






from collections import OrderedDict
from typing import Mapping

from packaging import version

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


a_						:  Dict									=			logging.get_logger(__name__)

a_						:  Optional[int]									=			{
    """google/mobilenet_v1_1.0_224""": """https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json""",
    """google/mobilenet_v1_0.75_192""": """https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json""",
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}

class 						_snake_case     (     lowercase_    ):
			_lowercase						:			Union[str, Any]	   =							'''mobilenet_v1'''






			def __init__(				self						,    a=3						,    a=224						,    a=1.0						,    a=8						,    a="relu6"						,    a=True						,    a=0.9_99						,    a=0.02						,    a=0.0_01						,    **a						,    )					->				Tuple:
						super().__init__(**SCREAMING_SNAKE_CASE_)

						if depth_multiplier <= 0:
									raise ValueError('depth_multiplier must be greater than zero.')

						SCREAMING_SNAKE_CASE						 =       num_channels
						SCREAMING_SNAKE_CASE						 =       image_size
						SCREAMING_SNAKE_CASE						 =       depth_multiplier
						SCREAMING_SNAKE_CASE						 =       min_depth
						SCREAMING_SNAKE_CASE						 =       hidden_act
						SCREAMING_SNAKE_CASE						 =       tf_padding
						SCREAMING_SNAKE_CASE						 =       classifier_dropout_prob
						SCREAMING_SNAKE_CASE						 =       initializer_range
						SCREAMING_SNAKE_CASE						 =       layer_norm_eps



class 						_snake_case     (     lowercase_    ):
			_lowercase						:			List[Any]	   =							version.parse('''1.11'''    )






			@property
			def       SCREAMING_SNAKE_CASE__			(				self)					->				Dict:
						return OrderedDict([('pixel_values', {0: 'batch'})])






			@property
			def       SCREAMING_SNAKE_CASE__			(				self)					->				List[str]:
						if self.task == "image-classification":
									return OrderedDict([('logits', {0: 'batch'})])
						else:
									return OrderedDict([('last_hidden_state', {0: 'batch'}), ('pooler_output', {0: 'batch'})])







			@property
			def       SCREAMING_SNAKE_CASE__			(				self)					->				Union[str, Any]:
						return 1E-4









"""simple docstring"""







import warnings

from diffusers import StableDiffusionImgaImgPipeline  # noqa F401


warnings.warn(
    """The `image_to_image.py` script is outdated. Please use directly `from diffusers import"""
    """ StableDiffusionImg2ImgPipeline` instead."""
)





