SYMBOL INDEX (133 symbols across 14 files)

FILE: feature_animation.py
  function extract_map_layer_7x7_res (line 18) | def extract_map_layer_7x7_res(res_model):
  function extract_map_layer_7x7 (line 23) | def extract_map_layer_7x7(mobilenetV2_model):
  function extract_map_layer_14x14 (line 28) | def extract_map_layer_14x14(mobilenetV2_model):
  function load_model_res (line 35) | def load_model_res(args):
  function load_model (line 49) | def load_model(args):
  function load_data (line 63) | def load_data(data_dir, args):
  function predict (line 78) | def predict(data_loader, model, batch_size, feature_idx):
  function show_img (line 118) | def show_img(ax, img, save_name):

FILE: feature_animation_class.py
  function extract_map_layer_7x7_res (line 18) | def extract_map_layer_7x7_res(res_model):
  function extract_map_layer_7x7 (line 23) | def extract_map_layer_7x7(mobilenetV2_model):
  function extract_map_layer_14x14 (line 28) | def extract_map_layer_14x14(mobilenetV2_model):
  function load_model_res (line 35) | def load_model_res(args):
  function load_model (line 49) | def load_model(args):
  function load_data (line 63) | def load_data(data_dir, args):
  function predict (line 78) | def predict(data_loader, model, batch_size, weights):
  function show_img (line 119) | def show_img(ax, img, save_name):

FILE: highly_activating_imgs.py
  function extract_map_layer_7x7 (line 14) | def extract_map_layer_7x7(mobilenetV2_model):
  function extract_map_layer_14x14 (line 19) | def extract_map_layer_14x14(mobilenetV2_model, layer):
  function load_model (line 26) | def load_model(args):
  function load_data (line 40) | def load_data(data_dir, args):
  function predict (line 55) | def predict(data_loader, model, neuron_idx):
  function show_img (line 77) | def show_img(ax, img, save_name):

FILE: imagenet_finetuning.py
  function set_parameter_requires_grad (line 52) | def set_parameter_requires_grad(model, feature_extracting=True):
  function main (line 62) | def main():
  function main_worker (line 84) | def main_worker(gpu, ngpus_per_node, args):
  function train (line 209) | def train(train_loader, model, criterion, optimizer, epoch, args):
  function validate (line 257) | def validate(val_loader, model, args):
  class AverageMeter (line 284) | class AverageMeter(object):
    method __init__ (line 286) | def __init__(self, name, fmt=':f'):
    method reset (line 291) | def reset(self):
    method update (line 297) | def update(self, val, n=1):
    method __str__ (line 303) | def __str__(self):
  class ProgressMeter (line 308) | class ProgressMeter(object):
    method __init__ (line 309) | def __init__(self, num_batches, meters, prefix=""):
    method display (line 314) | def display(self, batch):
    method _get_batch_fmtstr (line 319) | def _get_batch_fmtstr(self, num_batches):
  function adjust_learning_rate (line 325) | def adjust_learning_rate(optimizer, epoch, args):
  function accuracy (line 333) | def accuracy(output, target, topk=(1,)):

FILE: linear_combination_maps.py
  function extract_map_layer_7x7 (line 13) | def extract_map_layer_7x7(mobilenetV2_model):
  function extract_map_layer_14x14 (line 18) | def extract_map_layer_14x14(mobilenetV2_model):
  function load_model (line 25) | def load_model(args):
  function load_data (line 39) | def load_data(data_dir, args):
  function predict (line 54) | def predict(data_loader, model, weights, batch_size):
  function show_img (line 84) | def show_img(ax, img, save_name):

FILE: linear_decoding.py
  function set_parameter_requires_grad (line 52) | def set_parameter_requires_grad(model, feature_extracting=True):
  function load_split_train_test (line 59) | def load_split_train_test(datadir, args, train_frac=0.5):
  function main (line 96) | def main():
  function main_worker (line 118) | def main_worker(gpu, ngpus_per_node, args):
  function train (line 201) | def train(train_loader, model, criterion, optimizer, epoch, args):
  function validate (line 252) | def validate(val_loader, model, args):
  class AverageMeter (line 284) | class AverageMeter(object):
    method __init__ (line 286) | def __init__(self, name, fmt=':f'):
    method reset (line 291) | def reset(self):
    method update (line 297) | def update(self, val, n=1):
    method __str__ (line 303) | def __str__(self):
  class ProgressMeter (line 308) | class ProgressMeter(object):
    method __init__ (line 309) | def __init__(self, num_batches, meters, prefix=""):
    method display (line 314) | def display(self, batch):
    method _get_batch_fmtstr (line 319) | def _get_batch_fmtstr(self, num_batches):
  function accuracy (line 325) | def accuracy(output, target, topk=(1,)):

FILE: moco/builder.py
  class MoCo (line 6) | class MoCo(nn.Module):
    method __init__ (line 11) | def __init__(self, base_encoder, dim=128, K=65536, m=0.999, T=0.07, ml...
    method _momentum_update_key_encoder (line 48) | def _momentum_update_key_encoder(self):
    method _dequeue_and_enqueue (line 56) | def _dequeue_and_enqueue(self, keys):
    method _batch_shuffle_ddp (line 72) | def _batch_shuffle_ddp(self, x):
    method _batch_unshuffle_ddp (line 100) | def _batch_unshuffle_ddp(self, x, idx_unshuffle):
    method forward (line 118) | def forward(self, im_q, im_k):
  function concat_all_gather (line 168) | def concat_all_gather(tensor):

FILE: moco/loader.py
  class TwoCropsTransform (line 6) | class TwoCropsTransform:
    method __init__ (line 9) | def __init__(self, base_transform):
    method __call__ (line 12) | def __call__(self, x):
  class GaussianBlur (line 18) | class GaussianBlur(object):
    method __init__ (line 21) | def __init__(self, sigma=[.1, 2.]):
    method __call__ (line 24) | def __call__(self, x):

FILE: moco_img.py
  function main (line 101) | def main():
  function main_worker (line 136) | def main_worker(gpu, ngpus_per_node, args):
  function train (line 286) | def train(train_loader, model, criterion, optimizer, epoch, args):
  function save_checkpoint (line 334) | def save_checkpoint(state, is_best, filename='checkpoint.pth.tar'):
  class AverageMeter (line 340) | class AverageMeter(object):
    method __init__ (line 342) | def __init__(self, name, fmt=':f'):
    method reset (line 347) | def reset(self):
    method update (line 353) | def update(self, val, n=1):
    method __str__ (line 359) | def __str__(self):
  class ProgressMeter (line 364) | class ProgressMeter(object):
    method __init__ (line 365) | def __init__(self, num_batches, meters, prefix=""):
    method display (line 370) | def display(self, batch):
    method _get_batch_fmtstr (line 375) | def _get_batch_fmtstr(self, num_batches):
  function adjust_learning_rate (line 381) | def adjust_learning_rate(optimizer, epoch, args):
  function accuracy (line 393) | def accuracy(output, target, topk=(1,)):

FILE: moco_temp.py
  function main (line 102) | def main():
  function main_worker (line 137) | def main_worker(gpu, ngpus_per_node, args):
  function train (line 285) | def train(train_loader, model, criterion, optimizer, epoch, args):
  function save_checkpoint (line 333) | def save_checkpoint(state, is_best, filename='checkpoint.pth.tar'):
  class AverageMeter (line 339) | class AverageMeter(object):
    method __init__ (line 341) | def __init__(self, name, fmt=':f'):
    method reset (line 346) | def reset(self):
    method update (line 352) | def update(self, val, n=1):
    method __str__ (line 358) | def __str__(self):
  class ProgressMeter (line 363) | class ProgressMeter(object):
    method __init__ (line 364) | def __init__(self, num_batches, meters, prefix=""):
    method display (line 369) | def display(self, batch):
    method _get_batch_fmtstr (line 374) | def _get_batch_fmtstr(self, num_batches):
  function adjust_learning_rate (line 380) | def adjust_learning_rate(optimizer, epoch, args):
  function accuracy (line 392) | def accuracy(output, target, topk=(1,)):

FILE: moco_utils.py
  class DistributedProxySampler (line 7) | class DistributedProxySampler(DistributedSampler):
    method __init__ (line 25) | def __init__(self, sampler, num_replicas=None, rank=None):
    method __iter__ (line 29) | def __iter__(self):
    method set_epoch (line 46) | def set_epoch(self, epoch):
  class ContrastiveBatchSampler (line 49) | class ContrastiveBatchSampler(Sampler):
    method __init__ (line 50) | def __init__(self, data_source, batch_size, pos_window, drop_last):
    method __iter__ (line 57) | def __iter__(self):
    method __len__ (line 68) | def __len__(self):

FILE: selectivities.py
  function extract_map_layer_7x7 (line 12) | def extract_map_layer_7x7(mobilenetV2_model):
  function extract_map_layer_14x14 (line 17) | def extract_map_layer_14x14(mobilenetV2_model, layer):
  function load_model (line 24) | def load_model(args):
  function load_data (line 38) | def load_data(data_dir, args):
  function predict (line 53) | def predict(data_loader, model):

FILE: temporal_classification.py
  function main (line 55) | def main():
  function main_worker (line 79) | def main_worker(gpu, ngpus_per_node, args):
  function train (line 153) | def train(train_loader, model, criterion, optimizer, epoch, args):
  class AverageMeter (line 201) | class AverageMeter(object):
    method __init__ (line 203) | def __init__(self, name, fmt=':f'):
    method reset (line 208) | def reset(self):
    method update (line 214) | def update(self, val, n=1):
    method __str__ (line 220) | def __str__(self):
  class ProgressMeter (line 225) | class ProgressMeter(object):
    method __init__ (line 226) | def __init__(self, num_batches, meters, prefix=""):
    method display (line 231) | def display(self, batch):
    method _get_batch_fmtstr (line 236) | def _get_batch_fmtstr(self, num_batches):
  function accuracy (line 242) | def accuracy(output, target, topk=(1,)):

FILE: utils.py
  class GaussianBlur (line 6) | class GaussianBlur(object):
    method __init__ (line 9) | def __init__(self, sigma=[.1, 2.]):
    method __call__ (line 12) | def __call__(self, x):