def get_recurrent_tokenizer(vocab,
max_context_tokens,
unk_token,
pad_token,
device="cpu"):
"""
Return a tokenizer to be used with recurrent-based models
"""
question_tokenizer = Tokenizer(WordLevel(vocab, unk_token=unk_token))
question_tokenizer.normalizer = Sequence(
[StripAccents(), Lowercase(), Strip()])
question_tokenizer.pre_tokenizer = PreSequence(
[Whitespace(), Punctuation()])
question_tokenizer.enable_padding(direction="right",
pad_id=vocab[pad_token],
pad_type_id=1,
pad_token=pad_token)
context_tokenizer = Tokenizer(WordLevel(vocab, unk_token=unk_token))
context_tokenizer.normalizer = Sequence(
[StripAccents(), Lowercase(), Strip()])
context_tokenizer.pre_tokenizer = PreSequence(
[Whitespace(), Punctuation()])
context_tokenizer.enable_padding(
direction="right",
pad_id=vocab[pad_token],
pad_type_id=1,
pad_token=pad_token,
)
context_tokenizer.enable_truncation(max_context_tokens)
return RecurrentSquadTokenizer(question_tokenizer,
context_tokenizer,
device=device)
def test_instantiate(self):
assert Punctuation() is not None
assert Punctuation("removed") is not None
assert isinstance(Punctuation(), PreTokenizer)
assert isinstance(Punctuation(), Punctuation)
assert isinstance(pickle.loads(pickle.dumps(Punctuation())),
Punctuation)
def test_bert_like(self):
pre_tokenizer = Sequence([WhitespaceSplit(), Punctuation()])
assert isinstance(Sequence([]), PreTokenizer)
assert isinstance(Sequence([]), Sequence)
assert isinstance(pickle.loads(pickle.dumps(pre_tokenizer)), Sequence)
result = pre_tokenizer.pre_tokenize_str("Hey friend! How are you?!?")
assert result == [
("Hey", (0, 3)),
("friend", (4, 10)),
("!", (10, 11)),
("How", (16, 19)),
("are", (20, 23)),
("you", (24, 27)),
("?", (27, 28)),
("!", (28, 29)),
("?", (29, 30)),
]
