SYMBOL INDEX (217 symbols across 25 files)

FILE: diffuzers/Home.py
  function parse_args (line 10) | def parse_args():
  function x2img_app (line 28) | def x2img_app():
  function run_app (line 84) | def run_app():

FILE: diffuzers/api/main.py
  function startup_event (line 26) | async def startup_event():
  function text2img (line 67) | async def text2img(params: Text2ImgParams) -> ImgResponse:
  function img2img (line 87) | async def img2img(params: Img2ImgParams = Depends(), image: UploadFile =...
  function instruct_pix2pix (line 107) | async def instruct_pix2pix(params: InstructPix2PixParams = Depends(), im...
  function inpainting (line 127) | async def inpainting(
  function read_root (line 152) | def read_root():

FILE: diffuzers/api/schemas.py
  class Text2ImgParams (line 6) | class Text2ImgParams(BaseModel):
  class Img2ImgParams (line 18) | class Img2ImgParams(BaseModel):
  class InstructPix2PixParams (line 29) | class InstructPix2PixParams(BaseModel):
  class ImgResponse (line 40) | class ImgResponse(BaseModel):
  class InpaintingParams (line 45) | class InpaintingParams(BaseModel):

FILE: diffuzers/api/utils.py
  function convert_to_b64_list (line 5) | def convert_to_b64_list(images):

FILE: diffuzers/blip.py
  class Mlp (line 59) | class Mlp(nn.Module):
    method __init__ (line 62) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 71) | def forward(self, x):
  class Attention (line 80) | class Attention(nn.Module):
    method __init__ (line 81) | def __init__(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, at...
    method save_attn_gradients (line 94) | def save_attn_gradients(self, attn_gradients):
    method get_attn_gradients (line 97) | def get_attn_gradients(self):
    method save_attention_map (line 100) | def save_attention_map(self, attention_map):
    method get_attention_map (line 103) | def get_attention_map(self):
    method forward (line 106) | def forward(self, x, register_hook=False):
  class Block (line 125) | class Block(nn.Module):
    method __init__ (line 126) | def __init__(
    method forward (line 155) | def forward(self, x, register_hook=False):
  class VisionTransformer (line 161) | class VisionTransformer(nn.Module):
    method __init__ (line 167) | def __init__(
    method _init_weights (line 241) | def _init_weights(self, m):
    method no_weight_decay (line 251) | def no_weight_decay(self):
    method forward (line 254) | def forward(self, x, register_blk=-1):
    method load_pretrained (line 271) | def load_pretrained(self, checkpoint_path, prefix=""):
  function _load_weights (line 276) | def _load_weights(model: VisionTransformer, checkpoint_path: str, prefix...
  function interpolate_pos_embed (line 352) | def interpolate_pos_embed(pos_embed_checkpoint, visual_encoder):
  class BertEmbeddings (line 380) | class BertEmbeddings(nn.Module):
    method __init__ (line 383) | def __init__(self, config):
    method forward (line 399) | def forward(self, input_ids=None, position_ids=None, inputs_embeds=Non...
  class BertSelfAttention (line 423) | class BertSelfAttention(nn.Module):
    method __init__ (line 424) | def __init__(self, config, is_cross_attention):
    method save_attn_gradients (line 452) | def save_attn_gradients(self, attn_gradients):
    method get_attn_gradients (line 455) | def get_attn_gradients(self):
    method save_attention_map (line 458) | def save_attention_map(self, attention_map):
    method get_attention_map (line 461) | def get_attention_map(self):
    method transpose_for_scores (line 464) | def transpose_for_scores(self, x):
    method forward (line 469) | def forward(
  class BertSelfOutput (line 554) | class BertSelfOutput(nn.Module):
    method __init__ (line 555) | def __init__(self, config):
    method forward (line 561) | def forward(self, hidden_states, input_tensor):
  class BertAttention (line 568) | class BertAttention(nn.Module):
    method __init__ (line 569) | def __init__(self, config, is_cross_attention=False):
    method prune_heads (line 575) | def prune_heads(self, heads):
    method forward (line 593) | def forward(
  class BertIntermediate (line 617) | class BertIntermediate(nn.Module):
    method __init__ (line 618) | def __init__(self, config):
    method forward (line 626) | def forward(self, hidden_states):
  class BertOutput (line 632) | class BertOutput(nn.Module):
    method __init__ (line 633) | def __init__(self, config):
    method forward (line 639) | def forward(self, hidden_states, input_tensor):
  class BertLayer (line 646) | class BertLayer(nn.Module):
    method __init__ (line 647) | def __init__(self, config, layer_num):
    method forward (line 659) | def forward(
    method feed_forward_chunk (line 706) | def feed_forward_chunk(self, attention_output):
  class BertEncoder (line 712) | class BertEncoder(nn.Module):
    method __init__ (line 713) | def __init__(self, config):
    method forward (line 719) | def forward(
  class BertPooler (line 812) | class BertPooler(nn.Module):
    method __init__ (line 813) | def __init__(self, config):
    method forward (line 818) | def forward(self, hidden_states):
  class BertPredictionHeadTransform (line 827) | class BertPredictionHeadTransform(nn.Module):
    method __init__ (line 828) | def __init__(self, config):
    method forward (line 837) | def forward(self, hidden_states):
  class BertLMPredictionHead (line 844) | class BertLMPredictionHead(nn.Module):
    method __init__ (line 845) | def __init__(self, config):
    method forward (line 858) | def forward(self, hidden_states):
  class BertOnlyMLMHead (line 864) | class BertOnlyMLMHead(nn.Module):
    method __init__ (line 865) | def __init__(self, config):
    method forward (line 869) | def forward(self, sequence_output):
  class BertPreTrainedModel (line 874) | class BertPreTrainedModel(PreTrainedModel):
    method _init_weights (line 884) | def _init_weights(self, module):
  class BertModel (line 897) | class BertModel(BertPreTrainedModel):
    method __init__ (line 907) | def __init__(self, config, add_pooling_layer=True):
    method get_input_embeddings (line 919) | def get_input_embeddings(self):
    method set_input_embeddings (line 922) | def set_input_embeddings(self, value):
    method _prune_heads (line 925) | def _prune_heads(self, heads_to_prune):
    method get_extended_attention_mask (line 933) | def get_extended_attention_mask(
    method forward (line 998) | def forward(
  class BertLMHeadModel (line 1139) | class BertLMHeadModel(BertPreTrainedModel):
    method __init__ (line 1144) | def __init__(self, config):
    method get_output_embeddings (line 1152) | def get_output_embeddings(self):
    method set_output_embeddings (line 1155) | def set_output_embeddings(self, new_embeddings):
    method forward (line 1158) | def forward(
    method prepare_inputs_for_generation (line 1260) | def prepare_inputs_for_generation(self, input_ids, past=None, attentio...
    method _reorder_cache (line 1279) | def _reorder_cache(self, past, beam_idx):
  class BLIP_Base (line 1286) | class BLIP_Base(nn.Module):
    method __init__ (line 1287) | def __init__(
    method forward (line 1329) | def forward(self, image, caption, mode):
  class BLIP_Decoder (line 1362) | class BLIP_Decoder(nn.Module):
    method __init__ (line 1363) | def __init__(
    method forward (line 1409) | def forward(self, image, caption):
    method generate (line 1435) | def generate(
  function blip_decoder (line 1485) | def blip_decoder(pretrained="", **kwargs):
  function blip_feature_extractor (line 1493) | def blip_feature_extractor(pretrained="", **kwargs):
  function init_tokenizer (line 1501) | def init_tokenizer():
  function create_vit (line 1509) | def create_vit(vit, image_size, use_grad_checkpointing=False, ckpt_layer...
  function is_url (line 1539) | def is_url(url_or_filename):
  function load_checkpoint (line 1544) | def load_checkpoint(model, url_or_filename):

FILE: diffuzers/cli/__init__.py
  class BaseDiffuzersCommand (line 5) | class BaseDiffuzersCommand(ABC):
    method register_subcommand (line 8) | def register_subcommand(parser: ArgumentParser):
    method run (line 12) | def run(self):

FILE: diffuzers/cli/main.py
  function main (line 8) | def main():

FILE: diffuzers/cli/run_api.py
  function run_api_command_factory (line 9) | def run_api_command_factory(args):
  class RunDiffuzersAPICommand (line 21) | class RunDiffuzersAPICommand(BaseDiffuzersCommand):
    method register_subcommand (line 23) | def register_subcommand(parser: ArgumentParser):
    method __init__ (line 75) | def __init__(self, output, port, host, device, workers, ssl_certfile, ...
    method run (line 90) | def run(self):

FILE: diffuzers/cli/run_app.py
  function run_app_command_factory (line 10) | def run_app_command_factory(args):
  class RunDiffuzersAppCommand (line 21) | class RunDiffuzersAppCommand(BaseDiffuzersCommand):
    method register_subcommand (line 23) | def register_subcommand(parser: ArgumentParser):
    method __init__ (line 68) | def __init__(self, output, share, port, host, device, ngrok_key):
    method run (line 85) | def run(self):

FILE: diffuzers/clip_interrogator.py
  class Config (line 26) | class Config:
  class Interrogator (line 54) | class Interrogator:
    method __init__ (line 55) | def __init__(self, config: Config):
    method load_clip_model (line 79) | def load_clip_model(self):
    method generate_caption (line 147) | def generate_caption(self, pil_image: Image) -> str:
    method image_to_features (line 175) | def image_to_features(self, image: Image) -> torch.Tensor:
    method interrogate_classic (line 182) | def interrogate_classic(self, image: Image, max_flavors: int = 3) -> str:
    method interrogate_fast (line 199) | def interrogate_fast(self, image: Image, max_flavors: int = 32) -> str:
    method interrogate (line 206) | def interrogate(self, image: Image, max_flavors: int = 32) -> str:
    method rank_top (line 257) | def rank_top(self, image_features: torch.Tensor, text_array: List[str]...
    method similarity (line 265) | def similarity(self, image_features: torch.Tensor, text: str) -> float:
  class LabelTable (line 274) | class LabelTable:
    method __init__ (line 275) | def __init__(self, labels: List[str], desc: str, clip_model, tokenize,...
    method _rank (line 322) | def _rank(self, image_features: torch.Tensor, text_embeds: torch.Tenso...
    method rank (line 330) | def rank(self, image_features: torch.Tensor, top_count: int = 1) -> Li...
  function _load_list (line 350) | def _load_list(data_path: str, filename: str) -> List[str]:
  function _merge_tables (line 356) | def _merge_tables(tables: List[LabelTable], config: Config) -> LabelTable:
  function _prompt_at_max_len (line 364) | def _prompt_at_max_len(text: str, tokenize) -> bool:
  function _truncate_to_fit (line 369) | def _truncate_to_fit(text: str, tokenize) -> str:

FILE: diffuzers/gfp_gan.py
  class GFPGAN (line 22) | class GFPGAN:
    method __str__ (line 26) | def __str__(self) -> str:
    method __post_init__ (line 29) | def __post_init__(self):
    method inference (line 71) | def inference(self, img, version, scale):
    method app (line 139) | def app(self):

FILE: diffuzers/gradio_app.py
  class Diffuzers (line 14) | class Diffuzers:
    method __post_init__ (line 20) | def __post_init__(self):
    method _text2img_input (line 35) | def _text2img_input(self):
    method _text2img_output (line 73) | def _text2img_output(self):
    method _text2img_generate (line 85) | def _text2img_generate(
    method _img2img_input (line 116) | def _img2img_input(self):
    method _img2img_output (line 149) | def _img2img_output(self):
    method _img2img_generate (line 161) | def _img2img_generate(
    method _save_images (line 206) | def _save_images(self, images, metadata, folder_name, prefix):
    method _png_info (line 216) | def _png_info(self, img):
    method app (line 226) | def app(self):

FILE: diffuzers/image_info.py
  class ImageInfo (line 8) | class ImageInfo:
    method app (line 9) | def app(self):

FILE: diffuzers/img2img.py
  class Img2Img (line 25) | class Img2Img:
    method __str__ (line 31) | def __str__(self) -> str:
    method __post_init__ (line 34) | def __post_init__(self):
    method _set_scheduler (line 71) | def _set_scheduler(self, scheduler_name):
    method generate_image (line 75) | def generate_image(
    method app (line 119) | def app(self):

FILE: diffuzers/inpainting.py
  class Inpainting (line 21) | class Inpainting:
    method __str__ (line 26) | def __str__(self) -> str:
    method __post_init__ (line 29) | def __post_init__(self):
    method _set_scheduler (line 64) | def _set_scheduler(self, scheduler_name):
    method generate_image (line 68) | def generate_image(
    method app (line 120) | def app(self):

FILE: diffuzers/interrogator.py
  class ImageInterrogator (line 15) | class ImageInterrogator:
    method inference (line 19) | def inference(self, model, image, mode):
    method app (line 53) | def app(self):

FILE: diffuzers/pages/1_Inpainting.py
  function app (line 7) | def app():

FILE: diffuzers/pages/2_Utilities.py
  function app (line 10) | def app():

FILE: diffuzers/pages/3_FAQs.py
  function app (line 6) | def app():

FILE: diffuzers/pages/4_Code of Conduct.py
  function app (line 6) | def app():

FILE: diffuzers/text2img.py
  class Text2Image (line 16) | class Text2Image:
    method __str__ (line 21) | def __str__(self) -> str:
    method __post_init__ (line 24) | def __post_init__(self):
    method _set_scheduler (line 41) | def _set_scheduler(self, scheduler_name):
    method generate_image (line 45) | def generate_image(self, prompt, negative_prompt, scheduler, image_siz...
    method app (line 89) | def app(self):

FILE: diffuzers/textual_inversion.py
  function load_embed (line 15) | def load_embed(learned_embeds_path, text_encoder, tokenizer, token=None):
  class TextualInversion (line 45) | class TextualInversion:
    method __str__ (line 52) | def __str__(self) -> str:
    method __post_init__ (line 55) | def __post_init__(self):
    method _set_scheduler (line 81) | def _set_scheduler(self, scheduler_name):
    method generate_image (line 85) | def generate_image(self, prompt, negative_prompt, scheduler, image_siz...
    method app (line 129) | def app(self):

FILE: diffuzers/upscaler.py
  class Upscaler (line 17) | class Upscaler:
    method __str__ (line 22) | def __str__(self) -> str:
    method __post_init__ (line 25) | def __post_init__(self):
    method _set_scheduler (line 36) | def _set_scheduler(self, scheduler_name):
    method generate_image (line 40) | def generate_image(
    method app (line 89) | def app(self):

FILE: diffuzers/utils.py
  function use_auth_token (line 44) | def use_auth_token():
  function create_base_page (line 53) | def create_base_page():
  function download_file (line 59) | def download_file(file_url):
  function cache_folder (line 68) | def cache_folder():
  function clear_memory (line 74) | def clear_memory(preserve):
  function save_to_hub (line 83) | def save_to_hub(api, images, module, current_datetime, metadata, output_...
  function save_to_local (line 107) | def save_to_local(images, module, current_datetime, metadata, output_path):
  function save_images (line 126) | def save_images(images, module, metadata, output_path):
  function display_and_download_images (line 146) | def display_and_download_images(output_images, metadata, download_col=No...

FILE: diffuzers/x2image.py
  function load_embed (line 30) | def load_embed(learned_embeds_path, text_encoder, tokenizer, token=None):
  class X2Image (line 60) | class X2Image:
    method __str__ (line 68) | def __str__(self) -> str:
    method __post_init__ (line 71) | def __post_init__(self):
    method _set_scheduler (line 134) | def _set_scheduler(self, pipeline_name, scheduler_name):
    method _pregen (line 151) | def _pregen(self, pipeline_name, scheduler, num_images, seed):
    method _postgen (line 161) | def _postgen(self, metadata, output_images, pipeline_name):
    method text2img_generate (line 175) | def text2img_generate(
    method img2img_generate (line 217) | def img2img_generate(
    method pix2pix_generate (line 257) | def pix2pix_generate(
    method app (line 297) | def app(self):