





'''simple docstring'''




from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

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


if TYPE_CHECKING:
							from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


__UpperCAmelCase			    =    logging.get_logger(__name__)

__UpperCAmelCase			    =    {
    """microsoft/deberta-v2-xlarge""": """https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/config.json""",
    """microsoft/deberta-v2-xxlarge""": """https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/config.json""",
    """microsoft/deberta-v2-xlarge-mnli""": (
        """https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/config.json"""
    ),
    """microsoft/deberta-v2-xxlarge-mnli""": (
        """https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/config.json"""
    ),
}




class 			UpperCamelCase__ ( __SCREAMING_SNAKE_CASE       ):




					"""simple docstring"""
					SCREAMING_SNAKE_CASE__            =     '''deberta-v2'''


					def __init__(		self							:       Union[str, Any]	,		lowerCamelCase_							:       Optional[Any]=12_81_00	,		lowerCamelCase_							:       Optional[int]=15_36	,		lowerCamelCase_							:       Union[str, Any]=24	,		lowerCamelCase_							:       int=24	,		lowerCamelCase_							:       Dict=61_44	,		lowerCamelCase_							:       List[Any]="gelu"	,		lowerCamelCase_							:       Optional[Any]=0.1	,		lowerCamelCase_							:       List[str]=0.1	,		lowerCamelCase_							:       Union[str, Any]=5_12	,		lowerCamelCase_							:       str=0	,		lowerCamelCase_							:       Tuple=0.02	,		lowerCamelCase_							:       List[Any]=1e-7	,		lowerCamelCase_							:       List[str]=False	,		lowerCamelCase_							:       List[Any]=-1	,		lowerCamelCase_							:       List[Any]=0	,		lowerCamelCase_							:       Optional[Any]=True	,		lowerCamelCase_							:       Any=None	,		lowerCamelCase_							:       Union[str, Any]=0	,		lowerCamelCase_							:       List[str]="gelu"	,		**lowerCamelCase_							:       Optional[int]	,		):

							'''simple docstring'''



							super().__init__(**UpperCAmelCase_		)

							SCREAMING_SNAKE_CASE      :							Union[str, Any]						=       hidden_size
							SCREAMING_SNAKE_CASE      :							List[str]						=       num_hidden_layers
							SCREAMING_SNAKE_CASE      :							Dict						=       num_attention_heads
							SCREAMING_SNAKE_CASE      :							Tuple						=       intermediate_size
							SCREAMING_SNAKE_CASE      :							Dict						=       hidden_act
							SCREAMING_SNAKE_CASE      :							int						=       hidden_dropout_prob
							SCREAMING_SNAKE_CASE      :							Optional[Any]						=       attention_probs_dropout_prob
							SCREAMING_SNAKE_CASE      :							List[Any]						=       max_position_embeddings
							SCREAMING_SNAKE_CASE      :							Union[str, Any]						=       type_vocab_size
							SCREAMING_SNAKE_CASE      :							List[Any]						=       initializer_range
							SCREAMING_SNAKE_CASE      :							List[Any]						=       relative_attention
							SCREAMING_SNAKE_CASE      :							List[str]						=       max_relative_positions
							SCREAMING_SNAKE_CASE      :							str						=       pad_token_id
							SCREAMING_SNAKE_CASE      :							Optional[Any]						=       position_biased_input

							# Backwards compatibility
							if type(UpperCAmelCase_		) == str:
									SCREAMING_SNAKE_CASE      :							Any						=       [x.strip() for x in pos_att_type.lower().split("""|"""		)]

							SCREAMING_SNAKE_CASE      :							Tuple						=       pos_att_type
							SCREAMING_SNAKE_CASE      :							Optional[Any]						=       vocab_size
							SCREAMING_SNAKE_CASE      :							Tuple						=       layer_norm_eps

							SCREAMING_SNAKE_CASE      :							Union[str, Any]						=       kwargs.get("""pooler_hidden_size"""	,		UpperCAmelCase_		)
							SCREAMING_SNAKE_CASE      :							Optional[Any]						=       pooler_dropout
							SCREAMING_SNAKE_CASE      :							Union[str, Any]						=       pooler_hidden_act







class 			UpperCamelCase__ ( __SCREAMING_SNAKE_CASE       ):




					"""simple docstring"""


					@property
					def lowerCamelCase_       (		self							:       Optional[Any]		):

							'''simple docstring'''



							if self.task == "multiple-choice":
									SCREAMING_SNAKE_CASE      :							Tuple						=       {0: "batch", 1: "choice", 2: "sequence"}
							else:
									SCREAMING_SNAKE_CASE      :							Dict						=       {0: "batch", 1: "sequence"}
							if self._config.type_vocab_size > 0:
									return OrderedDict(
									    [("""input_ids""", dynamic_axis), ("""attention_mask""", dynamic_axis), ("""token_type_ids""", dynamic_axis)]		)
							else:
									return OrderedDict([("""input_ids""", dynamic_axis), ("""attention_mask""", dynamic_axis)]		)


					@property
					def lowerCamelCase_       (		self							:       Tuple		):

							'''simple docstring'''



							return 12



					def lowerCamelCase_       (		self							:       Optional[int]	,		lowerCamelCase_							:       Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"]	,		lowerCamelCase_							:       int = -1	,		lowerCamelCase_							:       int = -1	,		lowerCamelCase_							:       int = -1	,		lowerCamelCase_							:       bool = False	,		lowerCamelCase_							:       Optional["TensorType"] = None	,		lowerCamelCase_							:       int = 3	,		lowerCamelCase_							:       int = 40	,		lowerCamelCase_							:       int = 40	,		lowerCamelCase_							:       "PreTrainedTokenizerBase" = None	,		):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE      :							List[Any]						=       super().generate_dummy_inputs(preprocessor=UpperCAmelCase_	,		framework=UpperCAmelCase_		)
							if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
									del dummy_inputs["token_type_ids"]
							return dummy_inputs










from collections import defaultdict

from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst





def      lowerCAmelCase_ (       )     ->		Optional[int]:







  """simple docstring"""





  lowerCamelCase__  ,					lowerCamelCase__:      int			  =9, 14  # noqa: F841
  lowerCamelCase__:      List[Any]			  =[
      [0, 1, 4],
      [0, 7, 8],
      [1, 2, 8],
      [7, 8, 7],
      [7, 6, 1],
      [2, 8, 2],
      [8, 6, 6],
      [2, 3, 7],
      [2, 5, 4],
      [6, 5, 2],
      [3, 5, 14],
      [3, 4, 9],
      [5, 4, 10],
      [1, 7, 11],
  ]

  lowerCamelCase__:      List[str]			  =defaultdict(__a		)
  for nodea, nodea, cost in edges:
    adjancency[nodea].append([nodea, cost]		)
    adjancency[nodea].append([nodea, cost]		)

  lowerCamelCase__:      List[str]			  =mst(__a		)

  lowerCamelCase__:      Union[str, Any]			  =[
      [7, 6, 1],
      [2, 8, 2],
      [6, 5, 2],
      [0, 1, 4],
      [2, 5, 4],
      [2, 3, 7],
      [0, 7, 8],
      [3, 4, 9],
  ]

  for answer in expected:
    lowerCamelCase__:      Optional[int]			  =tuple(answer[:2]		)
    lowerCamelCase__:      List[Any]			  =tuple(edge[::-1]		)
    assert edge in result or reverse in result

