SYMBOL INDEX (260 symbols across 66 files)

FILE: Result_Evaluations.py
  function get_data (line 9) | def get_data(project):
  function name_filter (line 80) | def name_filter(n):
  function name_adjust (line 84) | def name_adjust(n, prep='', app='', for_plot=True):
  function single_table (line 123) | def single_table(vals):
  function shared_table (line 148) | def shared_table():
  function give_basic_metr (line 190) | def give_basic_metr(vals, key='CUB'):
  function give_reg_metr (line 212) | def give_reg_metr(vals, key='CUB'):
  function full_rel_plot (line 326) | def full_rel_plot():
  function plot (line 481) | def plot(vals, recalls, errs, names, reg_vals=None, reg_recalls=None, re...

FILE: architectures/__init__.py
  function select (line 5) | def select(arch, opt):

FILE: architectures/bninception.py
  class Network (line 10) | class Network(torch.nn.Module):
    method __init__ (line 11) | def __init__(self, opt, return_embed_dict=False):
    method forward (line 35) | def forward(self, x, warmup=False, **kwargs):
    method functional_forward (line 49) | def functional_forward(self, x):

FILE: architectures/googlenet.py
  class Network (line 12) | class Network(torch.nn.Module):
    method __init__ (line 13) | def __init__(self, opt):
    method forward (line 24) | def forward(self, x):

FILE: architectures/resnet50.py
  class Network (line 12) | class Network(torch.nn.Module):
    method __init__ (line 13) | def __init__(self, opt):
    method forward (line 33) | def forward(self, x, **kwargs):

FILE: batchminer/__init__.py
  function select (line 16) | def select(batchminername, opt):

FILE: batchminer/distance.py
  class BatchMiner (line 6) | class BatchMiner():
    method __init__ (line 7) | def __init__(self, opt):
    method __call__ (line 13) | def __call__(self, batch, labels, tar_labels=None, return_distances=Fa...
    method inverse_sphere_distances (line 48) | def inverse_sphere_distances(self, dim, bs, anchor_to_all_dists, label...
    method pdist (line 66) | def pdist(self, A):

FILE: batchminer/intra_random.py
  class BatchMiner (line 5) | class BatchMiner():
    method __init__ (line 6) | def __init__(self, opt):
    method __call__ (line 10) | def __call__(self, batch, labels):

FILE: batchminer/lifted.py
  class BatchMiner (line 3) | class BatchMiner():
    method __init__ (line 4) | def __init__(self, opt):
    method __call__ (line 8) | def __call__(self, batch, labels):

FILE: batchminer/npair.py
  class BatchMiner (line 2) | class BatchMiner():
    method __init__ (line 3) | def __init__(self, opt):
    method __call__ (line 7) | def __call__(self, batch, labels):

FILE: batchminer/parametric.py
  class BatchMiner (line 4) | class BatchMiner():
    method __init__ (line 5) | def __init__(self, opt):
    method __call__ (line 17) | def __call__(self, batch, labels):
    method pdist (line 58) | def pdist(self, A, eps=1e-4):
    method set_sample_distr (line 65) | def set_sample_distr(self):

FILE: batchminer/random.py
  class BatchMiner (line 5) | class BatchMiner():
    method __init__ (line 6) | def __init__(self, opt):
    method __call__ (line 10) | def __call__(self, batch, labels):

FILE: batchminer/random_distance.py
  class BatchMiner (line 4) | class BatchMiner():
    method __init__ (line 5) | def __init__(self, opt):
    method __call__ (line 11) | def __call__(self, batch, labels):
    method inverse_sphere_distances (line 38) | def inverse_sphere_distances(self, batch, anchor_to_all_dists, labels,...
    method pdist (line 57) | def pdist(self, A):

FILE: batchminer/rho_distance.py
  class BatchMiner (line 4) | class BatchMiner():
    method __init__ (line 5) | def __init__(self, opt):
    method __call__ (line 13) | def __call__(self, batch, labels, return_distances=False):
    method inverse_sphere_distances (line 50) | def inverse_sphere_distances(self, batch, anchor_to_all_dists, labels,...
    method pdist (line 69) | def pdist(self, A, eps=1e-4):

FILE: batchminer/semihard.py
  class BatchMiner (line 4) | class BatchMiner():
    method __init__ (line 5) | def __init__(self, opt):
    method __call__ (line 10) | def __call__(self, batch, labels, return_distances=False):
    method pdist (line 43) | def pdist(self, A):

FILE: batchminer/softhard.py
  class BatchMiner (line 4) | class BatchMiner():
    method __init__ (line 5) | def __init__(self, opt):
    method __call__ (line 9) | def __call__(self, batch, labels, return_distances=False):
    method pdist (line 50) | def pdist(self, A):

FILE: criteria/__init__.py
  function select (line 13) | def select(loss, opt, to_optim, batchminer=None):

FILE: criteria/adversarial_separation.py
  class Criterion (line 12) | class Criterion(torch.nn.Module):
    method __init__ (line 13) | def __init__(self, opt):
    method forward (line 49) | def forward(self, feature_dict):
  class GradRev (line 62) | class GradRev(torch.autograd.Function):
    method forward (line 66) | def forward(self, x):
    method backward (line 75) | def backward(self, grad_output):
  function grad_reverse (line 85) | def grad_reverse(x):

FILE: criteria/angular.py
  class Criterion (line 11) | class Criterion(torch.nn.Module):
    method __init__ (line 12) | def __init__(self, opt, batchminer):
    method forward (line 29) | def forward(self, batch, labels, **kwargs):

FILE: criteria/arcface.py
  class Criterion (line 11) | class Criterion(torch.nn.Module):
    method __init__ (line 12) | def __init__(self, opt):
    method forward (line 36) | def forward(self, batch, labels, **kwargs):

FILE: criteria/contrastive.py
  class Criterion (line 11) | class Criterion(torch.nn.Module):
    method __init__ (line 12) | def __init__(self, opt, batchminer):
    method forward (line 27) | def forward(self, batch, labels, **kwargs):

FILE: criteria/histogram.py
  class Criterion (line 12) | class Criterion(torch.nn.Module):
    method __init__ (line 13) | def __init__(self, opt):
    method forward (line 36) | def forward(self, batch, labels, **kwargs):
    method histogram (line 81) | def histogram(self, unique_sim_rep, assigned_bin_values, idxs, n_elem):

FILE: criteria/lifted.py
  class Criterion (line 11) | class Criterion(torch.nn.Module):
    method __init__ (line 12) | def __init__(self, opt, batchminer):
    method forward (line 28) | def forward(self, batch, labels, **kwargs):

FILE: criteria/margin.py
  class Criterion (line 11) | class Criterion(torch.nn.Module):
    method __init__ (line 12) | def __init__(self, opt, batchminer):
    method forward (line 39) | def forward(self, batch, labels, **kwargs):

FILE: criteria/multisimilarity.py
  class Criterion (line 10) | class Criterion(torch.nn.Module):
    method __init__ (line 11) | def __init__(self, opt):
    method forward (line 28) | def forward(self, batch, labels, **kwargs):

FILE: criteria/npair.py
  class Criterion (line 11) | class Criterion(torch.nn.Module):
    method __init__ (line 12) | def __init__(self, opt, batchminer):
    method forward (line 29) | def forward(self, batch, labels, **kwargs):

FILE: criteria/proxynca.py
  class Criterion (line 12) | class Criterion(torch.nn.Module):
    method __init__ (line 13) | def __init__(self, opt):
    method forward (line 39) | def forward(self, batch, labels, **kwargs):

FILE: criteria/quadruplet.py
  class Criterion (line 10) | class Criterion(torch.nn.Module):
    method __init__ (line 11) | def __init__(self, opt, batchminer):
    method triplet_distance (line 27) | def triplet_distance(self, anchor, positive, negative):
    method quadruplet_distance (line 30) | def quadruplet_distance(self, anchor, positive, negative, fourth_negat...
    method forward (line 33) | def forward(self, batch, labels, **kwargs):

FILE: criteria/snr.py
  class Criterion (line 11) | class Criterion(torch.nn.Module):
    method __init__ (line 12) | def __init__(self, opt, batchminer):
    method forward (line 29) | def forward(self, batch, labels, **kwargs):

FILE: criteria/softmax.py
  class Criterion (line 12) | class Criterion(torch.nn.Module):
    method __init__ (line 13) | def __init__(self, opt):
    method forward (line 33) | def forward(self, batch, labels, **kwargs):

FILE: criteria/softtriplet.py
  class Criterion (line 11) | class Criterion(torch.nn.Module):
    method __init__ (line 12) | def __init__(self, opt):
    method forward (line 50) | def forward(self, batch, labels, **kwargs):

FILE: criteria/triplet.py
  class Criterion (line 11) | class Criterion(torch.nn.Module):
    method __init__ (line 12) | def __init__(self, opt, batchminer):
    method triplet_distance (line 24) | def triplet_distance(self, anchor, positive, negative):
    method forward (line 27) | def forward(self, batch, labels, **kwargs):

FILE: datasampler/__init__.py
  function select (line 9) | def select(sampler, opt, image_dict, image_list=None, **kwargs):

FILE: datasampler/class_random_sampler.py
  class Sampler (line 12) | class Sampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 16) | def __init__(self, opt, image_dict, image_list, **kwargs):
    method __iter__ (line 35) | def __iter__(self):
    method __len__ (line 48) | def __len__(self):

FILE: datasampler/d2_coreset_sampler.py
  class Sampler (line 12) | class Sampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 16) | def __init__(self, opt, image_dict, image_list):
    method __iter__ (line 38) | def __iter__(self):
    method precompute_indices (line 43) | def precompute_indices(self):
    method replace_storage_entries (line 72) | def replace_storage_entries(self, embeddings, indices):
    method create_storage (line 75) | def create_storage(self, dataloader, model, device):
    method d2_coreset (line 90) | def d2_coreset(self, calls, pos):
    method __len__ (line 144) | def __len__(self):

FILE: datasampler/disthist_batchmatch_sampler.py
  class Sampler (line 12) | class Sampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 16) | def __init__(self, opt, image_dict, image_list):
    method __iter__ (line 39) | def __iter__(self):
    method precompute_indices (line 56) | def precompute_indices(self):
    method replace_storage_entries (line 69) | def replace_storage_entries(self, embeddings, indices):
    method create_storage (line 72) | def create_storage(self, dataloader, model, device):
    method spc_batchfinder (line 87) | def spc_batchfinder(self, n_samples):
    method get_distmat (line 99) | def get_distmat(self, arr):
    method disthist_match (line 105) | def disthist_match(self, calls, pos):
    method __len__ (line 164) | def __len__(self):

FILE: datasampler/fid_batchmatch_sampler.py
  class Sampler (line 12) | class Sampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 16) | def __init__(self, opt, image_dict, image_list):
    method __iter__ (line 38) | def __iter__(self):
    method precompute_indices (line 54) | def precompute_indices(self):
    method replace_storage_entries (line 67) | def replace_storage_entries(self, embeddings, indices):
    method create_storage (line 70) | def create_storage(self, dataloader, model, device):
    method spc_batchfinder (line 85) | def spc_batchfinder(self, n_samples):
    method spc_fid_match (line 97) | def spc_fid_match(self, calls, pos):
    method __len__ (line 147) | def __len__(self):

FILE: datasampler/greedy_coreset_sampler.py
  class Sampler (line 12) | class Sampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 16) | def __init__(self, opt, image_dict, image_list):
    method __iter__ (line 39) | def __iter__(self):
    method precompute_indices (line 44) | def precompute_indices(self):
    method replace_storage_entries (line 75) | def replace_storage_entries(self, embeddings, indices):
    method create_storage (line 78) | def create_storage(self, dataloader, model, device):
    method full_storage_update (line 93) | def full_storage_update(self, dataloader, model, device):
    method greedy_coreset (line 111) | def greedy_coreset(self, calls, pos):
    method __len__ (line 155) | def __len__(self):

FILE: datasampler/random_sampler.py
  class Sampler (line 12) | class Sampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 16) | def __init__(self, opt, image_dict, image_list=None):
    method __iter__ (line 28) | def __iter__(self):
    method __len__ (line 40) | def __len__(self):

FILE: datasampler/samplers.py
  function sampler_parse_args (line 8) | def sampler_parse_args(parser):
  class AdvancedSampler (line 18) | class AdvancedSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 22) | def __init__(self, method='class_random', random_subset_perc=0.1, batc...
    method create_storage (line 34) | def create_storage(self, dataloader, model, device):
    method update_storage (line 54) | def update_storage(self, embeddings, indices):
    method __iter__ (line 58) | def __iter__(self):
    method __len__ (line 100) | def __len__(self):
    method pdistsq (line 103) | def pdistsq(self, A):
    method greedy_coreset (line 108) | def greedy_coreset(self, A, samples):
    method presample_infobatch (line 127) | def presample_infobatch(self, classes, A, samples):

FILE: datasets/__init__.py
  function select (line 6) | def select(dataset, opt, data_path):

FILE: datasets/basic_dataset_scaffold.py
  class BaseDataset (line 9) | class BaseDataset(Dataset):
    method __init__ (line 10) | def __init__(self, image_dict, opt, is_validation=False):
    method init_setup (line 50) | def init_setup(self):
    method ensure_3dim (line 72) | def ensure_3dim(self, img):
    method __getitem__ (line 78) | def __getitem__(self, idx):
    method __len__ (line 88) | def __len__(self):

FILE: datasets/cars196.py
  function Give (line 5) | def Give(opt, datapath):

FILE: datasets/cub200.py
  function Give (line 4) | def Give(opt, datapath):

FILE: datasets/stanford_online_products.py
  function Give (line 6) | def Give(opt, datapath):

FILE: evaluation/__init__.py
  function evaluate (line 7) | def evaluate(dataset, LOG, metric_computer, dataloaders, model, opt, eva...
  function set_checkpoint (line 68) | def set_checkpoint(model, opt, progress_saver, savepath, aux=None):
  function recover_closest_standard (line 82) | def recover_closest_standard(feature_matrix_all, image_paths, save_path,...

FILE: metrics/__init__.py
  function select (line 12) | def select(metricname, opt):
  class MetricComputer (line 61) | class MetricComputer():
    method __init__ (line 62) | def __init__(self, metric_names, opt):
    method compute_standard (line 69) | def compute_standard(self, opt, model, dataloader, evaltypes, device, ...

FILE: metrics/c_f1.py
  class Metric (line 5) | class Metric():
    method __init__ (line 6) | def __init__(self, **kwargs):
    method __call__ (line 10) | def __call__(self, target_labels, computed_cluster_labels_cosine, feat...

FILE: metrics/c_mAP_1000.py
  class Metric (line 7) | class Metric():
    method __init__ (line 8) | def __init__(self, **kwargs):
    method __call__ (line 12) | def __call__(self, target_labels, features_cosine):

FILE: metrics/c_mAP_c.py
  class Metric (line 7) | class Metric():
    method __init__ (line 8) | def __init__(self, **kwargs):
    method __call__ (line 12) | def __call__(self, target_labels, features_cosine):

FILE: metrics/c_mAP_lim.py
  class Metric (line 7) | class Metric():
    method __init__ (line 8) | def __init__(self, **kwargs):
    method __call__ (line 12) | def __call__(self, target_labels, features_cosine):

FILE: metrics/c_nmi.py
  class Metric (line 3) | class Metric():
    method __init__ (line 4) | def __init__(self, **kwargs):
    method __call__ (line 8) | def __call__(self, target_labels, computed_cluster_labels_cosine):

FILE: metrics/c_recall.py
  class Metric (line 3) | class Metric():
    method __init__ (line 4) | def __init__(self, k, **kwargs):
    method __call__ (line 9) | def __call__(self, target_labels, k_closest_classes_cosine, **kwargs):

FILE: metrics/dists.py
  class Metric (line 6) | class Metric():
    method __init__ (line 7) | def __init__(self, mode, **kwargs):
    method __call__ (line 12) | def __call__(self, features, target_labels):

FILE: metrics/e_recall.py
  class Metric (line 3) | class Metric():
    method __init__ (line 4) | def __init__(self, k, **kwargs):
    method __call__ (line 9) | def __call__(self, target_labels, k_closest_classes, **kwargs):

FILE: metrics/f1.py
  class Metric (line 5) | class Metric():
    method __init__ (line 6) | def __init__(self, **kwargs):
    method __call__ (line 10) | def __call__(self, target_labels, computed_cluster_labels, features, c...

FILE: metrics/mAP.py
  class Metric (line 7) | class Metric():
    method __init__ (line 8) | def __init__(self, **kwargs):
    method __call__ (line 12) | def __call__(self, target_labels, features):

FILE: metrics/mAP_1000.py
  class Metric (line 7) | class Metric():
    method __init__ (line 8) | def __init__(self, **kwargs):
    method __call__ (line 12) | def __call__(self, target_labels, features):

FILE: metrics/mAP_c.py
  class Metric (line 7) | class Metric():
    method __init__ (line 8) | def __init__(self, **kwargs):
    method __call__ (line 12) | def __call__(self, target_labels, features):

FILE: metrics/mAP_lim.py
  class Metric (line 7) | class Metric():
    method __init__ (line 8) | def __init__(self, **kwargs):
    method __call__ (line 12) | def __call__(self, target_labels, features):

FILE: metrics/nmi.py
  class Metric (line 3) | class Metric():
    method __init__ (line 4) | def __init__(self, **kwargs):
    method __call__ (line 8) | def __call__(self, target_labels, computed_cluster_labels):

FILE: metrics/rho_spectrum.py
  class Metric (line 6) | class Metric():
    method __init__ (line 7) | def __init__(self, embed_dim, mode,  **kwargs):
    method __call__ (line 13) | def __call__(self, features):

FILE: parameters.py
  function basic_training_parameters (line 5) | def basic_training_parameters(parser):
  function wandb_parameters (line 61) | def wandb_parameters(parser):
  function loss_specific_parameters (line 73) | def loss_specific_parameters(parser):
  function batchmining_specific_parameters (line 142) | def batchmining_specific_parameters(parser):
  function batch_creation_parameters (line 154) | def batch_creation_parameters(parser):

FILE: toy_experiments/toy_example_diagonal_lines.py
  class Backbone (line 50) | class Backbone(nn.Module):
    method __init__ (line 51) | def __init__(self):
    method forward (line 55) | def forward(self, x):
  function train (line 67) | def train(net2train, p_switch=0):
  function get_embeds (line 119) | def get_embeds(net):

FILE: utilities/logger.py
  class CSV_Writer (line 8) | class CSV_Writer():
    method __init__ (line 9) | def __init__(self, save_path):
    method log (line 14) | def log(self, group, segments, content):
  class InfoPlotter (line 30) | class InfoPlotter():
    method __init__ (line 31) | def __init__(self, save_path, title='Training Log', figsize=(25,19)):
    method make_plot (line 37) | def make_plot(self, base_title, title_append, sub_plots, sub_plots_data):
  function set_logging (line 64) | def set_logging(opt):
  class Progress_Saver (line 89) | class Progress_Saver():
    method __init__ (line 90) | def __init__(self):
    method log (line 93) | def log(self, segment, content, group=None):
  class LOGGER (line 104) | class LOGGER():
    method __init__ (line 105) | def __init__(self, opt, sub_loggers=[], prefix=None, start_new=True, l...
    method update (line 139) | def update(self, *sub_loggers, all=False):

FILE: utilities/misc.py
  function gimme_params (line 9) | def gimme_params(model):
  function gimme_save_string (line 16) | def gimme_save_string(opt):
  class DataParallel (line 33) | class DataParallel(nn.Module):
    method __init__ (line 34) | def __init__(self, model, device_ids, dim):
    method forward (line 39) | def forward(self, x):