
import os




def 							a		(				snake_case__:   str = "matrix.txt"   ):


				'''simple docstring'''





				with open(os.path.join(os.path.dirname(_lowerCamelCase   )		,  _lowerCamelCase   )   ) as in_file:
								lowercase_	    =   in_file.read()

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

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

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

				return dp[-1][-1]


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










'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


UpperCAmelCase_							:	List[str]	     =		{
    '''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig'''],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase_							:	int	     =		[
         '''GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''GPTBigCodeForSequenceClassification''',
         '''GPTBigCodeForTokenClassification''',
         '''GPTBigCodeForCausalLM''',
         '''GPTBigCodeModel''',
         '''GPTBigCodePreTrainedModel''',
     ]

if TYPE_CHECKING:
     from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_gpt_bigcode import (
              GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
              GPTBigCodeForCausalLM,
              GPTBigCodeForSequenceClassification,
              GPTBigCodeForTokenClassification,
              GPTBigCodeModel,
              GPTBigCodePreTrainedModel,
          )


else:
     import sys

     UpperCAmelCase_							:	Any	     =		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






