SYMBOL INDEX (639 symbols across 45 files) FILE: config.py function path (line 11) | def path(fn): function stanford_path (line 14) | def stanford_path(fn): class ModelConfig (line 63) | class ModelConfig(object): method __init__ (line 65) | def __init__(self): method setup_parser (line 143) | def setup_parser(self): FILE: dataloaders/blob.py class Blob (line 10) | class Blob(object): method __init__ (line 11) | def __init__(self, mode='det', is_train=False, num_gpus=1, primary_gpu... method is_flickr (line 52) | def is_flickr(self): method is_rel (line 56) | def is_rel(self): method volatile (line 60) | def volatile(self): method append (line 63) | def append(self, d): method _chunkize (line 110) | def _chunkize(self, datom, tensor=torch.LongTensor): method reduce (line 122) | def reduce(self): method _scatter (line 148) | def _scatter(self, x, chunk_sizes, dim=0): method scatter (line 155) | def scatter(self): method __getitem__ (line 182) | def __getitem__(self, index): FILE: dataloaders/image_transforms.py class SquarePad (line 8) | class SquarePad(object): method __call__ (line 9) | def __call__(self, img): class Grayscale (line 16) | class Grayscale(object): method __call__ (line 20) | def __call__(self, img): class Brightness (line 27) | class Brightness(object): method __call__ (line 31) | def __call__(self, img): class Contrast (line 40) | class Contrast(object): method __call__ (line 44) | def __call__(self, img): class Hue (line 53) | class Hue(object): method __call__ (line 57) | def __call__(self, img): class Sharpness (line 70) | class Sharpness(object): method __call__ (line 74) | def __call__(self, img): function random_crop (line 81) | def random_crop(img, boxes, box_scale, round_boxes=True, max_crop_fracti... class RandomOrder (line 115) | class RandomOrder(object): method __init__ (line 119) | def __init__(self, transforms): method __call__ (line 122) | def __call__(self, img): FILE: dataloaders/mscoco.py class CocoDetection (line 13) | class CocoDetection(Dataset): method __init__ (line 18) | def __init__(self, mode): method is_train (line 55) | def is_train(self): method __getitem__ (line 58) | def __getitem__(self, index): method splits (line 130) | def splits(cls, *args, **kwargs): method __len__ (line 136) | def __len__(self): function coco_collate (line 140) | def coco_collate(data, num_gpus=3, is_train=False): class CocoDataLoader (line 149) | class CocoDataLoader(torch.utils.data.DataLoader): method splits (line 162) | def splits(cls, train_data, val_data, batch_size=3, num_workers=1, num... FILE: dataloaders/visual_genome.py class VG (line 23) | class VG(Dataset): method __init__ (line 24) | def __init__(self, mode, roidb_file=VG_SGG_FN, dict_file=VG_SGG_DICT_FN, method coco (line 103) | def coco(self): method is_train (line 130) | def is_train(self): method splits (line 134) | def splits(cls, *args, **kwargs): method __getitem__ (line 141) | def __getitem__(self, index): method __len__ (line 205) | def __len__(self): method num_predicates (line 209) | def num_predicates(self): method num_classes (line 213) | def num_classes(self): function assertion_checks (line 222) | def assertion_checks(entry): function load_image_filenames (line 239) | def load_image_filenames(image_file, image_dir=VG_IMAGES): function load_graphs (line 264) | def load_graphs(graphs_file, mode='train', num_im=-1, num_val_im=0, filt... function load_info (line 365) | def load_info(info_file): function vg_collate (line 384) | def vg_collate(data, num_gpus=3, is_train=False, mode='det'): class VGDataLoader (line 394) | class VGDataLoader(torch.utils.data.DataLoader): method splits (line 401) | def splits(cls, train_data, val_data, batch_size=3, num_workers=1, num... 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viz_dict=N... method save (line 34) | def save(self, fn): method print_stats (line 37) | def print_stats(self): function evaluate_from_dict (line 43) | def evaluate_from_dict(gt_entry, pred_entry, mode, result_dict, multiple... function evaluate_recall (line 147) | def evaluate_recall(gt_rels, gt_boxes, gt_classes, function _triplet (line 210) | def _triplet(predicates, relations, classes, boxes, function _compute_pred_matches (line 243) | def _compute_pred_matches(gt_triplets, pred_triplets, FILE: lib/evaluation/sg_eval_all_rel_cates.py class BasicSceneGraphEvaluator (line 12) | class BasicSceneGraphEvaluator: method __init__ (line 13) | def __init__(self, mode, multiple_preds=False): method all_modes (line 78) | def all_modes(cls, **kwargs): method vrd_modes (line 83) | def vrd_modes(cls, **kwargs): method evaluate_scene_graph_entry (line 87) | def evaluate_scene_graph_entry(self, gt_entry, pred_scores, viz_dict=N... method save (line 93) | def save(self, fn): method print_stats (line 96) | def print_stats(self): function evaluate_from_dict (line 103) | def evaluate_from_dict(gt_entry, pred_entry, mode, result_dict, multiple... function evaluate_recall (line 213) | def evaluate_recall(gt_rels, gt_boxes, gt_classes, function _triplet (line 277) | def _triplet(predicates, relations, classes, boxes, function _compute_pred_matches (line 310) | def _compute_pred_matches(gt_triplets, pred_triplets, FILE: lib/evaluation/sg_eval_slow.py class BasicSceneGraphEvaluator (line 5) | class BasicSceneGraphEvaluator: method __init__ (line 7) | def __init__(self, mode): method all_modes (line 16) | def all_modes(cls): method evaluate_scene_graph_entry (line 19) | def evaluate_scene_graph_entry(self, gt_entry, pred_entry, iou_thresh=... method save (line 43) | def save(self, fn): method print_stats (line 47) | def print_stats(self): method save (line 52) | def save(self, fn): method print_stats (line 55) | def print_stats(self): function eval_relation_recall (line 61) | def 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__Pyx_PyObject_IsTrue(PyObject* x) { function CYTHON_INLINE (line 8618) | static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { function CYTHON_INLINE (line 8680) | static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { FILE: lib/fpn/box_utils.py function bbox_loss (line 8) | def bbox_loss(prior_boxes, deltas, gt_boxes, eps=1e-4, scale_before=1): function bbox_preds (line 28) | def bbox_preds(boxes, deltas): function center_size (line 51) | def center_size(boxes): function point_form (line 66) | def point_form(boxes): function bbox_intersections (line 85) | def bbox_intersections(box_a, box_b): function bbox_overlaps (line 109) | def bbox_overlaps(box_a, box_b): function nms_overlaps (line 134) | def nms_overlaps(boxes): FILE: lib/fpn/generate_anchors.py function generate_anchors (line 39) | def generate_anchors(base_size=16, feat_stride=16, anchor_scales=(8,16,3... function generate_base_anchors (line 62) | def generate_base_anchors(base_size=16, ratios=[0.5, 1, 2], scales=2 ** ... function _whctrs (line 75) | def _whctrs(anchor): function _mkanchors (line 87) | def _mkanchors(ws, hs, x_ctr, y_ctr): function _ratio_enum (line 102) | def _ratio_enum(anchor, ratios): function _scale_enum (line 117) | def _scale_enum(anchor, scales): FILE: lib/fpn/nms/functions/nms.py function apply_nms (line 7) | def apply_nms(scores, boxes, pre_nms_topn=12000, post_nms_topn=2000, bo... function _nms_single_im (line 35) | def _nms_single_im(scores, boxes, pre_nms_topn=12000, post_nms_topn=200... FILE: lib/fpn/nms/src/nms_cuda.c function nms_apply (line 7) | int nms_apply(THIntTensor* keep, THCudaTensor* boxes_sorted, const float... FILE: lib/fpn/proposal_assignments/proposal_assignments_det.py function proposal_assignments_det (line 12) | def proposal_assignments_det(rpn_rois, gt_boxes, gt_classes, image_offse... function _sel_inds (line 94) | def _sel_inds(max_overlaps, fg_thresh=0.5, fg_rois_per_image=128, rois_p... FILE: lib/fpn/proposal_assignments/proposal_assignments_gtbox.py function proposal_assignments_gtbox (line 9) | def proposal_assignments_gtbox(rois, gt_boxes, gt_classes, gt_rels, imag... FILE: lib/fpn/proposal_assignments/proposal_assignments_postnms.py function proposal_assignments_postnms (line 15) | def proposal_assignments_postnms( FILE: lib/fpn/proposal_assignments/proposal_assignments_rel.py function proposal_assignments_rel (line 17) | def proposal_assignments_rel(rpn_rois, gt_boxes, gt_classes, gt_rels, im... function _sel_rels (line 97) | def _sel_rels(ious, pred_boxes, pred_labels, gt_classes, gt_rels, fg_thr... function _sel_inds (line 182) | def _sel_inds(ious, gt_classes_i, fg_thresh=0.5, fg_rois_per_image=128, ... FILE: lib/fpn/proposal_assignments/rel_assignments.py function rel_assignments (line 15) | def rel_assignments(im_inds, rpn_rois, roi_gtlabels, gt_boxes, gt_classe... FILE: lib/fpn/roi_align/_ext/roi_align/__init__.py function _import_symbols (line 6) | def _import_symbols(locals): FILE: lib/fpn/roi_align/functions/roi_align.py class RoIAlignFunction (line 9) | class RoIAlignFunction(Function): method __init__ (line 10) | def __init__(self, aligned_height, aligned_width, spatial_scale): method forward (line 17) | def forward(self, features, rois): method backward (line 50) | def backward(self, grad_output): FILE: lib/fpn/roi_align/modules/roi_align.py class RoIAlign (line 6) | class RoIAlign(Module): method __init__ (line 7) | def __init__(self, aligned_height, aligned_width, spatial_scale): method forward (line 14) | def forward(self, features, rois): class RoIAlignAvg (line 18) | class RoIAlignAvg(Module): method __init__ (line 19) | def __init__(self, aligned_height, aligned_width, spatial_scale): method forward (line 26) | def forward(self, features, rois): class RoIAlignMax (line 31) | class RoIAlignMax(Module): method __init__ (line 32) | def __init__(self, aligned_height, aligned_width, spatial_scale): method forward (line 39) | def forward(self, features, rois): FILE: lib/fpn/roi_align/src/roi_align_cuda.c function roi_align_forward_cuda (line 7) | int roi_align_forward_cuda(int crop_height, int crop_width, float spatia... function roi_align_backward_cuda (line 44) | int roi_align_backward_cuda(int crop_height, int crop_width, float spati... FILE: lib/get_dataset_counts.py function get_counts (line 12) | def get_counts(train_data=VG(mode='train', filter_duplicate_rels=False, ... function box_filter (line 49) | def box_filter(boxes, must_overlap=False): FILE: lib/get_union_boxes.py class UnionBoxesAndFeats (line 15) | class UnionBoxesAndFeats(Module): method __init__ (line 16) | def __init__(self, pooling_size=7, stride=16, dim=256, concat=False, u... method forward (line 42) | def forward(self, fmap, rois, union_inds): function union_boxes (line 72) | def union_boxes(fmap, rois, union_inds, pooling_size=14, stride=16): FILE: lib/lstm/decoder_rnn.py function get_dropout_mask (line 13) | def get_dropout_mask(dropout_probability: float, tensor_for_masking: tor... class DecoderRNN (line 40) | class DecoderRNN(torch.nn.Module): method __init__ (line 41) | def __init__(self, classes, embed_dim, inputs_dim, hidden_dim, recurre... method input_size (line 83) | def input_size(self): method reset_parameters (line 86) | def reset_parameters(self): method lstm_equations (line 96) | def lstm_equations(self, timestep_input, previous_state, previous_memo... method forward (line 133) | def forward(self, # pylint: disable=arguments-differ FILE: lib/lstm/highway_lstm_cuda/_ext/highway_lstm_layer/__init__.py function _import_symbols (line 6) | def _import_symbols(locals): FILE: lib/lstm/highway_lstm_cuda/alternating_highway_lstm.py function block_orthogonal (line 12) | def block_orthogonal(tensor, split_sizes, gain=1.0): class _AlternatingHighwayLSTMFunction (line 62) | class _AlternatingHighwayLSTMFunction(Function): method __init__ (line 63) | def __init__(self, input_size: int, hidden_size: int, num_layers: int,... method forward (line 71) | def forward(self, # pylint: disable=arguments-differ method backward (line 111) | def backward(self, grad_output, grad_hy): # pylint: disable=arguments... class AlternatingHighwayLSTM (line 165) | class AlternatingHighwayLSTM(torch.nn.Module): method __init__ (line 195) | def __init__(self, method reset_parameters (line 233) | def reset_parameters(self) -> None: method forward (line 259) | def forward(self, inputs, initial_state=None) -> Tuple[PackedSequence,... FILE: lib/lstm/highway_lstm_cuda/src/highway_lstm_cuda.c function highway_lstm_forward_cuda (line 6) | int highway_lstm_forward_cuda(int inputSize, int hiddenSize, int miniBatch, function highway_lstm_backward_cuda (line 48) | int highway_lstm_backward_cuda(int inputSize, int hiddenSize, int miniBa... FILE: lib/object_detector.py class Result (line 22) | class Result(object): method __init__ (line 26) | def __init__(self, od_obj_dists=None, rm_obj_dists=None, method is_none (line 36) | def is_none(self): function gather_res (line 40) | def gather_res(outputs, target_device, dim=0): class ObjectDetector (line 50) | class ObjectDetector(nn.Module): method __init__ (line 57) | def __init__(self, classes, mode='rpntrain', num_gpus=1, nms_filter_du... method num_classes (line 107) | def num_classes(self): method feature_map (line 110) | def feature_map(self, x): method obj_feature_map (line 129) | def obj_feature_map(self, features, rois): method rpn_boxes (line 140) | def rpn_boxes(self, fmap, im_sizes, image_offset, gt_boxes=None, gt_cl... method gt_boxes (line 200) | def gt_boxes(self, fmap, im_sizes, image_offset, gt_boxes=None, gt_cla... method proposal_boxes (line 226) | def proposal_boxes(self, fmap, im_sizes, image_offset, gt_boxes=None, ... method get_boxes (line 264) | def get_boxes(self, *args, **kwargs): method forward (line 274) | def forward(self, x, im_sizes, image_offset, method nms_boxes (line 363) | def nms_boxes(self, obj_dists, rois, box_deltas, im_sizes): method __getitem__ (line 410) | def __getitem__(self, batch): function filter_det (line 425) | def filter_det(scores, boxes, start_ind=0, max_per_img=100, thresh=0.001... class RPNHead (line 488) | class RPNHead(nn.Module): method __init__ (line 493) | def __init__(self, dim=512, input_dim=1024): method _A (line 518) | def _A(self): method forward (line 521) | def forward(self, fmap): method anchor_preds (line 533) | def anchor_preds(self, preds, train_anchor_inds, image_offset): method _reshape_channels (line 551) | def _reshape_channels(x): method roi_proposals (line 560) | def roi_proposals(self, fmap, im_sizes, nms_thresh=0.7, pre_nms_topn=1... function filter_roi_proposals (line 600) | def filter_roi_proposals(box_preds, class_preds, boxes_per_im, nms_thres... function load_resnet (line 615) | def load_resnet(): function load_vgg (line 623) | def load_vgg(use_dropout=True, use_relu=True, use_linear=True, pretraine... FILE: lib/pytorch_misc.py function optimistic_restore (line 14) | def optimistic_restore(network, state_dict): function pairwise (line 36) | def pairwise(iterable): function get_ranking (line 43) | def get_ranking(predictions, labels, num_guesses=5): function cache (line 63) | def cache(f): class Flattener (line 80) | class Flattener(nn.Module): method __init__ (line 81) | def __init__(self): method forward (line 86) | def forward(self, x): function to_variable (line 90) | def to_variable(f): function arange (line 103) | def arange(base_tensor, n=None): function to_onehot (line 110) | def to_onehot(vec, num_classes, fill=1000): function save_net (line 127) | def save_net(fname, net): function load_net (line 133) | def load_net(fname, net): function batch_index_iterator (line 144) | def batch_index_iterator(len_l, batch_size, skip_end=True): function batch_map (line 161) | def batch_map(f, a, batch_size): function const_row (line 178) | def const_row(fill, l, volatile=False): function print_para (line 185) | def print_para(model): function accuracy (line 206) | def accuracy(output, target, topk=(1,)): function nonintersecting_2d_inds (line 222) | def nonintersecting_2d_inds(x): function intersect_2d (line 233) | def intersect_2d(x1, x2): function np_to_variable (line 249) | def np_to_variable(x, is_cuda=True, dtype=torch.FloatTensor): function gather_nd (line 255) | def gather_nd(x, index): function enumerate_by_image (line 278) | def enumerate_by_image(im_inds): function diagonal_inds (line 301) | def diagonal_inds(tensor): function enumerate_imsize (line 314) | def enumerate_imsize(im_sizes): function argsort_desc (line 323) | def argsort_desc(scores): function unravel_index (line 333) | def unravel_index(index, dims): function de_chunkize (line 341) | def de_chunkize(tensor, chunks): function random_choose (line 347) | def random_choose(tensor, num): function transpose_packed_sequence_inds (line 365) | def transpose_packed_sequence_inds(lengths): function right_shift_packed_sequence_inds (line 387) | def right_shift_packed_sequence_inds(lengths): function clip_grad_norm (line 416) | def clip_grad_norm(named_parameters, max_norm, clip=False, verbose=False): function update_lr (line 457) | def update_lr(optimizer, lr=1e-4): FILE: lib/rel_model.py function _sort_by_score (line 31) | def _sort_by_score(im_inds, scores): class LinearizedContext (line 66) | class LinearizedContext(nn.Module): method __init__ (line 70) | def __init__(self, classes, rel_classes, mode='sgdet', method sort_rois (line 139) | def sort_rois(self, batch_idx, confidence, box_priors): method num_classes (line 164) | def num_classes(self): method num_rels (line 168) | def num_rels(self): method edge_ctx (line 171) | def edge_ctx(self, obj_feats, obj_dists, im_inds, obj_preds, box_prior... method obj_ctx (line 197) | def obj_ctx(self, obj_feats, obj_dists, im_inds, obj_labels=None, box_... method forward (line 236) | def forward(self, obj_fmaps, obj_logits, im_inds, obj_labels=None, box... class RelModel (line 299) | class RelModel(nn.Module): method __init__ (line 303) | def __init__(self, classes, rel_classes, mode='sgdet', num_gpus=1, use... method num_classes (line 396) | def num_classes(self): method num_rels (line 400) | def num_rels(self): method visual_rep (line 403) | def visual_rep(self, features, rois, pair_inds): method get_rel_inds (line 416) | def get_rel_inds(self, rel_labels, im_inds, box_priors): method obj_feature_map (line 439) | def obj_feature_map(self, features, rois): method forward (line 450) | def forward(self, x, im_sizes, image_offset, method __getitem__ (line 549) | def __getitem__(self, batch): FILE: lib/rel_model_stanford.py class RelModelStanford (line 20) | class RelModelStanford(RelModel): method __init__ (line 25) | def __init__(self, classes, rel_classes, mode='sgdet', num_gpus=1, req... method message_pass (line 60) | def message_pass(self, rel_rep, obj_rep, rel_inds): method forward (line 111) | def forward(self, x, im_sizes, image_offset, FILE: lib/resnet.py class Bottleneck (line 8) | class Bottleneck(nn.Module): method __init__ (line 11) | def __init__(self, inplanes, planes, stride=1, downsample=None, relu_e... method forward (line 25) | def forward(self, x): class ResNet (line 49) | class ResNet(nn.Module): method __init__ (line 51) | def __init__(self, block, layers, num_classes=1000): method _make_layer (line 74) | def _make_layer(self, block, planes, blocks, stride=1): method forward (line 91) | def forward(self, x): function resnet101 (line 108) | def resnet101(pretrained=False, **kwargs): function resnet_l123 (line 119) | def resnet_l123(): function resnet_l4 (line 126) | def resnet_l4(relu_end=True): function vgg_fc (line 135) | def vgg_fc(relu_end=True, linear_end=True): FILE: lib/sparse_targets.py class FrequencyBias (line 11) | class FrequencyBias(nn.Module): method __init__ (line 17) | def __init__(self, eps=1e-3): method index_with_labels (line 32) | def index_with_labels(self, labels): method forward (line 39) | def forward(self, obj_cands0, obj_cands1): FILE: lib/surgery.py function filter_dets (line 21) | def filter_dets(boxes, obj_scores, obj_classes, rel_inds, pred_scores): FILE: lib/word_vectors.py function obj_edge_vectors (line 17) | def obj_edge_vectors(names, wv_type='glove.6B', wv_dir=DATA_PATH, wv_dim... function load_word_vectors (line 47) | def load_word_vectors(root, wv_type, dim): function reporthook (line 115) | def reporthook(t): FILE: misc/motifs.py function id_to_str (line 63) | def id_to_str(_id): function increment_recursive (line 180) | def increment_recursive(i): function meme_length (line 189) | def meme_length(i): FILE: models/_visualize.py function get_cmap (line 54) | def get_cmap(N): function load_unscaled (line 71) | def load_unscaled(fn): function draw_box (line 84) | def draw_box(draw, boxx, cls_ind, text_str): function val_epoch (line 114) | def val_epoch(): function val_batch (line 123) | def val_batch(batch_num, b, evaluator, thrs=(20, 50, 100)): FILE: models/eval_rel_count.py function predict (line 76) | def predict(boxes, classes): function gimme_the_dist (line 92) | def gimme_the_dist(c1name, c2name): FILE: models/eval_rels.py function val_batch (line 59) | def val_batch(batch_num, b, evaluator, thrs=(20, 50, 100)): FILE: models/train_detector.py function train_epoch (line 60) | def train_epoch(epoch_num): function train_batch (line 78) | def train_batch(b): function val_epoch (line 158) | def val_epoch(): function val_batch (line 184) | def val_batch(batch_num, b): FILE: models/train_rels.py function get_optim (line 57) | def get_optim(lr): function train_epoch (line 100) | def train_epoch(epoch_num): function train_batch (line 118) | def train_batch(b, verbose=False): function val_epoch (line 155) | def val_epoch(): function val_batch (line 164) | def val_batch(batch_num, b, evaluator):