





'''simple docstring'''






from typing import Callable, Dict, Optional, Tuple

import torch
from torch import nn
from torch.distributions import (
    AffineTransform,
    Distribution,
    Independent,
    NegativeBinomial,
    Normal,
    StudentT,
    TransformedDistribution,
)
class 					__snake_case  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   def __init__(							self	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE=None	,		__SCREAMING_SNAKE_CASE=None	,		__SCREAMING_SNAKE_CASE=0       ):
    snake_case__     :					int    =  1.0 if scale is None else scale
    snake_case__     :					Dict    =  0.0 if loc is None else loc

    super().__init__(__SCREAMING_SNAKE_CASE	,		[AffineTransform(loc=self.loc	,		scale=self.scale	,		event_dim=__SCREAMING_SNAKE_CASE       )]       )

   @property
   def 		__UpperCamelCase						(							self       ):
    return self.base_dist.mean * self.scale + self.loc

   @property
   def 		__UpperCamelCase						(							self       ):
    return self.base_dist.variance * self.scale**2


   @property
   def 		__UpperCamelCase						(							self       ):
    return self.variance.sqrt()



class 					__snake_case  (					nn.Module							):






   '''simple docstring'''





   def __init__(							self	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE	,		**__SCREAMING_SNAKE_CASE       ):
    super().__init__(**__SCREAMING_SNAKE_CASE       )
    snake_case__     :					List[Any]    =  args_dim
    snake_case__     :					List[Any]    =  nn.ModuleList([nn.Linear(__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ) for dim in args_dim.values()]       )
    snake_case__     :					str    =  domain_map


   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE       ):
    snake_case__     :					Union[str, Any]    =  [proj(__SCREAMING_SNAKE_CASE       ) for proj in self.proj]

    return self.domain_map(*__SCREAMING_SNAKE_CASE       )



class 					__snake_case  (					nn.Module							):






   '''simple docstring'''





   def __init__(							self	,		__SCREAMING_SNAKE_CASE       ):
    super().__init__()
    snake_case__     :					Any    =  function


   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE	,		*__SCREAMING_SNAKE_CASE       ):
    return self.function(__SCREAMING_SNAKE_CASE	,		*__SCREAMING_SNAKE_CASE       )



class 					__snake_case  :






   '''simple docstring'''





   lowerCamelCase__    							=      42
   lowerCamelCase__    							=      42
   lowerCamelCase__    							=      42

   def __init__(							self	,		__SCREAMING_SNAKE_CASE = 1       ):
    snake_case__     :					List[Any]    =  dim
    snake_case__     :					List[str]    =  {k: dim * self.args_dim[k] for k in self.args_dim}

   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE       ):
    if self.dim == 1:
     return self.distribution_class(*__SCREAMING_SNAKE_CASE       )
    else:
     return Independent(self.distribution_class(*__SCREAMING_SNAKE_CASE       )	,		1       )

   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE = None	,		__SCREAMING_SNAKE_CASE = None	,		):
    snake_case__     :					List[str]    =  self._base_distribution(__SCREAMING_SNAKE_CASE       )
    if loc is None and scale is None:
     return distr
    else:
     return AffineTransformed(__SCREAMING_SNAKE_CASE	,		loc=__SCREAMING_SNAKE_CASE	,		scale=__SCREAMING_SNAKE_CASE	,		event_dim=self.event_dim       )

   @property
   def 		__UpperCamelCase						(							self       ):
    return () if self.dim == 1 else (self.dim,)

   @property
   def 		__UpperCamelCase						(							self       ):
    return len(self.event_shape       )

   @property
   def 		__UpperCamelCase						(							self       ):
    return 0.0

   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE       ):
    return ParameterProjection(
        in_features=__SCREAMING_SNAKE_CASE	,		args_dim=self.args_dim	,		domain_map=LambdaLayer(self.domain_map       )	,		)

   def 		__UpperCamelCase						(							self	,		*__SCREAMING_SNAKE_CASE       ):
    raise NotImplementedError()


   @staticmethod
   def 		__UpperCamelCase						(							__SCREAMING_SNAKE_CASE       ):
    return (x + torch.sqrt(torch.square(__SCREAMING_SNAKE_CASE       ) + 4.0       )) / 2.0



class 					__snake_case  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   lowerCamelCase__    							=      {"df": 1, "loc": 1, "scale": 1}
   lowerCamelCase__    							=      StudentT

   @classmethod
   def 		__UpperCamelCase						(							cls	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
    snake_case__     :					str    =  cls.squareplus(__SCREAMING_SNAKE_CASE       ).clamp_min(torch.finfo(scale.dtype       ).eps       )
    snake_case__     :					Dict    =  2.0 + cls.squareplus(__SCREAMING_SNAKE_CASE       )
    return df.squeeze(-1       ), loc.squeeze(-1       ), scale.squeeze(-1       )



class 					__snake_case  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   lowerCamelCase__    							=      {"loc": 1, "scale": 1}
   lowerCamelCase__    							=      Normal

   @classmethod
   def 		__UpperCamelCase						(							cls	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
    snake_case__     :					int    =  cls.squareplus(__SCREAMING_SNAKE_CASE       ).clamp_min(torch.finfo(scale.dtype       ).eps       )
    return loc.squeeze(-1       ), scale.squeeze(-1       )



class 					__snake_case  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   lowerCamelCase__    							=      {"total_count": 1, "logits": 1}
   lowerCamelCase__    							=      NegativeBinomial

   @classmethod
   def 		__UpperCamelCase						(							cls	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
    snake_case__     :					Optional[int]    =  cls.squareplus(__SCREAMING_SNAKE_CASE       )
    return total_count.squeeze(-1       ), logits.squeeze(-1       )

   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE       ):
    snake_case__  ,							snake_case__     :					List[str]    =  distr_args
    if self.dim == 1:
     return self.distribution_class(total_count=__SCREAMING_SNAKE_CASE	,		logits=__SCREAMING_SNAKE_CASE       )
    else:
     return Independent(self.distribution_class(total_count=__SCREAMING_SNAKE_CASE	,		logits=__SCREAMING_SNAKE_CASE       )	,		1       )


   def 		__UpperCamelCase						(							self	,		__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE = None	,		__SCREAMING_SNAKE_CASE = None       ):
    snake_case__  ,							snake_case__     :					Union[str, Any]    =  distr_args

    if scale is not None:
     # See scaling property of Gamma.
     logits += scale.log()

    return self._base_distribution((total_count, logits)       )






from __future__ import annotations

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

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

import requests





class    __A(					UpperCAmelCase							):

					def __init__(						self       :  Tuple ,       __UpperCamelCase       :  str ):
												super().__init__()
												lowerCamelCase_					=       []
												lowerCamelCase_					=       domain



					def  lowercase__   (						self       :  Any ,       __UpperCamelCase       :  str ,       __UpperCamelCase       :  list[tuple[str, str | None]] ):
												# Only parse the 'anchor' tag.
												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:
																																								lowerCamelCase_					=       parse.urljoin(self.domain ,       __UpperCamelCase )
																																								self.urls.append(__UpperCamelCase )



def   __lowerCAmelCase    (				UpperCAmelCase__					:   str							)	->     str:
							return ".".join(get_sub_domain_name(UpperCAmelCase__							).split("""."""							)[-2:]							)



def   __lowerCAmelCase    (				UpperCAmelCase__					:   str							)	->     str:
							return parse.urlparse(UpperCAmelCase__							).netloc



def   __lowerCAmelCase    (				UpperCAmelCase__					:   str = "https://github.com"							)	->     list[str]:
							lowerCamelCase_					=       get_domain_name(UpperCAmelCase__							)

							# Initialize the parser
							lowerCamelCase_					=       Parser(UpperCAmelCase__							)

							try:
														# Open URL
														lowerCamelCase_					=       requests.get(UpperCAmelCase__							)

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

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

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


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





