





from __future__ import annotations

from typing import TypedDict



class    _SCREAMING_SNAKE_CASE						(	__SCREAMING_SNAKE_CASE    ):







 '''simple docstring'''
 lowercase_		=			42
 lowercase_		=			42





def      lowerCAmelCase_ (       __a		)     ->		list[str]:







  """simple docstring"""





  if not isinstance(__a	,    __a		):
    raise TypeError("The parameter s type must be str."		)

  return [s[i:] + s[:i] for i in range(len(__a		)		)]





def      lowerCAmelCase_ (       __a		)     ->		BWTTransformDict:







  """simple docstring"""





  if not isinstance(__a	,    __a		):
    raise TypeError("The parameter s type must be str."		)
  if not s:
    raise ValueError("The parameter s must not be empty."		)

  lowerCamelCase__:      int			  =all_rotations(__a		)
  rotations.sort()  # sort the list of rotations in alphabetically order
  # make a string composed of the last char of each rotation
  lowerCamelCase__:      BWTTransformDict			  ={
      "bwt_string": "".join([word[-1] for word in rotations]		),
      "idx_original_string": rotations.index(__a		),
  }
  return response





def      lowerCAmelCase_ (       __a	,    __a		)     ->		str:







  """simple docstring"""





  if not isinstance(__a	,    __a		):
    raise TypeError("The parameter bwt_string type must be str."		)
  if not bwt_string:
    raise ValueError("The parameter bwt_string must not be empty."		)
  try:
    lowerCamelCase__:      Tuple			  =int(__a		)
  except ValueError:
    raise TypeError(
        "The parameter idx_original_string type must be int or passive"
        " of cast to int."		)
  if idx_original_string < 0:
    raise ValueError("The parameter idx_original_string must not be lower than 0."		)
  if idx_original_string >= len(__a		):
    raise ValueError(
        "The parameter idx_original_string must be lower than" " len(bwt_string)."		)

  lowerCamelCase__:      List[str]			  =[""] * len(__a		)
  for _ in range(len(__a		)		):
    for i in range(len(__a		)		):
      lowerCamelCase__:      List[str]			  =bwt_string[i] + ordered_rotations[i]
    ordered_rotations.sort()
  return ordered_rotations[idx_original_string]


if __name__ == "__main__":
     __A									=				"Provide a string that I will generate its BWT transform: "
     __A									=				input(entry_msg).strip()
     __A									=				bwt_transform(s)
     print(
         f'Burrows Wheeler transform for string \'{s}\' results '
         f'in \'{result["bwt_string"]}\''
     )
     __A									=				reverse_bwt(result["bwt_string"], result["idx_original_string"])
     print(
         f'Reversing Burrows Wheeler transform for entry \'{result["bwt_string"]}\' '
         f'we get original string \'{original_string}\''
     )





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  SCREAMING_SNAKE_CASE__  (				lowercase__						,    unittest.TestCase			):
      snake_case__				:     Any        =						GPTSanJapaneseTokenizer
      snake_case__				:     Tuple        =						False
      snake_case__				:     str        =						{'''do_clean_text''': False, '''add_prefix_space''': False}
      def        SCREAMING_SNAKE_CASE							(       self				:       List[Any]     )		->			str:
             super().setUp()

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

             a_					:		Any							=  os.path.join(self.tmpdirname     ,							VOCAB_FILES_NAMES['vocab_file']     )
             a_					:		List[str]							=  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(SCREAMING_SNAKE_CASE__     )     )
      def        SCREAMING_SNAKE_CASE							(       self				:       List[str]     ,							**SCREAMING_SNAKE_CASE__				:       Tuple     )		->			int:
             kwargs.update(self.special_tokens_map     )
             return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname     ,							**SCREAMING_SNAKE_CASE__     )
      def        SCREAMING_SNAKE_CASE							(       self				:       Dict     ,							SCREAMING_SNAKE_CASE__				:       Union[str, Any]     )		->			int:
             a_					:		Optional[int]							=  'こんにちは、世界。 \nこんばんは、㔺界。😀'
             a_					:		List[str]							=  'こんにちは、世界。 \nこんばんは、世界。😀'
             return input_text, output_text
      def        SCREAMING_SNAKE_CASE							(       self				:       str     ,							SCREAMING_SNAKE_CASE__				:       int     )		->			Dict:
             a_							,		a_					:		Union[str, Any]							=  self.get_input_output_texts(SCREAMING_SNAKE_CASE__     )
             a_					:		List[Any]							=  tokenizer.encode(SCREAMING_SNAKE_CASE__     ,							add_special_tokens=SCREAMING_SNAKE_CASE__     )
             a_					:		Dict							=  tokenizer.decode(SCREAMING_SNAKE_CASE__     ,							clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE__     )
             return text, ids
      def        SCREAMING_SNAKE_CASE							(       self				:       Dict     )		->			int:
             pass  # TODO add if relevant
      def        SCREAMING_SNAKE_CASE							(       self				:       Dict     )		->			Any:
             pass  # TODO add if relevant
      def        SCREAMING_SNAKE_CASE							(       self				:       Any     )		->			Tuple:
             pass  # TODO add if relevant
      def        SCREAMING_SNAKE_CASE							(       self				:       Dict     )		->			List[str]:
             a_					:		List[str]							=  self.get_tokenizer()

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

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

             # Testing conversion to ids with special tokens
             a_					:		int							=  tokens + [tokenizer.unk_token]
             a_					:		int							=  [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 1_9]
             a_					:		Tuple							=  tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__     )
             self.assertListEqual(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
      def        SCREAMING_SNAKE_CASE							(       self				:       List[str]     )		->			Dict:
             a_					:		Union[str, Any]							=  self.get_tokenizer()

             # Testing tokenization
             a_					:		Dict							=  'こんにちは、<|bagoftoken|>世界。こんばんは、<|bagoftoken|>㔺界。'
             a_					:		List[Any]							=  'こんにちは、、、、世界。こんばんは、、、、世界。'
             a_					:		Any							=  tokenizer.encode(SCREAMING_SNAKE_CASE__     )
             a_					:		Optional[Any]							=  tokenizer.decode(SCREAMING_SNAKE_CASE__     )
             self.assertEqual(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
      @slow
      def        SCREAMING_SNAKE_CASE							(       self				:       str     )		->			Dict:
             a_					:		Tuple							=  self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'     )

             # Testing tokenization
             a_					:		List[Any]							=  'こんにちは、世界。'
             a_					:		int							=  'こんばんは、㔺界。😀'
             a_					:		Dict							=  'こんにちは、世界。こんばんは、世界。😀'
             a_					:		Optional[int]							=  tokenizer.encode(prefix_text + input_text     )
             a_					:		Any							=  tokenizer.encode(''     ,							prefix_text=prefix_text + input_text     )
             a_					:		Union[str, Any]							=  tokenizer.encode(SCREAMING_SNAKE_CASE__     ,							prefix_text=SCREAMING_SNAKE_CASE__     )
             a_					:		List[Any]							=  tokenizer.decode(SCREAMING_SNAKE_CASE__     )
             a_					:		Tuple							=  tokenizer.decode(SCREAMING_SNAKE_CASE__     )
             a_					:		str							=  tokenizer.decode(SCREAMING_SNAKE_CASE__     )
             self.assertEqual(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
             self.assertEqual(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
             self.assertEqual(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
      @slow
      def        SCREAMING_SNAKE_CASE							(       self				:       Optional[int]     )		->			Optional[int]:
             a_					:		Tuple							=  self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'     )

             # Testing tokenization
             a_					:		str							=  'こんにちは、世界。'
             a_					:		List[str]							=  'こんばんは、㔺界。😀'

             a_					:		str							=  len(tokenizer.encode(SCREAMING_SNAKE_CASE__     )     ) - 2
             a_					:		Tuple							=  len(tokenizer.encode(SCREAMING_SNAKE_CASE__     )     ) - 2

             a_					:		Optional[Any]							=  [1] + [0] * (len_prefix + len_text + 1)
             a_					:		Optional[Any]							=  [1] * (len_prefix + len_text + 1) + [0]
             a_					:		Tuple							=  [1] + [1] * (len_prefix) + [0] * (len_text + 1)

             a_					:		List[str]							=  tokenizer(prefix_text + input_text     ).token_type_ids
             a_					:		Union[str, Any]							=  tokenizer(''     ,							prefix_text=prefix_text + input_text     ).token_type_ids
             a_					:		Any							=  tokenizer(SCREAMING_SNAKE_CASE__     ,							prefix_text=SCREAMING_SNAKE_CASE__     ).token_type_ids
             self.assertListEqual(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
             self.assertListEqual(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
             self.assertListEqual(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
      @slow
      def        SCREAMING_SNAKE_CASE							(       self				:       Union[str, Any]     )		->			int:
             a_					:		str							=  self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'     )

             a_					:		Optional[int]							=  tokenizer.encode('あンいワ'     )
             a_					:		Dict							=  tokenizer.encode(''     ,							prefix_text='あンいワ'     )
             a_					:		Dict							=  tokenizer.encode('いワ'     ,							prefix_text='あン'     )

             self.assertEqual(tokenizer.decode(SCREAMING_SNAKE_CASE__     )     ,							tokenizer.decode(SCREAMING_SNAKE_CASE__     )     )
             self.assertEqual(tokenizer.decode(SCREAMING_SNAKE_CASE__     )     ,							tokenizer.decode(SCREAMING_SNAKE_CASE__     )     )
             self.assertNotEqual(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
             self.assertNotEqual(SCREAMING_SNAKE_CASE__     ,							SCREAMING_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        SCREAMING_SNAKE_CASE							(       self				:       Dict     )		->			Optional[Any]:
             a_					:		List[str]							=  self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'     )

             a_					:		Optional[Any]							=  [['武田信玄', 'は、'], ['織田信長', 'の配下の、']]
             a_					:		List[str]							=  tokenizer(SCREAMING_SNAKE_CASE__     ,							padding=SCREAMING_SNAKE_CASE__     )
             a_					:		Dict							=  tokenizer.batch_encode_plus(SCREAMING_SNAKE_CASE__     ,							padding=SCREAMING_SNAKE_CASE__     )

             # fmt: off
             a_					:		List[Any]							=  [[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]]
             a_					:		Any							=  [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
             a_					:		List[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     ,							SCREAMING_SNAKE_CASE__     )
             self.assertListEqual(x_token.token_type_ids     ,							SCREAMING_SNAKE_CASE__     )
             self.assertListEqual(x_token.attention_mask     ,							SCREAMING_SNAKE_CASE__     )
             self.assertListEqual(x_token_a.input_ids     ,							SCREAMING_SNAKE_CASE__     )
             self.assertListEqual(x_token_a.token_type_ids     ,							SCREAMING_SNAKE_CASE__     )
             self.assertListEqual(x_token_a.attention_mask     ,							SCREAMING_SNAKE_CASE__     )
      def        SCREAMING_SNAKE_CASE							(       self				:       Tuple     )		->			Dict:
             # Intentionally convert some words to accommodate character fluctuations unique to Japanese
             pass

      def        SCREAMING_SNAKE_CASE							(       self				:       Dict     )		->			int:
             # tokenizer has no padding token
             pass


