






'''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 				__SCREAMING_SNAKE_CASE							(				_lowerCAmelCase   ,   unittest.TestCase  ):
      __a	       =GPTSanJapaneseTokenizer
      __a	       =False
      __a	       ={"do_clean_text": False, "add_prefix_space": False}




      def 			__UpperCamelCase				(	self   )				->Tuple:



         '''simple docstring'''
         super().setUp()

         # fmt: off
         __a					  =     ['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					  =     {'emoji': {'\ud83d\ude00': '<|emoji1|>'}, 'emoji_inv': {'<|emoji1|>': '\ud83d\ude00'}}  # 😀
         __a					  =     {'unk_token': '<unk>'}

         __a					  =     os.path.join(self.tmpdirname			, VOCAB_FILES_NAMES['vocab_file']   )
         __a					  =     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 			__UpperCamelCase				(	self			, **lowerCamelCase   )				->Dict:



         '''simple docstring'''
         kwargs.update(self.special_tokens_map   )
         return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname			, **lowerCamelCase   )




      def 			__UpperCamelCase				(	self			, lowerCamelCase   )				->List[Any]:



         '''simple docstring'''
         __a					  =     'こんにちは、世界。 \nこんばんは、㔺界。😀'
         __a					  =     'こんにちは、世界。 \nこんばんは、世界。😀'
         return input_text, output_text




      def 			__UpperCamelCase				(	self			, lowerCamelCase   )				->int:



         '''simple docstring'''
         __a  ,      __a					  =     self.get_input_output_texts(lowerCamelCase   )
         __a					  =     tokenizer.encode(lowerCamelCase			, add_special_tokens=lowerCamelCase   )
         __a					  =     tokenizer.decode(lowerCamelCase			, clean_up_tokenization_spaces=lowerCamelCase   )
         return text, ids




      def 			__UpperCamelCase				(	self   )				->List[Any]:



         '''simple docstring'''
         pass  # TODO add if relevant




      def 			__UpperCamelCase				(	self   )				->Optional[int]:



         '''simple docstring'''
         pass  # TODO add if relevant




      def 			__UpperCamelCase				(	self   )				->Optional[int]:



         '''simple docstring'''
         pass  # TODO add if relevant




      def 			__UpperCamelCase				(	self   )				->Dict:



         '''simple docstring'''
         __a					  =     self.get_tokenizer()

         # Testing tokenization
         __a					  =     'こんにちは、世界。　こんばんは、㔺界。'
         __a					  =     ['こん', 'にちは', '、', '世界', '。', '<SP>', 'こん', 'ばんは', '、', '㔺界', '。']
         __a					  =     tokenizer.tokenize(lowerCamelCase   )
         self.assertListEqual(lowerCamelCase			, lowerCamelCase   )

         # Testing conversion to ids without special tokens
         __a					  =     [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
         __a					  =     tokenizer.convert_tokens_to_ids(lowerCamelCase   )
         self.assertListEqual(lowerCamelCase			, lowerCamelCase   )

         # Testing conversion to ids with special tokens
         __a					  =     tokens + [tokenizer.unk_token]
         __a					  =     [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
         __a					  =     tokenizer.convert_tokens_to_ids(lowerCamelCase   )
         self.assertListEqual(lowerCamelCase			, lowerCamelCase   )




      def 			__UpperCamelCase				(	self   )				->Optional[int]:



         '''simple docstring'''
         __a					  =     self.get_tokenizer()

         # Testing tokenization
         __a					  =     'こんにちは、<|bagoftoken|>世界。こんばんは、<|bagoftoken|>㔺界。'
         __a					  =     'こんにちは、、、、世界。こんばんは、、、、世界。'
         __a					  =     tokenizer.encode(lowerCamelCase   )
         __a					  =     tokenizer.decode(lowerCamelCase   )
         self.assertEqual(lowerCamelCase			, lowerCamelCase   )




      @slow
      def 			__UpperCamelCase				(	self   )				->Any:



         '''simple docstring'''
         __a					  =     self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'   )

         # Testing tokenization
         __a					  =     'こんにちは、世界。'
         __a					  =     'こんばんは、㔺界。😀'
         __a					  =     'こんにちは、世界。こんばんは、世界。😀'
         __a					  =     tokenizer.encode(prefix_text + input_text   )
         __a					  =     tokenizer.encode(''			, prefix_text=prefix_text + input_text   )
         __a					  =     tokenizer.encode(lowerCamelCase			, prefix_text=lowerCamelCase   )
         __a					  =     tokenizer.decode(lowerCamelCase   )
         __a					  =     tokenizer.decode(lowerCamelCase   )
         __a					  =     tokenizer.decode(lowerCamelCase   )
         self.assertEqual(lowerCamelCase			, lowerCamelCase   )
         self.assertEqual(lowerCamelCase			, lowerCamelCase   )
         self.assertEqual(lowerCamelCase			, lowerCamelCase   )




      @slow
      def 			__UpperCamelCase				(	self   )				->Optional[int]:



         '''simple docstring'''
         __a					  =     self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'   )

         # Testing tokenization
         __a					  =     'こんにちは、世界。'
         __a					  =     'こんばんは、㔺界。😀'

         __a					  =     len(tokenizer.encode(lowerCamelCase   )   ) - 2
         __a					  =     len(tokenizer.encode(lowerCamelCase   )   ) - 2

         __a					  =     [1] + [0] * (len_prefix + len_text + 1)
         __a					  =     [1] * (len_prefix + len_text + 1) + [0]
         __a					  =     [1] + [1] * (len_prefix) + [0] * (len_text + 1)

         __a					  =     tokenizer(prefix_text + input_text   ).token_type_ids
         __a					  =     tokenizer(''			, prefix_text=prefix_text + input_text   ).token_type_ids
         __a					  =     tokenizer(lowerCamelCase			, prefix_text=lowerCamelCase   ).token_type_ids
         self.assertListEqual(lowerCamelCase			, lowerCamelCase   )
         self.assertListEqual(lowerCamelCase			, lowerCamelCase   )
         self.assertListEqual(lowerCamelCase			, lowerCamelCase   )




      @slow
      def 			__UpperCamelCase				(	self   )				->str:



         '''simple docstring'''
         __a					  =     self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'   )

         __a					  =     tokenizer.encode('あンいワ'   )
         __a					  =     tokenizer.encode(''			, prefix_text='あンいワ'   )
         __a					  =     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 			__UpperCamelCase				(	self   )				->List[Any]:



         '''simple docstring'''
         __a					  =     self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'   )

         __a					  =     [['武田信玄', 'は、'], ['織田信長', 'の配下の、']]
         __a					  =     tokenizer(lowerCamelCase			, padding=lowerCamelCase   )
         __a					  =     tokenizer.batch_encode_plus(lowerCamelCase			, padding=lowerCamelCase   )

         # fmt: off
         __a					  =     [[3_5993, 8640, 2_5948, 3_5998, 3_0647, 3_5675, 3_5999, 3_5999], [3_5993, 1_0382, 9868, 3_5998, 3_0646, 9459, 3_0646, 3_5675]]
         __a					  =     [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
         __a					  =     [[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 			__UpperCamelCase				(	self   )				->List[str]:



         '''simple docstring'''
         # Intentionally convert some words to accommodate character fluctuations unique to Japanese
         pass






      def 			__UpperCamelCase				(	self   )				->Optional[Any]:



         '''simple docstring'''
         # tokenizer has no padding token
         pass







'''simple docstring'''



import os



def  __UpperCAmelCase						(					SCREAMING_SNAKE_CASE__:						str = "matrix.txt"     )	->      int:

   """simple docstring"""
   with open(os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE__     ),       SCREAMING_SNAKE_CASE__     )     ) as in_file:
      __a					  =     in_file.read()

   __a					  =     [[int(SCREAMING_SNAKE_CASE__     ) for cell in row.split(','     )] for row in data.strip().splitlines()]
   __a					  =     [[0 for cell in row] for row in grid]
   __a					  =     len(grid[0]     )

   __a					  =     [[0 for i in range(SCREAMING_SNAKE_CASE__     )] for j in range(SCREAMING_SNAKE_CASE__     )]
   __a					  =     grid[0][0]
   for i in range(1,       SCREAMING_SNAKE_CASE__     ):
      __a					  =     grid[0][i] + dp[0][i - 1]
   for i in range(1,       SCREAMING_SNAKE_CASE__     ):
      __a					  =     grid[i][0] + dp[i - 1][0]

   for i in range(1,       SCREAMING_SNAKE_CASE__     ):
      for j in range(1,       SCREAMING_SNAKE_CASE__     ):
         __a					  =     grid[i][j] + min(dp[i - 1][j],       dp[i][j - 1]     )

   return dp[-1][-1]


if __name__ == "__main__":
 print(f"""{solution() = }""")