



import os
import sys
import unittest


UpperCAmelCase__   =       os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
UpperCAmelCase__   =       os.path.join(git_repo_path, "src", "transformers")

UpperCAmelCase__   =       "\n{0} = None\n"

UpperCAmelCase__   =       "\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n"


UpperCAmelCase__   =       "\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n"







class 			__lowerCAmelCase    (			unittest.TestCase						):



			def     _lowerCamelCase       (						self   :  Tuple)   ->    List[Any]:



						"""simple docstring"""






						_UpperCAmelCase		       =   find_backend('    _import_structure["models.albert"].append("AlbertTokenizerFast")')
						self.assertIsNone(A)

						_UpperCAmelCase		       =   find_backend('    if not is_tokenizers_available():')
						self.assertEqual(A ,		'tokenizers')

						_UpperCAmelCase		       =   find_backend('    if not is_tensorflow_text_available():')
						self.assertEqual(A ,		'tensorflow_text')

						_UpperCAmelCase		       =   find_backend('    if not (is_sentencepiece_available() and is_tokenizers_available()):')
						self.assertEqual(A ,		'sentencepiece_and_tokenizers')

						_UpperCAmelCase		       =   find_backend(
						    '    if not (is_sentencepiece_available() and is_tensorflow_text_available()):')
						self.assertEqual(A ,		'sentencepiece_and_tensorflow_text')

						_UpperCAmelCase		       =   find_backend(
						    '    if not (is_sentencepiece_available() and is_tokenizers_available() and is_vision_available()):')
						self.assertEqual(A ,		'sentencepiece_and_tokenizers_and_vision')



			def     _lowerCamelCase       (						self   :  Union[str, Any])   ->    Union[str, Any]:



						"""simple docstring"""






						_UpperCAmelCase		       =   read_init()
						# We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
						self.assertIn('torch' ,		A)
						self.assertIn('tensorflow_text' ,		A)
						self.assertIn('sentencepiece_and_tokenizers' ,		A)

						# Likewise, we can't assert on the exact content of a key
						self.assertIn('BertModel' ,		objects['torch'])
						self.assertIn('TFBertModel' ,		objects['tf'])
						self.assertIn('FlaxBertModel' ,		objects['flax'])
						self.assertIn('BertModel' ,		objects['torch'])
						self.assertIn('TFBertTokenizer' ,		objects['tensorflow_text'])
						self.assertIn('convert_slow_tokenizer' ,		objects['sentencepiece_and_tokenizers'])



			def     _lowerCamelCase       (						self   :  Any)   ->    Tuple:



						"""simple docstring"""






						_UpperCAmelCase		       =   create_dummy_object('CONSTANT' ,		'\'torch\'')
						self.assertEqual(A ,		'\nCONSTANT = None\n')

						_UpperCAmelCase		       =   create_dummy_object('function' ,		'\'torch\'')
						self.assertEqual(
						    A ,		'\ndef function(*args, **kwargs):\n    requires_backends(function, \'torch\')\n')

						_UpperCAmelCase		       =   '\nclass FakeClass(metaclass=DummyObject):\n    _backends = \'torch\'\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, \'torch\')\n'
						_UpperCAmelCase		       =   create_dummy_object('FakeClass' ,		'\'torch\'')
						self.assertEqual(A ,		A)



			def     _lowerCamelCase       (						self   :  Optional[Any])   ->    int:



						"""simple docstring"""






						_UpperCAmelCase		       =   '# This file is autogenerated by the command `make fix-copies`, do not edit.\nfrom ..utils import DummyObject, requires_backends\n\n\nCONSTANT = None\n\n\ndef function(*args, **kwargs):\n    requires_backends(function, ["torch"])\n\n\nclass FakeClass(metaclass=DummyObject):\n    _backends = ["torch"]\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, ["torch"])\n'
						_UpperCAmelCase		       =   create_dummy_files({'torch': ['CONSTANT', 'function', 'FakeClass']})
						self.assertEqual(dummy_files['torch'] ,		A)



import os
def      a      (			A__	:   str = "input.txt"     )    ->      int:





      """simple docstring"""



      with open(os.path.join(os.path.dirname(A__     )      ,   A__     )     ) as input_file:
            _lowercase	       =[
                [int(A__     ) for element in line.split(','     )]
                for line in input_file.readlines()
            ]

      _lowercase	       =len(A__     )
      _lowercase	       =len(matrix[0]     )

      _lowercase	       =[[-1 for _ in range(A__     )] for _ in range(A__     )]
      for i in range(A__     ):
            _lowercase	       =matrix[i][0]

      for j in range(1      ,   A__     ):
            for i in range(A__     ):
                  _lowercase	       =minimal_path_sums[i][j - 1] + matrix[i][j]

            for i in range(1      ,   A__     ):
                  _lowercase	       =min(
                      minimal_path_sums[i][j]      ,   minimal_path_sums[i - 1][j] + matrix[i][j]     )

            for i in range(rows - 2      ,   -1      ,   -1     ):
                  _lowercase	       =min(
                      minimal_path_sums[i][j]      ,   minimal_path_sums[i + 1][j] + matrix[i][j]     )

      return min(minimal_path_sums_row[-1] for minimal_path_sums_row in minimal_path_sums     )


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


