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      :			List[Any]							       =		logging.get_logger(__name__)

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







class __snake_case    (						lowerCamelCase_		):
   lowerCAmelCase_														=							"efficientnet"




   def __init__(   self      :    int	,     _lowercase      :    int = 3	,     _lowercase      :    int = 6_00	,     _lowercase      :    float = 2.0	,     _lowercase      :    float = 3.1	,     _lowercase      :    int = 8	,     _lowercase      :    List[int] = [3, 3, 5, 3, 5, 5, 3]	,     _lowercase      :    List[int] = [32, 16, 24, 40, 80, 1_12, 1_92]	,     _lowercase      :    List[int] = [16, 24, 40, 80, 1_12, 1_92, 3_20]	,     _lowercase      :    List[int] = []	,     _lowercase      :    List[int] = [1, 2, 2, 2, 1, 2, 1]	,     _lowercase      :    List[int] = [1, 2, 2, 3, 3, 4, 1]	,     _lowercase      :    List[int] = [1, 6, 6, 6, 6, 6, 6]	,     _lowercase      :    float = 0.25	,     _lowercase      :    str = "swish"	,     _lowercase      :    int = 25_60	,     _lowercase      :    str = "mean"	,     _lowercase      :    float = 0.02	,     _lowercase      :    float = 0.0_01	,     _lowercase      :    float = 0.99	,     _lowercase      :    float = 0.5	,     _lowercase      :    float = 0.2	,     **_lowercase      :    List[str]	,     ):



     """simple docstring"""






     super().__init__(**_lowercase				)

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







class __snake_case    (						lowerCamelCase_		):
   lowerCAmelCase_														=							version.parse("1.11"		)




   @property
   def      __a						(   self      :    Union[str, Any]				):



     """simple docstring"""






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




   @property
   def      __a						(   self      :    Optional[int]				):



     """simple docstring"""






     return 1E-5

import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image


if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('''9.1.0'''):
   __lowerCamelCase      :			Optional[Any]							       =		{
       '''linear''': PIL.Image.Resampling.BILINEAR,
       '''bilinear''': PIL.Image.Resampling.BILINEAR,
       '''bicubic''': PIL.Image.Resampling.BICUBIC,
       '''lanczos''': PIL.Image.Resampling.LANCZOS,
       '''nearest''': PIL.Image.Resampling.NEAREST,
   }
else:
   __lowerCamelCase      :			int							       =		{
       '''linear''': PIL.Image.LINEAR,
       '''bilinear''': PIL.Image.BILINEAR,
       '''bicubic''': PIL.Image.BICUBIC,
       '''lanczos''': PIL.Image.LANCZOS,
       '''nearest''': PIL.Image.NEAREST,
   }



def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	int     )							-> Optional[Any]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				(images / 2 + 0.5).clamp(0			,					1     )
  SCREAMING_SNAKE_CASE__      							=				images.cpu().permute(0			,					2			,					3			,					1     ).float().numpy()
  SCREAMING_SNAKE_CASE__      							=				numpy_to_pil(__UpperCamelCase     )
  return images






def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	int     )							-> int:







  """simple docstring"""





  if images.ndim == 3:
    SCREAMING_SNAKE_CASE__      							=				images[None, ...]
  SCREAMING_SNAKE_CASE__      							=				(images * 2_55).round().astype("""uint8"""     )
  if images.shape[-1] == 1:
    # special case for grayscale (single channel) images
    SCREAMING_SNAKE_CASE__      							=				[Image.fromarray(image.squeeze()			,					mode="""L"""     ) for image in images]
  else:
    SCREAMING_SNAKE_CASE__      							=				[Image.fromarray(__UpperCamelCase     ) for image in images]

  return pil_images
