SYMBOL INDEX (695 symbols across 77 files)

FILE: data_processing/run_llava/main.py
  function main (line 18) | def main(args):

FILE: data_processing/run_llava/make_list.py
  function get_all_files (line 10) | def get_all_files(src_dir, extension="*.json"):

FILE: data_processing/run_llava/utils.py
  function image_parser (line 30) | def image_parser(args):
  function load_image (line 35) | def load_image(image_file):
  function load_images (line 44) | def load_images(image_files):
  class Predictor (line 52) | class Predictor:
    method __init__ (line 53) | def __init__(self, args) -> None:
    method set_args (line 70) | def set_args(self, args):
    method eval_model (line 73) | def eval_model(self):

FILE: dataset/dataset.py
  function zero_rank_print (line 16) | def zero_rank_print(s):
  function load_im_as_tensor (line 19) | def load_im_as_tensor(im_paths):
  class InvPaintingDataset (line 38) | class InvPaintingDataset(Dataset):
    method __init__ (line 39) | def __init__(
    method __len__ (line 82) | def __len__(self):
    method get_batch (line 85) | def get_batch(self,idx):
    method __getitem__ (line 254) | def __getitem__(self, idx):
  function collate_fn (line 310) | def collate_fn(data):

FILE: demo.py
  function parse_args (line 21) | def parse_args():
  function main (line 52) | def main(args):

FILE: models/ReferenceEncoder.py
  class ReferenceEncoder (line 11) | class ReferenceEncoder(nn.Module):
    method __init__ (line 12) | def __init__(self, model_path="openai/clip-vit-base-patch32"):
    method freeze (line 17) | def freeze(self):
    method forward (line 22) | def forward(self, pixel_values):

FILE: models/ReferenceNet.py
  class Identity (line 57) | class Identity(torch.nn.Module):
    method __init__ (line 77) | def __init__(self, scale=None, *args, **kwargs) -> None:
    method forward (line 80) | def forward(self, input, *args, **kwargs):
  class _LoRACompatibleLinear (line 85) | class _LoRACompatibleLinear(nn.Module):
    method __init__ (line 90) | def __init__(self, *args, lora_layer: Optional[LoRALinearLayer] = None...
    method set_lora_layer (line 94) | def set_lora_layer(self, lora_layer: Optional[LoRALinearLayer]):
    method _fuse_lora (line 97) | def _fuse_lora(self):
    method _unfuse_lora (line 100) | def _unfuse_lora(self):
    method forward (line 103) | def forward(self, hidden_states, scale=None, lora_scale: int = 1):
  class UNet2DConditionOutput (line 108) | class UNet2DConditionOutput(BaseOutput):
  class ReferenceNet (line 120) | class ReferenceNet(ModelMixin, ConfigMixin, UNet2DConditionLoadersMixin):
    method __init__ (line 211) | def __init__(
    method attn_processors (line 653) | def attn_processors(self) -> Dict[str, AttentionProcessor]:
    method set_attn_processor (line 676) | def set_attn_processor(
    method set_default_attn_processor (line 712) | def set_default_attn_processor(self):
    method set_attention_slice (line 727) | def set_attention_slice(self, slice_size):
    method _set_gradient_checkpointing (line 792) | def _set_gradient_checkpointing(self, module, value=False):
    method forward (line 796) | def forward(
    method load_referencenet (line 1091) | def load_referencenet(cls, pretrained_model_path):

FILE: models/ReferenceNet_attention.py
  function torch_dfs (line 12) | def torch_dfs(model: torch.nn.Module):
  class ReferenceNetAttention (line 19) | class ReferenceNetAttention():
    method __init__ (line 21) | def __init__(self,
    method register_reference_hooks (line 54) | def register_reference_hooks(
    method update (line 270) | def update(self, writer, dtype=torch.float32):
    method clear (line 294) | def clear(self):

FILE: models/ReferenceNet_attention_fp16.py
  function torch_dfs (line 12) | def torch_dfs(model: torch.nn.Module):
  class ReferenceNetAttention (line 19) | class ReferenceNetAttention():
    method __init__ (line 21) | def __init__(self,
    method register_reference_hooks (line 51) | def register_reference_hooks(
    method update (line 232) | def update(self, writer, dtype=torch.float16):
    method clear (line 254) | def clear(self):

FILE: models/attention.py
  class Transformer3DModelOutput (line 37) | class Transformer3DModelOutput(BaseOutput):
  class Transformer3DModel (line 48) | class Transformer3DModel(ModelMixin, ConfigMixin):
    method __init__ (line 50) | def __init__(
    method forward (line 112) | def forward(self, hidden_states, encoder_hidden_states=None, timestep=...
  class BasicTransformerBlock (line 164) | class BasicTransformerBlock(nn.Module):
    method __init__ (line 165) | def __init__(
    method set_use_memory_efficient_attention_xformers (line 248) | def set_use_memory_efficient_attention_xformers(self, use_memory_effic...
    method forward (line 276) | def forward(self, hidden_states, encoder_hidden_states=None, timestep=...

FILE: models/clip_adapter.py
  class NextImageFeaturePredictor (line 6) | class NextImageFeaturePredictor(nn.Module):
    method __init__ (line 7) | def __init__(self, input_feature_dim=768, output_feature_dim=768, hidd...
    method forward (line 18) | def forward(self, current_img_feature, final_img_feature):

FILE: models/hack_cur_image_guider.py
  class Hack_CurImageGuider (line 8) | class Hack_CurImageGuider(nn.Module):
    method __init__ (line 9) | def __init__(self, in_channels=3, noise_latent_channels=320):
    method _initialize_weights (line 54) | def _initialize_weights(self):
    method forward (line 69) | def forward(self, x):
    method from_pretrained (line 76) | def from_pretrained(cls,pretrained_model_path, in_channels=3):

FILE: models/hack_unet2d.py
  class Hack_UNet2DConditionModel (line 11) | class Hack_UNet2DConditionModel(UNet2DConditionModel):
    method forward (line 12) | def forward(

FILE: models/image_processor.py
  class LPIPS_Image_Processor (line 8) | class LPIPS_Image_Processor():
    method __init__ (line 9) | def __init__(self):
    method process (line 12) | def process(self, img):
  class Seg_Image_Processor (line 22) | class Seg_Image_Processor():
    method __init__ (line 23) | def __init__(self):
    method process (line 28) | def process(self, img):

FILE: models/orig_attention.py
  class Transformer2DModelOutput (line 36) | class Transformer2DModelOutput(BaseOutput):
  class Transformer2DModel (line 54) | class Transformer2DModel(ModelMixin, ConfigMixin):
    method __init__ (line 93) | def __init__(
    method forward (line 184) | def forward(self, hidden_states, encoder_hidden_states=None, timestep=...
  class AttentionBlock (line 253) | class AttentionBlock(nn.Module):
    method __init__ (line 271) | def __init__(
    method set_use_memory_efficient_attention_xformers (line 296) | def set_use_memory_efficient_attention_xformers(self, use_memory_effic...
    method reshape_heads_to_batch_dim (line 320) | def reshape_heads_to_batch_dim(self, tensor):
    method reshape_batch_dim_to_heads (line 327) | def reshape_batch_dim_to_heads(self, tensor):
    method forward (line 334) | def forward(self, hidden_states):
  class BasicTransformerBlock (line 388) | class BasicTransformerBlock(nn.Module):
    method __init__ (line 405) | def __init__(
    method set_use_memory_efficient_attention_xformers (line 458) | def set_use_memory_efficient_attention_xformers(self, use_memory_effic...
    method forward (line 485) | def forward(self, hidden_states, encoder_hidden_states=None, timestep=...
  class CrossAttention (line 516) | class CrossAttention(nn.Module):
    method __init__ (line 531) | def __init__(
    method reshape_heads_to_batch_dim (line 578) | def reshape_heads_to_batch_dim(self, tensor):
    method reshape_batch_dim_to_heads (line 585) | def reshape_batch_dim_to_heads(self, tensor):
    method set_attention_slice (line 592) | def set_attention_slice(self, slice_size):
    method forward (line 598) | def forward(self, hidden_states, encoder_hidden_states=None, attention...
    method _attention (line 655) | def _attention(self, query, key, value, attention_mask=None):
    method _sliced_attention (line 686) | def _sliced_attention(self, query, key, value, sequence_length, dim, a...
    method _memory_efficient_attention_xformers (line 729) | def _memory_efficient_attention_xformers(self, query, key, value, atte...
  class FeedForward (line 739) | class FeedForward(nn.Module):
    method __init__ (line 751) | def __init__(
    method forward (line 778) | def forward(self, hidden_states):
  class GELU (line 784) | class GELU(nn.Module):
    method __init__ (line 789) | def __init__(self, dim_in: int, dim_out: int):
    method gelu (line 793) | def gelu(self, gate):
    method forward (line 799) | def forward(self, hidden_states):
  class GEGLU (line 806) | class GEGLU(nn.Module):
    method __init__ (line 815) | def __init__(self, dim_in: int, dim_out: int):
    method gelu (line 819) | def gelu(self, gate):
    method forward (line 825) | def forward(self, hidden_states):
  class ApproximateGELU (line 830) | class ApproximateGELU(nn.Module):
    method __init__ (line 837) | def __init__(self, dim_in: int, dim_out: int):
    method forward (line 841) | def forward(self, x):
  class AdaLayerNorm (line 846) | class AdaLayerNorm(nn.Module):
    method __init__ (line 851) | def __init__(self, embedding_dim, num_embeddings):
    method forward (line 858) | def forward(self, x, timestep):
  class DualTransformer2DModel (line 865) | class DualTransformer2DModel(nn.Module):
    method __init__ (line 892) | def __init__(
    method forward (line 941) | def forward(

FILE: models/positional_encoder.py
  class Embedder (line 17) | class Embedder:
    method __init__ (line 18) | def __init__(self, **kwargs):
    method create_embedding_fn (line 22) | def create_embedding_fn(self):
    method embed (line 46) | def embed(self, inputs):
  function get_embedder (line 50) | def get_embedder(multires, i=0):
  class PositionalEncoder (line 72) | class PositionalEncoder(nn.Module):
    method __init__ (line 73) | def __init__(self,in_features=42 ):
    method forward (line 86) | def forward(self, x):

FILE: models/resnet.py
  class InflatedConv3d (line 30) | class InflatedConv3d(nn.Conv2d):
    method forward (line 31) | def forward(self, x):
  class Upsample3D (line 41) | class Upsample3D(nn.Module):
    method __init__ (line 42) | def __init__(self, channels, use_conv=False, use_conv_transpose=False,...
    method forward (line 56) | def forward(self, hidden_states, output_size=None):
  class Downsample3D (line 87) | class Downsample3D(nn.Module):
    method __init__ (line 88) | def __init__(self, channels, use_conv=False, out_channels=None, paddin...
    method forward (line 102) | def forward(self, hidden_states):
  class ResnetBlock3D (line 113) | class ResnetBlock3D(nn.Module):
    method __init__ (line 114) | def __init__(
    method forward (line 177) | def forward(self, input_tensor, temb):
  class Mish (line 210) | class Mish(torch.nn.Module):
    method forward (line 211) | def forward(self, hidden_states):

FILE: models/unet.py
  class UNet3DConditionOutput (line 32) | class UNet3DConditionOutput(BaseOutput):
  class UNet3DConditionModel (line 36) | class UNet3DConditionModel(ModelMixin, ConfigMixin):
    method __init__ (line 40) | def __init__(
    method set_attention_slice (line 241) | def set_attention_slice(self, slice_size):
    method _set_gradient_checkpointing (line 306) | def _set_gradient_checkpointing(self, module, value=False):
    method forward (line 310) | def forward(
    method from_pretrained_2d (line 449) | def from_pretrained_2d(cls, pretrained_model_path, subfolder=None, une...

FILE: models/unet_3d_blocks.py
  function get_down_block (line 9) | def get_down_block(
  function get_up_block (line 85) | def get_up_block(
  class UNetMidBlock3DCrossAttn (line 160) | class UNetMidBlock3DCrossAttn(nn.Module):
    method __init__ (line 161) | def __init__(
    method forward (line 255) | def forward(self, hidden_states, temb=None, encoder_hidden_states=None...
  class CrossAttnDownBlock3D (line 265) | class CrossAttnDownBlock3D(nn.Module):
    method __init__ (line 266) | def __init__(
    method forward (line 363) | def forward(self, hidden_states, temb=None, encoder_hidden_states=None...
  class DownBlock3D (line 404) | class DownBlock3D(nn.Module):
    method __init__ (line 405) | def __init__(
    method forward (line 469) | def forward(self, hidden_states, temb=None, encoder_hidden_states=None):
  class CrossAttnUpBlock3D (line 500) | class CrossAttnUpBlock3D(nn.Module):
    method __init__ (line 501) | def __init__(
    method forward (line 594) | def forward(
  class UpBlock3D (line 643) | class UpBlock3D(nn.Module):
    method __init__ (line 644) | def __init__(
    method forward (line 704) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, u...

FILE: pipelines/context.py
  function ordered_halving (line 12) | def ordered_halving(val):
  function uniform (line 20) | def uniform(
  function get_context_scheduler (line 45) | def get_context_scheduler(name: str) -> Callable:
  function get_total_steps (line 52) | def get_total_steps(

FILE: pipelines/pipeline_stage_1.py
  class InvPaintingPipelineOutput (line 50) | class InvPaintingPipelineOutput(BaseOutput):
  function retrieve_latents (line 56) | def retrieve_latents(
  class InvPaintingPipeline (line 71) | class InvPaintingPipeline(DiffusionPipeline):
    method __init__ (line 74) | def __init__(
    method _execution_device (line 159) | def _execution_device(self):
    method decode_latents (line 172) | def decode_latents(self, latents, rank, decoder_consistency=None):
    method prepare_extra_step_kwargs (line 183) | def prepare_extra_step_kwargs(self, generator, eta):
    method _encode_vae_image (line 202) | def _encode_vae_image(self, image: torch.Tensor, generator: torch.Gene...
    method prepare_latents (line 217) | def prepare_latents(
    method images2latents (line 278) | def images2latents(self, images, dtype):
    method get_timesteps (line 294) | def get_timesteps(self, num_inference_steps, strength, device):
    method __call__ (line 306) | def __call__(

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

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

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

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

FILE: training_scripts/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: training_scripts/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 122) | def process_anyres_image(image, processor, grid_pinpoints):
  function load_image_from_base64 (line 150) | def load_image_from_base64(image):
  function expand2square (line 154) | def expand2square(pil_img, background_color):
  function process_images (line 168) | def process_images(images, image_processor, model_cfg):
  function tokenizer_image_token (line 188) | def tokenizer_image_token(prompt, tokenizer, image_token_index=IMAGE_TOK...
  function get_model_name_from_path (line 210) | def get_model_name_from_path(model_path):
  class KeywordsStoppingCriteria (line 218) | class KeywordsStoppingCriteria(StoppingCriteria):
    method __init__ (line 219) | def __init__(self, keywords, tokenizer, input_ids):
    method call_for_batch (line 233) | def call_for_batch(self, output_ids: torch.LongTensor, scores: torch.F...
    method __call__ (line 246) | def __call__(self, output_ids: torch.LongTensor, scores: torch.FloatTe...

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

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

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

FILE: training_scripts/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 105) | def generate(
    method prepare_inputs_for_generation (line 145) | def prepare_inputs_for_generation(self, input_ids, past_key_values=None,

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

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

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

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

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

FILE: training_scripts/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: training_scripts/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: training_scripts/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: training_scripts/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 132) | def get_peft_state_maybe_zero_3(named_params, bias):
  function get_peft_state_non_lora_maybe_zero_3 (line 157) | def get_peft_state_non_lora_maybe_zero_3(named_params, require_grad_only...
  function get_mm_adapter_state_maybe_zero_3 (line 165) | def get_mm_adapter_state_maybe_zero_3(named_params, keys_to_match):
  function find_all_linear_names (line 171) | def find_all_linear_names(model):
  function safe_save_model_for_hf_trainer (line 187) | def safe_save_model_for_hf_trainer(trainer: transformers.Trainer,
  function smart_tokenizer_and_embedding_resize (line 226) | def smart_tokenizer_and_embedding_resize(
  function _tokenize_fn (line 251) | def _tokenize_fn(strings: Sequence[str],
  function _mask_targets (line 278) | def _mask_targets(target, tokenized_lens, speakers):
  function _add_speaker_and_signal (line 289) | def _add_speaker_and_signal(header, source, get_conversation=True):
  function preprocess_multimodal (line 310) | def preprocess_multimodal(
  function preprocess_llama_2 (line 334) | def preprocess_llama_2(
  function preprocess_v1 (line 416) | def preprocess_v1(
  function preprocess_mpt (line 502) | def preprocess_mpt(
  function preprocess_plain (line 590) | def preprocess_plain(
  function preprocess (line 612) | def preprocess(
  class LazySupervisedDataset (line 660) | class LazySupervisedDataset(Dataset):
    method __init__ (line 663) | def __init__(self, data_path: str,
    method __len__ (line 674) | def __len__(self):
    method lengths (line 678) | def lengths(self):
    method modality_lengths (line 686) | def modality_lengths(self):
    method __getitem__ (line 694) | def __getitem__(self, i) -> Dict[str, torch.Tensor]:
  class DataCollatorForSupervisedDataset (line 754) | class DataCollatorForSupervisedDataset(object):
    method __call__ (line 759) | def __call__(self, instances: Sequence[Dict]) -> Dict[str, torch.Tensor]:
  function make_supervised_data_module (line 787) | def make_supervised_data_module(tokenizer: transformers.PreTrainedTokeni...
  function train (line 799) | def train(attn_implementation=None):

FILE: training_scripts/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: training_scripts/scripts/merge_lora_weights.py
  function merge_lora (line 6) | def merge_lora(args):

FILE: training_scripts/train_mask_generator.py
  function init_dist (line 64) | def init_dist(launcher="slurm", backend='nccl', port=28888, **kwargs):
  function get_parameters_without_gradients (line 97) | def get_parameters_without_gradients(model):
  function main (line 115) | def main(

FILE: training_scripts/train_renderer.py
  function init_dist (line 55) | def init_dist(launcher="slurm", backend='nccl', port=28888, **kwargs):
  function get_parameters_without_gradients (line 87) | def get_parameters_without_gradients(model):
  function main (line 105) | def main(

FILE: unet_2d/attention.py
  class GatedSelfAttentionDense (line 28) | class GatedSelfAttentionDense(nn.Module):
    method __init__ (line 29) | def __init__(self, query_dim, context_dim, n_heads, d_head):
    method forward (line 46) | def forward(self, x, objs):
  class BasicTransformerBlock (line 60) | class BasicTransformerBlock(nn.Module):
    method __init__ (line 81) | def __init__(
    method set_chunk_feed_forward (line 164) | def set_chunk_feed_forward(self, chunk_size: Optional[int], dim: int):
    method forward (line 169) | def forward(
  class FeedForward (line 258) | class FeedForward(nn.Module):
    method __init__ (line 271) | def __init__(
    method forward (line 304) | def forward(self, hidden_states, scale: float = 1.0):
  class GELU (line 313) | class GELU(nn.Module):
    method __init__ (line 318) | def __init__(self, dim_in: int, dim_out: int, approximate: str = "none"):
    method gelu (line 323) | def gelu(self, gate):
    method forward (line 329) | def forward(self, hidden_states):
  class GEGLU (line 335) | class GEGLU(nn.Module):
    method __init__ (line 344) | def __init__(self, dim_in: int, dim_out: int):
    method gelu (line 348) | def gelu(self, gate):
    method forward (line 354) | def forward(self, hidden_states, scale: float = 1.0):
  class ApproximateGELU (line 359) | class ApproximateGELU(nn.Module):
    method __init__ (line 366) | def __init__(self, dim_in: int, dim_out: int):
    method forward (line 370) | def forward(self, x):
  class AdaLayerNorm (line 375) | class AdaLayerNorm(nn.Module):
    method __init__ (line 380) | def __init__(self, embedding_dim, num_embeddings):
    method forward (line 387) | def forward(self, x, timestep):
  class AdaLayerNormZero (line 394) | class AdaLayerNormZero(nn.Module):
    method __init__ (line 399) | def __init__(self, embedding_dim, num_embeddings):
    method forward (line 408) | def forward(self, x, timestep, class_labels, hidden_dtype=None):
  class AdaGroupNorm (line 415) | class AdaGroupNorm(nn.Module):
    method __init__ (line 420) | def __init__(
    method forward (line 434) | def forward(self, x, emb):

FILE: unet_2d/resnet.py
  class Upsample1D (line 29) | class Upsample1D(nn.Module):
    method __init__ (line 43) | def __init__(self, channels, use_conv=False, use_conv_transpose=False,...
    method forward (line 57) | def forward(self, inputs):
  class Downsample1D (line 70) | class Downsample1D(nn.Module):
    method __init__ (line 84) | def __init__(self, channels, use_conv=False, out_channels=None, paddin...
    method forward (line 99) | def forward(self, inputs):
  class Upsample2D (line 104) | class Upsample2D(nn.Module):
    method __init__ (line 118) | def __init__(self, channels, use_conv=False, use_conv_transpose=False,...
    method forward (line 138) | def forward(self, hidden_states, output_size=None, scale: float = 1.0):
  class Downsample2D (line 182) | class Downsample2D(nn.Module):
    method __init__ (line 196) | def __init__(self, channels, use_conv=False, out_channels=None, paddin...
    method forward (line 220) | def forward(self, hidden_states, scale: float = 1.0):
  class FirUpsample2D (line 235) | class FirUpsample2D(nn.Module):
    method __init__ (line 249) | def __init__(self, channels=None, out_channels=None, use_conv=False, f...
    method _upsample_2d (line 258) | def _upsample_2d(self, hidden_states, weight=None, kernel=None, factor...
    method forward (line 338) | def forward(self, hidden_states):
  class FirDownsample2D (line 348) | class FirDownsample2D(nn.Module):
    method __init__ (line 362) | def __init__(self, channels=None, out_channels=None, use_conv=False, f...
    method _downsample_2d (line 371) | def _downsample_2d(self, hidden_states, weight=None, kernel=None, fact...
    method forward (line 425) | def forward(self, hidden_states):
  class KDownsample2D (line 436) | class KDownsample2D(nn.Module):
    method __init__ (line 437) | def __init__(self, pad_mode="reflect"):
    method forward (line 444) | def forward(self, inputs):
  class KUpsample2D (line 453) | class KUpsample2D(nn.Module):
    method __init__ (line 454) | def __init__(self, pad_mode="reflect"):
    method forward (line 461) | def forward(self, inputs):
  class ResnetBlock2D (line 470) | class ResnetBlock2D(nn.Module):
    method __init__ (line 501) | def __init__(
    method forward (line 600) | def forward(self, input_tensor, scale: float = 1.0):
  function rearrange_dims (line 663) | def rearrange_dims(tensor):
  class Conv1dBlock (line 674) | class Conv1dBlock(nn.Module):
    method __init__ (line 679) | def __init__(self, inp_channels, out_channels, kernel_size, n_groups=8):
    method forward (line 686) | def forward(self, inputs):
  class ResidualTemporalBlock1D (line 696) | class ResidualTemporalBlock1D(nn.Module):
    method __init__ (line 697) | def __init__(self, inp_channels, out_channels, embed_dim, kernel_size=5):
    method forward (line 709) | def forward(self, inputs, t):
  function upsample_2d (line 725) | def upsample_2d(hidden_states, kernel=None, factor=2, gain=1):
  function downsample_2d (line 762) | def downsample_2d(hidden_states, kernel=None, factor=2, gain=1):
  function upfirdn2d_native (line 797) | def upfirdn2d_native(tensor, kernel, up=1, down=1, pad=(0, 0)):
  class TemporalConvLayer (line 841) | class TemporalConvLayer(nn.Module):
    method __init__ (line 847) | def __init__(self, in_dim, out_dim=None, dropout=0.0):
    method forward (line 880) | def forward(self, hidden_states, num_frames=1):

FILE: unet_2d/unet_2d_blocks.py
  function get_down_block (line 33) | def get_down_block(
  function get_up_block (line 243) | def get_up_block(
  class AutoencoderTinyBlock (line 456) | class AutoencoderTinyBlock(nn.Module):
    method __init__ (line 457) | def __init__(self, in_channels: int, out_channels: int, act_fn: str):
    method forward (line 474) | def forward(self, x):
  class UNetMidBlock2D (line 478) | class UNetMidBlock2D(nn.Module):
    method __init__ (line 479) | def __init__(
    method forward (line 559) | def forward(self, hidden_states, temb=None):
  class UNetMidBlock2DCrossAttn (line 569) | class UNetMidBlock2DCrossAttn(nn.Module):
    method __init__ (line 570) | def __init__(
    method forward (line 659) | def forward(
  class UNetMidBlock2DSimpleCrossAttn (line 710) | class UNetMidBlock2DSimpleCrossAttn(nn.Module):
    method __init__ (line 711) | def __init__(
    method forward (line 795) | def forward(
  class AttnDownBlock2D (line 834) | class AttnDownBlock2D(nn.Module):
    method __init__ (line 835) | def __init__(
    method forward (line 926) | def forward(self, hidden_states, temb=None, upsample_size=None, cross_...
  class CrossAttnDownBlock2D (line 951) | class CrossAttnDownBlock2D(nn.Module):
    method __init__ (line 952) | def __init__(
    method forward (line 1041) | def forward(
  class DownBlock2D (line 1110) | class DownBlock2D(nn.Module):
    method __init__ (line 1111) | def __init__(
    method forward (line 1162) | def forward(self, hidden_states, temb=None, scale: float = 1.0):
  class DownEncoderBlock2D (line 1196) | class DownEncoderBlock2D(nn.Module):
    method __init__ (line 1197) | def __init__(
    method forward (line 1245) | def forward(self, hidden_states, scale: float = 1.0):
  class AttnDownEncoderBlock2D (line 1256) | class AttnDownEncoderBlock2D(nn.Module):
    method __init__ (line 1257) | def __init__(
    method forward (line 1328) | def forward(self, hidden_states, scale: float = 1.0):
  class AttnSkipDownBlock2D (line 1341) | class AttnSkipDownBlock2D(nn.Module):
    method __init__ (line 1342) | def __init__(
    method forward (line 1422) | def forward(self, hidden_states, temb=None, skip_sample=None, scale: f...
  class SkipDownBlock2D (line 1443) | class SkipDownBlock2D(nn.Module):
    method __init__ (line 1444) | def __init__(
    method forward (line 1503) | def forward(self, hidden_states, temb=None, skip_sample=None, scale: f...
  class ResnetDownsampleBlock2D (line 1522) | class ResnetDownsampleBlock2D(nn.Module):
    method __init__ (line 1523) | def __init__(
    method forward (line 1586) | def forward(self, hidden_states, temb=None, scale: float = 1.0):
  class SimpleCrossAttnDownBlock2D (line 1620) | class SimpleCrossAttnDownBlock2D(nn.Module):
    method __init__ (line 1621) | def __init__(
    method forward (line 1715) | def forward(
  class KDownBlock2D (line 1780) | class KDownBlock2D(nn.Module):
    method __init__ (line 1781) | def __init__(
    method forward (line 1826) | def forward(self, hidden_states, temb=None, scale: float = 1.0):
  class KCrossAttnDownBlock2D (line 1858) | class KCrossAttnDownBlock2D(nn.Module):
    method __init__ (line 1859) | def __init__(
    method forward (line 1923) | def forward(
  class AttnUpBlock2D (line 1985) | class AttnUpBlock2D(nn.Module):
    method __init__ (line 1986) | def __init__(
    method forward (line 2074) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, u...
  class CrossAttnUpBlock2D (line 2095) | class CrossAttnUpBlock2D(nn.Module):
    method __init__ (line 2096) | def __init__(
    method forward (line 2181) | def forward(
  class UpBlock2D (line 2243) | class UpBlock2D(nn.Module):
    method __init__ (line 2244) | def __init__(
    method forward (line 2291) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, u...
  class UpDecoderBlock2D (line 2324) | class UpDecoderBlock2D(nn.Module):
    method __init__ (line 2325) | def __init__(
    method forward (line 2368) | def forward(self, hidden_states, temb=None, scale: float = 1.0):
  class AttnUpDecoderBlock2D (line 2379) | class AttnUpDecoderBlock2D(nn.Module):
    method __init__ (line 2380) | def __init__(
    method forward (line 2447) | def forward(self, hidden_states, temb=None, scale: float = 1.0):
  class AttnSkipUpBlock2D (line 2460) | class AttnSkipUpBlock2D(nn.Module):
    method __init__ (line 2461) | def __init__(
    method forward (line 2551) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, s...
  class SkipUpBlock2D (line 2580) | class SkipUpBlock2D(nn.Module):
    method __init__ (line 2581) | def __init__(
    method forward (line 2649) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, s...
  class ResnetUpsampleBlock2D (line 2675) | class ResnetUpsampleBlock2D(nn.Module):
    method __init__ (line 2676) | def __init__(
    method forward (line 2742) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, u...
  class SimpleCrossAttnUpBlock2D (line 2775) | class SimpleCrossAttnUpBlock2D(nn.Module):
    method __init__ (line 2776) | def __init__(
    method forward (line 2872) | def forward(
  class KUpBlock2D (line 2939) | class KUpBlock2D(nn.Module):
    method __init__ (line 2940) | def __init__(
    method forward (line 2987) | def forward(self, hidden_states, res_hidden_states_tuple, temb=None, u...
  class KCrossAttnUpBlock2D (line 3019) | class KCrossAttnUpBlock2D(nn.Module):
    method __init__ (line 3020) | def __init__(
    method forward (line 3103) | def forward(
  class KAttentionBlock (line 3165) | class KAttentionBlock(nn.Module):
    method __init__ (line 3182) | def __init__(
    method _to_3d (line 3225) | def _to_3d(self, hidden_states, height, weight):
    method _to_4d (line 3228) | def _to_4d(self, hidden_states, height, weight):
    method forward (line 3231) | def forward(

FILE: unet_2d/unet_2d_condition.py
  class UNet2DConditionOutput (line 57) | class UNet2DConditionOutput(BaseOutput):
  class UNet2DConditionModel (line 69) | class UNet2DConditionModel(ModelMixin, ConfigMixin, UNet2DConditionLoade...
    method __init__ (line 161) | def __init__(
    method attn_processors (line 593) | def attn_processors(self) -> Dict[str, AttentionProcessor]:
    method set_attn_processor (line 616) | def set_attn_processor(
    method set_default_attn_processor (line 652) | def set_default_attn_processor(self):
    method set_attention_slice (line 667) | def set_attention_slice(self, slice_size):
    method _set_gradient_checkpointing (line 732) | def _set_gradient_checkpointing(self, module, value=False):
    method forward (line 736) | def forward(

FILE: utils/dist_tools.py
  function distributed_init (line 18) | def distributed_init(args):
  function get_rank (line 62) | def get_rank():
  function is_master (line 72) | def is_master():
  function synchronize (line 76) | def synchronize():
  function suppress_output (line 81) | def suppress_output(is_master):

FILE: utils/inference_helpers.py
  function prepare_results_dir (line 32) | def prepare_results_dir(config, ckpt_path, root_dst_dir):
  function get_dataset_info (line 44) | def get_dataset_info(test_dir):
  function load_pipeline (line 57) | def load_pipeline(config, pretrained_model_path, pretrained_clip_path, f...
  class PE_wrapper (line 127) | class PE_wrapper():
    method __init__ (line 128) | def __init__(self, config,full_state_dict, device, dtype):
    method norm (line 153) | def norm(self, pos):
    method embed (line 160) | def embed(self, cur_pos):
  function pad_to_16 (line 186) | def pad_to_16(source_image):
  class TP_wrapper (line 228) | class TP_wrapper(nn.Module):
    method __init__ (line 229) | def __init__(self, config, full_state_dict, device, dtype):
    method forward (line 239) | def forward(self, cur_img_path, ref_img_path, cache_path=None):
    method get_negative_embeddings (line 242) | def get_negative_embeddings(self):
    method get_negative_embeddings_exclude (line 245) | def get_negative_embeddings_exclude(self, next_text):
    method encode_text_prompt (line 248) | def encode_text_prompt(self, next_prompt):
  class TP_text_wrapper (line 251) | class TP_text_wrapper(nn.Module):
    method __init__ (line 252) | def __init__(self, config,full_state_dict, device, dtype):
    method forward (line 306) | def forward(self, cur_img_path, ref_img_path, cache_path=None):
    method encode_text_prompt (line 337) | def encode_text_prompt(self, next_prompt):
    method get_negative_embeddings (line 357) | def get_negative_embeddings(self):
  class RP_wrapper (line 380) | class RP_wrapper(nn.Module):
    method __init__ (line 381) | def __init__(self, config, full_state_dict, device, dtype):
    method read_RP_mask (line 459) | def read_RP_mask(self, mask_path):
    method forward (line 467) | def forward(self, cur_img_path, ref_img_path, next_prompt=None, next_R...

FILE: utils/llava_utils.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):
  class Predictor (line 50) | class Predictor:
    method __init__ (line 51) | def __init__(self, args) -> None:
    method set_args (line 65) | def set_args(self, args):
    method eval_model (line 68) | def eval_model(self):

FILE: utils/text_wrapper.py
  function import_model_class_from_model_name_or_path (line 6) | def import_model_class_from_model_name_or_path(pretrained_model_name_or_...
  function tokenize_prompt (line 30) | def tokenize_prompt(tokenizer, prompt, tokenizer_max_length=None):
  function encode_prompt (line 47) | def encode_prompt(text_encoder, input_ids, attention_mask, text_encoder_...

FILE: utils/util.py
  function zero_rank_print (line 22) | def zero_rank_print(s):
  function save_videos_grid (line 25) | def save_videos_grid(videos: torch.Tensor, path: str, rescale=False, n_r...
  function save_images_grid (line 39) | def save_images_grid(images: torch.Tensor, path: str):
  function init_prompt (line 49) | def init_prompt(prompt, pipeline):
  function next_step (line 68) | def next_step(model_output: Union[torch.FloatTensor, np.ndarray], timest...
  function get_noise_pred_single (line 81) | def get_noise_pred_single(latents, t, context, unet):
  function ddim_loop (line 87) | def ddim_loop(pipeline, ddim_scheduler, latent, num_inv_steps, prompt):
  function ddim_inversion (line 101) | def ddim_inversion(pipeline, ddim_scheduler, video_latent, num_inv_steps...
  function video2images (line 106) | def video2images(path, step=4, length=16, start=0):
  function images2video (line 115) | def images2video(video, path, fps=8):
  function get_tensor_interpolation_method (line 122) | def get_tensor_interpolation_method():
  function set_tensor_interpolation_method (line 125) | def set_tensor_interpolation_method(is_slerp):
  function linear (line 129) | def linear(v1, v2, t):
  function slerp (line 132) | def slerp(