
from typing import Callable, Optional, Union

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


_A   =     logging.get_logger(__name__)

_A   =     {
    "microsoft/xprophetnet-large-wiki100-cased": (
        "https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json"
    ),
}





class 	_lowerCAmelCase					(	A_       ):
				_lowercase					='''xlm-prophetnet'''
				_lowercase					=['''past_key_values''']
				_lowercase					={
				    '''num_attention_heads''': '''num_encoder_attention_heads''',
				}




				def __init__(					self				,				_UpperCamelCase = 0.1				,				_UpperCamelCase = "gelu"				,				_UpperCamelCase = 30_522				,				_UpperCamelCase = 1_024				,				_UpperCamelCase = 4_096				,				_UpperCamelCase = 12				,				_UpperCamelCase = 16				,				_UpperCamelCase = 4_096				,				_UpperCamelCase = 12				,				_UpperCamelCase = 16				,				_UpperCamelCase = 0.1				,				_UpperCamelCase = 0.1				,				_UpperCamelCase = 512				,				_UpperCamelCase = 0.02				,				_UpperCamelCase = True				,				_UpperCamelCase = True				,				_UpperCamelCase = 0				,				_UpperCamelCase = 2				,				_UpperCamelCase = 32				,				_UpperCamelCase = 128				,				_UpperCamelCase = False				,				_UpperCamelCase = 0.0				,				_UpperCamelCase = True				,				_UpperCamelCase = 0				,				_UpperCamelCase = 1				,				_UpperCamelCase = 2				,				**_UpperCamelCase				,				)				->      Union[str, Any]:
							lowerCAmelCase_						=	vocab_size
							lowerCAmelCase_						=	hidden_size
							lowerCAmelCase_						=	encoder_ffn_dim
							lowerCAmelCase_						=	num_encoder_layers
							lowerCAmelCase_						=	num_encoder_attention_heads
							lowerCAmelCase_						=	decoder_ffn_dim
							lowerCAmelCase_						=	num_decoder_layers
							lowerCAmelCase_						=	num_decoder_attention_heads
							lowerCAmelCase_						=	max_position_embeddings
							lowerCAmelCase_						=	init_std  # Normal(0, this parameter)
							lowerCAmelCase_						=	activation_function

							# parameters for xlmprophetnet
							lowerCAmelCase_						=	ngram
							lowerCAmelCase_						=	num_buckets
							lowerCAmelCase_						=	relative_max_distance
							lowerCAmelCase_						=	disable_ngram_loss
							lowerCAmelCase_						=	eps

							# 3 Types of Dropout
							lowerCAmelCase_						=	attention_dropout
							lowerCAmelCase_						=	activation_dropout
							lowerCAmelCase_						=	dropout

							lowerCAmelCase_						=	use_cache

							super().__init__(
							    pad_token_id=_lowerCamelCase				,				bos_token_id=_lowerCamelCase				,				eos_token_id=_lowerCamelCase				,				is_encoder_decoder=_lowerCamelCase				,				add_cross_attention=_lowerCamelCase				,				decoder_start_token_id=_lowerCamelCase				,				**_lowerCamelCase				,				)




				@property
				def      __a						(					self     )				->      List[Any]:
							return self.num_encoder_layers + self.num_decoder_layers




				@num_hidden_layers.setter
				def      __a						(					self				,				_UpperCamelCase     )				->      Any:
							raise NotImplementedError(
							    "This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and"
							    " `num_decoder_layers`."     )





"""simple docstring"""



import logging

from transformers.configuration_utils import PretrainedConfig


UpperCAmelCase__          = logging.getLogger(__name__)

class       lowerCAmelCase__				(						A_	):
     __a						=					"""masked_bert"""







     def __init__(							self			:			Union[str, Any]    ,      _lowerCamelCase			:			Any=30522    ,      _lowerCamelCase			:			Union[str, Any]=768    ,      _lowerCamelCase			:			Tuple=12    ,      _lowerCamelCase			:			Any=12    ,      _lowerCamelCase			:			str=3072    ,      _lowerCamelCase			:			str="gelu"    ,      _lowerCamelCase			:			int=0.1    ,      _lowerCamelCase			:			Optional[int]=0.1    ,      _lowerCamelCase			:			Dict=512    ,      _lowerCamelCase			:			List[Any]=2    ,      _lowerCamelCase			:			int=0.0_2    ,      _lowerCamelCase			:			Union[str, Any]=1e-12    ,      _lowerCamelCase			:			Union[str, Any]=0    ,      _lowerCamelCase			:			List[str]="topK"    ,      _lowerCamelCase			:			Optional[Any]="constant"    ,      _lowerCamelCase			:			Optional[Any]=0.0    ,      **_lowerCamelCase			:			str    ,      ):
       super().__init__(pad_token_id=_lowerCamelCase    ,      **_lowerCamelCase			)

       _snake_case					     =       vocab_size
       _snake_case					     =       hidden_size
       _snake_case					     =       num_hidden_layers
       _snake_case					     =       num_attention_heads
       _snake_case					     =       hidden_act
       _snake_case					     =       intermediate_size
       _snake_case					     =       hidden_dropout_prob
       _snake_case					     =       attention_probs_dropout_prob
       _snake_case					     =       max_position_embeddings
       _snake_case					     =       type_vocab_size
       _snake_case					     =       initializer_range
       _snake_case					     =       layer_norm_eps
       _snake_case					     =       pruning_method
       _snake_case					     =       mask_init
       _snake_case					     =       mask_scale



