
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        lowerCAmelCase__      (   __lowercase	):
						UpperCamelCase_							: Optional[Any]	=		"efficientnet"

						def __init__(			self       ,							a = 3       ,							a = 6_00       ,							a = 2.0       ,							a = 3.1       ,							a = 8       ,							a = [3, 3, 5, 3, 5, 5, 3]       ,							a = [32, 16, 24, 40, 80, 1_12, 1_92]       ,							a = [16, 24, 40, 80, 1_12, 1_92, 3_20]       ,							a = []       ,							a = [1, 2, 2, 2, 1, 2, 1]       ,							a = [1, 2, 2, 3, 3, 4, 1]       ,							a = [1, 6, 6, 6, 6, 6, 6]       ,							a = 0.25       ,							a = "swish"       ,							a = 25_60       ,							a = "mean"       ,							a = 0.02       ,							a = 0.001       ,							a = 0.99       ,							a = 0.5       ,							a = 0.2       ,							**a       ,							)					->      List[str]:


								'''simple docstring'''

								super().__init__(**a				)

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







class        lowerCAmelCase__      (   __lowercase	):
						UpperCamelCase_							: Dict	=		version.parse("1.11"	)

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


								'''simple docstring'''

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







						@property
						def  A_				(			self				)					->      float:


								'''simple docstring'''

								return 1e-5





import warnings

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


lowerCamelCase__	=							logging.get_logger(__name__)







class        lowerCAmelCase__      (   __lowercase	):

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


								'''simple docstring'''

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



