code: 
  """simple docstring"""
  
  
  
  
  
  from typing import Dict, List, Optional, Union
  
  import numpy as np
  
  from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
  from ...image_transforms import (
      center_crop,
      convert_to_rgb,
      get_resize_output_image_size,
      normalize,
      rescale,
      resize,
      to_channel_dimension_format,
  )
  from ...image_utils import (
      OPENAI_CLIP_MEAN,
      OPENAI_CLIP_STD,
      ChannelDimension,
      ImageInput,
      PILImageResampling,
      make_list_of_images,
      to_numpy_array,
      valid_images,
  )
  from ...utils import TensorType, is_vision_available, logging
  
  
  _a	 =							logging.get_logger(__name__)
  
  
  if is_vision_available():
      import PIL
  
  
  class A_			(lowercase__   ):
  
  
  
  
    '''simple docstring'''
    SCREAMING_SNAKE_CASE__    :		Dict						  =	["""pixel_values"""]
  
  
  
  
  
  
  
    def __init__(	self       ,     lowercase_ = True       ,     lowercase_ = None       ,     lowercase_ = PILImageResampling.BICUBIC       ,     lowercase_ = True       ,     lowercase_ = None       ,     lowercase_ = True       ,     lowercase_ = 1 / 255       ,     lowercase_ = True       ,     lowercase_ = None       ,     lowercase_ = None       ,     lowercase_ = True       ,     **lowercase_       ,     ):
  
       """simple docstring"""
       super().__init__(**lowercase_						)
       UpperCAmelCase_      :      List[str]      =					size if size is not None else {"shortest_edge": 224}
       UpperCAmelCase_      :      Dict      =					get_size_dict(lowercase_       ,     default_to_square=lowercase_						)
       UpperCAmelCase_      :      Tuple      =					crop_size if crop_size is not None else {"height": 224, "width": 224}
       UpperCAmelCase_      :      Any      =					get_size_dict(lowercase_						)
  
       UpperCAmelCase_      :      str      =					do_resize
       UpperCAmelCase_      :      Any      =					size
       UpperCAmelCase_      :      Optional[int]      =					resample
       UpperCAmelCase_      :      Tuple      =					do_center_crop
       UpperCAmelCase_      :      str      =					crop_size
       UpperCAmelCase_      :      Any      =					do_rescale
       UpperCAmelCase_      :      List[Any]      =					rescale_factor
       UpperCAmelCase_      :      int      =					do_normalize
       UpperCAmelCase_      :      Union[str, Any]      =					image_mean if image_mean is not None else OPENAI_CLIP_MEAN
       UpperCAmelCase_      :      List[str]      =					image_std if image_std is not None else OPENAI_CLIP_STD
       UpperCAmelCase_      :      str      =					do_convert_rgb
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self       ,     lowercase_       ,     lowercase_       ,     lowercase_ = PILImageResampling.BICUBIC       ,     lowercase_ = None       ,     **lowercase_       ,     ):
  
       """simple docstring"""
       UpperCAmelCase_      :      Optional[int]      =					get_size_dict(lowercase_       ,     default_to_square=lowercase_						)
       UpperCAmelCase_      :      List[str]      =					get_resize_output_image_size(
           lowercase_       ,     size=(size["height"], size["width"])       ,     default_to_square=lowercase_						)
       return resize(lowercase_       ,     size=lowercase_       ,     resample=lowercase_       ,     data_format=lowercase_       ,     **lowercase_						)
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self       ,     lowercase_       ,     lowercase_       ,     lowercase_ = None       ,     **lowercase_       ,     ):
  
       """simple docstring"""
       UpperCAmelCase_      :      List[Any]      =					get_size_dict(lowercase_						)
       return center_crop(lowercase_       ,     size=(size["height"], size["width"])       ,     data_format=lowercase_       ,     **lowercase_						)
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self       ,     lowercase_       ,     lowercase_       ,     lowercase_ = None       ,     **lowercase_       ,     ):
  
       """simple docstring"""
       return rescale(lowercase_       ,     scale=lowercase_       ,     data_format=lowercase_       ,     **lowercase_						)
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self       ,     lowercase_       ,     lowercase_       ,     lowercase_       ,     lowercase_ = None       ,     **lowercase_       ,     ):
  
       """simple docstring"""
       return normalize(lowercase_       ,     mean=lowercase_       ,     std=lowercase_       ,     data_format=lowercase_       ,     **lowercase_						)
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self       ,     lowercase_       ,     lowercase_ = None       ,     lowercase_ = None       ,     lowercase_ = None       ,     lowercase_ = None       ,     lowercase_ = None       ,     lowercase_ = None       ,     lowercase_ = None       ,     lowercase_ = None       ,     lowercase_ = None       ,     lowercase_ = None       ,     lowercase_ = None       ,     lowercase_ = None       ,     lowercase_ = ChannelDimension.FIRST       ,     **lowercase_       ,     ):
  
       """simple docstring"""
       UpperCAmelCase_      :      Dict      =					do_resize if do_resize is not None else self.do_resize
       UpperCAmelCase_      :      List[str]      =					size if size is not None else self.size
       UpperCAmelCase_      :      int      =					get_size_dict(lowercase_       ,     default_to_square=lowercase_						)
       UpperCAmelCase_      :      Optional[int]      =					resample if resample is not None else self.resample
       UpperCAmelCase_      :      int      =					do_center_crop if do_center_crop is not None else self.do_center_crop
       UpperCAmelCase_      :      Union[str, Any]      =					crop_size if crop_size is not None else self.crop_size
       UpperCAmelCase_      :      List[Any]      =					get_size_dict(lowercase_						)
       UpperCAmelCase_      :      List[Any]      =					do_rescale if do_rescale is not None else self.do_rescale
       UpperCAmelCase_      :      Optional[Any]      =					rescale_factor if rescale_factor is not None else self.rescale_factor
       UpperCAmelCase_      :      Optional[Any]      =					do_normalize if do_normalize is not None else self.do_normalize
       UpperCAmelCase_      :      int      =					image_mean if image_mean is not None else self.image_mean
       UpperCAmelCase_      :      Union[str, Any]      =					image_std if image_std is not None else self.image_std
       UpperCAmelCase_      :      Optional[int]      =					do_convert_rgb if do_convert_rgb is not None else self.do_convert_rgb
  
       UpperCAmelCase_      :      Union[str, Any]      =					make_list_of_images(lowercase_						)
  
       if not valid_images(lowercase_						):
          raise ValueError(
              "Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, "
              "torch.Tensor, tf.Tensor or jax.ndarray."						)
  
       if do_resize and size is None:
          raise ValueError("Size must be specified if do_resize is True."						)
  
       if do_center_crop and crop_size is None:
          raise ValueError("Crop size must be specified if do_center_crop is True."						)
  
       if do_rescale and rescale_factor is None:
          raise ValueError("Rescale factor must be specified if do_rescale is True."						)
  
       if do_normalize and (image_mean is None or image_std is None):
          raise ValueError("Image mean and std must be specified if do_normalize is True."						)
  
       # PIL RGBA images are converted to RGB
       if do_convert_rgb:
          UpperCAmelCase_      :      List[Any]      =					[convert_to_rgb(lowercase_						) for image in images]
  
       # All transformations expect numpy arrays.
       UpperCAmelCase_      :      Union[str, Any]      =					[to_numpy_array(lowercase_						) for image in images]
  
       if do_resize:
          UpperCAmelCase_      :      Optional[int]      =					[self.resize(image=lowercase_       ,     size=lowercase_       ,     resample=lowercase_						) for image in images]
  
       if do_center_crop:
          UpperCAmelCase_      :      Union[str, Any]      =					[self.center_crop(image=lowercase_       ,     size=lowercase_						) for image in images]
  
       if do_rescale:
          UpperCAmelCase_      :      Any      =					[self.rescale(image=lowercase_       ,     scale=lowercase_						) for image in images]
  
       if do_normalize:
          UpperCAmelCase_      :      Dict      =					[self.normalize(image=lowercase_       ,     mean=lowercase_       ,     std=lowercase_						) for image in images]
  
       UpperCAmelCase_      :      List[str]      =					[to_channel_dimension_format(lowercase_       ,     lowercase_						) for image in images]
  
       UpperCAmelCase_      :      Any      =					{"pixel_values": images}
       return BatchFeature(data=lowercase_       ,     tensor_type=lowercase_						)
  
  
  
style_context: 
  """simple docstring"""
  
  
  
  
  
  from __future__ import annotations
  
  from typing import Any
  
  
  class A_			:
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    def __init__(	self       ,     lowercase_       ,     lowercase_						):  # noqa: A002
  
       """simple docstring"""
       UpperCAmelCase_      :      Optional[Any]      =					item
       UpperCAmelCase_      :      Optional[Any]      =					next
  
  
  
  
  class A_			:
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    def __init__(	self						):
  
       """simple docstring"""
       UpperCAmelCase_      :      Node | None      =					None
       UpperCAmelCase_      :      Optional[int]      =					0
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self       ,     lowercase_						):
  
       """simple docstring"""
       UpperCAmelCase_      :      int      =					Node(lowercase_       ,     self.head						)
       self.size += 1
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       # Switched 'self.is_empty()' to 'self.head is None'
       # because mypy was considering the possibility that 'self.head'
       # can be None in below else part and giving error
       if self.head is None:
          return None
       else:
          UpperCAmelCase_      :      int      =					self.head.item
          UpperCAmelCase_      :      str      =					self.head.next
          self.size -= 1
          return item
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       return self.head is None
  
  
  
  
  
  
  
    def __str__(	self						):
  
       """simple docstring"""
       if self.is_empty():
          return ""
       else:
          UpperCAmelCase_      :      str      =					self.head
          UpperCAmelCase_      :      str      =					""
          UpperCAmelCase_      :      list[str]      =					[]
          while iterate:
             item_list.append(str(iterate.item						)						)
             UpperCAmelCase_      :      Tuple      =					iterate.next
  
          UpperCAmelCase_      :      Optional[Any]      =					" --> ".join(lowercase_						)
  
          return item_str
  
  
  
  
  
  
  
    def __len__(	self						):
  
       """simple docstring"""
       return self.size
  
  
  