


import os






def 						_A						(						_lowercase = "input.txt"      ) ->      Any:


     """simple docstring"""


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

     __UpperCamelCase      =       len(snake_case__      )
     __UpperCamelCase      =       len(matrix[0]      )

     __UpperCamelCase      =       [[-1 for _ in range(snake_case__      )] for _ in range(snake_case__      )]
     for i in range(snake_case__      ):
          __UpperCamelCase      =       matrix[i][0]

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

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

          for i in range(rows - 2 ,   -1 ,   -1      ):
               __UpperCamelCase      =       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() = }""")




import tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


__a  			=					'sshleifer/bart-tiny-random'
__a  			=					'patrickvonplaten/t5-tiny-random'
@require_torch
class  lowercase__(				unittest.TestCase							):



	"""simple docstring"""




	@cached_property
	def 						_lowercase  (       self  :			Any       )       ->     Tuple:
					return AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			int       )       ->     List[Any]:
					lowercase_  ,	*lowercase_       =					create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=1       ,							d=1       )
					self.assertEqual(student.config.num_hidden_layers       ,							1       )
	def 						_lowercase  (       self  :			Union[str, Any]       )       ->     Optional[int]:
					lowercase_  ,	*lowercase_       =					create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=1       ,							d=SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			List[str]       )       ->     List[Any]:
					lowercase_  ,	*lowercase_       =					create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=1       ,							d=SCREAMING_SNAKE_CASE_       )
					self.assertEqual(student.config.encoder_layers       ,							1       )
					self.assertEqual(student.config.decoder_layers       ,							self.teacher_config.encoder_layers       )
	def 						_lowercase  (       self  :			List[Any]       )       ->     List[Any]:
					lowercase_  ,	*lowercase_       =					create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=1       ,							d=1       )
					self.assertEqual(student.config.encoder_layers       ,							1       )
					self.assertEqual(student.config.decoder_layers       ,							1       )




	def 						_lowercase  (       self  :			Union[str, Any]       )       ->     Optional[int]:
					with self.assertRaises(SCREAMING_SNAKE_CASE_       ):
									create_student_by_copying_alternating_layers(SCREAMING_SNAKE_CASE_       ,							tempfile.mkdtemp()       ,							e=SCREAMING_SNAKE_CASE_       ,							d=SCREAMING_SNAKE_CASE_       )




