


"""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():
 __lowercase    					=      get_tests_dir("""fixtures/test_sentencepiece.model""")


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

__lowercase    					=      128022
__lowercase    					=      128028






@require_sentencepiece
class 						_A  (  _a    ,unittest.TestCase  ):







    """simple docstring"""




    UpperCAmelCase       :							List[Any]	=       MaMaaaTokenizer
    UpperCAmelCase       :							List[str]	=       False
    UpperCAmelCase       :							Tuple	=       False
    UpperCAmelCase       :							str	=       True






    def 	__snake_case							(					self				:    int):
      super().setUp()

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

      a						:		Tuple      							=			MaMaaaTokenizer.from_pretrained(self.tmpdirname)
      tokenizer.save_pretrained(self.tmpdirname)






    def 	__snake_case							(					self				:    str				, **__UpperCAmelCase				:    str):
      return MaMaaaTokenizer.from_pretrained(self.tmpdirname				, **__UpperCAmelCase)






    def 	__snake_case							(					self				:    int				, __UpperCAmelCase				:    List[Any]):
      return (
          "This is a test",
          "This is a test",
      )






    def 	__snake_case							(					self				:    Tuple):
      a						:		int      							=			"</s>"
      a						:		Dict      							=			0

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






    def 	__snake_case							(					self				:    List[str]):
      a						:		Tuple      							=			self.get_tokenizer()
      a						:		Optional[Any]      							=			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(__UpperCAmelCase)				, tokenizer.vocab_size + len(tokenizer.get_added_vocab()))






    @unittest.skip("Skip this test while all models are still to be uploaded.")
    def 	__snake_case							(					self				:    str):
      pass






    def 	__snake_case							(					self				:    Optional[int]):
      a						:		Tuple      							=			self.get_tokenizer()

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

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

      a						:		str      							=			tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6])
      self.assertListEqual(__UpperCAmelCase				, ["▁This", "▁is", "▁a", "▁t", "est"])

      a						:		Optional[Any]      							=			tokenizer.convert_tokens_to_string(__UpperCAmelCase)
      self.assertEqual(__UpperCAmelCase				, "This is a test")






    @slow
    def 	__snake_case							(					self				:    Tuple):
      # fmt: off
      a						:		Optional[int]      							=			{"input_ids": [[128022, 110108, 397, 11, 38272, 2247, 124811, 285, 18105, 1586, 207, 7, 39534, 4428, 397, 1019, 18105, 1586, 207, 7, 41337, 16786, 241, 7, 20214, 17, 125690, 10398, 7, 44378, 58069, 68342, 7798, 7343, 11, 299, 33310, 4, 158, 37350, 94077, 4569, 299, 33310, 90, 4, 52840, 290, 4, 31270, 112, 299, 682, 4, 52840, 39953, 14079, 193, 52519, 90894, 17894, 120697, 11, 40445, 551, 17, 1019, 52519, 90894, 17756, 963, 11, 40445, 480, 17, 9792, 1120, 5173, 1393, 6240, 16786, 241, 120996, 28, 1245, 1393, 118240, 11123, 1019, 93612, 2691, 10618, 98058, 120409, 1928, 279, 4, 40683, 367, 178, 207, 1019, 103, 103121, 506, 65296, 5, 2], [128022, 21217, 367, 117, 125450, 128, 719, 7, 7308, 40, 93612, 12669, 1116, 16704, 71, 17785, 3699, 15592, 35, 144, 9584, 241, 11943, 713, 950, 799, 2247, 88427, 150, 149, 118813, 120706, 1019, 106906, 81518, 28, 1224, 22799, 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], [128022, 1658, 123311, 5155, 5578, 4722, 279, 14947, 2366, 1120, 1197, 14, 1348, 9232, 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=__UpperCAmelCase				, model_name="facebook/m2m100_418M"				, revision="c168bae485c864188cf9aa0e4108b0b6934dc91e"				, )






@require_torch
@require_sentencepiece
@require_tokenizers
class 						_A  (  unittest.TestCase  ):







    """simple docstring"""




    UpperCAmelCase       :							Union[str, Any]	=       """facebook/m2m100_418M"""
    UpperCAmelCase       :							Union[str, Any]	=       [
        """In my opinion, there are two levels of response from the French government.""",
        """NSA Affair Emphasizes Complete Lack of Debate on Intelligence""",
    ]
    UpperCAmelCase       :							Dict	=       [
        """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
    UpperCAmelCase       :							List[str]	=       [EN_CODE, 5_9_3, 1_9_4_9, 1_1_5_7_8_1, 4, 7_1_5_8_6, 4_2_3_4, 6_0_6_3_3, 1_2_6_2_3_3, 4_3_2, 1_2_3_8_0_8, 1_5_5_9_2, 1_1_9_7, 1_1_7_1_3_2, 1_2_0_6_1_8, 5, 2]






    @classmethod
    def 	__snake_case							(					cls				:    List[str]):
      a						:		MaMaaaTokenizer      							=			MaMaaaTokenizer.from_pretrained(
          cls.checkpoint_name				, src_lang="en"				, tgt_lang="fr")
      a						:		List[str]      							=			1
      return cls






    def 	__snake_case							(					self				:    Union[str, Any]):
      self.assertEqual(self.tokenizer.get_lang_id("ar")				, 128006)
      self.assertEqual(self.tokenizer.get_lang_id("en")				, 128022)
      self.assertEqual(self.tokenizer.get_lang_id("ro")				, 128076)
      self.assertEqual(self.tokenizer.get_lang_id("mr")				, 128063)






    def 	__snake_case							(					self				:    Tuple):
      a						:		Union[str, Any]      							=			self.tokenizer.get_vocab()
      self.assertEqual(len(__UpperCAmelCase)				, self.tokenizer.vocab_size)
      self.assertEqual(vocab["<unk>"]				, 3)
      self.assertIn(self.tokenizer.get_lang_token("en")				, __UpperCAmelCase)






    def 	__snake_case							(					self				:    List[Any]):
      a						:		int      							=			"en"
      a						:		int      							=			self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
      self.assertListEqual(self.expected_src_tokens				, __UpperCAmelCase)






    def 	__snake_case							(					self				:    Any):
      self.assertIn(__UpperCAmelCase				, self.tokenizer.all_special_ids)
      # fmt: off
      a						:		List[Any]      							=			[FR_CODE, 5364, 82, 8642, 4, 294, 47, 8, 14028, 136, 3286, 9706, 6, 90797, 6, 144012, 162, 88128, 30061, 5, 2]
      # fmt: on
      a						:		str      							=			self.tokenizer.decode(__UpperCAmelCase				, skip_special_tokens=__UpperCAmelCase)
      a						:		Optional[Any]      							=			self.tokenizer.decode(generated_ids[1:]				, skip_special_tokens=__UpperCAmelCase)
      self.assertEqual(__UpperCAmelCase				, __UpperCAmelCase)
      self.assertNotIn(self.tokenizer.eos_token				, __UpperCAmelCase)






    def 	__snake_case							(					self				:    List[str]):
      a						:		Optional[int]      							=			tempfile.mkdtemp()
      a						:		Union[str, Any]      							=			self.tokenizer.lang_token_to_id
      self.tokenizer.save_pretrained(__UpperCAmelCase)
      a						:		int      							=			MaMaaaTokenizer.from_pretrained(__UpperCAmelCase)
      self.assertDictEqual(new_tok.lang_token_to_id				, __UpperCAmelCase)






    @require_torch
    def 	__snake_case							(					self				:    Optional[int]):
      a						:		Dict      							=			"en"
      a						:		List[str]      							=			"fr"

      a						:		str      							=			self.tokenizer(self.src_text				, text_target=self.tgt_text				, padding=__UpperCAmelCase				, return_tensors="pt")

      a						:		Any      							=			shift_tokens_right(
          batch["labels"]				, self.tokenizer.pad_token_id				, self.tokenizer.eos_token_id)

      for k in batch:
        a						:		str      							=			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 	__snake_case							(					self				:    Union[str, Any]):
      a						:		Dict      							=			"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						:		List[Any]      							=			"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 	__snake_case							(					self				:    Optional[int]):
      a						:		Any      							=			"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						:		List[Any]      							=			"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 	__snake_case							(					self				:    Any):
      a						:		str      							=			self.tokenizer._build_translation_inputs("A test"				, return_tensors="pt"				, src_lang="en"				, tgt_lang="ar")

      self.assertEqual(
          nested_simplify(__UpperCAmelCase)				, {
              # en_XX, A, test, EOS
              "input_ids": [[128022, 58, 4183, 2]],
              "attention_mask": [[1, 1, 1, 1]],
              # ar_AR
              "forced_bos_token_id": 128006,
          }				, )







from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core


# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers

UpperCamelCase__											=					[
    'python',
    'tqdm',
    'regex',
    'requests',
    'packaging',
    'filelock',
    'numpy',
    'tokenizers',
    'huggingface-hub',
    'safetensors',
    'accelerate',
    'pyyaml',
]

for pkg in pkgs_to_check_at_runtime:
      if pkg in deps:
            if pkg == "tokenizers":
                  # must be loaded here, or else tqdm check may fail
                  from .utils import is_tokenizers_available

                  if not is_tokenizers_available():
                        continue  # not required, check version only if installed
            elif pkg == "accelerate":
                  # must be loaded here, or else tqdm check may fail
                  from .utils import is_accelerate_available

                  # Maybe switch to is_torch_available in the future here so that Accelerate is hard dep of
                  # Transformers with PyTorch
                  if not is_accelerate_available():
                        continue  # not required, check version only if installed

            require_version_core(deps[pkg])
      else:
            raise ValueError(f'''can\'t find {pkg} in {deps.keys()}, check dependency_versions_table.py''')




def    lowerCAmelCase_ (     __A,  __A=None							)     ->				Dict:







      '''simple docstring'''


      require_version(deps[pkg],  __A							)



