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from tokenizers import BertWordPieceTokenizer
from ..utils import bert_files, data_dir, multiprocessing_with_parallelism
class TestBertWordPieceTokenizer:
def test_basic_encode(self, bert_files):
tokenizer = BertWordPieceTokenizer.from_file(bert_files["vocab"])
# Encode with special tokens by default
output = tokenizer.encode("My name is John", "pair")
assert output.ids == [101, 2026, 2171, 2003, 2198, 102, 3940, 102]
assert output.tokens == [
"[CLS]",
"my",
"name",
"is",
"john",
"[SEP]",
"pair",
"[SEP]",
]
assert output.offsets == [
(0, 0),
(0, 2),
(3, 7),
(8, 10),
(11, 15),
(0, 0),
(0, 4),
(0, 0),
]
assert output.type_ids == [0, 0, 0, 0, 0, 0, 1, 1]
# Can encode without the special tokens
output = tokenizer.encode("My name is John", "pair", add_special_tokens=False)
assert output.ids == [2026, 2171, 2003, 2198, 3940]
assert output.tokens == ["my", "name", "is", "john", "pair"]
assert output.offsets == [(0, 2), (3, 7), (8, 10), (11, 15), (0, 4)]
assert output.type_ids == [0, 0, 0, 0, 1]
def test_multiprocessing_with_parallelism(self, bert_files):
tokenizer = BertWordPieceTokenizer.from_file(bert_files["vocab"])
multiprocessing_with_parallelism(tokenizer, False)
multiprocessing_with_parallelism(tokenizer, True)
def test_train_from_iterator(self):
text = ["A first sentence", "Another sentence", "And a last one"]
tokenizer = BertWordPieceTokenizer()
tokenizer.train_from_iterator(text, show_progress=False)
output = tokenizer.encode("A sentence")
assert output.tokens == ["a", "sentence"]
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