SYMBOL INDEX (466 symbols across 60 files)

FILE: FaithDiff/create_FaithDiff_model.py
  function FaithDiff_pipeline (line 10) | def FaithDiff_pipeline(sdxl_path, VAE_FP16_path, FaithDiff_path, use_fp8...
  function create_bsrnet (line 35) | def create_bsrnet(bsrnet_path):

FILE: FaithDiff/models/bsrnet_arch.py
  function initialize_weights (line 8) | def initialize_weights(net_l, scale=1):
  function make_layer (line 28) | def make_layer(block, n_layers):
  class ResidualDenseBlock_5C (line 35) | class ResidualDenseBlock_5C(nn.Module):
    method __init__ (line 36) | def __init__(self, nf=64, gc=32, bias=True):
    method forward (line 49) | def forward(self, x):
  class RRDB (line 58) | class RRDB(nn.Module):
    method __init__ (line 61) | def __init__(self, nf, gc=32):
    method forward (line 67) | def forward(self, x):
  class RRDBNet (line 74) | class RRDBNet(nn.Module):
    method __init__ (line 75) | def __init__(self, in_nc=3, out_nc=3, nf=64, nb=23, gc=32, sf=4):
    method check_image_size (line 93) | def check_image_size(self, x, scale):
    method forward (line 101) | def forward(self, x):
    method deg_remove (line 116) | def deg_remove(self, input, tile_size=512, tile_pad=16):

FILE: FaithDiff/models/unet_2d_condition_vae_extension.py
  function zero_module (line 33) | def zero_module(module):
  class Encoder (line 39) | class Encoder(nn.Module):
    method __init__ (line 41) | def __init__(
    method to_rgb_init (line 110) | def to_rgb_init(self):
    method enable_tiling (line 118) | def enable_tiling(self):
    method encode (line 122) | def encode(self, sample: torch.FloatTensor) -> torch.FloatTensor:
    method blend_v (line 150) | def blend_v(self, a: torch.Tensor, b: torch.Tensor, blend_extent: int)...
    method blend_h (line 157) | def blend_h(self, a: torch.Tensor, b: torch.Tensor, blend_extent: int)...
    method tiled_encode (line 164) | def tiled_encode(self, x: torch.FloatTensor) -> torch.FloatTensor:
    method forward (line 192) | def forward(self, sample: torch.FloatTensor) -> torch.FloatTensor:
  class ControlNetConditioningEmbedding (line 199) | class ControlNetConditioningEmbedding(nn.Module):
    method __init__ (line 201) | def __init__(
    method forward (line 213) | def forward(self, conditioning):
  class QuickGELU (line 222) | class QuickGELU(nn.Module):
    method forward (line 224) | def forward(self, x: torch.Tensor):
  class LayerNorm (line 229) | class LayerNorm(nn.LayerNorm):
    method forward (line 231) | def forward(self, x: torch.Tensor):
  class ResidualAttentionBlock (line 238) | class ResidualAttentionBlock(nn.Module):
    method __init__ (line 240) | def __init__(self, d_model: int, n_head: int, attn_mask: torch.Tensor ...
    method attention (line 251) | def attention(self, x: torch.Tensor):
    method forward (line 256) | def forward(self, x: torch.Tensor):
  class UNet2DConditionOutput (line 264) | class UNet2DConditionOutput(BaseOutput):
  class UNet2DConditionModel (line 269) | class UNet2DConditionModel(OriginalUNet2DConditionModel, ConfigMixin, UN...
    method __init__ (line 274) | def __init__(
    method init_vae_encoder (line 389) | def init_vae_encoder(self, dtype):
    method init_information_transformer_layes (line 393) | def init_information_transformer_layes(self):
    method init_ControlNetConditioningEmbedding (line 400) | def init_ControlNetConditioningEmbedding(self, channel=512):
    method init_extra_weights (line 402) | def init_extra_weights(self):
    method load_additional_layers (line 405) | def load_additional_layers(self, dtype: Optional[torch.dtype] = torch....
    method to (line 435) | def to(self, *args, **kwargs):
    method load_state_dict (line 444) | def load_state_dict(self, state_dict, strict=True):
    method forward (line 480) | def forward(

FILE: FaithDiff/pipelines/pipeline_FaithDiff_tlc.py
  function img2tensor (line 74) | def img2tensor(imgs, bgr2rgb=True, float32=True):
  class LocalAttention (line 101) | class LocalAttention:
    method __init__ (line 104) | def __init__(self, kernel_size=None, overlap=0.5):
    method grids_list (line 115) | def grids_list(self, x):
    method grids (line 160) | def grids(self, x):
    method _gaussian_weights (line 207) | def _gaussian_weights(self, tile_width, tile_height):
    method grids_inverse (line 230) | def grids_inverse(self, outs):
    method _pad (line 254) | def _pad(self, x):
    method forward (line 271) | def forward(self, x):
  function rescale_noise_cfg (line 286) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  function retrieve_latents (line 308) | def retrieve_latents(
  function retrieve_timesteps (line 331) | def retrieve_timesteps(
  class FaithDiffStableDiffusionXLPipeline (line 374) | class FaithDiffStableDiffusionXLPipeline(
    method __init__ (line 445) | def __init__(
    method encode_prompt (line 485) | def encode_prompt(
    method prepare_extra_step_kwargs (line 720) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 737) | def check_inputs(
    method prepare_latents (line 820) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method upcast_vae (line 837) | def upcast_vae(self):
    method get_guidance_scale_embedding (line 858) | def get_guidance_scale_embedding(
    method set_encoder_tile_settings (line 888) | def set_encoder_tile_settings(self,
    method enable_vae_tiling (line 898) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 907) | def disable_vae_tiling(self):
    method guidance_scale (line 916) | def guidance_scale(self):
    method guidance_rescale (line 920) | def guidance_rescale(self):
    method clip_skip (line 924) | def clip_skip(self):
    method do_classifier_free_guidance (line 931) | def do_classifier_free_guidance(self):
    method cross_attention_kwargs (line 935) | def cross_attention_kwargs(self):
    method denoising_end (line 939) | def denoising_end(self):
    method num_timesteps (line 943) | def num_timesteps(self):
    method interrupt (line 947) | def interrupt(self):
    method prepare_image_latents (line 950) | def prepare_image_latents(
    method __call__ (line 1008) | def __call__(

FILE: FaithDiff/pipelines/pipeline_output.py
  class FaithDiffStableDiffusionXLPipelineOutput (line 11) | class FaithDiffStableDiffusionXLPipelineOutput(BaseOutput):
  class FlaxFaithDiffStableDiffusionXLPipelineOutput (line 28) | class FlaxFaithDiffStableDiffusionXLPipelineOutput(BaseOutput):

FILE: FaithDiff/training_utils.py
  function set_seed (line 40) | def set_seed(seed: int):
  function compute_snr (line 60) | def compute_snr(noise_scheduler, timesteps):
  function resolve_interpolation_mode (line 97) | def resolve_interpolation_mode(interpolation_type: str):
  function compute_dream_and_update_latents (line 141) | def compute_dream_and_update_latents(
  function unet_lora_state_dict (line 195) | def unet_lora_state_dict(unet: UNet2DConditionModel) -> Dict[str, torch....
  function cast_training_params (line 214) | def cast_training_params(model: Union[torch.nn.Module, List[torch.nn.Mod...
  function _set_state_dict_into_text_encoder (line 231) | def _set_state_dict_into_text_encoder(
  function compute_density_for_timestep_sampling (line 250) | def compute_density_for_timestep_sampling(
  function compute_loss_weighting_for_sd3 (line 272) | def compute_loss_weighting_for_sd3(weighting_scheme: str, sigmas=None):
  function free_memory (line 290) | def free_memory():
  function should_update_ema (line 305) | def should_update_ema(args, step):
  class EMAModel (line 316) | class EMAModel:
    method __init__ (line 321) | def __init__(
    method save_state_dict (line 414) | def save_state_dict(self, path: str) -> None:
    method load_state_dict (line 429) | def load_state_dict(self, path: str) -> None:
    method from_pretrained (line 470) | def from_pretrained(cls, path, model_cls) -> "EMAModel":
    method save_pretrained (line 481) | def save_pretrained(self, path, max_shard_size: str = "10GB"):
    method get_decay (line 500) | def get_decay(self, optimization_step: int = None) -> float:
    method step (line 523) | def step(self, parameters: Iterable[torch.nn.Parameter], global_step: ...
    method copy_to (line 633) | def copy_to(self, parameters: Iterable[torch.nn.Parameter]) -> None:
    method pin_memory (line 655) | def pin_memory(self) -> None:
    method to (line 670) | def to(self, *args, **kwargs):
    method cuda (line 675) | def cuda(self, device=None):
    method cpu (line 678) | def cpu(self):
    method state_dict (line 681) | def state_dict(
    method store (line 704) | def store(self, parameters: Iterable[torch.nn.Parameter]) -> None:
    method restore (line 710) | def restore(self, parameters: Iterable[torch.nn.Parameter]) -> None:
    method parameter_count (line 731) | def parameter_count(self) -> int:
    method named_children (line 736) | def named_children(self):
    method children (line 740) | def children(self):
    method modules (line 743) | def modules(self):
    method named_modules (line 746) | def named_modules(self, memo=None, prefix=""):
    method parameters (line 749) | def parameters(self, recurse=True):
    method named_parameters (line 752) | def named_parameters(self, prefix="", recurse=True):
    method buffers (line 757) | def buffers(self, recurse=True):
    method named_buffers (line 760) | def named_buffers(self, prefix="", recurse=True):
    method train (line 763) | def train(self, mode=True):
    method eval (line 767) | def eval(self):
    method zero_grad (line 770) | def zero_grad(self):

FILE: dataloader/Realesrgan_offline_dataset.py
  function ordered_yaml (line 26) | def ordered_yaml():
  function opt_parse (line 50) | def opt_parse(opt_path):
  function convert_image_to_fn (line 57) | def convert_image_to_fn(img_type, image, minsize=512, eps=0.02):
  function exists (line 66) | def exists(x):
  class LocalImageDataset (line 70) | class LocalImageDataset(data.Dataset):
    method __init__ (line 71) | def __init__(self,
    method __getitem__ (line 144) | def __getitem__(self, index):
    method __len__ (line 276) | def __len__(self):

FILE: dataloader/realesrgan.py
  function ordered_yaml (line 22) | def ordered_yaml():
  function opt_parse (line 46) | def opt_parse(opt_path):
  class RealESRGAN_degradation (line 53) | class RealESRGAN_degradation(object):
    method __init__ (line 54) | def __init__(self, opt_name='params_realesrgan.yml', device='cpu'):
    method color_jitter_pt (line 88) | def color_jitter_pt(self, img, brightness, contrast, saturation, hue):
    method random_augment (line 108) | def random_augment(self, img_gt):
    method random_kernels (line 129) | def random_kernels(self):
    method degrade_process (line 191) | def degrade_process(self, img_gt, resize_bak=False, seed=42):

FILE: gradio_demo.py
  function caption_process (line 59) | def caption_process(
  function clear_result (line 69) | def clear_result():
  function randomize_seed_fn (line 72) | def randomize_seed_fn(generation_seed: int, randomize_seed: bool) -> int:
  function process (line 78) | def process(

FILE: llava/conversation.py
  class SeparatorStyle (line 9) | class SeparatorStyle(Enum):
  class Conversation (line 19) | class Conversation:
    method get_prompt (line 32) | def get_prompt(self):
    method append_message (line 109) | def append_message(self, role, message):
    method process_image (line 112) | def process_image(self, image, image_process_mode, return_pil=False, i...
    method get_images (line 152) | def get_images(self, return_pil=False):
    method to_gradio_chatbot (line 162) | def to_gradio_chatbot(self):
    method copy (line 180) | def copy(self):
    method dict (line 191) | def dict(self):

FILE: llava/eval/eval_gpt_review.py
  function get_eval (line 13) | def get_eval(content: str, max_tokens: int):
  function parse_score (line 39) | def parse_score(review):

FILE: llava/eval/eval_gpt_review_bench.py
  function get_eval (line 11) | def get_eval(content: str, max_tokens: int):
  function parse_score (line 36) | def parse_score(review):

FILE: llava/eval/eval_gpt_review_visual.py
  function get_eval (line 11) | def get_eval(content: str, max_tokens: int):
  function parse_score (line 36) | def parse_score(review):

FILE: llava/eval/eval_pope.py
  function eval_pope (line 5) | def eval_pope(answers, label_file):

FILE: llava/eval/eval_science_qa.py
  function get_args (line 8) | def get_args():
  function convert_caps (line 19) | def convert_caps(results):
  function get_pred_idx (line 28) | def get_pred_idx(prediction, choices, options):

FILE: llava/eval/eval_science_qa_gpt4.py
  function get_args (line 9) | def get_args():
  function convert_caps (line 19) | def convert_caps(results):
  function get_pred_idx (line 28) | def get_pred_idx(prediction, choices, options):

FILE: llava/eval/eval_science_qa_gpt4_requery.py
  function get_args (line 9) | def get_args():
  function convert_caps (line 21) | def convert_caps(results):
  function get_pred_idx (line 30) | def get_pred_idx(prediction, choices, options):

FILE: llava/eval/eval_textvqa.py
  function get_args (line 9) | def get_args():
  function prompt_processor (line 17) | def prompt_processor(prompt):
  function eval_single (line 35) | def eval_single(annotation_file, result_file):

FILE: llava/eval/generate_webpage_data_from_table.py
  function read_jsonl (line 10) | def read_jsonl(path: str, key: str=None):
  function trim_hanging_lines (line 23) | def trim_hanging_lines(s: str, n: int) -> str:

FILE: llava/eval/m4c_evaluator.py
  class EvalAIAnswerProcessor (line 7) | class EvalAIAnswerProcessor:
    method __init__ (line 178) | def __init__(self, *args, **kwargs):
    method word_tokenize (line 181) | def word_tokenize(self, word):
    method process_punctuation (line 186) | def process_punctuation(self, in_text):
    method process_digit_article (line 198) | def process_digit_article(self, in_text):
    method __call__ (line 213) | def __call__(self, item):
  class TextVQAAccuracyEvaluator (line 221) | class TextVQAAccuracyEvaluator:
    method __init__ (line 222) | def __init__(self):
    method _compute_answer_scores (line 225) | def _compute_answer_scores(self, raw_answers):
    method eval_pred_list (line 248) | def eval_pred_list(self, pred_list):
  class STVQAAccuracyEvaluator (line 260) | class STVQAAccuracyEvaluator:
    method __init__ (line 261) | def __init__(self):
    method eval_pred_list (line 264) | def eval_pred_list(self, pred_list):
  class STVQAANLSEvaluator (line 276) | class STVQAANLSEvaluator:
    method __init__ (line 277) | def __init__(self):
    method get_anls (line 282) | def get_anls(self, s1, s2):
    method eval_pred_list (line 289) | def eval_pred_list(self, pred_list):
  class TextCapsBleu4Evaluator (line 301) | class TextCapsBleu4Evaluator:
    method __init__ (line 302) | def __init__(self):
    method eval_pred_list (line 321) | def eval_pred_list(self, pred_list):

FILE: llava/eval/model_qa.py
  function eval_model (line 14) | def eval_model(model_name, questions_file, answers_file):

FILE: llava/eval/model_vqa.py
  function split_list (line 18) | def split_list(lst, n):
  function get_chunk (line 24) | def get_chunk(lst, n, k):
  function eval_model (line 29) | def eval_model(args):

FILE: llava/eval/model_vqa_loader.py
  function split_list (line 19) | def split_list(lst, n):
  function get_chunk (line 25) | def get_chunk(lst, n, k):
  class CustomDataset (line 31) | class CustomDataset(Dataset):
    method __init__ (line 32) | def __init__(self, questions, image_folder, tokenizer, image_processor...
    method __getitem__ (line 39) | def __getitem__(self, index):
    method __len__ (line 60) | def __len__(self):
  function collate_fn (line 64) | def collate_fn(batch):
  function create_data_loader (line 72) | def create_data_loader(questions, image_folder, tokenizer, image_process...
  function eval_model (line 79) | def eval_model(args):

FILE: llava/eval/model_vqa_mmbench.py
  function split_list (line 22) | def split_list(lst, n):
  function get_chunk (line 28) | def get_chunk(lst, n, k):
  function is_none (line 33) | def is_none(value):
  function get_options (line 44) | def get_options(row, options):
  function eval_model (line 54) | def eval_model(args):

FILE: llava/eval/model_vqa_science.py
  function split_list (line 18) | def split_list(lst, n):
  function get_chunk (line 24) | def get_chunk(lst, n, k):
  function eval_model (line 29) | def eval_model(args):

FILE: llava/eval/qa_baseline_gpt35.py
  function get_answer (line 16) | def get_answer(question_id: int, question: str, max_tokens: int):

FILE: llava/eval/run_llava.py
  function image_parser (line 28) | def image_parser(args):
  function load_image (line 33) | def load_image(image_file):
  function load_images (line 42) | def load_images(image_files):
  function eval_model (line 50) | def eval_model(args):

FILE: llava/eval/summarize_gpt_review.py
  function parse_args (line 9) | def parse_args():

FILE: llava/eval/webpage/script.js
  function text2Markdown (line 35) | function text2Markdown(text) {
  function capitalizeFirstChar (line 41) | function capitalizeFirstChar(str) {
  function updateQuestionSelect (line 48) | function updateQuestionSelect(question_id) {
  function updateModelSelect (line 64) | function updateModelSelect() {
  function populateModels (line 70) | function populateModels(models) {
  function populateQuestions (line 81) | function populateQuestions(questions) {
  function displayQuestion (line 110) | function displayQuestion(index) {
  function displayAnswers (line 116) | function displayAnswers(index) {
  function switchQuestionAndCategory (line 203) | function switchQuestionAndCategory() {
  function updateExpandButtonVisibility (line 226) | function updateExpandButtonVisibility(card) {

FILE: llava/llm_agent.py
  class LLavaAgent (line 18) | class LLavaAgent:
    method __init__ (line 19) | def __init__(self, model_path, device='cuda', conv_mode='vicuna_v1', l...
    method update_qs (line 49) | def update_qs(self, qs=None):
    method gen_image_caption (line 65) | def gen_image_caption(self, imgs, temperature=0.2, top_p=0.7, num_beam...

FILE: llava/mm_utils.py
  function select_best_resolution (line 12) | def select_best_resolution(original_size, possible_resolutions):
  function resize_and_pad_image (line 42) | def resize_and_pad_image(image, target_resolution):
  function divide_to_patches (line 77) | def divide_to_patches(image, patch_size):
  function get_anyres_image_grid_shape (line 99) | def get_anyres_image_grid_shape(image_size, grid_pinpoints, patch_size):
  function process_anyres_image (line 119) | def process_anyres_image(image, processor, grid_pinpoints):
  function load_image_from_base64 (line 148) | def load_image_from_base64(image):
  function expand2square (line 152) | def expand2square(pil_img, background_color):
  function process_images (line 166) | def process_images(images, image_processor, model_cfg):
  function tokenizer_image_token (line 185) | def tokenizer_image_token(prompt, tokenizer, image_token_index=IMAGE_TOK...
  function get_model_name_from_path (line 207) | def get_model_name_from_path(model_path):
  class KeywordsStoppingCriteria (line 215) | class KeywordsStoppingCriteria(StoppingCriteria):
    method __init__ (line 216) | def __init__(self, keywords, tokenizer, input_ids):
    method call_for_batch (line 230) | def call_for_batch(self, output_ids: torch.LongTensor, scores: torch.F...
    method __call__ (line 243) | def __call__(self, output_ids: torch.LongTensor, scores: torch.FloatTe...

FILE: llava/model/apply_delta.py
  function apply_delta (line 13) | def apply_delta(base_model_path, target_model_path, delta_path):

FILE: llava/model/builder.py
  function load_pretrained_model (line 26) | def load_pretrained_model(model_path, model_base, model_name, load_8bit=...

FILE: llava/model/consolidate.py
  function consolidate_ckpt (line 13) | def consolidate_ckpt(src_path, dst_path):

FILE: llava/model/language_model/llava_llama.py
  class LlavaConfig (line 30) | class LlavaConfig(LlamaConfig):
  class LlavaLlamaModel (line 34) | class LlavaLlamaModel(LlavaMetaModel, LlamaModel):
    method __init__ (line 37) | def __init__(self, config: LlamaConfig):
  class LlavaLlamaForCausalLM (line 41) | class LlavaLlamaForCausalLM(LlamaForCausalLM, LlavaMetaForCausalLM):
    method __init__ (line 44) | def __init__(self, config):
    method get_model (line 54) | def get_model(self):
    method forward (line 57) | def forward(
    method generate (line 106) | def generate(
    method prepare_inputs_for_generation (line 145) | def prepare_inputs_for_generation(self, input_ids, past_key_values=None,

FILE: llava/model/language_model/llava_mistral.py
  class LlavaMistralConfig (line 31) | class LlavaMistralConfig(MistralConfig):
  class LlavaMistralModel (line 35) | class LlavaMistralModel(LlavaMetaModel, MistralModel):
    method __init__ (line 38) | def __init__(self, config: MistralConfig):
  class LlavaMistralForCausalLM (line 42) | class LlavaMistralForCausalLM(MistralForCausalLM, LlavaMetaForCausalLM):
    method __init__ (line 45) | def __init__(self, config):
    method get_model (line 54) | def get_model(self):
    method forward (line 57) | def forward(
    method generate (line 105) | def generate(
    method prepare_inputs_for_generation (line 144) | def prepare_inputs_for_generation(self, input_ids, past_key_values=None,

FILE: llava/model/language_model/llava_mpt.py
  class LlavaMptConfig (line 25) | class LlavaMptConfig(MptConfig):
  class LlavaMptModel (line 29) | class LlavaMptModel(LlavaMetaModel, MptModel):
    method __init__ (line 32) | def __init__(self, config: MptConfig):
    method embed_tokens (line 36) | def embed_tokens(self, x):
  class LlavaMptForCausalLM (line 40) | class LlavaMptForCausalLM(MptForCausalLM, LlavaMetaForCausalLM):
    method __init__ (line 44) | def __init__(self, config):
    method get_model (line 53) | def get_model(self):
    method _set_gradient_checkpointing (line 56) | def _set_gradient_checkpointing(self, module, value=False):
    method forward (line 60) | def forward(
    method prepare_inputs_for_generation (line 87) | def prepare_inputs_for_generation(self, input_ids, past_key_values=Non...

FILE: llava/model/llava_arch.py
  class LlavaMetaModel (line 29) | class LlavaMetaModel:
    method __init__ (line 31) | def __init__(self, config):
    method get_vision_tower (line 43) | def get_vision_tower(self):
    method initialize_vision_modules (line 49) | def initialize_vision_modules(self, model_args, fsdp=None):
  function unpad_image (line 100) | def unpad_image(tensor, original_size):
  class LlavaMetaForCausalLM (line 131) | class LlavaMetaForCausalLM(ABC):
    method get_model (line 134) | def get_model(self):
    method get_vision_tower (line 137) | def get_vision_tower(self):
    method encode_images (line 140) | def encode_images(self, images):
    method prepare_inputs_labels_for_multimodal (line 145) | def prepare_inputs_labels_for_multimodal(
    method initialize_vision_tokenizer (line 326) | def initialize_vision_tokenizer(self, model_args, tokenizer):

FILE: llava/model/make_delta.py
  function make_delta (line 13) | def make_delta(base_model_path, target_model_path, delta_path, hub_repo_...

FILE: llava/model/multimodal_encoder/builder.py
  function build_vision_tower (line 5) | def build_vision_tower(vision_tower_cfg, **kwargs):

FILE: llava/model/multimodal_encoder/clip_encoder.py
  class CLIPVisionTower (line 7) | class CLIPVisionTower(nn.Module):
    method __init__ (line 8) | def __init__(self, vision_tower, args, delay_load=False):
    method load_model (line 24) | def load_model(self, device_map=None):
    method feature_select (line 35) | def feature_select(self, image_forward_outs):
    method forward (line 46) | def forward(self, images):
    method dummy_feature (line 60) | def dummy_feature(self):
    method dtype (line 64) | def dtype(self):
    method device (line 68) | def device(self):
    method config (line 72) | def config(self):
    method hidden_size (line 79) | def hidden_size(self):
    method num_patches_per_side (line 83) | def num_patches_per_side(self):
    method num_patches (line 87) | def num_patches(self):

FILE: llava/model/multimodal_projector/builder.py
  class IdentityMap (line 6) | class IdentityMap(nn.Module):
    method __init__ (line 7) | def __init__(self):
    method forward (line 10) | def forward(self, x, *args, **kwargs):
    method config (line 14) | def config(self):
  class SimpleResBlock (line 18) | class SimpleResBlock(nn.Module):
    method __init__ (line 19) | def __init__(self, channels):
    method forward (line 28) | def forward(self, x):
  function build_vision_projector (line 33) | def build_vision_projector(config, delay_load=False, **kwargs):

FILE: llava/model/utils.py
  function auto_upgrade (line 4) | def auto_upgrade(config):

FILE: llava/serve/cli.py
  function load_image (line 18) | def load_image(image_file):
  function main (line 27) | def main(args):

FILE: llava/serve/controller.py
  class DispatchMethod (line 28) | class DispatchMethod(Enum):
    method from_str (line 33) | def from_str(cls, name):
  class WorkerInfo (line 43) | class WorkerInfo:
  function heart_beat_controller (line 51) | def heart_beat_controller(controller):
  class Controller (line 57) | class Controller:
    method __init__ (line 58) | def __init__(self, dispatch_method: str):
    method register_worker (line 69) | def register_worker(self, worker_name: str, check_heart_beat: bool,
    method get_worker_status (line 88) | def get_worker_status(self, worker_name: str):
    method remove_worker (line 101) | def remove_worker(self, worker_name: str):
    method refresh_all_workers (line 104) | def refresh_all_workers(self):
    method list_models (line 112) | def list_models(self):
    method get_worker_address (line 120) | def get_worker_address(self, model_name: str):
    method receive_heart_beat (line 173) | def receive_heart_beat(self, worker_name: str, queue_length: int):
    method remove_stable_workers_by_expiration (line 183) | def remove_stable_workers_by_expiration(self):
    method worker_api_generate_stream (line 193) | def worker_api_generate_stream(self, params):
    method worker_api_get_status (line 220) | def worker_api_get_status(self):
  function register_worker (line 243) | async def register_worker(request: Request):
  function refresh_all_workers (line 251) | async def refresh_all_workers():
  function list_models (line 256) | async def list_models():
  function get_worker_address (line 262) | async def get_worker_address(request: Request):
  function receive_heart_beat (line 269) | async def receive_heart_beat(request: Request):
  function worker_api_generate_stream (line 277) | async def worker_api_generate_stream(request: Request):
  function worker_api_get_status (line 284) | async def worker_api_get_status(request: Request):

FILE: llava/serve/gradio_web_server.py
  function get_conv_log_filename (line 32) | def get_conv_log_filename():
  function get_model_list (line 38) | def get_model_list():
  function load_demo (line 58) | def load_demo(url_params, request: gr.Request):
  function load_demo_refresh_model_list (line 71) | def load_demo_refresh_model_list(request: gr.Request):
  function vote_last_response (line 82) | def vote_last_response(state, vote_type, model_selector, request: gr.Req...
  function upvote_last_response (line 94) | def upvote_last_response(state, model_selector, request: gr.Request):
  function downvote_last_response (line 100) | def downvote_last_response(state, model_selector, request: gr.Request):
  function flag_last_response (line 106) | def flag_last_response(state, model_selector, request: gr.Request):
  function regenerate (line 112) | def regenerate(state, image_process_mode, request: gr.Request):
  function clear_history (line 122) | def clear_history(request: gr.Request):
  function add_text (line 128) | def add_text(state, text, image, image_process_mode, request: gr.Request):
  function http_bot (line 154) | def http_bot(state, model_selector, temperature, top_p, max_new_tokens, ...
  function build_demo (line 315) | def build_demo(embed_mode, cur_dir=None, concurrency_count=10):

FILE: llava/serve/model_worker.py
  function heart_beat_worker (line 37) | def heart_beat_worker(controller):
  class ModelWorker (line 44) | class ModelWorker:
    method __init__ (line 45) | def __init__(self, controller_addr, worker_addr,
    method register_to_controller (line 75) | def register_to_controller(self):
    method send_heart_beat (line 87) | def send_heart_beat(self):
    method get_queue_length (line 108) | def get_queue_length(self):
    method get_status (line 115) | def get_status(self):
    method generate_stream (line 123) | def generate_stream(self, params):
    method generate_stream_gate (line 195) | def generate_stream_gate(self, params):
  function release_model_semaphore (line 225) | def release_model_semaphore(fn=None):
  function generate_stream (line 232) | async def generate_stream(request: Request):
  function get_status (line 248) | async def get_status(request: Request):

FILE: llava/serve/sglang_worker.py
  function heart_beat_worker (line 38) | def heart_beat_worker(controller):
  function pipeline (line 45) | def pipeline(s, prompt, max_tokens):
  class ModelWorker (line 54) | class ModelWorker:
    method __init__ (line 55) | def __init__(self, controller_addr, worker_addr, sgl_endpoint,
    method register_to_controller (line 85) | def register_to_controller(self):
    method send_heart_beat (line 97) | def send_heart_beat(self):
    method get_queue_length (line 118) | def get_queue_length(self):
    method get_status (line 125) | def get_status(self):
    method generate_stream (line 132) | async def generate_stream(self, params):
    method generate_stream_gate (line 172) | async def generate_stream_gate(self, params):
  function release_model_semaphore (line 195) | def release_model_semaphore(fn=None):
  function generate_stream (line 202) | async def generate_stream(request: Request):
  function get_status (line 218) | async def get_status(request: Request):

FILE: llava/serve/test_message.py
  function main (line 9) | def main():

FILE: llava/train/llama_flash_attn_monkey_patch.py
  function forward (line 16) | def forward(
  function _prepare_decoder_attention_mask (line 98) | def _prepare_decoder_attention_mask(
  function replace_llama_attn_with_flash_attn (line 105) | def replace_llama_attn_with_flash_attn():

FILE: llava/train/llama_xformers_attn_monkey_patch.py
  function replace_llama_attn_with_xformers_attn (line 19) | def replace_llama_attn_with_xformers_attn():
  function xformers_forward (line 23) | def xformers_forward(

FILE: llava/train/llava_trainer.py
  function maybe_zero_3 (line 18) | def maybe_zero_3(param, ignore_status=False, name=None):
  function get_mm_adapter_state_maybe_zero_3 (line 32) | def get_mm_adapter_state_maybe_zero_3(named_params, keys_to_match):
  function split_to_even_chunks (line 38) | def split_to_even_chunks(indices, lengths, num_chunks):
  function get_modality_length_grouped_indices (line 60) | def get_modality_length_grouped_indices(lengths, batch_size, world_size,...
  function get_length_grouped_indices (line 88) | def get_length_grouped_indices(lengths, batch_size, world_size, generato...
  class LengthGroupedSampler (line 99) | class LengthGroupedSampler(Sampler):
    method __init__ (line 105) | def __init__(
    method __len__ (line 122) | def __len__(self):
    method __iter__ (line 125) | def __iter__(self):
  class LLaVATrainer (line 133) | class LLaVATrainer(Trainer):
    method _get_train_sampler (line 135) | def _get_train_sampler(self) -> Optional[torch.utils.data.Sampler]:
    method create_optimizer (line 150) | def create_optimizer(self):
    method _save_checkpoint (line 230) | def _save_checkpoint(self, model, trial, metrics=None):
    method _save (line 251) | def _save(self, output_dir: Optional[str] = None, state_dict=None):

FILE: llava/train/train.py
  function rank0_print (line 44) | def rank0_print(*args):
  class ModelArguments (line 54) | class ModelArguments:
  class DataArguments (line 70) | class DataArguments:
  class TrainingArguments (line 80) | class TrainingArguments(transformers.TrainingArguments):
  function maybe_zero_3 (line 115) | def maybe_zero_3(param, ignore_status=False, name=None):
  function get_peft_state_maybe_zero_3 (line 130) | def get_peft_state_maybe_zero_3(named_params, bias):
  function get_peft_state_non_lora_maybe_zero_3 (line 155) | def get_peft_state_non_lora_maybe_zero_3(named_params, require_grad_only...
  function get_mm_adapter_state_maybe_zero_3 (line 163) | def get_mm_adapter_state_maybe_zero_3(named_params, keys_to_match):
  function find_all_linear_names (line 169) | def find_all_linear_names(model):
  function safe_save_model_for_hf_trainer (line 185) | def safe_save_model_for_hf_trainer(trainer: transformers.Trainer,
  function smart_tokenizer_and_embedding_resize (line 224) | def smart_tokenizer_and_embedding_resize(
  function _tokenize_fn (line 249) | def _tokenize_fn(strings: Sequence[str],
  function _mask_targets (line 276) | def _mask_targets(target, tokenized_lens, speakers):
  function _add_speaker_and_signal (line 287) | def _add_speaker_and_signal(header, source, get_conversation=True):
  function preprocess_multimodal (line 308) | def preprocess_multimodal(
  function preprocess_llama_2 (line 332) | def preprocess_llama_2(
  function preprocess_v1 (line 414) | def preprocess_v1(
  function preprocess_mpt (line 500) | def preprocess_mpt(
  function preprocess_plain (line 588) | def preprocess_plain(
  function preprocess (line 610) | def preprocess(
  class LazySupervisedDataset (line 658) | class LazySupervisedDataset(Dataset):
    method __init__ (line 661) | def __init__(self, data_path: str,
    method __len__ (line 672) | def __len__(self):
    method lengths (line 676) | def lengths(self):
    method modality_lengths (line 684) | def modality_lengths(self):
    method __getitem__ (line 692) | def __getitem__(self, i) -> Dict[str, torch.Tensor]:
  class DataCollatorForSupervisedDataset (line 743) | class DataCollatorForSupervisedDataset(object):
    method __call__ (line 748) | def __call__(self, instances: Sequence[Dict]) -> Dict[str, torch.Tensor]:
  function make_supervised_data_module (line 776) | def make_supervised_data_module(tokenizer: transformers.PreTrainedTokeni...
  function train (line 788) | def train(attn_implementation=None):

FILE: llava/utils.py
  function build_logger (line 17) | def build_logger(logger_name, logger_filename):
  class StreamToLogger (line 60) | class StreamToLogger(object):
    method __init__ (line 64) | def __init__(self, logger, log_level=logging.INFO):
    method __getattr__ (line 70) | def __getattr__(self, attr):
    method write (line 73) | def write(self, buf):
    method flush (line 87) | def flush(self):
  function disable_torch_init (line 93) | def disable_torch_init():
  function violates_moderation (line 102) | def violates_moderation(text):
  function pretty_print_semaphore (line 123) | def pretty_print_semaphore(semaphore):

FILE: test_metrics.py
  function get_timestamp (line 19) | def get_timestamp():
  function setup_logger (line 23) | def setup_logger(logger_name, root, phase, level=logging.INFO, screen=Fa...
  function dict2str (line 53) | def dict2str(opt, indent=1):
  function main (line 74) | def main():

FILE: train_SDXL_stage_1.py
  function ordered_yaml (line 74) | def ordered_yaml():
  function image_grid (line 97) | def image_grid(imgs, rows, cols):
  function image_grid (line 109) | def image_grid(imgs, rows, cols):
  function get_concat_h (line 121) | def get_concat_h(im1, im2):
  function log_validation (line 127) | def log_validation(unet, args, accelerator, weight_dtype, step):
  function parse_args (line 200) | def parse_args():
  function convert_to_np (line 547) | def convert_to_np(image, resolution):
  function main (line 553) | def main():

FILE: train_SDXL_stage_2.py
  function ordered_yaml (line 74) | def ordered_yaml():
  function image_grid (line 97) | def image_grid(imgs, rows, cols):
  function image_grid (line 108) | def image_grid(imgs, rows, cols):
  function get_concat_h (line 119) | def get_concat_h(im1, im2):
  function log_validation (line 125) | def log_validation(unet, args, accelerator, weight_dtype, step):
  function parse_args (line 207) | def parse_args():
  function convert_to_np (line 559) | def convert_to_np(image, resolution):
  function main (line 565) | def main():

FILE: utils/color_fix.py
  function adain_color_fix (line 14) | def adain_color_fix(target: Image, source: Image):
  function wavelet_color_fix (line 29) | def wavelet_color_fix(target: Image, source: Image):
  function calc_mean_std (line 44) | def calc_mean_std(feat: Tensor, eps=1e-5):
  function adaptive_instance_normalization (line 59) | def adaptive_instance_normalization(content_feat:Tensor, style_feat:Tens...
  function wavelet_blur (line 73) | def wavelet_blur(image: Tensor, radius: int):
  function wavelet_decomposition (line 94) | def wavelet_decomposition(image: Tensor, levels=5):
  function wavelet_reconstruction (line 108) | def wavelet_reconstruction(content_feat:Tensor, style_feat:Tensor):

FILE: utils/image_process.py
  function check_image_size (line 7) | def check_image_size(x, padder_size=8):
  function image2tensor (line 24) | def image2tensor(img):
  function tensor2image (line 30) | def tensor2image(img):
  function create_hdr_effect (line 37) | def create_hdr_effect(original_image, hdr):

FILE: utils/system.py
  function torch_gc (line 6) | def torch_gc():
  function quantize_8bit (line 13) | def quantize_8bit(unet):