
import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class    __A(					UpperCAmelCase  ,		unittest.TestCase							):
					SCREAMING_SNAKE_CASE           =     LEDTokenizer
					SCREAMING_SNAKE_CASE           =     LEDTokenizerFast
					SCREAMING_SNAKE_CASE           =     True

					def  lowercase__   (						self       :  Any ):
												super().setUp()
												lowerCamelCase_					=       [
												    """l""",
												    """o""",
												    """w""",
												    """e""",
												    """r""",
												    """s""",
												    """t""",
												    """i""",
												    """d""",
												    """n""",
												    """\u0120""",
												    """\u0120l""",
												    """\u0120n""",
												    """\u0120lo""",
												    """\u0120low""",
												    """er""",
												    """\u0120lowest""",
												    """\u0120newer""",
												    """\u0120wider""",
												    """<unk>""",
												]
												lowerCamelCase_					=       dict(zip(__UpperCamelCase ,       range(len(__UpperCamelCase ) ) ) )
												lowerCamelCase_					=       ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
												lowerCamelCase_					=       {"""unk_token""": """<unk>"""}

												lowerCamelCase_					=       os.path.join(self.tmpdirname ,       VOCAB_FILES_NAMES["""vocab_file"""] )
												lowerCamelCase_					=       os.path.join(self.tmpdirname ,       VOCAB_FILES_NAMES["""merges_file"""] )
												with open(self.vocab_file ,       """w""" ,       encoding="""utf-8""" ) as fp:
																			fp.write(json.dumps(__UpperCamelCase ) + """\n""" )
												with open(self.merges_file ,       """w""" ,       encoding="""utf-8""" ) as fp:
																			fp.write("""\n""".join(__UpperCamelCase ) )

					def  lowercase__   (						self       :  List[str] ,       **__UpperCamelCase       :  Dict ):
												kwargs.update(self.special_tokens_map )
												return self.tokenizer_class.from_pretrained(self.tmpdirname ,       **__UpperCamelCase )

					def  lowercase__   (						self       :  Tuple ,       **__UpperCamelCase       :  List[str] ):
												kwargs.update(self.special_tokens_map )
												return self.rust_tokenizer_class.from_pretrained(self.tmpdirname ,       **__UpperCamelCase )

					def  lowercase__   (						self       :  Dict ,       __UpperCamelCase       :  List[Any] ):
												return "lower newer", "lower newer"

					@cached_property
					def  lowercase__   (						self       :  str ):
												return LEDTokenizer.from_pretrained("""allenai/led-base-16384""" )

					@cached_property
					def  lowercase__   (						self       :  Tuple ):
												return LEDTokenizerFast.from_pretrained("""allenai/led-base-16384""" )

					@require_torch
					def  lowercase__   (						self       :  Dict ):
												lowerCamelCase_					=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
												lowerCamelCase_					=       [0, 2_5_0, 2_5_1, 1_7_8_1_8, 1_3, 3_9_1_8_6, 1_9_3_8, 4, 2]

												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																			lowerCamelCase_					=       tokenizer(__UpperCamelCase ,       max_length=len(__UpperCamelCase ) ,       padding=__UpperCamelCase ,       return_tensors="""pt""" )
																			self.assertIsInstance(__UpperCamelCase ,       __UpperCamelCase )

																			self.assertEqual((2, 9) ,       batch.input_ids.shape )
																			self.assertEqual((2, 9) ,       batch.attention_mask.shape )
																			lowerCamelCase_					=       batch.input_ids.tolist()[0]
																			self.assertListEqual(__UpperCamelCase ,       __UpperCamelCase )

					@require_torch
					def  lowercase__   (						self       :  List[Any] ):
												lowerCamelCase_					=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																			lowerCamelCase_					=       tokenizer(__UpperCamelCase ,       padding=__UpperCamelCase ,       return_tensors="""pt""" )
																			self.assertIn("""input_ids""" ,       __UpperCamelCase )
																			self.assertIn("""attention_mask""" ,       __UpperCamelCase )
																			self.assertNotIn("""labels""" ,       __UpperCamelCase )
																			self.assertNotIn("""decoder_attention_mask""" ,       __UpperCamelCase )

					@require_torch
					def  lowercase__   (						self       :  List[str] ):
												lowerCamelCase_					=       [
												    """Summary of the text.""",
												    """Another summary.""",
												]
												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																			lowerCamelCase_					=       tokenizer(text_target=__UpperCamelCase ,       max_length=3_2 ,       padding="""max_length""" ,       return_tensors="""pt""" )
																			self.assertEqual(3_2 ,       targets["""input_ids"""].shape[1] )

					@require_torch
					def  lowercase__   (						self       :  int ):
												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																			lowerCamelCase_					=       tokenizer(
																			    ["""I am a small frog""" * 1_0_2_4, """I am a small frog"""] ,       padding=__UpperCamelCase ,       truncation=__UpperCamelCase ,       return_tensors="""pt""" )
																			self.assertIsInstance(__UpperCamelCase ,       __UpperCamelCase )
																			self.assertEqual(batch.input_ids.shape ,       (2, 5_1_2_2) )

					@require_torch
					def  lowercase__   (						self       :  List[str] ):
												lowerCamelCase_					=       ["""A long paragraph for summarization."""]
												lowerCamelCase_					=       [
												    """Summary of the text.""",
												]
												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																			lowerCamelCase_					=       tokenizer(__UpperCamelCase ,       return_tensors="""pt""" )
																			lowerCamelCase_					=       tokenizer(text_target=__UpperCamelCase ,       return_tensors="""pt""" )
																			lowerCamelCase_					=       inputs["""input_ids"""]
																			lowerCamelCase_					=       targets["""input_ids"""]
																			self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item() )
																			self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item() )
																			self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item() )
																			self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item() )

					@require_torch
					def  lowercase__   (						self       :  Tuple ):
												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																			lowerCamelCase_					=       ["""Summary of the text.""", """Another summary."""]
																			lowerCamelCase_					=       [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

																			lowerCamelCase_					=       tokenizer(__UpperCamelCase ,       padding=__UpperCamelCase )
																			lowerCamelCase_					=       [[0] * len(__UpperCamelCase ) for x in encoded_output["""input_ids"""]]
																			lowerCamelCase_					=       tokenizer.pad(__UpperCamelCase )
																			self.assertSequenceEqual(outputs["""global_attention_mask"""] ,       __UpperCamelCase )

					def  lowercase__   (						self       :  int ):
												pass



					def  lowercase__   (						self       :  str ):
												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																			with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})''' ):
																										lowerCamelCase_					=       self.rust_tokenizer_class.from_pretrained(__UpperCamelCase ,       **__UpperCamelCase )
																										lowerCamelCase_					=       self.tokenizer_class.from_pretrained(__UpperCamelCase ,       **__UpperCamelCase )
																										lowerCamelCase_					=       """A, <mask> AllenNLP sentence."""
																										lowerCamelCase_					=       tokenizer_r.encode_plus(__UpperCamelCase ,       add_special_tokens=__UpperCamelCase ,       return_token_type_ids=__UpperCamelCase )
																										lowerCamelCase_					=       tokenizer_p.encode_plus(__UpperCamelCase ,       add_special_tokens=__UpperCamelCase ,       return_token_type_ids=__UpperCamelCase )
																										self.assertEqual(sum(tokens_r["""token_type_ids"""] ) ,       sum(tokens_p["""token_type_ids"""] ) )
																										self.assertEqual(
																										    sum(tokens_r["""attention_mask"""] ) / len(tokens_r["""attention_mask"""] ) ,       sum(tokens_p["""attention_mask"""] ) / len(tokens_p["""attention_mask"""] ) ,       )

																										lowerCamelCase_					=       tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""] )
																										lowerCamelCase_					=       tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""] )
																										self.assertSequenceEqual(tokens_p["""input_ids"""] ,       [0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2] )
																										self.assertSequenceEqual(tokens_r["""input_ids"""] ,       [0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2] )

																										self.assertSequenceEqual(
																										    __UpperCamelCase ,       ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""] )
																										self.assertSequenceEqual(
																										    __UpperCamelCase ,       ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""] )







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)))





