SYMBOL INDEX (69 symbols across 7 files)

FILE: evaluation/classification/evaluate/mgpt_classification.py
  function merge_lang_datasets (line 24) | def merge_lang_datasets(benchmark, task_lang_name, split, langs, cache_d...
  class Metrics (line 38) | class Metrics:
    method __init__ (line 39) | def __init__(self, task_name):
    method calculate_metric (line 42) | def calculate_metric(self, predictions, answers):
    method calculate_accuracies (line 47) | def calculate_accuracies(self, answers, predictions):
  class MultilingualClassificationTask (line 55) | class MultilingualClassificationTask(RuGPTEvaluationTask):
    method __init__ (line 56) | def __init__(self, config):
    method verbalize_samples (line 65) | def verbalize_samples(self, lang, dataset, prompt):
    method load_data (line 68) | def load_data(self, split):
    method verbalize_train_examples (line 71) | def verbalize_train_examples(self, ds_train, ds_test, lang):
    method calculate_scores (line 100) | def calculate_scores(self, data, model):
    method predict_subset (line 106) | def predict_subset(self, lang, dataset_lang, model):
    method predict (line 138) | def predict(self, model):
  class AMAZONTask (line 167) | class AMAZONTask(MultilingualClassificationTask):
    method __init__ (line 168) | def __init__(self, config):
    method verbalize_samples (line 172) | def verbalize_samples(self, lang, dataset, prompt):
    method load_data (line 176) | def load_data(self, split):
  class PAWSXTask (line 190) | class PAWSXTask(MultilingualClassificationTask):
    method __init__ (line 191) | def __init__(self, config):
    method verbalize_samples (line 195) | def verbalize_samples(self, lang, dataset, prompt):
    method load_data (line 215) | def load_data(self, split):
  class XNLITask (line 225) | class XNLITask(MultilingualClassificationTask):
    method __init__ (line 226) | def __init__(self, config):
    method verbalize_samples (line 230) | def verbalize_samples(self, lang, dataset, prompt):
    method load_data (line 250) | def load_data(self, split):
  class XCOPATask (line 258) | class XCOPATask(MultilingualClassificationTask):
    method __init__ (line 259) | def __init__(self, config):
    method verbalize_samples (line 264) | def verbalize_samples(self, lang, dataset, prompt):
    method load_data (line 284) | def load_data(self, split):
  class XWINOTask (line 300) | class XWINOTask(MultilingualClassificationTask):
    method __init__ (line 301) | def __init__(self, config):
    method verbalize_samples (line 305) | def verbalize_samples(self, lang, dataset, prompt):
    method preprocess_sentence (line 309) | def preprocess_sentence(self, sent, idxs, candidate, lang):
    method load_data (line 322) | def load_data(self, split):
  function evaluate_task (line 361) | def evaluate_task(task_name, model, shots=0):

FILE: evaluation/classification/evaluate/mgpt_classification_configs.py
  class TaskConfig (line 6) | class TaskConfig:
  class XNLITaskConfig (line 14) | class XNLITaskConfig(TaskConfig):
  class PAWSXTaskConfig (line 133) | class PAWSXTaskConfig(TaskConfig):
  class AMAZONTaskConfig (line 149) | class AMAZONTaskConfig(TaskConfig):
  class XCOPATaskConfig (line 163) | class XCOPATaskConfig(TaskConfig):
  class XWINOTaskConfig (line 184) | class XWINOTaskConfig(TaskConfig):

FILE: evaluation/classification/evaluate/task.py
  class RuGPTEvaluationTask (line 1) | class RuGPTEvaluationTask:
    method __init__ (line 2) | def __init__(self, config):
    method verbalize_samples (line 5) | def verbalize_samples(self, lang, dataset, prompt):
    method load_data (line 8) | def load_data(self):
    method calculate_scores (line 11) | def calculate_scores(self, data, model):
    method predict (line 14) | def predict(self, model):

FILE: evaluation/classification/inference.py
  class InferenceModel (line 12) | class InferenceModel:
    method __init__ (line 13) | def __init__(self, model_path, tokenizer_path=None, device=0):
    method forward (line 22) | def forward(self, texts, batch_size=8, seq_length=512, loss_per_pos=Fa...
    method forward_pretokenized (line 28) | def forward_pretokenized(self, dataset, loss_per_pos=False, limit=0):
    method forward_single_batch (line 51) | def forward_single_batch(self, inputs, loss_per_pos=False):
  function load_mgpt (line 77) | def load_mgpt(path, tokenizer_path=None, device=0):

FILE: evaluation/classification/list_docs_dataset.py
  class ListDocsDataset (line 6) | class ListDocsDataset(Dataset):
    method __init__ (line 7) | def __init__(self, texts, tokenizer, max_length, padding=True, strip=T...
    method __len__ (line 24) | def __len__(self):
    method __getitem__ (line 27) | def __getitem__(self, item):
  function get_dataloader (line 31) | def get_dataloader(texts, tokenizer, batch_size, max_length):

FILE: evaluation/sequence_labeling/inference.py
  class InferenceModel (line 12) | class InferenceModel:
    method __init__ (line 13) | def __init__(self, model_path, tokenizer_path=None, device=0):
    method forward (line 22) | def forward(self, texts, batch_size=8, seq_length=512, loss_per_pos=Fa...
    method forward_pretokenized (line 28) | def forward_pretokenized(self, dataset, loss_per_pos=False, limit=0):
    method forward_single_batch (line 51) | def forward_single_batch(self, inputs, loss_per_pos=False):
  function load_mgpt (line 77) | def load_mgpt(path, tokenizer_path=None, device=0):

FILE: evaluation/sequence_labeling/list_docs_dataset.py
  class ListDocsDataset (line 6) | class ListDocsDataset(Dataset):
    method __init__ (line 7) | def __init__(self, texts, tokenizer, max_length, padding=True, strip=T...
    method __len__ (line 24) | def __len__(self):
    method __getitem__ (line 27) | def __getitem__(self, item):
  function get_dataloader (line 31) | def get_dataloader(texts, tokenizer, batch_size, max_length):