



'''simple docstring'''





import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch

import multiprocess
import numpy as np
import pytest

from datasets.utils.py_utils import (
    NestedDataStructure,
    asdict,
    iflatmap_unordered,
    map_nested,
    temp_seed,
    temporary_assignment,
    zip_dict,
)

from .utils import require_tf, require_torch





def 						__snake_case(				_lowerCAmelCase		)		-> str:  # picklable for multiprocessing
      return x.sum()





def 						__snake_case(				_lowerCAmelCase		)		-> Tuple:  # picklable for multiprocessing
      return i + 1







@dataclass
class     UpperCAmelCase_       :
    """simple docstring"""







    lowercase					=		42
    lowercase					=		42







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    def lowerCamelCase       (    self					:     str						):
          snake_case__  :    int    						=      {}
          snake_case__  :    Tuple    						=      []
          snake_case__  :    Any    						=      1
          snake_case__  :    str    						=      [1, 2]
          snake_case__  :    List[str]    						=      {"""a""": 1, """b""": 2}
          snake_case__  :    List[str]    						=      {"""a""": [1, 2], """b""": [3, 4]}
          snake_case__  :    Dict    						=      {"""a""": {"""1""": 1}, """b""": 2}
          snake_case__  :    List[Any]    						=      {"""a""": 1, """b""": 2, """c""": 3, """d""": 4}
          snake_case__  :    List[str]    						=      {}
          snake_case__  :    List[str]    						=      []
          snake_case__  :    str    						=      2
          snake_case__  :    Dict    						=      [2, 3]
          snake_case__  :    List[Any]    						=      {"""a""": 2, """b""": 3}
          snake_case__  :    Dict    						=      {"""a""": [2, 3], """b""": [4, 5]}
          snake_case__  :    List[str]    						=      {"""a""": {"""1""": 2}, """b""": 3}
          snake_case__  :    List[Any]    						=      {"""a""": 2, """b""": 3, """c""": 4, """d""": 5}
          self.assertEqual(map_nested(snake_case_ ,     snake_case_						) ,     snake_case_						)
          self.assertEqual(map_nested(snake_case_ ,     snake_case_						) ,     snake_case_						)
          self.assertEqual(map_nested(snake_case_ ,     snake_case_						) ,     snake_case_						)
          self.assertEqual(map_nested(snake_case_ ,     snake_case_						) ,     snake_case_						)
          self.assertEqual(map_nested(snake_case_ ,     snake_case_						) ,     snake_case_						)
          self.assertEqual(map_nested(snake_case_ ,     snake_case_						) ,     snake_case_						)
          self.assertEqual(map_nested(snake_case_ ,     snake_case_						) ,     snake_case_						)
          self.assertEqual(map_nested(snake_case_ ,     snake_case_						) ,     snake_case_						)

          snake_case__  :    List[str]    						=      2
          self.assertEqual(map_nested(snake_case_ ,     snake_case_ ,     num_proc=snake_case_						) ,     snake_case_						)
          self.assertEqual(map_nested(snake_case_ ,     snake_case_ ,     num_proc=snake_case_						) ,     snake_case_						)
          self.assertEqual(map_nested(snake_case_ ,     snake_case_ ,     num_proc=snake_case_						) ,     snake_case_						)
          self.assertEqual(map_nested(snake_case_ ,     snake_case_ ,     num_proc=snake_case_						) ,     snake_case_						)
          self.assertEqual(map_nested(snake_case_ ,     snake_case_ ,     num_proc=snake_case_						) ,     snake_case_						)
          self.assertEqual(map_nested(snake_case_ ,     snake_case_ ,     num_proc=snake_case_						) ,     snake_case_						)
          self.assertEqual(map_nested(snake_case_ ,     snake_case_ ,     num_proc=snake_case_						) ,     snake_case_						)
          self.assertEqual(map_nested(snake_case_ ,     snake_case_ ,     num_proc=snake_case_						) ,     snake_case_						)

          snake_case__  :    Tuple    						=      {"""a""": np.eye(2						), """b""": np.zeros(3						), """c""": np.ones(2						)}
          snake_case__  :    Union[str, Any]    						=      {"""a""": 2, """b""": 0, """c""": 2}
          snake_case__  :    Optional[Any]    						=      {
              """a""": np.eye(2						).astype(snake_case_						),
              """b""": np.zeros(3						).astype(snake_case_						),
              """c""": np.ones(2						).astype(snake_case_						),
          }
          self.assertEqual(map_nested(snake_case_ ,     snake_case_ ,     map_numpy=snake_case_						) ,     snake_case_						)
          self.assertEqual(
              {k: v.tolist() for k, v in map_nested(snake_case_ ,     snake_case_ ,     map_numpy=snake_case_						).items()} ,     {k: v.tolist() for k, v in expected_map_nested_sna_int.items()} ,     )
          self.assertEqual(map_nested(snake_case_ ,     snake_case_ ,     map_numpy=snake_case_ ,     num_proc=snake_case_						) ,     snake_case_						)
          self.assertEqual(
              {k: v.tolist() for k, v in map_nested(snake_case_ ,     snake_case_ ,     map_numpy=snake_case_ ,     num_proc=snake_case_						).items()} ,     {k: v.tolist() for k, v in expected_map_nested_sna_int.items()} ,     )
          with self.assertRaises(snake_case_						):  # can't pickle a local lambda
                map_nested(lambda snake_case_						: x + 1 ,     snake_case_ ,     num_proc=snake_case_						)




    def lowerCamelCase       (    self					:     int						):
          snake_case__  :    Tuple    						=      {"""a""": 1, """b""": 2}
          snake_case__  :    Dict    						=      {"""a""": 3, """b""": 4}
          snake_case__  :    List[str]    						=      {"""a""": 5, """b""": 6}
          snake_case__  :    Tuple    						=      sorted([("""a""", (1, 3, 5)), ("""b""", (2, 4, 6))]						)
          self.assertEqual(sorted(zip_dict(snake_case_ ,     snake_case_ ,     snake_case_						)						) ,     snake_case_						)




    def lowerCamelCase       (    self					:     int						):







          class     UpperCAmelCase_       :
              """simple docstring"""







              lowercase					=		"bar"
          snake_case__  :    Tuple    						=      Foo()
          self.assertEqual(foo.my_attr ,     """bar"""						)
          with temporary_assignment(snake_case_ ,     """my_attr""" ,     """BAR"""						):
                self.assertEqual(foo.my_attr ,     """BAR"""						)
          self.assertEqual(foo.my_attr ,     """bar"""						)





@pytest.mark.parametrize(
    """iterable_length, num_proc, expected_num_proc"""     ,   [
        (1, None, 1),
        (1, 1, 1),
        (2, None, 1),
        (2, 1, 1),
        (2, 2, 1),
        (2, 3, 1),
        (3, 2, 1),
        (16, 16, 16),
        (16, 17, 16),
        (17, 16, 16),
    ]     ,   )
def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase     ,   _lowerCAmelCase		)		-> Optional[int]:
      with patch("""datasets.utils.py_utils._single_map_nested"""		) as mock_single_map_nested, patch(
          """datasets.parallel.parallel.Pool"""		) as mock_multiprocessing_pool:
            snake_case__  :    Union[str, Any]    						=      {f"{i}": i for i in range(_lowerCAmelCase		)}
            snake_case__  :    int    						=      map_nested(lambda _lowerCAmelCase		: x + 10     ,   _lowerCAmelCase     ,   num_proc=_lowerCAmelCase     ,   parallel_min_length=16		)
            if expected_num_proc == 1:
                  assert mock_single_map_nested.called
                  assert not mock_multiprocessing_pool.called
            else:
                  assert not mock_single_map_nested.called
                  assert mock_multiprocessing_pool.called
                  assert mock_multiprocessing_pool.call_args[0][0] == expected_num_proc







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    @require_tf
    def lowerCamelCase       (    self					:     Optional[int]						):
          import tensorflow as tf
          from tensorflow.keras import layers

          snake_case__  :    Tuple    						=      layers.Dense(2						)

          def gen_random_output():
                snake_case__  :    Union[str, Any]    						=      tf.random.uniform((1, 3)						)
                return model(snake_case_						).numpy()

          with temp_seed(42 ,     set_tensorflow=snake_case_						):
                snake_case__  :    List[Any]    						=      gen_random_output()
          with temp_seed(42 ,     set_tensorflow=snake_case_						):
                snake_case__  :    List[str]    						=      gen_random_output()
          snake_case__  :    Any    						=      gen_random_output()

          np.testing.assert_equal(snake_case_ ,     snake_case_						)
          self.assertGreater(np.abs(outa - outa						).sum() ,     0						)




    @require_torch
    def lowerCamelCase       (    self					:     Union[str, Any]						):
          import torch

          def gen_random_output():
                snake_case__  :    List[str]    						=      torch.nn.Linear(3 ,     2						)
                snake_case__  :    Tuple    						=      torch.rand(1 ,     3						)
                return model(snake_case_						).detach().numpy()

          with temp_seed(42 ,     set_pytorch=snake_case_						):
                snake_case__  :    List[str]    						=      gen_random_output()
          with temp_seed(42 ,     set_pytorch=snake_case_						):
                snake_case__  :    List[str]    						=      gen_random_output()
          snake_case__  :    List[str]    						=      gen_random_output()

          np.testing.assert_equal(snake_case_ ,     snake_case_						)
          self.assertGreater(np.abs(outa - outa						).sum() ,     0						)




    def lowerCamelCase       (    self					:     Optional[Any]						):
          def gen_random_output():
                return np.random.rand(1 ,     3						)

          with temp_seed(42						):
                snake_case__  :    Union[str, Any]    						=      gen_random_output()
          with temp_seed(42						):
                snake_case__  :    List[str]    						=      gen_random_output()
          snake_case__  :    Optional[int]    						=      gen_random_output()

          np.testing.assert_equal(snake_case_ ,     snake_case_						)
          self.assertGreater(np.abs(outa - outa						).sum() ,     0						)





@pytest.mark.parametrize("""input_data"""     ,   [{}]		)
def 						__snake_case(				_lowerCAmelCase		)		-> Union[str, Any]:
      snake_case__  :    Any    						=      NestedDataStructure(_lowerCAmelCase		).data
      assert output_data == input_data





@pytest.mark.parametrize(
    """data, expected_output"""     ,   [
        ({}, []),
        ([], []),
        ("""foo""", ["""foo"""]),
        (["""foo""", """bar"""], ["""foo""", """bar"""]),
        ([["""foo""", """bar"""]], ["""foo""", """bar"""]),
        ([[["""foo"""], ["""bar"""]]], ["""foo""", """bar"""]),
        ([[["""foo"""], """bar"""]], ["""foo""", """bar"""]),
        ({"""a""": 1, """b""": 2}, [1, 2]),
        ({"""a""": [1, 2], """b""": [3, 4]}, [1, 2, 3, 4]),
        ({"""a""": [[1, 2]], """b""": [[3, 4]]}, [1, 2, 3, 4]),
        ({"""a""": [[1, 2]], """b""": [3, 4]}, [1, 2, 3, 4]),
        ({"""a""": [[[1], [2]]], """b""": [[[3], [4]]]}, [1, 2, 3, 4]),
        ({"""a""": [[[1], [2]]], """b""": [[3, 4]]}, [1, 2, 3, 4]),
        ({"""a""": [[[1], [2]]], """b""": [3, 4]}, [1, 2, 3, 4]),
        ({"""a""": [[[1], [2]]], """b""": [3, [4]]}, [1, 2, 3, 4]),
        ({"""a""": {"""1""": 1}, """b""": 2}, [1, 2]),
        ({"""a""": {"""1""": [1]}, """b""": 2}, [1, 2]),
        ({"""a""": {"""1""": [1]}, """b""": [2]}, [1, 2]),
    ]     ,   )
def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase		)		-> Union[str, Any]:
      snake_case__  :    Dict    						=      NestedDataStructure(_lowerCAmelCase		).flatten()
      assert output == expected_output





def 						__snake_case(				)		-> Any:
      snake_case__  :    Optional[int]    						=      A(x=1     ,   y="""foobar"""		)
      snake_case__  :    Any    						=      {"""x""": 1, """y""": """foobar"""}
      assert asdict(_lowerCAmelCase		) == expected_output

      snake_case__  :    str    						=      {"""a""": {"""b""": A(x=10     ,   y="""foo"""		)}, """c""": [A(x=20     ,   y="""bar"""		)]}
      snake_case__  :    Optional[int]    						=      {"""a""": {"""b""": {"""x""": 10, """y""": """foo"""}}, """c""": [{"""x""": 20, """y""": """bar"""}]}
      assert asdict(_lowerCAmelCase		) == expected_output

      with pytest.raises(_lowerCAmelCase		):
            asdict([1, A(x=10     ,   y="""foo"""		)]		)





def 						__snake_case(				_lowerCAmelCase		)		-> Optional[int]:
      return text.split()





def 						__snake_case(				_lowerCAmelCase		)		-> Optional[int]:
      yield (time.time(), content)
      time.sleep(2		)
      yield (time.time(), content)





def 						__snake_case(				)		-> Optional[Any]:
      with Pool(2		) as pool:
            snake_case__  :    Tuple    						=      list(iflatmap_unordered(_lowerCAmelCase     ,   _split_text     ,   kwargs_iterable=[{"""text""": """hello there"""}] * 10		)		)
            assert out.count("""hello"""		) == 10
            assert out.count("""there"""		) == 10
            assert len(_lowerCAmelCase		) == 20

      # check multiprocess from pathos (uses dill for pickling)
      with multiprocess.Pool(2		) as pool:
            snake_case__  :    Optional[Any]    						=      list(iflatmap_unordered(_lowerCAmelCase     ,   _split_text     ,   kwargs_iterable=[{"""text""": """hello there"""}] * 10		)		)
            assert out.count("""hello"""		) == 10
            assert out.count("""there"""		) == 10
            assert len(_lowerCAmelCase		) == 20

      # check that we get items as fast as possible
      with Pool(2		) as pool:
            snake_case__  :    str    						=      []
            for yield_time, content in iflatmap_unordered(
                _lowerCAmelCase     ,   _aseconds_generator_of_aitems_with_timing     ,   kwargs_iterable=[{"""content""": """a"""}, {"""content""": """b"""}]		):
                  assert yield_time < time.time() + 0.1, "we should each item directly after it was yielded"
                  out.append(_lowerCAmelCase		)
            assert out.count("""a"""		) == 2
            assert out.count("""b"""		) == 2
            assert len(_lowerCAmelCase		) == 4





'''simple docstring'''





import json
import os
import unittest

from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
    VOCAB_FILES_NAMES,
    GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class     UpperCAmelCase_       (       _a		,		unittest.TestCase	):
    """simple docstring"""







    lowercase					=		GPTSanJapaneseTokenizer
    lowercase					=		False
    lowercase					=		{"do_clean_text": False, "add_prefix_space": False}




    def lowerCamelCase       (    self					:     str						):
          super().setUp()

          # fmt: off
          snake_case__  :    Optional[Any]    						=      ["""こん""", """こんに""", """にちは""", """ばんは""", """世界,㔺界""", """、""", """。""", """<BR>""", """<SP>""", """<TAB>""", """<URL>""", """<EMAIL>""", """<TEL>""", """<DATE>""", """<PRICE>""", """<BLOCK>""", """<KIGOU>""", """<U2000U2BFF>""", """<|emoji1|>""", """<unk>""", """<|bagoftoken|>""", """<|endoftext|>"""]
          # fmt: on
          snake_case__  :    int    						=      {"""emoji""": {"""\ud83d\ude00""": """<|emoji1|>"""}, """emoji_inv""": {"""<|emoji1|>""": """\ud83d\ude00"""}}  # 😀
          snake_case__  :    List[Any]    						=      {"""unk_token""": """<unk>"""}

          snake_case__  :    Optional[Any]    						=      os.path.join(self.tmpdirname ,     VOCAB_FILES_NAMES["""vocab_file"""]						)
          snake_case__  :    Dict    						=      os.path.join(self.tmpdirname ,     VOCAB_FILES_NAMES["""emoji_file"""]						)
          with open(self.vocab_file ,     """w""" ,     encoding="""utf-8"""						) as vocab_writer:
                vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]						)						)
          with open(self.emoji_file ,     """w"""						) as emoji_writer:
                emoji_writer.write(json.dumps(snake_case_						)						)




    def lowerCamelCase       (    self					:     Any ,     **snake_case_					:     Union[str, Any]						):
          kwargs.update(self.special_tokens_map						)
          return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname ,     **snake_case_						)




    def lowerCamelCase       (    self					:     Any ,     snake_case_					:     str						):
          snake_case__  :    Union[str, Any]    						=      """こんにちは、世界。 \nこんばんは、㔺界。😀"""
          snake_case__  :    List[str]    						=      """こんにちは、世界。 \nこんばんは、世界。😀"""
          return input_text, output_text




    def lowerCamelCase       (    self					:     Any ,     snake_case_					:     Dict						):
          snake_case__						,				snake_case__  :    int    						=      self.get_input_output_texts(snake_case_						)
          snake_case__  :    int    						=      tokenizer.encode(snake_case_ ,     add_special_tokens=snake_case_						)
          snake_case__  :    List[str]    						=      tokenizer.decode(snake_case_ ,     clean_up_tokenization_spaces=snake_case_						)
          return text, ids




    def lowerCamelCase       (    self					:     Optional[Any]						):
          pass  # TODO add if relevant




    def lowerCamelCase       (    self					:     Union[str, Any]						):
          pass  # TODO add if relevant




    def lowerCamelCase       (    self					:     List[str]						):
          pass  # TODO add if relevant




    def lowerCamelCase       (    self					:     Dict						):
          snake_case__  :    Optional[Any]    						=      self.get_tokenizer()

          # Testing tokenization
          snake_case__  :    int    						=      """こんにちは、世界。　こんばんは、㔺界。"""
          snake_case__  :    Optional[int]    						=      ["""こん""", """にちは""", """、""", """世界""", """。""", """<SP>""", """こん""", """ばんは""", """、""", """㔺界""", """。"""]
          snake_case__  :    Dict    						=      tokenizer.tokenize(snake_case_						)
          self.assertListEqual(snake_case_ ,     snake_case_						)

          # Testing conversion to ids without special tokens
          snake_case__  :    Union[str, Any]    						=      [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
          snake_case__  :    List[Any]    						=      tokenizer.convert_tokens_to_ids(snake_case_						)
          self.assertListEqual(snake_case_ ,     snake_case_						)

          # Testing conversion to ids with special tokens
          snake_case__  :    Union[str, Any]    						=      tokens + [tokenizer.unk_token]
          snake_case__  :    Dict    						=      [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
          snake_case__  :    Any    						=      tokenizer.convert_tokens_to_ids(snake_case_						)
          self.assertListEqual(snake_case_ ,     snake_case_						)




    def lowerCamelCase       (    self					:     Optional[Any]						):
          snake_case__  :    Union[str, Any]    						=      self.get_tokenizer()

          # Testing tokenization
          snake_case__  :    Union[str, Any]    						=      """こんにちは、<|bagoftoken|>世界。こんばんは、<|bagoftoken|>㔺界。"""
          snake_case__  :    Optional[int]    						=      """こんにちは、、、、世界。こんばんは、、、、世界。"""
          snake_case__  :    Any    						=      tokenizer.encode(snake_case_						)
          snake_case__  :    int    						=      tokenizer.decode(snake_case_						)
          self.assertEqual(snake_case_ ,     snake_case_						)




    @slow
    def lowerCamelCase       (    self					:     Union[str, Any]						):
          snake_case__  :    Optional[Any]    						=      self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""						)

          # Testing tokenization
          snake_case__  :    Tuple    						=      """こんにちは、世界。"""
          snake_case__  :    Optional[Any]    						=      """こんばんは、㔺界。😀"""
          snake_case__  :    List[str]    						=      """こんにちは、世界。こんばんは、世界。😀"""
          snake_case__  :    Dict    						=      tokenizer.encode(prefix_text + input_text						)
          snake_case__  :    Dict    						=      tokenizer.encode("""""" ,     prefix_text=prefix_text + input_text						)
          snake_case__  :    int    						=      tokenizer.encode(snake_case_ ,     prefix_text=snake_case_						)
          snake_case__  :    Optional[Any]    						=      tokenizer.decode(snake_case_						)
          snake_case__  :    Union[str, Any]    						=      tokenizer.decode(snake_case_						)
          snake_case__  :    str    						=      tokenizer.decode(snake_case_						)
          self.assertEqual(snake_case_ ,     snake_case_						)
          self.assertEqual(snake_case_ ,     snake_case_						)
          self.assertEqual(snake_case_ ,     snake_case_						)




    @slow
    def lowerCamelCase       (    self					:     Union[str, Any]						):
          snake_case__  :    Optional[Any]    						=      self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""						)

          # Testing tokenization
          snake_case__  :    Dict    						=      """こんにちは、世界。"""
          snake_case__  :    Optional[int]    						=      """こんばんは、㔺界。😀"""

          snake_case__  :    Any    						=      len(tokenizer.encode(snake_case_						)						) - 2
          snake_case__  :    Optional[int]    						=      len(tokenizer.encode(snake_case_						)						) - 2

          snake_case__  :    List[str]    						=      [1] + [0] * (len_prefix + len_text + 1)
          snake_case__  :    Optional[int]    						=      [1] * (len_prefix + len_text + 1) + [0]
          snake_case__  :    int    						=      [1] + [1] * (len_prefix) + [0] * (len_text + 1)

          snake_case__  :    Any    						=      tokenizer(prefix_text + input_text						).token_type_ids
          snake_case__  :    str    						=      tokenizer("""""" ,     prefix_text=prefix_text + input_text						).token_type_ids
          snake_case__  :    Optional[Any]    						=      tokenizer(snake_case_ ,     prefix_text=snake_case_						).token_type_ids
          self.assertListEqual(snake_case_ ,     snake_case_						)
          self.assertListEqual(snake_case_ ,     snake_case_						)
          self.assertListEqual(snake_case_ ,     snake_case_						)




    @slow
    def lowerCamelCase       (    self					:     Optional[int]						):
          snake_case__  :    Optional[Any]    						=      self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""						)

          snake_case__  :    Union[str, Any]    						=      tokenizer.encode("""あンいワ"""						)
          snake_case__  :    int    						=      tokenizer.encode("""""" ,     prefix_text="""あンいワ"""						)
          snake_case__  :    Dict    						=      tokenizer.encode("""いワ""" ,     prefix_text="""あン"""						)

          self.assertEqual(tokenizer.decode(snake_case_						) ,     tokenizer.decode(snake_case_						)						)
          self.assertEqual(tokenizer.decode(snake_case_						) ,     tokenizer.decode(snake_case_						)						)
          self.assertNotEqual(snake_case_ ,     snake_case_						)
          self.assertNotEqual(snake_case_ ,     snake_case_						)
          self.assertEqual(x_token_a[1] ,     x_token_a[-1]						)  # SEG token
          self.assertEqual(x_token_a[1] ,     x_token_a[3]						)  # SEG token




    @slow
    def lowerCamelCase       (    self					:     Any						):
          snake_case__  :    Optional[int]    						=      self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""						)

          snake_case__  :    int    						=      [["""武田信玄""", """は、"""], ["""織田信長""", """の配下の、"""]]
          snake_case__  :    Optional[Any]    						=      tokenizer(snake_case_ ,     padding=snake_case_						)
          snake_case__  :    Tuple    						=      tokenizer.batch_encode_plus(snake_case_ ,     padding=snake_case_						)

          # fmt: off
          snake_case__  :    Optional[Any]    						=      [[35_993, 8_640, 25_948, 35_998, 30_647, 35_675, 35_999, 35_999], [35_993, 10_382, 9_868, 35_998, 30_646, 9_459, 30_646, 35_675]]
          snake_case__  :    Optional[Any]    						=      [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
          snake_case__  :    Optional[Any]    						=      [[1, 1, 1, 1, 1, 1, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1]]
          # fmt: on
          self.assertListEqual(x_token.input_ids ,     snake_case_						)
          self.assertListEqual(x_token.token_type_ids ,     snake_case_						)
          self.assertListEqual(x_token.attention_mask ,     snake_case_						)
          self.assertListEqual(x_token_a.input_ids ,     snake_case_						)
          self.assertListEqual(x_token_a.token_type_ids ,     snake_case_						)
          self.assertListEqual(x_token_a.attention_mask ,     snake_case_						)




    def lowerCamelCase       (    self					:     Any						):
          # Intentionally convert some words to accommodate character fluctuations unique to Japanese
          pass




    def lowerCamelCase       (    self					:     List[str]						):
          # tokenizer has no padding token
          pass
