

'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase			:				str 			=					logging.get_logger(__name__)

lowerCamelCase			:				Union[str, Any] 			=					{
    "sayakpaul/vit-msn-base": "https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json",
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}







class 							A__   (	_snake_case  ):
  A__					=    'vit_msn'





  def __init__(		self				:     Any							, _a				:     List[str]=768							, _a				:     Optional[int]=12							, _a				:     Union[str, Any]=12							, _a				:     Optional[int]=3072							, _a				:     Union[str, Any]="gelu"							, _a				:     Dict=0.0							, _a				:     List[Any]=0.0							, _a				:     Optional[Any]=0.02							, _a				:     Dict=1e-06							, _a				:     List[Any]=224							, _a				:     int=16							, _a				:     List[Any]=3							, _a				:     List[Any]=True							, **_a				:     Any							, )     ->   Optional[Any]:





       '''simple docstring'''






       super().__init__(**UpperCamelCase__			)

       _SCREAMING_SNAKE_CASE							   =hidden_size
       _SCREAMING_SNAKE_CASE							   =num_hidden_layers
       _SCREAMING_SNAKE_CASE							   =num_attention_heads
       _SCREAMING_SNAKE_CASE							   =intermediate_size
       _SCREAMING_SNAKE_CASE							   =hidden_act
       _SCREAMING_SNAKE_CASE							   =hidden_dropout_prob
       _SCREAMING_SNAKE_CASE							   =attention_probs_dropout_prob
       _SCREAMING_SNAKE_CASE							   =initializer_range
       _SCREAMING_SNAKE_CASE							   =layer_norm_eps
       _SCREAMING_SNAKE_CASE							   =image_size
       _SCREAMING_SNAKE_CASE							   =patch_size
       _SCREAMING_SNAKE_CASE							   =num_channels
       _SCREAMING_SNAKE_CASE							   =qkv_bias



'''simple docstring'''
import warnings


warnings.warn(
    "memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
    "`from accelerate import find_executable_batch_size` to avoid this warning.",
    FutureWarning,
)
