

'''simple docstring'''
from collections import OrderedDict
from typing import Mapping

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


_lowerCamelCase      					=     logging.get_logger(__name__)

_lowerCamelCase      					=     {
    """facebook/xmod-base""": """https://huggingface.co/facebook/xmod-base/resolve/main/config.json""",
    """facebook/xmod-large-prenorm""": """https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json""",
    """facebook/xmod-base-13-125k""": """https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json""",
    """facebook/xmod-base-30-125k""": """https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json""",
    """facebook/xmod-base-30-195k""": """https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json""",
    """facebook/xmod-base-60-125k""": """https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json""",
    """facebook/xmod-base-60-265k""": """https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json""",
    """facebook/xmod-base-75-125k""": """https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json""",
    """facebook/xmod-base-75-269k""": """https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json""",
}
class 					_snake_case		(__SCREAMING_SNAKE_CASE):
			__A  :	str        ="xmod"






			def __init__(  self			,_snake_case=3_05_22			,_snake_case=7_68			,_snake_case=12			,_snake_case=12			,_snake_case=30_72			,_snake_case="gelu"			,_snake_case=0.1			,_snake_case=0.1			,_snake_case=5_12			,_snake_case=2			,_snake_case=0.02			,_snake_case=1E-12			,_snake_case=1			,_snake_case=0			,_snake_case=2			,_snake_case="absolute"			,_snake_case=True			,_snake_case=None			,_snake_case=False			,_snake_case=2			,_snake_case=False			,_snake_case=True			,_snake_case=True			,_snake_case=("en_XX",)			,_snake_case=None			,**_snake_case			,):
				super().__init__(pad_token_id=_snake_case			,bos_token_id=_snake_case			,eos_token_id=_snake_case			,**_snake_case     )

				UpperCAmelCase_     :      Tuple						=  vocab_size
				UpperCAmelCase_     :      str						=  hidden_size
				UpperCAmelCase_     :      List[Any]						=  num_hidden_layers
				UpperCAmelCase_     :      List[Any]						=  num_attention_heads
				UpperCAmelCase_     :      List[str]						=  hidden_act
				UpperCAmelCase_     :      Dict						=  intermediate_size
				UpperCAmelCase_     :      Dict						=  hidden_dropout_prob
				UpperCAmelCase_     :      Union[str, Any]						=  attention_probs_dropout_prob
				UpperCAmelCase_     :      int						=  max_position_embeddings
				UpperCAmelCase_     :      Optional[Any]						=  type_vocab_size
				UpperCAmelCase_     :      Any						=  initializer_range
				UpperCAmelCase_     :      Optional[Any]						=  layer_norm_eps
				UpperCAmelCase_     :      Any						=  position_embedding_type
				UpperCAmelCase_     :      Union[str, Any]						=  use_cache
				UpperCAmelCase_     :      Union[str, Any]						=  classifier_dropout
				UpperCAmelCase_     :      Optional[Any]						=  pre_norm
				UpperCAmelCase_     :      int						=  adapter_reduction_factor
				UpperCAmelCase_     :      Dict						=  adapter_layer_norm
				UpperCAmelCase_     :      str						=  adapter_reuse_layer_norm
				UpperCAmelCase_     :      Dict						=  ln_before_adapter
				UpperCAmelCase_     :      List[Any]						=  list(_snake_case     )
				UpperCAmelCase_     :      Optional[Any]						=  default_language




class 					_snake_case		(__SCREAMING_SNAKE_CASE):






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








import warnings

from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor


lowerCamelCase__							:						int							     =   logging.get_logger(__name__)
class 		__magic_name__						(snake_case_				):





     '''simple docstring'''



     def __init__(					self:List[Any]     ,		*_a:Dict     ,		**_a:Tuple   ):
       warnings.warn(
           '''The class PerceiverFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
           ''' Please use PerceiverImageProcessor instead.'''     ,		_a     ,		)
       super().__init__(*_a     ,		**_a   )

