
'''simple docstring'''
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


__lowerCAmelCase												=	get_tests_dir('fixtures/test_sentencepiece.model')

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

__lowerCAmelCase												=	250_004
__lowerCAmelCase												=	250_020


@require_sentencepiece
@require_tokenizers
class       _lowerCAmelCase   (   _lowerCamelCase					,							unittest.TestCase				):







							'''simple docstring'''

							lowerCAmelCase_ 						=						MBartaaTokenizer
							lowerCAmelCase_ 						=						MBartaaTokenizerFast
							lowerCAmelCase_ 						=						True
							lowerCAmelCase_ 						=						True

							def 	lowercase							(self  )					->       List[Any]:
														super().setUp()

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

							def 	lowercase							(self  )					->       Any:
														_snake_case       =  """<s>"""
														_snake_case       =  0

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

							def 	lowercase							(self  )					->       List[str]:
														_snake_case       =  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 	lowercase							(self  )					->       Tuple:
														self.assertEqual(self.get_tokenizer().vocab_size  ,  1054  )

							def 	lowercase							(self  )					->       Dict:
														_snake_case       =  MBartaaTokenizer(lowercase_  ,  src_lang="""en_XX"""  ,  tgt_lang="""ro_RO"""  ,  keep_accents=lowercase_  )

														_snake_case       =  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]]  ,  )

														_snake_case       =  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""", """."""]  ,  )
														_snake_case       =  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]
														    ]  ,  )

														_snake_case       =  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 	lowercase							(self  )					->       List[str]:
														# fmt: off
														_snake_case       =  {"""input_ids""": [[250004, 11062, 82772, 7, 15, 82772, 538, 51529, 237, 17198, 1290, 206, 9, 215175, 1314, 136, 17198, 1290, 206, 9, 56359, 42, 122009, 9, 16466, 16, 87344, 4537, 9, 4717, 78381, 6, 159958, 7, 15, 24480, 618, 4, 527, 22693, 5428, 4, 2777, 24480, 9874, 4, 43523, 594, 4, 803, 18392, 33189, 18, 4, 43523, 24447, 12399, 100, 24955, 83658, 9626, 144057, 15, 839, 22335, 16, 136, 24955, 83658, 83479, 15, 39102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 122009, 115774, 23, 805, 1328, 46876, 7, 136, 53894, 1940, 42227, 41159, 17721, 823, 425, 4, 27512, 98722, 206, 136, 5531, 4970, 919, 17336, 5, 2], [250004, 20080, 618, 83, 82775, 47, 479, 9, 1517, 73, 53894, 333, 80581, 110117, 18811, 5256, 1295, 51, 152526, 297, 7986, 390, 124416, 538, 35431, 214, 98, 15044, 25737, 136, 7108, 43701, 23, 756, 135355, 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], [250004, 581, 63773, 119455, 6, 147797, 88203, 7, 645, 70, 21, 3285, 10269, 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 	lowercase							(self  )					->       Union[str, Any]:
														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

														_snake_case       =  (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})"""  ):
																												_snake_case       =  self.rust_tokenizer_class.from_pretrained(lowercase_  ,  **lowercase_  )
																												_snake_case       =  self.tokenizer_class.from_pretrained(lowercase_  ,  **lowercase_  )

																												_snake_case       =  tempfile.mkdtemp()

																												_snake_case       =  tokenizer_r.save_pretrained(lowercase_  )
																												_snake_case       =  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  )  )
																												_snake_case       =  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
																												_snake_case       =  tokenizer_r.from_pretrained(lowercase_  )
																												_snake_case       =  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
																												_snake_case       =  tempfile.mkdtemp()

																												_snake_case       =  tokenizer_r.save_pretrained(lowercase_  ,  legacy_format=lowercase_  )
																												_snake_case       =  tokenizer_p.save_pretrained(lowercase_  )

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

																												# Checks everything loads correctly in the same way
																												_snake_case       =  tokenizer_r.from_pretrained(lowercase_  )
																												_snake_case       =  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
																												_snake_case       =  tempfile.mkdtemp()

																												_snake_case       =  tokenizer_r.save_pretrained(lowercase_  ,  legacy_format=lowercase_  )
																												_snake_case       =  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
																												_snake_case       =  tokenizer_r.from_pretrained(lowercase_  )
																												_snake_case       =  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       _lowerCAmelCase   (   unittest.TestCase				):







							'''simple docstring'''

							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, 82_74, 12_78_73, 2_59_16, 7, 86_22, 20_71, 4_38, 6_74_85, 53, 18_78_95, 23, 5_17_12, 2]

							@classmethod
							def 	lowercase							(cls  )					->       Tuple:
														_snake_case       =  MBartaaTokenizer.from_pretrained(
														    cls.checkpoint_name  ,  src_lang="""en_XX"""  ,  tgt_lang="""ro_RO"""  )
														_snake_case       =  1
														return cls

							def 	lowercase							(self  )					->       Dict:
														self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ar_AR"""]  ,  250001  )
														self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""en_EN"""]  ,  250004  )
														self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ro_RO"""]  ,  250020  )
														self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""mr_IN"""]  ,  250038  )

							def 	lowercase							(self  )					->       Tuple:
														_snake_case       =  self.tokenizer.batch_encode_plus(self.src_text  ).input_ids[0]
														self.assertListEqual(self.expected_src_tokens  ,  lowercase_  )

							def 	lowercase							(self  )					->       int:
														self.assertIn(lowercase_  ,  self.tokenizer.all_special_ids  )
														_snake_case       =  [RO_CODE, 884, 9019, 96, 9, 916, 86792, 36, 18743, 15596, 5, 2]
														_snake_case       =  self.tokenizer.decode(lowercase_  ,  skip_special_tokens=lowercase_  )
														_snake_case       =  self.tokenizer.decode(generated_ids[1:]  ,  skip_special_tokens=lowercase_  )
														self.assertEqual(lowercase_  ,  lowercase_  )
														self.assertNotIn(self.tokenizer.eos_token  ,  lowercase_  )

							def 	lowercase							(self  )					->       Optional[Any]:
														_snake_case       =  ["""this is gunna be a long sentence """ * 20]
														assert isinstance(src_text[0]  ,  lowercase_  )
														_snake_case       =  10
														_snake_case       =  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 	lowercase							(self  )					->       List[Any]:
														self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]  )  ,  [250053, 250001]  )

							def 	lowercase							(self  )					->       Tuple:
														_snake_case       =  tempfile.mkdtemp()
														_snake_case       =  self.tokenizer.fairseq_tokens_to_ids
														self.tokenizer.save_pretrained(lowercase_  )
														_snake_case       =  MBartaaTokenizer.from_pretrained(lowercase_  )
														self.assertDictEqual(new_tok.fairseq_tokens_to_ids  ,  lowercase_  )

							@require_torch
							def 	lowercase							(self  )					->       List[str]:
														_snake_case       =  self.tokenizer(self.src_text  ,  text_target=self.tgt_text  ,  padding=lowercase_  ,  return_tensors="""pt"""  )
														_snake_case       =  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 	lowercase							(self  )					->       List[str]:
														_snake_case       =  self.tokenizer(
														    self.src_text  ,  text_target=self.tgt_text  ,  padding=lowercase_  ,  truncation=lowercase_  ,  max_length=len(self.expected_src_tokens  )  ,  return_tensors="""pt"""  ,  )
														_snake_case       =  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  )
														_snake_case       =  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 	lowercase							(self  )					->       str:
														_snake_case       =  self.tokenizer(self.src_text  ,  padding=lowercase_  ,  truncation=lowercase_  ,  max_length=3  ,  return_tensors="""pt"""  )
														_snake_case       =  self.tokenizer(
														    text_target=self.tgt_text  ,  padding=lowercase_  ,  truncation=lowercase_  ,  max_length=10  ,  return_tensors="""pt"""  )
														_snake_case       =  targets["""input_ids"""]
														_snake_case       =  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 	lowercase							(self  )					->       Union[str, Any]:
														_snake_case       =  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""": [[250004, 62, 3034, 2]],
														        """attention_mask""": [[1, 1, 1, 1]],
														        # ar_AR
														        """forced_bos_token_id""": 250001,
														    }  ,  )

'''simple docstring'''
from random import randint, random






def  __SCREAMING_SNAKE_CASE				(  _SCREAMING_SNAKE_CASE							, _SCREAMING_SNAKE_CASE							, _SCREAMING_SNAKE_CASE							, _SCREAMING_SNAKE_CASE = False							, _SCREAMING_SNAKE_CASE = False							, _SCREAMING_SNAKE_CASE = 5							, ):
							_snake_case       =  [[-1] * number_of_cells]  # Create a highway without any car
							_snake_case       =  0
							_snake_case       =  max(_SCREAMING_SNAKE_CASE							, 0				)
							while i < number_of_cells:
														_snake_case       =  (
														    randint(0							, _SCREAMING_SNAKE_CASE				) if random_speed else initial_speed
														)  # Place the cars
														i += (
														    randint(1							, max_speed * 2				) if random_frequency else frequency
														)  # Arbitrary number, may need tuning
							return highway






def  __SCREAMING_SNAKE_CASE				(  _SCREAMING_SNAKE_CASE							, _SCREAMING_SNAKE_CASE				):
							_snake_case       =  0
							_snake_case       =  highway_now[car_index + 1 :]
							for cell in range(len(_SCREAMING_SNAKE_CASE				)				):  # May need a better name for this
														if cells[cell] != -1:  # If the cell is not empty then
																					return distance  # we have the distance we wanted
														distance += 1
							# Here if the car is near the end of the highway
							return distance + get_distance(_SCREAMING_SNAKE_CASE							, -1				)






def  __SCREAMING_SNAKE_CASE				(  _SCREAMING_SNAKE_CASE							, _SCREAMING_SNAKE_CASE							, _SCREAMING_SNAKE_CASE				):
							_snake_case       =  len(_SCREAMING_SNAKE_CASE				)
							# Beforce calculations, the highway is empty
							_snake_case       =  [-1] * number_of_cells

							for car_index in range(_SCREAMING_SNAKE_CASE				):
														if highway_now[car_index] != -1:
																					# Add 1 to the current speed of the car and cap the speed
																					_snake_case       =  min(highway_now[car_index] + 1							, _SCREAMING_SNAKE_CASE				)
																					# Number of empty cell before the next car
																					_snake_case       =  get_distance(_SCREAMING_SNAKE_CASE							, _SCREAMING_SNAKE_CASE				) - 1
																					# We can't have the car causing an accident
																					_snake_case       =  min(next_highway[car_index]							, _SCREAMING_SNAKE_CASE				)
																					if random() < probability:
																												# Randomly, a driver will slow down
																												_snake_case       =  max(next_highway[car_index] - 1							, 0				)
							return next_highway






def  __SCREAMING_SNAKE_CASE				(  _SCREAMING_SNAKE_CASE							, _SCREAMING_SNAKE_CASE							, _SCREAMING_SNAKE_CASE							, _SCREAMING_SNAKE_CASE				):
							_snake_case       =  len(highway[0]				)

							for i in range(_SCREAMING_SNAKE_CASE				):
														_snake_case       =  update(highway[i]							, _SCREAMING_SNAKE_CASE							, _SCREAMING_SNAKE_CASE				)
														_snake_case       =  [-1] * number_of_cells

														for car_index in range(_SCREAMING_SNAKE_CASE				):
																					_snake_case       =  next_speeds_calculated[car_index]
																					if speed != -1:
																												# Change the position based on the speed (with % to create the loop)
																												_snake_case       =  (car_index + speed) % number_of_cells
																												# Commit the change of position
																												_snake_case       =  speed
														highway.append(_SCREAMING_SNAKE_CASE				)

							return highway


if __name__ == "__main__":
				import doctest

				doctest.testmod()