code: 
  
  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
  
  
  snake_case_    						=				logging.get_logger(__name__)
  
  snake_case_    						=				{
      '''MBZUAI/swiftformer-xs''': '''https://huggingface.co/MBZUAI/swiftformer-xs/resolve/main/config.json''',
  }
  
  
  class    SCREAMING_SNAKE_CASE__      (UpperCamelCase__  ):
      __lowerCamelCase		: Dict														=  """swiftformer"""
  
  
  
  
  
      def __init__(   self		,     a=3		,     a=[3, 3, 6, 4]		,     a=[48, 56, 112, 220]		,     a=4		,     a=[True, True, True, True]		,     a="gelu"		,     a=3		,     a=2		,     a=1		,     a=0.0		,     a=True		,     a=1e-5		,     a=1e-5		,     **a		,     ):
           super().__init__(**snake_case_)
           lowercase__					:     List[Any]   = num_channels
           lowercase__					:     Optional[int]   = depths
           lowercase__					:     List[str]   = embed_dims
           lowercase__					:     Dict   = mlp_ratio
           lowercase__					:     Dict   = downsamples
           lowercase__					:     List[Any]   = hidden_act
           lowercase__					:     Any   = down_patch_size
           lowercase__					:     Any   = down_stride
           lowercase__					:     Any   = down_pad
           lowercase__					:     Optional[int]   = drop_path_rate
           lowercase__					:     Dict   = use_layer_scale
           lowercase__					:     Any   = layer_scale_init_value
           lowercase__					:     Union[str, Any]   = batch_norm_eps
  
  
  
  class    SCREAMING_SNAKE_CASE__      (UpperCamelCase__  ):
      __lowerCamelCase		: int														=  version.parse("""1.11"""  )
  
  
  
  
  
      @property
      def    snake_case_       (   self):
           return OrderedDict(
               [
                   ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
               ])
  
  
  
  
  
      @property
      def    snake_case_       (   self):
           return 1e-4
  
  
style_context: 
  
  from dataclasses import dataclass
  from typing import List, Optional, Union
  
  import numpy as np
  import PIL
  
  from ...utils import BaseOutput, is_invisible_watermark_available, is_torch_available, is_transformers_available
  
  
  @dataclass
  class    SCREAMING_SNAKE_CASE__      (__snake_case  ):
      __lowerCamelCase		: Union[List[PIL.Image.Image], np.ndarray]
  
  
  if is_transformers_available() and is_torch_available() and is_invisible_watermark_available():
         from .pipeline_stable_diffusion_xl import StableDiffusionXLPipeline
         from .pipeline_stable_diffusion_xl_imgaimg import StableDiffusionXLImgaImgPipeline
  
  