


"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


__UpperCAmelCase     					=   {
    "albert-base-v1": "https://huggingface.co/albert-base-v1/resolve/main/config.json",
    "albert-large-v1": "https://huggingface.co/albert-large-v1/resolve/main/config.json",
    "albert-xlarge-v1": "https://huggingface.co/albert-xlarge-v1/resolve/main/config.json",
    "albert-xxlarge-v1": "https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json",
    "albert-base-v2": "https://huggingface.co/albert-base-v2/resolve/main/config.json",
    "albert-large-v2": "https://huggingface.co/albert-large-v2/resolve/main/config.json",
    "albert-xlarge-v2": "https://huggingface.co/albert-xlarge-v2/resolve/main/config.json",
    "albert-xxlarge-v2": "https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json",
}

class 			lowercase_	(			a_    ):
      __magic_name__  :				Tuple 							=					"albert"







      def __init__(   self			:				Any		,	_lowercase			:				int=3_0_0_0_0		,	_lowercase			:				str=1_2_8		,	_lowercase			:				Optional[Any]=4_0_9_6		,	_lowercase			:				Optional[Any]=1_2		,	_lowercase			:				Any=1		,	_lowercase			:				Any=6_4		,	_lowercase			:				Dict=1_6_3_8_4		,	_lowercase			:				Optional[Any]=1		,	_lowercase			:				List[str]="gelu_new"		,	_lowercase			:				List[Any]=0		,	_lowercase			:				List[Any]=0		,	_lowercase			:				List[Any]=5_1_2		,	_lowercase			:				List[Any]=2		,	_lowercase			:				int=0.02		,	_lowercase			:				Optional[Any]=1e-1_2		,	_lowercase			:				List[str]=0.1		,	_lowercase			:				Union[str, Any]="absolute"		,	_lowercase			:				str=0		,	_lowercase			:				Optional[Any]=2		,	_lowercase			:				str=3		,	**_lowercase			:				int		,	):
        super().__init__(pad_token_id=_lowercase		,	bos_token_id=_lowercase		,	eos_token_id=_lowercase		,	**_lowercase     )

        lowerCAmelCase__     :     Optional[Any]										=       vocab_size
        lowerCAmelCase__     :     Dict										=       embedding_size
        lowerCAmelCase__     :     Union[str, Any]										=       hidden_size
        lowerCAmelCase__     :     Optional[int]										=       num_hidden_layers
        lowerCAmelCase__     :     List[Any]										=       num_hidden_groups
        lowerCAmelCase__     :     List[str]										=       num_attention_heads
        lowerCAmelCase__     :     Tuple										=       inner_group_num
        lowerCAmelCase__     :     Any										=       hidden_act
        lowerCAmelCase__     :     List[Any]										=       intermediate_size
        lowerCAmelCase__     :     Any										=       hidden_dropout_prob
        lowerCAmelCase__     :     int										=       attention_probs_dropout_prob
        lowerCAmelCase__     :     Optional[Any]										=       max_position_embeddings
        lowerCAmelCase__     :     Optional[Any]										=       type_vocab_size
        lowerCAmelCase__     :     int										=       initializer_range
        lowerCAmelCase__     :     List[str]										=       layer_norm_eps
        lowerCAmelCase__     :     Union[str, Any]										=       classifier_dropout_prob
        lowerCAmelCase__     :     Optional[int]										=       position_embedding_type

class 			lowercase_	(			a_    ):







      @property
      def 					_lowerCAmelCase							(   self			:				Union[str, Any]     ):







        if self.task == "multiple-choice":
          lowerCAmelCase__     :     str										=       {0: "batch", 1: "choice", 2: "sequence"}
        else:
          lowerCAmelCase__     :     int										=       {0: "batch", 1: "sequence"}
        return OrderedDict(
            [
                ("input_ids", dynamic_axis),
                ("attention_mask", dynamic_axis),
                ("token_type_ids", dynamic_axis),
            ]     )




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


UpperCAmelCase   :    Union[str, Any]     =		logging.get_logger(__name__)

UpperCAmelCase   :    List[Any]     =		{
    "SCUT-DLVCLab/lilt-roberta-en-base": (
        "https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json"
    ),
}







class        __lowercase       (							a_  ):



		"""simple docstring"""

		UpperCamelCase     :					List[str]			       =		"lilt"







		def __init__( self		,      A=3_05_22		,      A=7_68		,      A=12		,      A=12		,      A=30_72		,      A="gelu"		,      A=0.1		,      A=0.1		,      A=5_12		,      A=2		,      A=0.02		,      A=1e-1_2		,      A=0		,      A="absolute"		,      A=None		,      A=4		,      A=10_24		,      **A		,      )  -> List[Any]:







					'''simple docstring'''







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

					lowerCamelCase    		=  vocab_size
					lowerCamelCase    		=  hidden_size
					lowerCamelCase    		=  num_hidden_layers
					lowerCamelCase    		=  num_attention_heads
					lowerCamelCase    		=  hidden_act
					lowerCamelCase    		=  intermediate_size
					lowerCamelCase    		=  hidden_dropout_prob
					lowerCamelCase    		=  attention_probs_dropout_prob
					lowerCamelCase    		=  max_position_embeddings
					lowerCamelCase    		=  type_vocab_size
					lowerCamelCase    		=  initializer_range
					lowerCamelCase    		=  layer_norm_eps
					lowerCamelCase    		=  position_embedding_type
					lowerCamelCase    		=  classifier_dropout
					lowerCamelCase    		=  channel_shrink_ratio
					lowerCamelCase    		=  max_ad_position_embeddings

