SYMBOL INDEX (104 symbols across 17 files)

FILE: engine_finetune.py
  function train_one_epoch (line 25) | def train_one_epoch(model: torch.nn.Module, criterion: torch.nn.Module,
  function evaluate (line 99) | def evaluate(data_loader, model, device):

FILE: engine_pretrain.py
  function train_one_epoch (line 21) | def train_one_epoch(model: torch.nn.Module,

FILE: main_finetune.py
  function get_args_parser (line 42) | def get_args_parser():
  function main (line 158) | def main(args):

FILE: main_linprobe.py
  function get_args_parser (line 42) | def get_args_parser():
  function main (line 116) | def main(args):

FILE: main_pretrain.py
  function get_args_parser (line 38) | def get_args_parser():
  function main (line 107) | def main(args):

FILE: models_mae.py
  class MaskedAutoencoderViT (line 22) | class MaskedAutoencoderViT(nn.Module):
    method __init__ (line 25) | def __init__(self, img_size=224, patch_size=16, in_chans=3,
    method initialize_weights (line 65) | def initialize_weights(self):
    method _init_weights (line 85) | def _init_weights(self, m):
    method patchify (line 95) | def patchify(self, imgs):
    method unpatchify (line 109) | def unpatchify(self, x):
    method random_masking (line 123) | def random_masking(self, x, mask_ratio):
    method forward_encoder (line 150) | def forward_encoder(self, x, mask_ratio):
    method forward_decoder (line 172) | def forward_decoder(self, x, ids_restore):
    method forward_loss (line 198) | def forward_loss(self, imgs, pred, mask):
    method forward (line 216) | def forward(self, imgs, mask_ratio=0.75):
  function mae_vit_base_patch16_dec512d8b (line 223) | def mae_vit_base_patch16_dec512d8b(**kwargs):
  function mae_vit_large_patch16_dec512d8b (line 231) | def mae_vit_large_patch16_dec512d8b(**kwargs):
  function mae_vit_huge_patch14_dec512d8b (line 239) | def mae_vit_huge_patch14_dec512d8b(**kwargs):

FILE: models_vit.py
  class VisionTransformer (line 20) | class VisionTransformer(timm.models.vision_transformer.VisionTransformer):
    method __init__ (line 23) | def __init__(self, global_pool=False, **kwargs):
    method forward_features (line 34) | def forward_features(self, x):
  function vit_base_patch16 (line 56) | def vit_base_patch16(**kwargs):
  function vit_large_patch16 (line 63) | def vit_large_patch16(**kwargs):
  function vit_huge_patch14 (line 70) | def vit_huge_patch14(**kwargs):

FILE: submitit_finetune.py
  function parse_args (line 19) | def parse_args():
  function get_shared_folder (line 33) | def get_shared_folder() -> Path:
  function get_init_file (line 42) | def get_init_file():
  class Trainer (line 51) | class Trainer(object):
    method __init__ (line 52) | def __init__(self, args):
    method __call__ (line 55) | def __call__(self):
    method checkpoint (line 61) | def checkpoint(self):
    method _setup_gpu_args (line 73) | def _setup_gpu_args(self):
  function main (line 86) | def main():

FILE: submitit_linprobe.py
  function parse_args (line 19) | def parse_args():
  function get_shared_folder (line 33) | def get_shared_folder() -> Path:
  function get_init_file (line 42) | def get_init_file():
  class Trainer (line 51) | class Trainer(object):
    method __init__ (line 52) | def __init__(self, args):
    method __call__ (line 55) | def __call__(self):
    method checkpoint (line 61) | def checkpoint(self):
    method _setup_gpu_args (line 73) | def _setup_gpu_args(self):
  function main (line 86) | def main():

FILE: submitit_pretrain.py
  function parse_args (line 19) | def parse_args():
  function get_shared_folder (line 33) | def get_shared_folder() -> Path:
  function get_init_file (line 42) | def get_init_file():
  class Trainer (line 51) | class Trainer(object):
    method __init__ (line 52) | def __init__(self, args):
    method __call__ (line 55) | def __call__(self):
    method checkpoint (line 61) | def checkpoint(self):
    method _setup_gpu_args (line 73) | def _setup_gpu_args(self):
  function main (line 86) | def main():

FILE: util/crop.py
  class RandomResizedCrop (line 15) | class RandomResizedCrop(transforms.RandomResizedCrop):
    method get_params (line 23) | def get_params(img, scale, ratio):

FILE: util/datasets.py
  function build_dataset (line 20) | def build_dataset(is_train, args):
  function build_transform (line 31) | def build_transform(is_train, args):

FILE: util/lars.py
  class LARS (line 14) | class LARS(torch.optim.Optimizer):
    method __init__ (line 18) | def __init__(self, params, lr=0, weight_decay=0, momentum=0.9, trust_c...
    method step (line 23) | def step(self):

FILE: util/lr_decay.py
  function param_groups_lrd (line 15) | def param_groups_lrd(model, weight_decay=0.05, no_weight_decay_list=[], ...
  function get_layer_id_for_vit (line 64) | def get_layer_id_for_vit(name, num_layers):

FILE: util/lr_sched.py
  function adjust_learning_rate (line 9) | def adjust_learning_rate(optimizer, epoch, args):

FILE: util/misc.py
  class SmoothedValue (line 24) | class SmoothedValue(object):
    method __init__ (line 29) | def __init__(self, window_size=20, fmt=None):
    method update (line 37) | def update(self, value, n=1):
    method synchronize_between_processes (line 42) | def synchronize_between_processes(self):
    method median (line 56) | def median(self):
    method avg (line 61) | def avg(self):
    method global_avg (line 66) | def global_avg(self):
    method max (line 70) | def max(self):
    method value (line 74) | def value(self):
    method __str__ (line 77) | def __str__(self):
  class MetricLogger (line 86) | class MetricLogger(object):
    method __init__ (line 87) | def __init__(self, delimiter="\t"):
    method update (line 91) | def update(self, **kwargs):
    method __getattr__ (line 100) | def __getattr__(self, attr):
    method __str__ (line 108) | def __str__(self):
    method synchronize_between_processes (line 116) | def synchronize_between_processes(self):
    method add_meter (line 120) | def add_meter(self, name, meter):
    method log_every (line 123) | def log_every(self, iterable, print_freq, header=None):
  function setup_for_distributed (line 170) | def setup_for_distributed(is_master):
  function is_dist_avail_and_initialized (line 187) | def is_dist_avail_and_initialized():
  function get_world_size (line 195) | def get_world_size():
  function get_rank (line 201) | def get_rank():
  function is_main_process (line 207) | def is_main_process():
  function save_on_master (line 211) | def save_on_master(*args, **kwargs):
  function init_distributed_mode (line 216) | def init_distributed_mode(args):
  class NativeScalerWithGradNormCount (line 251) | class NativeScalerWithGradNormCount:
    method __init__ (line 254) | def __init__(self):
    method __call__ (line 257) | def __call__(self, loss, optimizer, clip_grad=None, parameters=None, c...
    method state_dict (line 273) | def state_dict(self):
    method load_state_dict (line 276) | def load_state_dict(self, state_dict):
  function get_grad_norm_ (line 280) | def get_grad_norm_(parameters, norm_type: float = 2.0) -> torch.Tensor:
  function save_model (line 295) | def save_model(args, epoch, model, model_without_ddp, optimizer, loss_sc...
  function load_model (line 315) | def load_model(args, model_without_ddp, optimizer, loss_scaler):
  function all_reduce_mean (line 332) | def all_reduce_mean(x):

FILE: util/pos_embed.py
  function get_2d_sincos_pos_embed (line 20) | def get_2d_sincos_pos_embed(embed_dim, grid_size, cls_token=False):
  function get_2d_sincos_pos_embed_from_grid (line 38) | def get_2d_sincos_pos_embed_from_grid(embed_dim, grid):
  function get_1d_sincos_pos_embed_from_grid (line 49) | def get_1d_sincos_pos_embed_from_grid(embed_dim, pos):
  function interpolate_pos_embed (line 75) | def interpolate_pos_embed(model, checkpoint_model):