def __init__(self):
self._tokenizer = load_bert_tokenizer('data')
self._device = torch.device(
'cuda:0' if torch.cuda.is_available() else 'cpu')
self._batch_collector = _get_batch_collector(self._device,
is_train=False)
self._model = BertClassifier(init_bert('data/'),
output_name='label').to(self._device)
def __init__(self, data_path='data'):
self._model = BertMulticlassClassifier(
init_bert(data_path), class_count=len(_ERRORS), output_name='error_type'
)
self._tokenizer = load_bert_tokenizer(data_path)
self.morph = pymorphy2.MorphAnalyzer()
use_cuda = torch.cuda.is_available()
self._device = torch.device('cuda:0' if use_cuda else 'cpu')
self._batch_collector = _get_batch_collector(self._device, is_train=False)
def __init__(self, seed=42, bert_path="data/models/bert/rubert/qbic"):
self.seed = seed
self.init_seed()
self.is_loaded = False
self.bert_path = bert_path
self._tokenizer = load_bert_tokenizer(self.bert_path)
self._device = torch.device(
"cuda:0" if torch.cuda.is_available() else "cpu")
self._batch_collector = _get_batch_collector(self._device,
is_train=False)
self._model = RubertClassifier(init_bert(self.bert_path),
output_name="label").to(self._device)
def __init__(self, seed=42, bert_path="data/models/bert/rubert/qbic"):
self.is_loaded = False
self.bert_path = bert_path
self._model = RubertMulticlassClassifier(
init_bert(self.bert_path),
class_count=len(_ERRORS),
output_name="error_type",
)
self._tokenizer = load_bert_tokenizer(self.bert_path)
self.morph = pymorphy2.MorphAnalyzer()
self.seed = seed
self.init_seed()
use_cuda = torch.cuda.is_available()
self._device = torch.device("cuda:0" if use_cuda else "cpu")
self._batch_collector = _get_batch_collector(self._device, is_train=False)