






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


A_						:						int						      =					logging.get_logger(__name__)

A_						:						Optional[int]						      =					{
    'RWKV/rwkv-4-169m-pile': 'https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json',
    'RWKV/rwkv-4-430m-pile': 'https://huggingface.co/RWKV/rwkv-4-430m-pile/resolve/main/config.json',
    'RWKV/rwkv-4-1b5-pile': 'https://huggingface.co/RWKV/rwkv-4-1b5-pile/resolve/main/config.json',
    'RWKV/rwkv-4-3b-pile': 'https://huggingface.co/RWKV/rwkv-4-3b-pile/resolve/main/config.json',
    'RWKV/rwkv-4-7b-pile': 'https://huggingface.co/RWKV/rwkv-4-7b-pile/resolve/main/config.json',
    'RWKV/rwkv-4-14b-pile': 'https://huggingface.co/RWKV/rwkv-4-14b-pile/resolve/main/config.json',
    'RWKV/rwkv-raven-1b5': 'https://huggingface.co/RWKV/rwkv-raven-1b5/resolve/main/config.json',
    'RWKV/rwkv-raven-3b': 'https://huggingface.co/RWKV/rwkv-raven-3b/resolve/main/config.json',
    'RWKV/rwkv-raven-7b': 'https://huggingface.co/RWKV/rwkv-raven-7b/resolve/main/config.json',
    'RWKV/rwkv-raven-14b': 'https://huggingface.co/RWKV/rwkv-raven-14b/resolve/main/config.json',
}




class 							_lowerCAmelCase(			UpperCAmelCase_   ):





       """simple docstring"""







       a							:						List[str]										='''rwkv'''
       a							:						int										={'''max_position_embeddings''': '''context_length'''}





       def __init__(   self    ,     _lowerCamelCase=5_0_2_7_7    ,     _lowerCamelCase=1_0_2_4    ,     _lowerCamelCase=4_0_9_6    ,     _lowerCamelCase=3_2    ,     _lowerCamelCase=None    ,     _lowerCamelCase=None    ,     _lowerCamelCase=1e-5    ,     _lowerCamelCase=0    ,     _lowerCamelCase=0    ,     _lowerCamelCase=6    ,     _lowerCamelCase=False    ,     _lowerCamelCase=True    ,     **_lowerCamelCase    ,     ):
         UpperCamelCase_:   Optional[Any]        =							vocab_size
         UpperCamelCase_:   int        =							context_length
         UpperCamelCase_:   Optional[int]        =							hidden_size
         UpperCamelCase_:   List[str]        =							num_hidden_layers
         UpperCamelCase_:   Optional[int]        =							attention_hidden_size if attention_hidden_size is not None else hidden_size
         UpperCamelCase_:   Tuple        =							intermediate_size if intermediate_size is not None else 4 * hidden_size
         UpperCamelCase_:   List[str]        =							layer_norm_epsilon
         UpperCamelCase_:   Optional[Any]        =							rescale_every
         UpperCamelCase_:   Union[str, Any]        =							use_cache

         UpperCamelCase_:   Optional[int]        =							bos_token_id
         UpperCamelCase_:   Dict        =							eos_token_id

         super().__init__(
             tie_word_embeddings=_lowerCamelCase    ,     bos_token_id=_lowerCamelCase    ,     eos_token_id=_lowerCamelCase    ,     **_lowerCamelCase				)







import warnings

from ...utils import logging
from .image_processing_deit import DeiTImageProcessor


__a   :							Any						= logging.get_logger(__name__)


class    __lowercase   (						lowercase_	):







     '''simple docstring'''




     def __init__(					self							:      Union[str, Any]			,						*UpperCamelCase_							:      Tuple			,						**UpperCamelCase_							:      Tuple					):


         """simple docstring"""



         warnings.warn(
             """The class DeiTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
             """ use DeiTImageProcessor instead."""			,						UpperCamelCase_			,						)
         super().__init__(*UpperCamelCase_			,						**UpperCamelCase_					)




