



import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


_snake_case	=						get_tests_dir("fixtures/test_sentencepiece.model")

if is_torch_available():
						from transformers.models.mbart.modeling_mbart import shift_tokens_right

_snake_case	=						25_0004
_snake_case	=						25_0020



@require_sentencepiece
@require_tokenizers
class 						UpperCAmelCase_					( snake_case__     ,      unittest.TestCase):
							lowerCamelCase__         =	MBartaaTokenizer
							lowerCamelCase__         =	MBartaaTokenizerFast
							lowerCamelCase__         =	True
							lowerCamelCase__         =	True







							def      snake_case__   (     self):

														'''simple docstring'''

														super().setUp()

														# We have a SentencePiece fixture for testing
														_lowerCAmelCase  :							Dict				     =					MBartaaTokenizer(lowercase_,    src_lang="en_XX",    tgt_lang="ro_RO",    keep_accents=lowercase_)
														tokenizer.save_pretrained(self.tmpdirname)







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							List[str]				     =					"<s>"
														_lowerCAmelCase  :							Any				     =					0

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







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							int				     =					list(self.get_tokenizer().get_vocab().keys())

														self.assertEqual(vocab_keys[0],    "<s>")
														self.assertEqual(vocab_keys[1],    "<pad>")
														self.assertEqual(vocab_keys[-1],    "<mask>")
														self.assertEqual(len(lowercase_),    1054)







							def      snake_case__   (     self):

														'''simple docstring'''

														self.assertEqual(self.get_tokenizer().vocab_size,    1054)







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Any				     =					MBartaaTokenizer(lowercase_,    src_lang="en_XX",    tgt_lang="ro_RO",    keep_accents=lowercase_)

														_lowerCAmelCase  :							List[str]				     =					tokenizer.tokenize("This is a test")
														self.assertListEqual(lowercase_,    ["▁This", "▁is", "▁a", "▁t", "est"])

														self.assertListEqual(
														    tokenizer.convert_tokens_to_ids(lowercase_),    [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]],    )

														_lowerCAmelCase  :							List[str]				     =					tokenizer.tokenize("I was born in 92000, and this is falsé.")
														self.assertListEqual(
														    lowercase_,    [SPIECE_UNDERLINE + "I", SPIECE_UNDERLINE + "was", SPIECE_UNDERLINE + "b", "or", "n", SPIECE_UNDERLINE + "in", SPIECE_UNDERLINE + "", "9", "2", "0", "0", "0", ",", SPIECE_UNDERLINE + "and", SPIECE_UNDERLINE + "this", SPIECE_UNDERLINE + "is", SPIECE_UNDERLINE + "f", "al", "s", "é", "."],    )
														_lowerCAmelCase  :							Tuple				     =					tokenizer.convert_tokens_to_ids(lowercase_)
														self.assertListEqual(
														    lowercase_,    [
														        value + tokenizer.fairseq_offset
														        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
														    ],    )

														_lowerCAmelCase  :							List[str]				     =					tokenizer.convert_ids_to_tokens(lowercase_)
														self.assertListEqual(
														    lowercase_,    [SPIECE_UNDERLINE + "I", SPIECE_UNDERLINE + "was", SPIECE_UNDERLINE + "b", "or", "n", SPIECE_UNDERLINE + "in", SPIECE_UNDERLINE + "", "<unk>", "2", "0", "0", "0", ",", SPIECE_UNDERLINE + "and", SPIECE_UNDERLINE + "this", SPIECE_UNDERLINE + "is", SPIECE_UNDERLINE + "f", "al", "s", "<unk>", "."],    )







							@slow
							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							int				     =					{"input_ids": [[25_0004, 1_1062, 8_2772, 7, 15, 8_2772, 538, 5_1529, 237, 1_7198, 1290, 206, 9, 21_5175, 1314, 136, 1_7198, 1290, 206, 9, 5_6359, 42, 12_2009, 9, 1_6466, 16, 8_7344, 4537, 9, 4717, 7_8381, 6, 15_9958, 7, 15, 2_4480, 618, 4, 527, 2_2693, 5428, 4, 2777, 2_4480, 9874, 4, 4_3523, 594, 4, 803, 1_8392, 3_3189, 18, 4, 4_3523, 2_4447, 1_2399, 100, 2_4955, 8_3658, 9626, 14_4057, 15, 839, 2_2335, 16, 136, 2_4955, 8_3658, 8_3479, 15, 3_9102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 12_2009, 11_5774, 23, 805, 1328, 4_6876, 7, 136, 5_3894, 1940, 4_2227, 4_1159, 1_7721, 823, 425, 4, 2_7512, 9_8722, 206, 136, 5531, 4970, 919, 1_7336, 5, 2], [25_0004, 2_0080, 618, 83, 8_2775, 47, 479, 9, 1517, 73, 5_3894, 333, 8_0581, 11_0117, 1_8811, 5256, 1295, 51, 15_2526, 297, 7986, 390, 12_4416, 538, 3_5431, 214, 98, 1_5044, 2_5737, 136, 7108, 4_3701, 23, 756, 13_5355, 7, 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], [25_0004, 581, 6_3773, 11_9455, 6, 14_7797, 8_8203, 7, 645, 70, 21, 3285, 1_0269, 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]], "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, 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], [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]]}  # noqa: E501
														# fmt: on

														self.tokenizer_integration_test_util(
														    expected_encoding=lowercase_,    model_name="facebook/mbart-large-50",    revision="d3913889c59cd5c9e456b269c376325eabad57e2",    )







							def      snake_case__   (     self):

														'''simple docstring'''

														if not self.test_slow_tokenizer:
																					# as we don't have a slow version, we can't compare the outputs between slow and fast versions
																					return

														_lowerCAmelCase  :							Union[str, Any]				     =					(self.rust_tokenizer_class, "hf-internal-testing/tiny-random-mbart50", {})
														for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																					with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"):
																												_lowerCAmelCase  :							Dict				     =					self.rust_tokenizer_class.from_pretrained(lowercase_,    **lowercase_)
																												_lowerCAmelCase  :							Tuple				     =					self.tokenizer_class.from_pretrained(lowercase_,    **lowercase_)

																												_lowerCAmelCase  :							List[Any]				     =					tempfile.mkdtemp()

																												_lowerCAmelCase  :							Optional[int]				     =					tokenizer_r.save_pretrained(lowercase_)
																												_lowerCAmelCase  :							Optional[Any]				     =					tokenizer_p.save_pretrained(lowercase_)

																												# Checks it save with the same files + the tokenizer.json file for the fast one
																												self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files))
																												_lowerCAmelCase  :							Any				     =					tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f)
																												self.assertSequenceEqual(lowercase_,    lowercase_)

																												# Checks everything loads correctly in the same way
																												_lowerCAmelCase  :							List[Any]				     =					tokenizer_r.from_pretrained(lowercase_)
																												_lowerCAmelCase  :							str				     =					tokenizer_p.from_pretrained(lowercase_)

																												# Check special tokens are set accordingly on Rust and Python
																												for key in tokenizer_pp.special_tokens_map:
																																			self.assertTrue(hasattr(lowercase_,    lowercase_))
																																			# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
																																			# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

																												shutil.rmtree(lowercase_)

																												# Save tokenizer rust, legacy_format=True
																												_lowerCAmelCase  :							List[Any]				     =					tempfile.mkdtemp()

																												_lowerCAmelCase  :							List[Any]				     =					tokenizer_r.save_pretrained(lowercase_,    legacy_format=lowercase_)
																												_lowerCAmelCase  :							List[Any]				     =					tokenizer_p.save_pretrained(lowercase_)

																												# Checks it save with the same files
																												self.assertSequenceEqual(lowercase_,    lowercase_)

																												# Checks everything loads correctly in the same way
																												_lowerCAmelCase  :							List[str]				     =					tokenizer_r.from_pretrained(lowercase_)
																												_lowerCAmelCase  :							Union[str, Any]				     =					tokenizer_p.from_pretrained(lowercase_)

																												# Check special tokens are set accordingly on Rust and Python
																												for key in tokenizer_pp.special_tokens_map:
																																			self.assertTrue(hasattr(lowercase_,    lowercase_))

																												shutil.rmtree(lowercase_)

																												# Save tokenizer rust, legacy_format=False
																												_lowerCAmelCase  :							Union[str, Any]				     =					tempfile.mkdtemp()

																												_lowerCAmelCase  :							Optional[Any]				     =					tokenizer_r.save_pretrained(lowercase_,    legacy_format=lowercase_)
																												_lowerCAmelCase  :							List[str]				     =					tokenizer_p.save_pretrained(lowercase_)

																												# Checks it saved the tokenizer.json file
																												self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files))

																												# Checks everything loads correctly in the same way
																												_lowerCAmelCase  :							Tuple				     =					tokenizer_r.from_pretrained(lowercase_)
																												_lowerCAmelCase  :							List[str]				     =					tokenizer_p.from_pretrained(lowercase_)

																												# Check special tokens are set accordingly on Rust and Python
																												for key in tokenizer_pp.special_tokens_map:
																																			self.assertTrue(hasattr(lowercase_,    lowercase_))

																												shutil.rmtree(lowercase_)



@require_torch
@require_sentencepiece
@require_tokenizers
class 						UpperCAmelCase_					( unittest.TestCase):
							lowerCamelCase__         =	'facebook/mbart-large-50-one-to-many-mmt'
							lowerCamelCase__         =	[
							    ' UN Chief Says There Is No Military Solution in Syria',
							    ' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.',
							]
							lowerCamelCase__         =	[
							    'Şeful ONU declară că nu există o soluţie militară în Siria',
							    'Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei'
							    ' pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor'
							    ' face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.',
							]
							lowerCamelCase__         =	[EN_CODE, 8274, 127873, 25916, 7, 8622, 2071, 438, 67485, 53, 187895, 23, 51712, 2]







							@classmethod
							def      snake_case__   (     cls):

														'''simple docstring'''

														_lowerCAmelCase  :							MBartaaTokenizer				     =					MBartaaTokenizer.from_pretrained(
														    cls.checkpoint_name,    src_lang="en_XX",    tgt_lang="ro_RO")
														_lowerCAmelCase  :							Dict				     =					1
														return cls







							def      snake_case__   (     self):

														'''simple docstring'''

														self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"],    25_0001)
														self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"],    25_0004)
														self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"],    25_0020)
														self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["mr_IN"],    25_0038)







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							int				     =					self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
														self.assertListEqual(self.expected_src_tokens,    lowercase_)







							def      snake_case__   (     self):

														'''simple docstring'''

														self.assertIn(lowercase_,    self.tokenizer.all_special_ids)
														_lowerCAmelCase  :							List[str]				     =					[RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
														_lowerCAmelCase  :							List[Any]				     =					self.tokenizer.decode(lowercase_,    skip_special_tokens=lowercase_)
														_lowerCAmelCase  :							Optional[Any]				     =					self.tokenizer.decode(generated_ids[1:],    skip_special_tokens=lowercase_)
														self.assertEqual(lowercase_,    lowercase_)
														self.assertNotIn(self.tokenizer.eos_token,    lowercase_)







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Union[str, Any]				     =					["this is gunna be a long sentence " * 20]
														assert isinstance(src_text[0],    lowercase_)
														_lowerCAmelCase  :							str				     =					10
														_lowerCAmelCase  :							Any				     =					self.tokenizer(lowercase_,    max_length=lowercase_,    truncation=lowercase_).input_ids[0]
														self.assertEqual(ids[0],    lowercase_)
														self.assertEqual(ids[-1],    2)
														self.assertEqual(len(lowercase_),    lowercase_)







							def      snake_case__   (     self):

														'''simple docstring'''

														self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]),    [25_0053, 25_0001])







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Optional[int]				     =					tempfile.mkdtemp()
														_lowerCAmelCase  :							List[str]				     =					self.tokenizer.fairseq_tokens_to_ids
														self.tokenizer.save_pretrained(lowercase_)
														_lowerCAmelCase  :							int				     =					MBartaaTokenizer.from_pretrained(lowercase_)
														self.assertDictEqual(new_tok.fairseq_tokens_to_ids,    lowercase_)







							@require_torch
							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Optional[Any]				     =					self.tokenizer(self.src_text,    text_target=self.tgt_text,    padding=lowercase_,    return_tensors="pt")
														_lowerCAmelCase  :							Optional[int]				     =					shift_tokens_right(batch["labels"],    self.tokenizer.pad_token_id)

														# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
														assert batch.input_ids[1][0] == EN_CODE
														assert batch.input_ids[1][-1] == 2
														assert batch.labels[1][0] == RO_CODE
														assert batch.labels[1][-1] == 2
														assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]







							@require_torch
							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Tuple				     =					self.tokenizer(
														    self.src_text,    text_target=self.tgt_text,    padding=lowercase_,    truncation=lowercase_,    max_length=len(self.expected_src_tokens),    return_tensors="pt",    )
														_lowerCAmelCase  :							Tuple				     =					shift_tokens_right(batch["labels"],    self.tokenizer.pad_token_id)

														self.assertIsInstance(lowercase_,    lowercase_)

														self.assertEqual((2, 14),    batch.input_ids.shape)
														self.assertEqual((2, 14),    batch.attention_mask.shape)
														_lowerCAmelCase  :							Optional[int]				     =					batch.input_ids.tolist()[0]
														self.assertListEqual(self.expected_src_tokens,    lowercase_)
														self.assertEqual(2,    batch.decoder_input_ids[0, 0])  # decoder_start_token_id
														# Test that special tokens are reset
														self.assertEqual(self.tokenizer.prefix_tokens,    [EN_CODE])
														self.assertEqual(self.tokenizer.suffix_tokens,    [self.tokenizer.eos_token_id])







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Union[str, Any]				     =					self.tokenizer(self.src_text,    padding=lowercase_,    truncation=lowercase_,    max_length=3,    return_tensors="pt")
														_lowerCAmelCase  :							List[Any]				     =					self.tokenizer(
														    text_target=self.tgt_text,    padding=lowercase_,    truncation=lowercase_,    max_length=10,    return_tensors="pt")
														_lowerCAmelCase  :							str				     =					targets["input_ids"]
														_lowerCAmelCase  :							List[Any]				     =					shift_tokens_right(lowercase_,    self.tokenizer.pad_token_id)

														self.assertEqual(batch.input_ids.shape[1],    3)
														self.assertEqual(batch.decoder_input_ids.shape[1],    10)







							@require_torch
							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Union[str, Any]				     =					self.tokenizer._build_translation_inputs(
														    "A test",    return_tensors="pt",    src_lang="en_XX",    tgt_lang="ar_AR")

														self.assertEqual(
														    nested_simplify(lowercase_),    {
														        # en_XX, A, test, EOS
														        "input_ids": [[25_0004, 62, 3034, 2]],
														        "attention_mask": [[1, 1, 1, 1]],
														        # ar_AR
														        "forced_bos_token_id": 25_0001,
														    },    )











import requests
from bsa import BeautifulSoup






def        A       (      _lowerCamelCase       ,				_lowerCamelCase						):





							'''simple docstring'''




							_lowerCAmelCase  :							List[str]				     =					BeautifulSoup(requests.get(_lowerCamelCase       ,				params=_lowerCamelCase						).content       ,				"html.parser"						)
							_lowerCAmelCase  :							Any				     =					soup.find("div"       ,				attrs={"class": "gs_ri"}						)
							_lowerCAmelCase  :							str				     =					div.find("div"       ,				attrs={"class": "gs_fl"}						).find_all("a"						)
							return anchors[2].get_text()


if __name__ == "__main__":
						_snake_case	=						{
						    "title": (
						        "Precisely geometry controlled microsupercapacitors for ultrahigh areal "
						        "capacitance, volumetric capacitance, and energy density"
						    ),
						    "journal": "Chem. Mater.",
						    "volume": 30,
						    "pages": "3979-3990",
						    "year": 2018,
						    "hl": "en",
						}
						print(get_citation("https://scholar.google.com/scholar_lookup", params=params))
