


import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin






class       _UpperCamelCase    (					__snake_case    ,		unittest.TestCase				):

				"""simple docstring"""







				lowerCAmelCase 		= XLMTokenizer
				lowerCAmelCase 		= False

				def      _UpperCAmelCase					(						self   )	->				Dict:
					super().setUp()

					# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
					A								=				[
					    """l""",
					    """o""",
					    """w""",
					    """e""",
					    """r""",
					    """s""",
					    """t""",
					    """i""",
					    """d""",
					    """n""",
					    """w</w>""",
					    """r</w>""",
					    """t</w>""",
					    """lo""",
					    """low""",
					    """er</w>""",
					    """low</w>""",
					    """lowest</w>""",
					    """newer</w>""",
					    """wider</w>""",
					    """<unk>""",
					]
					A								=				dict(zip(a__				,   range(len(a__   )   )   )   )
					A								=				["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

					A								=				os.path.join(self.tmpdirname				,   VOCAB_FILES_NAMES["""vocab_file"""]   )
					A								=				os.path.join(self.tmpdirname				,   VOCAB_FILES_NAMES["""merges_file"""]   )
					with open(self.vocab_file				,   """w"""   ) as fp:
						fp.write(json.dumps(a__   )   )
					with open(self.merges_file				,   """w"""   ) as fp:
						fp.write("""\n""".join(a__   )   )

				def      _UpperCAmelCase					(						self				,   a__   )	->				List[str]:
					A								=				"""lower newer"""
					A								=				"""lower newer"""
					return input_text, output_text

				def      _UpperCAmelCase					(						self   )	->				Tuple:
					A								=				XLMTokenizer(self.vocab_file				,   self.merges_file   )

					A								=				"""lower"""
					A								=				["""low""", """er</w>"""]
					A								=				tokenizer.tokenize(a__   )
					self.assertListEqual(a__				,   a__   )

					A								=				tokens + ["""<unk>"""]
					A								=				[14, 15, 20]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(a__   )				,   a__   )

				@slow
				def      _UpperCAmelCase					(						self   )	->				Union[str, Any]:
					A								=				XLMTokenizer.from_pretrained("""xlm-mlm-en-2048"""   )

					A								=				tokenizer.encode("""sequence builders"""				,   add_special_tokens=a__   )
					A								=				tokenizer.encode("""multi-sequence build"""				,   add_special_tokens=a__   )

					A								=				tokenizer.build_inputs_with_special_tokens(a__   )
					A								=				tokenizer.build_inputs_with_special_tokens(a__				,   a__   )

					assert encoded_sentence == [0] + text + [1]
					assert encoded_pair == [0] + text + [1] + text_a + [1]







import os





def   _lowerCAmelCase				(   UpperCamelCase__:     str = "matrix.txt"						) ->   int:





	"""simple docstring"""







	with open(os.path.join(os.path.dirname(UpperCamelCase__						)							,					UpperCamelCase__						)						) as in_file:
		A								=				in_file.read()

	A								=				[[int(UpperCamelCase__						) 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(UpperCamelCase__						)] for j in range(UpperCamelCase__						)]
	A								=				grid[0][0]
	for i in range(1							,					UpperCamelCase__						):
		A								=				grid[0][i] + dp[0][i - 1]
	for i in range(1							,					UpperCamelCase__						):
		A								=				grid[i][0] + dp[i - 1][0]

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

	return dp[-1][-1]


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



