





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


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

lowerCamelCase__				  =   12_8022
lowerCamelCase__				  =   12_8028



@require_sentencepiece
class      __SCREAMING_SNAKE_CASE    (						_UpperCamelCase		,  unittest.TestCase   ):







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__							:Any	     =					MaMaaaTokenizer
  SCREAMING_SNAKE_CASE__							:Optional[Any]	     =					False
  SCREAMING_SNAKE_CASE__							:Tuple	     =					False
  SCREAMING_SNAKE_CASE__							:str	     =					True

  def    __SCREAMING_SNAKE_CASE				(		self   :       List[str]	)		->				str:
        super().setUp()

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

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

  def    __SCREAMING_SNAKE_CASE				(		self   :       Dict					,   **__a   :       Dict	)		->				Optional[int]:
        return MaMaaaTokenizer.from_pretrained(self.tmpdirname					,   **__a	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       str					,   __a   :       Union[str, Any]	)		->				int:
        return (
            "This is a test",
            "This is a test",
        )

  def    __SCREAMING_SNAKE_CASE				(		self   :       Any	)		->				Union[str, Any]:
        _UpperCamelCase      :	List[str]						=       "</s>"
        _UpperCamelCase      :	List[Any]						=       0

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

  def    __SCREAMING_SNAKE_CASE				(		self   :       List[str]	)		->				int:
        _UpperCamelCase      :	Tuple						=       self.get_tokenizer()
        _UpperCamelCase      :	str						=       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(__a	)					,   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   :       Dict	)		->				Optional[int]:
        pass

  def    __SCREAMING_SNAKE_CASE				(		self   :       List[str]	)		->				str:
        _UpperCamelCase      :	Optional[int]						=       self.get_tokenizer()

        _UpperCamelCase      :	Optional[int]						=       tokenizer.tokenize("This is a test"	)
        self.assertListEqual(__a					,   ["▁This", "▁is", "▁a", "▁t", "est"]	)

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

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

        _UpperCamelCase      :	Any						=       tokenizer.convert_tokens_to_string(__a	)
        self.assertEqual(__a					,   "This is a test"	)


  @slow
  def    __SCREAMING_SNAKE_CASE				(		self   :       List[str]	)		->				Tuple:
        # fmt: off
        _UpperCamelCase      :	List[Any]						=       {"input_ids": [[12_8022, 11_0108, 397, 11, 3_8272, 2247, 12_4811, 285, 1_8105, 1586, 207, 7, 3_9534, 4428, 397, 1019, 1_8105, 1586, 207, 7, 4_1337, 1_6786, 241, 7, 2_0214, 17, 12_5690, 1_0398, 7, 4_4378, 5_8069, 6_8342, 7798, 7343, 11, 299, 3_3310, 4, 158, 3_7350, 9_4077, 4569, 299, 3_3310, 90, 4, 5_2840, 290, 4, 3_1270, 112, 299, 682, 4, 5_2840, 3_9953, 1_4079, 193, 5_2519, 9_0894, 1_7894, 12_0697, 11, 4_0445, 551, 17, 1019, 5_2519, 9_0894, 1_7756, 963, 11, 4_0445, 480, 17, 9792, 1120, 5173, 1393, 6240, 1_6786, 241, 12_0996, 28, 1245, 1393, 11_8240, 1_1123, 1019, 9_3612, 2691, 1_0618, 9_8058, 12_0409, 1928, 279, 4, 4_0683, 367, 178, 207, 1019, 103, 10_3121, 506, 6_5296, 5, 2], [12_8022, 2_1217, 367, 117, 12_5450, 128, 719, 7, 7308, 40, 9_3612, 1_2669, 1116, 1_6704, 71, 1_7785, 3699, 1_5592, 35, 144, 9584, 241, 1_1943, 713, 950, 799, 2247, 8_8427, 150, 149, 11_8813, 12_0706, 1019, 10_6906, 8_1518, 28, 1224, 2_2799, 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], [12_8022, 1658, 12_3311, 5155, 5578, 4722, 279, 1_4947, 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=__a					,   model_name="facebook/m2m100_418M"					,   revision="c168bae485c864188cf9aa0e4108b0b6934dc91e"					,   )





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







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__							:str	     =					"facebook/m2m100_418M"
  SCREAMING_SNAKE_CASE__							: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",
  ]
  SCREAMING_SNAKE_CASE__							:Optional[int]	     =					[
      "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__							:int	     =					[EN_CODE, 593, 1_949, 115_781, 4, 71_586, 4_234, 60_633, 126_233, 432, 123_808, 15_592, 1_197, 117_132, 120_618, 5, 2]

  @classmethod
  def    __SCREAMING_SNAKE_CASE				(		cls   :       List[Any]	)		->				str:
        _UpperCamelCase      :	MaMaaaTokenizer						=       MaMaaaTokenizer.from_pretrained(
            cls.checkpoint_name					,   src_lang="en"					,   tgt_lang="fr"	)
        _UpperCamelCase      :	Union[str, Any]						=       1
        return cls

  def    __SCREAMING_SNAKE_CASE				(		self   :       Tuple	)		->				Optional[Any]:
        self.assertEqual(self.tokenizer.get_lang_id("ar"	)					,   12_8006	)
        self.assertEqual(self.tokenizer.get_lang_id("en"	)					,   12_8022	)
        self.assertEqual(self.tokenizer.get_lang_id("ro"	)					,   12_8076	)
        self.assertEqual(self.tokenizer.get_lang_id("mr"	)					,   12_8063	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       Union[str, Any]	)		->				Union[str, Any]:
        _UpperCamelCase      :	Union[str, Any]						=       self.tokenizer.get_vocab()
        self.assertEqual(len(__a	)					,   self.tokenizer.vocab_size	)
        self.assertEqual(vocab["<unk>"]					,   3	)
        self.assertIn(self.tokenizer.get_lang_token("en"	)					,   __a	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       Optional[int]	)		->				str:
        _UpperCamelCase      :	Union[str, Any]						=       "en"
        _UpperCamelCase      :	Union[str, Any]						=       self.tokenizer.batch_encode_plus(self.src_text	).input_ids[0]
        self.assertListEqual(self.expected_src_tokens					,   __a	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       List[str]	)		->				Optional[Any]:
        self.assertIn(__a					,   self.tokenizer.all_special_ids	)
        # fmt: off
        _UpperCamelCase      :	Union[str, Any]						=       [FR_CODE, 5364, 82, 8642, 4, 294, 47, 8, 1_4028, 136, 3286, 9706, 6, 9_0797, 6, 14_4012, 162, 8_8128, 3_0061, 5, 2]
        # fmt: on
        _UpperCamelCase      :	Dict						=       self.tokenizer.decode(__a					,   skip_special_tokens=__a	)
        _UpperCamelCase      :	Dict						=       self.tokenizer.decode(generated_ids[1:]					,   skip_special_tokens=__a	)
        self.assertEqual(__a					,   __a	)
        self.assertNotIn(self.tokenizer.eos_token					,   __a	)

  def    __SCREAMING_SNAKE_CASE				(		self   :       Any	)		->				Optional[Any]:
        _UpperCamelCase      :	Tuple						=       tempfile.mkdtemp()
        _UpperCamelCase      :	List[str]						=       self.tokenizer.lang_token_to_id
        self.tokenizer.save_pretrained(__a	)
        _UpperCamelCase      :	int						=       MaMaaaTokenizer.from_pretrained(__a	)
        self.assertDictEqual(new_tok.lang_token_to_id					,   __a	)

  @require_torch
  def    __SCREAMING_SNAKE_CASE				(		self   :       Optional[int]	)		->				Any:
        _UpperCamelCase      :	Optional[Any]						=       "en"
        _UpperCamelCase      :	int						=       "fr"

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

        _UpperCamelCase      :	Optional[int]						=       shift_tokens_right(
            batch["labels"]					,   self.tokenizer.pad_token_id					,   self.tokenizer.eos_token_id	)

        for k in batch:
              _UpperCamelCase      :	Any						=       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   :       int	)		->				Optional[Any]:
        _UpperCamelCase      :	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]	)

        _UpperCamelCase      :	Optional[int]						=       "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   :       Optional[int]	)		->				List[str]:
        _UpperCamelCase      :	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	)]	)

        _UpperCamelCase      :	List[str]						=       "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   :       Optional[Any]	)		->				Optional[Any]:
        _UpperCamelCase      :	Union[str, Any]						=       self.tokenizer._build_translation_inputs("A test"					,   return_tensors="pt"					,   src_lang="en"					,   tgt_lang="ar"	)

        self.assertEqual(
            nested_simplify(__a	)					,   {
                # en_XX, A, test, EOS
                "input_ids": [[12_8022, 58, 4183, 2]],
                "attention_mask": [[1, 1, 1, 1]],
                # ar_AR
                "forced_bos_token_id": 12_8006,
            }					,   )







"""simple docstring"""


lowerCamelCase__				  =   "\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"

lowerCamelCase__				  =   [{"type": "code", "content": INSTALL_CONTENT}]
lowerCamelCase__				  =   {
    "{processor_class}": "FakeProcessorClass",
    "{model_class}": "FakeModelClass",
    "{object_class}": "FakeObjectClass",
}
