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faster dataset building

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This commit is contained in:
mgrankin 2019-09-26 16:53:13 +03:00
parent 0f92f76ca3
commit f71a4577b8
1 changed files with 2 additions and 3 deletions
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5
examples/run_lm_finetuning.py
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@ -74,9 +74,8 @@ class TextDataset(Dataset):
tokenized_text = tokenizer.convert_tokens_to_ids(tokenizer.tokenize(text))
while len(tokenized_text) >= block_size: # Truncate in block of block_size
self.examples.append(tokenizer.add_special_tokens_single_sequence(tokenized_text[:block_size]))
tokenized_text = tokenized_text[block_size:]
for i in range(0, len(tokenized_text)-block_size+1, block_size): # Truncate in block of block_size
self.examples.append(tokenizer.add_special_tokens_single_sentence(tokenized_text[i:i+block_size]))
# Note that we are loosing the last truncated example here for the sake of simplicity (no padding)
# If your dataset is small, first you should loook for a bigger one :-) and second you
# can change this behavior by adding (model specific) padding.