddingSine (line 30) | class PositionEmbeddingSine(nn.Module):
    method __init__ (line 36) | def __init__(self, num_pos_feats=64, temperature=10000, normalize=Fals...
    method forward (line 47) | def forward(self, tensor_list: NestedTensor):
  class PositionEmbeddingSineHW (line 78) | class PositionEmbeddingSineHW(nn.Module):
    method __init__ (line 84) | def __init__(
    method forward (line 98) | def forward(self, tensor_list: NestedTensor):
  class PositionEmbeddingLearned (line 134) | class PositionEmbeddingLearned(nn.Module):
    method __init__ (line 139) | def __init__(self, num_pos_feats=256):
    method reset_parameters (line 145) | def reset_parameters(self):
    method forward (line 149) | def forward(self, tensor_list: NestedTensor):
  function build_position_encoding (line 171) | def build_position_encoding(args):

FILE: GroundingDINO/groundingdino/models/GroundingDINO/backbone/swin_transformer.py
  class Mlp (line 24) | class Mlp(nn.Module):
    method __init__ (line 27) | def __init__(
    method forward (line 38) | def forward(self, x):
  function window_partition (line 47) | def window_partition(x, window_size):
  function window_reverse (line 61) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 77) | class WindowAttention(nn.Module):
    method __init__ (line 90) | def __init__(
    method forward (line 134) | def forward(self, x, mask=None):
  class SwinTransformerBlock (line 177) | class SwinTransformerBlock(nn.Module):
    method __init__ (line 194) | def __init__(
    method forward (line 238) | def forward(self, x, mask_matrix):
  class PatchMerging (line 301) | class PatchMerging(nn.Module):
    method __init__ (line 308) | def __init__(self, dim, norm_layer=nn.LayerNorm):
    method forward (line 314) | def forward(self, x, H, W):
  class BasicLayer (line 343) | class BasicLayer(nn.Module):
    method __init__ (line 361) | def __init__(
    method forward (line 409) | def forward(self, x, H, W):
  class PatchEmbed (line 459) | class PatchEmbed(nn.Module):
    method __init__ (line 468) | def __init__(self, patch_size=4, in_chans=3, embed_dim=96, norm_layer=...
    method forward (line 482) | def forward(self, x):
  class SwinTransformer (line 501) | class SwinTransformer(nn.Module):
    method __init__ (line 530) | def __init__(
    method _freeze_stages (line 636) | def _freeze_stages(self):
    method forward_raw (line 678) | def forward_raw(self, x):
    method forward (line 712) | def forward(self, tensor_list: NestedTensor):
    method train (line 756) | def train(self, mode=True):
  function build_swin_transformer (line 762) | def build_swin_transformer(modelname, pretrain_img_size, **kw):

FILE: GroundingDINO/groundingdino/models/GroundingDINO/bertwarper.py
  class BertModelWarper (line 17) | class BertModelWarper(nn.Module):
    method __init__ (line 18) | def __init__(self, bert_model):
    method forward (line 31) | def forward(
  class TextEncoderShell (line 169) | class TextEncoderShell(nn.Module):
    method __init__ (line 170) | def __init__(self, text_encoder):
    method forward (line 175) | def forward(self, **kw):
  function generate_masks_with_special_tokens (line 180) | def generate_masks_with_special_tokens(tokenized, special_tokens_list, t...
  function generate_masks_with_special_tokens_and_transfer_map (line 224) | def generate_masks_with_special_tokens_and_transfer_map(tokenized, speci...

FILE: GroundingDINO/groundingdino/models/GroundingDINO/csrc/MsDeformAttn/ms_deform_attn.h
  function namespace (line 19) | namespace groundingdino {

FILE: GroundingDINO/groundingdino/models/GroundingDINO/csrc/MsDeformAttn/ms_deform_attn_cpu.cpp
  type groundingdino (line 16) | namespace groundingdino {
    function ms_deform_attn_cpu_forward (line 18) | at::Tensor
    function ms_deform_attn_cpu_backward (line 30) | std::vector<at::Tensor>

FILE: GroundingDINO/groundingdino/models/GroundingDINO/csrc/MsDeformAttn/ms_deform_attn_cpu.h
  function namespace (line 14) | namespace groundingdino {

FILE: GroundingDINO/groundingdino/models/GroundingDINO/csrc/MsDeformAttn/ms_deform_attn_cuda.h
  function namespace (line 14) | namespace groundingdino {

FILE: GroundingDINO/groundingdino/models/GroundingDINO/csrc/vision.cpp
  type groundingdino (line 5) | namespace groundingdino {
    function get_cuda_version (line 11) | std::string get_cuda_version() {
    function get_compiler_version (line 32) | std::string get_compiler_version() {
    function PYBIND11_MODULE (line 53) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: GroundingDINO/groundingdino/models/GroundingDINO/fuse_modules.py
  class FeatureResizer (line 14) | class FeatureResizer(nn.Module):
    method __init__ (line 20) | def __init__(self, input_feat_size, output_feat_size, dropout, do_ln=T...
    method forward (line 28) | def forward(self, encoder_features):
  function l1norm (line 36) | def l1norm(X, dim, eps=1e-8):
  function l2norm (line 43) | def l2norm(X, dim, eps=1e-8):
  function func_attention (line 50) | def func_attention(query, context, smooth=1, raw_feature_norm="softmax",...
  class BiMultiHeadAttention (line 99) | class BiMultiHeadAttention(nn.Module):
    method __init__ (line 100) | def __init__(self, v_dim, l_dim, embed_dim, num_heads, dropout=0.1, cf...
    method _shape (line 129) | def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
    method _reset_parameters (line 132) | def _reset_parameters(self):
    method forward (line 146) | def forward(self, v, l, attention_mask_v=None, attention_mask_l=None):
  class BiAttentionBlock (line 252) | class BiAttentionBlock(nn.Module):
    method __init__ (line 253) | def __init__(
    method forward (line 286) | def forward(self, v, l, attention_mask_v=None, attention_mask_l=None):

FILE: GroundingDINO/groundingdino/models/GroundingDINO/groundingdino.py
  class GroundingDINO (line 51) | class GroundingDINO(nn.Module):
    method __init__ (line 54) | def __init__(
    method _reset_parameters (line 204) | def _reset_parameters(self):
    method init_ref_points (line 210) | def init_ref_points(self, use_num_queries):
    method forward (line 213) | def forward(self, samples: NestedTensor, targets: List = None, **kw):
    method _set_aux_loss (line 353) | def _set_aux_loss(self, outputs_class, outputs_coord):
  function build_groundingdino (line 364) | def build_groundingdino(args):

FILE: GroundingDINO/groundingdino/models/GroundingDINO/ms_deform_attn.py
  function _is_power_of_2 (line 35) | def _is_power_of_2(n):
  class MultiScaleDeformableAttnFunction (line 41) | class MultiScaleDeformableAttnFunction(Function):
    method forward (line 43) | def forward(
    method backward (line 72) | def backward(ctx, grad_output):
  function multi_scale_deformable_attn_pytorch (line 93) | def multi_scale_deformable_attn_pytorch(
  class MultiScaleDeformableAttention (line 136) | class MultiScaleDeformableAttention(nn.Module):
    method __init__ (line 154) | def __init__(
    method _reset_parameters (line 194) | def _reset_parameters(self):
    method init_weights (line 197) | def init_weights(self):
    method freeze_sampling_offsets (line 222) | def freeze_sampling_offsets(self):
    method freeze_attention_weights (line 227) | def freeze_attention_weights(self):
    method forward (line 232) | def forward(
  function create_dummy_class (line 362) | def create_dummy_class(klass, dependency, message=""):
  function create_dummy_func (line 391) | def create_dummy_func(func, dependency, message=""):

FILE: GroundingDINO/groundingdino/models/GroundingDINO/transformer.py
  class Transformer (line 40) | class Transformer(nn.Module):
    method __init__ (line 41) | def __init__(
    method _reset_parameters (line 189) | def _reset_parameters(self):
    method get_valid_ratio (line 199) | def get_valid_ratio(self, mask):
    method init_ref_points (line 208) | def init_ref_points(self, use_num_queries):
    method forward (line 211) | def forward(self, srcs, masks, refpoint_embed, pos_embeds, tgt, attn_m...
  class TransformerEncoder (line 406) | class TransformerEncoder(nn.Module):
    method __init__ (line 407) | def __init__(
    method get_reference_points (line 466) | def get_reference_points(spatial_shapes, valid_ratios, device):
    method forward (line 482) | def forward(
  class TransformerDecoder (line 599) | class TransformerDecoder(nn.Module):
    method __init__ (line 600) | def __init__(
    method forward (line 634) | def forward(
  class DeformableTransformerEncoderLayer (line 739) | class DeformableTransformerEncoderLayer(nn.Module):
    method __init__ (line 740) | def __init__(
    method with_pos_embed (line 772) | def with_pos_embed(tensor, pos):
    method forward_ffn (line 775) | def forward_ffn(self, src):
    method forward (line 781) | def forward(
  class DeformableTransformerDecoderLayer (line 803) | class DeformableTransformerDecoderLayer(nn.Module):
    method __init__ (line 804) | def __init__(
    method rm_self_attn_modules (line 853) | def rm_self_attn_modules(self):
    method with_pos_embed (line 859) | def with_pos_embed(tensor, pos):
    method forward_ffn (line 862) | def forward_ffn(self, tgt):
    method forward (line 869) | def forward(
  function build_transformer (line 931) | def build_transformer(args):

FILE: GroundingDINO/groundingdino/models/GroundingDINO/transformer_vanilla.py
  class TextTransformer (line 33) | class TextTransformer(nn.Module):
    method __init__ (line 34) | def __init__(self, num_layers, d_model=256, nheads=8, dim_feedforward=...
    method forward (line 47) | def forward(self, memory_text: torch.Tensor, text_attention_mask: torc...
  class TransformerEncoderLayer (line 72) | class TransformerEncoderLayer(nn.Module):
    method __init__ (line 73) | def __init__(
    method with_pos_embed (line 98) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward (line 101) | def forward(

FILE: GroundingDINO/groundingdino/models/GroundingDINO/utils.py
  function _get_clones (line 16) | def _get_clones(module, N, layer_share=False):
  function get_sine_pos_embed (line 24) | def get_sine_pos_embed(
  function gen_encoder_output_proposals (line 56) | def gen_encoder_output_proposals(
  class RandomBoxPerturber (line 120) | class RandomBoxPerturber:
    method __init__ (line 121) | def __init__(
    method __call__ (line 128) | def __call__(self, refanchors: Tensor) -> Tensor:
  function sigmoid_focal_loss (line 139) | def sigmoid_focal_loss(
  class MLP (line 172) | class MLP(nn.Module):
    method __init__ (line 175) | def __init__(self, input_dim, hidden_dim, output_dim, num_layers):
    method forward (line 183) | def forward(self, x):
  function _get_activation_fn (line 189) | def _get_activation_fn(activation, d_model=256, batch_dim=0):
  function gen_sineembed_for_position (line 205) | def gen_sineembed_for_position(pos_tensor):
  class ContrastiveEmbed (line 235) | class ContrastiveEmbed(nn.Module):
    method __init__ (line 236) | def __init__(self, max_text_len=256):
    method forward (line 244) | def forward(self, x, text_dict):

FILE: GroundingDINO/groundingdino/models/__init__.py
  function build_model (line 11) | def build_model(args):

FILE: GroundingDINO/groundingdino/models/registry.py
  class Registry (line 18) | class Registry(object):
    method __init__ (line 19) | def __init__(self, name):
    method __repr__ (line 23) | def __repr__(self):
    method __len__ (line 29) | def __len__(self):
    method name (line 33) | def name(self):
    method module_dict (line 37) | def module_dict(self):
    method get (line 40) | def get(self, key):
    method registe_with_name (line 43) | def registe_with_name(self, module_name=None, force=False):
    method register (line 46) | def register(self, module_build_function, module_name=None, force=False):

FILE: GroundingDINO/groundingdino/util/box_ops.py
  function box_cxcywh_to_xyxy (line 9) | def box_cxcywh_to_xyxy(x):
  function box_xyxy_to_cxcywh (line 15) | def box_xyxy_to_cxcywh(x):
  function box_iou (line 22) | def box_iou(boxes1, boxes2):
  function generalized_box_iou (line 39) | def generalized_box_iou(boxes1, boxes2):
  function box_iou_pairwise (line 66) | def box_iou_pairwise(boxes1, boxes2):
  function generalized_box_iou_pairwise (line 82) | def generalized_box_iou_pairwise(boxes1, boxes2):
  function masks_to_boxes (line 107) | def masks_to_boxes(masks):

FILE: GroundingDINO/groundingdino/util/get_tokenlizer.py
  function get_tokenlizer (line 4) | def get_tokenlizer(text_encoder_type, bert_base_uncased_path):
  function get_pretrained_language_model (line 27) | def get_pretrained_language_model(text_encoder_type, bert_base_uncased_p...
  function is_bert_model_use_local_path (line 36) | def is_bert_model_use_local_path(bert_base_uncased_path):

FILE: GroundingDINO/groundingdino/util/inference.py
  function preprocess_caption (line 22) | def preprocess_caption(caption: str) -> str:
  function load_model (line 29) | def load_model(model_config_path: str, model_checkpoint_path: str, devic...
  function load_image (line 39) | def load_image(image_path: str) -> Tuple[np.array, torch.Tensor]:
  function predict (line 53) | def predict(
  function annotate (line 88) | def annotate(image_source: np.ndarray, boxes: torch.Tensor, logits: torc...
  class Model (line 111) | class Model:
    method __init__ (line 113) | def __init__(
    method predict_with_caption (line 126) | def predict_with_caption(
    method predict_with_classes (line 167) | def predict_with_classes(
    method preprocess_image (line 213) | def preprocess_image(image_bgr: np.ndarray) -> torch.Tensor:
    method post_process_result (line 226) | def post_process_result(
    method phrases2classes (line 238) | def phrases2classes(phrases: List[str], classes: List[str]) -> np.ndar...
    method find_index (line 249) | def find_index(string, lst):

FILE: GroundingDINO/groundingdino/util/logger.py
  class _ColorfulFormatter (line 10) | class _ColorfulFormatter(logging.Formatter):
    method __init__ (line 11) | def __init__(self, *args, **kwargs):
    method formatMessage (line 18) | def formatMessage(self, record):
  function setup_logger (line 32) | def setup_logger(output=None, distributed_rank=0, *, color=True, name="i...
  function _cached_log_stream (line 92) | def _cached_log_stream(filename):

FILE: GroundingDINO/groundingdino/util/misc.py
  class SmoothedValue (line 33) | class SmoothedValue(object):
    method __init__ (line 38) | def __init__(self, window_size=20, fmt=None):
    method update (line 46) | def update(self, value, n=1):
    method synchronize_between_processes (line 51) | def synchronize_between_processes(self):
    method median (line 65) | def median(self):
    method avg (line 72) | def avg(self):
    method global_avg (line 77) | def global_avg(self):
    method max (line 85) | def max(self):
    method value (line 89) | def value(self):
    method __str__ (line 92) | def __str__(self):
  function _get_global_gloo_group (line 103) | def _get_global_gloo_group():
  function all_gather_cpu (line 115) | def all_gather_cpu(data):
  function all_gather (line 173) | def all_gather(data):
  function reduce_dict (line 220) | def reduce_dict(input_dict, average=True):
  class MetricLogger (line 247) | class MetricLogger(object):
    method __init__ (line 248) | def __init__(self, delimiter="\t"):
    method update (line 252) | def update(self, **kwargs):
    method __getattr__ (line 259) | def __getattr__(self, attr):
    method __str__ (line 266) | def __str__(self):
    method synchronize_between_processes (line 275) | def synchronize_between_processes(self):
    method add_meter (line 279) | def add_meter(self, name, meter):
    method log_every (line 282) | def log_every(self, iterable, print_freq, header=None, logger=None):
  function get_sha (line 362) | def get_sha():
  function collate_fn (line 383) | def collate_fn(batch):
  function _max_by_axis (line 390) | def _max_by_axis(the_list):
  class NestedTensor (line 399) | class NestedTensor(object):
    method __init__ (line 400) | def __init__(self, tensors, mask: Optional[Tensor]):
    method imgsize (line 416) | def imgsize(self):
    method to (line 425) | def to(self, device):
    method to_img_list_single (line 436) | def to_img_list_single(self, tensor, mask):
    method to_img_list (line 443) | def to_img_list(self):
    method device (line 460) | def device(self):
    method decompose (line 463) | def decompose(self):
    method __repr__ (line 466) | def __repr__(self):
    method shape (line 470) | def shape(self):
  function nested_tensor_from_tensor_list (line 474) | def nested_tensor_from_tensor_list(tensor_list: List[Tensor]):
  function _onnx_nested_tensor_from_tensor_list (line 502) | def _onnx_nested_tensor_from_tensor_list(tensor_list: List[Tensor]) -> N...
  function setup_for_distributed (line 532) | def setup_for_distributed(is_master):
  function is_dist_avail_and_initialized (line 548) | def is_dist_avail_and_initialized():
  function get_world_size (line 556) | def get_world_size():
  function get_rank (line 562) | def get_rank():
  function is_main_process (line 568) | def is_main_process():
  function save_on_master (line 572) | def save_on_master(*args, **kwargs):
  function init_distributed_mode (line 577) | def init_distributed_mode(args):
  function accuracy (line 638) | def accuracy(output, target, topk=(1,)):
  function accuracy_onehot (line 657) | def accuracy_onehot(pred, gt):
  function interpolate (line 669) | def interpolate(input, size=None, scale_factor=None, mode="nearest", ali...
  class color_sys (line 687) | class color_sys:
    method __init__ (line 688) | def __init__(self, num_colors) -> None:
    method __call__ (line 700) | def __call__(self, idx):
  function inverse_sigmoid (line 704) | def inverse_sigmoid(x, eps=1e-3):
  function clean_state_dict (line 711) | def clean_state_dict(state_dict):

FILE: GroundingDINO/groundingdino/util/slconfig.py
  function check_file_exist (line 21) | def check_file_exist(filename, msg_tmpl='file "{}" does not exist'):
  class ConfigDict (line 26) | class ConfigDict(Dict):
    method __missing__ (line 27) | def __missing__(self, name):
    method __getattr__ (line 30) | def __getattr__(self, name):
  class SLConfig (line 42) | class SLConfig(object):
    method _validate_py_syntax (line 68) | def _validate_py_syntax(filename):
    method _file2dict (line 77) | def _file2dict(filename):
    method _merge_a_into_b (line 140) | def _merge_a_into_b(a, b):
    method fromfile (line 184) | def fromfile(filename):
    method __init__ (line 188) | def __init__(self, cfg_dict=None, cfg_text=None, filename=None):
    method filename (line 209) | def filename(self):
    method text (line 213) | def text(self):
    method pretty_text (line 217) | def pretty_text(self):
    method __repr__ (line 310) | def __repr__(self):
    method __len__ (line 313) | def __len__(self):
    method __getattr__ (line 316) | def __getattr__(self, name):
    method __getitem__ (line 329) | def __getitem__(self, name):
    method __setattr__ (line 332) | def __setattr__(self, name, value):
    method __setitem__ (line 337) | def __setitem__(self, name, value):
    method __iter__ (line 342) | def __iter__(self):
    method dump (line 345) | def dump(self, file=None):
    method merge_from_dict (line 353) | def merge_from_dict(self, options):
    method __setstate__ (line 386) | def __setstate__(self, state):
    method copy (line 389) | def copy(self):
    method deepcopy (line 392) | def deepcopy(self):
  class DictAction (line 396) | class DictAction(Action):
    method _parse_int_float_bool (line 404) | def _parse_int_float_bool(val):
    method __call__ (line 419) | def __call__(self, parser, namespace, values, option_string=None):

FILE: GroundingDINO/groundingdino/util/slio.py
  class BaseFileHandler (line 23) | class BaseFileHandler(metaclass=ABCMeta):
    method load_from_fileobj (line 25) | def load_from_fileobj(self, file, **kwargs):
    method dump_to_fileobj (line 29) | def dump_to_fileobj(self, obj, file, **kwargs):
    method dump_to_str (line 33) | def dump_to_str(self, obj, **kwargs):
    method load_from_path (line 36) | def load_from_path(self, filepath, mode="r", **kwargs):
    method dump_to_path (line 40) | def dump_to_path(self, obj, filepath, mode="w", **kwargs):
  class JsonHandler (line 45) | class JsonHandler(BaseFileHandler):
    method load_from_fileobj (line 46) | def load_from_fileobj(self, file):
    method dump_to_fileobj (line 49) | def dump_to_fileobj(self, obj, file, **kwargs):
    method dump_to_str (line 52) | def dump_to_str(self, obj, **kwargs):
  class PickleHandler (line 56) | class PickleHandler(BaseFileHandler):
    method load_from_fileobj (line 57) | def load_from_fileobj(self, file, **kwargs):
    method load_from_path (line 60) | def load_from_path(self, filepath, **kwargs):
    method dump_to_str (line 63) | def dump_to_str(self, obj, **kwargs):
    method dump_to_fileobj (line 67) | def dump_to_fileobj(self, obj, file, **kwargs):
    method dump_to_path (line 71) | def dump_to_path(self, obj, filepath, **kwargs):
  class YamlHandler (line 75) | class YamlHandler(BaseFileHandler):
    method load_from_fileobj (line 76) | def load_from_fileobj(self, file, **kwargs):
    method dump_to_fileobj (line 80) | def dump_to_fileobj(self, obj, file, **kwargs):
    method dump_to_str (line 84) | def dump_to_str(self, obj, **kwargs):
  function is_str (line 102) | def is_str(x):
  function slload (line 110) | def slload(file, file_format=None, **kwargs):
  function sldump (line 143) | def sldump(obj, file=None, file_format=None, **kwargs):

FILE: GroundingDINO/groundingdino/util/time_counter.py
  class TimeCounter (line 5) | class TimeCounter:
    method __init__ (line 6) | def __init__(self) -> None:
    method clear (line 9) | def clear(self):
    method timeit (line 13) | def timeit(self, name):
  class TimeHolder (line 19) | class TimeHolder:
    method __init__ (line 20) | def __init__(self) -> None:
    method update (line 23) | def update(self, _timedict: dict):
    method final_res (line 29) | def final_res(self):
    method __str__ (line 32) | def __str__(self):
  class AverageMeter (line 36) | class AverageMeter(object):
    method __init__ (line 39) | def __init__(self, name, fmt=":f", val_only=False):
    method reset (line 45) | def reset(self):
    method update (line 51) | def update(self, val, n=1):
    method __str__ (line 57) | def __str__(self):

FILE: GroundingDINO/groundingdino/util/utils.py
  function slprint (line 15) | def slprint(x, name="x"):
  function clean_state_dict (line 29) | def clean_state_dict(state_dict):
  function renorm (line 38) | def renorm(
  class CocoClassMapper (line 66) | class CocoClassMapper:
    method __init__ (line 67) | def __init__(self) -> None:
    method origin2compact (line 153) | def origin2compact(self, idx):
    method compact2origin (line 156) | def compact2origin(self, idx):
  function to_device (line 160) | def to_device(item, device):
  function get_gaussian_mean (line 174) | def get_gaussian_mean(x, axis, other_axis, softmax=True):
  function get_expected_points_from_map (line 200) | def get_expected_points_from_map(hm, softmax=True):
  class Embedder (line 222) | class Embedder:
    method __init__ (line 223) | def __init__(self, **kwargs):
    method create_embedding_fn (line 227) | def create_embedding_fn(self):
    method embed (line 251) | def embed(self, inputs):
  function get_embedder (line 255) | def get_embedder(multires, i=0):
  class APOPMeter (line 275) | class APOPMeter:
    method __init__ (line 276) | def __init__(self) -> None:
    method update (line 282) | def update(self, pred, gt):
    method update_cm (line 293) | def update_cm(self, tp, fp, tn, fn):
  function inverse_sigmoid (line 300) | def inverse_sigmoid(x, eps=1e-5):
  function get_raw_dict (line 307) | def get_raw_dict(args):
  function stat_tensors (line 325) | def stat_tensors(tensor):
  class NiceRepr (line 340) | class NiceRepr:
    method __nice__ (line 374) | def __nice__(self):
    method __repr__ (line 384) | def __repr__(self):
    method __str__ (line 394) | def __str__(self):
  function ensure_rng (line 405) | def ensure_rng(rng=None):
  function random_boxes (line 436) | def random_boxes(num=1, scale=1, rng=None):
  class ModelEma (line 473) | class ModelEma(torch.nn.Module):
    method __init__ (line 474) | def __init__(self, model, decay=0.9997, device=None):
    method _update (line 487) | def _update(self, model, update_fn):
    method update (line 496) | def update(self, model):
    method set (line 499) | def set(self, model):
  class BestMetricSingle (line 503) | class BestMetricSingle:
    method __init__ (line 504) | def __init__(self, init_res=0.0, better="large") -> None:
    method isbetter (line 512) | def isbetter(self, new_res, old_res):
    method update (line 518) | def update(self, new_res, ep):
    method __str__ (line 525) | def __str__(self) -> str:
    method __repr__ (line 528) | def __repr__(self) -> str:
    method summary (line 531) | def summary(self) -> dict:
  class BestMetricHolder (line 538) | class BestMetricHolder:
    method __init__ (line 539) | def __init__(self, init_res=0.0, better="large", use_ema=False) -> None:
    method update (line 546) | def update(self, new_res, epoch, is_ema=False):
    method summary (line 560) | def summary(self):
    method __repr__ (line 570) | def __repr__(self) -> str:
    method __str__ (line 573) | def __str__(self) -> str:
  function targets_to (line 577) | def targets_to(targets: List[Dict[str, Any]], device):
  function get_phrases_from_posmap (line 599) | def get_phrases_from_posmap(

FILE: GroundingDINO/groundingdino/util/visualizer.py
  function renorm (line 22) | def renorm(
  class ColorMap (line 50) | class ColorMap:
    method __init__ (line 51) | def __init__(self, basergb=[255, 255, 0]):
    method __call__ (line 54) | def __call__(self, attnmap):
  function rainbow_text (line 66) | def rainbow_text(x, y, ls, lc, **kw):
  class COCOVisualizer (line 95) | class COCOVisualizer:
    method __init__ (line 96) | def __init__(self, coco=None, tokenlizer=None) -> None:
    method visualize (line 99) | def visualize(self, img, tgt, caption=None, dpi=180, savedir="vis"):
    method addtgt (line 135) | def addtgt(self, tgt):
    method showAnns (line 225) | def showAnns(self, anns, draw_bbox=False):

FILE: GroundingDINO/groundingdino/util/vl_utils.py
  function create_positive_map_from_span (line 8) | def create_positive_map_from_span(tokenized, token_span, max_text_len=256):
  function build_captions_and_token_span (line 49) | def build_captions_and_token_span(cat_list, force_lowercase):
  function build_id2posspan_and_caption (line 90) | def build_id2posspan_and_caption(category_dict: dict):

FILE: GroundingDINO/setup.py
  function write_version_file (line 44) | def write_version_file():
  function get_extensions (line 56) | def get_extensions():
  function parse_requirements (line 114) | def parse_requirements(fname="requirements.txt", with_version=True):

FILE: SG_Nav.py
  class SG_Nav_Agent (line 40) | class SG_Nav_Agent():
    method __init__ (line 41) | def __init__(self, task_config, args=None):
    method add_predicates (line 142) | def add_predicates(self, model):
    method add_rules (line 156) | def add_rules(self, model):
    method reset (line 164) | def reset(self):
    method detect_objects (line 224) | def detect_objects(self, observations):
    method act (line 356) | def act(self, observations):
    method not_use_random_goal (line 508) | def not_use_random_goal(self):
    method get_glip_real_label (line 512) | def get_glip_real_label(self, prediction):
    method fbe (line 525) | def fbe(self, traversible, start):
    method get_goal_gps (line 572) | def get_goal_gps(self, observations, angle, distance):
    method get_relative_goal_gps (line 582) | def get_relative_goal_gps(self, observations, goal_gps=None):
    method init_map (line 592) | def init_map(self):
    method update_map (line 611) | def update_map(self, observations):
    method update_free_map (line 617) | def update_free_map(self, observations):
    method update_room_map (line 624) | def update_room_map(self, observations, room_prediction_result):
    method get_traversible (line 636) | def get_traversible(self, map_pred, pose_pred):
    method _plan (line 680) | def _plan(self, traversible, goal_map, agent_pose, start, start_o, goa...
    method _get_stg (line 746) | def _get_stg(self, traversible, start, goal, goal_found):
    method set_random_goal (line 781) | def set_random_goal(self):
    method update_metrics (line 796) | def update_metrics(self, metrics):
    method visualize (line 804) | def visualize(self, traversible, observations, number_action):
    method save_video (line 840) | def save_video(self):
    method visualize_agent_and_goal (line 852) | def visualize_agent_and_goal(self, map):
  function main (line 864) | def main():

FILE: habitat-lab/examples/benchmark.py
  class ForwardOnlyAgent (line 13) | class ForwardOnlyAgent(habitat.Agent):
    method reset (line 14) | def reset(self):
    method act (line 17) | def act(self, observations):
  function main (line 22) | def main():

FILE: habitat-lab/examples/example.py
  function example (line 10) | def example():

FILE: habitat-lab/examples/example_pointnav.py
  function example (line 10) | def example():

FILE: habitat-lab/examples/interactive_play.py
  function step_env (line 66) | def step_env(env, action_name, action_args, args):
  function get_input_vel_ctlr (line 70) | def get_input_vel_ctlr(skip_pygame, arm_action, g_args, prev_obs, env):
  function get_wrapped_prop (line 209) | def get_wrapped_prop(venv, prop):
  function play_env (line 220) | def play_env(env, args, config):
  function has_pygame (line 323) | def has_pygame():

FILE: habitat-lab/examples/new_actions.py
  class NoisyStrafeActuationSpec (line 28) | class NoisyStrafeActuationSpec:
  function _strafe_impl (line 35) | def _strafe_impl(
  class NoisyStrafeLeft (line 62) | class NoisyStrafeLeft(habitat_sim.SceneNodeControl):
    method __call__ (line 63) | def __call__(
  class NoisyStrafeRight (line 78) | class NoisyStrafeRight(habitat_sim.SceneNodeControl):
    method __call__ (line 79) | def __call__(
  class NoNoiseStrafe (line 96) | class NoNoiseStrafe(HabitatSimV1ActionSpaceConfiguration):
    method get (line 97) | def get(self):
  class NoiseStrafe (line 113) | class NoiseStrafe(HabitatSimV1ActionSpaceConfiguration):
    method get (line 114) | def get(self):
  class StrafeLeft (line 130) | class StrafeLeft(SimulatorTaskAction):
    method _get_uuid (line 131) | def _get_uuid(self, *args, **kwargs) -> str:
    method step (line 134) | def step(self, *args, **kwargs):
  class StrafeRight (line 139) | class StrafeRight(SimulatorTaskAction):
    method _get_uuid (line 140) | def _get_uuid(self, *args, **kwargs) -> str:
    method step (line 143) | def step(self, *args, **kwargs):
  function main (line 147) | def main():

FILE: habitat-lab/examples/register_new_sensors_and_measures.py
  class EpisodeInfoExample (line 18) | class EpisodeInfoExample(habitat.Measure):
    method __init__ (line 19) | def __init__(self, sim, config, **kwargs: Any):
    method _get_uuid (line 26) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method reset_metric (line 30) | def reset_metric(self, *args: Any, episode, **kwargs: Any):
    method update_metric (line 37) | def update_metric(self, *args: Any, episode, action, **kwargs: Any):
  class AgentPositionSensor (line 45) | class AgentPositionSensor(habitat.Sensor):
    method __init__ (line 46) | def __init__(self, sim, config, **kwargs: Any):
    method _get_uuid (line 54) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method _get_sensor_type (line 58) | def _get_sensor_type(self, *args: Any, **kwargs: Any):
    method _get_observation_space (line 62) | def _get_observation_space(self, *args: Any, **kwargs: Any):
    method get_observation (line 71) | def get_observation(
  function main (line 77) | def main():

FILE: habitat-lab/examples/shortest_path_follower_example.py
  class SimpleRLEnv (line 25) | class SimpleRLEnv(habitat.RLEnv):
    method get_reward_range (line 26) | def get_reward_range(self):
    method get_reward (line 29) | def get_reward(self, observations):
    method get_done (line 32) | def get_done(self, observations):
    method get_info (line 35) | def get_info(self, observations):
  function draw_top_down_map (line 39) | def draw_top_down_map(info, output_size):
  function shortest_path_example (line 45) | def shortest_path_example():
  function main (line 85) | def main():

FILE: habitat-lab/examples/tutorials/nb_python/Habitat_Lab.py
  function display_sample (line 76) | def display_sample(
  class NewNavigationTask (line 254) | class NewNavigationTask(NavigationTask):
    method __init__ (line 255) | def __init__(self, config, sim, dataset):
    method _check_episode_is_active (line 259) | def _check_episode_is_active(self, *args, **kwargs):
  class AgentPositionSensor (line 313) | class AgentPositionSensor(habitat.Sensor):
    method __init__ (line 314) | def __init__(self, sim, config, **kwargs):
    method _get_uuid (line 319) | def _get_uuid(self, *args, **kwargs):
    method _get_sensor_type (line 323) | def _get_sensor_type(self, *args, **kwargs):
    method _get_observation_space (line 327) | def _get_observation_space(self, *args, **kwargs):
    method get_observation (line 336) | def get_observation(self, observations, *args, episode, **kwargs):
  class ForwardOnlyAgent (line 383) | class ForwardOnlyAgent(habitat.Agent):
    method __init__ (line 384) | def __init__(self, success_distance, goal_sensor_uuid):
    method reset (line 388) | def reset(self):
    method is_goal_reached (line 391) | def is_goal_reached(self, observations):
    method act (line 395) | def act(self, observations):

FILE: habitat-lab/examples/visualization_examples.py
  function example_pointnav_draw_target_birdseye_view (line 22) | def example_pointnav_draw_target_birdseye_view():
  function example_pointnav_draw_target_birdseye_view_agent_on_border (line 48) | def example_pointnav_draw_target_birdseye_view_agent_on_border():
  function example_get_topdown_map (line 82) | def example_get_topdown_map():
  function main (line 101) | def main():

FILE: habitat-lab/examples/vln_benchmark.py
  function reference_path_benchmark (line 17) | def reference_path_benchmark(config, num_episodes=None):
  function main (line 61) | def main():

FILE: habitat-lab/examples/vln_reference_path_follower_example.py
  function save_map (line 28) | def save_map(observations, info, images):
  function reference_path_example (line 38) | def reference_path_example(mode):

FILE: habitat-lab/habitat/config/default.py
  class Config (line 13) | class Config(yacs.config.CfgNode):
    method __init__ (line 14) | def __init__(self, *args, **kwargs):
  function get_config (line 446) | def get_config(

FILE: habitat-lab/habitat/core/agent.py
  class Agent (line 16) | class Agent:
    method reset (line 22) | def reset(self) -> None:
    method act (line 26) | def act(

FILE: habitat-lab/habitat/core/benchmark.py
  class Benchmark (line 29) | class Benchmark:
    method __init__ (line 32) | def __init__(
    method remote_evaluate (line 52) | def remote_evaluate(
    method local_evaluate (line 126) | def local_evaluate(
    method evaluate (line 208) | def evaluate(

FILE: habitat-lab/habitat/core/challenge.py
  class Challenge (line 13) | class Challenge(Benchmark):
    method __init__ (line 14) | def __init__(self, eval_remote=False, split_l=-1, split_r=-1):
    method submit (line 18) | def submit(self, agent):

FILE: habitat-lab/habitat/core/dataset.py
  class Episode (line 40) | class Episode:
    method _reset_shortest_path_cache_hook (line 79) | def _reset_shortest_path_cache_hook(
    method __getstate__ (line 85) | def __getstate__(self):
    method __setstate__ (line 92) | def __setstate__(self, state):
  class Dataset (line 100) | class Dataset(Generic[T]):
    method scene_from_scene_path (line 105) | def scene_from_scene_path(scene_path: str) -> str:
    method get_scenes_to_load (line 116) | def get_scenes_to_load(cls, config: Config) -> List[str]:
    method build_content_scenes_filter (line 130) | def build_content_scenes_filter(cls, config) -> Callable[[T], bool]:
    method num_episodes (line 145) | def num_episodes(self) -> int:
    method scene_ids (line 150) | def scene_ids(self) -> List[str]:
    method get_scene_episodes (line 154) | def get_scene_episodes(self, scene_id: str) -> List[T]:
    method get_episodes (line 164) | def get_episodes(self, indexes: List[int]) -> List[T]:
    method get_episode_iterator (line 172) | def get_episode_iterator(self, *args: Any, **kwargs: Any) -> Iterator[T]:
    method to_json (line 186) | def to_json(self) -> str:
    method from_json (line 201) | def from_json(
    method filter_episodes (line 215) | def filter_episodes(self, filter_fn: Callable[[T], bool]) -> "Dataset":
    method get_splits (line 230) | def get_splits(
  class EpisodeIterator (line 328) | class EpisodeIterator(Iterator[T]):
    method __init__ (line 356) | def __init__(
    method __iter__ (line 425) | def __iter__(self) -> "EpisodeIterator":
    method __next__ (line 428) | def __next__(self) -> Episode:
    method _forced_scene_switch (line 457) | def _forced_scene_switch(self) -> None:
    method _shuffle (line 472) | def _shuffle(self) -> None:
    method _group_scenes (line 486) | def _group_scenes(
    method step_taken (line 505) | def step_taken(self) -> None:
    method _randomize_value (line 509) | def _randomize_value(value: int, value_range: float) -> int:
    method _set_shuffle_intervals (line 514) | def _set_shuffle_intervals(self) -> None:
    method _forced_scene_switch_if (line 527) | def _forced_scene_switch_if(self) -> None:

FILE: habitat-lab/habitat/core/embodied_task.py
  class Action (line 21) | class Action:
    method __init__ (line 30) | def __init__(self, *args: Any, **kwargs: Any) -> None:
    method reset (line 33) | def reset(self, *args: Any, **kwargs: Any) -> None:
    method step (line 40) | def step(self, *args: Any, **kwargs: Any) -> Observations:
    method action_space (line 51) | def action_space(self) -> Space:
  class SimulatorTaskAction (line 56) | class SimulatorTaskAction(Action):
    method __init__ (line 61) | def __init__(
    method action_space (line 68) | def action_space(self):
    method reset (line 71) | def reset(self, *args: Any, **kwargs: Any) -> None:
    method step (line 74) | def step(self, *args: Any, **kwargs: Any) -> Observations:
  class Measure (line 79) | class Measure:
    method __init__ (line 98) | def __init__(self, *args: Any, **kwargs: Any) -> None:
    method _get_uuid (line 102) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method reset_metric (line 105) | def reset_metric(self, *args: Any, **kwargs: Any) -> None:
    method update_metric (line 111) | def update_metric(self, *args: Any, **kwargs: Any) -> None:
    method get_metric (line 117) | def get_metric(self):
  class Metrics (line 125) | class Metrics(dict):
    method __init__ (line 128) | def __init__(self, measures: Dict[str, Measure]) -> None:
  class Measurements (line 140) | class Measurements:
    method __init__ (line 147) | def __init__(self, measures: Iterable[Measure]) -> None:
    method reset_measures (line 160) | def reset_measures(self, *args: Any, **kwargs: Any) -> None:
    method update_measures (line 164) | def update_measures(self, *args: Any, **kwargs: Any) -> None:
    method get_metrics (line 168) | def get_metrics(self) -> Metrics:
    method _get_measure_index (line 174) | def _get_measure_index(self, measure_name):
    method check_measure_dependencies (line 177) | def check_measure_dependencies(
  class EmbodiedTask (line 200) | class EmbodiedTask:
    method __init__ (line 226) | def __init__(
    method _init_entities (line 260) | def _init_entities(
    method reset (line 283) | def reset(self, episode: Episode):
    method _step_single_action (line 298) | def _step_single_action(
    method step (line 320) | def step(self, action: Dict[str, Any], episode: Episode):
    method get_action_name (line 352) | def get_action_name(self, action_index: Union[int, np.integer]):
    method action_space (line 358) | def action_space(self) -> Space:
    method overwrite_sim_config (line 366) | def overwrite_sim_config(
    method _check_episode_is_active (line 377) | def _check_episode_is_active(
    method is_episode_active (line 387) | def is_episode_active(self):
    method seed (line 390) | def seed(self, seed: int) -> None:

FILE: habitat-lab/habitat/core/env.py
  class Env (line 26) | class Env:
    method __init__ (line 57) | def __init__(
    method _setup_episode_iterator (line 129) | def _setup_episode_iterator(self):
    method current_episode (line 141) | def current_episode(self) -> Episode:
    method current_episode (line 146) | def current_episode(self, episode: Episode) -> None:
    method episode_iterator (line 154) | def episode_iterator(self) -> Iterator[Episode]:
    method episode_iterator (line 158) | def episode_iterator(self, new_iter: Iterator[Episode]) -> None:
    method episodes (line 164) | def episodes(self) -> List[Episode]:
    method episodes (line 172) | def episodes(self, episodes: List[Episode]) -> None:
    method sim (line 186) | def sim(self) -> Simulator:
    method episode_start_time (line 190) | def episode_start_time(self) -> Optional[float]:
    method episode_over (line 194) | def episode_over(self) -> bool:
    method task (line 198) | def task(self) -> EmbodiedTask:
    method _elapsed_seconds (line 202) | def _elapsed_seconds(self) -> float:
    method get_metrics (line 208) | def get_metrics(self) -> Metrics:
    method _past_limit (line 211) | def _past_limit(self) -> bool:
    method _reset_stats (line 220) | def _reset_stats(self) -> None:
    method reset (line 225) | def reset(self) -> Observations:
    method _update_step_stats (line 261) | def _update_step_stats(self) -> None:
    method step (line 272) | def step(
    method _seed_numba (line 316) | def _seed_numba(seed: int):
    method seed (line 320) | def seed(self, seed: int) -> None:
    method reconfigure (line 327) | def reconfigure(self, config: Config) -> None:
    method render (line 338) | def render(self, mode="rgb") -> np.ndarray:
    method close (line 341) | def close(self) -> None:
    method __enter__ (line 344) | def __enter__(self):
    method __exit__ (line 347) | def __exit__(self, exc_type, exc_val, exc_tb):
  class RLEnv (line 351) | class RLEnv(gym.Env):
    method __init__ (line 365) | def __init__(
    method config (line 381) | def config(self) -> Config:
    method habitat_env (line 385) | def habitat_env(self) -> Env:
    method episodes (line 389) | def episodes(self) -> List[Episode]:
    method episodes (line 393) | def episodes(self, episodes: List[Episode]) -> None:
    method current_episode (line 397) | def current_episode(self) -> Episode:
    method reset (line 401) | def reset(self) -> Observations:
    method get_reward_range (line 404) | def get_reward_range(self):
    method get_reward (line 411) | def get_reward(self, observations: Observations) -> Any:
    method get_done (line 421) | def get_done(self, observations: Observations) -> bool:
    method get_info (line 432) | def get_info(self, observations) -> Dict[Any, Any]:
    method step (line 441) | def step(self, *args, **kwargs) -> Tuple[Observations, Any, bool, dict]:
    method seed (line 454) | def seed(self, seed: Optional[int] = None) -> None:
    method render (line 457) | def render(self, mode: str = "rgb") -> np.ndarray:
    method close (line 460) | def close(self) -> None:
    method __enter__ (line 463) | def __enter__(self):
    method __exit__ (line 466) | def __exit__(self, exc_type, exc_val, exc_tb):

FILE: habitat-lab/habitat/core/environments.py
  function get_env_class (line 21) | def get_env_class(env_name: str) -> Type[habitat.RLEnv]:
  class RearrangeRLEnv (line 34) | class RearrangeRLEnv(habitat.RLEnv):
    method __init__ (line 35) | def __init__(self, config: Config, dataset: Optional[Dataset] = None):
    method reset (line 40) | def reset(self):
    method step (line 44) | def step(self, *args, **kwargs):
    method get_reward_range (line 47) | def get_reward_range(self):
    method get_reward (line 51) | def get_reward(self, observations):
    method _episode_success (line 62) | def _episode_success(self):
    method get_done (line 65) | def get_done(self, observations):
    method get_info (line 73) | def get_info(self, observations):
  class NavRLEnv (line 78) | class NavRLEnv(habitat.RLEnv):
    method __init__ (line 79) | def __init__(self, config: Config, dataset: Optional[Dataset] = None):
    method reset (line 86) | def reset(self):
    method step (line 93) | def step(self, *args, **kwargs):
    method get_reward_range (line 96) | def get_reward_range(self):
    method get_reward (line 102) | def get_reward(self, observations):
    method _episode_success (line 115) | def _episode_success(self):
    method get_done (line 118) | def get_done(self, observations):
    method get_info (line 124) | def get_info(self, observations):

FILE: habitat-lab/habitat/core/logging.py
  class HabitatLogger (line 10) | class HabitatLogger(logging.Logger):
    method __init__ (line 11) | def __init__(
    method add_filehandler (line 31) | def add_filehandler(self, log_filename):

FILE: habitat-lab/habitat/core/registry.py
  class Registry (line 43) | class Registry(metaclass=Singleton):
    method _register_impl (line 47) | def _register_impl(
    method register_task (line 72) | def register_task(cls, to_register=None, *, name: Optional[str] = None):
    method register_simulator (line 101) | def register_simulator(
    method register_sensor (line 132) | def register_sensor(cls, to_register=None, *, name: Optional[str] = No...
    method register_measure (line 144) | def register_measure(cls, to_register=None, *, name: Optional[str] = N...
    method register_task_action (line 156) | def register_task_action(
    method register_dataset (line 173) | def register_dataset(cls, to_register=None, *, name: Optional[str] = N...
    method register_action_space_configuration (line 185) | def register_action_space_configuration(
    method register_env (line 202) | def register_env(cls, to_register=None, *, name: Optional[str] = None):
    method _get_impl (line 216) | def _get_impl(cls, _type: str, name: str) -> Type:
    method get_task (line 220) | def get_task(cls, name: str) -> Type[EmbodiedTask]:
    method get_task_action (line 224) | def get_task_action(cls, name: str) -> Type[Action]:
    method get_simulator (line 228) | def get_simulator(cls, name: str) -> Type[Simulator]:
    method get_sensor (line 232) | def get_sensor(cls, name: str) -> Type[Sensor]:
    method get_measure (line 236) | def get_measure(cls, name: str) -> Type[Measure]:
    method get_dataset (line 240) | def get_dataset(cls, name: str) -> Type[Dataset]:
    method get_action_space_configuration (line 244) | def get_action_space_configuration(
    method get_env (line 250) | def get_env(cls, name: str) -> Type["RLEnv"]:

FILE: habitat-lab/habitat/core/simulator.py
  class ActionSpaceConfiguration (line 38) | class ActionSpaceConfiguration(metaclass=abc.ABCMeta):
    method get (line 42) | def get(self) -> Any:
  class SensorTypes (line 46) | class SensorTypes(Enum):
  class Sensor (line 65) | class Sensor(metaclass=abc.ABCMeta):
    method __init__ (line 83) | def __init__(self, *args: Any, **kwargs: Any) -> None:
    method _get_uuid (line 93) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method _get_sensor_type (line 96) | def _get_sensor_type(self, *args: Any, **kwargs: Any) -> SensorTypes:
    method _get_observation_space (line 99) | def _get_observation_space(self, *args: Any, **kwargs: Any) -> Space:
    method get_observation (line 103) | def get_observation(self, *args: Any, **kwargs: Any) -> Any:
  class Observations (line 111) | class Observations(Dict[str, Any]):
    method __init__ (line 114) | def __init__(
  class RGBSensor (line 130) | class RGBSensor(Sensor, metaclass=abc.ABCMeta):
    method __init__ (line 131) | def __init__(self, *args: Any, **kwargs: Any) -> None:
    method _get_uuid (line 134) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method _get_sensor_type (line 137) | def _get_sensor_type(self, *args: Any, **kwargs: Any) -> SensorTypes:
    method _get_observation_space (line 140) | def _get_observation_space(self, *args: Any, **kwargs: Any) -> Space:
    method get_observation (line 143) | def get_observation(self, *args: Any, **kwargs: Any) -> VisualObservat...
  class DepthSensor (line 147) | class DepthSensor(Sensor, metaclass=abc.ABCMeta):
    method __init__ (line 148) | def __init__(self, *args: Any, **kwargs: Any) -> None:
    method _get_uuid (line 151) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method _get_sensor_type (line 154) | def _get_sensor_type(self, *args: Any, **kwargs: Any) -> SensorTypes:
    method _get_observation_space (line 157) | def _get_observation_space(self, *args: Any, **kwargs: Any) -> Space:
    method get_observation (line 160) | def get_observation(self, *args: Any, **kwargs: Any) -> VisualObservat...
  class SemanticSensor (line 164) | class SemanticSensor(Sensor):
    method __init__ (line 165) | def __init__(self, *args: Any, **kwargs: Any) -> None:
    method _get_uuid (line 168) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method _get_sensor_type (line 171) | def _get_sensor_type(self, *args: Any, **kwargs: Any) -> SensorTypes:
    method _get_observation_space (line 174) | def _get_observation_space(self, *args: Any, **kwargs: Any) -> Space:
    method get_observation (line 177) | def get_observation(self, *args: Any, **kwargs: Any) -> VisualObservat...
  class BumpSensor (line 181) | class BumpSensor(Sensor):
    method __init__ (line 182) | def __init__(self, *args: Any, **kwargs: Any) -> None:
    method _get_uuid (line 185) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method _get_sensor_type (line 188) | def _get_sensor_type(self, *args: Any, **kwargs: Any) -> SensorTypes:
    method _get_observation_space (line 191) | def _get_observation_space(self, *args: Any, **kwargs: Any) -> Space:
    method get_observation (line 194) | def get_observation(self, *args: Any, **kwargs: Any) -> Any:
  class SensorSuite (line 198) | class SensorSuite:
    method __init__ (line 206) | def __init__(self, sensors: Iterable[Sensor]) -> None:
    method get (line 222) | def get(self, uuid: str) -> Sensor:
    method get_observations (line 225) | def get_observations(self, *args: Any, **kwargs: Any) -> Observations:
  class AgentState (line 233) | class AgentState:
  class ShortestPathPoint (line 239) | class ShortestPathPoint:
  class Simulator (line 245) | class Simulator:
    method __init__ (line 251) | def __init__(self, *args, **kwargs) -> None:
    method sensor_suite (line 255) | def sensor_suite(self) -> SensorSuite:
    method action_space (line 259) | def action_space(self) -> Space:
    method reset (line 262) | def reset(self) -> Observations:
    method step (line 269) | def step(self, action, *args, **kwargs) -> Observations:
    method seed (line 277) | def seed(self, seed: int) -> None:
    method reconfigure (line 280) | def reconfigure(self, config: Config) -> None:
    method geodesic_distance (line 283) | def geodesic_distance(
    method get_agent_state (line 305) | def get_agent_state(self, agent_id: int = 0) -> AgentState:
    method get_observations_at (line 313) | def get_observations_at(
    method sample_navigable_point (line 334) | def sample_navigable_point(self) -> List[float]:
    method is_navigable (line 342) | def is_navigable(self, point: List[float]) -> bool:
    method action_space_shortest_path (line 349) | def action_space_shortest_path(
    method get_straight_shortest_path_points (line 363) | def get_straight_shortest_path_points(
    method up_vector (line 380) | def up_vector(self) -> "np.ndarray":
    method forward_vector (line 387) | def forward_vector(self) -> "np.ndarray":
    method render (line 394) | def render(self, mode: str = "rgb") -> Any:
    method close (line 397) | def close(self, destroy: bool = True) -> None:
    method previous_step_collided (line 400) | def previous_step_collided(self) -> bool:
    method __enter__ (line 408) | def __enter__(self) -> "Simulator":
    method __exit__ (line 411) | def __exit__(self, exc_type, exc_val, exc_tb):

FILE: habitat-lab/habitat/core/spaces.py
  class EmptySpace (line 15) | class EmptySpace(Space):
    method sample (line 21) | def sample(self):
    method contains (line 24) | def contains(self, x):
    method __repr__ (line 29) | def __repr__(self):
  class ActionSpace (line 33) | class ActionSpace(gym.spaces.Dict):
    method __init__ (line 48) | def __init__(self, spaces: Union[List, Dict]):
    method n (line 56) | def n(self) -> int:
    method sample (line 59) | def sample(self):
    method contains (line 66) | def contains(self, x):
    method __repr__ (line 75) | def __repr__(self):
  class ListSpace (line 83) | class ListSpace(Space):
    method __init__ (line 94) | def __init__(
    method sample (line 107) | def sample(self):
    method contains (line 111) | def contains(self, x):
    method __repr__ (line 120) | def __repr__(self):

FILE: habitat-lab/habitat/core/utils.py
  function tile_images (line 30) | def tile_images(images: List[np.ndarray]) -> np.ndarray:
  function not_none_validator (line 63) | def not_none_validator(
  function try_cv2_import (line 70) | def try_cv2_import():
  class Singleton (line 92) | class Singleton(type):
    method __call__ (line 95) | def __call__(cls, *args, **kwargs):
  function center_crop (line 103) | def center_crop(obs, new_shape):
  class DatasetFloatJSONEncoder (line 117) | class DatasetFloatJSONEncoder(json.JSONEncoder):
    method default (line 123) | def default(self, obj):
    method iterencode (line 138) | def iterencode(self, o, _one_shot=False):

FILE: habitat-lab/habitat/core/vector_env.py
  function _make_env_fn (line 67) | def _make_env_fn(
  class _ReadWrapper (line 83) | class _ReadWrapper:
    method __call__ (line 91) | def __call__(self) -> Any:
  class _WriteWrapper (line 104) | class _WriteWrapper:
    method __call__ (line 112) | def __call__(self, data: Any) -> None:
  class VectorEnv (line 122) | class VectorEnv:
    method __init__ (line 141) | def __init__(
    method num_envs (line 209) | def num_envs(self):
    method _worker_env (line 215) | def _worker_env(
    method _spawn_workers (line 298) | def _spawn_workers(
    method current_episodes (line 343) | def current_episodes(self):
    method count_episodes (line 351) | def count_episodes(self):
    method episode_over (line 359) | def episode_over(self):
    method get_metrics (line 367) | def get_metrics(self):
    method reset (line 375) | def reset(self):
    method reset_at (line 387) | def reset_at(self, index_env: int):
    method async_step_at (line 397) | def async_step_at(
    method wait_step_at (line 408) | def wait_step_at(self, index_env: int) -> Any:
    method step_at (line 411) | def step_at(self, index_env: int, action: Union[int, str, Dict[str, An...
    method async_step (line 421) | def async_step(
    method wait_step (line 435) | def wait_step(self) -> List[Any]:
    method step (line 441) | def step(
    method close (line 454) | def close(self) -> None:
    method pause_at (line 476) | def pause_at(self, index: int) -> None:
    method resume_all (line 493) | def resume_all(self) -> None:
    method call_at (line 501) | def call_at(
    method call (line 521) | def call(
    method render (line 548) | def render(
    method _valid_start_methods (line 570) | def _valid_start_methods(self) -> Set[str]:
    method _warn_cuda_tensors (line 573) | def _warn_cuda_tensors(
    method __del__ (line 591) | def __del__(self):
    method __enter__ (line 594) | def __enter__(self):
    method __exit__ (line 597) | def __exit__(self, exc_type, exc_val, exc_tb):
  class ThreadedVectorEnv (line 601) | class ThreadedVectorEnv(VectorEnv):
    method _spawn_workers (line 611) | def _spawn_workers(

FILE: habitat-lab/habitat/datasets/eqa/__init__.py
  function _try_register_mp3d_eqa_dataset (line 11) | def _try_register_mp3d_eqa_dataset():

FILE: habitat-lab/habitat/datasets/eqa/mp3d_eqa_dataset.py
  function get_default_mp3d_v1_config (line 25) | def get_default_mp3d_v1_config(split: str = "val"):
  class Matterport3dDatasetV1 (line 34) | class Matterport3dDatasetV1(Dataset):
    method check_config_paths_exist (line 48) | def check_config_paths_exist(config: Config) -> bool:
    method __init__ (line 51) | def __init__(self, config: Config = None) -> None:
    method from_json (line 64) | def from_json(

FILE: habitat-lab/habitat/datasets/object_nav/__init__.py
  function _try_register_objectnavdatasetv1 (line 18) | def _try_register_objectnavdatasetv1():

FILE: habitat-lab/habitat/datasets/object_nav/object_nav_dataset.py
  class ObjectNavDatasetV1 (line 28) | class ObjectNavDatasetV1(PointNavDatasetV1):
    method dedup_goals (line 37) | def dedup_goals(dataset: Dict[str, Any]) -> Dict[str, Any]:
    method to_json (line 58) | def to_json(self) -> str:
    method __init__ (line 72) | def __init__(self, config: Optional[Config] = None) -> None:
    method __deserialize_goal (line 78) | def __deserialize_goal(serialized_goal: Dict[str, Any]) -> ObjectGoal:
    method from_json (line 88) | def from_json(

FILE: habitat-lab/habitat/datasets/pointnav/__init__.py
  function _try_register_pointnavdatasetv1 (line 18) | def _try_register_pointnavdatasetv1():

FILE: habitat-lab/habitat/datasets/pointnav/pointnav_dataset.py
  class PointNavDatasetV1 (line 26) | class PointNavDatasetV1(Dataset):
    method check_config_paths_exist (line 33) | def check_config_paths_exist(config: Config) -> bool:
    method get_scenes_to_load (line 39) | def get_scenes_to_load(cls, config: Config) -> List[str]:
    method _get_scenes_from_folder (line 69) | def _get_scenes_from_folder(
    method __init__ (line 86) | def __init__(self, config: Optional[Config] = None) -> None:
    method from_json (line 123) | def from_json(

FILE: habitat-lab/habitat/datasets/pointnav/pointnav_generator.py
  function _ratio_sample_rate (line 31) | def _ratio_sample_rate(ratio: float, ratio_threshold: float) -> float:
  function is_compatible_episode (line 45) | def is_compatible_episode(
  function _create_episode (line 73) | def _create_episode(
  function generate_pointnav_episode (line 95) | def generate_pointnav_episode(

FILE: habitat-lab/habitat/datasets/rearrange/__init__.py
  function _try_register_rearrangedatasetv0 (line 18) | def _try_register_rearrangedatasetv0():

FILE: habitat-lab/habitat/datasets/rearrange/generate_episode_inits.py
  function generate_inits (line 14) | def generate_inits(cfg_path, opts):

FILE: habitat-lab/habitat/datasets/rearrange/rearrange_dataset.py
  class RearrangeEpisode (line 24) | class RearrangeEpisode(Episode):
  class RearrangeDatasetV0 (line 39) | class RearrangeDatasetV0(PointNavDatasetV1):
    method to_json (line 44) | def to_json(self) -> str:
    method __init__ (line 48) | def __init__(self, config: Optional[Config] = None) -> None:
    method from_json (line 64) | def from_json(

FILE: habitat-lab/habitat/datasets/rearrange/rearrange_generator.py
  class RearrangeEpisodeGenerator (line 32) | class RearrangeEpisodeGenerator:
    method __enter__ (line 42) | def __enter__(self) -> "RearrangeEpisodeGenerator":
    method __exit__ (line 45) | def __exit__(self, exc_type, exc_val, exc_tb) -> None:
    method __init__ (line 50) | def __init__(self, cfg: CN, debug_visualization: bool = False) -> None:
    method _get_resource_sets (line 82) | def _get_resource_sets(self) -> None:
    method _get_obj_samplers (line 169) | def _get_obj_samplers(self) -> None:
    method _get_object_target_samplers (line 217) | def _get_object_target_samplers(self) -> None:
    method _get_scene_sampler (line 258) | def _get_scene_sampler(self) -> None:
    method _get_ao_state_samplers (line 285) | def _get_ao_state_samplers(self) -> None:
    method _reset_samplers (line 340) | def _reset_samplers(self) -> None:
    method generate_scene (line 349) | def generate_scene(self) -> str:
    method visualize_scene_receptacles (line 359) | def visualize_scene_receptacles(self) -> None:
    method generate_episodes (line 385) | def generate_episodes(
    method generate_single_episode (line 412) | def generate_single_episode(self) -> Optional[RearrangeEpisode]:
    method initialize_sim (line 556) | def initialize_sim(self, scene_name: str, dataset_path: str) -> None:
    method settle_sim (line 625) | def settle_sim(
  function get_config_defaults (line 695) | def get_config_defaults() -> CN:

FILE: habitat-lab/habitat/datasets/rearrange/receptacle.py
  class Receptacle (line 17) | class Receptacle(ABC):
    method __init__ (line 25) | def __init__(
    method is_parent_object_articulated (line 51) | def is_parent_object_articulated(self):
    method sample_uniform_local (line 58) | def sample_uniform_local(
    method get_global_transform (line 68) | def get_global_transform(self, sim: habitat_sim.Simulator) -> mn.Matrix4:
    method sample_uniform_global (line 73) | def sample_uniform_global(
    method add_receptacle_visualization (line 84) | def add_receptacle_visualization(
  class AABBReceptacle (line 93) | class AABBReceptacle(Receptacle):
    method __init__ (line 98) | def __init__(
    method sample_uniform_local (line 119) | def sample_uniform_local(
    method get_global_transform (line 138) | def get_global_transform(self, sim: habitat_sim.Simulator) -> mn.Matrix4:
    method add_receptacle_visualization (line 184) | def add_receptacle_visualization(
  function get_all_scenedataset_receptacles (line 222) | def get_all_scenedataset_receptacles(sim) -> Dict[str, Dict[str, List[st...
  function parse_receptacles_from_user_config (line 270) | def parse_receptacles_from_user_config(
  function find_receptacles (line 361) | def find_receptacles(

FILE: habitat-lab/habitat/datasets/rearrange/samplers.py
  class SceneSampler (line 21) | class SceneSampler(ABC):
    method num_scenes (line 23) | def num_scenes(self):
    method reset (line 26) | def reset(self) -> None:
    method sample (line 30) | def sample(self):
  class SingleSceneSampler (line 34) | class SingleSceneSampler(SceneSampler):
    method __init__ (line 39) | def __init__(self, scene: str) -> None:
    method sample (line 42) | def sample(self) -> str:
    method num_scenes (line 45) | def num_scenes(self) -> int:
  class MultiSceneSampler (line 49) | class MultiSceneSampler(SceneSampler):
    method __init__ (line 54) | def __init__(self, scenes: List[str]) -> None:
    method sample (line 58) | def sample(self) -> str:
    method num_scenes (line 61) | def num_scenes(self) -> int:
  class ObjectSampler (line 65) | class ObjectSampler:
    method __init__ (line 70) | def __init__(
    method reset (line 102) | def reset(self) -> None:
    method sample_receptacle (line 110) | def sample_receptacle(
    method sample_object (line 196) | def sample_object(self) -> str:
    method sample_placement (line 202) | def sample_placement(
    method single_sample (line 296) | def single_sample(
    method sample (line 315) | def sample(
  class ObjectTargetSampler (line 364) | class ObjectTargetSampler(ObjectSampler):
    method __init__ (line 369) | def __init__(
    method sample (line 389) | def sample(
  class ArticulatedObjectStateSampler (line 459) | class ArticulatedObjectStateSampler:
    method __init__ (line 460) | def __init__(
    method sample (line 468) | def sample(
  class CompositeArticulatedObjectStateSampler (line 507) | class CompositeArticulatedObjectStateSampler(ArticulatedObjectStateSampl...
    method __init__ (line 512) | def __init__(
    method sample (line 528) | def sample(

FILE: habitat-lab/habitat/datasets/registration.py
  function make_dataset (line 16) | def make_dataset(id_dataset, **kwargs):

FILE: habitat-lab/habitat/datasets/utils.py
  function tokenize (line 32) | def tokenize(
  function load_str_list (line 48) | def load_str_list(fname):
  class VocabDict (line 55) | class VocabDict:
    method __init__ (line 61) | def __init__(self, word_list=None, filepath=None):
    method _build (line 70) | def _build(self):
    method idx2word (line 94) | def idx2word(self, n_w):
    method token_idx_2_string (line 97) | def token_idx_2_string(self, tokens: Iterable[int]) -> str:
    method __len__ (line 106) | def __len__(self):
    method get_size (line 109) | def get_size(self):
    method get_unk_index (line 112) | def get_unk_index(self):
    method get_unk_token (line 115) | def get_unk_token(self):
    method word2idx (line 118) | def word2idx(self, w):
    method tokenize_and_index (line 130) | def tokenize_and_index(
  class VocabFromText (line 144) | class VocabFromText(VocabDict):
    method __init__ (line 152) | def __init__(
  function get_action_shortest_path (line 180) | def get_action_shortest_path(
  function check_and_gen_physics_config (line 215) | def check_and_gen_physics_config():

FILE: habitat-lab/habitat/datasets/vln/__init__.py
  function _try_register_r2r_vln_dataset (line 11) | def _try_register_r2r_vln_dataset():

FILE: habitat-lab/habitat/datasets/vln/r2r_vln_dataset.py
  class VLNDatasetV1 (line 23) | class VLNDatasetV1(Dataset):
    method check_config_paths_exist (line 32) | def check_config_paths_exist(config: Config) -> bool:
    method __init__ (line 37) | def __init__(self, config: Optional[Config] = None) -> None:
    method from_json (line 51) | def from_json(

FILE: habitat-lab/habitat/sims/habitat_simulator/__init__.py
  function _try_register_habitat_sim (line 9) | def _try_register_habitat_sim():

FILE: habitat-lab/habitat/sims/habitat_simulator/actions.py
  class _DefaultHabitatSimActions (line 18) | class _DefaultHabitatSimActions(Enum):
  class HabitatSimActionsSingleton (line 29) | class HabitatSimActionsSingleton(metaclass=Singleton):
    method __attrs_post_init__ (line 42) | def __attrs_post_init__(self):
    method extend_action_space (line 46) | def extend_action_space(self, name: str) -> int:
    method has_action (line 68) | def has_action(self, name: str) -> bool:
    method __getattr__ (line 77) | def __getattr__(self, name):
    method __getitem__ (line 80) | def __getitem__(self, name):
    method __len__ (line 83) | def __len__(self):
    method __iter__ (line 86) | def __iter__(self):
  class HabitatSimV0ActionSpaceConfiguration (line 94) | class HabitatSimV0ActionSpaceConfiguration(ActionSpaceConfiguration):
    method get (line 95) | def get(self):
  class HabitatSimV1ActionSpaceConfiguration (line 116) | class HabitatSimV1ActionSpaceConfiguration(
    method get (line 119) | def get(self):
  class HabitatSimPyRobotActionSpaceConfiguration (line 138) | class HabitatSimPyRobotActionSpaceConfiguration(ActionSpaceConfiguration):
    method get (line 139) | def get(self):
  class HabitatSimVelocityCtrlActionSpaceConfiguration (line 196) | class HabitatSimVelocityCtrlActionSpaceConfiguration(ActionSpaceConfigur...
    method get (line 197) | def get(self):

FILE: habitat-lab/habitat/sims/habitat_simulator/debug_visualizer.py
  class DebugVisualizer (line 17) | class DebugVisualizer:
    method __init__ (line 23) | def __init__(
    method look_at (line 40) | def look_at(
    method get_observation (line 68) | def get_observation(
    method save_observation (line 86) | def save_observation(
    method peek_rigid_object (line 118) | def peek_rigid_object(
    method peek_articulated_object (line 136) | def peek_articulated_object(
    method _peek_object (line 154) | def _peek_object(
    method make_debug_video (line 227) | def make_debug_video(

FILE: habitat-lab/habitat/sims/habitat_simulator/habitat_simulator.py
  function overwrite_config (line 46) | def overwrite_config(
  class HabitatSimSensor (line 87) | class HabitatSimSensor:
  class HabitatSimRGBSensor (line 94) | class HabitatSimRGBSensor(RGBSensor, HabitatSimSensor):
    method __init__ (line 100) | def __init__(self, config: Config) -> None:
    method _get_observation_space (line 103) | def _get_observation_space(self, *args: Any, **kwargs: Any) -> Box:
    method get_observation (line 115) | def get_observation(
  class HabitatSimDepthSensor (line 127) | class HabitatSimDepthSensor(DepthSensor, HabitatSimSensor):
    method __init__ (line 139) | def __init__(self, config: Config) -> None:
    method _get_observation_space (line 151) | def _get_observation_space(self, *args: Any, **kwargs: Any) -> Box:
    method get_observation (line 159) | def get_observation(
  class HabitatSimSemanticSensor (line 185) | class HabitatSimSemanticSensor(SemanticSensor, HabitatSimSensor):
    method __init__ (line 189) | def __init__(self, config: Config) -> None:
    method _get_observation_space (line 192) | def _get_observation_space(self, *args: Any, **kwargs: Any):
    method get_observation (line 200) | def get_observation(
  class HabitatSimEquirectangularRGBSensor (line 215) | class HabitatSimEquirectangularRGBSensor(HabitatSimRGBSensor):
  class HabitatSimEquirectangularDepthSensor (line 220) | class HabitatSimEquirectangularDepthSensor(HabitatSimDepthSensor):
  class HabitatSimEquirectangularSemanticSensor (line 225) | class HabitatSimEquirectangularSemanticSensor(HabitatSimSemanticSensor):
  class HabitatSimFisheyeRGBSensor (line 230) | class HabitatSimFisheyeRGBSensor(HabitatSimRGBSensor):
  class HabitatSimFisheyeDepthSensor (line 235) | class HabitatSimFisheyeDepthSensor(HabitatSimDepthSensor):
  class HabitatSimFisheyeSemanticSensor (line 240) | class HabitatSimFisheyeSemanticSensor(HabitatSimSemanticSensor):
  function check_sim_obs (line 244) | def check_sim_obs(
  class HabitatSim (line 254) | class HabitatSim(habitat_sim.Simulator, Simulator):
    method __init__ (line 263) | def __init__(self, config: Config) -> None:
    method create_sim_config (line 291) | def create_sim_config(
    method sensor_suite (line 366) | def sensor_suite(self) -> SensorSuite:
    method action_space (line 370) | def action_space(self) -> Space:
    method _update_agents_state (line 373) | def _update_agents_state(self) -> bool:
    method reset (line 387) | def reset(self) -> Observations:
    method step (line 395) | def step(self, action: Union[str, np.ndarray, int]) -> Observations:
    method render (line 401) | def render(self, mode: str = "rgb") -> Any:
    method reconfigure (line 422) | def reconfigure(
    method geodesic_distance (line 437) | def geodesic_distance(
    method action_space_shortest_path (line 465) | def action_space_shortest_path(
    method up_vector (line 487) | def up_vector(self) -> np.ndarray:
    method forward_vector (line 491) | def forward_vector(self) -> np.ndarray:
    method get_straight_shortest_path_points (line 494) | def get_straight_shortest_path_points(self, position_a, position_b):
    method sample_navigable_point (line 501) | def sample_navigable_point(self) -> List[float]:
    method is_navigable (line 504) | def is_navigable(self, point: List[float]) -> bool:
    method semantic_annotations (line 507) | def semantic_annotations(self):
    method _get_agent_config (line 539) | def _get_agent_config(self, agent_id: Optional[int] = None) -> Any:
    method get_agent_state (line 546) | def get_agent_state(self, agent_id: int = 0) -> habitat_sim.AgentState:
    method set_agent_state (line 549) | def set_agent_state(
    method get_observations_at (line 587) | def get_observations_at(
    method distance_to_closest_obstacle (line 617) | def distance_to_closest_obstacle(
    method island_radius (line 624) | def island_radius(self, position: Sequence[float]) -> float:
    method previous_step_collided (line 628) | def previous_step_collided(self):

FILE: habitat-lab/habitat/sims/habitat_simulator/sim_utilities.py
  function register_custom_wireframe_box_template (line 15) | def register_custom_wireframe_box_template(
  function add_wire_box (line 33) | def add_wire_box(
  function add_transformed_wire_box (line 58) | def add_transformed_wire_box(
  function add_viz_sphere (line 80) | def add_viz_sphere(
  function get_bb_corners (line 102) | def get_bb_corners(
  function get_ao_global_bb (line 121) | def get_ao_global_bb(
  function bb_ray_prescreen (line 138) | def bb_ray_prescreen(
  function snap_down (line 231) | def snap_down(
  function get_all_object_ids (line 294) | def get_all_object_ids(sim: habitat_sim.Simulator) -> Dict[int, str]:

FILE: habitat-lab/habitat/sims/pyrobot/__init__.py
  function _try_register_pyrobot (line 11) | def _try_register_pyrobot():

FILE: habitat-lab/habitat/sims/pyrobot/pyrobot.py
  function _locobot_base_action_space (line 27) | def _locobot_base_action_space():
  function _locobot_camera_action_space (line 36) | def _locobot_camera_action_space():
  function _resize_observation (line 46) | def _resize_observation(obs, observation_space, config):
  class PyRobotRGBSensor (line 72) | class PyRobotRGBSensor(RGBSensor):
    method __init__ (line 73) | def __init__(self, config):
    method _get_observation_space (line 76) | def _get_observation_space(self, *args: Any, **kwargs: Any):
    method get_observation (line 84) | def get_observation(self, robot_obs, *args: Any, **kwargs: Any):
  class PyRobotDepthSensor (line 97) | class PyRobotDepthSensor(DepthSensor):
    method __init__ (line 101) | def __init__(self, config):
    method _get_observation_space (line 111) | def _get_observation_space(self, *args: Any, **kwargs: Any):
    method get_observation (line 119) | def get_observation(self, robot_obs, *args: Any, **kwargs: Any):
  class PyRobotBumpSensor (line 143) | class PyRobotBumpSensor(BumpSensor):
    method _get_observation_space (line 144) | def _get_observation_space(self, *args: Any, **kwargs: Any):
    method get_observation (line 147) | def get_observation(self, robot_obs, *args: Any, **kwargs: Any):
  class PyRobot (line 152) | class PyRobot(Simulator):
    method __init__ (line 170) | def __init__(self, config: Config) -> None:
    method get_robot_observations (line 202) | def get_robot_observations(self):
    method sensor_suite (line 210) | def sensor_suite(self) -> SensorSuite:
    method base (line 214) | def base(self):
    method camera (line 218) | def camera(self):
    method _robot_action_space (line 221) | def _robot_action_space(self, robot_type, robot_config):
    method action_space (line 230) | def action_space(self) -> Space:
    method reset (line 233) | def reset(self):
    method step (line 241) | def step(self, action, action_params):
    method render (line 262) | def render(self, mode: str = "rgb") -> Any:
    method get_agent_state (line 272) | def get_agent_state(
    method seed (line 285) | def seed(self, seed: int) -> None:

FILE: habitat-lab/habitat/sims/registration.py
  function make_sim (line 13) | def make_sim(id_sim, **kwargs):

FILE: habitat-lab/habitat/tasks/eqa/__init__.py
  function _try_register_eqa_task (line 11) | def _try_register_eqa_task():

FILE: habitat-lab/habitat/tasks/eqa/eqa.py
  class QuestionData (line 21) | class QuestionData:
  class EQAEpisode (line 30) | class EQAEpisode(NavigationEpisode):
  class QuestionSensor (line 50) | class QuestionSensor(Sensor):
    method __init__ (line 51) | def __init__(self, dataset, *args: Any, **kwargs: Any):
    method _get_uuid (line 55) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method _get_sensor_type (line 58) | def _get_sensor_type(self, *args: Any, **kwargs: Any) -> SensorTypes:
    method get_observation (line 61) | def get_observation(
    method _get_observation_space (line 70) | def _get_observation_space(self, *args: Any, **kwargs: Any) -> Space:
  class CorrectAnswer (line 77) | class CorrectAnswer(Measure):
    method __init__ (line 80) | def __init__(self, dataset, *args: Any, **kwargs: Any):
    method _get_uuid (line 84) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method reset_metric (line 87) | def reset_metric(self, episode, *args: Any, **kwargs: Any):
    method update_metric (line 90) | def update_metric(self, *args: Any, **kwargs: Any):
  class EpisodeInfo (line 95) | class EpisodeInfo(Measure):
    method __init__ (line 98) | def __init__(self, sim, config, *args: Any, **kwargs: Any):
    method _get_uuid (line 104) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method reset_metric (line 107) | def reset_metric(self, episode, *args: Any, **kwargs: Any):
    method update_metric (line 110) | def update_metric(self, episode, action, *args: Any, **kwargs: Any):
  class AnswerAccuracy (line 115) | class AnswerAccuracy(Measure):
    method __init__ (line 118) | def __init__(self, dataset, *args: Any, **kwargs: Any):
    method _get_uuid (line 122) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method reset_metric (line 125) | def reset_metric(self, episode, *args: Any, **kwargs: Any):
    method update_metric (line 128) | def update_metric(
  class EQATask (line 144) | class EQATask(NavigationTask):
    method _check_episode_is_active (line 173) | def _check_episode_is_active(
  class AnswerAction (line 180) | class AnswerAction(Action):
    method __init__ (line 184) | def __init__(self, *args: Any, sim, dataset, **kwargs: Any) -> None:
    method reset (line 188) | def reset(self, task: EQATask, *args: Any, **kwargs: Any) -> None:
    method step (line 193) | def step(
    method action_space (line 204) | def action_space(self) -> spaces.Dict:

FILE: habitat-lab/habitat/tasks/nav/__init__.py
  function _try_register_nav_task (line 11) | def _try_register_nav_task():

FILE: habitat-lab/habitat/tasks/nav/nav.py
  function merge_sim_episode_config (line 61) | def merge_sim_episode_config(sim_config: Config, episode: Episode) -> Any:
  class NavigationGoal (line 80) | class NavigationGoal:
  class RoomGoal (line 88) | class RoomGoal(NavigationGoal):
  class NavigationEpisode (line 96) | class NavigationEpisode(Episode):
  class PointGoalSensor (line 123) | class PointGoalSensor(Sensor):
    method __init__ (line 146) | def __init__(
    method _get_uuid (line 159) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method _get_sensor_type (line 162) | def _get_sensor_type(self, *args: Any, **kwargs: Any):
    method _get_observation_space (line 165) | def _get_observation_space(self, *args: Any, **kwargs: Any):
    method _compute_pointgoal (line 175) | def _compute_pointgoal(
    method get_observation (line 209) | def get_observation(
  class ImageGoalSensor (line 226) | class ImageGoalSensor(Sensor):
    method __init__ (line 239) | def __init__(
    method _get_uuid (line 259) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method _get_sensor_type (line 262) | def _get_sensor_type(self, *args: Any, **kwargs: Any):
    method _get_observation_space (line 265) | def _get_observation_space(self, *args: Any, **kwargs: Any):
    method _get_pointnav_episode_image_goal (line 270) | def _get_pointnav_episode_image_goal(self, episode: NavigationEpisode):
    method get_observation (line 283) | def get_observation(
  class IntegratedPointGoalGPSAndCompassSensor (line 303) | class IntegratedPointGoalGPSAndCompassSensor(PointGoalSensor):
    method _get_uuid (line 326) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method get_observation (line 329) | def get_observation(
  class HeadingSensor (line 343) | class HeadingSensor(Sensor):
    method __init__ (line 353) | def __init__(
    method _get_uuid (line 359) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method _get_sensor_type (line 362) | def _get_sensor_type(self, *args: Any, **kwargs: Any):
    method _get_observation_space (line 365) | def _get_observation_space(self, *args: Any, **kwargs: Any):
    method _quat_to_xy_heading (line 368) | def _quat_to_xy_heading(self, quat):
    method get_observation (line 376) | def get_observation(
  class EpisodicCompassSensor (line 389) | class EpisodicCompassSensor(HeadingSensor):
    method _get_uuid (line 395) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method get_observation (line 398) | def get_observation(
  class EpisodicGPSSensor (line 414) | class EpisodicGPSSensor(Sensor):
    method __init__ (line 426) | def __init__(
    method _get_uuid (line 435) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method _get_sensor_type (line 438) | def _get_sensor_type(self, *args: Any, **kwargs: Any):
    method _get_observation_space (line 441) | def _get_observation_space(self, *args: Any, **kwargs: Any):
    method get_observation (line 450) | def get_observation(
  class ProximitySensor (line 472) | class ProximitySensor(Sensor):
    method __init__ (line 481) | def __init__(self, sim, config, *args: Any, **kwargs: Any):
    method _get_uuid (line 488) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method _get_sensor_type (line 491) | def _get_sensor_type(self, *args: Any, **kwargs: Any):
    method _get_observation_space (line 494) | def _get_observation_space(self, *args: Any, **kwargs: Any):
    method get_observation (line 502) | def get_observation(
  class Success (line 518) | class Success(Measure):
    method __init__ (line 526) | def __init__(
    method _get_uuid (line 534) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method reset_metric (line 537) | def reset_metric(self, episode, task, *args: Any, **kwargs: Any):
    method update_metric (line 543) | def update_metric(
  class SPL (line 561) | class SPL(Measure):
    method __init__ (line 571) | def __init__(
    method _get_uuid (line 585) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method reset_metric (line 588) | def reset_metric(self, episode, task, *args: Any, **kwargs: Any):
    method _euclidean_distance (line 602) | def _euclidean_distance(self, position_a, position_b):
    method update_metric (line 605) | def update_metric(
  class SoftSPL (line 626) | class SoftSPL(SPL):
    method _get_uuid (line 633) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method reset_metric (line 636) | def reset_metric(self, episode, task, *args: Any, **kwargs: Any):
    method update_metric (line 648) | def update_metric(self, episode, task, *args: Any, **kwargs: Any):
  class Collisions (line 673) | class Collisions(Measure):
    method __init__ (line 674) | def __init__(self, sim, config, *args: Any, **kwargs: Any):
    method _get_uuid (line 680) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method reset_metric (line 683) | def reset_metric(self, episode, *args: Any, **kwargs: Any):
    method update_metric (line 686) | def update_metric(self, episode, action, *args: Any, **kwargs: Any):
  class TopDownMap (line 696) | class TopDownMap(Measure):
    method __init__ (line 699) | def __init__(
    method _get_uuid (line 722) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method get_original_map (line 725) | def get_original_map(self):
    method _draw_point (line 739) | def _draw_point(self, position, point_type):
    method _draw_goals_view_points (line 751) | def _draw_goals_view_points(self, episode):
    method _draw_goals_positions (line 765) | def _draw_goals_positions(self, episode):
    method _draw_goals_aabb (line 777) | def _draw_goals_aabb(self, episode):
    method _draw_shortest_path (line 828) | def _draw_shortest_path(
    method _is_on_same_floor (line 853) | def _is_on_same_floor(
    method reset_metric (line 860) | def reset_metric(self, episode, *args: Any, **kwargs: Any):
    method update_metric (line 887) | def update_metric(self, episode, action, *args: Any, **kwargs: Any):
    method get_polar_angle (line 900) | def get_polar_angle(self):
    method update_map (line 913) | def update_map(self, agent_position):
    method update_fog_of_war_mask (line 940) | def update_fog_of_war_mask(self, agent_position):
  class DistanceToGoal (line 956) | class DistanceToGoal(Measure):
    method __init__ (line 961) | def __init__(
    method _get_uuid (line 973) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method reset_metric (line 976) | def reset_metric(self, episode, *args: Any, **kwargs: Any):
    method update_metric (line 987) | def update_metric(
  class MoveForwardAction (line 1019) | class MoveForwardAction(SimulatorTaskAction):
    method step (line 1022) | def step(self, *args: Any, **kwargs: Any):
  class TurnLeftAction (line 1030) | class TurnLeftAction(SimulatorTaskAction):
    method step (line 1031) | def step(self, *args: Any, **kwargs: Any):
  class TurnRightAction (line 1039) | class TurnRightAction(SimulatorTaskAction):
    method step (line 1040) | def step(self, *args: Any, **kwargs: Any):
  class TurnRightAction2 (line 1047) | class TurnRightAction2(SimulatorTaskAction):
    method step (line 1048) | def step(self, *args: Any, **kwargs: Any):
  class StopAction (line 1055) | class StopAction(SimulatorTaskAction):
    method reset (line 1058) | def reset(self, task: EmbodiedTask, *args: Any, **kwargs: Any):
    method step (line 1061) | def step(self, task: EmbodiedTask, *args: Any, **kwargs: Any):
  class LookUpAction (line 1070) | class LookUpAction(SimulatorTaskAction):
    method step (line 1071) | def step(self, *args: Any, **kwargs: Any):
  class LookDownAction (line 1079) | class LookDownAction(SimulatorTaskAction):
    method step (line 1080) | def step(self, *args: Any, **kwargs: Any):
  class TeleportAction (line 1088) | class TeleportAction(SimulatorTaskAction):
    method _get_uuid (line 1094) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method step (line 1097) | def step(
    method action_space (line 1119) | def action_space(self) -> spaces.Dict:
  class VelocityAction (line 1137) | class VelocityAction(SimulatorTaskAction):
    method __init__ (line 1140) | def __init__(self, *args: Any, **kwargs: Any):
    method action_space (line 1156) | def action_space(self):
    method reset (line 1172) | def reset(self, task: EmbodiedTask, *args: Any, **kwargs: Any):
    method step (line 1175) | def step(
  class NavigationTask (line 1286) | class NavigationTask(EmbodiedTask):
    method __init__ (line 1287) | def __init__(
    method overwrite_sim_config (line 1292) | def overwrite_sim_config(self, sim_config: Any, episode: Episode) -> Any:
    method _check_episode_is_active (line 1295) | def _check_episode_is_active(self, *args: Any, **kwargs: Any) -> bool:

FILE: habitat-lab/habitat/tasks/nav/object_nav_task.py
  class ObjectGoalNavEpisode (line 32) | class ObjectGoalNavEpisode(NavigationEpisode):
    method goals_key (line 40) | def goals_key(self) -> str:
  class ObjectViewLocation (line 46) | class ObjectViewLocation:
  class ObjectGoal (line 69) | class ObjectGoal(NavigationGoal):
  class ObjectGoalSensor (line 99) | class ObjectGoalSensor(Sensor):
    method __init__ (line 116) | def __init__(
    method _get_uuid (line 128) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method _get_sensor_type (line 131) | def _get_sensor_type(self, *args: Any, **kwargs: Any):
    method _get_observation_space (line 134) | def _get_observation_space(self, *args: Any, **kwargs: Any):
    method get_observation (line 146) | def get_observation(
  class ObjectNavigationTask (line 181) | class ObjectNavigationTask(NavigationTask):

FILE: habitat-lab/habitat/tasks/nav/shortest_path_follower.py
  function action_to_one_hot (line 17) | def action_to_one_hot(action: int) -> np.ndarray:
  class ShortestPathFollower (line 23) | class ShortestPathFollower:
    method __init__ (line 38) | def __init__(
    method _build_follower (line 53) | def _build_follower(self):
    method _get_return_value (line 65) | def _get_return_value(self, action) -> Union[int, np.ndarray]:
    method get_next_action (line 71) | def get_next_action(
    method mode (line 88) | def mode(self):
    method mode (line 93) | def mode(self, new_mode: str):

FILE: habitat-lab/habitat/tasks/rearrange/__init__.py
  function _try_register_rearrange_task (line 12) | def _try_register_rearrange_task():

FILE: habitat-lab/habitat/tasks/rearrange/actions.py
  class EmptyAction (line 31) | class EmptyAction(SimulatorTaskAction):
    method action_space (line 37) | def action_space(self):
    method step (line 49) | def step(self, *args, **kwargs):
  class ArmAction (line 54) | class ArmAction(SimulatorTaskAction):
    method __init__ (line 57) | def __init__(self, *args, config, sim: RearrangeSim, **kwargs):
    method reset (line 77) | def reset(self, *args, **kwargs):
    method action_space (line 83) | def action_space(self):
    method step (line 91) | def step(self, arm_action, grip_action=None, *args, **kwargs):
  class ArmRelPosAction (line 100) | class ArmRelPosAction(SimulatorTaskAction):
    method action_space (line 107) | def action_space(self):
    method step (line 115) | def step(self, delta_pos, should_step=True, *args, **kwargs):
  class ArmRelPosKinematicAction (line 131) | class ArmRelPosKinematicAction(SimulatorTaskAction):
    method action_space (line 138) | def action_space(self):
    method step (line 146) | def step(self, delta_pos, should_step=True, *args, **kwargs):
  class ArmAbsPosAction (line 162) | class ArmAbsPosAction(SimulatorTaskAction):
    method action_space (line 169) | def action_space(self):
    method step (line 177) | def step(self, set_pos, should_step=True, *args, **kwargs):
  class ArmAbsPosKinematicAction (line 189) | class ArmAbsPosKinematicAction(SimulatorTaskAction):
    method action_space (line 196) | def action_space(self):
    method step (line 204) | def step(self, set_pos, should_step=True, *args, **kwargs):
  class BaseVelAction (line 216) | class BaseVelAction(SimulatorTaskAction):
    method __init__ (line 223) | def __init__(self, *args, config, sim: RearrangeSim, **kwargs):
    method action_space (line 235) | def action_space(self):
    method _capture_robot_state (line 239) | def _capture_robot_state(self, sim):
    method _set_robot_state (line 246) | def _set_robot_state(self, sim: RearrangeSim, set_dat):
    method reset (line 251) | def reset(self, *args, **kwargs):
    method update_base (line 255) | def update_base(self):
    method step (line 290) | def step(self, base_vel, should_step=True, *args, **kwargs):
  class ArmEEAction (line 316) | class ArmEEAction(SimulatorTaskAction):
    method __init__ (line 319) | def __init__(self, *args, config, sim: RearrangeSim, **kwargs):
    method reset (line 331) | def reset(self, *args, **kwargs):
    method action_space (line 340) | def action_space(self):
    method apply_ee_constraints (line 343) | def apply_ee_constraints(self):
    method set_desired_ee_pos (line 350) | def set_desired_ee_pos(self, ee_pos: np.ndarray) -> None:
    method step (line 366) | def step(self, ee_pos, should_step=True, **kwargs):

FILE: habitat-lab/habitat/tasks/rearrange/grip_actions.py
  class GripSimulatorTaskAction (line 20) | class GripSimulatorTaskAction(SimulatorTaskAction):
    method __init__ (line 21) | def __init__(self, *args, config, sim: RearrangeSim, **kwargs):
    method requires_action (line 26) | def requires_action(self):
  class MagicGraspAction (line 31) | class MagicGraspAction(GripSimulatorTaskAction):
    method action_space (line 33) | def action_space(self):
    method _grasp (line 36) | def _grasp(self):
    method _ungrasp (line 70) | def _ungrasp(self):
    method step (line 73) | def step(self, grip_action, should_step=True, *args, **kwargs):
  class SuctionGraspAction (line 83) | class SuctionGraspAction(GripSimulatorTaskAction):
    method __init__ (line 88) | def __init__(self, *args, config, sim: RearrangeSim, **kwargs):
    method action_space (line 93) | def action_space(self):
    method _ungrasp (line 96) | def _ungrasp(self):
    method step (line 99) | def step(self, _, should_step=True, *args, **kwargs):

FILE: habitat-lab/habitat/tasks/rearrange/marker_info.py
  class MarkerInfo (line 11) | class MarkerInfo:
    method __init__ (line 18) | def __init__(self, offset_position, link_node, ao_parent, link_id):
    method set_targ_js (line 29) | def set_targ_js(self, js):
    method get_targ_js (line 32) | def get_targ_js(self):
    method get_targ_js_vel (line 35) | def get_targ_js_vel(self):
    method update (line 38) | def update(self):
    method get_current_position (line 42) | def get_current_position(self) -> np.ndarray:
    method get_current_transform (line 45) | def get_current_transform(self) -> mn.Matrix4:

FILE: habitat-lab/habitat/tasks/rearrange/rearrange_grasp_manager.py
  class RearrangeGraspManager (line 24) | class RearrangeGraspManager:
    method __init__ (line 29) | def __init__(
    method reconfigure (line 45) | def reconfigure(self) -> None:
    method reset (line 53) | def reset(self) -> None:
    method is_violating_hold_constraint (line 64) | def is_violating_hold_constraint(self) -> bool:
    method is_grasped (line 86) | def is_grasped(self) -> bool:
    method update (line 93) | def update(self) -> None:
    method desnap (line 110) | def desnap(self, force=False) -> None:
    method snap_idx (line 143) | def snap_idx(self) -> int:
    method snapped_marker_id (line 148) | def snapped_marker_id(self) -> str:
    method snap_rigid_obj (line 153) | def snap_rigid_obj(self) -> ManagedRigidObject:
    method snap_to_marker (line 159) | def snap_to_marker(self, marker_name: str) -> None:
    method create_hold_constraint (line 186) | def create_hold_constraint(
    method snap_to_obj (line 213) | def snap_to_obj(self, snap_obj_id: int, force: bool = True) -> None:

FILE: habitat-lab/habitat/tasks/rearrange/rearrange_sensors.py
  class TargetPointGoalGPSAndCompassSensor (line 19) | class TargetPointGoalGPSAndCompassSensor(PointGoalSensor):
    method __init__ (line 22) | def __init__(self, *args, task, **kwargs):
    method get_observation (line 27) | def get_observation(self, observations, episode, *args, **kwargs):
  class MultiObjSensor (line 38) | class MultiObjSensor(PointGoalSensor):
    method __init__ (line 39) | def __init__(self, *args, task, **kwargs):
    method _get_observation_space (line 44) | def _get_observation_space(self, *args, **kwargs):
  class AbsObjectGoalPositionSensor (line 55) | class AbsObjectGoalPositionSensor(MultiObjSensor):
    method get_observation (line 62) | def get_observation(self, observations, episode, *args, **kwargs):
  class ObjectGoalPositionSensor (line 72) | class ObjectGoalPositionSensor(MultiObjSensor):
    method _get_observation_space (line 79) | def _get_observation_space(self, *args, **kwargs):
    method get_observation (line 87) | def get_observation(self, observations, episode, *args, **kwargs):
  class TargetStartSensor (line 102) | class TargetStartSensor(MultiObjSensor):
    method _get_observation_space (line 109) | def _get_observation_space(self, *args, **kwargs):
    method get_observation (line 117) | def get_observation(self, *args, observations, episode, **kwargs):
  class AbsTargetStartSensor (line 129) | class AbsTargetStartSensor(MultiObjSensor):
    method _get_observation_space (line 136) | def _get_observation_space(self, *args, **kwargs):
    method get_observation (line 145) | def get_observation(self, observations, episode, *args, **kwargs):
  class GoalSensor (line 151) | class GoalSensor(MultiObjSensor):
    method get_observation (line 158) | def get_observation(self, observations, episode, *args, **kwargs):
  class AbsGoalSensor (line 169) | class AbsGoalSensor(MultiObjSensor):
    method get_observation (line 172) | def get_observation(self, *args, observations, episode, **kwargs):
  class JointSensor (line 178) | class JointSensor(Sensor):
    method __init__ (line 179) | def __init__(self, sim, config, *args, **kwargs):
    method _get_uuid (line 183) | def _get_uuid(self, *args, **kwargs):
    method _get_sensor_type (line 186) | def _get_sensor_type(self, *args, **kwargs):
    method _get_observation_space (line 189) | def _get_observation_space(self, *args, config, **kwargs):
    method get_observation (line 197) | def get_observation(self, observations, episode, *args, **kwargs):
  class JointVelocitySensor (line 203) | class JointVelocitySensor(Sensor):
    method __init__ (line 204) | def __init__(self, sim, config, *args, **kwargs):
    method _get_uuid (line 208) | def _get_uuid(self, *args, **kwargs):
    method _get_sensor_type (line 211) | def _get_sensor_type(self, *args, **kwargs):
    method _get_observation_space (line 214) | def _get_observation_space(self, *args, config, **kwargs):
    method get_observation (line 222) | def get_observation(self, observations, episode, *args, **kwargs):
  class EEPositionSensor (line 228) | class EEPositionSensor(Sensor):
    method __init__ (line 231) | def __init__(self, sim, config, *args, **kwargs):
    method _get_uuid (line 236) | def _get_uuid(*args, **kwargs):
    method _get_sensor_type (line 239) | def _get_sensor_type(self, *args, **kwargs):
    method _get_observation_space (line 242) | def _get_observation_space(self, *args, **kwargs):
    method get_observation (line 250) | def get_observation(self, observations, episode, *args, **kwargs):
  class RelativeRestingPositionSensor (line 259) | class RelativeRestingPositionSensor(Sensor):
    method _get_uuid (line 262) | def _get_uuid(self, *args, **kwargs):
    method __init__ (line 265) | def __init__(self, sim, config, *args, **kwargs):
    method _get_sensor_type (line 269) | def _get_sensor_type(self, *args, **kwargs):
    method _get_observation_space (line 272) | def _get_observation_space(self, *args, **kwargs):
    method get_observation (line 280) | def get_observation(self, observations, episode, task, *args, **kwargs):
  class RestingPositionSensor (line 291) | class RestingPositionSensor(Sensor):
    method _get_uuid (line 294) | def _get_uuid(self, *args, **kwargs):
    method __init__ (line 297) | def __init__(self, sim, config, *args, **kwargs):
    method _get_sensor_type (line 301) | def _get_sensor_type(self, *args, **kwargs):
    method _get_observation_space (line 304) | def _get_observation_space(self, *args, **kwargs):
    method get_observation (line 312) | def get_observation(self, observations, episode, task, *args, **kwargs):
  class IsHoldingSensor (line 317) | class IsHoldingSensor(Sensor):
    method __init__ (line 318) | def __init__(self, sim, config, *args, **kwargs):
    method _get_uuid (line 322) | def _get_uuid(self, *args, **kwargs):
    method _get_sensor_type (line 325) | def _get_sensor_type(self, *args, **kwargs):
    method _get_observation_space (line 328) | def _get_observation_space(self, *args, **kwargs):
    method get_observation (line 331) | def get_observation(self, observations, episode, *args, **kwargs):
  class ObjectToGoalDistance (line 336) | class ObjectToGoalDistance(Measure):
    method __init__ (line 339) | def __init__(self, sim, config, *args, **kwargs):
    method _get_uuid (line 345) | def _get_uuid(*args, **kwargs):
    method reset_metric (line 348) | def reset_metric(self, *args, episode, **kwargs):
    method update_metric (line 351) | def update_metric(self, *args, episode, **kwargs):
  class EndEffectorToObjectDistance (line 360) | class EndEffectorToObjectDistance(Measure):
    method __init__ (line 367) | def __init__(self, sim, config, *args, **kwargs):
    method _get_uuid (line 373) | def _get_uuid(*args, **kwargs):
    method reset_metric (line 376) | def reset_metric(self, *args, episode, **kwargs):
    method update_metric (line 379) | def update_metric(self, *args, episode, **kwargs):
  class EndEffectorToRestDistance (line 392) | class EndEffectorToRestDistance(Measure):
    method __init__ (line 399) | def __init__(self, sim, config, *args, **kwargs):
    method _get_uuid (line 405) | def _get_uuid(*args, **kwargs):
    method reset_metric (line 408) | def reset_metric(self, *args, episode, **kwargs):
    method update_metric (line 411) | def update_metric(self, *args, episode, task, observations, **kwargs):
  class ReturnToRestDistance (line 419) | class ReturnToRestDistance(Measure):
    method __init__ (line 426) | def __init__(self, sim, config, *args, **kwargs):
    method _get_uuid (line 432) | def _get_uuid(*args, **kwargs):
    method reset_metric (line 435) | def reset_metric(self, *args, episode, **kwargs):
    method update_metric (line 438) | def update_metric(self, *args, episode, task, observations, **kwargs):
  class DummyMeasure (line 459) | class DummyMeasure(Measure):
    method _get_uuid (line 463) | def _get_uuid(*args, **kwargs):
    method reset_metric (line 466) | def reset_metric(self, *args, episode, **kwargs):
    method update_metric (line 469) | def update_metric(self, *args, episode, **kwargs):
  class RobotCollisions (line 474) | class RobotCollisions(Measure):
    method __init__ (line 477) | def __init__(self, *args, sim, config, task, **kwargs):
    method _get_uuid (line 484) | def _get_uuid(*args, **kwargs):
    method reset_metric (line 487) | def reset_metric(self, *args, episode, task, observations, **kwargs):
    method update_metric (line 497) | def update_metric(self, *args, episode, task, observations, **kwargs):
  class RobotForce (line 509) | class RobotForce(Measure):
    method __init__ (line 512) | def __init__(self, *args, sim, config, task, **kwargs):
    method _get_uuid (line 519) | def _get_uuid(*args, **kwargs):
    method reset_metric (line 522) | def reset_metric(self, *args, episode, task, observations, **kwargs):
    method add_force (line 536) | def add_force(self):
    method update_metric (line 539) | def update_metric(self, *args, episode, task, observations, **kwargs):
  class ForceTerminate (line 563) | class ForceTerminate(Measure):
    method __init__ (line 566) | def __init__(self, *args, sim, config, task, **kwargs):
    method _get_uuid (line 573) | def _get_uuid(*args, **kwargs):
    method reset_metric (line 576) | def reset_metric(self, *args, episode, task, observations, **kwargs):
    method update_metric (line 592) | def update_metric(self, *args, episode, task, observations, **kwargs):
  class RearrangeReward (line 606) | class RearrangeReward(Measure):
    method __init__ (line 607) | def __init__(self, *args, sim, config, task, **kwargs):
    method reset_metric (line 614) | def reset_metric(self, *args, episode, task, observations, **kwargs):
    method update_metric (line 631) | def update_metric(self, *args, episode, task, observations, **kwargs):
    method _get_coll_reward (line 647) | def _get_coll_reward(self):

FILE: habitat-lab/habitat/tasks/rearrange/rearrange_sim.py
  class RearrangeSim (line 32) | class RearrangeSim(HabitatSim):
    method __init__ (line 33) | def __init__(self, config: Config):
    method _get_target_trans (line 83) | def _get_target_trans(self):
    method _try_acquire_context (line 98) | def _try_acquire_context(self):
    method sleep_all_objects (line 102) | def sleep_all_objects(self):
    method add_markers (line 113) | def add_markers(self, ep_info: Config):
    method get_marker (line 134) | def get_marker(self, name: str) -> MarkerInfo:
    method get_all_markers (line 137) | def get_all_markers(self):
    method _update_markers (line 140) | def _update_markers(self) -> None:
    method ik_helper (line 145) | def ik_helper(self):
    method reconfigure (line 152) | def reconfigure(self, config: Config):
    method _recompute_navmesh (line 264) | def _recompute_navmesh(self):
    method _clear_objects (line 289) | def _clear_objects(self, should_add_objects: bool) -> None:
    method _set_ao_states_from_ep (line 301) | def _set_ao_states_from_ep(self, ep_info: Config) -> None:
    method _add_objs (line 317) | def _add_objs(self, ep_info: Config, should_add_objects: bool) -> None:
    method _create_obj_viz (line 363) | def _create_obj_viz(self, ep_info: Config) -> None:
    method capture_state (line 380) | def capture_state(self, with_robot_js=False) -> Dict[str, Any]:
    method set_state (line 416) | def set_state(self, state: Dict[str, Any], set_hold=False) -> None:
    method step (line 454) | def step(self, action: Union[str, int]) -> Observations:
    method visualize_position (line 520) | def visualize_position(
    method internal_step (line 555) | def internal_step(self, dt: Union[int, float]) -> None:
    method get_targets (line 571) | def get_targets(self) -> Tuple[np.ndarray, np.ndarray]:
    method get_n_targets (line 586) | def get_n_targets(self) -> int:
    method get_target_objs_start (line 590) | def get_target_objs_start(self) -> np.ndarray:
    method get_scene_pos (line 594) | def get_scene_pos(self) -> np.ndarray:

FILE: habitat-lab/habitat/tasks/rearrange/rearrange_task.py
  function merge_sim_episode_with_object_config (line 19) | def merge_sim_episode_with_object_config(sim_config, episode):
  class RearrangeTask (line 27) | class RearrangeTask(NavigationTask):
    method overwrite_sim_config (line 33) | def overwrite_sim_config(self, sim_config, episode):
    method __init__ (line 36) | def __init__(self, *args, sim, dataset=None, **kwargs) -> None:
    method targ_idx (line 48) | def targ_idx(self):
    method abs_targ_idx (line 52) | def abs_targ_idx(self):
    method desired_resting (line 58) | def desired_resting(self):
    method set_args (line 61) | def set_args(self, **kwargs):
    method set_sim_reset (line 64) | def set_sim_reset(self, sim_reset):
    method reset (line 67) | def reset(self, episode: Episode):
    method step (line 93) | def step(self, action: Dict[str, Any], episode: Episode):
    method _check_episode_is_active (line 100) | def _check_episode_is_active(
    method get_coll_forces (line 120) | def get_coll_forces(self):
    method get_cur_collision_info (line 155) | def get_cur_collision_info(self) -> CollisionDetails:
    method get_n_targets (line 162) | def get_n_targets(self) -> int:

FILE: habitat-lab/habitat/tasks/rearrange/sub_tasks/pick_sensors.py
  class RearrangePickReward (line 20) | class RearrangePickReward(RearrangeReward):
    method __init__ (line 23) | def __init__(self, *args, sim, config, task, **kwargs):
    method _get_uuid (line 31) | def _get_uuid(*args, **kwargs):
    method reset_metric (line 34) | def reset_metric(self, *args, episode, task, observations, **kwargs):
    method update_metric (line 54) | def update_metric(self, *args, episode, task, observations, **kwargs):
    method _get_coll_reward (line 122) | def _get_coll_reward(self):
  class RearrangePickSuccess (line 136) | class RearrangePickSuccess(Measure):
    method __init__ (line 139) | def __init__(self, sim, config, *args, **kwargs):
    method _get_uuid (line 146) | def _get_uuid(*args, **kwargs):
    method reset_metric (line 149) | def reset_metric(self, *args, episode, task, observations, **kwargs):
    method update_metric (line 162) | def update_metric(self, *args, episode, task, observations, **kwargs):

FILE: habitat-lab/habitat/tasks/rearrange/sub_tasks/pick_task.py
  class RearrangePickTaskV1 (line 19) | class RearrangePickTaskV1(RearrangeTask):
    method __init__ (line 24) | def __init__(self, *args, config, dataset=None, **kwargs):
    method set_args (line 42) | def set_args(self, obj, **kwargs):
    method _get_targ_pos (line 45) | def _get_targ_pos(self, sim):
    method _gen_start_pos (line 48) | def _gen_start_pos(self, sim, is_easy_init):
    method _should_prevent_grip (line 124) | def _should_prevent_grip(self, action_args):
    method step (line 131) | def step(self, action, episode):
    method reset (line 141) | def reset(self, episode: Episode):

FILE: habitat-lab/habitat/tasks/rearrange/utils.py
  function make_render_only (line 25) | def make_render_only(obj, sim):
  function make_border_red (line 30) | def make_border_red(img):
  function coll_name_matches (line 40) | def coll_name_matches(coll, name):
  function coll_link_name_matches (line 44) | def coll_link_name_matches(coll, name):
  function get_match_link (line 48) | def get_match_link(coll, name):
  function swap_axes (line 56) | def swap_axes(x):
  class CollisionDetails (line 62) | class CollisionDetails:
    method total_collisions (line 70) | def total_collisions(self):
    method __add__ (line 77) | def __add__(self, other):
  function rearrange_collision (line 87) | def rearrange_collision(
  function get_nav_mesh_settings (line 165) | def get_nav_mesh_settings(agent_config):
  function get_nav_mesh_settings_from_height (line 169) | def get_nav_mesh_settings_from_height(height):
  function convert_legacy_cfg (line 178) | def convert_legacy_cfg(obj_list):
  function get_aabb (line 209) | def get_aabb(obj_id, sim, transformed=False):
  function euler_to_quat (line 222) | def euler_to_quat(rpy):
  function allowed_region_to_bb (line 228) | def allowed_region_to_bb(allowed_region):
  class CacheHelper (line 237) | class CacheHelper:
    method __init__ (line 238) | def __init__(
    method exists (line 249) | def exists(self):
    method load (line 252) | def load(self, load_depth=0):
    method save (line 273) | def save(self, val):
  function reshape_obs_space (line 280) | def reshape_obs_space(obs_space, new_shape):
  function is_pb_installed (line 296) | def is_pb_installed():
  class IkHelper (line 300) | class IkHelper:
    method __init__ (line 301) | def __init__(self, only_arm_urdf, arm_start):
    method set_arm_state (line 334) | def set_arm_state(self, joint_pos, joint_vel=None):
    method calc_fk (line 346) | def calc_fk(self, js):
    method get_joint_limits (line 357) | def get_joint_limits(self):
    method calc_ik (line 371) | def calc_ik(self, targ_ee: np.ndarray):

FILE: habitat-lab/habitat/tasks/registration.py
  function make_task (line 15) | def make_task(id_task, **kwargs):

FILE: habitat-lab/habitat/tasks/utils.py
  function quaternion_to_rotation (line 11) | def quaternion_to_rotation(q_r, q_i, q_j, q_k):
  function cartesian_to_polar (line 39) | def cartesian_to_polar(x, y):
  function compute_pixel_coverage (line 45) | def compute_pixel_coverage(instance_seg, object_id):
  function get_angle (line 51) | def get_angle(x, y):

FILE: habitat-lab/habitat/tasks/vln/__init__.py
  function _try_register_vln_task (line 11) | def _try_register_vln_task():

FILE: habitat-lab/habitat/tasks/vln/vln.py
  class InstructionData (line 23) | class InstructionData:
  class VLNEpisode (line 29) | class VLNEpisode(NavigationEpisode):
  class InstructionSensor (line 57) | class InstructionSensor(Sensor):
    method __init__ (line 58) | def __init__(self, **kwargs):
    method _get_uuid (line 62) | def _get_uuid(self, *args: Any, **kwargs: Any) -> str:
    method _get_observation (line 65) | def _get_observation(
    method get_observation (line 77) | def get_observation(self, **kwargs):
  class VLNTask (line 82) | class VLNTask(NavigationTask):
    method __init__ (line 91) | def __init__(self, **kwargs) -> None:

FILE: habitat-lab/habitat/utils/common.py
  function check_make_dir (line 14) | def check_make_dir(directory_path: str) -> bool:
  function cull_string_list_by_substrings (line 33) | def cull_string_list_by_substrings(

FILE: habitat-lab/habitat/utils/geometry_utils.py
  function angle_between_quaternions (line 15) | def angle_between_quaternions(
  function quaternion_from_two_vectors (line 27) | def quaternion_from_two_vectors(
  function quaternion_to_list (line 50) | def quaternion_to_list(q: quaternion.quaternion):
  function quaternion_from_coeff (line 54) | def quaternion_from_coeff(coeffs: List[float]) -> quaternion.quaternion:
  function quaternion_rotate_vector (line 62) | def quaternion_rotate_vector(
  function agent_state_target2ref (line 77) | def agent_state_target2ref(

FILE: habitat-lab/habitat/utils/pickle5_multiprocessing.py
  class ForkingPickler5 (line 28) | class ForkingPickler5(pickle.Pickler):
    method dumps (line 33) | def dumps(cls, obj, protocol: int = -1):
    method __init__ (line 38) | def __init__(self, file, protocol: int = -1, **kwargs):
  class ConnectionWrapper (line 50) | class ConnectionWrapper:
    method __init__ (line 54) | def __init__(self, conn: Connection):
    method send (line 57) | def send(self, obj):
    method recv (line 64) | def recv(self):
    method __getattr__ (line 70) | def __getattr__(self, name):

FILE: habitat-lab/habitat/utils/profiling_wrapper.py
  function configure (line 24) | def configure(capture_start_step=-1, num_steps_to_capture=-1):
  function on_start_step (line 30) | def on_start_step():
  function range_push (line 36) | def range_push(msg: str):
  function range_pop (line 42) | def range_pop():
  class RangeContext (line 48) | class RangeContext(ContextDecorator):
    method __init__ (line 53) | def __init__(self, msg: str):
    method __enter__ (line 56) | def __enter__(self):
    method __exit__ (line 60) | def __exit__(self, *exc):

FILE: habitat-lab/habitat/utils/test_utils.py
  function sample_non_stop_action (line 10) | def sample_non_stop_action(action_space, num_samples=1):

FILE: habitat-lab/habitat/utils/visualizations/fog_of_war.py
  function bresenham_supercover_line (line 14) | def bresenham_supercover_line(pt1, pt2):
  function draw_fog_of_war_line (line 82) | def draw_fog_of_war_line(top_down_map, fog_of_war_mask, pt1, pt2):
  function _draw_loop (line 101) | def _draw_loop(
  function reveal_fog_of_war (line 122) | def reveal_fog_of_war(

FILE: habitat-lab/habitat/utils/visualizations/maps.py
  function draw_agent (line 57) | def draw_agent(
  function pointnav_draw_target_birdseye_view (line 93) | def pointnav_draw_target_birdseye_view(
  function to_grid (line 188) | def to_grid(
  function from_grid (line 219) | def from_grid(
  function _outline_border (line 251) | def _outline_border(top_down_map):
  function calculate_meters_per_pixel (line 273) | def calculate_meters_per_pixel(
  function get_topdown_map (line 292) | def get_topdown_map(
  function get_topdown_map_from_sim (line 328) | def get_topdown_map_from_sim(
  function colorize_topdown_map (line 349) | def colorize_topdown_map(
  function draw_path (line 380) | def draw_path(
  function colorize_draw_agent_and_fit_to_height (line 404) | def colorize_draw_agent_and_fit_to_height(

FILE: habitat-lab/habitat/utils/visualizations/utils.py
  function paste_overlapping_image (line 22) | def paste_overlapping_image(
  function images_to_video (line 100) | def images_to_video(
  function draw_collision (line 150) | def draw_collision(view: np.ndarray, alpha: float = 0.4) -> np.ndarray:
  function tile_images (line 167) | def tile_images(render_obs_images: List[np.ndarray]) -> np.ndarray:
  function observations_to_image (line 206) | def observations_to_image(observation: Dict, info: Dict) -> np.ndarray:
  function append_text_to_image (line 264) | def append_text_to_image(image: np.ndarray, text: str):

FILE: habitat-lab/habitat_baselines/agents/benchmark_gym.py
  function compress_action (line 24) | def compress_action(action):
  class BenchmarkGym (line 39) | class BenchmarkGym:
    method __init__ (line 40) | def __init__(
    method _env (line 63) | def _env(self):
    method evaluate (line 66) | def evaluate(

FILE: habitat-lab/habitat_baselines/agents/mp_agents.py
  function get_noop_arm_action (line 23) | def get_noop_arm_action(sim, task):
  class ParameterizedAgent (line 54) | class ParameterizedAgent(habitat.Agent):
    method __init__ (line 55) | def __init__(
    method _end_episode (line 73) | def _end_episode(self):
    method _set_info (line 76) | def _set_info(self, k: str, v: Any) -> None:
    method _has_info (line 79) | def _has_info(self, k: str) -> bool:
    method get_and_clear_info (line 82) | def get_and_clear_info(self) -> Dict[str, Any]:
    method reset (line 87) | def reset(self) -> None:
    method set_args (line 91) | def set_args(self, **kwargs) -> None:
    method _log (line 94) | def _log(self, txt):
    method act (line 98) | def act(self, observations: Observations) -> Dict[str, Any]:
    method should_term (line 103) | def should_term(self, observations: Observations) -> bool:
  class AgentComposition (line 107) | class AgentComposition(ParameterizedAgent):
    method __init__ (line 108) | def __init__(
    method _set_info (line 123) | def _set_info(self, k, v):
    method _has_info (line 126) | def _has_info(self, k):
    method get_and_clear_info (line 129) | def get_and_clear_info(self):
    method set_args (line 135) | def set_args(self, **kwargs):
    method _is_done_with_skills (line 143) | def _is_done_with_skills(self):
    method reset (line 146) | def reset(self):
    method act (line 151) | def act(self, observations):
    method should_term (line 158) | def should_term(self, observations):
  class ArmTargModule (line 170) | class ArmTargModule(ParameterizedAgent):
    method __init__ (line 173) | def __init__(
    method wait_after (line 192) | def wait_after(self) -> int:
    method timeout (line 196) | def timeout(self) -> int:
    method set_args (line 199) | def set_args(self, **kwargs) -> None:
    method reset (line 203) | def reset(self) -> None:
    method _add_debug_viz_point (line 215) | def _add_debug_viz_point(self, pos):
    method act (line 222) | def act(self, observations: Observations) -> Dict[str, Any]:
    method _get_plan_ac (line 253) | def _get_plan_ac(self, observations) -> np.ndarray:
    method _internal_should_term (line 266) | def _internal_should_term(self, observations):
    method should_term (line 269) | def should_term(self, observations: Observations) -> bool:
    method _get_force_set_ee (line 293) | def _get_force_set_ee(self):
    method _on_done (line 296) | def _on_done(self):
    method _clean_viz_points (line 299) | def _clean_viz_points(self):
    method _get_gripper_ac (line 310) | def _get_gripper_ac(self, plan_ac) -> float:
    method adjusted_plan_idx (line 319) | def adjusted_plan_idx(self) -> bool:
    method _generate_plan (line 323) | def _generate_plan(self, observations, **kwargs) -> np.ndarray:
    method _clean_mp (line 330) | def _clean_mp(self):
  class IkMoveArm (line 336) | class IkMoveArm(ArmTargModule):
    method _get_plan_ac (line 337) | def _get_plan_ac(self, observations):
    method _on_done (line 347) | def _on_done(self):
    method _generate_plan (line 351) | def _generate_plan(self, observations, robot_target, **kwargs):
    method _internal_should_term (line 355) | def _internal_should_term(self, observations):
  class SpaManipPick (line 363) | class SpaManipPick(ArmTargModule):
    method wait_after (line 365) | def wait_after(self):
    method _internal_should_term (line 368) | def _internal_should_term(self, observations):
    method _generate_plan (line 378) | def _generate_plan(self, observations, obj, **kwargs):
    method _on_done (line 410) | def _on_done(self):
    method _get_gripper_ac (line 429) | def _get_gripper_ac(self, plan_ac):
  class SpaResetModule (line 437) | class SpaResetModule(ArmTargModule):
    method __init__ (line 438) | def __init__(
    method _generate_plan (line 452) | def _generate_plan(self, observations, **kwargs):
    method _on_done (line 483) | def _on_done(self):
    method _get_gripper_ac (line 489) | def _get_gripper_ac(self, plan_ac):
    method wait_after (line 497) | def wait_after(self):
  function main (line 501) | def main():

FILE: habitat-lab/habitat_baselines/agents/ppo_agents.py
  function get_default_config (line 26) | def get_default_config() -> Config:
  class PPOAgent (line 38) | class PPOAgent(Agent):
    method __init__ (line 39) | def __init__(self, config: Config) -> None:
    method reset (line 108) | def reset(self) -> None:
    method act (line 122) | def act(self, observations: Observations) -> Dict[str, int]:
  function main (line 144) | def main():

FILE: habitat-lab/habitat_baselines/agents/simple_agents.py
  class RandomAgent (line 21) | class RandomAgent(habitat.Agent):
    method __init__ (line 22) | def __init__(self, success_distance: float, goal_sensor_uuid: str) -> ...
    method reset (line 26) | def reset(self) -> None:
    method is_goal_reached (line 29) | def is_goal_reached(self, observations: Observations) -> bool_:
    method act (line 33) | def act(self, observations: Observations) -> Dict[str, int64]:
  class ForwardOnlyAgent (line 47) | class ForwardOnlyAgent(RandomAgent):
    method act (line 48) | def act(self, observations: Observations) -> Dict[str, int]:
  class RandomForwardAgent (line 56) | class RandomForwardAgent(RandomAgent):
    method __init__ (line 57) | def __init__(self, success_distance: float, goal_sensor_uuid: str) -> ...
    method act (line 61) | def act(self, observations: Observations) -> Dict[str, Union[int, int6...
  class GoalFollower (line 75) | class GoalFollower(RandomAgent):
    method __init__ (line 76) | def __init__(self, success_distance: float, goal_sensor_uuid: str) -> ...
    method normalize_angle (line 82) | def normalize_angle(self, angle: ndarray) -> ndarray:
    method turn_towards_goal (line 89) | def turn_towards_goal(self, angle_to_goal: ndarray) -> int:
    method act (line 98) | def act(self, observations: Observations) -> Dict[str, int]:
  function get_all_subclasses (line 113) | def get_all_subclasses(cls):
  function get_agent_cls (line 119) | def get_agent_cls(agent_class_name):
  function main (line 128) | def main():

FILE: habitat-lab/habitat_baselines/agents/slam_agents.py
  function download (line 46) | def download(url, filename):
  function ResizePIL2 (line 68) | def ResizePIL2(np_img, size=256):
  function make_good_config_for_orbslam2 (line 73) | def make_good_config_for_orbslam2(config):
  class RandomAgent (line 94) | class RandomAgent:
    method __init__ (line 99) | def __init__(self, config):
    method reset (line 106) | def reset(self):
    method update_internal_state (line 110) | def update_internal_state(self, habitat_observation):
    method is_goal_reached (line 115) | def is_goal_reached(self):
    method act (line 119) | def act(self, habitat_observation=None, random_prob=1.0):
  class BlindAgent (line 130) | class BlindAgent(RandomAgent):
    method __init__ (line 131) | def __init__(self, config):
    method decide_what_to_do (line 138) | def decide_what_to_do(self):
    method act (line 158) | def act(self, habitat_observation=None, random_prob=0.1):
  class ORBSLAM2Agent (line 173) | class ORBSLAM2Agent(RandomAgent):
    method __init__ (line 174) | def __init__(self, config, device=torch.device("cuda:0")):  # noqa: B008
    method reset (line 218) | def reset(self):
    method update_internal_state (line 244) | def update_internal_state(self, habitat_observation):
    method init_pose6d (line 291) | def init_pose6d(self):
    method map_size_in_cells (line 294) | def map_size_in_cells(self):
    method init_map2d (line 297) | def init_map2d(self):
    method get_orientation_on_map (line 306) | def get_orientation_on_map(self):
    method get_position_on_map (line 315) | def get_position_on_map(self, do_floor=True):
    method act (line 323) | def act(self, habitat_observation, random_prob=0.1):
    method is_waypoint_good (line 369) | def is_waypoint_good(self, pose6d):
    method is_waypoint_reached (line 375) | def is_waypoint_reached(self, pose6d):
    method get_waypoint_dist_dir (line 381) | def get_waypoint_dist_dir(self):
    method get_valid_waypoint_pose6d (line 397) | def get_valid_waypoint_pose6d(self):
    method set_offset_to_goal (line 408) | def set_offset_to_goal(self, observation):
    method rgb_d_from_observation (line 428) | def rgb_d_from_observation(self, habitat_observation):
    method prev_plan_is_not_valid (line 435) | def prev_plan_is_not_valid(self):
    method rawmap2_planner_ready (line 445) | def rawmap2_planner_ready(self, rawmap, start_map, goal_map):
    method plan_path (line 454) | def plan_path(self, overwrite=False):
    method planner_prediction_to_command (line 493) | def planner_prediction_to_command(self, p_next):
    method decide_what_to_do (line 514) | def decide_what_to_do(self):
  class ORBSLAM2MonodepthAgent (line 527) | class ORBSLAM2MonodepthAgent(ORBSLAM2Agent):
    method __init__ (line 528) | def __init__(
    method rgb_d_from_observation (line 586) | def rgb_d_from_observation(self, habitat_observation):
  function main (line 599) | def main():

FILE: habitat-lab/habitat_baselines/common/base_il_trainer.py
  class BaseILTrainer (line 14) | class BaseILTrainer(BaseTrainer):
    method __init__ (line 23) | def __init__(self, config: Config):
    method flush_secs (line 31) | def flush_secs(self):
    method flush_secs (line 35) | def flush_secs(self, value: int):
    method _make_dirs (line 38) | def _make_dirs(self) -> None:
    method _make_log_dir (line 45) | def _make_log_dir(self) -> None:
    method _make_ckpt_dir (line 52) | def _make_ckpt_dir(self) -> None:
    method _make_results_dir (line 57) | def _make_results_dir(self) -> None:
    method train (line 62) | def train(self) -> None:
    method _eval_checkpoint (line 65) | def _eval_checkpoint(
    method save_checkpoint (line 84) | def save_checkpoint(self, state_dict: OrderedDict, file_name: str) -> ...
    method load_checkpoint (line 98) | def load_checkpoint(self, checkpoint_path, *args, **kwargs) -> Dict:

FILE: habitat-lab/habitat_baselines/common/base_trainer.py
  class BaseTrainer (line 25) | class BaseTrainer:
    method train (line 34) | def train(self) -> None:
    method _setup_eval_config (line 37) | def _setup_eval_config(self, checkpoint_config: Config) -> Config:
    method eval (line 73) | def eval(self) -> None:
    method _eval_checkpoint (line 132) | def _eval_checkpoint(
    method save_checkpoint (line 140) | def save_checkpoint(self, file_name) -> None:
    method load_checkpoint (line 143) | def load_checkpoint(self, checkpoint_path, *args, **kwargs) -> Dict:
  class BaseRLTrainer (line 147) | class BaseRLTrainer(BaseTrainer):
    method __init__ (line 159) | def __init__(self, config: Config) -> None:
    method percent_done (line 201) | def percent_done(self) -> float:
    method is_done (line 207) | def is_done(self) -> bool:
    method should_checkpoint (line 210) | def should_checkpoint(self) -> bool:
    method _should_save_resume_state (line 227) | def _should_save_resume_state(self) -> bool:
    method flush_secs (line 243) | def flush_secs(self):
    method flush_secs (line 247) | def flush_secs(self, value: int):
    method train (line 250) | def train(self) -> None:
    method _eval_checkpoint (line 253) | def _eval_checkpoint(
    method save_checkpoint (line 272) | def save_checkpoint(self, file_name) -> None:
    method load_checkpoint (line 275) | def load_checkpoint(self, checkpoint_path, *args, **kwargs) -> Dict:
    method _pause_envs (line 279) | def _pause_envs(

FILE: habitat-lab/habitat_baselines/common/baseline_registry.py
  class BaselineRegistry (line 29) | class BaselineRegistry(Registry):
    method register_trainer (line 31) | def register_trainer(cls, to_register=None, *, name: Optional[str] = N...
    method get_trainer (line 46) | def get_trainer(cls, name):
    method register_env (line 50) | def register_env(cls, to_register=None, *, name: Optional[str] = None):
    method get_env (line 64) | def get_env(cls, name):
    method register_policy (line 68) | def register_policy(cls, to_register=None, *, name: Optional[str] = No...
    method get_policy (line 100) | def get_policy(cls, name: str):
    method register_obs_transformer (line 105) | def register_obs_transformer(
    method get_obs_transformer (line 144) | def get_obs_transformer(cls, name: str):

FILE: habitat-lab/habitat_baselines/common/environments.py
  function get_env_class (line 22) | def get_env_class(env_name: str) -> Type[habitat.RLEnv]:
  class RearrangeRLEnv (line 35) | class RearrangeRLEnv(habitat.RLEnv):
    method __init__ (line 36) | def __init__(self, config: Config, dataset: Optional[Dataset] = None):
    method reset (line 45) | def reset(self):
    method step (line 50) | def step(self, *args, **kwargs):
    method get_reward_range (line 54) | def get_reward_range(self):
    method get_reward (line 58) | def get_reward(self, observations):
    method _episode_success (line 69) | def _episode_success(self):
    method get_done (line 72) | def get_done(self, observations):
    method get_info (line 83) | def get_info(self, observations):
  class NavRLEnv (line 88) | class NavRLEnv(habitat.RLEnv):
    method __init__ (line 89) | def __init__(self, config: Config, dataset: Optional[Dataset] = None):
    method reset (line 99) | def reset(self):
    method step (line 107) | def step(self, *args, **kwargs):
    method get_reward_range (line 111) | def get_reward_range(self):
    method get_reward (line 117) | def get_reward(self, observations):
    method _episode_success (line 130) | def _episode_success(self):
    method get_done (line 133) | def get_done(self, observations):
    method get_info (line 139) | def get_info(self, observations):

FILE: habitat-lab/habitat_baselines/common/obs_transformers.py
  class ObservationTransformer (line 45) | class ObservationTransformer(nn.Module, metaclass=abc.ABCMeta):
    method transform_observation_space (line 51) | def transform_observation_space(
    method from_config (line 58) | def from_config(cls, config: Config):
    method forward (line 61) | def forward(
  class ResizeShortestEdge (line 68) | class ResizeShortestEdge(ObservationTransformer):
    method __init__ (line 73) | def __init__(
    method transform_observation_space (line 90) | def transform_observation_space(
    method _transform_obs (line 118) | def _transform_obs(
    method forward (line 129) | def forward(
    method from_config (line 144) | def from_config(cls, config: Config):
  class CenterCropper (line 149) | class CenterCropper(ObservationTransformer):
    method __init__ (line 152) | def __init__(
    method transform_observation_space (line 172) | def transform_observation_space(
    method _transform_obs (line 197) | def _transform_obs(self, obs: torch.Tensor) -> torch.Tensor:
    method forward (line 205) | def forward(
    method from_config (line 219) | def from_config(cls, config: Config):
  class _DepthFrom (line 229) | class _DepthFrom(Enum):
  class CameraProjection (line 234) | class CameraProjection(metaclass=abc.ABCMeta):
    method __init__ (line 242) | def __init__(
    method projection (line 266) | def projection(
    method unprojection (line 278) | def unprojection(
    method rotation (line 291) | def rotation(self):
    method shape (line 299) | def shape(self):
    method size (line 303) | def size(self):
    method camcoord2worldcoord (line 307) | def camcoord2worldcoord(self, pts: torch.Tensor):
    method worldcoord2camcoord (line 323) | def worldcoord2camcoord(self, pts: torch.Tensor):
  class PerspectiveProjection (line 340) | class PerspectiveProjection(CameraProjection):
    method __init__ (line 343) | def __init__(
    method projection (line 364) | def projection(
    method unprojection (line 387) | def unprojection(
  class EquirectProjection (line 409) | class EquirectProjection(CameraProjection):
    method __init__ (line 412) | def __init__(
    method projection (line 422) | def projection(
    method unprojection (line 443) | def unprojection(
    method get_theta_phi_map (line 455) | def get_theta_phi_map(
    method angle2sphere (line 466) | def angle2sphere(
  class FisheyeProjection (line 479) | class FisheyeProjection(CameraProjection):
    method __init__ (line 486) | def __init__(
    method projection (line 514) | def projection(
    method unprojection (line 558) | def unprojection(
  class ProjectionConverter (line 597) | class ProjectionConverter(nn.Module):
    method __init__ (line 602) | def __init__(
    method _generate_grid_one_output (line 649) | def _generate_grid_one_output(
    method generate_grid (line 668) | def generate_grid(self) -> torch.Tensor:
    method _convert (line 676) | def _convert(self, batch: torch.Tensor) -> torch.Tensor:
    method to_converted_tensor (line 698) | def to_converted_tensor(self, batch: torch.Tensor) -> torch.Tensor:
    method calculate_zfactor (line 740) | def calculate_zfactor(
    method forward (line 780) | def forward(
  function get_cubemap_projections (line 802) | def get_cubemap_projections(
  class Cube2Equirect (line 839) | class Cube2Equirect(ProjectionConverter):
    method __init__ (line 844) | def __init__(self, equ_h: int, equ_w: int):
  class ProjectionTransformer (line 860) | class ProjectionTransformer(ObservationTransformer):
    method __init__ (line 866) | def __init__(
    method transform_observation_space (line 900) | def transform_observation_space(
    method forward (line 925) | def forward(
  class CubeMap2Equirect (line 961) | class CubeMap2Equirect(ProjectionTransformer):
    method __init__ (line 973) | def __init__(
    method from_config (line 999) | def from_config(cls, config):
  class Cube2Fisheye (line 1016) | class Cube2Fisheye(ProjectionConverter):
    method __init__ (line 1022) | def __init__(
  class CubeMap2Fisheye (line 1055) | class CubeMap2Fisheye(ProjectionTransformer):
    method __init__ (line 1067) | def __init__(
    method from_config (line 1110) | def from_config(cls, config):
  class Equirect2Cube (line 1129) | class Equirect2Cube(ProjectionConverter):
    method __init__ (line 1133) | def __init__(self, img_h: int, img_w: int):
  class Equirect2CubeMap (line 1150) | class Equirect2CubeMap(ProjectionTransformer):
    method __init__ (line 1157) | def __init__(
    method from_config (line 1183) | def from_config(cls, config):
  function get_active_obs_transforms (line 1201) | def get_active_obs_transforms(config: Config) -> List[ObservationTransfo...
  function apply_obs_transforms_batch (line 1216) | def apply_obs_transforms_batch(
  function apply_obs_transforms_obs_space (line 1225) | def apply_obs_transforms_obs_space(

FILE: habitat-lab/habitat_baselines/common/rollout_storage.py
  class RolloutStorage (line 16) | class RolloutStorage:
    method __init__ (line 19) | def __init__(
    method current_rollout_step_idx (line 96) | def current_rollout_step_idx(self) -> int:
    method to (line 103) | def to(self, device):
    method insert (line 106) | def insert(
    method advance_rollout (line 156) | def advance_rollout(self, buffer_index: int = 0):
    method after_update (line 159) | def after_update(self):
    method compute_returns (line 166) | def compute_returns(self, next_value, use_gae, gamma, tau):
    method recurrent_generator (line 197) | def recurrent_generator(

FILE: habitat-lab/habitat_baselines/common/tensor_dict.py
  class TensorDict (line 22) | class TensorDict(Dict[str, Union["TensorDict", torch.Tensor]]):
    method from_tree (line 37) | def from_tree(cls, tree: DictTree) -> "TensorDict":
    method to_tree (line 47) | def to_tree(self) -> DictTree:
    method __getitem__ (line 58) | def __getitem__(self, index: str) -> Union["TensorDict", torch.Tensor]:
    method __getitem__ (line 62) | def __getitem__(self, index: TensorIndexType) -> "TensorDict":
    method __getitem__ (line 65) | def __getitem__(
    method set (line 74) | def set(
    method set (line 83) | def set(
    method set (line 91) | def set(
    method __setitem__ (line 129) | def __setitem__(
    method __setitem__ (line 137) | def __setitem__(
    method __setitem__ (line 144) | def __setitem__(
    method map_func (line 152) | def map_func(
    method map (line 171) | def map(
    method map_in_place (line 176) | def map_in_place(
    method __deepcopy__ (line 181) | def __deepcopy__(self, _memo=None) -> "TensorDict":

FILE: habitat-lab/habitat_baselines/common/tensorboard_utils.py
  class TensorboardWriter (line 14) | class TensorboardWriter:
    method __init__ (line 15) | def __init__(self, log_dir: str, *args: Any, **kwargs: Any):
    method __getattr__ (line 30) | def __getattr__(self, item):
    method __enter__ (line 36) | def __enter__(self):
    method __exit__ (line 39) | def __exit__(self, exc_type, exc_val, exc_tb):
    method add_video_from_np_images (line 43) | def add_video_from_np_images(

FILE: habitat-lab/habitat_baselines/config/default.py
  function get_config (line 210) | def get_config(

FILE: habitat-lab/habitat_baselines/il/metrics.py
  class Metric (line 15) | class Metric:
    method __init__ (line 16) | def __init__(self, info=None, metric_names=None, log_json=None):
    method update (line 29) | def update(self, values: List) -> None:
    method get_stat_string (line 66) | def get_stat_string(self, mode: int = 1) -> str:
    method get_stats (line 83) | def get_stats(self, mode: int = 1) -> List[float]:
    method dump_log (line 90) | def dump_log(self) -> bool:
  class VqaMetric (line 103) | class VqaMetric(Metric):
    method __init__ (line 104) | def __init__(self, info=None, metric_names=None, log_json=None):
    method compute_ranks (line 107) | def compute_ranks(
  class NavMetric (line 120) | class NavMetric(Metric):
    method __init__ (line 121) | def __init__(self, info=None, metric_names=None, log_json=None):

FILE: habitat-lab/habitat_baselines/il/models/models.py
  function build_mlp (line 15) | def build_mlp(
  class MultitaskCNN (line 44) | class MultitaskCNN(nn.Module):
    method __init__ (line 45) | def __init__(
    method forward (line 132) | def forward(self, x: Tensor) -> Tuple[Tensor, Tensor, Tensor]:
  class QuestionLstmEncoder (line 217) | class QuestionLstmEncoder(nn.Module):
    method __init__ (line 218) | def __init__(
    method init_weights (line 244) | def init_weights(self) -> None:
    method forward (line 248) | def forward(self, x: Tensor) -> Tensor:
  class VqaLstmCnnAttentionModel (line 264) | class VqaLstmCnnAttentionModel(nn.Module):
    method __init__ (line 265) | def __init__(
    method forward (line 321) | def forward(
  class MaskedNLLCriterion (line 359) | class MaskedNLLCriterion(nn.Module):
    method __init__ (line 360) | def __init__(self) -> None:
    method forward (line 363) | def forward(self, inp: Tensor, target: Tensor, mask: Tensor) -> Tensor:
  class NavPlannerControllerModel (line 370) | class NavPlannerControllerModel(nn.Module):
    method __init__ (line 371) | def __init__(
    method forward (line 434) | def forward(
    method planner_step (line 508) | def planner_step(
    method controller_step (line 524) | def controller_step(
  class NavRnn (line 541) | class NavRnn(nn.Module):
    method __init__ (line 542) | def __init__(
    method init_hidden (line 618) | def init_hidden(
    method forward (line 638) | def forward(
    method step_forward (line 687) | def step_forward(

FILE: habitat-lab/habitat_baselines/il/trainers/eqa_cnn_pretrain_trainer.py
  class EQACNNPretrainTrainer (line 29) | class EQACNNPretrainTrainer(BaseILTrainer):
    method __init__ (line 36) | def __init__(self, config=None):
    method _make_results_dir (line 48) | def _make_results_dir(self):
    method _save_results (line 55) | def _save_results(
    method train (line 81) | def train(self) -> None:
    method _eval_checkpoint (line 178) | def _eval_checkpoint(

FILE: habitat-lab/habitat_baselines/il/trainers/pacman_trainer.py
  class PACMANTrainer (line 37) | class PACMANTrainer(BaseILTrainer):
    method __init__ (line 44) | def __init__(self, config=None):
    method _save_nav_results (line 56) | def _save_nav_results(
    method train (line 129) | def train(self) -> None:
    method _eval_checkpoint (line 336) | def _eval_checkpoint(

FILE: habitat-lab/habitat_baselines/il/trainers/vqa_trainer.py
  class VQATrainer (line 27) | class VQATrainer(BaseILTrainer):
    method __init__ (line 33) | def __init__(self, config=None):
    method _make_results_dir (line 45) | def _make_results_dir(self):
    method _save_vqa_results (line 50) | def _save_vqa_results(
    method train (line 105) | def train(self) -> None:
    method _eval_checkpoint (line 267) | def _eval_checkpoint(

FILE: habitat-lab/habitat_baselines/motion_planning/grasp_generator.py
  class GraspGenerator (line 19) | class GraspGenerator:
    method __init__ (line 20) | def __init__(
    method get_def_js (line 48) | def get_def_js(self):
    method get_targ_obj (line 52) | def get_targ_obj(self, start_js, obj_id):
    method _gen_goal_state (line 55) | def _gen_goal_state(self, local_ee_targ, grasp_idx=0, timeout=100):
    method _fk (line 95) | def _fk(self, joints):
    method gen_target_from_ee_pos (line 99) | def gen_target_from_ee_pos(self, ee_pos):
    method _verbose_log (line 127) | def _verbose_log(self, s):
    method get_obj_goal_offset (line 131) | def get_obj_goal_offset(self, obj_idx):
    method _bounding_sphere_sample (line 136) | def _bounding_sphere_sample(
    method _get_real_ee_pos (line 230) | def _get_real_ee_pos(self, joints):
    method _clean_grasp_debug_points (line 242) | def _clean_grasp_debug_points(self):
    method _grasp_debug_points (line 257) | def _grasp_debug_points(self, obj_pos, grasp_point):
    method gen_target_from_obj_idx (line 268) | def gen_target_from_obj_idx(self, obj_idx):

FILE: habitat-lab/habitat_baselines/motion_planning/motion_plan.py
  function is_ompl_installed (line 44) | def is_ompl_installed() -> bool:
  class MotionPlanner (line 48) | class MotionPlanner:
    method __init__ (line 49) | def __init__(self, sim: RearrangeSim, config: CfgNode):
    method set_should_render (line 66) | def set_should_render(self, should_render: bool):
    method _log (line 72) | def _log(self, txt: str):
    method action_space (line 80) | def action_space(self):
    method _render_debug_image (line 83) | def _render_debug_image(
    method get_mp_space (line 104) | def get_mp_space(self) -> MpSpace:
    method _is_state_valid (line 112) | def _is_state_valid(self, x: np.ndarray, take_image: bool = False) -> ...
    method set_config (line 154) | def set_config(
    method setup_ee_margin (line 192) | def setup_ee_margin(self, obj_id_target: int):
    method remove_ee_margin (line 203) | def remove_ee_margin(self, obj_id_target: int):
    method get_recent_plan_stats (line 215) | def get_recent_plan_stats(
    method motion_plan (line 238) | def motion_plan(
    method _render_verify_motion_plan (line 315) | def _render_verify_motion_plan(
    method set_plan_ignore_obj (line 376) | def set_plan_ignore_obj(self, obj_id):
    method _get_sim (line 379) | def _get_sim(self) -> MpSim:
    method _check_ee_coll (line 388) | def _check_ee_coll(
    method _get_path (line 403) | def _get_path(

FILE: habitat-lab/habitat_baselines/motion_planning/mp_sim.py
  class MpSim (line 16) | class MpSim(ABC):
    method __init__ (line 21) | def __init__(self, sim: RearrangeSim):
    method setup (line 25) | def setup(self, use_prev):
    method should_ignore_first_collisions (line 28) | def should_ignore_first_collisions(self):
    method set_targ_obj_idx (line 32) | def set_targ_obj_idx(self, targ_obj_idx):
    method unset_targ_obj_idx (line 36) | def unset_targ_obj_idx(self, targ_obj_idx):
    method get_robot_transform (line 40) | def get_robot_transform(self):
    method get_collisions (line 46) | def get_collisions(self, count_obj_colls, ignore_names, verbose):
    method capture_state (line 57) | def capture_state(self):
    method get_arm_pos (line 61) | def get_arm_pos(self):
    method set_arm_pos (line 65) | def set_arm_pos(self, joint_pos):
    method set_position (line 69) | def set_position(self, pos, obj_id):
    method micro_step (line 73) | def micro_step(self):
    method add_sphere (line 77) | def add_sphere(self, radius, color=None):
    method get_ee_pos (line 81) | def get_ee_pos(self):
    method remove_object (line 87) | def remove_object(self, obj_id):
    method set_state (line 91) | def set_state(self, state):
    method render (line 95) | def render(self):
    method start_mp (line 101) | def start_mp(self):
    method end_mp (line 105) | def end_mp(self):
    method get_obj_info (line 109) | def get_obj_info(self, obj_idx) -> ObjectGraspTarget:
  class HabMpSim (line 115) | class HabMpSim(MpSim):
    method get_collisions (line 116) | def get_collisions(
    method _snap_idx (line 131) | def _snap_idx(self):
    method capture_state (line 134) | def capture_state(self):
    method get_ee_pos (line 138) | def get_ee_pos(self):
    method set_state (line 141) | def set_state(self, state):
    method set_arm_pos (line 148) | def set_arm_pos(self, joint_pos):
    method get_robot_transform (line 151) | def get_robot_transform(self):
    method get_obj_info (line 154) | def get_obj_info(self, obj_idx) -> ObjectGraspTarget:
    method set_position (line 162) | def set_position(self, pos, obj_id):
    method get_arm_pos (line 167) | def get_arm_pos(self):
    method micro_step (line 170) | def micro_step(self):
    method add_sphere (line 174) | def add_sphere(self, radius, color=None):
    method remove_object (line 183) | def remove_object(self, obj_id):
    method set_targ_obj_idx (line 186) | def set_targ_obj_idx(self, targ_obj_idx):
    method unset_targ_obj_idx (line 192) | def unset_targ_obj_idx(self, targ_obj_idx):
    method render (line 198) | def render(self):
    method start_mp (line 208) | def start_mp(self):
    method end_mp (line 227) | def end_mp(self):

FILE: habitat-lab/habitat_baselines/motion_planning/mp_spaces.py
  function to_ob_state (line 20) | def to_ob_state(vec: np.ndarray, space: "ob.StateSpace", dim: int):
  class MpSpace (line 27) | class MpSpace(ABC):
    method __init__ (line 32) | def __init__(self, use_sim: RearrangeSim, ik: IkHelper):
    method convert_state (line 37) | def convert_state(self, x: Iterable) -> np.ndarray:
    method set_arm (line 41) | def set_arm(self, x: Union[List[float], np.ndarray]):
    method set_env_state (line 44) | def set_env_state(self, env_state: Dict[str, Any]):
    method get_range (line 48) | def get_range(self) -> float:
    method get_state_lims (line 54) | def get_state_lims(self, restrictive: bool = False) -> np.ndarray:
    method get_state_dim (line 60) | def get_state_dim(self) -> int:
    method get_start_goal (line 66) | def get_start_goal(self) -> Tuple[np.ndarray, np.ndarray]:
    method convert_sol (line 73) | def convert_sol(self, path) -> np.ndarray:
    method get_planner (line 79) | def get_planner(self, si: "ob.SpaceInformation"):
    method set_problem (line 83) | def set_problem(
    method render_start_targ (line 95) | def render_start_targ(
  function getPathLengthObjWithCostToGo (line 107) | def getPathLengthObjWithCostToGo(si):
  class JsMpSpace (line 113) | class JsMpSpace(MpSpace):
    method __init__ (line 114) | def __init__(self, use_sim, ik, start_num_calls, should_render):
    method convert_state (line 125) | def convert_state(self, x):
    method _norm_joint_angle (line 128) | def _norm_joint_angle(self, angles):
    method get_planner (line 131) | def get_planner(self, si):
    method get_state_lims (line 134) | def get_state_lims(self, restrictive=False):
    method get_state_dim (line 153) | def get_state_dim(self):
    method _fk (line 156) | def _fk(self, joints):
    method get_start_goal (line 161) | def get_start_goal(self) -> Tuple[np.ndarray, np.ndarray]:
    method set_problem (line 164) | def set_problem(
    method render_start_targ (line 216) | def render_start_targ(self, render_dir, subdir, targ_state, suffix="ta...
    method get_range (line 241) | def get_range(self):
    method set_arm (line 244) | def set_arm(self, des_joint_pos):
    method convert_sol (line 250) | def convert_sol(self, path):

FILE: habitat-lab/habitat_baselines/motion_planning/robot_target.py
  class RobotTarget (line 13) | class RobotTarget:
  class ObjectGraspTarget (line 26) | class ObjectGraspTarget:

FILE: habitat-lab/habitat_baselines/rl/ddppo/algo/ddppo.py
  function distributed_mean_and_var (line 18) | def distributed_mean_and_var(
  class _EvalActionsWrapper (line 46) | class _EvalActionsWrapper(torch.nn.Module):
    method __init__ (line 51) | def __init__(self, actor_critic):
    method forward (line 55) | def forward(self, *args, **kwargs):
  class DecentralizedDistributedMixin (line 59) | class DecentralizedDistributedMixin:
    method _get_advantages_distributed (line 60) | def _get_advantages_distributed(
    method init_distributed (line 76) | def init_distributed(self, find_unused_params: bool = True) -> None:
    method _evaluate_actions (line 107) | def _evaluate_actions(
  class DDPPO (line 118) | class DDPPO(DecentralizedDistributedMixin, PPO):

FILE: habitat-lab/habitat_baselines/rl/ddppo/data_generation/create_gibson_large_dataset.py
  function safe_mkdir (line 32) | def safe_mkdir(path):
  function _generate_fn (line 39) | def _generate_fn(scene):
  function generate_gibson_large_dataset (line 67) | def generate_gibson_large_dataset():

FILE: habitat-lab/habitat_baselines/rl/ddppo/ddp_utils.py
  function is_slurm_job (line 33) | def is_slurm_job() -> bool:
  function is_slurm_batch_job (line 37) | def is_slurm_batch_job() -> bool:
  function resume_state_filename (line 53) | def resume_state_filename(config: Config) -> str:
  function rank0_only (line 63) | def rank0_only() -> bool:
  function rank0_only (line 68) | def rank0_only(fn: Callable) -> Callable:
  function rank0_only (line 72) | def rank0_only(fn: Optional[Callable] = None) -> Union[Callable, bool]:
  function _ignore_handler (line 113) | def _ignore_handler(signum, frame):
  function _clean_exit_handler (line 117) | def _clean_exit_handler(signum, frame):
  function _clean_exit_and_save_handler (line 122) | def _clean_exit_and_save_handler(signum, frame):
  function _requeue_handler (line 128) | def _requeue_handler(signal, frame):
  function add_signal_handlers (line 135) | def add_signal_handlers() -> None:
  function save_resume_state (line 155) | def save_resume_state(state: Any, filename_or_config: Union[Config, str]):
  function load_resume_state (line 170) | def load_resume_state(filename_or_config: Union[Config, str]) -> Optiona...
  function requeue_job (line 191) | def requeue_job():
  function get_ifname (line 207) | def get_ifname() -> str:
  function get_distrib_size (line 211) | def get_distrib_size() -> Tuple[int, int, int]:
  function init_distrib_slurm (line 231) | def init_distrib_slurm(

FILE: habitat-lab/habitat_baselines/rl/ddppo/policy/resnet.py
  function conv3x3 (line 15) | def conv3x3(
  function conv1x1 (line 30) | def conv1x1(in_planes: int, out_planes: int, stride: int = 1) -> Conv2d:
  class BasicBlock (line 37) | class BasicBlock(nn.Module):
    method __init__ (line 41) | def __init__(
    method forward (line 61) | def forward(self, x):
  function _build_bottleneck_branch (line 72) | def _build_bottleneck_branch(
  class SE (line 92) | class SE(nn.Module):
    method __init__ (line 93) | def __init__(self, planes, r=16):
    method forward (line 103) | def forward(self, x):
  function _build_se_branch (line 112) | def _build_se_branch(planes, r=16):
  class Bottleneck (line 116) | class Bottleneck(nn.Module):
    method __init__ (line 120) | def __init__(
    method _impl (line 141) | def _impl(self, x: Tensor) -> Tensor:
    method forward (line 151) | def forward(self, x: Tensor) -> Tensor:
  class SEBottleneck (line 155) | class SEBottleneck(Bottleneck):
    method __init__ (line 156) | def __init__(
    method _impl (line 171) | def _impl(self, x):
  class SEResNeXtBottleneck (line 183) | class SEResNeXtBottleneck(SEBottleneck):
  class ResNeXtBottleneck (line 188) | class ResNeXtBottleneck(Bottleneck):
  class ResNet (line 196) | class ResNet(nn.Module):
    method __init__ (line 197) | def __init__(
    method _make_layer (line 240) | def _make_layer(
    method forward (line 272) | def forward(self, x) -> Tensor:
  function resnet18 (line 284) | def resnet18(in_channels, base_planes, ngroups):
  function resnet50 (line 290) | def resnet50(in_channels: int, base_planes: int, ngroups: int) -> ResNet:
  function resneXt50 (line 296) | def resneXt50(in_channels, base_planes, ngroups):
  function se_resnet50 (line 309) | def se_resnet50(in_channels, base_planes, ngroups):
  function se_resneXt50 (line 317) | def se_resneXt50(in_channels, base_planes, ngroups):
  function se_resneXt101 (line 330) | def se_resneXt101(in_channels, base_planes, ngroups):

FILE: habitat-lab/habitat_baselines/rl/ddppo/policy/resnet_policy.py
  class PointNavResNetPolicy (line 39) | class PointNavResNetPolicy(Policy):
    method __init__ (line 40) | def __init__(
    method from_config (line 82) | def from_config(
  class ResNetEncoder (line 98) | class ResNetEncoder(nn.Module):
    method __init__ (line 99) | def __init__(
    method is_blind (line 159) | def is_blind(self):
    method layer_init (line 162) | def layer_init(self):
    method forward (line 171) | def forward(self, observations: Dict[str, torch.Tensor]) -> torch.Tens...
  class PointNavResNetNet (line 202) | class PointNavResNetNet(Net):
    method __init__ (line 209) | def __init__(
    method output_size (line 349) | def output_size(self):
    method is_blind (line 353) | def is_blind(self):
    method num_recurrent_layers (line 357) | def num_recurrent_layers(self):
    method forward (line 360) | def forward(

FILE: habitat-lab/habitat_baselines/rl/ddppo/policy/running_mean_and_var.py
  class RunningMeanAndVar (line 13) | class RunningMeanAndVar(nn.Module):
    method __init__ (line 14) | def __init__(self, n_channels: int) -> None:
    method forward (line 23) | def forward(self, x: Tensor) -> Tensor:

FILE: habitat-lab/habitat_baselines/rl/models/rnn_state_encoder.py
  function _invert_permutation (line 14) | def _invert_permutation(permutation: torch.Tensor) -> torch.Tensor:
  function _build_pack_info_from_dones (line 24) | def _build_pack_info_from_dones(
  function build_rnn_inputs (line 154) | def build_rnn_inputs(
  function build_rnn_out_from_seq (line 226) | def build_rnn_out_from_seq(
  class RNNStateEncoder (line 261) | class RNNStateEncoder(nn.Module):
    method layer_init (line 270) | def layer_init(self):
    method pack_hidden (line 277) | def pack_hidden(self, hidden_states: torch.Tensor) -> torch.Tensor:
    method unpack_hidden (line 280) | def unpack_hidden(self, hidden_states: torch.Tensor) -> torch.Tensor:
    method single_forward (line 283) | def single_forward(
    method seq_forward (line 300) | def seq_forward(
    method forward (line 337) | def forward(
  class LSTMStateEncoder (line 351) | class LSTMStateEncoder(RNNStateEncoder):
    method __init__ (line 352) | def __init__(
    method pack_hidden (line 370) | def pack_hidden(
    method unpack_hidden (line 375) | def unpack_hidden(
  class GRUStateEncoder (line 382) | class GRUStateEncoder(RNNStateEncoder):
    method __init__ (line 383) | def __init__(
  function build_rnn_state_encoder (line 402) | def build_rnn_state_encoder(

FILE: habitat-lab/habitat_baselines/rl/models/simple_cnn.py
  class SimpleCNN (line 8) | class SimpleCNN(nn.Module):
    method __init__ (line 18) | def __init__(
    method _conv_output_dim (line 93) | def _conv_output_dim(
    method layer_init (line 122) | def layer_init(self):
    method is_blind (line 132) | def is_blind(self):
    method forward (line 135) | def forward(self, observations: Dict[str, torch.Tensor]):

FILE: habitat-lab/habitat_baselines/rl/ppo/policy.py
  class Policy (line 27) | class Policy(nn.Module, metaclass=abc.ABCMeta):
    method __init__ (line 30) | def __init__(self, net, dim_actions, policy_config=None):
    method forward (line 61) | def forward(self, *x):
    method act (line 64) | def act(
    method get_value (line 90) | def get_value(self, observations, rnn_hidden_states, prev_actions, mas...
    method evaluate_actions (line 96) | def evaluate_actions(
    method from_config (line 112) | def from_config(cls, config, observation_space, action_space):
  class CriticHead (line 116) | class CriticHead(nn.Module):
    method __init__ (line 117) | def __init__(self, input_size):
    method forward (line 123) | def forward(self, x):
  class PointNavBaselinePolicy (line 128) | class PointNavBaselinePolicy(Policy):
    method __init__ (line 129) | def __init__(
    method from_config (line 146) | def from_config(
  class Net (line 156) | class Net(nn.Module, metaclass=abc.ABCMeta):
    method forward (line 158) | def forward(self, observations, rnn_hidden_states, prev_actions, masks):
    method output_size (line 163) | def output_size(self):
    method num_recurrent_layers (line 168) | def num_recurrent_layers(self):
    method is_blind (line 173) | def is_blind(self):
  class PointNavBaselineNet (line 177) | class PointNavBaselineNet(Net):
    method __init__ (line 182) | def __init__(
    method output_size (line 221) | def output_size(self):
    method is_blind (line 225) | def is_blind(self):
    method num_recurrent_layers (line 229) | def num_recurrent_layers(self):
    method forward (line 232) | def forward(self, observations, rnn_hidden_states, prev_actions, masks):

FILE: habitat-lab/habitat_baselines/rl/ppo/ppo.py
  class PPO (line 21) | class PPO(nn.Module):
    method __init__ (line 22) | def __init__(
    method forward (line 59) | def forward(self, *x):
    method get_advantages (line 62) | def get_advantages(self, rollouts: RolloutStorage) -> Tensor:
    method update (line 72) | def update(self, rollouts: RolloutStorage) -> Tuple[float, float, float]:
    method _evaluate_actions (line 155) | def _evaluate_actions(
    method before_backward (line 165) | def before_backward(self, loss: Tensor) -> None:
    method after_backward (line 168) | def after_backward(self, loss: Tensor) -> None:
    method before_step (line 171) | def before_step(self) -> None:
    method after_step (line 176) | def after_step(self) -> None:

FILE: habitat-lab/habitat_baselines/rl/ppo/ppo_trainer.py
  class PPOTrainer (line 62) | class PPOTrainer(BaseRLTrainer):
    method __init__ (line 75) | def __init__(self, config=None):
    method obs_space (line 96) | def obs_space(self):
    method obs_space (line 103) | def obs_space(self, new_obs_space):
    method _all_reduce (line 106) | def _all_reduce(self, t: torch.Tensor) -> torch.Tensor:
    method _setup_actor_critic_agent (line 119) | def _setup_actor_critic_agent(self, ppo_cfg: Config) -> None:
    method _init_envs (line 190) | def _init_envs(self, config=None):
    method _init_train (line 200) | def _init_train(self):
    method save_checkpoint (line 340) | def save_checkpoint(
    method load_checkpoint (line 362) | def load_checkpoint(self, checkpoint_path: str, *args, **kwargs) -> Dict:
    method _extract_scalars_from_info (line 378) | def _extract_scalars_from_info(
    method _extract_scalars_from_infos (line 404) | def _extract_scalars_from_infos(
    method _compute_actions_and_step_envs (line 415) | def _compute_actions_and_step_envs(self, buffer_index: int = 0):
    method _collect_environment_result (line 475) | def _collect_environment_result(self, buffer_index: int = 0):
    method _collect_rollout_step (line 551) | def _collect_rollout_step(self):
    method _update_agent (line 556) | def _update_agent(self):
    method _coalesce_post_step (line 590) | def _coalesce_post_step(
    method _training_log (line 626) | def _training_log(
    method should_end_early (line 689) | def should_end_early(self, rollout_step) -> bool:
    method train (line 702) | def train(self) -> None:
    method _eval_checkpoint (line 866) | def _eval_checkpoint(

FILE: habitat-lab/habitat_baselines/run.py
  function main (line 18) | def main():
  function execute_exp (line 43) | def execute_exp(config: Config, run_type: str) -> None:
  function run_exp (line 65) | def run_exp(exp_config: str, run_type: str, opts=None) -> None:

FILE: habitat-lab/habitat_baselines/slambased/mappers.py
  function depth2local3d (line 18) | def depth2local3d(depth, fx, fy, cx, cy):
  function pcl_to_obstacles (line 38) | def pcl_to_obstacles(pts3d, map_size=40, cell_size=0.2, min_pts=10):
  class DirectDepthMapper (line 64) | class DirectDepthMapper(nn.Module):
    method __init__ (line 71) | def __init__(
    method forward (line 94) | def forward(self, depth, pose=torch.eye(4).float()):  # noqa: B008

FILE: habitat-lab/habitat_baselines/slambased/monodepth.py
  function conv3x3 (line 51) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 63) | class BasicBlock(nn.Module):
    method __init__ (line 66) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 76) | def forward(self, x):
  class Bottleneck (line 95) | class Bottleneck(nn.Module):
    method __init__ (line 98) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 112) | def forward(self, x):
  class ResNet (line 135) | class ResNet(nn.Module):
    method __init__ (line 136) | def __init__(self, block, layers, num_classes=1000):
    method _make_layer (line 160) | def _make_layer(self, block, planes, blocks, stride=1):
    method forward (line 182) | def forward(self, x):
  function resnet18 (line 200) | def resnet18(pretrained=False, **kwargs):
  function resnet34 (line 211) | def resnet34(pretrained=False, **kwargs):
  function resnet50 (line 222) | def resnet50(pretrained=False, **kwargs):
  function resnet101 (line 237) | def resnet101(pretrained=False, **kwargs):
  function resnet152 (line 248) | def resnet152(pretrained=False, **kwargs):
  class model (line 259) | class model(nn.Module):
    method __init__ (line 260) | def __init__(self, Encoder, num_features, block_channel):
    method forward (line 269) | def forward(self, x):
  class _UpProjection (line 284) | class _UpProjection(nn.Sequential):
    method __init__ (line 285) | def __init__(self, num_input_features, num_output_features):
    method forward (line 318) | def forward(self, x, size):
  class E_resnet (line 329) | class E_resnet(nn.Module):
    method __init__ (line 330) | def __init__(self, original_model, num_features=2048):
    method forward (line 342) | def forward(self, x):
  class D (line 356) | class D(nn.Module):
    method __init__ (line 357) | def __init__(self, num_features=2048):
    method forward (line 393) | def forward(self, x_block1, x_block2, x_block3, x_block4):
  class MFF (line 403) | class MFF(nn.Module):
    method __init__ (line 404) | def __init__(self, block_channel, num_features=64):
    method forward (line 434) | def forward(self, x_block1, x_block2, x_block3, x_block4, size):
  class R (line 446) | class R(nn.Module):
    method __init__ (line 447) | def __init__(self, block_channel):
    method forward (line 476) | def forward(self, x):
  function _is_pil_image (line 490) | def _is_pil_image(img):
  function _is_numpy_image (line 494) | def _is_numpy_image(img):
  class Scale (line 498) | class Scale:
    method __init__ (line 499) | def __init__(self, size):
    method __call__ (line 502) | def __call__(self, image):
    method changeScale (line 507) | def changeScale(self, img, size, interpolation=Image.BILINEAR):
  class CenterCrop (line 513) | class CenterCrop:
    method __init__ (line 514) | def __init__(self, size):
    method __call__ (line 517) | def __call__(self, image):
    method centerCrop (line 522) | def centerCrop(self, image, size):
  class ToTensor (line 537) | class ToTensor:
    method __call__ (line 543) | def __call__(self, image):
    method to_tensor (line 548) | def to_tensor(self, pic):
  class Normalize (line 592) | class Normalize:
    method __init__ (line 593) | def __init__(self, mean, std):
    method __call__ (line 597) | def __call__(self, image):
    method normalize (line 602) | def normalize(self, tensor, mean, std):
  function define_model (line 609) | def define_model(is_resnet, is_densenet, is_senet):
  class MonoDepthEstimator (line 633) | class MonoDepthEstimator:
    method __init__ (line 634) | def __init__(self, checkpoint="./pretrained_model/model_resnet"):
    method init_preprocessor (line 646) | def init_preprocessor(self):
    method preprocess (line 661) | def preprocess(self, image):
    method compute_depth (line 665) | def compute_depth(self, image):

FILE: habitat-lab/habitat_baselines/slambased/path_planners.py
  function safe_roi_2d (line 16) | def safe_roi_2d(array2d, ymin, ymax, xmin, xmax):
  function f2ind (line 21) | def f2ind(ten, i):
  function init_neights_to_channels (line 26) | def init_neights_to_channels(ks=3):
  class SoftArgMin (line 37) | class SoftArgMin(nn.Module):
    method __init__ (line 38) | def __init__(self, beta=5):
    method forward (line 43) | def forward(self, x, coords2d=None):
  class HardArgMin (line 53) | class HardArgMin(nn.Module):
    method __init__ (line 54) | def __init__(self):
    method forward (line 58) | def forward(self, x, coords2d=None):
  class DifferentiableStarPlanner (line 66) | class DifferentiableStarPlanner(nn.Module):
    method __init__ (line 67) | def __init__(
    method preprocess_obstacle_map (line 139) | def preprocess_obstacle_map(self, obstacle_map):
    method coords2grid (line 144) | def coords2grid(self, node_coords, h, w):
    method init_closelistmap (line 151) | def init_closelistmap(self):
    method init_openlistmap (line 154) | def init_openlistmap(self):
    method init_g_map (line 157) | def init_g_map(self):
    method safe_roi_2d (line 165) | def safe_roi_2d(self, ymin, ymax, xmin, xmax):
    method forward (line 173) | def forward(
    method calculate_local_path_costs (line 328) | def calculate_local_path_costs(self, non_obstacle_cost_map=None):
    method propagate_traversal (line 425) | def propagate_traversal(self, node_coords, close, g, coords):
    method get_clean_costmap_and_goodmask (line 466) | def get_clean_costmap_and_goodmask(self):
    method reconstruct_path (line 473) | def reconstruct_path(self):

FILE: habitat-lab/habitat_baselines/slambased/reprojection.py
  function p_zx (line 13) | def p_zx(p):
  function get_map_size_in_cells (line 17) | def get_map_size_in_cells(map_size_in_meters, cell_size_in_meters):
  function get_pos_diff (line 21) | def get_pos_diff(p_init, p_fin):
  function get_distance (line 25) | def get_distance(p_init, p_fin):
  function get_pos_diffs (line 29) | def get_pos_diffs(ps):
  function angle_to_pi_2_minus_pi_2 (line 33) | def angle_to_pi_2_minus_pi_2(angle):
  function get_direction (line 41) | def get_direction(p_init, p_fin, ang_th=0.2, pos_th=0.1):
  function reproject_local_to_global (line 56) | def reproject_local_to_global(xyz_local, p):
  function project2d_pcl_into_worldmap (line 78) | def project2d_pcl_into_worldmap(zx, map_size, cell_size):
  function get_pose2d (line 92) | def get_pose2d(poses6d):
  function get_rotation_matrix (line 99) | def get_rotation_matrix(angle_in_radians):
  function normalize_zx_ori (line 109) | def normalize_zx_ori(p):
  function add_rot_wps (line 125) | def add_rot_wps(p):
  function planned_path2tps (line 149) | def planned_path2tps(path, cell_size, map_size, agent_h, add_rot=False):
  function habitat_goalpos_to_tp (line 180) | def habitat_goalpos_to_tp(ro_phi, p_curr):
  function habitat_goalpos_to_mapgoal_pos (line 210) | def habitat_goalpos_to_mapgoal_pos(offset, p_curr, cell_size, map_size):
  function homogenize_p (line 224) | def homogenize_p(tps):
  function project_tps_into_worldmap (line 239) | def project_tps_into_worldmap(tps, cell_size, map_size, do_floor=True):
  function project_tps_into_worldmap_numpy (line 271) | def project_tps_into_worldmap_numpy(tps, slam_to_world, cell_size, map_s...

FILE: habitat-lab/habitat_baselines/slambased/utils.py
  function generate_2dgrid (line 14) | def generate_2dgrid(h, w, centered=False):
  function str2bool (line 27) | def str2bool(v):
  function resize_pil (line 36) | def resize_pil(np_img, size=128):
  function find_map_size (line 42) | def find_map_size(h, w):
  function gettimestr (line 51) | def gettimestr():

FILE: habitat-lab/habitat_baselines/utils/common.py
  class CustomFixedCategorical (line 46) | class CustomFixedCategorical(torch.distributions.Categorical):  # type: ...
    method sample (line 47) | def sample(
    method log_probs (line 52) | def log_probs(self, actions: Tensor) -> Tensor:
    method mode (line 61) | def mode(self):
  class CategoricalNet (line 65) | class CategoricalNet(nn.Module):
    method __init__ (line 66) | def __init__(self, num_inputs: int, num_outputs: int) -> None:
    method forward (line 74) | def forward(self, x: Tensor) -> CustomFixedCategorical:
  class CustomNormal (line 79) | class CustomNormal(torch.distributions.normal.Normal):
    method sample (line 80) | def sample(
    method log_probs (line 85) | def log_probs(self, actions) -> Tensor:
  class GaussianNet (line 90) | class GaussianNet(nn.Module):
    method __init__ (line 91) | def __init__(
    method forward (line 117) | def forward(self, x: Tensor) -> CustomNormal:
  function linear_decay (line 131) | def linear_decay(epoch: int, total_num_updates: int) -> float:
  class ObservationBatchingCache (line 145) | class ObservationBatchingCache:
    method get (line 151) | def get(
  function batch_obs (line 196) | def batch_obs(
  function get_checkpoint_id (line 281) | def get_checkpoint_id(ckpt_path: str) -> Optional[int]:
  function poll_checkpoint_folder (line 298) | def poll_checkpoint_folder(
  function generate_video (line 325) | def generate_video(
  function tensor_to_depth_images (line 370) | def tensor_to_depth_images(
  function tensor_to_bgr_images (line 388) | def tensor_to_bgr_images(
  function image_resize_shortest_edge (line 408) | def image_resize_shortest_edge(
  function center_crop (line 458) | def center_crop(
  function get_image_height_width (line 487) | def get_image_height_width(
  function overwrite_gym_box_shape (line 501) | def overwrite_gym_box_shape(box: Box, shape) -> Box:
  function get_scene_episode_dict (line 510) | def get_scene_episode_dict(episodes: List[Episode]) -> Dict:
  function base_plus_ext (line 524) | def base_plus_ext(path: str) -> Union[Tuple[str, str], Tuple[None, None]]:
  function valid_sample (line 536) | def valid_sample(sample: Optional[Any]) -> bool:
  function img_bytes_2_np_array (line 548) | def img_bytes_2_np_array(
  function create_tar_archive (line 570) | def create_tar_archive(archive_path: str, dataset_path: str) -> None:
  function delete_folder (line 581) | def delete_folder(path: str) -> None:
  function action_to_velocity_control (line 585) | def action_to_velocity_control(

FILE: habitat-lab/habitat_baselines/utils/env_utils.py
  function make_env_fn (line 14) | def make_env_fn(
  function construct_envs (line 36) | def construct_envs(

FILE: habitat-lab/habitat_baselines/utils/gym_adapter.py
  function flatten_dict (line 17) | def flatten_dict(d, parent_key=""):
  function smash_observation_space (line 29) | def smash_observation_space(obs_space, limit_keys):
  class HabGymWrapper (line 49) | class HabGymWrapper(gym.Env):
    method __init__ (line 88) | def __init__(self, env, save_orig_obs: bool = False):
    method step (line 167) | def step(self, action: np.ndarray):
    method direct_hab_step (line 177) | def direct_hab_step(self, action: Union[int, str, Dict[str, Any]]):
    method _is_space_flat (line 187) | def _is_space_flat(self, space_name):
    method _transform_obs (line 194) | def _transform_obs(self, obs):
    method reset (line 215) | def reset(self) -> Union[np.ndarray, Dict[str, np.ndarray]]:
    method render (line 220) | def render(self, mode: str = "rgb_array") -> np.ndarray:
    method close (line 231) | def close(self):

FILE: habitat-lab/habitat_baselines/utils/gym_definitions.py
  function _get_config_no_base_task_load (line 30) | def _get_config_no_base_task_load(cfg_file_path):
  function _make_habitat_gym_env (line 39) | def _make_habitat_gym_env(

FILE: habitat-lab/habitat_baselines/utils/render_wrapper.py
  function append_text_to_image (line 16) | def append_text_to_image(image: np.ndarray, text: List[str]):
  function overlay_frame (line 46) | def overlay_frame(frame, info, additional=None):
  class HabRenderWrapper (line 59) | class HabRenderWrapper(gym.Wrapper):
    method __init__ (line 76) | def __init__(self, env):
    method step (line 84) | def step(self, action):
    method reset (line 92) | def reset(self):
    method render (line 98) | def render(self, mode="rgb_array"):

FILE: habitat-lab/habitat_baselines/utils/visualizations/utils.py
  function save_rgb_results (line 25) | def save_rgb_results(
  function save_seg_results (line 41) | def save_seg_results(
  function save_depth_results (line 65) | def save_depth_results(
  function put_vqa_text_on_image (line 84) | def put_vqa_text_on_image(
  function save_vqa_image_results (line 136) | def save_vqa_image_results(

FILE: habitat-lab/setup.py
  class OptionedCommand (line 46) | class OptionedCommand:
    method initialize_options (line 56) | def initialize_options(self):
    method run (line 60) | def run(self):
  class InstallCommand (line 72) | class InstallCommand(OptionedCommand, DefaultInstallCommand):
  class DevelopCommand (line 79) | class DevelopCommand(OptionedCommand, DefaultDevelopCommand):

FILE: habitat-lab/test/test_baseline_agents.py
  function test_ppo_agents (line 36) | def test_ppo_agents(input_type, resolution):
  function test_simple_agents (line 73) | def test_simple_agents():

FILE: habitat-lab/test/test_baseline_trainers.py
  function _powerset (line 37) | def _powerset(s):
  function test_trainers (line 79) | def test_trainers(test_cfg_path, mode, gpu2gpu, observation_transforms):
  function test_cubemap_stiching (line 125) | def test_cubemap_stiching(
  function test_eval_config (line 230) | def test_eval_config():
  function __do_pause_test (line 252) | def __do_pause_test(num_envs, envs_to_pause):
  function test_pausing (line 318) | def test_pausing():
  function test_batch_obs (line 343) | def test_batch_obs(sensor_device, batched_device):

FILE: habitat-lab/test/test_config.py
  function test_merged_configs (line 15) | def test_merged_configs():
  function test_new_keys_merged_configs (line 26) | def test_new_keys_merged_configs():
  function test_overwrite_options (line 40) | def test_overwrite_options():

FILE: habitat-lab/test/test_dataset.py
  function _construct_dataset (line 15) | def _construct_dataset(num_episodes, num_groups=10):
  function test_scene_ids (line 30) | def test_scene_ids():
  function test_get_scene_episodes (line 35) | def test_get_scene_episodes():
  function test_filter_episodes (line 44) | def test_filter_episodes():
  function test_get_splits_even_split_possible (line 56) | def test_get_splits_even_split_possible():
  function test_get_splits_with_remainder (line 64) | def test_get_splits_with_remainder():
  function test_get_splits_num_episodes_specified (line 72) | def test_get_splits_num_episodes_specified():
  function test_get_splits_collate_scenes (line 99) | def test_get_splits_collate_scenes():
  function test_get_splits_sort_by_episode_id (line 155) | def test_get_splits_sort_by_episode_id():
  function test_get_splits_func (line 170) | def test_get_splits_func(num_episodes: int, num_splits: int):
  function test_sample_episodes (line 183) | def test_sample_episodes():
  function test_iterator_cycle (line 207) | def test_iterator_cycle():
  function test_iterator_shuffle (line 223) | def test_iterator_shuffle():
  function test_iterator_scene_switching_episodes (line 244) | def test_iterator_scene_switching_episodes():
  function test_iterator_scene_switching_episodes_without_shuffle_cycle (line 294) | def test_iterator_scene_switching_episodes_without_shuffle_cycle():
  function test_iterator_scene_switching_steps (line 317) | def test_iterator_scene_switching_steps():
  function test_preserve_order (line 356) | def test_preserve_order():
  function test_reset_goals (line 365) | def test_reset_goals():

FILE: habitat-lab/test/test_ddppo_reduce.py
  function _worker_fn (line 26) | def _worker_fn(
  function test_ddppo_reduce (line 120) | def test_ddppo_reduce(unused_params: bool):

FILE: habitat-lab/test/test_demo_notebook.py
  function test_demo_notebook (line 14) | def test_demo_notebook():

FILE: habitat-lab/test/test_examples.py
  function run_main (line 10) | def run_main(*args):
  function powerset (line 23) | def powerset(iterable):
  function run_main_subproc (line 30) | def run_main_subproc(args):
  function test_example_modules (line 56) | def test_example_modules(args):
  function test_rearrange_example_modules (line 69) | def test_rearrange_example_modules(args):

FILE: habitat-lab/test/test_gym_wrapper.py
  function test_gym_wrapper_contract (line 36) | def test_gym_wrapper_contract(config_file, overrides, expected_action_dim):
  function test_full_gym_wrapper (line 71) | def test_full_gym_wrapper(config_file):
  function test_auto_gym_wrapper (line 100) | def test_auto_gym_wrapper(test_cfg_path):

FILE: habitat-lab/test/test_habitat_env.py
  class DummyRLEnv (line 25) | class DummyRLEnv(habitat.RLEnv):
    method __init__ (line 26) | def __init__(self, config, dataset=None, env_ind=0):
    method get_reward_range (line 30) | def get_reward_range(self):
    method get_reward (line 33) | def get_reward(self, observations):
    method get_done (line 36) | def get_done(self, observations):
    method get_info (line 42) | def get_info(self, observations):
    method get_env_ind (line 45) | def get_env_ind(self):
    method set_env_ind (line 48) | def set_env_ind(self, new_env_ind):
  function _load_test_data (line 52) | def _load_test_data():
  function _vec_env_test_fn (line 76) | def _vec_env_test_fn(configs, datasets, multiprocessing_start_method, gp...
  function test_vectorized_envs (line 101) | def test_vectorized_envs(multiprocessing_start_method, gpu2gpu):
  function test_with_scope (line 128) | def test_with_scope():
  function test_number_of_episodes (line 140) | def test_number_of_episodes():
  function test_threaded_vectorized_env (line 150) | def test_threaded_vectorized_env():
  function test_env (line 165) | def test_env(gpu2gpu):
  function make_rl_env (line 216) | def make_rl_env(config, dataset, rank: int = 0):
  function test_rl_vectorized_envs (line 229) | def test_rl_vectorized_envs(gpu2gpu):
  function test_rl_env (line 278) | def test_rl_env(gpu2gpu):
  function _make_dummy_env_func (line 330) | def _make_dummy_env_func(config, dataset, env_id):
  function test_vec_env_call_func (line 334) | def test_vec_env_call_func():
  function test_close_with_paused (line 376) | def test_close_with_paused():
  function test_action_space_shortest_path (line 393) | def test_action_space_shortest_path():
  function test_set_episodes (line 438) | def test_set_episodes(set_method):

FILE: habitat-lab/test/test_habitat_example.py
  function test_readme_example (line 20) | def test_readme_example():
  function test_visualizations_example (line 28) | def test_visualizations_example():
  function test_shortest_path_follower_example (line 36) | def test_shortest_path_follower_example():
  function test_register_new_sensors_and_measures (line 44) | def test_register_new_sensors_and_measures():
  function test_new_actions (line 53) | def test_new_actions():

FILE: habitat-lab/test/test_habitat_sim.py
  function init_sim (line 18) | def init_sim():
  function test_sim_trajectory (line 25) | def test_sim_trajectory():
  function test_sim_no_sensors (line 74) | def test_sim_no_sensors():
  function test_sim_geodesic_distance (line 84) | def test_sim_geodesic_distance():

FILE: habitat-lab/test/test_habitat_task.py
  function test_task_actions (line 22) | def test_task_actions():
  function test_task_actions_sampling_for_teleport (line 50) | def test_task_actions_sampling_for_teleport():
  function test_task_actions_sampling (line 79) | def test_task_actions_sampling(config_file):

FILE: habitat-lab/test/test_install.py
  function test_habitat_install (line 11) | def test_habitat_install():

FILE: habitat-lab/test/test_motion_plan.py
  function test_pick_motion_planning (line 26) | def test_pick_motion_planning():

FILE: habitat-lab/test/test_mp3d_eqa.py
  function get_minos_for_sim_eqa_config (line 50) | def get_minos_for_sim_eqa_config():
  function check_json_serializaiton (line 73) | def check_json_serializaiton(dataset: habitat.Dataset):
  function test_mp3d_eqa_dataset (line 89) | def test_mp3d_eqa_dataset():
  function test_dataset_splitting (line 105) | def test_dataset_splitting(split):
  function test_mp3d_eqa_sim (line 154) | def test_mp3d_eqa_sim():
  function test_mp3d_eqa_sim_correspondence (line 186) | def test_mp3d_eqa_sim_correspondence():
  function test_eqa_task (line 276) | def test_eqa_task():

FILE: habitat-lab/test/test_object_nav_task.py
  function check_json_serializaiton (line 25) | def check_json_serializaiton(dataset: habitat.Dataset):
  function test_mp3d_object_nav_dataset (line 44) | def test_mp3d_object_nav_dataset():
  function test_dataset_splitting (line 65) | def test_dataset_splitting(split):
  function test_object_nav_task (line 112) | def test_object_nav_task():

FILE: habitat-lab/test/test_pointnav_dataset.py
  function check_json_serializaiton (line 35) | def check_json_serializaiton(dataset: habitat.Dataset):
  function test_single_pointnav_dataset (line 51) | def test_single_pointnav_dataset():
  function test_multiple_files_scene_path (line 67) | def test_multiple_files_scene_path():
  function test_multiple_files_pointnav_dataset (line 95) | def test_multiple_files_pointnav_dataset():
  function test_dataset_splitting (line 116) | def test_dataset_splitting(split):
  function check_shortest_path (line 163) | def check_shortest_path(env, episode):
  function test_pointnav_episode_generator (line 192) | def test_pointnav_episode_generator():

FILE: habitat-lab/test/test_pyrobot.py
  class CameraMock (line 14) | class CameraMock:
    method get_rgb (line 15) | def get_rgb(self):
    method get_depth (line 18) | def get_depth(self):
    method reset (line 21) | def reset(self):
    method step (line 24) | def step(self, *args, **kwargs):
  class RobotMock (line 28) | class RobotMock:  # noqa: SIM119
    method __init__ (line 29) | def __init__(self, *args, **kwargs):
  class BaseMock (line 34) | class BaseMock:
    method __init__ (line 35) | def __init__(self, *args, **kwargs):
    method go_to_relative (line 39) | def go_to_relative(self, *args, **kwargs):
  function test_pyrobot (line 43) | def test_pyrobot(mocker):

FILE: habitat-lab/test/test_r2r_vln.py
  function check_json_serializaiton (line 23) | def check_json_serializaiton(dataset: habitat.Dataset):
  function test_r2r_vln_dataset (line 39) | def test_r2r_vln_dataset():
  function test_dataset_splitting (line 58) | def test_dataset_splitting(split):
  function test_r2r_vln_sim (line 107) | def test_r2r_vln_sim():

FILE: habitat-lab/test/test_rearrange_task.py
  function check_json_serialization (line 31) | def check_json_serialization(dataset: habitat.Dataset):
  function test_rearrange_dataset (line 51) | def test_rearrange_dataset():
  function test_rearrange_basline_envs (line 72) | def test_rearrange_basline_envs(test_cfg_path):
  function test_rearrange_tasks (line 99) | def test_rearrange_tasks(test_cfg_path):
  function test_rearrange_episode_generator (line 119) | def test_rearrange_episode_generator(

FILE: habitat-lab/test/test_rnn_state_encoder.py
  function test_rnn_state_encoder (line 16) | def test_rnn_state_encoder():

FILE: habitat-lab/test/test_sensors.py
  function _random_episode (line 32) | def _random_episode(env, config):
  function test_state_sensors (line 54) | def test_state_sensors():
  function test_tactile (line 93) | def test_tactile():
  function test_collisions (line 115) | def test_collisions():
  function test_pointgoal_sensor (line 155) | def test_pointgoal_sensor():
  function test_pointgoal_with_gps_compass_sensor (line 195) | def test_pointgoal_with_gps_compass_sensor():
  function test_imagegoal_sensor (line 257) | def test_imagegoal_sensor():
  function test_get_observations_at (line 317) | def test_get_observations_at():
  function smoke_test_sensor (line 381) | def smoke_test_sensor(config, N_STEPS=100):
  function test_smoke_not_pinhole_sensors (line 426) | def test_smoke_not_pinhole_sensors(sensors, cuda):
  function test_smoke_pinhole_sensors (line 447) | def test_smoke_pinhole_sensors(sensor, sensor_subtype, cuda):
  function test_noise_models_rgbd (line 463) | def test_noise_models_rgbd():

FILE: habitat-lab/test/test_spaces.py
  function test_empty_space (line 12) | def test_empty_space():
  function test_action_space (line 19) | def test_action_space():
  function test_list_space (line 48) | def test_list_space():

FILE: habitat-lab/test/test_tensor_dict.py
  function test_tensor_dict_constructor (line 22) | def test_tensor_dict_constructor():
  function test_tensor_dict_to_tree (line 35) | def test_tensor_dict_to_tree():
  function test_tensor_dict_str_index (line 42) | def test_tensor_dict_str_index():
  function test_tensor_dict_index (line 55) | def test_tensor_dict_index():
  function test_tensor_dict_map (line 81) | def test_tensor_dict_map():

FILE: habitat-lab/test/test_visual_utils.py
  function test_observations_to_image (line 12) | def test_observations_to_image():
  function test_different_dim_observations_to_image (line 36) | def test_different_dim_observations_to_image():

FILE: scenegraph.py
  class RoomNode (line 35) | class RoomNode():
    method __init__ (line 36) | def __init__(self, caption):
  class GroupNode (line 43) | class GroupNode():
    method __init__ (line 44) | def __init__(self, caption=''):
    method __lt__ (line 53) | def __lt__(self, other):
    method get_graph (line 56) | def get_graph(self):
    method graph_to_text (line 67) | def graph_to_text(self, nodes, edges):
  class ObjectNode (line 73) | class ObjectNode():
    method __init__ (line 74) | def __init__(self):
    method __lt__ (line 87) | def __lt__(self, other):
    method add_edge (line 90) | def add_edge(self, edge):
    method remove_edge (line 93) | def remove_edge(self, edge):
    method set_caption (line 96) | def set_caption(self, new_caption):
    method set_object (line 107) | def set_object(self, object):
    method set_center (line 111) | def set_center(self, center):
  class Edge (line 115) | class Edge():
    method __init__ (line 116) | def __init__(self, node1, node2):
    method set_relation (line 123) | def set_relation(self, relation):
    method delete (line 126) | def delete(self):
    method text (line 130) | def text(self):
  class SceneGraph (line 135) | class SceneGraph():
    method __init__ (line 136) | def __init__(self, map_resolution, map_size_cm, map_size, camera_matri...
    method reset (line 209) | def reset(self):
    method set_cfg (line 226) | def set_cfg(self):
    method set_agent (line 234) | def set_agent(self, agent):
    method set_obj_goal (line 237) | def set_obj_goal(self, obj_goal, obj_goal_sg):
    method set_navigate_steps (line 243) | def set_navigate_steps(self, navigate_steps):
    method set_room_map (line 246) | def set_room_map(self, room_map):
    method set_fbe_free_map (line 249) | def set_fbe_free_map(self, fbe_free_map):
    method set_observations (line 252) | def set_observations(self, observations):
    method set_frontier_map (line 258) | def set_frontier_map(self, frontier_map):
    method set_full_map (line 261) | def set_full_map(self, full_map):
    method set_fbe_free_map (line 264) | def set_fbe_free_map(self, fbe_free_map):
    method set_full_pose (line 267) | def set_full_pose(self, full_pose):
    method get_nodes (line 270) | def get_nodes(self):
    method get_edges (line 273) | def get_edges(self):
    method get_seg_xyxy (line 280) | def get_seg_xyxy(self):
    method get_seg_caption (line 283) | def get_seg_caption(self):
    method init_room_nodes (line 286) | def init_room_nodes(self):
    method get_sam_mask_generator (line 293) | def get_sam_mask_generator(self, variant:str, device) -> SamAutomaticM...
    method get_sam_segmentation_dense (line 321) | def get_sam_segmentation_dense(
    method compute_clip_features (line 402) | def compute_clip_features(self, image, detections, clip_model, clip_pr...
    method process_cfg (line 458) | def process_cfg(self, cfg: DictConfig):
    method crop_image_and_mask (line 478) | def crop_image_and_mask(self, image: Image, mask: np.ndarray, x1: int,...
    method get_pose_matrix (line 509) | def get_pose_matrix(self):
    method segment2d (line 521) | def segment2d(self):
    method mapping3d (line 553) | def mapping3d(self):
    method get_caption (line 599) | def get_caption(self):
    method update_node (line 609) | def update_node(self):
    method update_edge (line 647) | def update_edge(self):
    method update_group (line 706) | def update_group(self):
    method insert_goal (line 723) | def insert_goal(self, goal=None):
    method update_scenegraph (line 750) | def update_scenegraph(self):
    method get_llm_response (line 759) | def get_llm_response(self, prompt):
    method get_vlm_response (line 769) | def get_vlm_response(self, prompt, image):
    method find_modes (line 784) | def find_modes(self, lst):
    method get_joint_image (line 793) | def get_joint_image(self, node1, node2):
    method score (line 812) | def score(self, frontier_locations_16, num_16_frontiers):
    method discriminate_relation (line 847) | def discriminate_relation(self, edge):
    method perception (line 875) | def perception(self):
    method graph_corr (line 882) | def graph_corr(self, goal, graph):

FILE: segment_anything/scripts/amg.py
  function write_masks_to_folder (line 152) | def write_masks_to_folder(masks: List[Dict[str, Any]], path: str) -> None:
  function get_amg_kwargs (line 177) | def get_amg_kwargs(args):
  function main (line 195) | def main(args: argparse.Namespace) -> None:

FILE: segment_anything/scripts/export_onnx_model.py
  function run_export (line 97) | def run_export(
  function to_numpy (line 173) | def to_numpy(tensor):

FILE: segment_anything/segment_anything/automatic_mask_generator.py
  class SamAutomaticMaskGenerator (line 35) | class SamAutomaticMaskGenerator:
    method __init__ (line 36) | def __init__(
    method generate (line 137) | def generate(self, image: np.ndarray) -> List[Dict[str, Any]]:
    method _generate_masks (line 197) | def _generate_masks(self, image: np.ndarray) -> MaskData:
    method _process_crop (line 225) | def _process_crop(
    method _process_batch (line 266) | def _process_batch(
    method postprocess_small_regions (line 324) | def postprocess_small_regions(

FILE: segment_anything/segment_anything/build_sam.py
  function build_sam_vit_h (line 14) | def build_sam_vit_h(checkpoint=None):
  function build_sam_vit_l (line 27) | def build_sam_vit_l(checkpoint=None):
  function build_sam_vit_b (line 37) | def build_sam_vit_b(checkpoint=None):
  function _build_sam (line 55) | def _build_sam(

FILE: segment_anything/segment_anything/build_sam_hq.py
  function build_sam_hq_vit_h (line 14) | def build_sam_hq_vit_h(checkpoint=None):
  function build_sam_hq_vit_l (line 27) | def build_sam_hq_vit_l(checkpoint=None):
  function build_sam_hq_vit_b (line 37) | def build_sam_hq_vit_b(checkpoint=None):
  function _build_sam (line 55) | def _build_sam(

FILE: segment_anything/segment_anything/modeling/common.py
  class MLPBlock (line 13) | class MLPBlock(nn.Module):
    method __init__ (line 14) | def __init__(
    method forward (line 25) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class LayerNorm2d (line 31) | class LayerNorm2d(nn.Module):
    method __init__ (line 32) | def __init__(self, num_channels: int, eps: float = 1e-6) -> None:
    method forward (line 38) | def forward(self, x: torch.Tensor) -> torch.Tensor:

FILE: segment_anything/segment_anything/modeling/image_encoder.py
  class ImageEncoderViT (line 17) | class ImageEncoderViT(nn.Module):
    method __init__ (line 18) | def __init__(
    method forward (line 106) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class Block (line 122) | class Block(nn.Module):
    method __init__ (line 125) | def __init__(
    method forward (line 169) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class Attention (line 188) | class Attention(nn.Module):
    method __init__ (line 191) | def __init__(
    method forward (line 227) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  function window_partition (line 246) | def window_partition(x: torch.Tensor, window_size: int) -> Tuple[torch.T...
  function window_unpartition (line 270) | def window_unpartition(
  function get_rel_pos (line 295) | def get_rel_pos(q_size: int, k_size: int, rel_pos: torch.Tensor) -> torc...
  function add_decomposed_rel_pos (line 328) | def add_decomposed_rel_pos(
  class PatchEmbed (line 367) | class PatchEmbed(nn.Module):
    method __init__ (line 372) | def __init__(
    method forward (line 394) | def forward(self, x: torch.Tensor) -> torch.Tensor:

FILE: segment_anything/segment_anything/modeling/mask_decoder.py
  class MaskDecoder (line 16) | class MaskDecoder(nn.Module):
    method __init__ (line 17) | def __init__(
    method forward (line 71) | def forward(
    method predict_masks (line 114) | def predict_masks(
  class MLP (line 156) | class MLP(nn.Module):
    method __init__ (line 157) | def __init__(
    method forward (line 173) | def forward(self, x):

FILE: segment_anything/segment_anything/modeling/mask_decoder_hq.py
  class MaskDecoderHQ (line 17) | class MaskDecoderHQ(nn.Module):
    method __init__ (line 18) | def __init__(
    method forward (line 99) | def forward(
    method predict_masks (line 158) | def predict_masks(
  class MLP (line 210) | class MLP(nn.Module):
    method __init__ (line 211) | def __init__(
    method forward (line 227) | def forward(self, x):

FILE: segment_anything/segment_anything/modeling/prompt_encoder.py
  class PromptEncoder (line 16) | class PromptEncoder(nn.Module):
    method __init__ (line 17) | def __init__(
    method get_dense_pe (line 62) | def get_dense_pe(self) -> torch.Tensor:
    method _embed_points (line 73) | def _embed_points(
    method _embed_boxes (line 93) | def _embed_boxes(self, boxes: torch.Tensor) -> torch.Tensor:
    method _embed_masks (line 102) | def _embed_masks(self, masks: torch.Tensor) -> torch.Tensor:
    method _get_batch_size (line 107) | def _get_batch_size(
    method _get_device (line 125) | def _get_device(self) -> torch.device:
    method forward (line 128) | def forward(
  class PositionEmbeddingRandom (line 171) | class PositionEmbeddingRandom(nn.Module):
    method __init__ (line 176) | def __init__(self, num_pos_feats: int = 64, scale: Optional[float] = N...
    method _pe_encoding (line 185) | def _pe_encoding(self, coords: torch.Tensor) -> torch.Tensor:
    method forward (line 194) | def forward(self, size: Tuple[int, int]) -> torch.Tensor:
    method forward_with_coords (line 207) | def forward_with_coords(

FILE: segment_anything/segment_anything/modeling/sam.py
  class Sam (line 18) | class Sam(nn.Module):
    method __init__ (line 22) | def __init__(
    method device (line 50) | def device(self) -> Any:
    method forward (line 54) | def forward(
    method postprocess_masks (line 133) | def postprocess_masks(
    method preprocess (line 164) | def preprocess(self, x: torch.Tensor) -> torch.Tensor:

FILE: segment_anything/segment_anything/modeling/transformer.py
  class TwoWayTransformer (line 16) | class TwoWayTransformer(nn.Module):
    method __init__ (line 17) | def __init__(
    method forward (line 62) | def forward(
  class TwoWayAttentionBlock (line 109) | class TwoWayAttentionBlock(nn.Module):
    method __init__ (line 110) | def __init__(
    method forward (line 151) | def forward(
  class Attention (line 185) | class Attention(nn.Module):
    method __init__ (line 191) | def __init__(
    method _separate_heads (line 208) | def _separate_heads(self, x: Tensor, num_heads: int) -> Tensor:
    method _recombine_heads (line 213) | def _recombine_heads(self, x: Tensor) -> Tensor:
    method forward (line 218) | def forward(self, q: Tensor, k: Tensor, v: Tensor) -> Tensor:

FILE: segment_anything/segment_anything/predictor.py
  class SamPredictor (line 17) | class SamPredictor:
    method __init__ (line 18) | def __init__(
    method set_image (line 34) | def set_image(
    method set_torch_image (line 65) | def set_torch_image(
    method predict (line 94) | def predict(
    method predict_torch (line 173) | def predict_torch(
    method get_image_embedding (line 252) | def get_image_embedding(self) -> torch.Tensor:
    method device (line 266) | def device(self) -> torch.device:
    method reset_image (line 269) | def reset_image(self) -> None:

FILE: segment_anything/segment_anything/utils/amg.py
  class MaskData (line 16) | class MaskData:
    method __init__ (line 22) | def __init__(self, **kwargs) -> None:
    method __setitem__ (line 29) | def __setitem__(self, key: str, item: Any) -> None:
    method __delitem__ (line 35) | def __delitem__(self, key: str) -> None:
    method __getitem__ (line 38) | def __getitem__(self, key: str) -> Any:
    method items (line 41) | def items(self) -> ItemsView[str, Any]:
    method filter (line 44) | def filter(self, keep: torch.Tensor) -> None:
    method cat (line 59) | def cat(self, new_stats: "MaskData") -> None:
    method to_numpy (line 72) | def to_numpy(self) -> None:
  function is_box_near_crop_edge (line 78) | def is_box_near_crop_edge(
  function box_xyxy_to_xywh (line 91) | def box_xyxy_to_xywh(box_xyxy: torch.Tensor) -> torch.Tensor:
  function batch_iterator (line 98) | def batch_iterator(batch_size: int, *args) -> Generator[List[Any], None,...
  function mask_to_rle_pytorch (line 107) | def mask_to_rle_pytorch(tensor: torch.Tensor) -> List[Dict[str, Any]]:
  function rle_to_mask (line 138) | def rle_to_mask(rle: Dict[str, Any]) -> np.ndarray:
  function area_from_rle (line 152) | def area_from_rle(rle: Dict[str, Any]) -> int:
  function calculate_stability_score (line 156) | def calculate_stability_score(
  function build_point_grid (line 179) | def build_point_grid(n_per_side: int) -> np.ndarray:
  function build_all_layer_point_grids (line 189) | def build_all_layer_point_grids(
  function generate_crop_boxes (line 200) | def generate_crop_boxes(
  function uncrop_boxes_xyxy (line 237) | def uncrop_boxes_xyxy(boxes: torch.Tensor, crop_box: List[int]) -> torch...
  function uncrop_points (line 246) | def uncrop_points(points: torch.Tensor, crop_box: List[int]) -> torch.Te...
  function uncrop_masks (line 255) | def uncrop_masks(
  function remove_small_regions (line 267) | def remove_small_regions(
  function coco_encode_rle (line 294) | def coco_encode_rle(uncompressed_rle: Dict[str, Any]) -> Dict[str, Any]:
  function batched_mask_to_box (line 303) | def batched_mask_to_box(masks: torch.Tensor) -> torch.Tensor:

FILE: segment_anything/segment_anything/utils/onnx.py
  class SamOnnxModel (line 17) | class SamOnnxModel(nn.Module):
    method __init__ (line 25) | def __init__(
    method resize_longest_image_size (line 42) | def resize_longest_image_size(
    method _embed_points (line 51) | def _embed_points(self, point_coords: torch.Tensor, point_labels: torc...
    method _embed_masks (line 69) | def _embed_masks(self, input_mask: torch.Tensor, has_mask_input: torch...
    method mask_postprocessing (line 76) | def mask_postprocessing(self, masks: torch.Tensor, orig_im_size: torch...
    method select_masks (line 92) | def select_masks(
    method forward (line 108) | def forward(

FILE: segment_anything/segment_anything/utils/transforms.py
  class ResizeLongestSide (line 16) | class ResizeLongestSide:
    method __init__ (line 23) | def __init__(self, target_length: int) -> None:
    method apply_image (line 26) | def apply_image(self, image: np.ndarray) -> np.ndarray:
    method apply_coords (line 33) | def apply_coords(self, coords: np.ndarray, original_size: Tuple[int, ....
    method apply_boxes (line 47) | def apply_boxes(self, boxes: np.ndarray, original_size: Tuple[int, ......
    method apply_image_torch (line 55) | def apply_image_torch(self, image: torch.Tensor) -> torch.Tensor:
    method apply_coords_torch (line 67) | def apply_coords_torch(
    method apply_boxes_torch (line 83) | def apply_boxes_torch(
    method get_preprocess_shape (line 94) | def get_preprocess_shape(oldh: int, oldw: int, long_side_length: int) ...

FILE: tools/agent.py
  class ActionSpec (line 37) | class ActionSpec:
  function _default_action_space (line 48) | def _default_action_space() -> Dict[str, ActionSpec]:
  function _triple_zero (line 56) | def _triple_zero() -> np.ndarray:
  function _default_quaternion (line 60) | def _default_quaternion() -> qt.quaternion:
  class SixDOFPose (line 65) | class SixDOFPose:
  class AgentState (line 79) | class AgentState:
  class AgentConfiguration (line 95) | class AgentConfiguration:
  class Agent (line 104) | class Agent:
    method __init__ (line 128) | def __init__(
    method reconfigure (line 144) | def reconfigure(
    method _add_sensor (line 162) | def _add_sensor(
    method act (line 174) | def act(self, action_id: Any) -> bool:
    method get_state (line 203) | def get_state(self) -> AgentState:
    method set_state (line 220) | def set_state(
    method scene_node (line 282) | def scene_node(self) -> SceneNode:
    method state (line 287) | def state(self):
    method state (line 298) | def state(self, new_state):
    method close (line 303) | def close(self) -> None:

FILE: tools/download_mp.py
  function get_release_scans (line 53) | def get_release_scans(release_file):
  function download_release (line 62) | def download_release(release_scans, out_dir, file_types):
  function download_file (line 70) | def download_file(url, out_file):
  function download_scan (line 82) | def download_scan(scan_id, out_dir, file_types):
  function download_task_data (line 93) | def download_task_data(task_data, out_dir):
  function main (line 108) | def main():

FILE: utils/image_process.py
  function line_list (line 6) | def line_list(text, line_length=80):
  function add_text (line 12) | def add_text(image: np.ndarray, text: str, position=(50, 50), font=cv2.F...
  function add_text_list (line 16) | def add_text_list(image: np.ndarray, text_list: list, position=(50, 50),...
  function add_rectangle (line 22) | def add_rectangle(image: np.ndarray, top_left: tuple, bottom_right: tupl...
  function add_resized_image (line 26) | def add_resized_image(base_image: np.ndarray, overlay_image: np.ndarray,...
  function crop_around_point (line 39) | def crop_around_point(image: np.ndarray, point: tuple, size: tuple):
  function draw_agent (line 64) | def draw_agent(agent, map, pose, agent_size, color_index, alpha=1):
  function draw_goal (line 71) | def draw_goal(agent, map, goal_size, color_index):

FILE: utils/utils_fmm/control_helper.py
  function _which_direction (line 20) | def _which_direction(y):
  function _which_direction_angle (line 37) | def _which_direction_angle(start_o):
  function get_valid_directions (line 56) | def get_valid_directions(goal_loc):
  function _check_five_pixels_ahead_map_pred_for_moving (line 73) | def _check_five_pixels_ahead_map_pred_for_moving(args, grid, start, xy):
  function _add_cross_dilation_one_center (line 103) | def _add_cross_dilation_one_center(goal,  goal_loc, magnitude, additiona...
  function _add_cross_dilation (line 126) | def _add_cross_dilation(goal, magnitude, additional_thickness):
  function _where_connected_to_curr_pose (line 134) | def _where_connected_to_curr_pose(start, traversible, seed, visited):
  function _planner_broken (line 158) | def _planner_broken(fmm_dist, goal, traversible, start,  seed, visited):
  function _get_closest_goal (line 165) | def _get_closest_goal(start, goal):
  function _block_goal (line 172) | def _block_goal(centers, goal, original_goal, goal_found):
  function _get_center_goal (line 176) | def _get_center_goal(goal, pointer=None):
  function _get_approximate_success (line 191) | def _get_approximate_success(prev_rgb, frame, action):
  function _append_to_actseq (line 210) | def _append_to_actseq(success, actions, api_action):

FILE: utils/utils_fmm/depth_utils.py
  function get_camera_matrix (line 8) | def get_camera_matrix(width, height, fov):
  function get_point_cloud_from_z (line 18) | def get_point_cloud_from_z(Y, camera_matrix, scale=1):
  function transform_camera_view (line 41) | def transform_camera_view(XYZ, sensor_height, camera_elevation_degree):
  function transform_pose (line 58) | def transform_pose(XYZ, current_pose):
  function bin_points (line 75) | def bin_points(XYZ_cms, map_size, z_bins, xy_resolution):
  function get_point_cloud_from_z_t (line 106) | def get_point_cloud_from_z_t(Y_t, camera_matrix, device, scale=1):
  function transform_camera_view_t (line 131) | def transform_camera_view_t(XYZ, sensor_height, camera_elevation_degree,...
  function transform_camera_view_t_multiple (line 149) | def transform_camera_view_t_multiple(XYZ, sensor_height, camera_elevatio...
  function transform_pose_t (line 185) | def transform_pose_t(XYZ, current_pose, device):
  function splat_feat_nd (line 203) | def splat_feat_nd(init_grid, feat, coords):

FILE: utils/utils_fmm/fmm_planner.py
  function get_mask (line 10) | def get_mask(sx, sy, scale, step_size):
  function get_dist (line 43) | def get_dist(sx, sy, scale, step_size):
  function moving_avg (line 53) | def moving_avg(a, n=2):
  class FMMPlanner (line 67) | class FMMPlanner():
    method __init__ (line 68) | def __init__(self, traversible, args, scale=1, step_size=5):
    method set_goal (line 87) | def set_goal(self, goal, auto_improve=False):
    method set_multi_goal (line 101) | def set_multi_goal(self, goal_map, state):
    method get_short_term_goal (line 120) | def get_short_term_goal(self, state, found_goal = 0, decrease_stop_con...
    method _find_nearest_goal (line 180) | def _find_nearest_goal(self, goal, state=None):

FILE: utils/utils_fmm/mapping.py
  class Semantic_Mapping (line 15) | class Semantic_Mapping(nn.Module):
    method __init__ (line 21) | def __init__(self, agent, max_height=None, min_height=None, num_cats=1):
    method set_view_angles (line 60) | def set_view_angles(self, view_angle):
    method forward (line 64) | def forward(self, depth, pose_obs, maps_last, type_mask=None, type_pro...
    method forward_ (line 189) | def forward_(self, depth, pose_obs, maps_last, type_mask=None, type_pr...

FILE: utils/utils_fmm/model.py
  function get_grid (line 7) | def get_grid(pose, grid_size, device):
  class ChannelPool (line 47) | class ChannelPool(nn.MaxPool1d):
    method forward (line 48) | def forward(self, x):
  class AddBias (line 59) | class AddBias(nn.Module):
    method __init__ (line 60) | def __init__(self, bias):
    method forward (line 64) | def forward(self, x):
  class Flatten (line 74) | class Flatten(nn.Module):
    method forward (line 75) | def forward(self, x):
  class NNBase (line 80) | class NNBase(nn.Module):
    method __init__ (line 82) | def __init__(self, recurrent, recurrent_input_size, hidden_size):
    method is_recurrent (line 96) | def is_recurrent(self):
    method rec_state_size (line 100) | def rec_state_size(self):
    method output_size (line 106) | def output_size(self):
    method _forward_gru (line 109) | def _forward_gru(self, x, hxs, masks):

FILE: utils/utils_fmm/pose_utils.py
  function get_l2_distance (line 4) | def get_l2_distance(x1, x2, y1, y2):
  function get_rel_pose_change (line 11) | def get_rel_pose_change(pos2, pos1):
  function get_new_pose (line 24) | def get_new_pose(pose, rel_pose_change):
  function threshold_poses (line 39) | def threshold_poses(coords, shape):

FILE: utils/utils_fmm/rotation_utils.py
  function normalize (line 23) | def normalize(v):
  function get_r_matrix (line 27) | def get_r_matrix(ax_, angle):
  function r_between (line 40) | def r_between(v_from_, v_to_):
  function rotate_camera_to_point_at (line 48) | def rotate_camera_to_point_at(up_from, lookat_from, up_to, lookat_to):

FILE: utils/utils_glip.py
  function get_iou (line 61) | def get_iou(bb1, bb2):

FILE: utils/utils_scenegraph/grounded_sam_demo.py
  function load_image (line 32) | def load_image(image_path):
  function load_model (line 47) | def load_model(model_config_path, model_checkpoint_path, bert_base_uncas...
  function get_grounding_output (line 59) | def get_grounding_output(model, image, caption, box_threshold, text_thre...
  function show_mask (line 94) | def show_mask(mask, ax, random_color=False):
  function show_box (line 104) | def show_box(box, ax, label):
  function save_mask_data (line 111) | def save_mask_data(output_dir, mask_list, box_list, label_list):

FILE: utils/utils_scenegraph/iou.py
  function expand_3d_box (line 5) | def expand_3d_box(bbox: torch.Tensor, eps=0.02) -> torch.Tensor:
  function compute_3d_iou_accuracte_batch (line 45) | def compute_3d_iou_accuracte_batch(bbox1, bbox2):
  function compute_iou_batch (line 68) | def compute_iou_batch(bbox1: torch.Tensor, bbox2: torch.Tensor) -> torch...
  function mask_subtract_contained (line 108) | def mask_subtract_contained(xyxy: np.ndarray, mask: np.ndarray, th1=0.8,...

FILE: utils/utils_scenegraph/mapping.py
  function compute_spatial_similarities (line 7) | def compute_spatial_similarities(cfg, detection_list: DetectionList, obj...
  function merge_detections_to_objects (line 37) | def merge_detections_to_objects(

FILE: utils/utils_scenegraph/slam_classes.py
  function to_numpy (line 10) | def to_numpy(tensor):
  function to_tensor (line 15) | def to_tensor(numpy_array, device=None):
  class DetectionList (line 23) | class DetectionList(list):
    method get_values (line 24) | def get_values(self, key, idx:int=None):
    method get_stacked_values_torch (line 30) | def get_stacked_values_torch(self, key, idx:int=None):
    method get_stacked_values_numpy (line 44) | def get_stacked_values_numpy(self, key, idx:int=None):
    method __add__ (line 48) | def __add__(self, other):
    method __iadd__ (line 53) | def __iadd__(self, other):
    method slice_by_indices (line 57) | def slice_by_indices(self, index):
    method slice_by_mask (line 66) | def slice_by_mask(self, mask):
    method get_most_common_class (line 76) | def get_most_common_class(self):
    method color_by_most_common_classes (line 84) | def color_by_most_common_classes(self, colors_dict, color_bbox: bool=T...
    method color_by_instance (line 95) | def color_by_instance(self):
  class MapObjectList (line 113) | class MapObjectList(DetectionList):
    method compute_similarities (line 114) | def compute_similarities(self, new_clip_ft):
    method to_serializable (line 129) | def to_serializable(self):
    method load_serializable (line 148) | def load_serializable(self, s_obj_list):

FILE: utils/utils_scenegraph/utils.py
  function filter_objects (line 12) | def filter_objects(cfg, objects: MapObjectList):
  function filter_gobs (line 22) | def filter_gobs(
  function resize_gobs (line 76) | def resize_gobs(
  function to_scalar (line 107) | def to_scalar(d):
  function from_intrinsics_matrix (line 126) | def from_intrinsics_matrix(K: torch.Tensor):
  function create_object_pcd (line 139) | def create_object_pcd(depth_array, mask, cam_K, image, obj_color=None, i...
  function gobs_to_detection_list (line 200) | def gobs_to_detection_list(
  function compute_overlap_matrix_2set (line 299) | def compute_overlap_matrix_2set(cfg, objects_map: MapObjectList, objects...
  function pcd_denoise_dbscan (line 367) | def pcd_denoise_dbscan(pcd: o3d.geometry.PointCloud, eps=0.02, min_point...
  function process_pcd (line 411) | def process_pcd(pcd, cfg, run_dbscan=True):
  function get_bounding_box (line 426) | def get_bounding_box(cfg, pcd):
  function merge_obj2_into_obj1 (line 437) | def merge_obj2_into_obj1(cfg, obj1, obj2, run_dbscan=True):
  function text2value (line 484) | def text2value(text):