SYMBOL INDEX (215 symbols across 34 files)

FILE: docs/conf.py
  function linkcode_resolve (line 123) | def linkcode_resolve(domain, info):

FILE: hubconf.py
  function resnet50 (line 10) | def resnet50(pretrained: bool = False, **kwargs):

FILE: scripts/build_vocabulary.py
  function _read_captions (line 41) | def _read_captions(annotations_path: str) -> List[str]:

FILE: scripts/clf_linear.py
  function main (line 70) | def main(_A: argparse.Namespace):

FILE: scripts/clf_voc07.py
  function train_test_single_svm (line 56) | def train_test_single_svm(args):
  function main (line 108) | def main(_A: argparse.Namespace):

FILE: scripts/eval_captioning.py
  function main (line 44) | def main(_A: argparse.Namespace):

FILE: scripts/eval_detectron2.py
  class Res5ROIHeadsExtraNorm (line 82) | class Res5ROIHeadsExtraNorm(Res5ROIHeads):
    method _build_res5_block (line 88) | def _build_res5_block(self, cfg):
  function build_detectron2_config (line 95) | def build_detectron2_config(_C: Config, _A: argparse.Namespace):
  class DownstreamTrainer (line 119) | class DownstreamTrainer(DefaultTrainer):
    method __init__ (line 131) | def __init__(self, cfg, weights):
    method build_evaluator (line 153) | def build_evaluator(cls, cfg, dataset_name, output_folder=None):
    method test (line 165) | def test(self, cfg=None, model=None, evaluators=None):
  function main (line 177) | def main(_A: argparse.Namespace):

FILE: scripts/pretrain_virtex.py
  function main (line 44) | def main(_A: argparse.Namespace):

FILE: setup.py
  function get_model_zoo_configs (line 9) | def get_model_zoo_configs() -> List[str]:

FILE: virtex/config.py
  class Config (line 6) | class Config:
    method __init__ (line 36) | def __init__(
    method dump (line 221) | def dump(self, file_path: str):
    method __getattr__ (line 229) | def __getattr__(self, attr: str):
    method __str__ (line 232) | def __str__(self):
    method __repr__ (line 235) | def __repr__(self):

FILE: virtex/data/datasets/captioning.py
  class CaptioningDataset (line 13) | class CaptioningDataset(Dataset):
    method __init__ (line 30) | def __init__(
    method __len__ (line 48) | def __len__(self):
    method __getitem__ (line 51) | def __getitem__(self, idx: int) -> Dict[str, torch.Tensor]:
    method collate_fn (line 79) | def collate_fn(

FILE: virtex/data/datasets/classification.py
  class TokenClassificationDataset (line 19) | class TokenClassificationDataset(Dataset):
    method __init__ (line 35) | def __init__(
    method __len__ (line 52) | def __len__(self):
    method __getitem__ (line 55) | def __getitem__(self, idx: int) -> Dict[str, torch.Tensor]:
    method collate_fn (line 81) | def collate_fn(
  class MultiLabelClassificationDataset (line 97) | class MultiLabelClassificationDataset(Dataset):
    method __init__ (line 110) | def __init__(
    method __len__ (line 154) | def __len__(self):
    method __getitem__ (line 157) | def __getitem__(self, idx: int):
    method collate_fn (line 176) | def collate_fn(

FILE: virtex/data/datasets/coco_captions.py
  class CocoCaptionsDataset (line 11) | class CocoCaptionsDataset(Dataset):
    method __init__ (line 22) | def __init__(self, data_root: str, split: str):
    method __len__ (line 53) | def __len__(self):
    method __getitem__ (line 56) | def __getitem__(self, idx: int):

FILE: virtex/data/datasets/downstream.py
  class ImageNetDataset (line 16) | class ImageNetDataset(ImageNet):
    method __init__ (line 29) | def __init__(
    method __getitem__ (line 38) | def __getitem__(self, idx: int) -> Dict[str, torch.Tensor]:
    method collate_fn (line 50) | def collate_fn(data: List[Dict[str, torch.Tensor]]) -> Dict[str, torch...
  class INaturalist2018Dataset (line 57) | class INaturalist2018Dataset(Dataset):
    method __init__ (line 69) | def __init__(
    method __len__ (line 92) | def __len__(self):
    method __getitem__ (line 95) | def __getitem__(self, idx: int):
    method collate_fn (line 111) | def collate_fn(data: List[Dict[str, torch.Tensor]]) -> Dict[str, torch...
  class VOC07ClassificationDataset (line 118) | class VOC07ClassificationDataset(Dataset):
    method __init__ (line 131) | def __init__(
    method __len__ (line 177) | def __len__(self):
    method __getitem__ (line 180) | def __getitem__(self, idx: int):
    method collate_fn (line 195) | def collate_fn(data: List[Dict[str, torch.Tensor]]) -> Dict[str, torch...
  class ImageDirectoryDataset (line 202) | class ImageDirectoryDataset(Dataset):
    method __init__ (line 214) | def __init__(
    method __len__ (line 220) | def __len__(self):
    method __getitem__ (line 223) | def __getitem__(self, idx: int):

FILE: virtex/data/datasets/masked_lm.py
  class MaskedLmDataset (line 15) | class MaskedLmDataset(Dataset):
    method __init__ (line 16) | def __init__(
    method __len__ (line 43) | def __len__(self):
    method __getitem__ (line 46) | def __getitem__(self, idx: int) -> Dict[str, torch.Tensor]:
    method collate_fn (line 101) | def collate_fn(
    method _random_token_index (line 124) | def _random_token_index(self) -> int:

FILE: virtex/data/tokenizers.py
  class SentencePieceBPETokenizer (line 6) | class SentencePieceBPETokenizer:
    method __init__ (line 16) | def __init__(self, model_path: str):
    method __getstate__ (line 23) | def __getstate__(self):
    method __setstate__ (line 32) | def __setstate__(self, state_dict: Dict[str, Any]):
    method get_vocab_size (line 38) | def get_vocab_size(self) -> int:
    method token_to_id (line 42) | def token_to_id(self, token: str) -> int:
    method id_to_token (line 48) | def id_to_token(self, token_id: int) -> str:
    method encode (line 52) | def encode(self, text: str) -> List[int]:
    method decode (line 56) | def decode(self, token_ids: List[int]) -> str:

FILE: virtex/data/transforms.py
  class HorizontalFlip (line 5) | class HorizontalFlip(alb.BasicTransform):
    method targets (line 25) | def targets(self):
    method apply (line 28) | def apply(self, img, **params):
    method apply_to_caption (line 31) | def apply_to_caption(self, caption, **params):
  class RandomResizedSquareCrop (line 40) | class RandomResizedSquareCrop(alb.RandomResizedCrop):
    method __init__ (line 49) | def __init__(self, size: int, *args, **kwargs):
  class CenterSquareCrop (line 53) | class CenterSquareCrop(alb.CenterCrop):
    method __init__ (line 62) | def __init__(self, size: int, *args, **kwargs):
  class SquareResize (line 66) | class SquareResize(alb.Resize):
    method __init__ (line 75) | def __init__(self, size: int, *args, **kwargs):

FILE: virtex/factories.py
  class Factory (line 40) | class Factory:
    method __init__ (line 60) | def __init__(self):
    method create (line 68) | def create(cls, name: str, *args, **kwargs) -> Any:
    method from_config (line 76) | def from_config(cls, config: Config) -> Any:
  class TokenizerFactory (line 81) | class TokenizerFactory(Factory):
    method from_config (line 94) | def from_config(cls, config: Config) -> SentencePieceBPETokenizer:
  class ImageTransformsFactory (line 111) | class ImageTransformsFactory(Factory):
    method create (line 158) | def create(cls, name: str, *args, **kwargs) -> Any:
    method from_config (line 171) | def from_config(cls, config: Config):
  class PretrainingDatasetFactory (line 176) | class PretrainingDatasetFactory(Factory):
    method from_config (line 200) | def from_config(cls, config: Config, split: str = "train"):
  class DownstreamDatasetFactory (line 249) | class DownstreamDatasetFactory(Factory):
    method from_config (line 264) | def from_config(cls, config: Config, split: str = "train"):
  class VisualBackboneFactory (line 306) | class VisualBackboneFactory(Factory):
    method from_config (line 322) | def from_config(cls, config: Config) -> visual_backbones.VisualBackbone:
  class TextualHeadFactory (line 344) | class TextualHeadFactory(Factory):
    method from_config (line 369) | def from_config(cls, config: Config) -> nn.Module:
  class PretrainingModelFactory (line 410) | class PretrainingModelFactory(Factory):
    method from_config (line 429) | def from_config(cls, config: Config) -> nn.Module:
  class CaptionDecoderFactory (line 469) | class CaptionDecoderFactory(Factory):
    method from_config (line 482) | def from_config(cls, config: Config) -> nn.Module:
  class OptimizerFactory (line 503) | class OptimizerFactory(Factory):
    method from_config (line 509) | def from_config(
  class LRSchedulerFactory (line 548) | class LRSchedulerFactory(Factory):
    method from_config (line 564) | def from_config(

FILE: virtex/model_zoo/model_zoo.py
  class _ModelZooUrls (line 30) | class _ModelZooUrls:
  function get (line 63) | def get(config_path: str, pretrained: bool = False):

FILE: virtex/models/captioning.py
  class CaptioningModel (line 13) | class CaptioningModel(nn.Module):
    method __init__ (line 40) | def __init__(
    method forward (line 71) | def forward(self, batch: Dict[str, torch.Tensor]) -> Dict[str, Any]:
    method decoding_step (line 165) | def decoding_step(
    method log_predictions (line 215) | def log_predictions(
  class ForwardCaptioningModel (line 234) | class ForwardCaptioningModel(CaptioningModel):
    method __init__ (line 240) | def __init__(
  class BidirectionalCaptioningModel (line 258) | class BidirectionalCaptioningModel(CaptioningModel):
    method __init__ (line 264) | def __init__(

FILE: virtex/models/classification.py
  class ClassificationModel (line 12) | class ClassificationModel(nn.Module):
    method __init__ (line 35) | def __init__(
    method forward (line 43) | def forward(self, batch: Dict[str, torch.Tensor]):
  class TokenClassificationModel (line 111) | class TokenClassificationModel(ClassificationModel):
    method log_predictions (line 120) | def log_predictions(
  class MultiLabelClassificationModel (line 143) | class MultiLabelClassificationModel(ClassificationModel):
    method log_predictions (line 152) | def log_predictions(

FILE: virtex/models/masked_lm.py
  class MaskedLMModel (line 11) | class MaskedLMModel(nn.Module):
    method __init__ (line 28) | def __init__(self, visual: VisualBackbone, textual: TextualHead):
    method forward (line 35) | def forward(self, batch: Dict[str, torch.Tensor]) -> Dict[str, Any]:
    method log_predictions (line 88) | def log_predictions(

FILE: virtex/modules/embedding.py
  class WordAndPositionalEmbedding (line 7) | class WordAndPositionalEmbedding(nn.Module):
    method __init__ (line 24) | def __init__(
    method forward (line 46) | def forward(self, tokens: torch.Tensor) -> torch.Tensor:
    method _create_position_indices (line 77) | def _create_position_indices(self, tokens: torch.Tensor):

FILE: virtex/modules/textual_heads.py
  class TextualHead (line 15) | class TextualHead(nn.Module):
    method __init__ (line 29) | def __init__(self, visual_feature_size: int, vocab_size: int, hidden_s...
    method textual_feature_size (line 36) | def textual_feature_size(self):
  class LinearTextualHead (line 46) | class LinearTextualHead(TextualHead):
    method __init__ (line 57) | def __init__(self, visual_feature_size: int, vocab_size: int, **kwargs):
    method forward (line 63) | def forward(
  class TransformerDecoderTextualHead (line 98) | class TransformerDecoderTextualHead(TextualHead):
    method __init__ (line 146) | def __init__(
    method _init_weights (line 203) | def _init_weights(module):
    method forward (line 216) | def forward(
    method make_future_mask (line 282) | def make_future_mask(

FILE: virtex/modules/visual_backbones.py
  class VisualBackbone (line 8) | class VisualBackbone(nn.Module):
    method __init__ (line 15) | def __init__(self, visual_feature_size: int):
  class TorchvisionVisualBackbone (line 20) | class TorchvisionVisualBackbone(VisualBackbone):
    method __init__ (line 34) | def __init__(
    method forward (line 55) | def forward(self, image: torch.Tensor) -> torch.Tensor:
    method detectron2_backbone_state_dict (line 76) | def detectron2_backbone_state_dict(self) -> Dict[str, Any]:

FILE: virtex/optim/lookahead.py
  class Lookahead (line 25) | class Lookahead(Optimizer):
    method __init__ (line 36) | def __init__(self, optimizer: Optimizer, k: int = 5, alpha: float = 0.8):
    method __getstate__ (line 52) | def __getstate__(self):
    method param_groups (line 62) | def param_groups(self):
    method zero_grad (line 65) | def zero_grad(self):
    method state_dict (line 69) | def state_dict(self):
    method load_state_dict (line 72) | def load_state_dict(self, state_dict: Dict[str, Any]):
    method step (line 82) | def step(self, closure: Callable = None):
    method load_slow_weights (line 104) | def load_slow_weights(self):
    method restore_fast_weights (line 120) | def restore_fast_weights(self):

FILE: virtex/optim/lr_scheduler.py
  class LinearWarmupNoDecayLR (line 9) | class LinearWarmupNoDecayLR(LambdaLR):
    method __init__ (line 23) | def __init__(
    method _lr_multiplier (line 38) | def _lr_multiplier(self, step: int) -> float:
  class LinearWarmupMultiStepLR (line 43) | class LinearWarmupMultiStepLR(LambdaLR):
    method __init__ (line 64) | def __init__(
    method _lr_multiplier (line 89) | def _lr_multiplier(self, step: int) -> float:
  class LinearWarmupLinearDecayLR (line 101) | class LinearWarmupLinearDecayLR(LambdaLR):
    method __init__ (line 115) | def __init__(
    method _lr_multiplier (line 130) | def _lr_multiplier(self, step: int) -> float:
  class LinearWarmupCosineAnnealingLR (line 141) | class LinearWarmupCosineAnnealingLR(LambdaLR):
    method __init__ (line 159) | def __init__(
    method _lr_multiplier (line 174) | def _lr_multiplier(self, step: int) -> float:

FILE: virtex/utils/beam_search.py
  class AutoRegressiveBeamSearch (line 25) | class AutoRegressiveBeamSearch:
    method __init__ (line 40) | def __init__(
    method search (line 52) | def search(

FILE: virtex/utils/checkpointing.py
  class CheckpointManager (line 12) | class CheckpointManager:
    method __init__ (line 48) | def __init__(
    method step (line 68) | def step(self, iteration: int, metric: Optional[float] = None):
    method _state_dict (line 107) | def _state_dict(self):
    method remove_earliest_checkpoint (line 121) | def remove_earliest_checkpoint(self):
    method load (line 127) | def load(self, checkpoint_path: str):

FILE: virtex/utils/common.py
  function cycle (line 14) | def cycle(dataloader, device, start_iteration: int = 0):
  function common_setup (line 39) | def common_setup(_C: Config, _A: argparse.Namespace, job_type: str = "pr...
  function common_parser (line 102) | def common_parser(description: str = "") -> argparse.ArgumentParser:

FILE: virtex/utils/distributed.py
  function launch (line 15) | def launch(
  function _job_worker (line 82) | def _job_worker(
  function synchronize (line 115) | def synchronize() -> None:
  function get_world_size (line 121) | def get_world_size() -> int:
  function get_rank (line 126) | def get_rank() -> int:
  function is_master_process (line 131) | def is_master_process() -> bool:
  function average_across_processes (line 140) | def average_across_processes(t: Union[torch.Tensor, Dict[str, torch.Tens...
  function gpu_mem_usage (line 163) | def gpu_mem_usage() -> int:

FILE: virtex/utils/metrics.py
  class TopkAccuracy (line 22) | class TopkAccuracy:
    method __init__ (line 35) | def __init__(self, k: int = 1):
    method reset (line 39) | def reset(self):
    method __call__ (line 43) | def __call__(self, predictions: torch.Tensor, ground_truth: torch.Tens...
    method get_result (line 70) | def get_result(self):
  class CocoCaptionsEvaluator (line 75) | class CocoCaptionsEvaluator:
    method __init__ (line 85) | def __init__(self, gt_annotations_path: str):
    method evaluate (line 95) | def evaluate(self, preds: List[Dict[str, Any]]) -> Dict[str, float]:
  function tokenize (line 125) | def tokenize(image_id_to_captions: Dict[int, List[str]]) -> Dict[int, Li...
  function cider (line 177) | def cider(
  function spice (line 267) | def spice(

FILE: virtex/utils/nucleus_sampling.py
  class AutoRegressiveNucleusSampling (line 25) | class AutoRegressiveNucleusSampling:
    method __init__ (line 36) | def __init__(
    method search (line 47) | def search(

FILE: virtex/utils/timer.py
  class Timer (line 5) | class Timer:
    method __init__ (line 17) | def __init__(
    method tic (line 31) | def tic(self) -> None:
    method toc (line 35) | def toc(self) -> None:
    method stats (line 42) | def stats(self) -> str:
    method eta_hhmm (line 50) | def eta_hhmm(self) -> str: