



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


SCREAMING_SNAKE_CASE_:Any 			=		logging.get_logger(__name__)

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






class SCREAMING_SNAKE_CASE__	(						SCREAMING_SNAKE_CASE_       ):




    '''simple docstring'''






    __lowerCamelCase     :					int   = "efficientnet"






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

        A					:			str		=  num_channels
        A					:			List[str]		=  image_size
        A					:			List[str]		=  width_coefficient
        A					:			Optional[Any]		=  depth_coefficient
        A					:			Tuple		=  depth_divisor
        A					:			Dict		=  kernel_sizes
        A					:			int		=  in_channels
        A					:			str		=  out_channels
        A					:			Dict		=  depthwise_padding
        A					:			Union[str, Any]		=  strides
        A					:			Dict		=  num_block_repeats
        A					:			Tuple		=  expand_ratios
        A					:			List[str]		=  squeeze_expansion_ratio
        A					:			Any		=  hidden_act
        A					:			Tuple		=  hidden_dim
        A					:			int		=  pooling_type
        A					:			int		=  initializer_range
        A					:			List[str]		=  batch_norm_eps
        A					:			str		=  batch_norm_momentum
        A					:			List[str]		=  dropout_rate
        A					:			Dict		=  drop_connect_rate
        A					:			Optional[Any]		=  sum(__snake_case						) * 4






class SCREAMING_SNAKE_CASE__	(						SCREAMING_SNAKE_CASE_       ):




    '''simple docstring'''






    __lowerCamelCase     :					Any   = version.parse("1.11"       )






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






    @property
    def      _lowerCAmelCase   (			self						):
        return 1e-5










"""simple docstring"""





from argparse import ArgumentParser

from .env import EnvironmentCommand



def   a    (     )    ->							Tuple:
						__magic_name__:	Optional[int]							=       ArgumentParser("""Diffusers CLI tool"""      ,   usage="""diffusers-cli <command> [<args>]"""  )
						__magic_name__:	Any							=       parser.add_subparsers(help="""diffusers-cli command helpers"""  )

						# Register commands
						EnvironmentCommand.register_subcommand(__UpperCAmelCase  )

						# Let's go
						__magic_name__:	int							=       parser.parse_args()

						if not hasattr(__UpperCAmelCase      ,   """func"""  ):
												parser.print_help()
												exit(1  )

						# Run
						__magic_name__:	Optional[Any]							=       args.func(__UpperCAmelCase  )
						service.run()


if __name__ == "__main__":
							main()



