






"""simple docstring"""





import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


A__					: Tuple=	get_tests_dir("""fixtures/test_sentencepiece.model""")

if is_torch_available():
  from transformers.models.mbart.modeling_mbart import shift_tokens_right

A__					: Dict=	25_00_04
A__					: Union[str, Any]=	25_00_20
@require_sentencepiece
@require_tokenizers
class    __lowerCamelCase    (  lowerCamelCase__							,	unittest.TestCase  ):
   a      :				Optional[int] 						=MBartaaTokenizer
   a      :				List[str] 						=MBartaaTokenizerFast
   a      :				Tuple 						=True
   a      :				str 						=True

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       int:
       super().setUp()

       # We have a SentencePiece fixture for testing
       UpperCamelCase__         =    MBartaaTokenizer(__lowerCamelCase ,				src_lang='en_XX' ,				tgt_lang='ro_RO' ,				keep_accents=__lowerCamelCase      )
       tokenizer.save_pretrained(self.tmpdirname      )

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Any:
       UpperCamelCase__         =    '''<s>'''
       UpperCamelCase__         =    0

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

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Dict:
       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(__lowerCamelCase      ) ,				1054      )

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       List[Any]:
       self.assertEqual(self.get_tokenizer().vocab_size ,				1054      )

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       str:
       UpperCamelCase__         =    MBartaaTokenizer(__lowerCamelCase ,				src_lang='en_XX' ,				tgt_lang='ro_RO' ,				keep_accents=__lowerCamelCase      )

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

       self.assertListEqual(
           tokenizer.convert_tokens_to_ids(__lowerCamelCase      ) ,				[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]] ,				)

       UpperCamelCase__         =    tokenizer.tokenize('I was born in 92000, and this is falsé.'      )
       self.assertListEqual(
           __lowerCamelCase ,				[SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '9', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', 'é', '.'] ,				)
       UpperCamelCase__         =    tokenizer.convert_tokens_to_ids(__lowerCamelCase      )
       self.assertListEqual(
           __lowerCamelCase ,				[
               value + tokenizer.fairseq_offset
               for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
           ] ,				)

       UpperCamelCase__         =    tokenizer.convert_ids_to_tokens(__lowerCamelCase      )
       self.assertListEqual(
           __lowerCamelCase ,				[SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '<unk>', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', '<unk>', '.'] ,				)

   @slow
   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       List[Any]:
       UpperCamelCase__         =    {'''input_ids''': [[25_0004, 1_1062, 8_2772, 7, 15, 8_2772, 538, 5_1529, 237, 1_7198, 1290, 206, 9, 21_5175, 1314, 136, 1_7198, 1290, 206, 9, 5_6359, 42, 12_2009, 9, 1_6466, 16, 8_7344, 4537, 9, 4717, 7_8381, 6, 15_9958, 7, 15, 2_4480, 618, 4, 527, 2_2693, 5428, 4, 2777, 2_4480, 9874, 4, 4_3523, 594, 4, 803, 1_8392, 3_3189, 18, 4, 4_3523, 2_4447, 1_2399, 100, 2_4955, 8_3658, 9626, 14_4057, 15, 839, 2_2335, 16, 136, 2_4955, 8_3658, 8_3479, 15, 3_9102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 12_2009, 11_5774, 23, 805, 1328, 4_6876, 7, 136, 5_3894, 1940, 4_2227, 4_1159, 1_7721, 823, 425, 4, 2_7512, 9_8722, 206, 136, 5531, 4970, 919, 1_7336, 5, 2], [25_0004, 2_0080, 618, 83, 8_2775, 47, 479, 9, 1517, 73, 5_3894, 333, 8_0581, 11_0117, 1_8811, 5256, 1295, 51, 15_2526, 297, 7986, 390, 12_4416, 538, 3_5431, 214, 98, 1_5044, 2_5737, 136, 7108, 4_3701, 23, 756, 13_5355, 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], [25_0004, 581, 6_3773, 11_9455, 6, 14_7797, 8_8203, 7, 645, 70, 21, 3285, 1_0269, 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]], '''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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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=__lowerCamelCase ,				model_name='facebook/mbart-large-50' ,				revision='d3913889c59cd5c9e456b269c376325eabad57e2' ,				)







   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       List[Any]:






       if not self.test_slow_tokenizer:
           # as we don't have a slow version, we can't compare the outputs between slow and fast versions
           return

       UpperCamelCase__         =    (self.rust_tokenizer_class, '''hf-internal-testing/tiny-random-mbart50''', {})
       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
           with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'      ):
               UpperCamelCase__         =    self.rust_tokenizer_class.from_pretrained(__lowerCamelCase ,				**__lowerCamelCase      )
               UpperCamelCase__         =    self.tokenizer_class.from_pretrained(__lowerCamelCase ,				**__lowerCamelCase      )

               UpperCamelCase__         =    tempfile.mkdtemp()

               UpperCamelCase__         =    tokenizer_r.save_pretrained(__lowerCamelCase      )
               UpperCamelCase__         =    tokenizer_p.save_pretrained(__lowerCamelCase      )

               # Checks it save with the same files + the tokenizer.json file for the fast one
               self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files      )      )
               UpperCamelCase__         =    tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f      )
               self.assertSequenceEqual(__lowerCamelCase ,				__lowerCamelCase      )

               # Checks everything loads correctly in the same way
               UpperCamelCase__         =    tokenizer_r.from_pretrained(__lowerCamelCase      )
               UpperCamelCase__         =    tokenizer_p.from_pretrained(__lowerCamelCase      )

               # Check special tokens are set accordingly on Rust and Python
               for key in tokenizer_pp.special_tokens_map:
                   self.assertTrue(hasattr(__lowerCamelCase ,				__lowerCamelCase      )      )
                   # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
                   # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

               shutil.rmtree(__lowerCamelCase      )

               # Save tokenizer rust, legacy_format=True
               UpperCamelCase__         =    tempfile.mkdtemp()

               UpperCamelCase__         =    tokenizer_r.save_pretrained(__lowerCamelCase ,				legacy_format=__lowerCamelCase      )
               UpperCamelCase__         =    tokenizer_p.save_pretrained(__lowerCamelCase      )

               # Checks it save with the same files
               self.assertSequenceEqual(__lowerCamelCase ,				__lowerCamelCase      )

               # Checks everything loads correctly in the same way
               UpperCamelCase__         =    tokenizer_r.from_pretrained(__lowerCamelCase      )
               UpperCamelCase__         =    tokenizer_p.from_pretrained(__lowerCamelCase      )

               # Check special tokens are set accordingly on Rust and Python
               for key in tokenizer_pp.special_tokens_map:
                   self.assertTrue(hasattr(__lowerCamelCase ,				__lowerCamelCase      )      )

               shutil.rmtree(__lowerCamelCase      )

               # Save tokenizer rust, legacy_format=False
               UpperCamelCase__         =    tempfile.mkdtemp()

               UpperCamelCase__         =    tokenizer_r.save_pretrained(__lowerCamelCase ,				legacy_format=__lowerCamelCase      )
               UpperCamelCase__         =    tokenizer_p.save_pretrained(__lowerCamelCase      )

               # Checks it saved the tokenizer.json file
               self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files      )      )

               # Checks everything loads correctly in the same way
               UpperCamelCase__         =    tokenizer_r.from_pretrained(__lowerCamelCase      )
               UpperCamelCase__         =    tokenizer_p.from_pretrained(__lowerCamelCase      )

               # Check special tokens are set accordingly on Rust and Python
               for key in tokenizer_pp.special_tokens_map:
                   self.assertTrue(hasattr(__lowerCamelCase ,				__lowerCamelCase      )      )

               shutil.rmtree(__lowerCamelCase      )







@require_torch
@require_sentencepiece
@require_tokenizers
class    __lowerCamelCase    (  unittest.TestCase  ):
   a      :				List[str] 						="""facebook/mbart-large-50-one-to-many-mmt"""
   a      :				str 						=[
       """ UN Chief Says There Is No Military Solution in Syria""",
       """ Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.""",
   ]
   a      :				Optional[int] 						=[
       """Şeful ONU declară că nu există o soluţie militară în Siria""",
       """Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"""
       """ pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"""
       """ face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.""",
   ]
   a      :				Any 						=[EN_CODE, 8_2_7_4, 1_2_7_8_7_3, 2_5_9_1_6, 7, 8_6_2_2, 2_0_7_1, 4_3_8, 6_7_4_8_5, 5_3, 1_8_7_8_9_5, 2_3, 5_1_7_1_2, 2]

   @classmethod
   def 						SCREAMING_SNAKE_CASE__ (					cls      )		->       int:
       UpperCamelCase__         =    MBartaaTokenizer.from_pretrained(
           cls.checkpoint_name ,				src_lang='en_XX' ,				tgt_lang='ro_RO'      )
       UpperCamelCase__         =    1
       return cls

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       List[Any]:
       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR'] ,				25_0001      )
       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN'] ,				25_0004      )
       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO'] ,				25_0020      )
       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN'] ,				25_0038      )

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       str:
       UpperCamelCase__         =    self.tokenizer.batch_encode_plus(self.src_text      ).input_ids[0]
       self.assertListEqual(self.expected_src_tokens ,				__lowerCamelCase      )

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       int:
       self.assertIn(__lowerCamelCase ,				self.tokenizer.all_special_ids      )
       UpperCamelCase__         =    [RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
       UpperCamelCase__         =    self.tokenizer.decode(__lowerCamelCase ,				skip_special_tokens=__lowerCamelCase      )
       UpperCamelCase__         =    self.tokenizer.decode(generated_ids[1:] ,				skip_special_tokens=__lowerCamelCase      )
       self.assertEqual(__lowerCamelCase ,				__lowerCamelCase      )
       self.assertNotIn(self.tokenizer.eos_token ,				__lowerCamelCase      )

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Tuple:
       UpperCamelCase__         =    ['''this is gunna be a long sentence ''' * 20]
       assert isinstance(src_text[0] ,				__lowerCamelCase      )
       UpperCamelCase__         =    10
       UpperCamelCase__         =    self.tokenizer(__lowerCamelCase ,				max_length=__lowerCamelCase ,				truncation=__lowerCamelCase      ).input_ids[0]
       self.assertEqual(ids[0] ,				__lowerCamelCase      )
       self.assertEqual(ids[-1] ,				2      )
       self.assertEqual(len(__lowerCamelCase      ) ,				__lowerCamelCase      )

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Optional[int]:
       self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']      ) ,				[25_0053, 25_0001]      )

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       List[str]:
       UpperCamelCase__         =    tempfile.mkdtemp()
       UpperCamelCase__         =    self.tokenizer.fairseq_tokens_to_ids
       self.tokenizer.save_pretrained(__lowerCamelCase      )
       UpperCamelCase__         =    MBartaaTokenizer.from_pretrained(__lowerCamelCase      )
       self.assertDictEqual(new_tok.fairseq_tokens_to_ids ,				__lowerCamelCase      )

   @require_torch
   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Union[str, Any]:
       UpperCamelCase__         =    self.tokenizer(self.src_text ,				text_target=self.tgt_text ,				padding=__lowerCamelCase ,				return_tensors='pt'      )
       UpperCamelCase__         =    shift_tokens_right(batch['labels'] ,				self.tokenizer.pad_token_id      )

       # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
       assert batch.input_ids[1][0] == EN_CODE
       assert batch.input_ids[1][-1] == 2
       assert batch.labels[1][0] == RO_CODE
       assert batch.labels[1][-1] == 2
       assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]

   @require_torch
   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Optional[int]:
       UpperCamelCase__         =    self.tokenizer(
           self.src_text ,				text_target=self.tgt_text ,				padding=__lowerCamelCase ,				truncation=__lowerCamelCase ,				max_length=len(self.expected_src_tokens      ) ,				return_tensors='pt' ,				)
       UpperCamelCase__         =    shift_tokens_right(batch['labels'] ,				self.tokenizer.pad_token_id      )

       self.assertIsInstance(__lowerCamelCase ,				__lowerCamelCase      )

       self.assertEqual((2, 14) ,				batch.input_ids.shape      )
       self.assertEqual((2, 14) ,				batch.attention_mask.shape      )
       UpperCamelCase__         =    batch.input_ids.tolist()[0]
       self.assertListEqual(self.expected_src_tokens ,				__lowerCamelCase      )
       self.assertEqual(2 ,				batch.decoder_input_ids[0, 0]      )  # decoder_start_token_id
       # Test that special tokens are reset
       self.assertEqual(self.tokenizer.prefix_tokens ,				[EN_CODE]      )
       self.assertEqual(self.tokenizer.suffix_tokens ,				[self.tokenizer.eos_token_id]      )

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Optional[int]:
       UpperCamelCase__         =    self.tokenizer(self.src_text ,				padding=__lowerCamelCase ,				truncation=__lowerCamelCase ,				max_length=3 ,				return_tensors='pt'      )
       UpperCamelCase__         =    self.tokenizer(
           text_target=self.tgt_text ,				padding=__lowerCamelCase ,				truncation=__lowerCamelCase ,				max_length=10 ,				return_tensors='pt'      )
       UpperCamelCase__         =    targets['''input_ids''']
       UpperCamelCase__         =    shift_tokens_right(__lowerCamelCase ,				self.tokenizer.pad_token_id      )

       self.assertEqual(batch.input_ids.shape[1] ,				3      )
       self.assertEqual(batch.decoder_input_ids.shape[1] ,				10      )







   @require_torch
   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Dict:
       UpperCamelCase__         =    self.tokenizer._build_translation_inputs(
           'A test' ,				return_tensors='pt' ,				src_lang='en_XX' ,				tgt_lang='ar_AR'      )

       self.assertEqual(
           nested_simplify(__lowerCamelCase      ) ,				{
               # en_XX, A, test, EOS
               'input_ids': [[25_0004, 62, 3034, 2]],
               'attention_mask': [[1, 1, 1, 1]],
               # ar_AR
               'forced_bos_token_id': 25_0001,
           } ,				)








"""simple docstring"""





import unittest
from pathlib import Path
from tempfile import TemporaryDirectory

from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow_text, require_tf, slow


if is_tf_available():
  import tensorflow as tf

if is_tensorflow_text_available():
  from transformers.models.bert import TFBertTokenizer


A__					: List[Any]=	["""bert-base-uncased""", """bert-base-cased"""]
A__					: Optional[int]=	"""hf-internal-testing/tiny-bert-tf-only"""

if is_tf_available():
  class    __lowerCamelCase    (  tf.keras.Model  ):

     def __init__(					self ,				snake_case_      )		->       Optional[int]:
         super().__init__()
         UpperCamelCase__         =    tokenizer
         UpperCamelCase__         =    AutoConfig.from_pretrained(snake_case_      )
         UpperCamelCase__         =    TFAutoModel.from_config(snake_case_      )







     def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       int:
         UpperCamelCase__         =    self.tokenizer(snake_case_      )
         UpperCamelCase__         =    self.bert(**snake_case_      )
         return out["pooler_output"]
@require_tf
@require_tensorflow_text
class    __lowerCamelCase    (  unittest.TestCase  ):

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       str:
       super().setUp()

       UpperCamelCase__         =    [
           BertTokenizer.from_pretrained(snake_case_      ) for checkpoint in (TOKENIZER_CHECKPOINTS * 2)
       ]  # repeat for when fast_bert_tokenizer=false
       UpperCamelCase__         =    [TFBertTokenizer.from_pretrained(snake_case_      ) for checkpoint in TOKENIZER_CHECKPOINTS] + [
           TFBertTokenizer.from_pretrained(snake_case_ ,				use_fast_bert_tokenizer=snake_case_      )
           for checkpoint in TOKENIZER_CHECKPOINTS
       ]
       assert len(self.tokenizers      ) == len(self.tf_tokenizers      )

       UpperCamelCase__         =    [
           'This is a straightforward English test sentence.',
           'This one has some weird characters\rto\nsee\r\nif  those\u00E9break things.',
           'Now we\'re going to add some Chinese: 一 二 三 一二三',
           'And some much more rare Chinese: 齉 堃 齉堃',
           'Je vais aussi écrire en français pour tester les accents',
           'Classical Irish also has some unusual characters, so in they go: Gaelaċ, ꝼ',
       ]
       UpperCamelCase__         =    list(zip(self.test_sentences ,				self.test_sentences[::-1]      )      )

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Any:
       for tokenizer, tf_tokenizer in zip(self.tokenizers ,				self.tf_tokenizers      ):
           for test_inputs in (self.test_sentences, self.paired_sentences):
               UpperCamelCase__         =    tokenizer(snake_case_ ,				return_tensors='tf' ,				padding='longest'      )
               UpperCamelCase__         =    tf_tokenizer(snake_case_      )

               for key in python_outputs.keys():
                   self.assertTrue(tf.reduce_all(python_outputs[key].shape == tf_outputs[key].shape      )      )
                   self.assertTrue(tf.reduce_all(tf.cast(python_outputs[key] ,				tf.intaa      ) == tf_outputs[key]      )      )

   @slow
   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       str:
       for tf_tokenizer in self.tf_tokenizers:
           UpperCamelCase__         =    tf_tokenizer(self.paired_sentences      )
           UpperCamelCase__         =    tf_tokenizer(
               text=[sentence[0] for sentence in self.paired_sentences] ,				text_pair=[sentence[1] for sentence in self.paired_sentences] ,				)
           for key in merged_outputs.keys():
               self.assertTrue(tf.reduce_all(tf.cast(merged_outputs[key] ,				tf.intaa      ) == separated_outputs[key]      )      )

   @slow
   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Dict:
       for tf_tokenizer in self.tf_tokenizers:
           UpperCamelCase__         =    tf.function(snake_case_      )
           for test_inputs in (self.test_sentences, self.paired_sentences):
               UpperCamelCase__         =    tf.constant(snake_case_      )
               UpperCamelCase__         =    compiled_tokenizer(snake_case_      )
               UpperCamelCase__         =    tf_tokenizer(snake_case_      )

               for key in eager_outputs.keys():
                   self.assertTrue(tf.reduce_all(eager_outputs[key] == compiled_outputs[key]      )      )







   @slow
   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       List[str]:
       for tf_tokenizer in self.tf_tokenizers:
           UpperCamelCase__         =    ModelToSave(tokenizer=snake_case_      )
           UpperCamelCase__         =    tf.convert_to_tensor(self.test_sentences      )
           UpperCamelCase__         =    model(snake_case_      )  # Build model with some sample inputs
           with TemporaryDirectory() as tempdir:
               UpperCamelCase__         =    Path(snake_case_      ) / 'saved.model'
               model.save(snake_case_      )
               UpperCamelCase__         =    tf.keras.models.load_model(snake_case_      )
           UpperCamelCase__         =    loaded_model(snake_case_      )
           # We may see small differences because the loaded model is compiled, so we need an epsilon for the test
           self.assertLessEqual(tf.reduce_max(tf.abs(out - loaded_output      )      ) ,				1E-5      )




