




_lowerCamelCase      :						Union[str, Any]							=  """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""

_lowerCamelCase      :						Dict							=  [{"""type""": """code""", """content""": INSTALL_CONTENT}]
_lowerCamelCase      :						Dict							=  {
    """{processor_class}""": """FakeProcessorClass""",
    """{model_class}""": """FakeModelClass""",
    """{object_class}""": """FakeObjectClass""",
}










'''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() = }""")