transformers/tests/test_tokenization_bert_japanese.py
SaulLu 476ba679dd
Feature to use the PreTrainedTokenizerFast class as a stand-alone tokenizer (#11810)
* feature for tokenizer without slow/legacy version

* format

* modify common test

* add tests

* add PreTrainedTokenizerFast to AutoTokenizer

* format

* change tokenizer common test in order to be able to run test without a slow version

* update tokenizer fast test in order to use `rust_tokenizer_class` attribute instead of `tokenizer_class`

* add autokenizer test

* replace  `if self.tokenizer_class is not None` with ` if self.tokenizer_class is None`

* remove obsolete change in comment

* Update src/transformers/tokenization_utils_base.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/tokenization_utils_fast.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* change `get_main_tokenizer` into `get_tokenizers`

* clarify `get_tokenizers` method

* homogenize with `test_slow_tokenizer` and `test_rust_tokenizer`

* add `test_rust_tokenizer = False` to tokenizer which don't define a fast version

* `test_rust_tokenizer = False` for BertJapaneseTokenizer

* `test_rust_tokenizer = False` for BertJapaneseCharacterTokenizationTest

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
2021-06-14 11:58:44 +02:00

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# coding=utf-8
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
MecabTokenizer,
WordpieceTokenizer,
)
from transformers.testing_utils import custom_tokenizers
from .test_tokenization_common import TokenizerTesterMixin
@custom_tokenizers
class BertJapaneseTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
tokenizer_class = BertJapaneseTokenizer
test_rust_tokenizer = False
space_between_special_tokens = True
def setUp(self):
super().setUp()
vocab_tokens = [
"[UNK]",
"[CLS]",
"[SEP]",
"こんにちは",
"こん",
"にちは",
"ばんは",
"##こん",
"##にちは",
"##ばんは",
"世界",
"##世界",
"",
"##、",
"",
"##。",
]
self.vocab_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"])
with open(self.vocab_file, "w", encoding="utf-8") as vocab_writer:
vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))
def get_input_output_texts(self, tokenizer):
input_text = "こんにちは、世界。 \nこんばんは、世界。"
output_text = "こんにちは 、 世界 。 こんばんは 、 世界 。"
return input_text, output_text
def get_clean_sequence(self, tokenizer):
input_text, output_text = self.get_input_output_texts(tokenizer)
ids = tokenizer.encode(output_text, add_special_tokens=False)
text = tokenizer.decode(ids, clean_up_tokenization_spaces=False)
return text, ids
def test_pretokenized_inputs(self):
pass # TODO add if relevant
def test_maximum_encoding_length_pair_input(self):
pass # TODO add if relevant
def test_maximum_encoding_length_single_input(self):
pass # TODO add if relevant
def test_full_tokenizer(self):
tokenizer = self.tokenizer_class(self.vocab_file)
tokens = tokenizer.tokenize("こんにちは、世界。\nこんばんは、世界。")
self.assertListEqual(tokens, ["こんにちは", "", "世界", "", "こん", "##ばんは", "", "世界", ""])
self.assertListEqual(tokenizer.convert_tokens_to_ids(tokens), [3, 12, 10, 14, 4, 9, 12, 10, 14])
def test_pickle_mecab_tokenizer(self):
tokenizer = self.tokenizer_class(self.vocab_file, word_tokenizer_type="mecab")
self.assertIsNotNone(tokenizer)
text = "こんにちは、世界。\nこんばんは、世界。"
tokens = tokenizer.tokenize(text)
self.assertListEqual(tokens, ["こんにちは", "", "世界", "", "こん", "##ばんは", "", "世界", ""])
self.assertListEqual(tokenizer.convert_tokens_to_ids(tokens), [3, 12, 10, 14, 4, 9, 12, 10, 14])
filename = os.path.join(self.tmpdirname, "tokenizer.bin")
with open(filename, "wb") as handle:
pickle.dump(tokenizer, handle)
with open(filename, "rb") as handle:
tokenizer_new = pickle.load(handle)
tokens_loaded = tokenizer_new.tokenize(text)
self.assertListEqual(tokens, tokens_loaded)
def test_mecab_tokenizer_ipadic(self):
tokenizer = MecabTokenizer(mecab_dic="ipadic")
self.assertListEqual(
tokenizer.tokenize(" \tアップルストアでiPhone\n 発売された 。 "),
["アップルストア", "", "iPhone", "8", "", "発売", "", "", "", ""],
)
def test_mecab_tokenizer_unidic_lite(self):
try:
tokenizer = MecabTokenizer(mecab_dic="unidic_lite")
except ModuleNotFoundError:
return
self.assertListEqual(
tokenizer.tokenize(" \tアップルストアでiPhone\n 発売された 。 "),
["アップル", "ストア", "", "iPhone", "8", "", "発売", "", "", "", ""],
)
def test_mecab_tokenizer_unidic(self):
try:
tokenizer = MecabTokenizer(mecab_dic="unidic")
except ModuleNotFoundError:
return
self.assertListEqual(
tokenizer.tokenize(" \tアップルストアでiPhone\n 発売された 。 "),
["アップル", "ストア", "", "iPhone", "8", "", "発売", "", "", "", ""],
)
def test_mecab_tokenizer_lower(self):
tokenizer = MecabTokenizer(do_lower_case=True, mecab_dic="ipadic")
self.assertListEqual(
tokenizer.tokenize(" \tアップルストアでiPhone\n 発売された 。 "),
["アップルストア", "", "iphone", "8", "", "発売", "", "", "", ""],
)
def test_mecab_tokenizer_with_option(self):
try:
tokenizer = MecabTokenizer(
do_lower_case=True, normalize_text=False, mecab_option="-d /usr/local/lib/mecab/dic/jumandic"
)
except RuntimeError:
# if dict doesn't exist in the system, previous code raises this error.
return
self.assertListEqual(
tokenizer.tokenize(" \tアップルストアでiPhone\n 発売された 。 "),
["アップルストア", "", "iPhone", "", "", "発売", "", "れた", "\u3000", ""],
)
def test_mecab_tokenizer_no_normalize(self):
tokenizer = MecabTokenizer(normalize_text=False, mecab_dic="ipadic")
self.assertListEqual(
tokenizer.tokenize(" \tアップルストアでiPhone\n 発売された 。 "),
["アップルストア", "", "iPhone", "", "", "発売", "", "", "", " ", ""],
)
def test_wordpiece_tokenizer(self):
vocab_tokens = ["[UNK]", "[CLS]", "[SEP]", "こんにちは", "こん", "にちは" "ばんは", "##こん", "##にちは", "##ばんは"]
vocab = {}
for (i, token) in enumerate(vocab_tokens):
vocab[token] = i
tokenizer = WordpieceTokenizer(vocab=vocab, unk_token="[UNK]")
self.assertListEqual(tokenizer.tokenize(""), [])
self.assertListEqual(tokenizer.tokenize("こんにちは"), ["こんにちは"])
self.assertListEqual(tokenizer.tokenize("こんばんは"), ["こん", "##ばんは"])
self.assertListEqual(tokenizer.tokenize("こんばんは こんばんにちは こんにちは"), ["こん", "##ばんは", "[UNK]", "こんにちは"])
def test_sequence_builders(self):
tokenizer = self.tokenizer_class.from_pretrained("cl-tohoku/bert-base-japanese")
text = tokenizer.encode("ありがとう。", add_special_tokens=False)
text_2 = tokenizer.encode("どういたしまして。", add_special_tokens=False)
encoded_sentence = tokenizer.build_inputs_with_special_tokens(text)
encoded_pair = tokenizer.build_inputs_with_special_tokens(text, text_2)
# 2 is for "[CLS]", 3 is for "[SEP]"
assert encoded_sentence == [2] + text + [3]
assert encoded_pair == [2] + text + [3] + text_2 + [3]
@custom_tokenizers
class BertJapaneseCharacterTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
tokenizer_class = BertJapaneseTokenizer
test_rust_tokenizer = False
def setUp(self):
super().setUp()
vocab_tokens = ["[UNK]", "[CLS]", "[SEP]", "", "", "", "", "", "", "", "", "", ""]
self.vocab_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"])
with open(self.vocab_file, "w", encoding="utf-8") as vocab_writer:
vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))
def get_tokenizer(self, **kwargs):
return BertJapaneseTokenizer.from_pretrained(self.tmpdirname, subword_tokenizer_type="character", **kwargs)
def get_input_output_texts(self, tokenizer):
input_text = "こんにちは、世界。 \nこんばんは、世界。"
output_text = "こ ん に ち は 、 世 界 。 こ ん ば ん は 、 世 界 。"
return input_text, output_text
def test_pretokenized_inputs(self):
pass # TODO add if relevant
def test_maximum_encoding_length_pair_input(self):
pass # TODO add if relevant
def test_maximum_encoding_length_single_input(self):
pass # TODO add if relevant
def test_full_tokenizer(self):
tokenizer = self.tokenizer_class(self.vocab_file, subword_tokenizer_type="character")
tokens = tokenizer.tokenize("こんにちは、世界。 \nこんばんは、世界。")
self.assertListEqual(
tokens, ["", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""]
)
self.assertListEqual(
tokenizer.convert_tokens_to_ids(tokens), [3, 4, 5, 6, 7, 11, 9, 10, 12, 3, 4, 8, 4, 7, 11, 9, 10, 12]
)
def test_character_tokenizer(self):
vocab_tokens = ["[UNK]", "[CLS]", "[SEP]", "", "", "", "", "", "", "", "" "", ""]
vocab = {}
for (i, token) in enumerate(vocab_tokens):
vocab[token] = i
tokenizer = CharacterTokenizer(vocab=vocab, unk_token="[UNK]")
self.assertListEqual(tokenizer.tokenize(""), [])
self.assertListEqual(tokenizer.tokenize("こんにちは"), ["", "", "", "", ""])
self.assertListEqual(tokenizer.tokenize("こんにちほ"), ["", "", "", "", "[UNK]"])
def test_sequence_builders(self):
tokenizer = self.tokenizer_class.from_pretrained("cl-tohoku/bert-base-japanese-char")
text = tokenizer.encode("ありがとう。", add_special_tokens=False)
text_2 = tokenizer.encode("どういたしまして。", add_special_tokens=False)
encoded_sentence = tokenizer.build_inputs_with_special_tokens(text)
encoded_pair = tokenizer.build_inputs_with_special_tokens(text, text_2)
# 2 is for "[CLS]", 3 is for "[SEP]"
assert encoded_sentence == [2] + text + [3]
assert encoded_pair == [2] + text + [3] + text_2 + [3]
@custom_tokenizers
class AutoTokenizerCustomTest(unittest.TestCase):
def test_tokenizer_bert_japanese(self):
EXAMPLE_BERT_JAPANESE_ID = "cl-tohoku/bert-base-japanese"
tokenizer = AutoTokenizer.from_pretrained(EXAMPLE_BERT_JAPANESE_ID)
self.assertIsInstance(tokenizer, BertJapaneseTokenizer)