


from collections import deque






def 				_lowercase     (		SCREAMING_SNAKE_CASE_ :		Optional[int]						):





			"""simple docstring"""




			UpperCamelCase								=       len(_lowercase						)
			UpperCamelCase								=       deque()
			UpperCamelCase								=       [False for _ in range(_lowercase						)]
			UpperCamelCase								=       [-1 for _ in range(_lowercase						)]
			UpperCamelCase								=       index_of[:]

			def strong_connect(SCREAMING_SNAKE_CASE_ :		Optional[Any]							,	SCREAMING_SNAKE_CASE_ :		Optional[int]							,	SCREAMING_SNAKE_CASE_ :		Union[str, Any]						):
						UpperCamelCase								=       index  # the number when this node is seen
						UpperCamelCase								=       index  # lowest rank node reachable from here
						index += 1
						stack.append(_lowercase						)
						UpperCamelCase								=       True

						for w in g[v]:
									if index_of[w] == -1:
												UpperCamelCase								=       strong_connect(_lowercase							,	_lowercase							,	_lowercase						)
												UpperCamelCase								=       (
												    lowlink_of[w] if lowlink_of[w] < lowlink_of[v] else lowlink_of[v]
												)
									elif on_stack[w]:
												UpperCamelCase								=       (
												    lowlink_of[w] if lowlink_of[w] < lowlink_of[v] else lowlink_of[v]
												)

						if lowlink_of[v] == index_of[v]:
									UpperCamelCase								=       []
									UpperCamelCase								=       stack.pop()
									UpperCamelCase								=       False
									component.append(_lowercase						)
									while w != v:
												UpperCamelCase								=       stack.pop()
												UpperCamelCase								=       False
												component.append(_lowercase						)
									components.append(_lowercase						)
						return index

			UpperCamelCase								=       []
			for v in range(_lowercase						):
						if index_of[v] == -1:
									strong_connect(_lowercase							,	0							,	_lowercase						)

			return components






def 				_lowercase     (		SCREAMING_SNAKE_CASE_ :		Union[str, Any]							,	SCREAMING_SNAKE_CASE_ :		List[Any]						):





			"""simple docstring"""




			UpperCamelCase								=       [[] for _ in range(_lowercase						)]
			for u, v in edges:
						g[u].append(_lowercase						)
			return g


if __name__ == "__main__":
			# Test
			__snake_case      = 7
			__snake_case      = [0, 0, 1, 2, 3, 3, 4, 4, 6]
			__snake_case      = [1, 3, 2, 0, 1, 4, 5, 6, 5]
			__snake_case      = [(u, v) for u, v in zip(source, target)]
			__snake_case      = create_graph(n_vertices, edges)

			assert [[5], [6], [4], [3, 2, 1, 0]] == tarjan(g)






from collections import OrderedDict
from typing import Mapping

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


_snake_case      = logging.get_logger(__name__)

_snake_case      = {
    '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/config.json''',
    '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/config.json''',
    '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/config.json''',
    '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/config.json''',
    '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json''',
    '''roberta-large-openai-detector''': '''https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json''',
}
class       _lowerCAmelCase  (		__magic_name__							):

 """simple docstring"""
 SCREAMING_SNAKE_CASE_				:					Dict       						="roberta"

 def __init__(						self			:			Union[str, Any]					, SCREAMING_SNAKE_CASE__			:			Tuple=5_02_65					, SCREAMING_SNAKE_CASE__			:			List[str]=7_68					, SCREAMING_SNAKE_CASE__			:			List[str]=12					, SCREAMING_SNAKE_CASE__			:			Any=12					, SCREAMING_SNAKE_CASE__			:			Tuple=30_72					, SCREAMING_SNAKE_CASE__			:			str="gelu"					, SCREAMING_SNAKE_CASE__			:			Union[str, Any]=0.1					, SCREAMING_SNAKE_CASE__			:			int=0.1					, SCREAMING_SNAKE_CASE__			:			int=5_12					, SCREAMING_SNAKE_CASE__			:			Optional[Any]=2					, SCREAMING_SNAKE_CASE__			:			Dict=0.02					, SCREAMING_SNAKE_CASE__			:			List[str]=1e-12					, SCREAMING_SNAKE_CASE__			:			Any=1					, SCREAMING_SNAKE_CASE__			:			Optional[Any]=0					, SCREAMING_SNAKE_CASE__			:			str=2					, SCREAMING_SNAKE_CASE__			:			Any="absolute"					, SCREAMING_SNAKE_CASE__			:			Any=True					, SCREAMING_SNAKE_CASE__			:			List[Any]=None					, **SCREAMING_SNAKE_CASE__			:			Optional[int]					, ):






      """simple docstring"""



      super().__init__(pad_token_id=SCREAMING_SNAKE_CASE__					, bos_token_id=SCREAMING_SNAKE_CASE__					, eos_token_id=SCREAMING_SNAKE_CASE__					, **SCREAMING_SNAKE_CASE__   )

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




class       _lowerCAmelCase  (		__magic_name__							):

 """simple docstring"""

 @property
 def      __lowerCAmelCase  (						self			:			Optional[int]   ):






      """simple docstring"""



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


