




"""simple docstring"""







import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
							from transformers import AutoModelForSeqaSeqLM, AutoTokenizer




@require_torch
@require_sentencepiece
@require_tokenizers
class 			A__	(     unittest.TestCase):

		@slow
		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Tuple						      =				AutoModelForSeqaSeqLM.from_pretrained('google/mt5-small'	,		return_dict=__A			).to(__A			)
			__lowerCAmelCase      :						Optional[int]						      =				AutoTokenizer.from_pretrained('google/mt5-small'			)

			__lowerCAmelCase      :						List[Any]						      =				tokenizer('Hello there'	,		return_tensors='pt'			).input_ids
			__lowerCAmelCase      :						Dict						      =				tokenizer('Hi I am'	,		return_tensors='pt'			).input_ids

			__lowerCAmelCase      :						Union[str, Any]						      =				model(input_ids.to(__A			)	,		labels=labels.to(__A			)			).loss
			__lowerCAmelCase      :						Tuple						      =				-(labels.shape[-1] * loss.item())

			__lowerCAmelCase      :						int						      =				-84.91_27
			self.assertTrue(abs(mtf_score - EXPECTED_SCORE			) < 1E-4			)

"""simple docstring"""







import os
def    __lowerCAmelCase    (_UpperCamelCase = "input.txt"		):

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

	__lowerCAmelCase      :						List[str]						      =				len(_UpperCamelCase		)
	__lowerCAmelCase      :						Tuple						      =				len(matrix[0]		)

	__lowerCAmelCase      :						int						      =				[[-1 for _ in range(_UpperCamelCase		)] for _ in range(_UpperCamelCase		)]
	for i in range(_UpperCamelCase		):
		__lowerCAmelCase      :						Any						      =				matrix[i][0]

	for j in range(1	,  _UpperCamelCase		):
		for i in range(_UpperCamelCase		):
			__lowerCAmelCase      :						Optional[Any]						      =				minimal_path_sums[i][j - 1] + matrix[i][j]

		for i in range(1	,  _UpperCamelCase		):
			__lowerCAmelCase      :						Optional[Any]						      =				min(
			    minimal_path_sums[i][j]	,  minimal_path_sums[i - 1][j] + matrix[i][j]		)

		for i in range(rows - 2	,  -1	,  -1		):
			__lowerCAmelCase      :						List[str]						      =				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() = }')