


"""simple docstring"""






from __future__ import annotations

__snake_case							:     List[Any]   =					'Muhammad Umer Farooq'
__snake_case							:     Tuple   =					'MIT'
__snake_case							:     Union[str, Any]   =					'1.0.0'
__snake_case							:     Union[str, Any]   =					'Muhammad Umer Farooq'
__snake_case							:     List[str]   =					'contact@muhammadumerfarooq.me'
__snake_case							:     int   =					'Alpha'

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

import requests



class     A__     (						_UpperCamelCase							):




	'''simple docstring'''





	def __init__(  self:	Dict ,    _SCREAMING_SNAKE_CASE:	str)       -> Optional[Any]:

				"""simple docstring"""

				super().__init__()
				__lowerCAmelCase   :						list[str]				= []
				__lowerCAmelCase   :						Tuple				= domain







	def 							_SCREAMING_SNAKE_CASE     (  self:	List[Any] ,    _SCREAMING_SNAKE_CASE:	str ,    _SCREAMING_SNAKE_CASE:	list[tuple[str, str | None]])       -> Optional[Any]:

				"""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:
																__lowerCAmelCase   :						Optional[Any]				= parse.urljoin(self.domain ,    _SCREAMING_SNAKE_CASE)
																self.urls.append(_SCREAMING_SNAKE_CASE)






def     _lowercase       (						__snake_case			)		->     List[str]:
			return ".".join(get_sub_domain_name(lowerCamelCase__			).split("."			)[-2:]			)


def     _lowercase       (						__snake_case			)		->     List[Any]:
			return parse.urlparse(lowerCamelCase__			).netloc


def     _lowercase       (						__snake_case = "https://github.com"			)		->     Union[str, Any]:
			__lowerCAmelCase   :						List[str]				= get_domain_name(lowerCamelCase__			)

			# Initialize the parser
			__lowerCAmelCase   :						Tuple				= Parser(lowerCamelCase__			)

			try:
						# Open URL
						__lowerCAmelCase   :						Any				= requests.get(lowerCamelCase__			)

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

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

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


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




"""simple docstring"""






import argparse

import torch

from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert


logging.set_verbosity_info()


def     _lowercase       (						__snake_case      ,__snake_case      ,__snake_case			)		->     Tuple:
			# Initialise PyTorch model
			__lowerCAmelCase   :						Any				= AlbertConfig.from_json_file(__snake_case			)
			print(F"""Building PyTorch model from configuration: {config}"""			)
			__lowerCAmelCase   :						str				= AlbertForPreTraining(__snake_case			)

			# Load weights from tf checkpoint
			load_tf_weights_in_albert(__snake_case      ,__snake_case      ,__snake_case			)

			# Save pytorch-model
			print(F"""Save PyTorch model to {pytorch_dump_path}"""			)
			torch.save(model.state_dict()      ,__snake_case			)


if __name__ == "__main__":
	__snake_case							:     Union[str, Any]   =					argparse.ArgumentParser()
	# Required parameters
	parser.add_argument(
	    '--tf_checkpoint_path', default=None, type=str, required=True, help='Path to the TensorFlow checkpoint path.'
	)
	parser.add_argument(
	    '--albert_config_file',
	    default=None,
	    type=str,
	    required=True,
	    help=(
	        'The config json file corresponding to the pre-trained ALBERT model. \n'
	        'This specifies the model architecture.'
	    ),
	)
	parser.add_argument(
	    '--pytorch_dump_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
	)
	__snake_case							:     str   =					parser.parse_args()
	convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.albert_config_file, args.pytorch_dump_path)