

'''simple docstring'''







from collections import OrderedDict
from typing import List, Mapping

from packaging import version

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


__lowerCamelCase		       =    logging.get_logger(__name__)

__lowerCamelCase		       =    {
    'google/efficientnet-b7': 'https://huggingface.co/google/efficientnet-b7/resolve/main/config.json',
}


class 					A__      (      UpperCamelCase_			):
    lowercase						=		"efficientnet"



    def __init__(					self		,				UpperCamelCase__ = 3		,				UpperCamelCase__ = 600		,				UpperCamelCase__ = 2.0		,				UpperCamelCase__ = 3.1		,				UpperCamelCase__ = 8		,				UpperCamelCase__ = [3, 3, 5, 3, 5, 5, 3]		,				UpperCamelCase__ = [32, 16, 24, 40, 80, 112, 192]		,				UpperCamelCase__ = [16, 24, 40, 80, 112, 192, 320]		,				UpperCamelCase__ = []		,				UpperCamelCase__ = [1, 2, 2, 2, 1, 2, 1]		,				UpperCamelCase__ = [1, 2, 2, 3, 3, 4, 1]		,				UpperCamelCase__ = [1, 6, 6, 6, 6, 6, 6]		,				UpperCamelCase__ = 0.25		,				UpperCamelCase__ = "swish"		,				UpperCamelCase__ = 2560		,				UpperCamelCase__ = "mean"		,				UpperCamelCase__ = 0.02		,				UpperCamelCase__ = 0.001		,				UpperCamelCase__ = 0.99		,				UpperCamelCase__ = 0.5		,				UpperCamelCase__ = 0.2		,				**UpperCamelCase__		,				)						->      List[str]:





           '''simple docstring'''
           super().__init__(**UpperCamelCase__       )

           A_						=      num_channels
           A_						=      image_size
           A_						=      width_coefficient
           A_						=      depth_coefficient
           A_						=      depth_divisor
           A_						=      kernel_sizes
           A_						=      in_channels
           A_						=      out_channels
           A_						=      depthwise_padding
           A_						=      strides
           A_						=      num_block_repeats
           A_						=      expand_ratios
           A_						=      squeeze_expansion_ratio
           A_						=      hidden_act
           A_						=      hidden_dim
           A_						=      pooling_type
           A_						=      initializer_range
           A_						=      batch_norm_eps
           A_						=      batch_norm_momentum
           A_						=      dropout_rate
           A_						=      drop_connect_rate
           A_						=      sum(UpperCamelCase__       ) * 4


class 					A__      (      UpperCamelCase_			):
    lowercase						=		version.parse("1.11"			)



    @property
    def 					snake_case_			(					self       )						->      Mapping[str, Mapping[int, str]]:





           '''simple docstring'''
           return OrderedDict(
               [
                   ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
               ]       )







    @property
    def 					snake_case_			(					self       )						->      float:





           '''simple docstring'''
           return 1e-5



'''simple docstring'''







import warnings

from ...utils import logging
from .image_processing_beit import BeitImageProcessor


__lowerCamelCase		       =    logging.get_logger(__name__)


class 					A__      (      _snake_case			):



    def __init__(					self		,				*UpperCamelCase__		,				**UpperCamelCase__       )						->      None:





           '''simple docstring'''
           warnings.warn(
               """The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
               """ use BeitImageProcessor instead."""		,				UpperCamelCase__		,				)
           super().__init__(*UpperCamelCase__		,				**UpperCamelCase__       )
