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| # -*- coding: utf-8 -*- | |
| """ Global variables. | |
| """ | |
| import tempfile | |
| from os.path import abspath, dirname | |
| # The ordering of these special tokens matter | |
| # blank tokens can be used for new purposes | |
| # Tokenizer should be updated if special token prefix is changed | |
| SPECIAL_PREFIX = 'CUSTOM_' | |
| SPECIAL_TOKENS = ['CUSTOM_MASK', | |
| 'CUSTOM_UNKNOWN', | |
| 'CUSTOM_AT', | |
| 'CUSTOM_URL', | |
| 'CUSTOM_NUMBER', | |
| 'CUSTOM_BREAK'] | |
| SPECIAL_TOKENS.extend(['{}BLANK_{}'.format(SPECIAL_PREFIX, i) for i in range(6, 10)]) | |
| ROOT_PATH = dirname(dirname(abspath(__file__))) | |
| VOCAB_PATH = '{}/model/vocabulary.json'.format(ROOT_PATH) | |
| PRETRAINED_PATH = '{}/model/pytorch_model.bin'.format(ROOT_PATH) | |
| WEIGHTS_DIR = tempfile.mkdtemp() | |
| NB_TOKENS = 50000 | |
| NB_EMOJI_CLASSES = 64 | |
| FINETUNING_METHODS = ['last', 'full', 'new', 'chain-thaw'] | |
| FINETUNING_METRICS = ['acc', 'weighted'] | |