




"""simple docstring"""

import functools
import operator

from ...configuration_utils import PretrainedConfig
from ...utils import logging


_lowerCamelCase  :			Any        =       logging.get_logger(__name__)

_lowerCamelCase  :			str        =       {
    'asapp/sew-tiny-100k': 'https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json',
    # See all SEW models at https://huggingface.co/models?filter=sew
}

class        lowercase      (    __UpperCAmelCase):
				__lowerCAmelCase    :    Tuple         =   """sew"""







				def __init__(							self   :					Optional[int]      ,     _lowerCamelCase   :					List[str]=32      ,     _lowerCamelCase   :					Dict=7_68      ,     _lowerCamelCase   :					List[str]=12      ,     _lowerCamelCase   :					int=12      ,     _lowerCamelCase   :					str=30_72      ,     _lowerCamelCase   :					Union[str, Any]=2      ,     _lowerCamelCase   :					List[Any]="gelu"      ,     _lowerCamelCase   :					Optional[Any]=0.1      ,     _lowerCamelCase   :					Tuple=0.1      ,     _lowerCamelCase   :					List[Any]=0.1      ,     _lowerCamelCase   :					Tuple=0.0      ,     _lowerCamelCase   :					Dict=0.1      ,     _lowerCamelCase   :					Optional[Any]=0.1      ,     _lowerCamelCase   :					Any=0.02      ,     _lowerCamelCase   :					Dict=1E-5      ,     _lowerCamelCase   :					Tuple="group"      ,     _lowerCamelCase   :					List[Any]="gelu"      ,     _lowerCamelCase   :					Optional[Any]=(64, 1_28, 1_28, 1_28, 1_28, 2_56, 2_56, 2_56, 2_56, 5_12, 5_12, 5_12, 5_12)      ,     _lowerCamelCase   :					List[str]=(5, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1)      ,     _lowerCamelCase   :					int=(10, 3, 1, 3, 1, 3, 1, 3, 1, 2, 1, 2, 1)      ,     _lowerCamelCase   :					Optional[int]=False      ,     _lowerCamelCase   :					Optional[int]=1_28      ,     _lowerCamelCase   :					Optional[int]=16      ,     _lowerCamelCase   :					Dict=True      ,     _lowerCamelCase   :					List[str]=0.05      ,     _lowerCamelCase   :					Tuple=10      ,     _lowerCamelCase   :					List[str]=2      ,     _lowerCamelCase   :					Union[str, Any]=0.0      ,     _lowerCamelCase   :					List[Any]=10      ,     _lowerCamelCase   :					Optional[Any]=0      ,     _lowerCamelCase   :					Union[str, Any]="mean"      ,     _lowerCamelCase   :					Dict=False      ,     _lowerCamelCase   :					Dict=False      ,     _lowerCamelCase   :					Dict=2_56      ,     _lowerCamelCase   :					Union[str, Any]=0      ,     _lowerCamelCase   :					Optional[Any]=1      ,     _lowerCamelCase   :					Dict=2      ,     **_lowerCamelCase   :					Any      ,     ):



					"""simple docstring"""

					super().__init__(**_lowerCamelCase      ,     pad_token_id=_lowerCamelCase      ,     bos_token_id=_lowerCamelCase      ,     eos_token_id=_lowerCamelCase       )
					A_  :				Tuple	   =		hidden_size
					A_  :				int	   =		feat_extract_norm
					A_  :				List[Any]	   =		feat_extract_activation
					A_  :				Union[str, Any]	   =		list(_lowerCamelCase       )
					A_  :				List[Any]	   =		list(_lowerCamelCase       )
					A_  :				Optional[Any]	   =		list(_lowerCamelCase       )
					A_  :				int	   =		conv_bias
					A_  :				Dict	   =		num_conv_pos_embeddings
					A_  :				Union[str, Any]	   =		num_conv_pos_embedding_groups
					A_  :				Tuple	   =		len(self.conv_dim       )
					A_  :				int	   =		num_hidden_layers
					A_  :				Tuple	   =		intermediate_size
					A_  :				Any	   =		squeeze_factor
					A_  :				int	   =		hidden_act
					A_  :				int	   =		num_attention_heads
					A_  :				Tuple	   =		hidden_dropout
					A_  :				Union[str, Any]	   =		attention_dropout
					A_  :				Tuple	   =		activation_dropout
					A_  :				Tuple	   =		feat_proj_dropout
					A_  :				Union[str, Any]	   =		final_dropout
					A_  :				Optional[Any]	   =		layerdrop
					A_  :				Optional[Any]	   =		layer_norm_eps
					A_  :				str	   =		initializer_range
					A_  :				int	   =		vocab_size

					if (
					    (len(self.conv_stride       ) != self.num_feat_extract_layers)
					    or (len(self.conv_kernel       ) != self.num_feat_extract_layers)
					    or (len(self.conv_dim       ) != self.num_feat_extract_layers)
					):
						raise ValueError(
						    '''Configuration for convolutional layers is incorrect.'''
						    '''It is required that `len(config.conv_dim)` == `len(config.conv_stride)` == `len(config.conv_kernel)`,'''
						    F"""but is `len(config.conv_dim) = {len(self.conv_dim       )}`, `len(config.conv_stride)"""
						    F"""= {len(self.conv_stride       )}`, `len(config.conv_kernel) = {len(self.conv_kernel       )}`."""       )

					# fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
					A_  :				Dict	   =		apply_spec_augment
					A_  :				Union[str, Any]	   =		mask_time_prob
					A_  :				Dict	   =		mask_time_length
					A_  :				Union[str, Any]	   =		mask_time_min_masks
					A_  :				int	   =		mask_feature_prob
					A_  :				List[Any]	   =		mask_feature_length
					A_  :				List[Any]	   =		mask_feature_min_masks

					# ctc loss
					A_  :				int	   =		ctc_loss_reduction
					A_  :				str	   =		ctc_zero_infinity

					# sequence classification
					A_  :				Dict	   =		use_weighted_layer_sum
					A_  :				Tuple	   =		classifier_proj_size







				@property
				def 					a_  (							self   :					Tuple       ):



					"""simple docstring"""

					return functools.reduce(operator.mul      ,     self.conv_stride      ,     1       )











"""simple docstring"""

import requests
from bsa import BeautifulSoup

def 		lowercase_      (		_UpperCAmelCase = "https://www.worldometers.info/coronavirus"	):




	"""simple docstring"""






	A_  :				str	   =		BeautifulSoup(requests.get(_UpperCAmelCase	).text  ,      '''html.parser'''	)
	A_  :				Union[str, Any]	   =		soup.findAll('''h1'''	)
	A_  :				Union[str, Any]	   =		soup.findAll('''div'''  ,      {'''class''': '''maincounter-number'''}	)
	keys += soup.findAll('''span'''  ,      {'''class''': '''panel-title'''}	)
	values += soup.findAll('''div'''  ,      {'''class''': '''number-table-main'''}	)
	return {key.text.strip(): value.text.strip() for key, value in zip(_UpperCAmelCase  ,      _UpperCAmelCase	)}


if __name__ == "__main__":
		print('\033[1m' + 'COVID-19 Status of the World' + '\033[0m\n')
		for key, value in world_covidaa_stats().items():
				print(f'{key}\n{value}\n')





