






import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)
from transformers.utils import is_sentencepiece_available


if is_sentencepiece_available():
				from transformers.models.mam_aaa.tokenization_mam_aaa import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


if is_sentencepiece_available():
				A        =     get_tests_dir('fixtures/test_sentencepiece.model')


if is_torch_available():
				from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

A        =     12_8022
A        =     12_8028


@require_sentencepiece
class 							__a							(  __A ,	unittest.TestCase						):





		'''simple docstring'''



		UpperCAmelCase__      :				Dict				    =						MaMaaaTokenizer
		UpperCAmelCase__      :				List[Any]				    =						False
		UpperCAmelCase__      :				Tuple				    =						False
		UpperCAmelCase__      :				Union[str, Any]				    =						True


		def   __snake_case			(						self       ):
						super().setUp()

						SCREAMING_SNAKE_CASE_   :	Dict													=   ['</s>', '<unk>', '▁This', '▁is', '▁a', '▁t', 'est', '\u0120', '<pad>']
						SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   dict(zip(UpperCamelCase__ ,    range(len(UpperCamelCase__       )       )       )       )
						SCREAMING_SNAKE_CASE_   :	List[Any]													=   Path(self.tmpdirname       )
						save_json(UpperCamelCase__ ,    save_dir / VOCAB_FILES_NAMES['vocab_file']       )
						if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
										copyfile(UpperCamelCase__ ,    save_dir / VOCAB_FILES_NAMES['spm_file']       )

						SCREAMING_SNAKE_CASE_   :	Any													=   MaMaaaTokenizer.from_pretrained(self.tmpdirname       )
						tokenizer.save_pretrained(self.tmpdirname       )


		def   __snake_case			(						self ,    **UpperCamelCase__       ):
						return MaMaaaTokenizer.from_pretrained(self.tmpdirname ,    **UpperCamelCase__       )


		def   __snake_case			(						self ,    UpperCamelCase__       ):
						return (
						    "This is a test",
						    "This is a test",
						)


		def   __snake_case			(						self       ):
						SCREAMING_SNAKE_CASE_   :	List[str]													=   '</s>'
						SCREAMING_SNAKE_CASE_   :	Dict													=   0

						self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCamelCase__       ) ,    UpperCamelCase__       )
						self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCamelCase__       ) ,    UpperCamelCase__       )


		def   __snake_case			(						self       ):
						SCREAMING_SNAKE_CASE_   :	List[Any]													=   self.get_tokenizer()
						SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   list(tokenizer.get_vocab().keys()       )

						self.assertEqual(vocab_keys[0] ,    '</s>'       )
						self.assertEqual(vocab_keys[1] ,    '<unk>'       )
						self.assertEqual(vocab_keys[-1] ,    '<s>'       )
						self.assertEqual(len(UpperCamelCase__       ) ,    tokenizer.vocab_size + len(tokenizer.get_added_vocab()       )       )


		@unittest.skip('Skip this test while all models are still to be uploaded.'       )
		def   __snake_case			(						self       ):
						pass


		def   __snake_case			(						self       ):
						SCREAMING_SNAKE_CASE_   :	int													=   self.get_tokenizer()

						SCREAMING_SNAKE_CASE_   :	Optional[int]													=   tokenizer.tokenize('This is a test'       )
						self.assertListEqual(UpperCamelCase__ ,    ['▁This', '▁is', '▁a', '▁t', 'est']       )

						self.assertListEqual(
						    tokenizer.convert_tokens_to_ids(UpperCamelCase__       ) ,    [2, 3, 4, 5, 6] ,    )

						SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]       )
						self.assertListEqual(UpperCamelCase__ ,    ['▁This', '▁is', '▁a', '▁t', 'est']       )

						SCREAMING_SNAKE_CASE_   :	Any													=   tokenizer.convert_tokens_to_string(UpperCamelCase__       )
						self.assertEqual(UpperCamelCase__ ,    'This is a test'       )






		@slow
		def   __snake_case			(						self       ):
						# fmt: off
						SCREAMING_SNAKE_CASE_   :	str													=   {'input_ids': [[128022, 110108, 397, 11, 38272, 2247, 124811, 285, 18105, 1586, 207, 7, 39534, 4428, 397, 1019, 18105, 1586, 207, 7, 41337, 16786, 241, 7, 20214, 17, 125690, 10398, 7, 44378, 58069, 68342, 7798, 7343, 11, 299, 33310, 4, 158, 37350, 94077, 4569, 299, 33310, 90, 4, 52840, 290, 4, 31270, 112, 299, 682, 4, 52840, 39953, 14079, 193, 52519, 90894, 17894, 120697, 11, 40445, 551, 17, 1019, 52519, 90894, 17756, 963, 11, 40445, 480, 17, 9792, 1120, 5173, 1393, 6240, 16786, 241, 120996, 28, 1245, 1393, 118240, 11123, 1019, 93612, 2691, 10618, 98058, 120409, 1928, 279, 4, 40683, 367, 178, 207, 1019, 103, 103121, 506, 65296, 5, 2], [128022, 21217, 367, 117, 125450, 128, 719, 7, 7308, 40, 93612, 12669, 1116, 16704, 71, 17785, 3699, 15592, 35, 144, 9584, 241, 11943, 713, 950, 799, 2247, 88427, 150, 149, 118813, 120706, 1019, 106906, 81518, 28, 1224, 22799, 397, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [128022, 1658, 123311, 5155, 5578, 4722, 279, 14947, 2366, 1120, 1197, 14, 1348, 9232, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
						# fmt: on

						self.tokenizer_integration_test_util(
						    expected_encoding=UpperCamelCase__ ,    model_name='facebook/m2m100_418M' ,    revision='c168bae485c864188cf9aa0e4108b0b6934dc91e' ,    )






@require_torch
@require_sentencepiece
@require_tokenizers
class 							__a							(  unittest.TestCase						):





		'''simple docstring'''



		UpperCAmelCase__      :				Optional[Any]				    =						"""facebook/m2m100_418M"""
		UpperCAmelCase__      :				Optional[int]				    =						[
		    """In my opinion, there are two levels of response from the French government.""",
		    """NSA Affair Emphasizes Complete Lack of Debate on Intelligence""",
		]
		UpperCAmelCase__      :				Optional[Any]				    =						[
		    """Selon moi, il y a deux niveaux de réponse de la part du gouvernement français.""",
		    """L'affaire NSA souligne l'absence totale de débat sur le renseignement""",
		]

		# fmt: off
		UpperCAmelCase__      :				Optional[Any]				    =						[EN_CODE, 593, 1949, 115781, 4, 71586, 4234, 60633, 126233, 432, 123808, 15592, 1197, 117132, 120618, 5, 2]


		@classmethod
		def   __snake_case			(						cls       ):
						SCREAMING_SNAKE_CASE_   :	MaMaaaTokenizer													=   MaMaaaTokenizer.from_pretrained(
						    cls.checkpoint_name ,    src_lang='en' ,    tgt_lang='fr'       )
						SCREAMING_SNAKE_CASE_   :	Any													=   1
						return cls


		def   __snake_case			(						self       ):
						self.assertEqual(self.tokenizer.get_lang_id('ar'       ) ,    128006       )
						self.assertEqual(self.tokenizer.get_lang_id('en'       ) ,    128022       )
						self.assertEqual(self.tokenizer.get_lang_id('ro'       ) ,    128076       )
						self.assertEqual(self.tokenizer.get_lang_id('mr'       ) ,    128063       )


		def   __snake_case			(						self       ):
						SCREAMING_SNAKE_CASE_   :	Any													=   self.tokenizer.get_vocab()
						self.assertEqual(len(UpperCamelCase__       ) ,    self.tokenizer.vocab_size       )
						self.assertEqual(vocab['<unk>'] ,    3       )
						self.assertIn(self.tokenizer.get_lang_token('en'       ) ,    UpperCamelCase__       )


		def   __snake_case			(						self       ):
						SCREAMING_SNAKE_CASE_   :	str													=   'en'
						SCREAMING_SNAKE_CASE_   :	str													=   self.tokenizer.batch_encode_plus(self.src_text       ).input_ids[0]
						self.assertListEqual(self.expected_src_tokens ,    UpperCamelCase__       )


		def   __snake_case			(						self       ):
						self.assertIn(UpperCamelCase__ ,    self.tokenizer.all_special_ids       )
						# fmt: off
						SCREAMING_SNAKE_CASE_   :	Any													=   [FR_CODE, 5364, 82, 8642, 4, 294, 47, 8, 14028, 136, 3286, 9706, 6, 90797, 6, 144012, 162, 88128, 30061, 5, 2]
						# fmt: on
						SCREAMING_SNAKE_CASE_   :	str													=   self.tokenizer.decode(UpperCamelCase__ ,    skip_special_tokens=UpperCamelCase__       )
						SCREAMING_SNAKE_CASE_   :	Dict													=   self.tokenizer.decode(generated_ids[1:] ,    skip_special_tokens=UpperCamelCase__       )
						self.assertEqual(UpperCamelCase__ ,    UpperCamelCase__       )
						self.assertNotIn(self.tokenizer.eos_token ,    UpperCamelCase__       )


		def   __snake_case			(						self       ):
						SCREAMING_SNAKE_CASE_   :	Any													=   tempfile.mkdtemp()
						SCREAMING_SNAKE_CASE_   :	List[str]													=   self.tokenizer.lang_token_to_id
						self.tokenizer.save_pretrained(UpperCamelCase__       )
						SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   MaMaaaTokenizer.from_pretrained(UpperCamelCase__       )
						self.assertDictEqual(new_tok.lang_token_to_id ,    UpperCamelCase__       )


		@require_torch
		def   __snake_case			(						self       ):
						SCREAMING_SNAKE_CASE_   :	int													=   'en'
						SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   'fr'

						SCREAMING_SNAKE_CASE_   :	List[Any]													=   self.tokenizer(self.src_text ,    text_target=self.tgt_text ,    padding=UpperCamelCase__ ,    return_tensors='pt'       )

						SCREAMING_SNAKE_CASE_   :	int													=   shift_tokens_right(
						    batch['labels'] ,    self.tokenizer.pad_token_id ,    self.tokenizer.eos_token_id       )

						for k in batch:
										SCREAMING_SNAKE_CASE_   :	Tuple													=   batch[k].tolist()
						# batch = {k: v.tolist() for k,v in batch.items()}
						# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
						# batch.decoder_inputs_ids[0][0] ==
						assert batch.input_ids[1][0] == EN_CODE
						assert batch.input_ids[1][-1] == 2
						assert batch.labels[1][0] == FR_CODE
						assert batch.labels[1][-1] == 2
						assert batch.decoder_input_ids[1][:2] == [2, FR_CODE]


		@require_torch
		def   __snake_case			(						self       ):
						SCREAMING_SNAKE_CASE_   :	str													=   'mr'
						self.assertListEqual(self.tokenizer.prefix_tokens ,    [self.tokenizer.get_lang_id('mr'       )]       )
						self.assertListEqual(self.tokenizer.suffix_tokens ,    [self.tokenizer.eos_token_id]       )

						SCREAMING_SNAKE_CASE_   :	str													=   'zh'
						self.assertListEqual(self.tokenizer.prefix_tokens ,    [self.tokenizer.get_lang_id('zh'       )]       )
						self.assertListEqual(self.tokenizer.suffix_tokens ,    [self.tokenizer.eos_token_id]       )


		@require_torch
		def   __snake_case			(						self       ):
						SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   'mr'
						self.tokenizer._switch_to_target_mode()
						self.assertListEqual(self.tokenizer.prefix_tokens ,    [self.tokenizer.get_lang_id('mr'       )]       )
						self.assertListEqual(self.tokenizer.suffix_tokens ,    [self.tokenizer.eos_token_id]       )
						self.tokenizer._switch_to_input_mode()
						self.assertListEqual(self.tokenizer.prefix_tokens ,    [self.tokenizer.get_lang_id(self.tokenizer.src_lang       )]       )

						SCREAMING_SNAKE_CASE_   :	str													=   'zh'
						self.tokenizer._switch_to_target_mode()
						self.assertListEqual(self.tokenizer.prefix_tokens ,    [self.tokenizer.get_lang_id('zh'       )]       )
						self.assertListEqual(self.tokenizer.suffix_tokens ,    [self.tokenizer.eos_token_id]       )
						self.tokenizer._switch_to_input_mode()
						self.assertListEqual(self.tokenizer.prefix_tokens ,    [self.tokenizer.get_lang_id(self.tokenizer.src_lang       )]       )






		@require_torch
		def   __snake_case			(						self       ):
						SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   self.tokenizer._build_translation_inputs('A test' ,    return_tensors='pt' ,    src_lang='en' ,    tgt_lang='ar'       )

						self.assertEqual(
						    nested_simplify(UpperCamelCase__       ) ,    {
						        # en_XX, A, test, EOS
						        'input_ids': [[128022, 58, 4183, 2]],
						        'attention_mask': [[1, 1, 1, 1]],
						        # ar_AR
						        'forced_bos_token_id': 128006,
						    } ,    )







from datetime import datetime

import requests
from bsa import BeautifulSoup

if __name__ == "__main__":
				A        =			input('Enter image url: ').strip()
				print(f"""Downloading image from {url} ...""")
				A        =			BeautifulSoup(requests.get(url).content, 'html.parser')
				# The image URL is in the content field of the first meta tag with property og:image
				A        =			soup.find('meta', {'property': 'og:image'})['content']
				A        =			requests.get(image_url).content
				A        =			f"""{datetime.now():%Y-%m-%d_%H:%M:%S}.jpg"""
				with open(file_name, 'wb') as fp:
								fp.write(image_data)
				print(f"""Done. Image saved to disk as {file_name}.""")