


"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


snake_case__		:     Optional[Any]    				=				logging.get_logger(__name__)

snake_case__		:     Union[str, Any]    				=				{
    '''facebook/data2vec-text-base''': '''https://huggingface.co/data2vec/resolve/main/config.json''',
}



class 		snake_case_(       a__			):
     __UpperCamelCase  =					'''data2vec-text'''






     def __init__(	self  :					int					,				UpperCamelCase_  :					Optional[int]=3_0_5_2_2					,				UpperCamelCase_  :					List[Any]=7_6_8					,				UpperCamelCase_  :					Any=1_2					,				UpperCamelCase_  :					Optional[Any]=1_2					,				UpperCamelCase_  :					Union[str, Any]=3_0_7_2					,				UpperCamelCase_  :					Optional[int]="gelu"					,				UpperCamelCase_  :					str=0.1					,				UpperCamelCase_  :					int=0.1					,				UpperCamelCase_  :					Tuple=5_1_2					,				UpperCamelCase_  :					Union[str, Any]=2					,				UpperCamelCase_  :					int=0.02					,				UpperCamelCase_  :					int=1E-12					,				UpperCamelCase_  :					str=1					,				UpperCamelCase_  :					Optional[Any]=0					,				UpperCamelCase_  :					List[Any]=2					,				UpperCamelCase_  :					List[Any]="absolute"					,				UpperCamelCase_  :					Any=True					,				UpperCamelCase_  :					Any=None					,				**UpperCamelCase_  :					List[Any]					,				):
           super().__init__(pad_token_id=UpperCamelCase_					,				bos_token_id=UpperCamelCase_					,				eos_token_id=UpperCamelCase_					,				**UpperCamelCase_				)

           lowerCAmelCase					:	str       =   vocab_size
           lowerCAmelCase					:	Union[str, Any]       =   hidden_size
           lowerCAmelCase					:	Any       =   num_hidden_layers
           lowerCAmelCase					:	List[str]       =   num_attention_heads
           lowerCAmelCase					:	Union[str, Any]       =   hidden_act
           lowerCAmelCase					:	List[str]       =   intermediate_size
           lowerCAmelCase					:	Tuple       =   hidden_dropout_prob
           lowerCAmelCase					:	Dict       =   attention_probs_dropout_prob
           lowerCAmelCase					:	Optional[int]       =   max_position_embeddings
           lowerCAmelCase					:	Any       =   type_vocab_size
           lowerCAmelCase					:	str       =   initializer_range
           lowerCAmelCase					:	List[str]       =   layer_norm_eps
           lowerCAmelCase					:	str       =   position_embedding_type
           lowerCAmelCase					:	Union[str, Any]       =   use_cache
           lowerCAmelCase					:	List[str]       =   classifier_dropout



class 		snake_case_(       a__			):






     @property
     def      lowerCamelCase__     (	self  :					Optional[Any]				):
           if self.task == "multiple-choice":
                 lowerCAmelCase					:	Any       =   {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
           else:
                 lowerCAmelCase					:	Any       =   {0: '''batch''', 1: '''sequence'''}
           return OrderedDict(
               [
                   ('''input_ids''', dynamic_axis),
                   ('''attention_mask''', dynamic_axis),
               ]				)






"""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


