


import shutil
import tempfile
import unittest

from transformers import (
    SPIECE_UNDERLINE,
    AddedToken,
    BatchEncoding,
    NllbTokenizer,
    NllbTokenizerFast,
    is_torch_available,
)
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


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


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

SCREAMING_SNAKE_CASE__     					=			256_047
SCREAMING_SNAKE_CASE__     					=			256_145



@require_sentencepiece
@require_tokenizers
class 						_UpperCAmelCase      (     lowercase		,		unittest.TestCase							):
		lowerCamelCase_	:			int       			=  NllbTokenizer
		lowerCamelCase_	:			int       			=  NllbTokenizerFast
		lowerCamelCase_	:			Optional[Any]       			=  True
		lowerCamelCase_	:			Dict       			=  True
		lowerCamelCase_	:			Dict       			=  {}






		def _snake_case		(						self				:     Union[str, Any]):
				super().setUp()

				# We have a SentencePiece fixture for testing
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						NllbTokenizer(lowerCamelCase__   ,  keep_accents=lowerCamelCase__)
				tokenizer.save_pretrained(self.tmpdirname)






		def _snake_case		(						self				:     str):
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						NllbTokenizer(lowerCamelCase__   ,  keep_accents=lowerCamelCase__)

				SCREAMING_SNAKE_CASE_				:Dict				     =						tokenizer.tokenize("This is a test")
				self.assertListEqual(lowerCamelCase__   ,  ["▁This", "▁is", "▁a", "▁t", "est"])

				self.assertListEqual(
				    tokenizer.convert_tokens_to_ids(lowerCamelCase__)   ,  [value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]   ,  )

				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						tokenizer.tokenize("I was born in 92000, and this is falsé.")
				self.assertListEqual(
				    lowerCamelCase__   ,  [
				        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",
				        ".",
				    ]   ,  )
				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						tokenizer.convert_tokens_to_ids(lowerCamelCase__)
				self.assertListEqual(
				    lowerCamelCase__   ,  [
				        value + tokenizer.fairseq_offset
				        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
				    ]   ,  )

				SCREAMING_SNAKE_CASE_				:List[str]				     =						tokenizer.convert_ids_to_tokens(lowerCamelCase__)
				self.assertListEqual(
				    lowerCamelCase__   ,  [
				        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>",
				        ".",
				    ]   ,  )






		def _snake_case		(						self				:     int):
				SCREAMING_SNAKE_CASE_				:Tuple				     =						(self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-nllb', {})
				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
						with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"):
								SCREAMING_SNAKE_CASE_				:str				     =						self.rust_tokenizer_class.from_pretrained(lowerCamelCase__   ,  **lowerCamelCase__)
								SCREAMING_SNAKE_CASE_				:Tuple				     =						self.tokenizer_class.from_pretrained(lowerCamelCase__   ,  **lowerCamelCase__)

								SCREAMING_SNAKE_CASE_				:Tuple				     =						tempfile.mkdtemp()

								SCREAMING_SNAKE_CASE_				:List[Any]				     =						tokenizer_r.save_pretrained(lowerCamelCase__)
								SCREAMING_SNAKE_CASE_				:Dict				     =						tokenizer_p.save_pretrained(lowerCamelCase__)

								# 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))
								SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f)
								self.assertSequenceEqual(lowerCamelCase__   ,  lowerCamelCase__)

								# Checks everything loads correctly in the same way
								SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						tokenizer_r.from_pretrained(lowerCamelCase__)
								SCREAMING_SNAKE_CASE_				:int				     =						tokenizer_p.from_pretrained(lowerCamelCase__)

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

								shutil.rmtree(lowerCamelCase__)

								# Save tokenizer rust, legacy_format=True
								SCREAMING_SNAKE_CASE_				:Any				     =						tempfile.mkdtemp()

								SCREAMING_SNAKE_CASE_				:Tuple				     =						tokenizer_r.save_pretrained(lowerCamelCase__   ,  legacy_format=lowerCamelCase__)
								SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						tokenizer_p.save_pretrained(lowerCamelCase__)

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

								# Checks everything loads correctly in the same way
								SCREAMING_SNAKE_CASE_				:str				     =						tokenizer_r.from_pretrained(lowerCamelCase__)
								SCREAMING_SNAKE_CASE_				:int				     =						tokenizer_p.from_pretrained(lowerCamelCase__)

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

								shutil.rmtree(lowerCamelCase__)

								# Save tokenizer rust, legacy_format=False
								SCREAMING_SNAKE_CASE_				:Tuple				     =						tempfile.mkdtemp()

								SCREAMING_SNAKE_CASE_				:List[Any]				     =						tokenizer_r.save_pretrained(lowerCamelCase__   ,  legacy_format=lowerCamelCase__)
								SCREAMING_SNAKE_CASE_				:int				     =						tokenizer_p.save_pretrained(lowerCamelCase__)

								# 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
								SCREAMING_SNAKE_CASE_				:int				     =						tokenizer_r.from_pretrained(lowerCamelCase__)
								SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						tokenizer_p.from_pretrained(lowerCamelCase__)

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

								shutil.rmtree(lowerCamelCase__)






		@require_torch
		def _snake_case		(						self				:     Optional[int]):
				if not self.test_seqaseq:
						return

				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						self.get_tokenizers()
				for tokenizer in tokenizers:
						with self.subTest(F"{tokenizer.__class__.__name__}"):
								# Longer text that will definitely require truncation.
								SCREAMING_SNAKE_CASE_				:int				     =						[
								    ' 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.',
								]
								SCREAMING_SNAKE_CASE_				:Tuple				     =						[
								    '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.',
								]
								try:
										SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						tokenizer.prepare_seqaseq_batch(
										    src_texts=lowerCamelCase__   ,  tgt_texts=lowerCamelCase__   ,  max_length=3   ,  max_target_length=10   ,  return_tensors="pt"   ,  src_lang="eng_Latn"   ,  tgt_lang="ron_Latn"   ,  )
								except NotImplementedError:
										return
								self.assertEqual(batch.input_ids.shape[1]   ,  3)
								self.assertEqual(batch.labels.shape[1]   ,  10)
								# max_target_length will default to max_length if not specified
								SCREAMING_SNAKE_CASE_				:Dict				     =						tokenizer.prepare_seqaseq_batch(
								    lowerCamelCase__   ,  tgt_texts=lowerCamelCase__   ,  max_length=3   ,  return_tensors="pt")
								self.assertEqual(batch.input_ids.shape[1]   ,  3)
								self.assertEqual(batch.labels.shape[1]   ,  3)

								SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						tokenizer.prepare_seqaseq_batch(
								    src_texts=lowerCamelCase__   ,  max_length=3   ,  max_target_length=10   ,  return_tensors="pt")
								self.assertEqual(batch_encoder_only.input_ids.shape[1]   ,  3)
								self.assertEqual(batch_encoder_only.attention_mask.shape[1]   ,  3)
								self.assertNotIn("decoder_input_ids"   ,  lowerCamelCase__)






		@unittest.skip("Unfortunately way too slow to build a BPE with SentencePiece.")
		def _snake_case		(						self				:     str):
				pass







		def _snake_case		(						self				:     List[str]):
				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
						with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"):
								SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						[AddedToken("<special>"   ,  lstrip=lowerCamelCase__)]

								SCREAMING_SNAKE_CASE_				:Tuple				     =						self.rust_tokenizer_class.from_pretrained(
								    lowerCamelCase__   ,  additional_special_tokens=lowerCamelCase__   ,  **lowerCamelCase__)
								SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						tokenizer_r.encode("Hey this is a <special> token")

								SCREAMING_SNAKE_CASE_				:List[str]				     =						tokenizer_r.encode("<special>"   ,  add_special_tokens=lowerCamelCase__)[0]

								self.assertTrue(special_token_id in r_output)

								if self.test_slow_tokenizer:
										SCREAMING_SNAKE_CASE_				:int				     =						self.rust_tokenizer_class.from_pretrained(
										    lowerCamelCase__   ,  additional_special_tokens=lowerCamelCase__   ,  **lowerCamelCase__   ,  )
										SCREAMING_SNAKE_CASE_				:List[Any]				     =						self.tokenizer_class.from_pretrained(
										    lowerCamelCase__   ,  additional_special_tokens=lowerCamelCase__   ,  **lowerCamelCase__)

										SCREAMING_SNAKE_CASE_				:List[Any]				     =						tokenizer_p.encode("Hey this is a <special> token")

										SCREAMING_SNAKE_CASE_				:Dict				     =						tokenizer_cr.encode("Hey this is a <special> token")

										self.assertEqual(lowerCamelCase__   ,  lowerCamelCase__)
										self.assertEqual(lowerCamelCase__   ,  lowerCamelCase__)
										self.assertTrue(special_token_id in p_output)
										self.assertTrue(special_token_id in cr_output)




@require_torch
@require_sentencepiece
@require_tokenizers
class 						_UpperCAmelCase      (     unittest.TestCase							):
		lowerCamelCase_	:			Any       			=  """facebook/nllb-200-distilled-600M"""
		lowerCamelCase_	:			List[Any]       			=  [
		    """ 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_	:			List[Any]       			=  [
		    """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_	:			List[Any]       			=  [
		    2_5_6_0_4_7,
		    1_6_2_9_7,
		    1_3_4_4_0_8,
		    8_1_6_5,
		    2_4_8_0_6_6,
		    1_4_7_3_4,
		    9_5_0,
		    1_1_3_5,
		    1_0_5_7_2_1,
		    3_5_7_3,
		    8_3,
		    2_7_3_5_2,
		    1_0_8,
		    4_9_4_8_6,
		    2,
		]






		@classmethod
		def _snake_case		(						cls				:     List[str]):
				SCREAMING_SNAKE_CASE_				:NllbTokenizer				     =						NllbTokenizer.from_pretrained(
				    cls.checkpoint_name   ,  src_lang="eng_Latn"   ,  tgt_lang="ron_Latn")
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						1
				return cls






		def _snake_case		(						self				:     Optional[int]):
				self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ace_Arab"]   ,  25_60_01)
				self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ace_Latn"]   ,  25_60_02)
				self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["fra_Latn"]   ,  25_60_57)






		def _snake_case		(						self				:     Any):
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
				self.assertListEqual(self.expected_src_tokens   ,  lowerCamelCase__)






		def _snake_case		(						self				:     Any):
				self.assertIn(lowerCamelCase__   ,  self.tokenizer.all_special_ids)
				# fmt: off
				SCREAMING_SNAKE_CASE_				:str				     =						[RO_CODE, 42_54, 9_80_68, 11_29_23, 3_90_72, 39_09, 7_13, 10_27_67, 26, 1_73_14, 3_56_42, 1_46_83, 3_31_18, 20_22, 6_69_87, 2, 25_60_47]
				# fmt: on

				SCREAMING_SNAKE_CASE_				:List[Any]				     =						self.tokenizer.decode(lowerCamelCase__   ,  skip_special_tokens=lowerCamelCase__)
				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						self.tokenizer.decode(generated_ids[1:]   ,  skip_special_tokens=lowerCamelCase__)
				self.assertEqual(lowerCamelCase__   ,  lowerCamelCase__)
				self.assertNotIn(self.tokenizer.eos_token   ,  lowerCamelCase__)






		def _snake_case		(						self				:     List[Any]):
				SCREAMING_SNAKE_CASE_				:List[Any]				     =						['this is gunna be a long sentence ' * 20]
				assert isinstance(src_text[0]   ,  lowerCamelCase__)
				SCREAMING_SNAKE_CASE_				:List[str]				     =						10
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						self.tokenizer(lowerCamelCase__   ,  max_length=lowerCamelCase__   ,  truncation=lowerCamelCase__).input_ids[0]
				self.assertEqual(ids[-1]   ,  2)
				self.assertEqual(ids[0]   ,  lowerCamelCase__)
				self.assertEqual(len(lowerCamelCase__)   ,  lowerCamelCase__)






		def _snake_case		(						self				:     str):
				self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"])   ,  [25_62_03, 3])






		def _snake_case		(						self				:     Dict):
				SCREAMING_SNAKE_CASE_				:int				     =						tempfile.mkdtemp()
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						self.tokenizer.fairseq_tokens_to_ids
				self.tokenizer.save_pretrained(lowerCamelCase__)
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						NllbTokenizer.from_pretrained(lowerCamelCase__)
				self.assertDictEqual(new_tok.fairseq_tokens_to_ids   ,  lowerCamelCase__)






		@require_torch
		def _snake_case		(						self				:     int):
				SCREAMING_SNAKE_CASE_				:Dict				     =						self.tokenizer(
				    self.src_text   ,  text_target=self.tgt_text   ,  padding=lowerCamelCase__   ,  truncation=lowerCamelCase__   ,  max_length=len(self.expected_src_tokens)   ,  return_tensors="pt"   ,  )
				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						shift_tokens_right(
				    batch["labels"]   ,  self.tokenizer.pad_token_id   ,  self.tokenizer.lang_code_to_id["ron_Latn"])

				self.assertIsInstance(lowerCamelCase__   ,  lowerCamelCase__)

				self.assertEqual((2, 15)   ,  batch.input_ids.shape)
				self.assertEqual((2, 15)   ,  batch.attention_mask.shape)
				SCREAMING_SNAKE_CASE_				:List[str]				     =						batch.input_ids.tolist()[0]
				self.assertListEqual(self.expected_src_tokens   ,  lowerCamelCase__)
				self.assertEqual(lowerCamelCase__   ,  batch.decoder_input_ids[0, 0])  # EOS
				# 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				:     Optional[Any]):
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						self.tokenizer(self.src_text   ,  padding=lowerCamelCase__   ,  truncation=lowerCamelCase__   ,  max_length=3   ,  return_tensors="pt")
				SCREAMING_SNAKE_CASE_				:Dict				     =						self.tokenizer(
				    text_target=self.tgt_text   ,  padding=lowerCamelCase__   ,  truncation=lowerCamelCase__   ,  max_length=10   ,  return_tensors="pt")
				SCREAMING_SNAKE_CASE_				:int				     =						targets['input_ids']
				SCREAMING_SNAKE_CASE_				:Dict				     =						shift_tokens_right(
				    lowerCamelCase__   ,  self.tokenizer.pad_token_id   ,  decoder_start_token_id=self.tokenizer.lang_code_to_id[self.tokenizer.tgt_lang]   ,  )

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






		@require_torch
		def _snake_case		(						self				:     Optional[Any]):
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						self.tokenizer._build_translation_inputs(
				    "A test"   ,  return_tensors="pt"   ,  src_lang="eng_Latn"   ,  tgt_lang="fra_Latn")

				self.assertEqual(
				    nested_simplify(lowerCamelCase__)   ,  {
				        # A, test, EOS, en_XX
				        "input_ids": [[25_60_47, 70, 73_56, 2]],
				        "attention_mask": [[1, 1, 1, 1]],
				        # ar_AR
				        "forced_bos_token_id": 25_60_57,
				    }   ,  )







		@require_torch
		def _snake_case		(						self				:     List[str]):
				SCREAMING_SNAKE_CASE_				:Dict				     =						True
				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						self.tokenizer(
				    "UN Chief says there is no military solution in Syria"   ,  src_lang="eng_Latn"   ,  tgt_lang="fra_Latn")
				self.assertEqual(
				    inputs.input_ids   ,  [1_62_97, 13_44_08, 2_56_53, 63_70, 2_48, 2_54, 10_39_29, 9_49_95, 1_08, 4_94_86, 2, 25_60_47])

				SCREAMING_SNAKE_CASE_				:int				     =						False
				SCREAMING_SNAKE_CASE_				:Any				     =						self.tokenizer(
				    "UN Chief says there is no military solution in Syria"   ,  src_lang="eng_Latn"   ,  tgt_lang="fra_Latn")
				self.assertEqual(
				    inputs.input_ids   ,  [25_60_47, 1_62_97, 13_44_08, 2_56_53, 63_70, 2_48, 2_54, 10_39_29, 9_49_95, 1_08, 4_94_86, 2])











'''simple docstring'''
def A__       (	UpperCAmelCase_ = 1_0_0_0				):
						_UpperCamelCase   :						List[str]												=  3
						_UpperCamelCase   :						Any												=  0
						while a < n:
												if a % 3 == 0 or a % 5 == 0:
																		result += a
												elif a % 1_5 == 0:
																		result -= a
												a += 1
						return result


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


