

"""simple docstring"""






import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCamelCase										=		get_tests_dir("fixtures/test_sentencepiece.model")
@require_sentencepiece
@require_tokenizers
class        _lowercase					(     __UpperCAmelCase   , unittest.TestCase     ):
     _lowerCamelCase     =       ReformerTokenizer
     _lowerCamelCase     =       ReformerTokenizerFast
     _lowerCamelCase     =       True
     _lowerCamelCase     =       False
     _lowerCamelCase     =       True







     def 	lowerCAmelCase__    (      self       ):
      super().setUp()

      __magic_name__     =      ReformerTokenizer(UpperCamelCase_ ,						keep_accents=UpperCamelCase_       )
      tokenizer.save_pretrained(self.tmpdirname       )







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      '''<s>'''
      __magic_name__     =      1

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







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      list(self.get_tokenizer().get_vocab().keys()       )

      self.assertEqual(vocab_keys[0] ,						'''<unk>'''       )
      self.assertEqual(vocab_keys[1] ,						'''<s>'''       )
      self.assertEqual(vocab_keys[-1] ,						'''j'''       )
      self.assertEqual(len(UpperCamelCase_       ) ,						1000       )







     def 	lowerCAmelCase__    (      self       ):
      self.assertEqual(self.get_tokenizer().vocab_size ,						1000       )







     def 	lowerCAmelCase__    (      self       ):
      if not self.test_rust_tokenizer:
       return

      __magic_name__     =      self.get_tokenizer()
      __magic_name__     =      self.get_rust_tokenizer()

      __magic_name__     =      '''I was born in 92000, and this is falsé.'''

      __magic_name__     =      tokenizer.tokenize(UpperCamelCase_       )
      __magic_name__     =      rust_tokenizer.tokenize(UpperCamelCase_       )
      self.assertListEqual(UpperCamelCase_ ,						UpperCamelCase_       )

      __magic_name__     =      tokenizer.encode(UpperCamelCase_ ,						add_special_tokens=UpperCamelCase_       )
      __magic_name__     =      rust_tokenizer.encode(UpperCamelCase_ ,						add_special_tokens=UpperCamelCase_       )
      self.assertListEqual(UpperCamelCase_ ,						UpperCamelCase_       )

      __magic_name__     =      self.get_rust_tokenizer()
      __magic_name__     =      tokenizer.encode(UpperCamelCase_       )
      __magic_name__     =      rust_tokenizer.encode(UpperCamelCase_       )
      self.assertListEqual(UpperCamelCase_ ,						UpperCamelCase_       )







     def 	lowerCAmelCase__    (      self ,						UpperCamelCase_=15       ):
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''       ):
        __magic_name__     =      self.rust_tokenizer_class.from_pretrained(UpperCamelCase_ ,						**UpperCamelCase_       )

        # Simple input
        __magic_name__     =      '''This is a simple input'''
        __magic_name__     =      ['''This is a simple input 1''', '''This is a simple input 2''']
        __magic_name__     =      ('''This is a simple input''', '''This is a pair''')
        __magic_name__     =      [
            ('''This is a simple input 1''', '''This is a simple input 2'''),
            ('''This is a simple pair 1''', '''This is a simple pair 2'''),
        ]

        # Simple input tests
        self.assertRaises(UpperCamelCase_ ,						tokenizer_r.encode ,						UpperCamelCase_ ,						max_length=UpperCamelCase_ ,						padding='''max_length'''       )

        # Simple input
        self.assertRaises(UpperCamelCase_ ,						tokenizer_r.encode_plus ,						UpperCamelCase_ ,						max_length=UpperCamelCase_ ,						padding='''max_length'''       )

        # Simple input
        self.assertRaises(
            UpperCamelCase_ ,						tokenizer_r.batch_encode_plus ,						UpperCamelCase_ ,						max_length=UpperCamelCase_ ,						padding='''max_length''' ,						)

        # Pair input
        self.assertRaises(UpperCamelCase_ ,						tokenizer_r.encode ,						UpperCamelCase_ ,						max_length=UpperCamelCase_ ,						padding='''max_length'''       )

        # Pair input
        self.assertRaises(UpperCamelCase_ ,						tokenizer_r.encode_plus ,						UpperCamelCase_ ,						max_length=UpperCamelCase_ ,						padding='''max_length'''       )

        # Pair input
        self.assertRaises(
            UpperCamelCase_ ,						tokenizer_r.batch_encode_plus ,						UpperCamelCase_ ,						max_length=UpperCamelCase_ ,						padding='''max_length''' ,						)







     def 	lowerCAmelCase__    (      self       ):
      pass







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      ReformerTokenizer(UpperCamelCase_ ,						keep_accents=UpperCamelCase_       )

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

      self.assertListEqual(
          tokenizer.convert_tokens_to_ids(UpperCamelCase_       ) ,						[285, 46, 10, 170, 382] ,						)

      __magic_name__     =      tokenizer.tokenize('''I was born in 92000, and this is falsé.'''       )
      self.assertListEqual(
          UpperCamelCase_ ,						[
              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''',
              '''.''',
          ] ,						)
      __magic_name__     =      tokenizer.convert_tokens_to_ids(UpperCamelCase_       )
      self.assertListEqual(
          UpperCamelCase_ ,						[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4] ,						)

      __magic_name__     =      tokenizer.convert_ids_to_tokens(UpperCamelCase_       )
      self.assertListEqual(
          UpperCamelCase_ ,						[
              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>''',
              '''.''',
          ] ,						)







     @cached_property
     def 	lowerCAmelCase__    (      self       ):
      return ReformerTokenizer.from_pretrained('''google/reformer-crime-and-punishment'''       )







     @slow
     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      '''Hello World!'''
      __magic_name__     =      [126, 32, 262, 152, 38, 72, 287]

      self.assertListEqual(UpperCamelCase_ ,						self.big_tokenizer.encode(UpperCamelCase_       )       )







     @slow
     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      (
          '''This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'''
          ''' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'''
      )
      __magic_name__     =      [
          108,
          265,
          24,
          111,
          4,
          258,
          156,
          35,
          28,
          275,
          3,
          259,
          297,
          260,
          84,
          4,
          35,
          110,
          44,
          8,
          259,
          91,
          268,
          21,
          11,
          209,
          274,
          109,
          266,
          277,
          117,
          86,
          93,
          315,
          258,
          278,
          258,
          277,
          258,
          0,
          258,
          288,
          258,
          319,
          258,
          0,
          258,
          0,
          258,
          0,
          258,
          0,
          258,
          287,
          258,
          315,
          258,
          289,
          258,
          278,
          99,
          269,
          266,
          262,
          8,
          259,
          241,
          4,
          217,
          230,
          268,
          266,
          55,
          168,
          106,
          75,
          193,
          266,
          223,
          27,
          49,
          26,
          282,
          25,
          264,
          299,
          19,
          26,
          0,
          258,
          277,
          117,
          86,
          93,
          176,
          183,
          270,
          11,
          262,
          42,
          61,
          265,
      ]

      self.assertListEqual(UpperCamelCase_ ,						self.big_tokenizer.encode(UpperCamelCase_       )       )







     @require_torch
     @slow
     def 	lowerCAmelCase__    (      self       ):
      import torch

      from transformers import ReformerConfig, ReformerModel

      # Build sequence
      __magic_name__     =      list(self.big_tokenizer.get_vocab().keys()       )[:10]
      __magic_name__     =      ''' '''.join(UpperCamelCase_       )
      __magic_name__     =      self.big_tokenizer.encode_plus(UpperCamelCase_ ,						return_tensors='''pt'''       )
      __magic_name__     =      self.big_tokenizer.batch_encode_plus([sequence, sequence] ,						return_tensors='''pt'''       )

      __magic_name__     =      ReformerConfig()
      # The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
      __magic_name__     =      encoded_sequence['''input_ids'''].shape
      __magic_name__     =      ReformerModel(UpperCamelCase_       )

      # Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
      assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

      with torch.no_grad():
       model(**UpperCamelCase_       )
       model(**UpperCamelCase_       )







     @slow
     def 	lowerCAmelCase__    (      self       ):
      # fmt: off
      __magic_name__     =      {'''input_ids''': [[108, 265, 24, 111, 4, 258, 156, 7, 51, 279, 58, 7, 76, 25, 69, 278], [140, 243, 264, 134, 17, 267, 77, 263, 22, 262, 297, 258, 304, 177, 279, 266, 14, 89, 13, 35, 261, 299, 272, 137, 275, 278]], '''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]]}  # noqa: E501
      # fmt: on

      # This tokenizer does not know some characters like ")".
      # That is the reason why we use very simple texts here.
      # Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
      __magic_name__     =      [
          '''This is a very simple sentence.''',
          '''The quick brown fox jumps over the lazy dog.''',
      ]

      self.tokenizer_integration_test_util(
          expected_encoding=UpperCamelCase_ ,						model_name='''google/reformer-crime-and-punishment''' ,						revision='''0e6c3decb8211d49bf881013425dc8b0448b3f5a''' ,						padding=UpperCamelCase_ ,						sequences=UpperCamelCase_ ,						)




"""simple docstring"""






import os
from tempfile import TemporaryDirectory
from unittest import TestCase

import pytest
from absl.testing import parameterized

from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
from datasets.iterable_dataset import IterableDataset
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.file_utils import cached_path


__lowerCamelCase										=		[
    {"dataset": "wikipedia", "config_name": "20220301.de"},
    {"dataset": "wikipedia", "config_name": "20220301.en"},
    {"dataset": "wikipedia", "config_name": "20220301.fr"},
    {"dataset": "wikipedia", "config_name": "20220301.frr"},
    {"dataset": "wikipedia", "config_name": "20220301.it"},
    {"dataset": "wikipedia", "config_name": "20220301.simple"},
    {"dataset": "snli", "config_name": "plain_text"},
    {"dataset": "eli5", "config_name": "LFQA_reddit"},
    {"dataset": "wiki40b", "config_name": "en"},
    {"dataset": "wiki_dpr", "config_name": "psgs_w100.nq.compressed"},
    {"dataset": "wiki_dpr", "config_name": "psgs_w100.nq.no_index"},
    {"dataset": "wiki_dpr", "config_name": "psgs_w100.multiset.no_index"},
    {"dataset": "natural_questions", "config_name": "default"},
]





def 	lowercase      (   __UpperCamelCase=True						) ->      List[Any]:
 if with_config:
  return [
      {
          "testcase_name": d["dataset"] + "/" + d["config_name"],
          "dataset": d["dataset"],
          "config_name": d["config_name"],
      }
      for d in DATASETS_ON_HF_GCP
  ]
 else:
  return [
      {"testcase_name": dataset, "dataset": dataset} for dataset in {d["dataset"] for d in DATASETS_ON_HF_GCP}
  ]
@parameterized.named_parameters(list_datasets_on_hf_gcp_parameters(with_config=__UpperCAmelCase     )     )
class        _lowercase					(     __UpperCAmelCase     ):
     _lowerCamelCase     =       None
     _lowerCamelCase     =       None







     def 	lowerCAmelCase__    (      self ,						UpperCamelCase_ ,						UpperCamelCase_       ):
      with TemporaryDirectory() as tmp_dir:
       __magic_name__     =      dataset_module_factory(UpperCamelCase_ ,						cache_dir=UpperCamelCase_       )

       __magic_name__     =      import_main_class(dataset_module.module_path ,						dataset=UpperCamelCase_       )

       __magic_name__     =      builder_cls(
           cache_dir=UpperCamelCase_ ,						config_name=UpperCamelCase_ ,						hash=dataset_module.hash ,						)

       __magic_name__     =      '''/'''.join(
           [
               HF_GCP_BASE_URL,
               builder_instance._relative_data_dir(with_hash=UpperCamelCase_       ).replace(os.sep ,						'''/'''       ),
               config.DATASET_INFO_FILENAME,
           ]       )
       __magic_name__     =      cached_path(UpperCamelCase_ ,						cache_dir=UpperCamelCase_       )
       self.assertTrue(os.path.exists(UpperCamelCase_       )       )





@pytest.mark.integration
def 	lowercase      (   __UpperCamelCase						) ->      Tuple:
 __magic_name__     =      tmp_path_factory.mktemp('''test_hf_gcp'''						) / '''test_wikipedia_simple'''
 __magic_name__     =      dataset_module_factory('''wikipedia'''      ,   cache_dir=__UpperCamelCase						)
 __magic_name__     =      import_main_class(dataset_module.module_path						)
 __magic_name__     =      builder_cls(
     cache_dir=__UpperCamelCase      ,   config_name='''20220301.frr'''      ,   hash=dataset_module.hash      ,   )
 # use the HF cloud storage, not the original download_and_prepare that uses apache-beam
 __magic_name__     =      None
 builder_instance.download_and_prepare()
 __magic_name__     =      builder_instance.as_dataset()
 assert ds





@pytest.mark.integration
def 	lowercase      (   __UpperCamelCase						) ->      Tuple:
 __magic_name__     =      dataset_module_factory('''wikipedia'''      ,   cache_dir=__UpperCamelCase						)
 __magic_name__     =      import_main_class(dataset_module.module_path      ,   dataset=__UpperCamelCase						)
 __magic_name__     =      builder_cls(
     cache_dir=__UpperCamelCase      ,   config_name='''20220301.frr'''      ,   hash=dataset_module.hash      ,   )
 __magic_name__     =      builder_instance.as_streaming_dataset()
 assert ds
 assert isinstance(__UpperCamelCase      ,   __UpperCamelCase						)
 assert "train" in ds
 assert isinstance(ds['''train''']      ,   __UpperCamelCase						)
 assert next(iter(ds['''train''']						)						)

