text: # coding=utf-8
  # Copyright 2018 The Google AI Language Team Authors.
  #
  # 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.testing_utils import custom_tokenizers
  from transformers.tokenization_bert import WordpieceTokenizer
  from transformers.tokenization_bert_japanese import (
      VOCAB_FILES_NAMES,
      BertJapaneseTokenizer,
      CharacterTokenizer,
      MecabTokenizer,
  )
  
  from .test_tokenization_common import TokenizerTesterMixin
  
  
  @custom_tokenizers
  class BertJapaneseTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
  
      tokenizer_class = BertJapaneseTokenizer
      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ｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "),
              ["アップルストア", "で", "iPhone", "8", "が", "発売", "さ", "れ", "た", "。"],
          )
  
      def test_mecab_tokenizer_unidic_lite(self):
          try:
              tokenizer = MecabTokenizer(mecab_dic="unidic_lite")
          except ModuleNotFoundError:
              return
  
          self.assertListEqual(
              tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "),
              ["アップル", "ストア", "で", "iPhone", "8", "が", "発売", "さ", "れ", "た", "。"],
          )
  
      def test_mecab_tokenizer_unidic(self):
          try:
              tokenizer = MecabTokenizer(mecab_dic="unidic")
          except ModuleNotFoundError:
              return
  
          self.assertListEqual(
              tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "),
              ["アップル", "ストア", "で", "iPhone", "8", "が", "発売", "さ", "れ", "た", "。"],
          )
  
      def test_mecab_tokenizer_lower(self):
          tokenizer = MecabTokenizer(do_lower_case=True, mecab_dic="ipadic")
  
          self.assertListEqual(
              tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "),
              ["アップルストア", "で", "iphone", "8", "が", "発売", "さ", "れ", "た", "。"],
          )
  
      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ｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "),
              ["ｱｯﾌﾟﾙストア", "で", "iPhone", "８", "が", "発売", "さ", "れた", "\u3000", "。"],
          )
  
      def test_mecab_tokenizer_no_normalize(self):
          tokenizer = MecabTokenizer(normalize_text=False, mecab_dic="ipadic")
  
          self.assertListEqual(
              tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  "),
              ["ｱｯﾌﾟﾙストア", "で", "iPhone", "８", "が", "発売", "さ", "れ", "た", "　", "。"],
          )
  
      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
  
      def setUp(self):
          super().setUp()
  
          vocab_tokens = ["[UNK]", "[CLS]", "[SEP]", "こ", "ん", "に", "ち", "は", "ば", "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_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, ["こ", "ん", "に", "ち", "は", "、", "世", "界", "。", "こ", "ん", "ば", "ん", "は", "、", "世", "界", "。"]
          )
          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]", "こ", "ん", "に", "ち", "は", "ば", "世", "界" "、", "。"]
  
          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"), ["こ", "ん", "に", "ち", "は"])
  
          self.assertListEqual(tokenizer.tokenize("こんにちほ"), ["こ", "ん", "に", "ち", "[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]
  