
"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE      =     {
    """configuration_lilt""": ["""LILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LiltConfig"""],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE      =     [
          """LILT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """LiltForQuestionAnswering""",
          """LiltForSequenceClassification""",
          """LiltForTokenClassification""",
          """LiltModel""",
          """LiltPreTrainedModel""",
      ]

if TYPE_CHECKING:
      from .configuration_lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_lilt import (
                LILT_PRETRAINED_MODEL_ARCHIVE_LIST,
                LiltForQuestionAnswering,
                LiltForSequenceClassification,
                LiltForTokenClassification,
                LiltModel,
                LiltPreTrainedModel,
            )

else:
      import sys

      SCREAMING_SNAKE_CASE      =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)







"""simple docstring"""


import unittest

from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
@require_sentencepiece
@slow  # see https://github.com/huggingface/transformers/issues/11457
class   __a  (      _lowerCAmelCase    ,     unittest.TestCase	):
       UpperCamelCase_		:					Any   =			BarthezTokenizer
       UpperCamelCase_		:					Tuple   =			BarthezTokenizerFast
       UpperCamelCase_		:					str   =			True
       UpperCamelCase_		:					Dict   =			True






       def 	_SCREAMING_SNAKE_CASE       (  self :							List[Any]			)->  int:







              """simple docstring"""
              super().setUp()

              UpperCamelCase					 =		BarthezTokenizerFast.from_pretrained("moussaKam/mbarthez"			)
              tokenizer.save_pretrained(self.tmpdirname			)
              tokenizer.save_pretrained(self.tmpdirname       ,      legacy_format=UpperCAmelCase_			)
              UpperCamelCase					 =		tokenizer






       def 	_SCREAMING_SNAKE_CASE       (  self :							Dict			)->  Optional[Any]:







              """simple docstring"""
              UpperCamelCase					 =		"<pad>"
              UpperCamelCase					 =		1

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






       def 	_SCREAMING_SNAKE_CASE       (  self :							Optional[int]			)->  int:







              """simple docstring"""
              UpperCamelCase					 =		list(self.get_tokenizer().get_vocab().keys()			)

              self.assertEqual(vocab_keys[0]       ,      "<s>"			)
              self.assertEqual(vocab_keys[1]       ,      "<pad>"			)
              self.assertEqual(vocab_keys[-1]       ,      "<mask>"			)
              self.assertEqual(len(UpperCAmelCase_			)       ,      101_122			)






       def 	_SCREAMING_SNAKE_CASE       (  self :							List[Any]			)->  List[str]:







              """simple docstring"""
              self.assertEqual(self.get_tokenizer().vocab_size       ,      101_122			)






       @require_torch
       def 	_SCREAMING_SNAKE_CASE       (  self :							Union[str, Any]			)->  int:







              """simple docstring"""
              UpperCamelCase					 =		["A long paragraph for summarization.", "Another paragraph for summarization."]
              UpperCamelCase					 =		[0, 57, 3_018, 70_307, 91, 2]

              UpperCamelCase					 =		self.tokenizer(
                  UpperCAmelCase_       ,      max_length=len(UpperCAmelCase_			)       ,      padding=UpperCAmelCase_       ,      truncation=UpperCAmelCase_       ,      return_tensors="pt"			)
              self.assertIsInstance(UpperCAmelCase_       ,      UpperCAmelCase_			)

              self.assertEqual((2, 6)       ,      batch.input_ids.shape			)
              self.assertEqual((2, 6)       ,      batch.attention_mask.shape			)
              UpperCamelCase					 =		batch.input_ids.tolist()[0]
              self.assertListEqual(UpperCAmelCase_       ,      UpperCAmelCase_			)






       def 	_SCREAMING_SNAKE_CASE       (  self :							Optional[int]			)->  Optional[int]:







              """simple docstring"""
              if not self.test_rust_tokenizer:
                     return

              UpperCamelCase					 =		self.get_tokenizer()
              UpperCamelCase					 =		self.get_rust_tokenizer()

              UpperCamelCase					 =		"I was born in 92000, and this is falsé."

              UpperCamelCase					 =		tokenizer.tokenize(UpperCAmelCase_			)
              UpperCamelCase					 =		rust_tokenizer.tokenize(UpperCAmelCase_			)
              self.assertListEqual(UpperCAmelCase_       ,      UpperCAmelCase_			)

              UpperCamelCase					 =		tokenizer.encode(UpperCAmelCase_       ,      add_special_tokens=UpperCAmelCase_			)
              UpperCamelCase					 =		rust_tokenizer.encode(UpperCAmelCase_       ,      add_special_tokens=UpperCAmelCase_			)
              self.assertListEqual(UpperCAmelCase_       ,      UpperCAmelCase_			)

              UpperCamelCase					 =		self.get_rust_tokenizer()
              UpperCamelCase					 =		tokenizer.encode(UpperCAmelCase_			)
              UpperCamelCase					 =		rust_tokenizer.encode(UpperCAmelCase_			)
              self.assertListEqual(UpperCAmelCase_       ,      UpperCAmelCase_			)






       @slow
       def 	_SCREAMING_SNAKE_CASE       (  self :							int			)->  Union[str, Any]:







              """simple docstring"""
              # fmt: off
              UpperCamelCase					 =		{"input_ids": [[0, 490, 14_328, 4_507, 354, 47, 43_669, 95, 25, 78_117, 20_215, 19_779, 190, 22, 400, 4, 35_343, 80_310, 603, 86, 24_937, 105, 33_438, 94_762, 196, 39_642, 7, 15, 15_933, 173, 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], [0, 10_534, 87, 25, 66, 3_358, 196, 55_289, 8, 82_961, 81, 2_204, 75_203, 7, 15, 763, 12_956, 216, 178, 14_328, 9_595, 1_377, 69_693, 7, 448, 71_021, 196, 18_106, 1_437, 13_974, 108, 9_083, 4, 49_315, 7, 39, 86, 1_326, 2_793, 46_333, 4, 448, 196, 74_588, 7, 49_315, 7, 39, 21, 822, 38_470, 74, 21, 66_723, 62_480, 8, 22_050, 5, 2]], "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, 0, 0, 0, 0, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
              # fmt: on

              # moussaKam/mbarthez is a french model. So we also use french texts.
              UpperCamelCase					 =		[
                  "Le transformeur est un modèle d'apprentissage profond introduit en 2017, "
                  "utilisé principalement dans le domaine du traitement automatique des langues (TAL).",
                  "À l'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus "
                  "pour gérer des données séquentielles, telles que le langage naturel, pour des tâches "
                  "telles que la traduction et la synthèse de texte.",
              ]

              self.tokenizer_integration_test_util(
                  expected_encoding=UpperCAmelCase_       ,      model_name="moussaKam/mbarthez"       ,      revision="c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6"       ,      sequences=UpperCAmelCase_       ,      )





