SYMBOL INDEX (93 symbols across 8 files)

FILE: clip/clip.py
  function _download (line 45) | def _download(url: str, root: str):
  function _convert_image_to_rgb (line 77) | def _convert_image_to_rgb(image):
  function _transform (line 81) | def _transform(n_px):
  function available_models (line 91) | def available_models() -> List[str]:
  function load (line 96) | def load(name: str, device: Union[str, torch.device] = "cuda" if torch.c...
  function tokenize (line 198) | def tokenize(texts: Union[str, List[str]], context_length: int = 77, tru...

FILE: clip/model.py
  class Bottleneck (line 14) | class Bottleneck(nn.Module):
    method __init__ (line 17) | def __init__(self, inplanes, planes, stride=1):
    method forward (line 44) | def forward(self, x: torch.Tensor):
  class AttentionPool2d (line 60) | class AttentionPool2d(nn.Module):
    method __init__ (line 61) | def __init__(self, spacial_dim: int, embed_dim: int, num_heads: int, o...
    method forward (line 70) | def forward(self, x, return_all_tokens=False):
  class ModifiedResNet (line 99) | class ModifiedResNet(nn.Module):
    method __init__ (line 107) | def __init__(self, layers, output_dim, heads, input_resolution=224, wi...
    method _make_layer (line 132) | def _make_layer(self, planes, blocks, stride=1):
    method forward (line 141) | def forward(self, x, return_all_tokens=False):
  class LayerNorm (line 159) | class LayerNorm(nn.LayerNorm):
    method forward (line 162) | def forward(self, x: torch.Tensor):
  class QuickGELU (line 168) | class QuickGELU(nn.Module):
    method forward (line 169) | def forward(self, x: torch.Tensor):
  class ResidualAttentionBlock (line 173) | class ResidualAttentionBlock(nn.Module):
    method __init__ (line 174) | def __init__(self, d_model: int, n_head: int, attn_mask: torch.Tensor ...
    method attention (line 187) | def attention(self, x: torch.Tensor):
    method forward (line 192) | def forward(self, x: torch.Tensor):
  class Transformer (line 198) | class Transformer(nn.Module):
    method __init__ (line 199) | def __init__(self, width: int, layers: int, heads: int, attn_mask: tor...
    method forward (line 205) | def forward(self, x: torch.Tensor):
  class VisionTransformer (line 209) | class VisionTransformer(nn.Module):
    method __init__ (line 210) | def __init__(self, input_resolution: int, patch_size: int, width: int,...
    method forward (line 229) | def forward(self, x: torch.Tensor, return_all=False, csa=True):
    method interpolate_pos_encoding (line 263) | def interpolate_pos_encoding(self, x, w, h):
    method custom_attn (line 283) | def custom_attn(self, attn_layer, x, return_attn=False, with_attn=Fals...
    method get_attn (line 315) | def get_attn(self, x, layer='all', csa=False):
  class CLIP (line 358) | class CLIP(nn.Module):
    method __init__ (line 359) | def __init__(self,
    method initialize_parameters (line 413) | def initialize_parameters(self):
    method build_attention_mask (line 442) | def build_attention_mask(self):
    method dtype (line 451) | def dtype(self):
    method encode_image (line 454) | def encode_image(self, image, return_all=False, csa=False):
    method encode_text (line 457) | def encode_text(self, text):
    method forward (line 468) | def forward(self, image, text):
  function convert_weights (line 484) | def convert_weights(model: nn.Module):
  function build_model (line 507) | def build_model(state_dict: dict):

FILE: clip/simple_tokenizer.py
  function default_bpe (line 14) | def default_bpe():
  function bytes_to_unicode (line 19) | def bytes_to_unicode():
  function get_pairs (line 41) | def get_pairs(word):
  function basic_clean (line 53) | def basic_clean(text):
  function whitespace_clean (line 59) | def whitespace_clean(text):
  class SimpleTokenizer (line 65) | class SimpleTokenizer(object):
    method __init__ (line 66) | def __init__(self, bpe_path: str = default_bpe()):
    method bpe (line 83) | def bpe(self, token):
    method encode (line 124) | def encode(self, text):
    method decode (line 132) | def decode(self, tokens):

FILE: clip_segmentor.py
  class CLIPForSegmentation (line 18) | class CLIPForSegmentation(BaseSegmentor):
    method __init__ (line 19) | def __init__(self, clip_path, name_path, device=torch.device('cuda'),
    method forward_feature (line 59) | def forward_feature(self, img, logit_size=None):
    method forward_slide (line 80) | def forward_slide(self, img, img_metas, stride=112, crop_size=224):
    method predict (line 127) | def predict(self, inputs, data_samples):
    method postprocess_result (line 148) | def postprocess_result(self, seg_logits, data_samples):
    method _forward (line 181) | def _forward(data_samples):
    method inference (line 185) | def inference(self, img, batch_img_metas):
    method encode_decode (line 189) | def encode_decode(self, inputs, batch_img_metas):
    method extract_feat (line 193) | def extract_feat(self, inputs):
    method loss (line 197) | def loss(self, inputs, data_samples):
  function get_cls_idx (line 201) | def get_cls_idx(path):

FILE: custom_datasets.py
  class PascalVOC20Dataset (line 8) | class PascalVOC20Dataset(BaseSegDataset):
    method __init__ (line 26) | def __init__(self,
  class COCOObjectDataset (line 42) | class COCOObjectDataset(BaseSegDataset):
    method __init__ (line 74) | def __init__(self, **kwargs):
  class PascalContext60Dataset (line 78) | class PascalContext60Dataset(BaseSegDataset):
    method __init__ (line 106) | def __init__(self,
  class PascalContext59Dataset (line 120) | class PascalContext59Dataset(BaseSegDataset):
    method __init__ (line 148) | def __init__(self,

FILE: datasets/cvt_coco_object.py
  function convert_to_trainID (line 200) | def convert_to_trainID(maskpath, out_mask_dir, is_train):
  function parse_args (line 214) | def parse_args():
  function main (line 226) | def main():

FILE: eval.py
  function parse_args (line 9) | def parse_args():
  function trigger_visualization_hook (line 35) | def trigger_visualization_hook(cfg, args):
  function main (line 55) | def main():

FILE: pamr.py
  class LocalAffinity (line 13) | class LocalAffinity(nn.Module):
    method __init__ (line 15) | def __init__(self, dilations=[1]):
    method _init_aff (line 21) | def _init_aff(self):
    method forward (line 43) | def forward(self, x):
  class LocalAffinityCopy (line 60) | class LocalAffinityCopy(LocalAffinity):
    method _init_aff (line 62) | def _init_aff(self):
  class LocalStDev (line 80) | class LocalStDev(LocalAffinity):
    method _init_aff (line 82) | def _init_aff(self):
    method forward (line 101) | def forward(self, x):
  class LocalAffinityAbs (line 108) | class LocalAffinityAbs(LocalAffinity):
    method forward (line 110) | def forward(self, x):
  class PAMR (line 117) | class PAMR(nn.Module):
    method __init__ (line 119) | def __init__(self, num_iter=1, dilations=[1]):
    method forward (line 127) | def forward(self, x, mask):