





'''simple docstring'''






from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__:     List[Any]										=    logging.get_logger(__name__)

UpperCamelCase__:     int										=    {
    "SCUT-DLVCLab/lilt-roberta-en-base": (
        "https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json"
    ),
}

class        SCREAMING_SNAKE_CASE(							__A    ):







	"""simple docstring"""






	lowerCamelCase__    				= """lilt"""







	def __init__(		self    :  Tuple	,    __snake_case    :  Any=30522	,    __snake_case    :  Dict=768	,    __snake_case    :  int=12	,    __snake_case    :  Union[str, Any]=12	,    __snake_case    :  Dict=3072	,    __snake_case    :  Dict="gelu"	,    __snake_case    :  Optional[int]=0.1	,    __snake_case    :  Any=0.1	,    __snake_case    :  Optional[int]=512	,    __snake_case    :  Union[str, Any]=2	,    __snake_case    :  Optional[int]=0.02	,    __snake_case    :  Dict=1E-12	,    __snake_case    :  Optional[Any]=0	,    __snake_case    :  Tuple="absolute"	,    __snake_case    :  Any=None	,    __snake_case    :  Union[str, Any]=4	,    __snake_case    :  Dict=1024	,    **__snake_case    :  Optional[int]	,    )    ->	Optional[int]:
								super().__init__(pad_token_id=__snake_case	,    **__snake_case	)

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










'''simple docstring'''






import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict


@pytest.mark.parametrize(
    '''split_dict'''     ,   [
        SplitDict(),
        SplitDict({'''train''': SplitInfo(name='''train'''     ,   num_bytes=1337     ,   num_examples=42     ,   dataset_name='''my_dataset'''						)}						),
        SplitDict({'''train''': SplitInfo(name='''train'''     ,   num_bytes=1337     ,   num_examples=42						)}						),
        SplitDict({'''train''': SplitInfo()}						),
    ]     ,   )
def 				snake_case_  (      _lowerCAmelCase						:		SplitDict						)   ->     List[Any]:
							UpperCAmelCase				: str											=	split_dict._to_yaml_list()
							assert len(_lowerCAmelCase						) == len(_lowerCAmelCase						)
							UpperCAmelCase				: Optional[int]											=	SplitDict._from_yaml_list(_lowerCAmelCase						)
							for split_name, split_info in split_dict.items():
														# dataset_name field is deprecated, and is therefore not part of the YAML dump
														UpperCAmelCase				: Optional[Any]											=	None
														# the split name of split_dict takes over the name of the split info object
														UpperCAmelCase				: Dict											=	split_name
							assert split_dict == reloaded




@pytest.mark.parametrize(
    '''split_info'''     ,   [SplitInfo(), SplitInfo(dataset_name=_lowerCAmelCase						), SplitInfo(dataset_name='''my_dataset'''						)]						)
def 				snake_case_  (      _lowerCAmelCase						:		List[Any]						)   ->     Optional[Any]:
							# For backward compatibility, we need asdict(split_dict) to return split info dictrionaries with the "dataset_name"
							# field even if it's deprecated. This way old versionso of `datasets` can still reload dataset_infos.json files
							UpperCAmelCase				: Any											=	asdict(SplitDict({'''train''': split_info}						)						)
							assert "dataset_name" in split_dict_asdict["train"]
							assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name





