




'''simple docstring'''


import copy
from typing import Dict, List, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


_snake_case : Any  				=						{
    'facebook/mask2former-swin-small-coco-instance': (
        'https://huggingface.co/facebook/mask2former-swin-small-coco-instance/blob/main/config.json'
    )
    # See all Mask2Former models at https://huggingface.co/models?filter=mask2former
}

_snake_case : Optional[int]  				=						logging.get_logger(__name__)

class      A       (						_a       ):
							lowercase_							     =							'mask2former'
							lowercase_							     =							['swin']
							lowercase_							     =							{'hidden_size': 'hidden_dim'}







							def __init__(    self			:    Any				,     lowerCAmelCase_			:    Optional[Dict] = None				,     lowerCAmelCase_			:    int = 2_56				,     lowerCAmelCase_			:    int = 2_56				,     lowerCAmelCase_			:    int = 2_56				,     lowerCAmelCase_			:    int = 10_24				,     lowerCAmelCase_			:    str = "relu"				,     lowerCAmelCase_			:    int = 6				,     lowerCAmelCase_			:    int = 10				,     lowerCAmelCase_			:    int = 8				,     lowerCAmelCase_			:    float = 0.0				,     lowerCAmelCase_			:    int = 20_48				,     lowerCAmelCase_			:    bool = False				,     lowerCAmelCase_			:    bool = False				,     lowerCAmelCase_			:    int = 4				,     lowerCAmelCase_			:    int = 2_55				,     lowerCAmelCase_			:    int = 1_00				,     lowerCAmelCase_			:    float = 0.1				,     lowerCAmelCase_			:    float = 2.0				,     lowerCAmelCase_			:    float = 5.0				,     lowerCAmelCase_			:    float = 5.0				,     lowerCAmelCase_			:    int = 1_25_44				,     lowerCAmelCase_			:    float = 3.0				,     lowerCAmelCase_			:    float = 0.7_5				,     lowerCAmelCase_			:    float = 0.0_2				,     lowerCAmelCase_			:    float = 1.0				,     lowerCAmelCase_			:    bool = True				,     lowerCAmelCase_			:    List[int] = [4, 8, 16, 32]				,     lowerCAmelCase_			:    bool = None				,     **lowerCAmelCase_			:    int				,     )     ->				Optional[Any]:


														"""simple docstring"""


														if backbone_config is None:
																					logger.info('''`backbone_config` is `None`. Initializing the config with the default `Swin` backbone.'''   )
																					_a      	=							CONFIG_MAPPING['''swin'''](
																					    image_size=2_24				,     in_channels=3				,     patch_size=4				,     embed_dim=96				,     depths=[2, 2, 18, 2]				,     num_heads=[3, 6, 12, 24]				,     window_size=7				,     drop_path_rate=0.3				,     use_absolute_embeddings=lowerCAmelCase_				,     out_features=['''stage1''', '''stage2''', '''stage3''', '''stage4''']				,     )

														if isinstance(lowerCAmelCase_				,     lowerCAmelCase_   ):
																					_a      	=							backbone_config.pop('''model_type'''   )
																					_a      	=							CONFIG_MAPPING[backbone_model_type]
																					_a      	=							config_class.from_dict(lowerCAmelCase_   )

														# verify that the backbone is supported
														if backbone_config.model_type not in self.backbones_supported:
																					logger.warning_once(
																					    F'Backbone {backbone_config.model_type} is not a supported model and may not be compatible with Mask2Former. '
																					    F'Supported model types: {",".join(self.backbones_supported   )}'   )

														_a      	=							backbone_config
														_a      	=							feature_size
														_a      	=							mask_feature_size
														_a      	=							hidden_dim
														_a      	=							encoder_feedforward_dim
														_a      	=							activation_function
														_a      	=							encoder_layers
														_a      	=							decoder_layers
														_a      	=							num_attention_heads
														_a      	=							dropout
														_a      	=							dim_feedforward
														_a      	=							pre_norm
														_a      	=							enforce_input_projection
														_a      	=							common_stride
														_a      	=							ignore_value
														_a      	=							num_queries
														_a      	=							no_object_weight
														_a      	=							class_weight
														_a      	=							mask_weight
														_a      	=							dice_weight
														_a      	=							train_num_points
														_a      	=							oversample_ratio
														_a      	=							importance_sample_ratio
														_a      	=							init_std
														_a      	=							init_xavier_std
														_a      	=							use_auxiliary_loss
														_a      	=							feature_strides
														_a      	=							output_auxiliary_logits
														_a      	=							decoder_layers

														super().__init__(**lowerCAmelCase_   )







							@classmethod
							def   __lowerCAmelCase     (    cls			:    Any				,     lowerCAmelCase_			:    PretrainedConfig				,     **lowerCAmelCase_			:    List[str]   )     ->				Optional[int]:


														"""simple docstring"""


														return cls(
														    backbone_config=lowerCAmelCase_				,     **lowerCAmelCase_				,     )







							def   __lowerCAmelCase     (    self			:    int   )     ->				Dict[str, any]:


														"""simple docstring"""


														_a      	=							copy.deepcopy(self.__dict__   )
														_a      	=							self.backbone_config.to_dict()
														_a      	=							self.__class__.model_type
														return output





'''simple docstring'''



from collections import namedtuple

import requests
from lxml import html  # type: ignore

A__						:   Tuple				=    namedtuple("""covid_data""", """cases deaths recovered""")



def      UpperCAmelCase__   (      UpperCAmelCase_       :							str = "https://www.worldometers.info/coronavirus/"				)	->						covid_data:
     __lowerCamelCase  :      Union[str, Any]														=						'//div[@class = "maincounter-number"]/span/text()'
     return covid_data(*html.fromstring(requests.get(UpperCAmelCase_				).content				).xpath(UpperCAmelCase_				)				)


A__						:   str				=    """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()))






