
from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase       =					logging.get_logger(__name__)

UpperCAmelCase       =					{
    '''facebook/data2vec-text-base''': '''https://huggingface.co/data2vec/resolve/main/config.json''',
}







class 			A_  (     __lowerCamelCase  ):




	'''simple docstring'''


	_UpperCamelCase	:	Optional[int]									=			"""data2vec-text"""





	def __init__(			self						,       snake_case=3_0522						,       snake_case=768						,       snake_case=12						,       snake_case=12						,       snake_case=3072						,       snake_case="gelu"						,       snake_case=0.1						,       snake_case=0.1						,       snake_case=512						,       snake_case=2						,       snake_case=0.02						,       snake_case=1E-12						,       snake_case=1						,       snake_case=0						,       snake_case=2						,       snake_case="absolute"						,       snake_case=True						,       snake_case=None						,       **snake_case						,       ):
		super().__init__(pad_token_id=snake_case						,       bos_token_id=snake_case						,       eos_token_id=snake_case						,       **snake_case			)

		lowercase	    =       vocab_size
		lowercase	    =       hidden_size
		lowercase	    =       num_hidden_layers
		lowercase	    =       num_attention_heads
		lowercase	    =       hidden_act
		lowercase	    =       intermediate_size
		lowercase	    =       hidden_dropout_prob
		lowercase	    =       attention_probs_dropout_prob
		lowercase	    =       max_position_embeddings
		lowercase	    =       type_vocab_size
		lowercase	    =       initializer_range
		lowercase	    =       layer_norm_eps
		lowercase	    =       position_embedding_type
		lowercase	    =       use_cache
		lowercase	    =       classifier_dropout







class 			A_  (     __lowerCamelCase  ):




	'''simple docstring'''


	@property
	def       SCREAMING_SNAKE_CASE__		(			self			):
		if self.task == "multiple-choice":
			lowercase	    =       {0: 'batch', 1: 'choice', 2: 'sequence'}
		else:
			lowercase	    =       {0: 'batch', 1: 'sequence'}
		return OrderedDict(
		    [
		        ('input_ids', dynamic_axis),
		        ('attention_mask', dynamic_axis),
		    ]			)



from __future__ import annotations




def 							a		(				snake_case__:   list[list[int]]   ):


				'''simple docstring'''

				# preprocessing the first row
				for i in range(1		,  len(matrix[0]   )   ):
								matrix[0][i] += matrix[0][i - 1]

				# preprocessing the first column
				for i in range(1		,  len(snake_case__   )   ):
								matrix[i][0] += matrix[i - 1][0]

				# updating the path cost for current position
				for i in range(1		,  len(snake_case__   )   ):
								for j in range(1		,  len(matrix[0]   )   ):
												matrix[i][j] += min(matrix[i - 1][j]		,  matrix[i][j - 1]   )

				return matrix[-1][-1]


if __name__ == "__main__":
						import doctest

						doctest.testmod()




