





'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


a__					:			Tuple          =     logging.get_logger(__name__)

a__					:			List[Any]          =     {
    '''facebook/nllb-moe-54B''': '''https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json''',
}






class 				__snake_case     (					__magic_name__							):
	__lowerCAmelCase       						=  '''nllb-moe'''
	__lowerCAmelCase       						=  ['''past_key_values''']
	__lowerCAmelCase       						=  {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}





	def __init__(		self      ,       UpperCamelCase_=12_8112      ,       UpperCamelCase_=1024      ,       UpperCamelCase_=12      ,       UpperCamelCase_=4096      ,       UpperCamelCase_=16      ,       UpperCamelCase_=12      ,       UpperCamelCase_=4096      ,       UpperCamelCase_=16      ,       UpperCamelCase_=0.0_5      ,       UpperCamelCase_=0.0_5      ,       UpperCamelCase_=True      ,       UpperCamelCase_=True      ,       UpperCamelCase_="relu"      ,       UpperCamelCase_=1024      ,       UpperCamelCase_=0.1      ,       UpperCamelCase_=0.1      ,       UpperCamelCase_=0.0      ,       UpperCamelCase_=0.0_2      ,       UpperCamelCase_=2      ,       UpperCamelCase_=True      ,       UpperCamelCase_=False      ,       UpperCamelCase_="float32"      ,       UpperCamelCase_=False      ,       UpperCamelCase_=128      ,       UpperCamelCase_=64      ,       UpperCamelCase_=4      ,       UpperCamelCase_=4      ,       UpperCamelCase_=0.0_0_1      ,       UpperCamelCase_=0.0_0_1      ,       UpperCamelCase_="all"      ,       UpperCamelCase_=False      ,       UpperCamelCase_=False      ,       UpperCamelCase_=1.0      ,       UpperCamelCase_=0.2      ,       UpperCamelCase_=1      ,       UpperCamelCase_=0      ,       UpperCamelCase_=2      ,       UpperCamelCase_=False      ,       **UpperCamelCase_      ,       )      ->		Optional[int]:
		snake_case__	       =   vocab_size
		snake_case__	       =   max_position_embeddings
		snake_case__	       =   d_model
		snake_case__	       =   encoder_ffn_dim
		snake_case__	       =   encoder_layers
		snake_case__	       =   encoder_attention_heads
		snake_case__	       =   decoder_ffn_dim
		snake_case__	       =   decoder_layers
		snake_case__	       =   decoder_attention_heads
		snake_case__	       =   dropout
		snake_case__	       =   attention_dropout
		snake_case__	       =   activation_dropout
		snake_case__	       =   activation_function
		snake_case__	       =   init_std
		snake_case__	       =   encoder_layerdrop
		snake_case__	       =   decoder_layerdrop
		snake_case__	       =   use_cache
		snake_case__	       =   encoder_layers
		snake_case__	       =   scale_embedding  # scale factor will be sqrt(d_model) if True
		snake_case__	       =   router_z_loss_coef
		snake_case__	       =   router_aux_loss_coef
		snake_case__	       =   decoder_sparse_step
		snake_case__	       =   encoder_sparse_step
		snake_case__	       =   num_experts
		snake_case__	       =   expert_capacity
		snake_case__	       =   router_bias
		if router_dtype not in ["float32", "float16", "bfloat16"]:
			raise ValueError(F'''`router_dtype` must be one of \'float32\', \'float16\' or \'bfloat16\', got {router_dtype}'''		)
		snake_case__	       =   router_dtype

		snake_case__	       =   router_ignore_padding_tokens
		snake_case__	       =   batch_prioritized_routing
		snake_case__	       =   second_expert_policy
		snake_case__	       =   normalize_router_prob_before_dropping
		snake_case__	       =   moe_eval_capacity_token_fraction
		snake_case__	       =   moe_token_dropout
		snake_case__	       =   output_router_logits
		super().__init__(
		    pad_token_id=UpperCamelCase_      ,       bos_token_id=UpperCamelCase_      ,       eos_token_id=UpperCamelCase_      ,       is_encoder_decoder=UpperCamelCase_      ,       decoder_start_token_id=UpperCamelCase_      ,       **UpperCamelCase_      ,       )










'''simple docstring'''




import os




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

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

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

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

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

		for i in range(1					,				UpperCAmelCase_							):
			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() = }""")



