


"""simple docstring"""


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():
	UpperCamelCase    :					Any							   =   get_tests_dir("fixtures/test_sentencepiece.model")


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

UpperCamelCase    :					List[Any]							   =   128_022
UpperCamelCase    :					str							   =   128_028



@require_sentencepiece
class       lowerCamelCase__    ( snake_case_				,     unittest.TestCase      ):
						lowerCAmelCase  	=  MaMaaaTokenizer
						lowerCAmelCase  	=  False
						lowerCAmelCase  	=  False
						lowerCAmelCase  	=  True







						def __a    (				self :     Optional[int]		):
								super().setUp()

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

								A       							=			MaMaaaTokenizer.from_pretrained(self.tmpdirname		)
								tokenizer.save_pretrained(self.tmpdirname		)







						def __a    (				self :     Tuple      ,      **_lowercase :     Optional[int]		):
								return MaMaaaTokenizer.from_pretrained(self.tmpdirname      ,      **lowercase__		)







						def __a    (				self :     Dict      ,      _lowercase :     List[str]		):
								return (
								    "This is a test",
								    "This is a test",
								)







						def __a    (				self :     str		):
								A       							=			"""</s>"""
								A       							=			0

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







						def __a    (				self :     Any		):
								A       							=			self.get_tokenizer()
								A       							=			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(lowercase__		)      ,      tokenizer.vocab_size + len(tokenizer.get_added_vocab()		)		)







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







						def __a    (				self :     Optional[Any]		):
								A       							=			self.get_tokenizer()

								A       							=			tokenizer.tokenize('This is a test'		)
								self.assertListEqual(lowercase__      ,      ['▁This', '▁is', '▁a', '▁t', 'est']		)

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

								A       							=			tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]		)
								self.assertListEqual(lowercase__      ,      ['▁This', '▁is', '▁a', '▁t', 'est']		)

								A       							=			tokenizer.convert_tokens_to_string(lowercase__		)
								self.assertEqual(lowercase__      ,      'This is a test'		)







						@slow
						def __a    (				self :     List[str]		):
								A       							=			{"""input_ids""": [[128_022, 110_108, 397, 11, 38_272, 2_247, 124_811, 285, 18_105, 1_586, 207, 7, 39_534, 4_428, 397, 1_019, 18_105, 1_586, 207, 7, 41_337, 16_786, 241, 7, 20_214, 17, 125_690, 10_398, 7, 44_378, 58_069, 68_342, 7_798, 7_343, 11, 299, 33_310, 4, 158, 37_350, 94_077, 4_569, 299, 33_310, 90, 4, 52_840, 290, 4, 31_270, 112, 299, 682, 4, 52_840, 39_953, 14_079, 193, 52_519, 90_894, 17_894, 120_697, 11, 40_445, 551, 17, 1_019, 52_519, 90_894, 17_756, 963, 11, 40_445, 480, 17, 9_792, 1_120, 5_173, 1_393, 6_240, 16_786, 241, 120_996, 28, 1_245, 1_393, 118_240, 11_123, 1_019, 93_612, 2_691, 10_618, 98_058, 120_409, 1_928, 279, 4, 40_683, 367, 178, 207, 1_019, 103, 103_121, 506, 65_296, 5, 2], [128_022, 21_217, 367, 117, 125_450, 128, 719, 7, 7_308, 40, 93_612, 12_669, 1_116, 16_704, 71, 17_785, 3_699, 15_592, 35, 144, 9_584, 241, 11_943, 713, 950, 799, 2_247, 88_427, 150, 149, 118_813, 120_706, 1_019, 106_906, 81_518, 28, 1_224, 22_799, 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], [128_022, 1_658, 123_311, 5_155, 5_578, 4_722, 279, 14_947, 2_366, 1_120, 1_197, 14, 1_348, 9_232, 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=lowercase__      ,      model_name='facebook/m2m100_418M'      ,      revision='c168bae485c864188cf9aa0e4108b0b6934dc91e'      ,      )



@require_torch
@require_sentencepiece
@require_tokenizers
class       lowerCamelCase__    ( unittest.TestCase      ):
						lowerCAmelCase  	=  '''facebook/m2m100_418M'''
						lowerCAmelCase  	=  [
						    '''In my opinion, there are two levels of response from the French government.''',
						    '''NSA Affair Emphasizes Complete Lack of Debate on Intelligence''',
						]
						lowerCAmelCase  	=  [
						    '''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
						lowerCAmelCase  	=  [EN_CODE, 593, 1949, 115781, 4, 71586, 4234, 60633, 126233, 432, 123808, 15592, 1197, 117132, 120618, 5, 2]







						@classmethod
						def __a    (				cls :     Union[str, Any]		):
								A       							=			MaMaaaTokenizer.from_pretrained(
								    cls.checkpoint_name      ,      src_lang='en'      ,      tgt_lang='fr'		)
								A       							=			1
								return cls







						def __a    (				self :     Any		):
								self.assertEqual(self.tokenizer.get_lang_id('ar'		)      ,      128_006		)
								self.assertEqual(self.tokenizer.get_lang_id('en'		)      ,      128_022		)
								self.assertEqual(self.tokenizer.get_lang_id('ro'		)      ,      128_076		)
								self.assertEqual(self.tokenizer.get_lang_id('mr'		)      ,      128_063		)







						def __a    (				self :     Optional[Any]		):
								A       							=			self.tokenizer.get_vocab()
								self.assertEqual(len(lowercase__		)      ,      self.tokenizer.vocab_size		)
								self.assertEqual(vocab['<unk>']      ,      3		)
								self.assertIn(self.tokenizer.get_lang_token('en'		)      ,      lowercase__		)







						def __a    (				self :     Any		):
								A       							=			"""en"""
								A       							=			self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
								self.assertListEqual(self.expected_src_tokens      ,      lowercase__		)







						def __a    (				self :     List[Any]		):
								self.assertIn(lowercase__      ,      self.tokenizer.all_special_ids		)
								# fmt: off
								A       							=			[FR_CODE, 5_364, 82, 8_642, 4, 294, 47, 8, 14_028, 136, 3_286, 9_706, 6, 90_797, 6, 144_012, 162, 88_128, 30_061, 5, 2]
								# fmt: on
								A       							=			self.tokenizer.decode(lowercase__      ,      skip_special_tokens=lowercase__		)
								A       							=			self.tokenizer.decode(generated_ids[1:]      ,      skip_special_tokens=lowercase__		)
								self.assertEqual(lowercase__      ,      lowercase__		)
								self.assertNotIn(self.tokenizer.eos_token      ,      lowercase__		)







						def __a    (				self :     Dict		):
								A       							=			tempfile.mkdtemp()
								A       							=			self.tokenizer.lang_token_to_id
								self.tokenizer.save_pretrained(lowercase__		)
								A       							=			MaMaaaTokenizer.from_pretrained(lowercase__		)
								self.assertDictEqual(new_tok.lang_token_to_id      ,      lowercase__		)







						@require_torch
						def __a    (				self :     Optional[int]		):
								A       							=			"""en"""
								A       							=			"""fr"""

								A       							=			self.tokenizer(self.src_text      ,      text_target=self.tgt_text      ,      padding=lowercase__      ,      return_tensors='pt'		)

								A       							=			shift_tokens_right(
								    batch['labels']      ,      self.tokenizer.pad_token_id      ,      self.tokenizer.eos_token_id		)

								for k in batch:
										A       							=			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 __a    (				self :     str		):
								A       							=			"""mr"""
								self.assertListEqual(self.tokenizer.prefix_tokens      ,      [self.tokenizer.get_lang_id('mr'		)]		)
								self.assertListEqual(self.tokenizer.suffix_tokens      ,      [self.tokenizer.eos_token_id]		)

								A       							=			"""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 __a    (				self :     List[str]		):
								A       							=			"""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		)]		)

								A       							=			"""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 __a    (				self :     Optional[int]		):
								A       							=			self.tokenizer._build_translation_inputs('A test'      ,      return_tensors='pt'      ,      src_lang='en'      ,      tgt_lang='ar'		)

								self.assertEqual(
								    nested_simplify(lowercase__		)      ,      {
								        # en_XX, A, test, EOS
								        'input_ids': [[128_022, 58, 4_183, 2]],
								        'attention_mask': [[1, 1, 1, 1]],
								        # ar_AR
								        'forced_bos_token_id': 128_006,
								    }      ,      )











'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCAmelCase_      :  Dict				     =  {
    'configuration_graphormer': ['GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GraphormerConfig'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_      :  int				     =  [
     'GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
     'GraphormerForGraphClassification',
     'GraphormerModel',
     'GraphormerPreTrainedModel',
 ]


if TYPE_CHECKING:
 from .configuration_graphormer import GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, GraphormerConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_graphormer import (
      GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      GraphormerForGraphClassification,
      GraphormerModel,
      GraphormerPreTrainedModel,
  )


else:
 import sys

 lowerCAmelCase_      :  Tuple				     =  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
