lowercase_     :   List[Any] 				=				'0.21.0'

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
    from .utils import rich


import os







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

 SCREAMING_SNAKE_CASE__:   Optional[int]=      [[int(snake_case_      ) for cell in row.split(''','''      )] for row in data.strip().splitlines()]
 SCREAMING_SNAKE_CASE__:   int=      [[0 for cell in row] for row in grid]
 SCREAMING_SNAKE_CASE__:   Dict=      len(grid[0]      )

 SCREAMING_SNAKE_CASE__:   Dict=      [[0 for i in range(snake_case_      )] for j in range(snake_case_      )]
 SCREAMING_SNAKE_CASE__:   Optional[int]=      grid[0][0]
 for i in range(1       ,				snake_case_      ):
  SCREAMING_SNAKE_CASE__:   Optional[int]=      grid[0][i] + dp[0][i - 1]
 for i in range(1       ,				snake_case_      ):
  SCREAMING_SNAKE_CASE__:   List[Any]=      grid[i][0] + dp[i - 1][0]

 for i in range(1       ,				snake_case_      ):
  for j in range(1       ,				snake_case_      ):
   SCREAMING_SNAKE_CASE__:   Dict=      grid[i][j] + min(dp[i - 1][j]       ,				dp[i][j - 1]      )

 return dp[-1][-1]


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

