


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


snake_case__		:     str    				=				get_tests_dir('''fixtures/test_sentencepiece.model''')



@require_sentencepiece
@require_tokenizers
class 		snake_case_(       UpperCamelCase_							,					unittest.TestCase			):
     __UpperCamelCase  =					ReformerTokenizer
     __UpperCamelCase  =					ReformerTokenizerFast
     __UpperCamelCase  =					True
     __UpperCamelCase  =					False
     __UpperCamelCase  =					True






     def      lowerCamelCase__     (	self  :					Optional[int]				):
           super().setUp()

           lowerCAmelCase					:	Any       =   ReformerTokenizer(UpperCamelCase_					,				keep_accents=UpperCamelCase_				)
           tokenizer.save_pretrained(self.tmpdirname				)






     def      lowerCamelCase__     (	self  :					Dict				):
           lowerCAmelCase					:	List[Any]       =   '''<s>'''
           lowerCAmelCase					:	Union[str, Any]       =   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  :					Any				):
           lowerCAmelCase					:	List[str]       =   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_				)					,				1_0_0_0				)






     def      lowerCamelCase__     (	self  :					int				):
           self.assertEqual(self.get_tokenizer().vocab_size					,				1_0_0_0				)






     def      lowerCamelCase__     (	self  :					Any				):
           if not self.test_rust_tokenizer:
                 return

           lowerCAmelCase					:	Any       =   self.get_tokenizer()
           lowerCAmelCase					:	int       =   self.get_rust_tokenizer()

           lowerCAmelCase					:	List[Any]       =   '''I was born in 92000, and this is falsé.'''

           lowerCAmelCase					:	Union[str, Any]       =   tokenizer.tokenize(UpperCamelCase_				)
           lowerCAmelCase					:	Optional[Any]       =   rust_tokenizer.tokenize(UpperCamelCase_				)
           self.assertListEqual(UpperCamelCase_					,				UpperCamelCase_				)

           lowerCAmelCase					:	List[Any]       =   tokenizer.encode(UpperCamelCase_					,				add_special_tokens=UpperCamelCase_				)
           lowerCAmelCase					:	Dict       =   rust_tokenizer.encode(UpperCamelCase_					,				add_special_tokens=UpperCamelCase_				)
           self.assertListEqual(UpperCamelCase_					,				UpperCamelCase_				)

           lowerCAmelCase					:	List[str]       =   self.get_rust_tokenizer()
           lowerCAmelCase					:	Optional[Any]       =   tokenizer.encode(UpperCamelCase_				)
           lowerCAmelCase					:	List[str]       =   rust_tokenizer.encode(UpperCamelCase_				)
           self.assertListEqual(UpperCamelCase_					,				UpperCamelCase_				)






     def      lowerCamelCase__     (	self  :					List[Any]					,				UpperCamelCase_  :					str=1_5				):
           for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''				):
                       lowerCAmelCase					:	str       =   self.rust_tokenizer_class.from_pretrained(UpperCamelCase_					,				**UpperCamelCase_				)

                       # Simple input
                       lowerCAmelCase					:	Optional[Any]       =   '''This is a simple input'''
                       lowerCAmelCase					:	Optional[int]       =   ['''This is a simple input 1''', '''This is a simple input 2''']
                       lowerCAmelCase					:	Optional[int]       =   ('''This is a simple input''', '''This is a pair''')
                       lowerCAmelCase					:	int       =   [
                           ('''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  :					Any				):
           pass






     def      lowerCamelCase__     (	self  :					Optional[Any]				):
           lowerCAmelCase					:	Optional[Any]       =   ReformerTokenizer(UpperCamelCase_					,				keep_accents=UpperCamelCase_				)

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

           self.assertListEqual(
               tokenizer.convert_tokens_to_ids(UpperCamelCase_				)					,				[2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]					,				)

           lowerCAmelCase					:	Optional[int]       =   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''',
                   '''.''',
               ]					,				)
           lowerCAmelCase					:	Optional[Any]       =   tokenizer.convert_tokens_to_ids(UpperCamelCase_				)
           self.assertListEqual(
               UpperCamelCase_					,				[8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4]					,				)

           lowerCAmelCase					:	Union[str, Any]       =   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  :					List[str]				):
           return ReformerTokenizer.from_pretrained('''google/reformer-crime-and-punishment'''				)






     @slow
     def      lowerCamelCase__     (	self  :					List[Any]				):
           lowerCAmelCase					:	Optional[int]       =   '''Hello World!'''
           lowerCAmelCase					:	List[str]       =   [1_2_6, 3_2, 2_6_2, 1_5_2, 3_8, 7_2, 2_8_7]

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






     @slow
     def      lowerCamelCase__     (	self  :					str				):
           lowerCAmelCase					:	Tuple       =   (
               '''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'''
           )
           lowerCAmelCase					:	List[str]       =   [
               1_0_8,
               2_6_5,
               2_4,
               1_1_1,
               4,
               2_5_8,
               1_5_6,
               3_5,
               2_8,
               2_7_5,
               3,
               2_5_9,
               2_9_7,
               2_6_0,
               8_4,
               4,
               3_5,
               1_1_0,
               4_4,
               8,
               2_5_9,
               9_1,
               2_6_8,
               2_1,
               1_1,
               2_0_9,
               2_7_4,
               1_0_9,
               2_6_6,
               2_7_7,
               1_1_7,
               8_6,
               9_3,
               3_1_5,
               2_5_8,
               2_7_8,
               2_5_8,
               2_7_7,
               2_5_8,
               0,
               2_5_8,
               2_8_8,
               2_5_8,
               3_1_9,
               2_5_8,
               0,
               2_5_8,
               0,
               2_5_8,
               0,
               2_5_8,
               0,
               2_5_8,
               2_8_7,
               2_5_8,
               3_1_5,
               2_5_8,
               2_8_9,
               2_5_8,
               2_7_8,
               9_9,
               2_6_9,
               2_6_6,
               2_6_2,
               8,
               2_5_9,
               2_4_1,
               4,
               2_1_7,
               2_3_0,
               2_6_8,
               2_6_6,
               5_5,
               1_6_8,
               1_0_6,
               7_5,
               1_9_3,
               2_6_6,
               2_2_3,
               2_7,
               4_9,
               2_6,
               2_8_2,
               2_5,
               2_6_4,
               2_9_9,
               1_9,
               2_6,
               0,
               2_5_8,
               2_7_7,
               1_1_7,
               8_6,
               9_3,
               1_7_6,
               1_8_3,
               2_7_0,
               1_1,
               2_6_2,
               4_2,
               6_1,
               2_6_5,
           ]

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






     @require_torch
     @slow
     def      lowerCamelCase__     (	self  :					Tuple				):
           import torch

           from transformers import ReformerConfig, ReformerModel

           # Build sequence
           lowerCAmelCase					:	Union[str, Any]       =   list(self.big_tokenizer.get_vocab().keys()				)[:1_0]
           lowerCAmelCase					:	Optional[int]       =   ''' '''.join(UpperCamelCase_				)
           lowerCAmelCase					:	List[Any]       =   self.big_tokenizer.encode_plus(UpperCamelCase_					,				return_tensors='''pt'''				)
           lowerCAmelCase					:	int       =   self.big_tokenizer.batch_encode_plus([sequence, sequence]					,				return_tensors='''pt'''				)

           lowerCAmelCase					:	Dict       =   ReformerConfig()
           # The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
           lowerCAmelCase					:	int       =   encoded_sequence['''input_ids'''].shape
           lowerCAmelCase					:	Optional[Any]       =   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  :					Tuple				):
           # fmt: off
           lowerCAmelCase					:	List[Any]       =   {'''input_ids''': [[1_0_8, 2_6_5, 2_4, 1_1_1, 4, 2_5_8, 1_5_6, 7, 5_1, 2_7_9, 5_8, 7, 7_6, 2_5, 6_9, 2_7_8], [1_4_0, 2_4_3, 2_6_4, 1_3_4, 1_7, 2_6_7, 7_7, 2_6_3, 2_2, 2_6_2, 2_9_7, 2_5_8, 3_0_4, 1_7_7, 2_7_9, 2_6_6, 1_4, 8_9, 1_3, 3_5, 2_6_1, 2_9_9, 2_7_2, 1_3_7, 2_7_5, 2_7_8]], '''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
           lowerCAmelCase					:	Union[str, Any]       =   [
               '''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 collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


snake_case__		:     Optional[Any]    				=				namedtuple(
    '''_TestCommandArgs''',
    [
        '''dataset''',
        '''name''',
        '''cache_dir''',
        '''data_dir''',
        '''all_configs''',
        '''save_infos''',
        '''ignore_verifications''',
        '''force_redownload''',
        '''clear_cache''',
    ],
    defaults=[None, None, None, False, False, False, False, False],
)


def      _snake_case						(						_snake_case				:			List[Any] ,   _snake_case				:			List[str]			):
      return (abs(source - target			) / target) < 0.01






@pytest.mark.integration
def      _snake_case						(						_snake_case				:			Any			):
      lowerCAmelCase					:	Union[str, Any]       =   _TestCommandArgs(dataset=_snake_case ,   all_configs=_snake_case ,   save_infos=_snake_case			)
      lowerCAmelCase					:	str       =   TestCommand(*_snake_case			)
      test_command.run()
      lowerCAmelCase					:	str       =   os.path.join(_snake_case ,   '''README.md'''			)
      assert os.path.exists(_snake_case			)
      lowerCAmelCase					:	Tuple       =   DatasetInfosDict.from_directory(_snake_case			)
      lowerCAmelCase					:	List[str]       =   DatasetInfosDict(
          {
              '''default''': DatasetInfo(
                  features=Features(
                      {
                          '''tokens''': Sequence(Value('''string'''			)			),
                          '''ner_tags''': Sequence(
                              ClassLabel(names=['''O''', '''B-PER''', '''I-PER''', '''B-ORG''', '''I-ORG''', '''B-LOC''', '''I-LOC''']			)			),
                          '''langs''': Sequence(Value('''string'''			)			),
                          '''spans''': Sequence(Value('''string'''			)			),
                      }			) ,   splits=[
                      {
                          '''name''': '''train''',
                          '''num_bytes''': 2351563,
                          '''num_examples''': 10000,
                      },
                      {
                          '''name''': '''validation''',
                          '''num_bytes''': 238418,
                          '''num_examples''': 1000,
                      },
                  ] ,   download_size=3940680 ,   dataset_size=2589981 ,   )
          }			)
      assert dataset_infos.keys() == expected_dataset_infos.keys()
      for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
            lowerCAmelCase,      lowerCAmelCase					:	Union[str, Any]       =   getattr(dataset_infos['''default'''] ,   _snake_case			), getattr(expected_dataset_infos['''default'''] ,   _snake_case			)
            if key == "num_bytes":
                  assert is_apercent_close(_snake_case ,   _snake_case			)
            elif key == "splits":
                  assert list(_snake_case			) == list(_snake_case			)
                  for split in result:
                        assert result[split].name == expected[split].name
                        assert result[split].num_examples == expected[split].num_examples
                        assert is_apercent_close(result[split].num_bytes ,   expected[split].num_bytes			)
            else:
                  result == expected


