
'''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


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

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

_lowercase          =						250004
_lowercase          =						250020




@require_sentencepiece
@require_tokenizers
class     UpperCAmelCase_	(						_SCREAMING_SNAKE_CASE			,				unittest.TestCase					):






						'''simple docstring'''






						_lowercase						: Dict										=  MBartaaTokenizer
						_lowercase						: int										=  MBartaaTokenizerFast
						_lowercase						: int										=  True
						_lowercase						: int										=  True




						def    _lowercase      (   self ):

												"""simple docstring"""



												super().setUp()

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




						def    _lowercase      (   self ):

												"""simple docstring"""



												_lowerCAmelCase    		=					"""<s>"""
												_lowerCAmelCase    		=					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 ):

												"""simple docstring"""



												_lowerCAmelCase    		=					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 )       ,  1_054 )




						def    _lowercase      (   self ):

												"""simple docstring"""



												self.assertEqual(self.get_tokenizer().vocab_size       ,  1_054 )




						def    _lowercase      (   self ):

												"""simple docstring"""



												_lowerCAmelCase    		=					MBartaaTokenizer(_lowercase       ,  src_lang="""en_XX"""       ,  tgt_lang="""ro_RO"""       ,  keep_accents=_lowercase )

												_lowerCAmelCase    		=					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    		=					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    		=					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    		=					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 ):

												"""simple docstring"""



												_lowerCAmelCase    		=					{"""input_ids""": [[250_004, 11_062, 82_772, 7, 15, 82_772, 538, 51_529, 237, 17_198, 1_290, 206, 9, 215_175, 1_314, 136, 17_198, 1_290, 206, 9, 56_359, 42, 122_009, 9, 16_466, 16, 87_344, 4_537, 9, 4_717, 78_381, 6, 159_958, 7, 15, 24_480, 618, 4, 527, 22_693, 5_428, 4, 2_777, 24_480, 9_874, 4, 43_523, 594, 4, 803, 18_392, 33_189, 18, 4, 43_523, 24_447, 12_399, 100, 24_955, 83_658, 9_626, 144_057, 15, 839, 22_335, 16, 136, 24_955, 83_658, 83_479, 15, 39_102, 724, 16, 678, 645, 2_789, 1_328, 4_589, 42, 122_009, 115_774, 23, 805, 1_328, 46_876, 7, 136, 53_894, 1_940, 42_227, 41_159, 17_721, 823, 425, 4, 27_512, 98_722, 206, 136, 5_531, 4_970, 919, 17_336, 5, 2], [250_004, 20_080, 618, 83, 82_775, 47, 479, 9, 1_517, 73, 53_894, 333, 80_581, 110_117, 18_811, 5_256, 1_295, 51, 152_526, 297, 7_986, 390, 124_416, 538, 35_431, 214, 98, 15_044, 25_737, 136, 7_108, 43_701, 23, 756, 135_355, 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], [250_004, 581, 63_773, 119_455, 6, 147_797, 88_203, 7, 645, 70, 21, 3_285, 10_269, 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 ):

												"""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    		=					(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    		=					self.rust_tokenizer_class.from_pretrained(_lowercase       ,  **_lowercase )
																								_lowerCAmelCase    		=					self.tokenizer_class.from_pretrained(_lowercase       ,  **_lowercase )

																								_lowerCAmelCase    		=					tempfile.mkdtemp()

																								_lowerCAmelCase    		=					tokenizer_r.save_pretrained(_lowercase )
																								_lowerCAmelCase    		=					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    		=					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    		=					tokenizer_r.from_pretrained(_lowercase )
																								_lowerCAmelCase    		=					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    		=					tempfile.mkdtemp()

																								_lowerCAmelCase    		=					tokenizer_r.save_pretrained(_lowercase       ,  legacy_format=_lowercase )
																								_lowerCAmelCase    		=					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    		=					tokenizer_r.from_pretrained(_lowercase )
																								_lowerCAmelCase    		=					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    		=					tempfile.mkdtemp()

																								_lowerCAmelCase    		=					tokenizer_r.save_pretrained(_lowercase       ,  legacy_format=_lowercase )
																								_lowerCAmelCase    		=					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    		=					tokenizer_r.from_pretrained(_lowercase )
																								_lowerCAmelCase    		=					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					):






						'''simple docstring'''






						_lowercase						: int										=  '''facebook/mbart-large-50-one-to-many-mmt'''
						_lowercase						: Tuple										=  [
						    ''' 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.''',
						]
						_lowercase						: int										=  [
						    '''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.''',
						]
						_lowercase						: Dict										=  [EN_CODE, 8_2_7_4, 1_2_7_8_7_3, 2_5_9_1_6, 7, 8_6_2_2, 2_0_7_1, 4_3_8, 6_7_4_8_5, 5_3, 1_8_7_8_9_5, 2_3, 5_1_7_1_2, 2]




						@classmethod
						def    _lowercase      (   cls ):

												"""simple docstring"""



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




						def    _lowercase      (   self ):

												"""simple docstring"""



												self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ar_AR"""]       ,  250_001 )
												self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""en_EN"""]       ,  250_004 )
												self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ro_RO"""]       ,  250_020 )
												self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""mr_IN"""]       ,  250_038 )




						def    _lowercase      (   self ):

												"""simple docstring"""



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




						def    _lowercase      (   self ):

												"""simple docstring"""



												self.assertIn(_lowercase       ,  self.tokenizer.all_special_ids )
												_lowerCAmelCase    		=					[RO_CODE, 884, 9_019, 96, 9, 916, 86_792, 36, 18_743, 15_596, 5, 2]
												_lowerCAmelCase    		=					self.tokenizer.decode(_lowercase       ,  skip_special_tokens=_lowercase )
												_lowerCAmelCase    		=					self.tokenizer.decode(generated_ids[1:]       ,  skip_special_tokens=_lowercase )
												self.assertEqual(_lowercase       ,  _lowercase )
												self.assertNotIn(self.tokenizer.eos_token       ,  _lowercase )




						def    _lowercase      (   self ):

												"""simple docstring"""



												_lowerCAmelCase    		=					["""this is gunna be a long sentence """ * 20]
												assert isinstance(src_text[0]       ,  _lowercase )
												_lowerCAmelCase    		=					10
												_lowerCAmelCase    		=					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 ):

												"""simple docstring"""



												self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""] )       ,  [250_053, 250_001] )




						def    _lowercase      (   self ):

												"""simple docstring"""



												_lowerCAmelCase    		=					tempfile.mkdtemp()
												_lowerCAmelCase    		=					self.tokenizer.fairseq_tokens_to_ids
												self.tokenizer.save_pretrained(_lowercase )
												_lowerCAmelCase    		=					MBartaaTokenizer.from_pretrained(_lowercase )
												self.assertDictEqual(new_tok.fairseq_tokens_to_ids       ,  _lowercase )




						@require_torch
						def    _lowercase      (   self ):

												"""simple docstring"""



												_lowerCAmelCase    		=					self.tokenizer(self.src_text       ,  text_target=self.tgt_text       ,  padding=_lowercase       ,  return_tensors="""pt""" )
												_lowerCAmelCase    		=					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 ):

												"""simple docstring"""



												_lowerCAmelCase    		=					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    		=					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    		=					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 ):

												"""simple docstring"""



												_lowerCAmelCase    		=					self.tokenizer(self.src_text       ,  padding=_lowercase       ,  truncation=_lowercase       ,  max_length=3       ,  return_tensors="""pt""" )
												_lowerCAmelCase    		=					self.tokenizer(
												    text_target=self.tgt_text       ,  padding=_lowercase       ,  truncation=_lowercase       ,  max_length=10       ,  return_tensors="""pt""" )
												_lowerCAmelCase    		=					targets["""input_ids"""]
												_lowerCAmelCase    		=					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 ):

												"""simple docstring"""



												_lowerCAmelCase    		=					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""": [[250_004, 62, 3_034, 2]],
												        """attention_mask""": [[1, 1, 1, 1]],
												        # ar_AR
												        """forced_bos_token_id""": 250_001,
												    }       ,  )


'''simple docstring'''



from itertools import product


def A (__lowerCamelCase :int					,      __lowerCamelCase :int						):
						_lowerCAmelCase    		=					sides_number
						_lowerCAmelCase    		=					max_face_number * dice_number
						_lowerCAmelCase    		=					[0] * (max_total + 1)

						_lowerCAmelCase    		=					1
						_lowerCAmelCase    		=					range(__lowerCamelCase					,      max_face_number + 1						)
						for dice_numbers in product(__lowerCamelCase					,      repeat=__lowerCamelCase						):
												_lowerCAmelCase    		=					sum(__lowerCamelCase						)
												totals_frequencies[total] += 1

						return totals_frequencies


def A ():
						_lowerCAmelCase    		=					total_frequency_distribution(
						    sides_number=4					,      dice_number=9						)
						_lowerCAmelCase    		=					total_frequency_distribution(
						    sides_number=6					,      dice_number=6						)

						_lowerCAmelCase    		=					0
						_lowerCAmelCase    		=					9
						_lowerCAmelCase    		=					4 * 9
						_lowerCAmelCase    		=					6
						for peter_total in range(__lowerCamelCase					,      max_peter_total + 1						):
												peter_wins_count += peter_totals_frequencies[peter_total] * sum(
												    colin_totals_frequencies[min_colin_total:peter_total]						)

						_lowerCAmelCase    		=					(4**9) * (6**6)
						_lowerCAmelCase    		=					peter_wins_count / total_games_number

						_lowerCAmelCase    		=					round(__lowerCamelCase					,      ndigits=7						)

						return rounded_peter_win_probability


if __name__ == "__main__":
						print(F"""{solution() = }""")
