'''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 			__lowercase		(						_lowerCamelCase			,							unittest.TestCase						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						GPTSanJapaneseTokenizer
     SCREAMING_SNAKE_CASE__		   =						False
     SCREAMING_SNAKE_CASE__		   =						{'''do_clean_text''': False, '''add_prefix_space''': False}







     def lowerCAmelCase     (		self    ):
         super().setUp()

         # fmt: off
         __UpperCamelCase	:	Union[str, 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
         __UpperCamelCase	:	List[Any]		    =  {'emoji': {'\ud83d\ude00': '<|emoji1|>'}, 'emoji_inv': {'<|emoji1|>': '\ud83d\ude00'}}  # 😀
         __UpperCamelCase	:	Optional[Any]		    =  {'unk_token': '<unk>'}

         __UpperCamelCase	:	Any		    =  os.path.join(self.tmpdirname     ,			VOCAB_FILES_NAMES['vocab_file']    )
         __UpperCamelCase	:	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(_lowerCamelCase    )    )







     def lowerCAmelCase     (		self     ,			**_lowerCamelCase    ):
         kwargs.update(self.special_tokens_map    )
         return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname     ,			**_lowerCamelCase    )







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         __UpperCamelCase	:	int		    =  'こんにちは、世界。 \nこんばんは、㔺界。😀'
         __UpperCamelCase	:	List[Any]		    =  'こんにちは、世界。 \nこんばんは、世界。😀'
         return input_text, output_text







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         __UpperCamelCase	:	Any		    =  self.get_input_output_texts(_lowerCamelCase    )
         __UpperCamelCase	:	List[Any]		    =  tokenizer.encode(_lowerCamelCase     ,			add_special_tokens=_lowerCamelCase    )
         __UpperCamelCase	:	Any		    =  tokenizer.decode(_lowerCamelCase     ,			clean_up_tokenization_spaces=_lowerCamelCase    )
         return text, ids







     def lowerCAmelCase     (		self    ):
         pass  # TODO add if relevant







     def lowerCAmelCase     (		self    ):
         pass  # TODO add if relevant







     def lowerCAmelCase     (		self    ):
         pass  # TODO add if relevant







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Union[str, Any]		    =  self.get_tokenizer()

         # Testing tokenization
         __UpperCamelCase	:	Any		    =  'こんにちは、世界。　こんばんは、㔺界。'
         __UpperCamelCase	:	str		    =  ['こん', 'にちは', '、', '世界', '。', '<SP>', 'こん', 'ばんは', '、', '㔺界', '。']
         __UpperCamelCase	:	int		    =  tokenizer.tokenize(_lowerCamelCase    )
         self.assertListEqual(_lowerCamelCase     ,			_lowerCamelCase    )

         # Testing conversion to ids without special tokens
         __UpperCamelCase	:	Tuple		    =  [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
         __UpperCamelCase	:	Optional[Any]		    =  tokenizer.convert_tokens_to_ids(_lowerCamelCase    )
         self.assertListEqual(_lowerCamelCase     ,			_lowerCamelCase    )

         # Testing conversion to ids with special tokens
         __UpperCamelCase	:	Optional[Any]		    =  tokens + [tokenizer.unk_token]
         __UpperCamelCase	:	Union[str, Any]		    =  [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 1_9]
         __UpperCamelCase	:	Optional[Any]		    =  tokenizer.convert_tokens_to_ids(_lowerCamelCase    )
         self.assertListEqual(_lowerCamelCase     ,			_lowerCamelCase    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Any		    =  self.get_tokenizer()

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







     @slow
     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	List[str]		    =  self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'    )

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







     @slow
     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	List[Any]		    =  self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'    )

         # Testing tokenization
         __UpperCamelCase	:	Union[str, Any]		    =  'こんにちは、世界。'
         __UpperCamelCase	:	str		    =  'こんばんは、㔺界。😀'

         __UpperCamelCase	:	Optional[Any]		    =  len(tokenizer.encode(_lowerCamelCase    )    ) - 2
         __UpperCamelCase	:	Optional[int]		    =  len(tokenizer.encode(_lowerCamelCase    )    ) - 2

         __UpperCamelCase	:	int		    =  [1] + [0] * (len_prefix + len_text + 1)
         __UpperCamelCase	:	Union[str, Any]		    =  [1] * (len_prefix + len_text + 1) + [0]
         __UpperCamelCase	:	Dict		    =  [1] + [1] * (len_prefix) + [0] * (len_text + 1)

         __UpperCamelCase	:	Optional[int]		    =  tokenizer(prefix_text + input_text    ).token_type_ids
         __UpperCamelCase	:	List[Any]		    =  tokenizer(''     ,			prefix_text=prefix_text + input_text    ).token_type_ids
         __UpperCamelCase	:	List[str]		    =  tokenizer(_lowerCamelCase     ,			prefix_text=_lowerCamelCase    ).token_type_ids
         self.assertListEqual(_lowerCamelCase     ,			_lowerCamelCase    )
         self.assertListEqual(_lowerCamelCase     ,			_lowerCamelCase    )
         self.assertListEqual(_lowerCamelCase     ,			_lowerCamelCase    )







     @slow
     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	List[str]		    =  self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'    )

         __UpperCamelCase	:	str		    =  tokenizer.encode('あンいワ'    )
         __UpperCamelCase	:	str		    =  tokenizer.encode(''     ,			prefix_text='あンいワ'    )
         __UpperCamelCase	:	List[Any]		    =  tokenizer.encode('いワ'     ,			prefix_text='あン'    )

         self.assertEqual(tokenizer.decode(_lowerCamelCase    )     ,			tokenizer.decode(_lowerCamelCase    )    )
         self.assertEqual(tokenizer.decode(_lowerCamelCase    )     ,			tokenizer.decode(_lowerCamelCase    )    )
         self.assertNotEqual(_lowerCamelCase     ,			_lowerCamelCase    )
         self.assertNotEqual(_lowerCamelCase     ,			_lowerCamelCase    )
         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    ):
         __UpperCamelCase	:	Any		    =  self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'    )

         __UpperCamelCase	:	Optional[Any]		    =  [['武田信玄', 'は、'], ['織田信長', 'の配下の、']]
         __UpperCamelCase	:	Any		    =  tokenizer(_lowerCamelCase     ,			padding=_lowerCamelCase    )
         __UpperCamelCase	:	int		    =  tokenizer.batch_encode_plus(_lowerCamelCase     ,			padding=_lowerCamelCase    )

         # fmt: off
         __UpperCamelCase	:	int		    =  [[3_5_9_9_3, 8_6_4_0, 2_5_9_4_8, 3_5_9_9_8, 3_0_6_4_7, 3_5_6_7_5, 3_5_9_9_9, 3_5_9_9_9], [3_5_9_9_3, 1_0_3_8_2, 9_8_6_8, 3_5_9_9_8, 3_0_6_4_6, 9_4_5_9, 3_0_6_4_6, 3_5_6_7_5]]
         __UpperCamelCase	:	Union[str, Any]		    =  [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
         __UpperCamelCase	:	str		    =  [[1, 1, 1, 1, 1, 1, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1]]
         # fmt: on
         self.assertListEqual(x_token.input_ids     ,			_lowerCamelCase    )
         self.assertListEqual(x_token.token_type_ids     ,			_lowerCamelCase    )
         self.assertListEqual(x_token.attention_mask     ,			_lowerCamelCase    )
         self.assertListEqual(x_token_a.input_ids     ,			_lowerCamelCase    )
         self.assertListEqual(x_token_a.token_type_ids     ,			_lowerCamelCase    )
         self.assertListEqual(x_token_a.attention_mask     ,			_lowerCamelCase    )







     def lowerCAmelCase     (		self    ):
         pass







     def lowerCAmelCase     (		self    ):
         pass




'''simple docstring'''
from timeit import timeit

a=  {
    '''MALAYALAM''': True,
    '''String''': False,
    '''rotor''': True,
    '''level''': True,
    '''A''': True,
    '''BB''': True,
    '''ABC''': False,
    '''amanaplanacanalpanama''': True,  # "a man a plan a canal panama"
}
# Ensure our test data is valid
assert all((key == key[::-1]) is value for key, value in test_data.items())







def  _UpperCamelCase (     _a	:	str			):




    """simple docstring"""



    __UpperCamelCase	:	int		    =  0
    __UpperCamelCase	:	str		    =  len(_a			) - 1
    while start_i < end_i:
        if s[start_i] == s[end_i]:
            start_i += 1
            end_i -= 1
        else:
            return False
    return True







def  _UpperCamelCase (     _a	:	str			):




    """simple docstring"""



    __UpperCamelCase	:	Optional[Any]		    =  len(_a			) // 2
    __UpperCamelCase	:	Tuple		    =  len(_a			)

    # We need to traverse till half of the length of string
    # as we can get access of the i'th last element from
    # i'th index.
    # eg: [0,1,2,3,4,5] => 4th index can be accessed
    # with the help of 1st index (i==n-i-1)
    # where n is length of string
    return all(s[i] == s[n - i - 1] for i in range(_a			)			)







def  _UpperCamelCase (     _a	:	str			):




    """simple docstring"""



    if len(_a			) <= 2:
        return True
    if s[0] == s[len(_a			) - 1]:
        return is_palindrome_recursive(s[1:-1]			)
    else:
        return False







def  _UpperCamelCase (     _a	:	str			):




    """simple docstring"""



    return s == s[::-1]







def  _UpperCamelCase (     _a	:	str			):




    """simple docstring"""



    __UpperCamelCase	:	int		    =  f"""all({name}(key) is value for key, value in test_data.items())"""
    __UpperCamelCase	:	Union[str, Any]		    =  f"""from __main__ import test_data, {name}"""
    __UpperCamelCase	:	Any		    =  5_0_0_0_0_0
    __UpperCamelCase	:	Tuple		    =  timeit(stmt=_a				,     setup=_a				,     number=_a			)
    print(f"""{name:<35} finished {number:,} runs in {result:.5f} seconds"""			)


if __name__ == "__main__":
  for key, value in test_data.items():
    assert is_palindrome(key) is is_palindrome_recursive(key)
    assert is_palindrome(key) is is_palindrome_slice(key)
    print(F"""{key:21} {value}""")
  print('''a man a plan a canal panama''')

  # finished 500,000 runs in 0.46793 seconds
  benchmark_function('''is_palindrome_slice''')
  # finished 500,000 runs in 0.85234 seconds
  benchmark_function('''is_palindrome''')
  # finished 500,000 runs in 1.32028 seconds
  benchmark_function('''is_palindrome_recursive''')
  # finished 500,000 runs in 2.08679 seconds
  benchmark_function('''is_palindrome_traversal''')



