





import copy
from collections import OrderedDict
from typing import Dict, Mapping

from packaging import version

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


snake_case_           =  logging.get_logger(__name__)

snake_case_           =  {
    '''facebook/detr-resnet-50''': '''https://huggingface.co/facebook/detr-resnet-50/resolve/main/config.json''',
    # See all DETR models at https://huggingface.co/models?filter=detr
}

class 		SCREAMING_SNAKE_CASE__    (	_a  ):
      A_						:    int							=   """detr"""
      A_						:    str							=   ["""past_key_values"""]
      A_						:    Tuple							=   {
          """hidden_size""": """d_model""",
          """num_attention_heads""": """encoder_attention_heads""",
      }


      def __init__(self	:				int    ,      a__	:				Tuple=True    ,      a__	:				Tuple=None    ,      a__	:				Optional[int]=3    ,      a__	:				List[str]=100    ,      a__	:				Optional[int]=6    ,      a__	:				Optional[int]=2048    ,      a__	:				Any=8    ,      a__	:				List[Any]=6    ,      a__	:				Optional[Any]=2048    ,      a__	:				Union[str, Any]=8    ,      a__	:				List[Any]=0.0    ,      a__	:				Dict=0.0    ,      a__	:				Optional[Any]=True    ,      a__	:				Tuple="relu"    ,      a__	:				Any=256    ,      a__	:				List[Any]=0.1    ,      a__	:				List[Any]=0.0    ,      a__	:				Optional[int]=0.0    ,      a__	:				Dict=0.0_2    ,      a__	:				Dict=1.0    ,      a__	:				Union[str, Any]=False    ,      a__	:				List[str]="sine"    ,      a__	:				Union[str, Any]="resnet50"    ,      a__	:				str=True    ,      a__	:				Union[str, Any]=False    ,      a__	:				Optional[int]=1    ,      a__	:				Tuple=5    ,      a__	:				Optional[int]=2    ,      a__	:				Tuple=1    ,      a__	:				List[Any]=1    ,      a__	:				Optional[int]=5    ,      a__	:				Union[str, Any]=2    ,      a__	:				Optional[Any]=0.1    ,      **a__	:				Dict    ,      ):





         """simple docstring"""



         if backbone_config is not None and use_timm_backbone:
            raise ValueError('''You can\'t specify both `backbone_config` and `use_timm_backbone`.'''				)

         if not use_timm_backbone:
            if backbone_config is None:
               logger.info('''`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.'''				)
               __snake_case								=       CONFIG_MAPPING["""resnet"""](out_features=['''stage4''']				)
            elif isinstance(__lowerCamelCase    ,      __lowerCamelCase				):
               __snake_case								=       backbone_config.get('''model_type'''				)
               __snake_case								=       CONFIG_MAPPING[backbone_model_type]
               __snake_case								=       config_class.from_dict(__lowerCamelCase				)
            # set timm attributes to None
            __snake_case								=       None, None, None

         __snake_case								=       use_timm_backbone
         __snake_case								=       backbone_config
         __snake_case								=       num_channels
         __snake_case								=       num_queries
         __snake_case								=       d_model
         __snake_case								=       encoder_ffn_dim
         __snake_case								=       encoder_layers
         __snake_case								=       encoder_attention_heads
         __snake_case								=       decoder_ffn_dim
         __snake_case								=       decoder_layers
         __snake_case								=       decoder_attention_heads
         __snake_case								=       dropout
         __snake_case								=       attention_dropout
         __snake_case								=       activation_dropout
         __snake_case								=       activation_function
         __snake_case								=       init_std
         __snake_case								=       init_xavier_std
         __snake_case								=       encoder_layerdrop
         __snake_case								=       decoder_layerdrop
         __snake_case								=       encoder_layers
         __snake_case								=       auxiliary_loss
         __snake_case								=       position_embedding_type
         __snake_case								=       backbone
         __snake_case								=       use_pretrained_backbone
         __snake_case								=       dilation
         # Hungarian matcher
         __snake_case								=       class_cost
         __snake_case								=       bbox_cost
         __snake_case								=       giou_cost
         # Loss coefficients
         __snake_case								=       mask_loss_coefficient
         __snake_case								=       dice_loss_coefficient
         __snake_case								=       bbox_loss_coefficient
         __snake_case								=       giou_loss_coefficient
         __snake_case								=       eos_coefficient
         super().__init__(is_encoder_decoder=__lowerCamelCase    ,      **__lowerCamelCase				)


      @property
      def        a			(self	:				Any				):





         """simple docstring"""



         return self.encoder_attention_heads


      @property
      def        a			(self	:				List[str]				):





         """simple docstring"""



         return self.d_model


      @classmethod
      def        a			(cls	:				str    ,      a__	:				PretrainedConfig    ,      **a__	:				str				):





         """simple docstring"""



         return cls(backbone_config=__lowerCamelCase    ,      **__lowerCamelCase				)


      def        a			(self	:				List[Any]				):





         """simple docstring"""



         __snake_case								=       copy.deepcopy(self.__dict__				)
         if output["backbone_config"] is not None:
            __snake_case								=       self.backbone_config.to_dict()
         __snake_case								=       self.__class__.model_type
         return output






class 		SCREAMING_SNAKE_CASE__    (	_a  ):
      A_						:    List[str]							=   version.parse('1.11'  )


      @property
      def        a			(self	:				Any				):





         """simple docstring"""



         return OrderedDict(
             [
                 ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
                 ('''pixel_mask''', {0: '''batch'''}),
             ]				)


      @property
      def        a			(self	:				Optional[int]				):





         """simple docstring"""



         return 1E-5


      @property
      def        a			(self	:				Any				):





         """simple docstring"""



         return 12








from __future__ import annotations

snake_case_           =      'Muhammad Umer Farooq'
snake_case_           =      'MIT'
snake_case_           =      '1.0.0'
snake_case_           =      'Muhammad Umer Farooq'
snake_case_           =      'contact@muhammadumerfarooq.me'
snake_case_           =      'Alpha'

import re
from html.parser import HTMLParser
from urllib import parse

import requests

class 		SCREAMING_SNAKE_CASE__    (	_UpperCAmelCase  ):


      def __init__(self	:				Dict    ,      a__	:				str				):





         """simple docstring"""



         super().__init__()
         __snake_case								=       []
         __snake_case								=       domain


      def        a			(self	:				Tuple    ,      a__	:				str    ,      a__	:				list[tuple[str, str | None]]				):





         """simple docstring"""



         if tag == "a":
            # Check the list of defined attributes.
            for name, value in attrs:
               # If href is defined, and not empty nor # print it.
               if name == "href" and value != "#" and value != "":
                  # If not already in urls.
                  if value not in self.urls:
                     __snake_case								=       parse.urljoin(self.domain    ,      a__				)
                     self.urls.append(a__				)






def lowerCamelCase__   (							snake_case_     :  str	)				->    str:
   return ".".join(get_sub_domain_name(snake_case_	).split('''.'''	)[-2:]	)






def lowerCamelCase__   (							snake_case_     :  str	)				->    str:
   return parse.urlparse(snake_case_	).netloc






def lowerCamelCase__   (							snake_case_     :  str = "https://github.com"	)				->    list[str]:
   __snake_case								=       get_domain_name(snake_case_	)

   # Initialize the parser
   __snake_case								=       Parser(snake_case_	)

   try:
      # Open URL
      __snake_case								=       requests.get(snake_case_	)

      # pass the raw HTML to the parser to get links
      parser.feed(r.text	)

      # Get links and loop through
      __snake_case								=       set()
      for link in parser.urls:
         # open URL.
         # read = requests.get(link)
         try:
            __snake_case								=       requests.get(snake_case_	)
            # Get the valid email.
            __snake_case								=       re.findall('''[a-zA-Z0-9]+@''' + domain	,				read.text	)
            # If not in list then append it.
            for email in emails:
               valid_emails.add(snake_case_	)
         except ValueError:
            pass
   except ValueError:
      raise SystemExit(1	)

   # Finally return a sorted list of email addresses with no duplicates.
   return sorted(snake_case_	)


if __name__ == "__main__":
    snake_case_           =      emails_from_url('https://github.com')
    print(F'{len(emails)} emails found:')
    print('\n'.join(sorted(emails)))

