





'''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


lowerCAmelCase_ : Union[str, Any]	  =       logging.get_logger(__name__)

lowerCAmelCase_ : Dict	  =       {
    "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__  ):
	lowerCAmelCase__       :      Any										=    "deberta-v2"







	def __init__(					self      : str			,			lowerCamelCase      : int=1_2_8_1_0_0			,			lowerCamelCase      : Dict=1_5_3_6			,			lowerCamelCase      : Optional[int]=2_4			,			lowerCamelCase      : Dict=2_4			,			lowerCamelCase      : Union[str, Any]=6_1_4_4			,			lowerCamelCase      : List[Any]="gelu"			,			lowerCamelCase      : str=0.1			,			lowerCamelCase      : str=0.1			,			lowerCamelCase      : Optional[Any]=5_1_2			,			lowerCamelCase      : Tuple=0			,			lowerCamelCase      : int=0.02			,			lowerCamelCase      : Optional[int]=1e-7			,			lowerCamelCase      : Tuple=False			,			lowerCamelCase      : Optional[int]=-1			,			lowerCamelCase      : int=0			,			lowerCamelCase      : Union[str, Any]=True			,			lowerCamelCase      : Union[str, Any]=None			,			lowerCamelCase      : Optional[int]=0			,			lowerCamelCase      : Optional[int]="gelu"			,			**lowerCamelCase      : Union[str, Any]			,			):




				'''simple docstring'''
				super().__init__(**__lowerCamelCase		)

				a__	 =			hidden_size
				a__	 =			num_hidden_layers
				a__	 =			num_attention_heads
				a__	 =			intermediate_size
				a__	 =			hidden_act
				a__	 =			hidden_dropout_prob
				a__	 =			attention_probs_dropout_prob
				a__	 =			max_position_embeddings
				a__	 =			type_vocab_size
				a__	 =			initializer_range
				a__	 =			relative_attention
				a__	 =			max_relative_positions
				a__	 =			pad_token_id
				a__	 =			position_biased_input

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

				a__	 =			pos_att_type
				a__	 =			vocab_size
				a__	 =			layer_norm_eps

				a__	 =			kwargs.get("pooler_hidden_size"			,			__lowerCamelCase		)
				a__	 =			pooler_dropout
				a__	 =			pooler_hidden_act






class    UpperCamelCase__	(		SCREAMING_SNAKE_CASE__  ):







	@property
	def     __a (					self      : str		):




				'''simple docstring'''




				if self.task == "multiple-choice":
							a__	 =			{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
				else:
							a__	 =			{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     __a (					self      : List[str]		):




				'''simple docstring'''
				return 1_2







	def     __a (					self      : Any			,			lowerCamelCase      : Optional[int]			,			lowerCamelCase      : List[str] = -1			,			lowerCamelCase      : Optional[int] = -1			,			lowerCamelCase      : Any = -1			,			lowerCamelCase      : List[str] = False			,			lowerCamelCase      : str = None			,			lowerCamelCase      : str = 3			,			lowerCamelCase      : Dict = 4_0			,			lowerCamelCase      : Any = 4_0			,			lowerCamelCase      : List[str] = None			,			):




				'''simple docstring'''
				a__	 =			super().generate_dummy_inputs(preprocessor=__lowerCamelCase			,			framework=__lowerCamelCase		)
				if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
							del dummy_inputs["token_type_ids"]
				return dummy_inputs










"""simple docstring"""



from collections import namedtuple

import requests
from lxml import html  # type: ignore

a_					=     namedtuple("""covid_data""", """cases deaths recovered""")







def 						__lowercase	(  snake_case_    :    str = "https://www.worldometers.info/coronavirus/"		)  ->covid_data:



    '''simple docstring'''







    __A       :		List[str]							=	'''//div[@class = "maincounter-number"]/span/text()'''
    return covid_data(*html.fromstring(requests.get(snake_case_		).content		).xpath(snake_case_		)		)


a_					=     """Total COVID-19 cases in the world: {}
Total deaths due to COVID-19 in the world: {}
Total COVID-19 patients recovered in the world: {}"""




print(fmt.format(*covid_stats()))




