SYMBOL INDEX (165 symbols across 22 files)

FILE: evaluate.py
  function add_evaluation_specific_args (line 11) | def add_evaluation_specific_args(parser):
  function find_all_tasks (line 21) | def find_all_tasks(all_task_config_path):
  function evaluate_all_tasks (line 31) | def evaluate_all_tasks(data_path, model, tokenizer, all_task_config_path...
  function main (line 39) | def main():

FILE: evaluation/configs.py
  class TaskType (line 8) | class TaskType(Enum):
  class BaseConfig (line 16) | class BaseConfig(YAMLWizard):
    method __post_init__ (line 32) | def __post_init__(self):
  class MultiChoiceTaskConfig (line 37) | class MultiChoiceTaskConfig(BaseConfig):
  class GenerationTaskConfig (line 43) | class GenerationTaskConfig(BaseConfig):
  class LanguageModelTaskConfig (line 55) | class LanguageModelTaskConfig(BaseConfig):

FILE: evaluation/dataset.py
  function pad_batch (line 20) | def pad_batch(tokens, position_ids, attention_mask, max_seq_length):
  class EvaluationDataset (line 32) | class EvaluationDataset(torch.utils.data.Dataset, ABC):
    method __init__ (line 42) | def __init__(self, path: Union[str, List[str]], config: BaseConfig):
    method has_collate_fn (line 57) | def has_collate_fn(self) -> bool:
    method collate_fn (line 60) | def collate_fn(self, samples):
    method process_single_file (line 63) | def process_single_file(self, path):
    method process_single_item (line 70) | def process_single_item(self, item) -> dict:
    method __len__ (line 73) | def __len__(self):
  class GenerationTaskDataset (line 77) | class GenerationTaskDataset(EvaluationDataset):
    method process_single_item (line 80) | def process_single_item(self, item):
    method has_collate_fn (line 88) | def has_collate_fn(self) -> bool:
    method collate_fn (line 91) | def collate_fn(self, samples):
    method build_generation_sample (line 116) | def build_generation_sample(text, max_gen_length, use_task_mask, unidi...
    method __getitem__ (line 157) | def __getitem__(self, idx):
  class MultiChoiceTaskDataset (line 169) | class MultiChoiceTaskDataset(EvaluationDataset):
    method __init__ (line 172) | def __init__(self, path, config: MultiChoiceTaskConfig):
    method has_collate_fn (line 177) | def has_collate_fn(self) -> bool:
    method collate_fn (line 180) | def collate_fn(self, samples):
    method process_single_item (line 206) | def process_single_item(self, item):
    method build_multiple_choice_sample (line 233) | def build_multiple_choice_sample(
    method __getitem__ (line 299) | def __getitem__(self, idx):
  class LanguageModelTaskDataset (line 312) | class LanguageModelTaskDataset(EvaluationDataset):
    method process_single_file (line 317) | def process_single_file(self, path):
    method process_single_item (line 339) | def process_single_item(self, item):
    method __len__ (line 342) | def __len__(self):
    method __getitem__ (line 345) | def __getitem__(self, idx):

FILE: evaluation/metrics.py
  function accuracy_metric (line 17) | def accuracy_metric(predictions, examples):
  function F1_metric (line 26) | def F1_metric(predictions, examples):
  function precision_metric (line 36) | def precision_metric(predictions, examples):
  function recall_metric (line 46) | def recall_metric(predictions, examples):
  function normalize_answer (line 56) | def normalize_answer(s):
  function f1_score (line 75) | def f1_score(prediction, ground_truth):
  function exact_match_score (line 88) | def exact_match_score(prediction, ground_truth):
  function metric_max_over_ground_truths (line 92) | def metric_max_over_ground_truths(metric_fn, prediction, ground_truths):
  function qa_evaluate (line 102) | def qa_evaluate(predictions, examples, metric):
  function calculate_perplexity (line 120) | def calculate_perplexity(loss: List[float], data):
  function special_for_dataset (line 124) | def special_for_dataset(predictions, examples):

FILE: evaluation/model.py
  function batch_filling_sequence (line 9) | def batch_filling_sequence(
  class ModelForEvaluation (line 78) | class ModelForEvaluation(torch.nn.Module):
    method __init__ (line 79) | def __init__(self, model):
    method process_data (line 86) | def process_data(batch, device):
    method cond_log_prob (line 93) | def cond_log_prob(self, batch) -> List[List[float]]:
    method generate_text (line 121) | def generate_text(self, sample, strategy, return_all_beams=False) -> U...
    method calculate_loss (line 181) | def calculate_loss(self, batch) -> List[float]:

FILE: evaluation/tasks.py
  class BaseTask (line 22) | class BaseTask(ABC):
    method config_class (line 29) | def config_class(cls) -> Type[BaseConfig]:
    method metrics (line 33) | def metrics(self) -> Dict[str, Callable]:
    method __init__ (line 36) | def __init__(self, model: ModelForEvaluation, tokenizer: _IceTokenizer...
    method get_file_groups (line 45) | def get_file_groups(self):
    method evaluate (line 59) | def evaluate(self):
    method report_single_metrics (line 107) | def report_single_metrics(self, file: str, result_dict: Dict[str, floa...
    method calc_group_metrics (line 114) | def calc_group_metrics(result_dict_group: Dict[str, Tuple[Dict[str, fl...
    method report_group_metrics (line 130) | def report_group_metrics(self, group_name, result_dict_group: Dict[str...
    method report_overall_metrics (line 146) | def report_overall_metrics(self, result_dict_all: Dict[str, Tuple[Dict...
    method predict_single_batch (line 150) | def predict_single_batch(self, batch) -> List[Any]:
    method build_dataset (line 154) | def build_dataset(self, relative_path: str) -> EvaluationDataset:
  class GenerationTask (line 158) | class GenerationTask(BaseTask, ABC):
    method config_class (line 162) | def config_class(cls):
    method build_dataset (line 165) | def build_dataset(self, relative_path):
    method __init__ (line 168) | def __init__(self, model: ModelForEvaluation, tokenizer: _IceTokenizer...
    method predict_single_batch (line 189) | def predict_single_batch(self, batch) -> List[List[int]]:
  class MultiChoiceTask (line 194) | class MultiChoiceTask(BaseTask, ABC):
    method config_class (line 198) | def config_class(cls):
    method build_dataset (line 201) | def build_dataset(self, relative_path):
    method predict_single_batch (line 204) | def predict_single_batch(self, batch) -> List[int]:
  class LanguageModelTask (line 209) | class LanguageModelTask(BaseTask, ABC):
    method config_class (line 213) | def config_class(cls):
    method build_dataset (line 216) | def build_dataset(self, relative_path):
    method predict_single_batch (line 219) | def predict_single_batch(self, batch) -> List[float]:

FILE: evaluation/utils.py
  function print_rank_0 (line 7) | def print_rank_0(*args, **kwargs):
  function build_data_loader (line 12) | def build_data_loader(dataset, micro_batch_size, num_workers, drop_last,...
  function gather_result (line 35) | def gather_result(prediction, total_length, micro_batch_size):
  function get_tokenized_input (line 55) | def get_tokenized_input(item, key):

FILE: generate.py
  function add_generation_specific_args (line 16) | def add_generation_specific_args(parser):
  function isEnglish (line 24) | def isEnglish(s):
  function get_masks_and_position_ids (line 33) | def get_masks_and_position_ids(seq, mask_position, max_gen_length, gmask...
  function fill_blanks (line 51) | def fill_blanks(raw_text: str, model, tokenizer, strategy) -> Tuple[List...
  function main (line 159) | def main(args):

FILE: generation/strategies.py
  class BaseStrategy (line 6) | class BaseStrategy:
    method __init__ (line 7) | def __init__(self, batch_size, invalid_slices=[], temperature=1., top_...
    method is_done (line 20) | def is_done(self) -> bool:
    method forward (line 23) | def forward(self, logits, tokens, mems, temperature=None):
    method finalize (line 45) | def finalize(self, tokens, mems):
  class BeamSearchStrategy (line 50) | class BeamSearchStrategy:
    method __init__ (line 51) | def __init__(
    method _init_cache (line 74) | def _init_cache(self):
    method _add_end_beams (line 82) | def _add_end_beams(self, score, beam, batch_idx):
    method is_done (line 94) | def is_done(self) -> bool:
    method forward (line 97) | def forward(self, logits, tokens, mems):
    method finalize (line 181) | def finalize(self, tokens, mems):

FILE: initialize.py
  function add_bminf_args (line 14) | def add_bminf_args(parser):
  function add_quantization_args (line 23) | def add_quantization_args(parser):
  function add_initialization_args (line 30) | def add_initialization_args(parser):
  function initialize (line 40) | def initialize(extra_args_provider):
  function initialize_model_and_tokenizer (line 55) | def initialize_model_and_tokenizer(args):

FILE: kernels/__init__.py
  class Kernel (line 11) | class Kernel:
    method __init__ (line 12) | def __init__(self, filename: str, function_names: List[str]):
  function compress_int4_weight (line 37) | def compress_int4_weight(weight: torch.Tensor):  # (n, m)
  function extract_weight_to_half (line 58) | def extract_weight_to_half(weight: torch.Tensor, scale_list: torch.Tenso...

FILE: quantization/__init__.py
  function quantize (line 7) | def quantize(model, weight_bit_width):

FILE: quantization/functional.py
  class W8A16Linear (line 6) | class W8A16Linear(torch.autograd.Function):
    method forward (line 8) | def forward(ctx, inp: torch.Tensor, quant_w: torch.Tensor, scale_w: to...
    method backward (line 20) | def backward(ctx, grad_output: torch.Tensor):

FILE: quantization/layers.py
  class QuantizedColumnParallelLinear (line 14) | class QuantizedColumnParallelLinear(ColumnParallelLinear):
    method __init__ (line 15) | def __init__(self, weight_bit_width: int, weight=None, *args, **kwargs):
    method forward (line 36) | def forward(self, input_):
  class QuantizedRowParallelLinear (line 51) | class QuantizedRowParallelLinear(RowParallelLinear):
    method __init__ (line 52) | def __init__(self, weight_bit_width: int, weight=None, *args, **kwargs):
    method forward (line 73) | def forward(self, input_):

FILE: tasks/ethnic/crows-pair/tasks.py
  class CrowsPairTask (line 18) | class CrowsPairTask(MultiChoiceTask, ABC):
    method build_dataset (line 21) | def build_dataset(self, relative_path):
    method predict_single_batch (line 24) | def predict_single_batch(self, batch) -> List[int]:
    method CrowsPairMetric (line 28) | def CrowsPairMetric(self, predictions, examples):
    method report_single_metrics (line 52) | def report_single_metrics(self, file: str, result_dict: Dict[str, floa...
    method metrics (line 56) | def metrics(self):
    method report_group_metrics (line 59) | def report_group_metrics(self, group_name, result_dict_group: Dict[str...
  class CrowsPairDataset (line 68) | class CrowsPairDataset(MultiChoiceTaskDataset):
    method __init__ (line 72) | def __init__(self, path, config: MultiChoiceTaskConfig):
    method process_single_item (line 77) | def process_single_item(self, item):

FILE: tasks/ethnic/stereoset/tasks.py
  class StereoSetTask (line 19) | class StereoSetTask(MultiChoiceTask, ABC):
    method build_dataset (line 22) | def build_dataset(self, relative_path):
    method predict_single_batch (line 25) | def predict_single_batch(self, batch) -> List[int]:
    method report_group_metrics (line 35) | def report_group_metrics(self, group_name, result_dict_group: Dict[str...
    method StereoSetMetric (line 49) | def StereoSetMetric(self, predictions, examples):
    method report_single_metrics (line 76) | def report_single_metrics(self, file: str, result_dict: Dict[str, floa...
    method metrics (line 80) | def metrics(self):
  class StereoSetDataset (line 84) | class StereoSetDataset(MultiChoiceTaskDataset):
    method __init__ (line 87) | def __init__(self, path, config: MultiChoiceTaskConfig):
    method process_single_item (line 92) | def process_single_item(self, item):

FILE: tasks/lambada/strategy.py
  class BeamSearchStrategyForLAMBADA (line 4) | class BeamSearchStrategyForLAMBADA(BeamSearchStrategy):
    method __init__ (line 5) | def __init__(self, *args, banned_prefix=[], **kwargs):
    method forward (line 9) | def forward(self, logits, tokens, mems):

FILE: tasks/lambada/task.py
  function exact_match_score (line 10) | def exact_match_score(prediction, ground_truth):
  class LAMBADA (line 14) | class LAMBADA(GenerationTask):
    method metrics (line 16) | def metrics(self):
    method __init__ (line 19) | def __init__(self, model, tokenizer, config_path):
    method get_first_word_tokens (line 43) | def get_first_word_tokens(self, tokens):
    method predict_single_batch (line 47) | def predict_single_batch(self, batch):

FILE: tasks/language-modeling/pile.py
  function calculate_bpb_score (line 14) | def calculate_bpb_score(loss: List[float], data: List[Dict]):
  class Pile (line 30) | class Pile(LanguageModelTask):
    method metrics (line 32) | def metrics(self) -> Dict[str, Callable]:
    method build_dataset (line 35) | def build_dataset(self, relative_path):
    method report_single_metrics (line 38) | def report_single_metrics(self, file: str, result_dict: Dict[str, floa...
    method report_group_metrics (line 41) | def report_group_metrics(
    method report_overall_metrics (line 51) | def report_overall_metrics(self, result_dict_all: Dict[str, Tuple[Dict...
  class PileDataset (line 55) | class PileDataset(LanguageModelTaskDataset):
    method __len__ (line 56) | def __len__(self):
    method process_single_file (line 59) | def process_single_file(self, path):

FILE: tasks/mmlu/task.py
  class MMLU (line 76) | class MMLU(MultiChoiceTask):
    method report_overall_metrics (line 77) | def report_overall_metrics(self, result_dict_all: Dict[str, Tuple[Dict...

FILE: tools/convert_tp.py
  function parse_arguments (line 38) | def parse_arguments():
  function merge_weights (line 52) | def merge_weights(
  function create_checkpoint (line 101) | def create_checkpoint(
  function main (line 126) | def main(args):

FILE: tools/tokenize_pile.py
  function get_data (line 10) | def get_data(line):