SYMBOL INDEX (138 symbols across 17 files)

FILE: eval_mm/evaluate_caption.py
  class CaptionDataset (line 27) | class CaptionDataset(torch.utils.data.Dataset):
    method __init__ (line 29) | def __init__(self, train, test, prompt, few_shot=0):
    method __len__ (line 37) | def __len__(self):
    method __getitem__ (line 40) | def __getitem__(self, idx):
  function collate_fn (line 57) | def collate_fn(inputs, tokenizer):
  class InferenceSampler (line 68) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 70) | def __init__(self, size):
    method _get_local_indices (line 79) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 88) | def __iter__(self):
    method __len__ (line 91) | def __len__(self):

FILE: eval_mm/evaluate_grounding.py
  function box_iou (line 25) | def box_iou(boxes1, boxes2):
  function collate_fn (line 41) | def collate_fn(batches, tokenizer):
  class RefCOCODataset (line 52) | class RefCOCODataset(torch.utils.data.Dataset):
    method __init__ (line 54) | def __init__(self, test, tokenizer, prompt):
    method __len__ (line 59) | def __len__(self):
    method __getitem__ (line 62) | def __getitem__(self, idx):
  class InferenceSampler (line 77) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 79) | def __init__(self, size):
    method _get_local_indices (line 88) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 97) | def __iter__(self):
    method __len__ (line 100) | def __len__(self):

FILE: eval_mm/evaluate_multiple_choice.py
  function collate_fn (line 20) | def collate_fn(batches, pad_token_id):
  class MultipleChoiceDataste (line 40) | class MultipleChoiceDataste(torch.utils.data.Dataset):
    method __init__ (line 42) | def __init__(self, test, prompt, tokenizer):
    method __len__ (line 47) | def __len__(self):
    method __getitem__ (line 50) | def __getitem__(self, idx):
  class InferenceSampler (line 78) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 80) | def __init__(self, size):
    method _get_local_indices (line 89) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 98) | def __iter__(self):
    method __len__ (line 101) | def __len__(self):

FILE: eval_mm/evaluate_vqa.py
  function relaxed_correctness (line 113) | def relaxed_correctness(target: str,
  function evaluate_relaxed_accuracy (line 155) | def evaluate_relaxed_accuracy(entries):
  function evaluate_exact_match_accuracy (line 168) | def evaluate_exact_match_accuracy(entries):
  function collate_fn (line 182) | def collate_fn(batches, tokenizer):
  class VQADataset (line 193) | class VQADataset(torch.utils.data.Dataset):
    method __init__ (line 195) | def __init__(self, train, test, prompt, few_shot):
    method __len__ (line 203) | def __len__(self):
    method __getitem__ (line 206) | def __getitem__(self, idx):
  class InferenceSampler (line 227) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 229) | def __init__(self, size):
    method _get_local_indices (line 238) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 247) | def __iter__(self):
    method __len__ (line 250) | def __len__(self):

FILE: eval_mm/infographicsvqa_eval.py
  function save_json (line 14) | def save_json(file_path, data):
  function levenshtein_distance (line 20) | def levenshtein_distance(s1, s2):
  function validate_data (line 36) | def validate_data(gtFilePath, submFilePath):
  function evaluate_method (line 87) | def evaluate_method(gtFilePath, submFilePath, evaluationParams):
  function display_results (line 200) | def display_results(results, show_answer_types):

FILE: eval_mm/mmbench/evaluate_multiple_choice_mmbench.py
  function collate_fn (line 22) | def collate_fn(batches, pad_token_id):
  class MultipleChoiceDataste (line 43) | class MultipleChoiceDataste(torch.utils.data.Dataset):
    method __init__ (line 45) | def __init__(self, test, prompt, tokenizer):
    method __len__ (line 50) | def __len__(self):
    method __getitem__ (line 53) | def __getitem__(self, idx):
  class InferenceSampler (line 83) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 85) | def __init__(self, size):
    method _get_local_indices (line 94) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 103) | def __iter__(self):
    method __len__ (line 106) | def __len__(self):

FILE: eval_mm/mmbench/mmbench_converter_dev.py
  function decode_base64_to_image (line 15) | def decode_base64_to_image(base64_string):

FILE: eval_mm/mmbench/mmbench_converter_test.py
  function decode_base64_to_image (line 16) | def decode_base64_to_image(base64_string):

FILE: eval_mm/mmbench/mmbench_evaluation_tricky.py
  function most_common_elements (line 18) | def most_common_elements(lst):

FILE: eval_mm/mmbench/mmbench_predict_to_submission.py
  function most_common_elements (line 17) | def most_common_elements(lst):

FILE: eval_mm/seed_bench/eval.py
  function collate_fn (line 13) | def collate_fn(batches, pad_token_id):
  class MultipleChoiceDataste (line 34) | class MultipleChoiceDataste(torch.utils.data.Dataset):
    method __init__ (line 36) | def __init__(self, test, tokenizer):
    method __len__ (line 43) | def __len__(self):
    method __getitem__ (line 46) | def __getitem__(self, idx):
  class InferenceSampler (line 65) | class InferenceSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 67) | def __init__(self, size):
    method _get_local_indices (line 76) | def _get_local_indices(total_size, world_size, rank):
    method __iter__ (line 85) | def __iter__(self):
    method __len__ (line 88) | def __len__(self):

FILE: eval_mm/seed_bench/trans.py
  function is_integer_string (line 22) | def is_integer_string(s):
  function filter_questions (line 29) | def filter_questions(data, task='all'):
  function get_index (line 41) | def get_index(num_frames, num_segments):

FILE: eval_mm/vqa.py
  class VQA (line 31) | class VQA:
    method __init__ (line 33) | def __init__(self, annotation_file=None, question_file=None):
    method createIndex (line 55) | def createIndex(self):
    method info (line 73) | def info(self):
    method getQuesIds (line 81) | def getQuesIds(self, imgIds=[], quesTypes=[], ansTypes=[]):
    method getImgIds (line 114) | def getImgIds(self, quesIds=[], quesTypes=[], ansTypes=[]):
    method loadQA (line 143) | def loadQA(self, ids=[]):
    method showQA (line 154) | def showQA(self, anns):
    method loadRes (line 168) | def loadRes(self, resFile, quesFile):

FILE: eval_mm/vqa_eval.py
  class VQAEval (line 18) | class VQAEval:
    method __init__ (line 20) | def __init__(self, vqa=None, vqaRes=None, n=2):
    method evaluate (line 194) | def evaluate(self, quesIds=None):
    method processPunctuation (line 254) | def processPunctuation(self, inText):
    method processDigitArticle (line 265) | def processDigitArticle(self, inText):
    method setAccuracy (line 280) | def setAccuracy(self, accQA, accQuesType, accAnsType):
    method setEvalQA (line 298) | def setEvalQA(self, quesId, acc):
    method setEvalQuesType (line 301) | def setEvalQuesType(self, quesId, quesType, acc):
    method setEvalAnsType (line 306) | def setEvalAnsType(self, quesId, ansType, acc):
    method updateProgress (line 311) | def updateProgress(self, progress):

FILE: finetune.py
  class ModelArguments (line 24) | class ModelArguments:
  class DataArguments (line 29) | class DataArguments:
  class TrainingArguments (line 40) | class TrainingArguments(transformers.TrainingArguments):
  class LoraArguments (line 54) | class LoraArguments:
  function maybe_zero_3 (line 66) | def maybe_zero_3(param):
  function get_peft_state_maybe_zero_3 (line 77) | def get_peft_state_maybe_zero_3(named_params, bias):
  function rank0_print (line 103) | def rank0_print(*args):
  function safe_save_model_for_hf_trainer (line 108) | def safe_save_model_for_hf_trainer(trainer: transformers.Trainer, output...
  function preprocess (line 124) | def preprocess(
  class SupervisedDataset (line 178) | class SupervisedDataset(Dataset):
    method __init__ (line 181) | def __init__(self, raw_data, tokenizer: transformers.PreTrainedTokeniz...
    method __len__ (line 192) | def __len__(self):
    method __getitem__ (line 195) | def __getitem__(self, i) -> Dict[str, torch.Tensor]:
  class LazySupervisedDataset (line 203) | class LazySupervisedDataset(Dataset):
    method __init__ (line 206) | def __init__(self, raw_data, tokenizer: transformers.PreTrainedTokeniz...
    method __len__ (line 216) | def __len__(self):
    method __getitem__ (line 219) | def __getitem__(self, i) -> Dict[str, torch.Tensor]:
  function make_supervised_data_module (line 234) | def make_supervised_data_module(
  function train (line 255) | def train():

FILE: openai_api.py
  function lifespan (line 25) | async def lifespan(app: FastAPI):  # collects GPU memory
  class ModelCard (line 43) | class ModelCard(BaseModel):
  class ModelList (line 53) | class ModelList(BaseModel):
  class ChatMessage (line 58) | class ChatMessage(BaseModel):
  class DeltaMessage (line 64) | class DeltaMessage(BaseModel):
  class ChatCompletionRequest (line 69) | class ChatCompletionRequest(BaseModel):
  class ChatCompletionResponseChoice (line 80) | class ChatCompletionResponseChoice(BaseModel):
  class ChatCompletionResponseStreamChoice (line 86) | class ChatCompletionResponseStreamChoice(BaseModel):
  class ChatCompletionResponse (line 92) | class ChatCompletionResponse(BaseModel):
  function list_models (line 102) | async def list_models():
  function add_extra_stop_words (line 109) | def add_extra_stop_words(stop_words):
  function trim_stop_words (line 121) | def trim_stop_words(response, stop_words):
  function parse_messages (line 159) | def parse_messages(messages, functions):
  function parse_response (line 288) | def parse_response(response):
  function text_complete_last_message (line 324) | def text_complete_last_message(history, stop_words_ids):
  function create_chat_completion (line 352) | async def create_chat_completion(request: ChatCompletionRequest):
  function predict (line 401) | async def predict(
  function _get_args (line 449) | def _get_args():

FILE: web_demo_mm.py
  function _get_args (line 26) | def _get_args():
  function _load_model_tokenizer (line 45) | def _load_model_tokenizer(args):
  function _parse_text (line 69) | def _parse_text(text):
  function _remove_image_special (line 100) | def _remove_image_special(text):
  function _launch_demo (line 104) | def _launch_demo(args, model, tokenizer):
  function main (line 238) | def main():