



"""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__		:    Optional[Any]				   =     get_tests_dir("""fixtures/test_sentencepiece.model""")


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

lowercase__		:    Optional[Any]				   =     1_2_8_0_2_2
lowercase__		:    int				   =     1_2_8_0_2_8







@require_sentencepiece
class 				UpperCamelCase__       (     lowercase_, unittest.TestCase  ):




      """simple docstring"""




      _SCREAMING_SNAKE_CASE      =					MaMaaaTokenizer
      _SCREAMING_SNAKE_CASE      =					False
      _SCREAMING_SNAKE_CASE      =					False
      _SCREAMING_SNAKE_CASE      =					True



      def 					SCREAMING_SNAKE_CASE__			(				self    :				Tuple	):
        super().setUp()

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

        lowerCAmelCase_       :    Dict								=			MaMaaaTokenizer.from_pretrained(self.tmpdirname	)
        tokenizer.save_pretrained(self.tmpdirname	)



      def 					SCREAMING_SNAKE_CASE__			(				self    :				List[str]   ,      **SCREAMING_SNAKE_CASE_    :				str	):
        return MaMaaaTokenizer.from_pretrained(self.tmpdirname   ,      **SCREAMING_SNAKE_CASE_	)



      def 					SCREAMING_SNAKE_CASE__			(				self    :				Tuple   ,      SCREAMING_SNAKE_CASE_    :				Optional[Any]	):
        return (
            "This is a test",
            "This is a test",
        )



      def 					SCREAMING_SNAKE_CASE__			(				self    :				Dict	):
        lowerCAmelCase_       :    Tuple								=			'</s>'
        lowerCAmelCase_       :    Dict								=			0

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



      def 					SCREAMING_SNAKE_CASE__			(				self    :				Union[str, Any]	):
        lowerCAmelCase_       :    Dict								=			self.get_tokenizer()
        lowerCAmelCase_       :    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(SCREAMING_SNAKE_CASE_	)   ,      tokenizer.vocab_size + len(tokenizer.get_added_vocab()	)	)



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



      def 					SCREAMING_SNAKE_CASE__			(				self    :				List[str]	):
        lowerCAmelCase_       :    Any								=			self.get_tokenizer()

        lowerCAmelCase_       :    Any								=			tokenizer.tokenize('This is a test'	)
        self.assertListEqual(SCREAMING_SNAKE_CASE_   ,      ['▁This', '▁is', '▁a', '▁t', 'est']	)

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

        lowerCAmelCase_       :    int								=			tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]	)
        self.assertListEqual(SCREAMING_SNAKE_CASE_   ,      ['▁This', '▁is', '▁a', '▁t', 'est']	)

        lowerCAmelCase_       :    List[str]								=			tokenizer.convert_tokens_to_string(SCREAMING_SNAKE_CASE_	)
        self.assertEqual(SCREAMING_SNAKE_CASE_   ,      'This is a test'	)





      @slow
      def 					SCREAMING_SNAKE_CASE__			(				self    :				Tuple	):
        # fmt: off
        lowerCAmelCase_       :    str								=			{'input_ids': [[1_2_8_0_2_2, 1_1_0_1_0_8, 3_9_7, 1_1, 3_8_2_7_2, 2_2_4_7, 1_2_4_8_1_1, 2_8_5, 1_8_1_0_5, 1_5_8_6, 2_0_7, 7, 3_9_5_3_4, 4_4_2_8, 3_9_7, 1_0_1_9, 1_8_1_0_5, 1_5_8_6, 2_0_7, 7, 4_1_3_3_7, 1_6_7_8_6, 2_4_1, 7, 2_0_2_1_4, 1_7, 1_2_5_6_9_0, 1_0_3_9_8, 7, 4_4_3_7_8, 5_8_0_6_9, 6_8_3_4_2, 7_7_9_8, 7_3_4_3, 1_1, 2_9_9, 3_3_3_1_0, 4, 1_5_8, 3_7_3_5_0, 9_4_0_7_7, 4_5_6_9, 2_9_9, 3_3_3_1_0, 9_0, 4, 5_2_8_4_0, 2_9_0, 4, 3_1_2_7_0, 1_1_2, 2_9_9, 6_8_2, 4, 5_2_8_4_0, 3_9_9_5_3, 1_4_0_7_9, 1_9_3, 5_2_5_1_9, 9_0_8_9_4, 1_7_8_9_4, 1_2_0_6_9_7, 1_1, 4_0_4_4_5, 5_5_1, 1_7, 1_0_1_9, 5_2_5_1_9, 9_0_8_9_4, 1_7_7_5_6, 9_6_3, 1_1, 4_0_4_4_5, 4_8_0, 1_7, 9_7_9_2, 1_1_2_0, 5_1_7_3, 1_3_9_3, 6_2_4_0, 1_6_7_8_6, 2_4_1, 1_2_0_9_9_6, 2_8, 1_2_4_5, 1_3_9_3, 1_1_8_2_4_0, 1_1_1_2_3, 1_0_1_9, 9_3_6_1_2, 2_6_9_1, 1_0_6_1_8, 9_8_0_5_8, 1_2_0_4_0_9, 1_9_2_8, 2_7_9, 4, 4_0_6_8_3, 3_6_7, 1_7_8, 2_0_7, 1_0_1_9, 1_0_3, 1_0_3_1_2_1, 5_0_6, 6_5_2_9_6, 5, 2], [1_2_8_0_2_2, 2_1_2_1_7, 3_6_7, 1_1_7, 1_2_5_4_5_0, 1_2_8, 7_1_9, 7, 7_3_0_8, 4_0, 9_3_6_1_2, 1_2_6_6_9, 1_1_1_6, 1_6_7_0_4, 7_1, 1_7_7_8_5, 3_6_9_9, 1_5_5_9_2, 3_5, 1_4_4, 9_5_8_4, 2_4_1, 1_1_9_4_3, 7_1_3, 9_5_0, 7_9_9, 2_2_4_7, 8_8_4_2_7, 1_5_0, 1_4_9, 1_1_8_8_1_3, 1_2_0_7_0_6, 1_0_1_9, 1_0_6_9_0_6, 8_1_5_1_8, 2_8, 1_2_2_4, 2_2_7_9_9, 3_9_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_2_8_0_2_2, 1_6_5_8, 1_2_3_3_1_1, 5_1_5_5, 5_5_7_8, 4_7_2_2, 2_7_9, 1_4_9_4_7, 2_3_6_6, 1_1_2_0, 1_1_9_7, 1_4, 1_3_4_8, 9_2_3_2, 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=SCREAMING_SNAKE_CASE_   ,      model_name='facebook/m2m100_418M'   ,      revision='c168bae485c864188cf9aa0e4108b0b6934dc91e'   ,      )







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




      """simple docstring"""




      _SCREAMING_SNAKE_CASE      =					"""facebook/m2m100_418M"""
      _SCREAMING_SNAKE_CASE      =					[
          """In my opinion, there are two levels of response from the French government.""",
          """NSA Affair Emphasizes Complete Lack of Debate on Intelligence""",
      ]
      _SCREAMING_SNAKE_CASE      =					[
          """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
      _SCREAMING_SNAKE_CASE      =					[EN_CODE, 593, 1949, 11_5781, 4, 7_1586, 4234, 6_0633, 12_6233, 432, 12_3808, 1_5592, 1197, 11_7132, 12_0618, 5, 2]



      @classmethod
      def 					SCREAMING_SNAKE_CASE__			(				cls    :				Optional[int]	):
        lowerCAmelCase_       :    MaMaaaTokenizer								=			MaMaaaTokenizer.from_pretrained(
            cls.checkpoint_name   ,      src_lang='en'   ,      tgt_lang='fr'	)
        lowerCAmelCase_       :    Any								=			1
        return cls



      def 					SCREAMING_SNAKE_CASE__			(				self    :				Optional[int]	):
        self.assertEqual(self.tokenizer.get_lang_id('ar'	)   ,      1_2_8_0_0_6	)
        self.assertEqual(self.tokenizer.get_lang_id('en'	)   ,      1_2_8_0_2_2	)
        self.assertEqual(self.tokenizer.get_lang_id('ro'	)   ,      1_2_8_0_7_6	)
        self.assertEqual(self.tokenizer.get_lang_id('mr'	)   ,      1_2_8_0_6_3	)



      def 					SCREAMING_SNAKE_CASE__			(				self    :				str	):
        lowerCAmelCase_       :    str								=			self.tokenizer.get_vocab()
        self.assertEqual(len(SCREAMING_SNAKE_CASE_	)   ,      self.tokenizer.vocab_size	)
        self.assertEqual(vocab['<unk>']   ,      3	)
        self.assertIn(self.tokenizer.get_lang_token('en'	)   ,      SCREAMING_SNAKE_CASE_	)



      def 					SCREAMING_SNAKE_CASE__			(				self    :				int	):
        lowerCAmelCase_       :    int								=			'en'
        lowerCAmelCase_       :    Tuple								=			self.tokenizer.batch_encode_plus(self.src_text	).input_ids[0]
        self.assertListEqual(self.expected_src_tokens   ,      SCREAMING_SNAKE_CASE_	)



      def 					SCREAMING_SNAKE_CASE__			(				self    :				Tuple	):
        self.assertIn(SCREAMING_SNAKE_CASE_   ,      self.tokenizer.all_special_ids	)
        # fmt: off
        lowerCAmelCase_       :    str								=			[FR_CODE, 5_3_6_4, 8_2, 8_6_4_2, 4, 2_9_4, 4_7, 8, 1_4_0_2_8, 1_3_6, 3_2_8_6, 9_7_0_6, 6, 9_0_7_9_7, 6, 1_4_4_0_1_2, 1_6_2, 8_8_1_2_8, 3_0_0_6_1, 5, 2]
        # fmt: on
        lowerCAmelCase_       :    Any								=			self.tokenizer.decode(SCREAMING_SNAKE_CASE_   ,      skip_special_tokens=SCREAMING_SNAKE_CASE_	)
        lowerCAmelCase_       :    Dict								=			self.tokenizer.decode(generated_ids[1:]   ,      skip_special_tokens=SCREAMING_SNAKE_CASE_	)
        self.assertEqual(SCREAMING_SNAKE_CASE_   ,      SCREAMING_SNAKE_CASE_	)
        self.assertNotIn(self.tokenizer.eos_token   ,      SCREAMING_SNAKE_CASE_	)



      def 					SCREAMING_SNAKE_CASE__			(				self    :				Dict	):
        lowerCAmelCase_       :    str								=			tempfile.mkdtemp()
        lowerCAmelCase_       :    Optional[Any]								=			self.tokenizer.lang_token_to_id
        self.tokenizer.save_pretrained(SCREAMING_SNAKE_CASE_	)
        lowerCAmelCase_       :    Union[str, Any]								=			MaMaaaTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_	)
        self.assertDictEqual(new_tok.lang_token_to_id   ,      SCREAMING_SNAKE_CASE_	)



      @require_torch
      def 					SCREAMING_SNAKE_CASE__			(				self    :				Union[str, Any]	):
        lowerCAmelCase_       :    List[str]								=			'en'
        lowerCAmelCase_       :    Optional[Any]								=			'fr'

        lowerCAmelCase_       :    Tuple								=			self.tokenizer(self.src_text   ,      text_target=self.tgt_text   ,      padding=SCREAMING_SNAKE_CASE_   ,      return_tensors='pt'	)

        lowerCAmelCase_       :    Tuple								=			shift_tokens_right(
            batch['labels']   ,      self.tokenizer.pad_token_id   ,      self.tokenizer.eos_token_id	)

        for k in batch:
          lowerCAmelCase_       :    Dict								=			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 					SCREAMING_SNAKE_CASE__			(				self    :				Tuple	):
        lowerCAmelCase_       :    Union[str, Any]								=			'mr'
        self.assertListEqual(self.tokenizer.prefix_tokens   ,      [self.tokenizer.get_lang_id('mr'	)]	)
        self.assertListEqual(self.tokenizer.suffix_tokens   ,      [self.tokenizer.eos_token_id]	)

        lowerCAmelCase_       :    Tuple								=			'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 					SCREAMING_SNAKE_CASE__			(				self    :				Any	):
        lowerCAmelCase_       :    Dict								=			'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	)]	)

        lowerCAmelCase_       :    int								=			'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 					SCREAMING_SNAKE_CASE__			(				self    :				Dict	):
        lowerCAmelCase_       :    int								=			self.tokenizer._build_translation_inputs('A test'   ,      return_tensors='pt'   ,      src_lang='en'   ,      tgt_lang='ar'	)

        self.assertEqual(
            nested_simplify(SCREAMING_SNAKE_CASE_	)   ,      {
                # en_XX, A, test, EOS
                'input_ids': [[1_2_8_0_2_2, 5_8, 4_1_8_3, 2]],
                'attention_mask': [[1, 1, 1, 1]],
                # ar_AR
                'forced_bos_token_id': 1_2_8_0_0_6,
            }   ,      )










"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


lowercase__		:    Optional[int]				   =     {
    """configuration_trocr""": ["""TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TrOCRConfig"""],
    """processing_trocr""": ["""TrOCRProcessor"""],
}


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__		:    Dict				   =     [
         """TROCR_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """TrOCRForCausalLM""",
         """TrOCRPreTrainedModel""",
     ]


if TYPE_CHECKING:
     from .configuration_trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig
     from .processing_trocr import TrOCRProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel

else:
     import sys

     lowercase__		:    int				   =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





