



from typing import List

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


_lowerCamelCase   				=			logging.get_logger(__name__)

_lowerCamelCase   				=			{
    "snap-research/efficientformer-l1-300": (
        "https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json"
    ),
}




class   UpperCamelCase_       (     _SCREAMING_SNAKE_CASE    ):
							lowerCamelCase_           =					"efficientformer"


							def __init__(							self    :Dict							,				__A    :Optional[int] = [3, 2, 6, 4]							,				__A    :Optional[Any] = [48, 96, 224, 448]							,				__A    :str = [True, True, True, True]							,				__A    :Any = 448							,				__A    :Union[str, Any] = 32							,				__A    :Union[str, Any] = 4							,				__A    :int = 7							,				__A    :Dict = 5							,				__A    :Any = 8							,				__A    :List[Any] = 4							,				__A    :Optional[Any] = 0.0							,				__A    :Union[str, Any] = 16							,				__A    :str = 3							,				__A    :Union[str, Any] = 3							,				__A    :List[str] = 3							,				__A    :str = 2							,				__A    :Dict = 1							,				__A    :Any = 0.0							,				__A    :List[Any] = 1							,				__A    :Any = True							,				__A    :Optional[Any] = True							,				__A    :List[str] = 1E-5							,				__A    :Union[str, Any] = "gelu"							,				__A    :List[Any] = 0.0_2							,				__A    :int = 1E-12							,				__A    :Any = 224							,				__A    :Optional[Any] = 1E-05							,				**__A    :Optional[int]							,				)   ->   None:



									"""simple docstring"""



									super().__init__(**A_		)

									SCREAMING_SNAKE_CASE__			=      hidden_act
									SCREAMING_SNAKE_CASE__			=      hidden_dropout_prob
									SCREAMING_SNAKE_CASE__			=      hidden_sizes
									SCREAMING_SNAKE_CASE__			=      num_hidden_layers
									SCREAMING_SNAKE_CASE__			=      num_attention_heads
									SCREAMING_SNAKE_CASE__			=      initializer_range
									SCREAMING_SNAKE_CASE__			=      layer_norm_eps
									SCREAMING_SNAKE_CASE__			=      patch_size
									SCREAMING_SNAKE_CASE__			=      num_channels
									SCREAMING_SNAKE_CASE__			=      depths
									SCREAMING_SNAKE_CASE__			=      mlp_expansion_ratio
									SCREAMING_SNAKE_CASE__			=      downsamples
									SCREAMING_SNAKE_CASE__			=      dim
									SCREAMING_SNAKE_CASE__			=      key_dim
									SCREAMING_SNAKE_CASE__			=      attention_ratio
									SCREAMING_SNAKE_CASE__			=      resolution
									SCREAMING_SNAKE_CASE__			=      pool_size
									SCREAMING_SNAKE_CASE__			=      downsample_patch_size
									SCREAMING_SNAKE_CASE__			=      downsample_stride
									SCREAMING_SNAKE_CASE__			=      downsample_pad
									SCREAMING_SNAKE_CASE__			=      drop_path_rate
									SCREAMING_SNAKE_CASE__			=      num_metaad_blocks
									SCREAMING_SNAKE_CASE__			=      distillation
									SCREAMING_SNAKE_CASE__			=      use_layer_scale
									SCREAMING_SNAKE_CASE__			=      layer_scale_init_value
									SCREAMING_SNAKE_CASE__			=      image_size
									SCREAMING_SNAKE_CASE__			=      batch_norm_eps






import warnings

from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor


_lowerCamelCase   				=			logging.get_logger(__name__)




class   UpperCamelCase_       (     UpperCamelCase__    ):


							def __init__(							self    :List[Any]							,				*__A    :Tuple							,				**__A    :Dict		)   ->   None:



									"""simple docstring"""



									warnings.warn(
									    """The class LayoutLMv2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
									    """ Please use LayoutLMv2ImageProcessor instead."""							,				__A							,				)
									super().__init__(*__A							,				**__A		)