

import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset







@pytest.mark.parametrize("dataset_size"				,	[None, 4_00 * 2**20, 6_00 * 2**20]    )
@pytest.mark.parametrize("input_in_memory_max_size"				,	["default", 0, 1_00 * 2**20, 9_00 * 2**20]    )
def 			A_      (    _UpperCAmelCase				,	_UpperCAmelCase				,	_UpperCAmelCase    ):
						if input_in_memory_max_size != "default":
												monkeypatch.setattr(datasets.config				,	"IN_MEMORY_MAX_SIZE"				,	_UpperCAmelCase    )
						SCREAMING_SNAKE_CASE_: Any  		=       datasets.config.IN_MEMORY_MAX_SIZE
						if input_in_memory_max_size == "default":
												assert in_memory_max_size == 0
						else:
												assert in_memory_max_size == input_in_memory_max_size
						if dataset_size and in_memory_max_size:
												SCREAMING_SNAKE_CASE_: Optional[Any]  		=       dataset_size < in_memory_max_size
						else:
												SCREAMING_SNAKE_CASE_: Tuple  		=       False
						SCREAMING_SNAKE_CASE_: str  		=       is_small_dataset(_UpperCAmelCase    )
						assert result == expected













"""simple docstring"""



import logging

from transformers.configuration_utils import PretrainedConfig


a_ =			logging.getLogger(__name__)






class 		__snake_case					(		SCREAMING_SNAKE_CASE__     ):





 """simple docstring"""


 _lowerCamelCase        =     """masked_bert"""

 def __init__(    self					,						__lowerCamelCase=3_0522					,						__lowerCamelCase=768					,						__lowerCamelCase=12					,						__lowerCamelCase=12					,						__lowerCamelCase=3072					,						__lowerCamelCase="gelu"					,						__lowerCamelCase=0.1					,						__lowerCamelCase=0.1					,						__lowerCamelCase=512					,						__lowerCamelCase=2					,						__lowerCamelCase=0.0_2					,						__lowerCamelCase=1e-1_2					,						__lowerCamelCase=0					,						__lowerCamelCase="topK"					,						__lowerCamelCase="constant"					,						__lowerCamelCase=0.0					,						**__lowerCamelCase					,						):



     '''simple docstring'''




     super().__init__(pad_token_id=__lowerCamelCase					,						**__lowerCamelCase  )

     __A    :						Dict						 =     vocab_size
     __A    :						Union[str, Any]						 =     hidden_size
     __A    :						Tuple						 =     num_hidden_layers
     __A    :						Tuple						 =     num_attention_heads
     __A    :						Optional[Any]						 =     hidden_act
     __A    :						List[str]						 =     intermediate_size
     __A    :						Any						 =     hidden_dropout_prob
     __A    :						Optional[Any]						 =     attention_probs_dropout_prob
     __A    :						Any						 =     max_position_embeddings
     __A    :						str						 =     type_vocab_size
     __A    :						List[Any]						 =     initializer_range
     __A    :						str						 =     layer_norm_eps
     __A    :						Optional[int]						 =     pruning_method
     __A    :						str						 =     mask_init
     __A    :						Any						 =     mask_scale




