


import os





def 	_lowerCAmelCase       (    _lowerCAmelCase = "input.txt" )						->	int:


						'''simple docstring'''






						with open(os.path.join(os.path.dirname(_lowerCAmelCase )      ,	_lowerCAmelCase ) ) as input_file:
												__snake_case				=		[
												    [int(_lowerCAmelCase ) for element in line.split("," )]
												    for line in input_file.readlines()
												]

						__snake_case				=		len(_lowerCAmelCase )
						__snake_case				=		len(matrix[0] )

						__snake_case				=		[[-1 for _ in range(_lowerCAmelCase )] for _ in range(_lowerCAmelCase )]
						for i in range(_lowerCAmelCase ):
												__snake_case				=		matrix[i][0]

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

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

												for i in range(rows - 2      ,	-1      ,	-1 ):
																		__snake_case				=		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 baseaa
import io
import json
import os
from copy import deepcopy

from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler






class     UpperCamelCase:


					def __init__(						self	:		List[str]     ,    SCREAMING_SNAKE_CASE	:		Dict						)			->	str:




											'''simple docstring'''

											if isinstance(SCREAMING_SNAKE_CASE     ,    SCREAMING_SNAKE_CASE						):
																	# Don't modify user's data should they want to reuse it (e.g. in tests), because once we
																	# modified it, it will not be accepted here again, since `auto` values would have been overridden
																	__snake_case				=		deepcopy(SCREAMING_SNAKE_CASE						)
											elif os.path.exists(SCREAMING_SNAKE_CASE						):
																	with io.open(SCREAMING_SNAKE_CASE     ,    "r"     ,    encoding="utf-8"						) as f:
																							__snake_case				=		json.load(SCREAMING_SNAKE_CASE						)
											else:
																	try:
																							__snake_case				=		baseaa.urlsafe_baadecode(SCREAMING_SNAKE_CASE						).decode("utf-8"						)
																							__snake_case				=		json.loads(SCREAMING_SNAKE_CASE						)
																	except (UnicodeDecodeError, AttributeError, ValueError):
																							raise ValueError(
																							    f'''Expected a string path to an existing deepspeed config, or a dictionary, or a base64 encoded string. Received: {config_file_or_dict}'''						)

											__snake_case				=		config

											self.set_stage_and_offload()


					def 							SCREAMING_SNAKE_CASE_  (						self	:		Any						)			->	List[str]:




											'''simple docstring'''

											__snake_case				=		self.get_value("zero_optimization.stage"     ,    -1						)

											# offload
											__snake_case				=		False
											if self.is_zeroa() or self.is_zeroa():
																	__snake_case				=		set(["cpu", "nvme"]						)
																	__snake_case				=		set(
																	    [
																	        self.get_value("zero_optimization.offload_optimizer.device"						),
																	        self.get_value("zero_optimization.offload_param.device"						),
																	    ]						)
																	if len(offload_devices & offload_devices_valid						) > 0:
																							__snake_case				=		True


					def 							SCREAMING_SNAKE_CASE_  (						self	:		int     ,    SCREAMING_SNAKE_CASE	:		List[Any]						)			->	str:




											'''simple docstring'''

											__snake_case				=		self.config

											# find the config node of interest if it exists
											__snake_case				=		ds_key_long.split("."						)
											__snake_case				=		nodes.pop()
											for node in nodes:
																	__snake_case				=		config.get(SCREAMING_SNAKE_CASE						)
																	if config is None:
																							return None, ds_key

											return config, ds_key


					def 							SCREAMING_SNAKE_CASE_  (						self	:		Optional[Any]     ,    SCREAMING_SNAKE_CASE	:		str     ,    SCREAMING_SNAKE_CASE	:		Tuple=None						)			->	List[str]:




											'''simple docstring'''

											__snake_case		,					__snake_case				=		self.find_config_node(SCREAMING_SNAKE_CASE						)
											if config is None:
																	return default
											return config.get(SCREAMING_SNAKE_CASE     ,    SCREAMING_SNAKE_CASE						)


					def 							SCREAMING_SNAKE_CASE_  (						self	:		Any     ,    SCREAMING_SNAKE_CASE	:		Optional[int]     ,    SCREAMING_SNAKE_CASE	:		Tuple=False						)			->	Union[str, Any]:




											'''simple docstring'''

											__snake_case				=		self.config

											# find the config node of interest if it exists
											__snake_case				=		ds_key_long.split("."						)
											for node in nodes:
																	__snake_case				=		config
																	__snake_case				=		config.get(SCREAMING_SNAKE_CASE						)
																	if config is None:
																							if must_exist:
																													raise ValueError(f'''Can\'t find {ds_key_long} entry in the config: {self.config}'''						)
																							else:
																													return

        # if found remove it
											if parent_config is not None:
																	parent_config.pop(SCREAMING_SNAKE_CASE						)


					def 							SCREAMING_SNAKE_CASE_  (						self	:		Tuple     ,    SCREAMING_SNAKE_CASE	:		Any						)			->	Optional[Any]:




											'''simple docstring'''

											__snake_case				=		self.get_value(SCREAMING_SNAKE_CASE						)
											return False if value is None else bool(SCREAMING_SNAKE_CASE						)


					def 							SCREAMING_SNAKE_CASE_  (						self	:		Any     ,    SCREAMING_SNAKE_CASE	:		Union[str, Any]						)			->	str:




											'''simple docstring'''

											__snake_case				=		self.get_value(SCREAMING_SNAKE_CASE						)
											return False if value is None else not bool(SCREAMING_SNAKE_CASE						)


					def 							SCREAMING_SNAKE_CASE_  (						self	:		Dict						)			->	int:




											'''simple docstring'''

											return self._stage == 2


					def 							SCREAMING_SNAKE_CASE_  (						self	:		Optional[int]						)			->	List[str]:




											'''simple docstring'''

											return self._stage == 3






					def 							SCREAMING_SNAKE_CASE_  (						self	:		List[Any]						)			->	Optional[Any]:




											'''simple docstring'''

											return self._offload






class     UpperCamelCase:


					def __init__(						self	:		Union[str, Any]     ,    SCREAMING_SNAKE_CASE	:		Any						)			->	Optional[Any]:




											'''simple docstring'''

											__snake_case				=		engine






					def 							SCREAMING_SNAKE_CASE_  (						self	:		int     ,    SCREAMING_SNAKE_CASE	:		Tuple     ,    **SCREAMING_SNAKE_CASE	:		str						)			->	List[str]:




											'''simple docstring'''

											self.engine.backward(SCREAMING_SNAKE_CASE     ,    **SCREAMING_SNAKE_CASE						)

											# Deepspeed's `engine.step` performs the following operations:
											# - gradient accumulation check
											# - gradient clipping
											# - optimizer step
											# - zero grad
											# - checking overflow
											# - lr_scheduler step (only if engine.lr_scheduler is not None)
											self.engine.step()
											# and this plugin overrides the above calls with no-ops when Accelerate runs under
											# Deepspeed, but allows normal functionality for non-Deepspeed cases thus enabling a simple
											# training loop that works transparently under many training regimes.






class     UpperCamelCase(  _a   ):


					def __init__(						self	:		List[Any]     ,    SCREAMING_SNAKE_CASE	:		Dict						)			->	str:




											'''simple docstring'''

											super().__init__(SCREAMING_SNAKE_CASE     ,    device_placement=SCREAMING_SNAKE_CASE     ,    scaler=SCREAMING_SNAKE_CASE						)
											__snake_case				=		hasattr(self.optimizer     ,    "overflow"						)


					def 							SCREAMING_SNAKE_CASE_  (						self	:		Optional[Any]     ,    SCREAMING_SNAKE_CASE	:		List[Any]=None						)			->	str:




											'''simple docstring'''

											pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed


					def 							SCREAMING_SNAKE_CASE_  (						self	:		Dict						)			->	Any:




											'''simple docstring'''

											pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed






					@property
					def 							SCREAMING_SNAKE_CASE_  (						self	:		Optional[int]						)			->	Any:




											'''simple docstring'''

											if self.__has_overflow__:
																	return self.optimizer.overflow
											return False






class     UpperCamelCase(  _a   ):


					def __init__(						self	:		List[Any]     ,    SCREAMING_SNAKE_CASE	:		Any     ,    SCREAMING_SNAKE_CASE	:		str						)			->	Union[str, Any]:




											'''simple docstring'''

											super().__init__(SCREAMING_SNAKE_CASE     ,    SCREAMING_SNAKE_CASE						)






					def 							SCREAMING_SNAKE_CASE_  (						self	:		List[str]						)			->	Any:




											'''simple docstring'''

											pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed






class     UpperCamelCase:


					def __init__(						self	:		Union[str, Any]     ,    SCREAMING_SNAKE_CASE	:		List[Any]     ,    SCREAMING_SNAKE_CASE	:		Optional[Any]=0.001     ,    SCREAMING_SNAKE_CASE	:		Tuple=0     ,    **SCREAMING_SNAKE_CASE	:		Optional[int]						)			->	List[str]:




											'''simple docstring'''

											__snake_case				=		params
											__snake_case				=		lr
											__snake_case				=		weight_decay
											__snake_case				=		kwargs






class     UpperCamelCase:


					def __init__(						self	:		Optional[Any]     ,    SCREAMING_SNAKE_CASE	:		List[Any]     ,    SCREAMING_SNAKE_CASE	:		Dict=None     ,    SCREAMING_SNAKE_CASE	:		Tuple=0     ,    **SCREAMING_SNAKE_CASE	:		Tuple						)			->	Tuple:




											'''simple docstring'''

											__snake_case				=		optimizer
											__snake_case				=		total_num_steps
											__snake_case				=		warmup_num_steps
											__snake_case				=		kwargs





