


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


lowerCAmelCase			=				{'configuration_swin': ['SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwinConfig', 'SwinOnnxConfig']}


try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase			=				[
			    'SWIN_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'SwinForImageClassification',
			    'SwinForMaskedImageModeling',
			    'SwinModel',
			    'SwinPreTrainedModel',
			    'SwinBackbone',
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase			=				[
			    'TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'TFSwinForImageClassification',
			    'TFSwinForMaskedImageModeling',
			    'TFSwinModel',
			    'TFSwinPreTrainedModel',
			]

if TYPE_CHECKING:
			from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_swin import (
						    SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
						    SwinBackbone,
						    SwinForImageClassification,
						    SwinForMaskedImageModeling,
						    SwinModel,
						    SwinPreTrainedModel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_swin import (
						    TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFSwinForImageClassification,
						    TFSwinForMaskedImageModeling,
						    TFSwinModel,
						    TFSwinPreTrainedModel,
						)

else:
			import sys

			lowerCAmelCase			=				_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)










'''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() = }""")