'''simple docstring'''




import os
from typing import List, Optional, Union

from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
from ..auto import AutoTokenizer




class     a__      (   UpperCAmelCase__ ):
     lowerCamelCase  :     Union[str, Any]							=["image_processor", "tokenizer"]
     lowerCamelCase  :     int							="BlipImageProcessor"
     lowerCamelCase  :     int							="AutoTokenizer"






     def __init__( self		:		Dict  ,				a		:		Any  ,				a		:		Union[str, Any]  ,				a		:		str    ):





         """simple docstring"""



         super().__init__(a  ,				a    )

         # add QFormer tokenizer
         __lowerCamelCase		=  qformer_tokenizer






     def __call__( self		:		Union[str, Any]  ,				a		:		ImageInput = None  ,				a		:		Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None  ,				a		:		bool = True  ,				a		:		Union[bool, str, PaddingStrategy] = False  ,				a		:		Union[bool, str, TruncationStrategy] = None  ,				a		:		Optional[int] = None  ,				a		:		int = 0  ,				a		:		Optional[int] = None  ,				a		:		Optional[bool] = None  ,				a		:		bool = False  ,				a		:		bool = False  ,				a		:		bool = False  ,				a		:		bool = False  ,				a		:		bool = False  ,				a		:		bool = True  ,				a		:		Optional[Union[str, TensorType]] = None  ,				**a		:		List[Any]  ,				):





         """simple docstring"""



         if images is None and text is None:
             raise ValueError('''You have to specify at least images or text.'''    )

         __lowerCamelCase		=  BatchFeature()

         if text is not None:
             __lowerCamelCase		=  self.tokenizer(
                 text=a  ,				add_special_tokens=a  ,				padding=a  ,				truncation=a  ,				max_length=a  ,				stride=a  ,				pad_to_multiple_of=a  ,				return_attention_mask=a  ,				return_overflowing_tokens=a  ,				return_special_tokens_mask=a  ,				return_offsets_mapping=a  ,				return_token_type_ids=a  ,				return_length=a  ,				verbose=a  ,				return_tensors=a  ,				**a  ,				)
             encoding.update(a    )
             __lowerCamelCase		=  self.qformer_tokenizer(
                 text=a  ,				add_special_tokens=a  ,				padding=a  ,				truncation=a  ,				max_length=a  ,				stride=a  ,				pad_to_multiple_of=a  ,				return_attention_mask=a  ,				return_overflowing_tokens=a  ,				return_special_tokens_mask=a  ,				return_offsets_mapping=a  ,				return_token_type_ids=a  ,				return_length=a  ,				verbose=a  ,				return_tensors=a  ,				**a  ,				)
             __lowerCamelCase		=  qformer_text_encoding.pop('''input_ids'''    )
             __lowerCamelCase		=  qformer_text_encoding.pop('''attention_mask'''    )

         if images is not None:
             __lowerCamelCase		=  self.image_processor(a  ,				return_tensors=a    )
             encoding.update(a    )

         return encoding






     def    SCREAMING_SNAKE_CASE__   ( self		:		Dict  ,				*a		:		Dict  ,				**a		:		List[str]    ):





         """simple docstring"""



         return self.tokenizer.batch_decode(*a  ,				**a    )






     def    SCREAMING_SNAKE_CASE__   ( self		:		Any  ,				*a		:		List[str]  ,				**a		:		Tuple    ):





         """simple docstring"""



         return self.tokenizer.decode(*a  ,				**a    )






     @property
     # Copied from transformers.models.blip.processing_blip.BlipProcessor.model_input_names
     def    SCREAMING_SNAKE_CASE__   ( self		:		Optional[Any]    ):





         """simple docstring"""



         __lowerCamelCase		=  self.tokenizer.model_input_names
         __lowerCamelCase		=  self.image_processor.model_input_names
         return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names    )    )






     def    SCREAMING_SNAKE_CASE__   ( self		:		Dict  ,				a		:		str  ,				**a		:		List[Any]    ):





         """simple docstring"""



         if os.path.isfile(a    ):
             raise ValueError(f"""Provided path ({save_directory}) should be a directory, not a file"""    )
         os.makedirs(a  ,				exist_ok=a    )
         __lowerCamelCase		=  os.path.join(a  ,				'''qformer_tokenizer'''    )
         self.qformer_tokenizer.save_pretrained(a    )
         return super().save_pretrained(a  ,				**a    )






     @classmethod
     def    SCREAMING_SNAKE_CASE__   ( cls		:		str  ,				a		:		List[str]  ,				**a		:		Dict    ):





         """simple docstring"""



         __lowerCamelCase		=  AutoTokenizer.from_pretrained(a  ,				subfolder='''qformer_tokenizer'''    )
         __lowerCamelCase		=  cls._get_arguments_from_pretrained(a  ,				**a    )
         args.append(a    )
         return cls(*a    )








from __future__ import annotations

UpperCAmelCase__				   =		"Muhammad Umer Farooq"
UpperCAmelCase__				   =		"MIT"
UpperCAmelCase__				   =		"1.0.0"
UpperCAmelCase__				   =		"Muhammad Umer Farooq"
UpperCAmelCase__				   =		"contact@muhammadumerfarooq.me"
UpperCAmelCase__				   =		"Alpha"

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

import requests






class 		lowercase_					(	lowercase   ):






      '''simple docstring'''




      def __init__(      self      :						Union[str, Any] ,					__UpperCAmelCase      :						str  )    ->None:




       """simple docstring"""


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







      def       __lowerCAmelCase					(      self      :						List[str] ,					__UpperCAmelCase      :						str ,					__UpperCAmelCase      :						list[tuple[str, str | None]]  )    ->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:
           a		  =      parse.urljoin(self.domain ,					__UpperCAmelCase  )
           self.urls.append(__UpperCAmelCase  )
def 						_a    (      a :str )							->			str:
 return ".".join(get_sub_domain_name(a ).split('''.''' )[-2:] )
def 						_a    (      a :str )							->			str:
 return parse.urlparse(a ).netloc
def 						_a    (      a :str = "https://github.com" )							->			list[str]:
 a		  =      get_domain_name(a )

 # Initialize the parser
 a		  =      Parser(a )

 try:
  # Open URL
  a		  =      requests.get(a )

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

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

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


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


