



'''simple docstring'''
import os






def A__    (     UpperCAmelCase_ = "matrix.txt"							):
						with open(os.path.join(os.path.dirname(UpperCAmelCase_							)  ,  UpperCAmelCase_							)							) as in_file:
												_UpperCamelCase					:		str 				=   in_file.read()

						_UpperCamelCase					:		List[str] 				=   [[int(UpperCAmelCase_							) for cell in row.split(','							)] for row in data.strip().splitlines()]
						_UpperCamelCase					:		List[str] 				=   [[0 for cell in row] for row in grid]
						_UpperCamelCase					:		str 				=   len(grid[0]							)

						_UpperCamelCase					:		str 				=   [[0 for i in range(UpperCAmelCase_							)] for j in range(UpperCAmelCase_							)]
						_UpperCamelCase					:		Union[str, Any] 				=   grid[0][0]
						for i in range(1  ,  UpperCAmelCase_							):
												_UpperCamelCase					:		Any 				=   grid[0][i] + dp[0][i - 1]
						for i in range(1  ,  UpperCAmelCase_							):
												_UpperCamelCase					:		Union[str, Any] 				=   grid[i][0] + dp[i - 1][0]

						for i in range(1  ,  UpperCAmelCase_							):
												for j in range(1  ,  UpperCAmelCase_							):
																		_UpperCamelCase					:		Tuple 				=   grid[i][j] + min(dp[i - 1][j]  ,  dp[i][j - 1]							)

						return dp[-1][-1]


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








from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


snake_case_ : Union[str, Any]    		=       {"configuration_gpt_neox": ["GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXConfig"]}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    snake_case_ : Dict    		=       ["GPTNeoXTokenizerFast"]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    snake_case_ : str    		=       [
        "GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST",
        "GPTNeoXForCausalLM",
        "GPTNeoXForQuestionAnswering",
        "GPTNeoXForSequenceClassification",
        "GPTNeoXForTokenClassification",
        "GPTNeoXLayer",
        "GPTNeoXModel",
        "GPTNeoXPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_gpt_neox import (
            GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
            GPTNeoXForCausalLM,
            GPTNeoXForQuestionAnswering,
            GPTNeoXForSequenceClassification,
            GPTNeoXForTokenClassification,
            GPTNeoXLayer,
            GPTNeoXModel,
            GPTNeoXPreTrainedModel,
        )


else:
    import sys

    snake_case_ : Optional[int]    		=       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






