SYMBOL INDEX (163 symbols across 19 files)

FILE: base/base_data_loader.py
  class BaseDataLoader (line 6) | class BaseDataLoader(DataLoader):
    method __init__ (line 10) | def __init__(self, dataset, batch_size, split, shuffle, num_workers, c...

FILE: base/base_model.py
  class BaseModel (line 6) | class BaseModel(nn.Module):
    method forward (line 11) | def forward(self, *inputs):
    method __str__ (line 19) | def __str__(self):
    method tot_params (line 27) | def tot_params(self):

FILE: base/base_trainer.py
  class BaseTrainer (line 7) | class BaseTrainer:
    method __init__ (line 11) | def __init__(self, model, loss, metrics, optimizer, config):
    method _train_epoch (line 53) | def _train_epoch(self, epoch):
    method train (line 61) | def train(self):
    method _prepare_device (line 116) | def _prepare_device(self, n_gpu_use):
    method _save_checkpoint (line 133) | def _save_checkpoint(self, epoch, save_best=False):
    method _resume_checkpoint (line 158) | def _resume_checkpoint(self, resume_path):

FILE: data_loader/MovieClips_dataset.py
  class MovieClips (line 22) | class MovieClips(Dataset):
    method __init__ (line 24) | def __init__(self, data_dir, metadata_dir, label, experts_used, expert...
    method _load_metadata (line 38) | def _load_metadata(self):
    method _load_data (line 76) | def _load_data(self):
    method __len__ (line 115) | def __len__(self):
    method __getitem__ (line 118) | def __getitem__(self, item):
    method _get_expert_ftr (line 132) | def _get_expert_ftr(self, expert, videoid, context=False):
    method _pad_to_max_tokens (line 164) | def _pad_to_max_tokens(self, array, expert):
    method _characters_txt (line 174) | def _characters_txt(self, texts, clean_cast):
    method _clean_cast (line 177) | def _clean_cast(self, cast):
    method _expert_dims (line 186) | def _expert_dims(self):

FILE: data_loader/data_loaders.py
  class MovieClipsDataLoader (line 6) | class MovieClipsDataLoader(BaseDataLoader):
    method __init__ (line 11) | def __init__(self, data_dir, metadata_dir, label, experts_used, expert...

FILE: data_prep/download.py
  function download_features (line 10) | def download_features(data_dir):
  function download_facetracks (line 15) | def download_facetracks(data_dir):
  function youtube_download (line 21) | def youtube_download(data_dir):
  function trim_video_outro (line 55) | def trim_video_outro(video_dir, video_ext='.mkv'):
  function check_missing_vids (line 76) | def check_missing_vids(video_dir, video_ext='.mkv'):
  function main (line 100) | def main():

FILE: logger/logger.py
  function setup_logging (line 7) | def setup_logging(save_dir, log_config='logger/logger_config.json', defa...

FILE: logger/visualization.py
  class TensorboardWriter (line 5) | class TensorboardWriter():
    method __init__ (line 6) | def __init__(self, log_dir, logger, enabled):
    method set_step (line 42) | def set_step(self, step, mode='train'):
    method __getattr__ (line 51) | def __getattr__(self, name):

FILE: model/loss.py
  class MaxMarginRankingLoss (line 29) | class MaxMarginRankingLoss(nn.Module):
    method __init__ (line 31) | def __init__(self, margin=1, fix_norm=True):
    method forward (line 37) | def forward(self, x):
  function cosine_sim (line 66) | def cosine_sim(im, s):
  function order_sim (line 72) | def order_sim(im, s):
  class ContrastiveLoss (line 83) | class ContrastiveLoss(nn.Module):
    method __init__ (line 88) | def __init__(self, margin=0, measure=False, max_violation=False):
    method forward (line 93) | def forward(self, im, s, scores):
  class BCEWithLogitsLoss (line 122) | class BCEWithLogitsLoss(nn.Module):
    method __init__ (line 124) | def __init__(self, weight=None):
    method forward (line 128) | def forward(self, x, target):
  class CrossEntropyLoss (line 132) | class CrossEntropyLoss(nn.Module):
    method __init__ (line 134) | def __init__(self, weight=None):
    method forward (line 138) | def forward(self, x, target):

FILE: model/metric.py
  function t2v_metrics (line 18) | def t2v_metrics(sims, query_masks=None):
  function v2t_metrics (line 125) | def v2t_metrics(sims, query_masks=None):
  function retrieval_as_classification (line 217) | def retrieval_as_classification(sims, query_masks=None):
  function cols2metrics (line 283) | def cols2metrics(cols, num_queries):
  function mean_average_precision (line 296) | def mean_average_precision(sims, query_masks=None):
  class AverageMeter (line 302) | class AverageMeter(object):
    method __init__ (line 305) | def __init__(self, name, fmt=':f'):
    method reset (line 310) | def reset(self):
    method update (line 316) | def update(self, val, n=1):
    method __str__ (line 322) | def __str__(self):
  class Meter (line 327) | class Meter(object):
    method reset (line 332) | def reset(self):
    method add (line 336) | def add(self, value):
    method value (line 343) | def value(self):
  class APMeter (line 348) | class APMeter(Meter):
    method __init__ (line 362) | def __init__(self):
    method reset (line 366) | def reset(self):
    method add (line 372) | def add(self, output, target, weight=None):
    method value (line 438) | def value(self):
  class APMeterChallenge (line 481) | class APMeterChallenge(APMeter):
    method value (line 495) | def value(self):
  class ClassErrorMeter (line 516) | class ClassErrorMeter(Meter):
    method __init__ (line 517) | def __init__(self, topk=[1, 5, 10, 50], accuracy=True):
    method reset (line 523) | def reset(self):
    method add (line 527) | def add(self, output, target):
    method value (line 554) | def value(self, k=-1):

FILE: model/model.py
  class MoEE (line 11) | class MoEE(BaseModel):
    method __init__ (line 12) | def __init__(self, label, experts_used, expert_dims, aggregation_metho...
    method get_moe_scores (line 54) | def get_moe_scores(self, text):
    method forward (line 58) | def forward(self, x, evaluation=False, debug=False):
  class Collaborative_Gating_Unit (line 137) | class Collaborative_Gating_Unit(nn.Module):
    method __init__ (line 138) | def __init__(self, output_dimension, num_inputs, number_g_layers, numb...
    method instantiate_reason_module (line 149) | def instantiate_reason_module(self):
    method common_project (line 159) | def common_project(self, x):
    method forward (line 162) | def forward(self, cp1, cp2):
  class Gated_Embedding_Unit (line 167) | class Gated_Embedding_Unit(nn.Module):
    method __init__ (line 168) | def __init__(self, input_dimension, output_dimension, gating=True, cha...
    method forward (line 175) | def forward(self, x):
  class Gated_Embedding_Unit_Reasoning (line 183) | class Gated_Embedding_Unit_Reasoning(nn.Module):
    method __init__ (line 184) | def __init__(self, output_dimension, n_clips):
    method forward (line 188) | def forward(self, x, mask):
  class Context_Gating (line 194) | class Context_Gating(nn.Module):
    method __init__ (line 195) | def __init__(self, dimension, channels, add_batch_norm=True):
    method forward (line 206) | def forward(self, x):
  class ContextGatingReasoning (line 216) | class ContextGatingReasoning(nn.Module):
    method __init__ (line 217) | def __init__(self, dimension, n_clips, add_batch_norm=True):
    method forward (line 223) | def forward(self, x, x1):
  class ReduceDim (line 246) | class ReduceDim(nn.Module):
    method __init__ (line 247) | def __init__(self, input_dimension, output_dimension):
    method forward (line 254) | def forward(self, x):
  class Debug (line 261) | class Debug(BaseModel):
    method __init__ (line 262) | def __init__(self, experts_used):
    method forward (line 269) | def forward(self, x, target):
  class ScalarWeight (line 273) | class ScalarWeight(nn.Module):
    method __init__ (line 274) | def __init__(self, init_val=1, len=1):
    method forward (line 278) | def forward(self, x):
  class MeanToken (line 282) | class MeanToken(nn.Module):
    method __init__ (line 283) | def __init__(self, dim_idx):
    method forward (line 287) | def forward(self, x, n_tokens):
  class MaxToken (line 302) | class MaxToken(nn.Module):
    method __init__ (line 303) | def __init__(self, dim_idx):
    method forward (line 307) | def forward(self, x, n_tokens):
  function get_aggregation (line 311) | def get_aggregation(agg, feature_size):
  function cosine_similarity (line 324) | def cosine_similarity(content, text, eps=1e-8):
  function sim_matrix (line 342) | def sim_matrix(a, b, weights=None, eps=1e-8):

FILE: model/net_vlad.py
  class NetVLAD (line 25) | class NetVLAD(nn.Module):
    method __init__ (line 26) | def __init__(self, cluster_size, feature_size, ghost_clusters=0,
    method forward (line 44) | def forward(self, x, n_tokens, mask=None):
    method sanity_checks (line 90) | def sanity_checks(self, x):

FILE: parse_config.py
  class ConfigParser (line 12) | class ConfigParser:
    method __init__ (line 13) | def __init__(self, args, options='', timestamp=True, class_=False):
    method load_config (line 62) | def load_config(self, cfg_fname):
    method initialize (line 76) | def initialize(self, name, module, *args, **kwargs):
    method __getitem__ (line 87) | def __getitem__(self, name):
    method get_logger (line 90) | def get_logger(self, name, verbosity=2):
    method config (line 99) | def config(self):
    method save_dir (line 103) | def save_dir(self):
    method log_dir (line 107) | def log_dir(self):
  function _update_config (line 111) | def _update_config(config, options, args):
  function _get_opt_name (line 118) | def _get_opt_name(flags):
  function _set_by_path (line 124) | def _set_by_path(tree, keys, value):
  function _get_by_path (line 128) | def _get_by_path(tree, keys):

FILE: test.py
  function main (line 19) | def main(config):
  function verbose (line 123) | def verbose(epoch, metrics, mode, name="TEST"):
  function intra_movie_metrics (line 131) | def intra_movie_metrics(sims, imdbids, metrics):
  function sims2ids (line 164) | def sims2ids(sims, videoids):

FILE: train.py
  function main (line 13) | def main(config):
  class TestArg (line 52) | class TestArg:
    method __init__ (line 53) | def __init__(self, resume):

FILE: trainer/trainer.py
  class Trainer (line 10) | class Trainer(BaseTrainer):
    method __init__ (line 18) | def __init__(self, model, loss, metrics, optimizer, config, data_loader,
    method _eval_metrics (line 34) | def _eval_metrics(self, output):
    method _train_epoch (line 41) | def _train_epoch(self, epoch):
    method log_metrics (line 102) | def log_metrics(self, metric_store, metric_name, mode):
    method _valid_epoch (line 109) | def _valid_epoch(self, epoch):
    method _progress (line 171) | def _progress(self, batch_idx):
  function verbose (line 181) | def verbose(epoch, metrics, mode, name="TEST"):
  function intra_movie_metrics (line 189) | def intra_movie_metrics(sims, imdbids, metrics):

FILE: utils/util.py
  function ensure_dir (line 14) | def ensure_dir(dirname):
  function read_json (line 19) | def read_json(fname):
  function write_json (line 23) | def write_json(content, fname):
  function inf_loop (line 27) | def inf_loop(data_loader):
  function memory_summary (line 32) | def memory_summary():
  function memcache (line 41) | def memcache(path):
  function np_loader (line 52) | def np_loader(np_path, l2norm=False):
  class Timer (line 72) | class Timer:
    method __init__ (line 73) | def __init__(self):
    method check (line 76) | def check(self):
    method reset (line 82) | def reset(self):

FILE: utils/visualisation.py
  function visualise_path (line 10) | def visualise_path(pred, target, window):
  function batch_path_vis (line 43) | def batch_path_vis(pred_dict, target, window):

FILE: visualise_face_tracks.py
  function expandrect (line 10) | def expandrect(ROI, extensionx, extensiony, shape):