





"""simple docstring"""



from collections import OrderedDict
from typing import Mapping

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


a_					=     logging.get_logger(__name__)

a_					=     {
    """xlm-mlm-en-2048""": """https://huggingface.co/xlm-mlm-en-2048/resolve/main/config.json""",
    """xlm-mlm-ende-1024""": """https://huggingface.co/xlm-mlm-ende-1024/resolve/main/config.json""",
    """xlm-mlm-enfr-1024""": """https://huggingface.co/xlm-mlm-enfr-1024/resolve/main/config.json""",
    """xlm-mlm-enro-1024""": """https://huggingface.co/xlm-mlm-enro-1024/resolve/main/config.json""",
    """xlm-mlm-tlm-xnli15-1024""": """https://huggingface.co/xlm-mlm-tlm-xnli15-1024/resolve/main/config.json""",
    """xlm-mlm-xnli15-1024""": """https://huggingface.co/xlm-mlm-xnli15-1024/resolve/main/config.json""",
    """xlm-clm-enfr-1024""": """https://huggingface.co/xlm-clm-enfr-1024/resolve/main/config.json""",
    """xlm-clm-ende-1024""": """https://huggingface.co/xlm-clm-ende-1024/resolve/main/config.json""",
    """xlm-mlm-17-1280""": """https://huggingface.co/xlm-mlm-17-1280/resolve/main/config.json""",
    """xlm-mlm-100-1280""": """https://huggingface.co/xlm-mlm-100-1280/resolve/main/config.json""",
}






class 						__snake_case   (						SCREAMING_SNAKE_CASE__	):





 """simple docstring"""


 _lowerCamelCase								=	"""xlm"""
 _lowerCamelCase								=	{
     """hidden_size""": """emb_dim""",
     """num_attention_heads""": """n_heads""",
     """num_hidden_layers""": """n_layers""",
     """n_words""": """vocab_size""",  # For backward compatibility
 }

 def __init__(       self   ,		__lowerCamelCase=3_0145   ,		__lowerCamelCase=2048   ,		__lowerCamelCase=12   ,		__lowerCamelCase=16   ,		__lowerCamelCase=0.1   ,		__lowerCamelCase=0.1   ,		__lowerCamelCase=True   ,		__lowerCamelCase=False   ,		__lowerCamelCase=False   ,		__lowerCamelCase=False   ,		__lowerCamelCase=1   ,		__lowerCamelCase=True   ,		__lowerCamelCase=512   ,		__lowerCamelCase=2048**-0.5   ,		__lowerCamelCase=1e-1_2   ,		__lowerCamelCase=0.0_2   ,		__lowerCamelCase=0   ,		__lowerCamelCase=1   ,		__lowerCamelCase=2   ,		__lowerCamelCase=3   ,		__lowerCamelCase=5   ,		__lowerCamelCase=True   ,		__lowerCamelCase="first"   ,		__lowerCamelCase=True   ,		__lowerCamelCase=None   ,		__lowerCamelCase=True   ,		__lowerCamelCase=0.1   ,		__lowerCamelCase=5   ,		__lowerCamelCase=5   ,		__lowerCamelCase=0   ,		__lowerCamelCase=0   ,		__lowerCamelCase=2   ,		__lowerCamelCase=0   ,		**__lowerCamelCase   ,		):



     '''simple docstring'''




     __A       :		Union[str, Any]							=	vocab_size
     __A       :		List[Any]							=	emb_dim
     __A       :		Optional[Any]							=	n_layers
     __A       :		List[str]							=	n_heads
     __A       :		Union[str, Any]							=	dropout
     __A       :		Dict							=	attention_dropout
     __A       :		List[str]							=	gelu_activation
     __A       :		Tuple							=	sinusoidal_embeddings
     __A       :		int							=	causal
     __A       :		int							=	asm
     __A       :		List[str]							=	n_langs
     __A       :		Tuple							=	use_lang_emb
     __A       :		Union[str, Any]							=	layer_norm_eps
     __A       :		Optional[int]							=	bos_index
     __A       :		Tuple							=	eos_index
     __A       :		Union[str, Any]							=	pad_index
     __A       :		Optional[int]							=	unk_index
     __A       :		Optional[Any]							=	mask_index
     __A       :		Union[str, Any]							=	is_encoder
     __A       :		Any							=	max_position_embeddings
     __A       :		Any							=	embed_init_std
     __A       :		List[str]							=	init_std
     __A       :		List[str]							=	summary_type
     __A       :		Optional[Any]							=	summary_use_proj
     __A       :		int							=	summary_activation
     __A       :		Any							=	summary_proj_to_labels
     __A       :		List[str]							=	summary_first_dropout
     __A       :		Optional[Any]							=	start_n_top
     __A       :		Optional[Any]							=	end_n_top
     __A       :		Dict							=	mask_token_id
     __A       :		List[str]							=	lang_id

     if "n_words" in kwargs:
         __A       :		Optional[Any]							=	kwargs['''n_words''']

     super().__init__(pad_token_id=__lowerCamelCase   ,		bos_token_id=__lowerCamelCase   ,		**__lowerCamelCase    )






class 						__snake_case   (						SCREAMING_SNAKE_CASE__	):





 """simple docstring"""


 @property
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




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











"""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()))




