



"""simple docstring"""
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
    IMAGENET_STANDARD_MEAN,
    IMAGENET_STANDARD_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    get_image_size,
    is_torch_available,
    is_torch_tensor,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_vision_available, logging


if is_torch_available():
   import torch

if is_vision_available():
   import PIL


_UpperCAmelCase     =			logging.get_logger(__name__)





def      __magic_name__(							lowercase							,			lowercase							,			lowercase							,			lowercase ):







   def constraint_to_multiple_of(lowercase							,			lowercase							,			lowercase=0							,			lowercase=None ):
      SCREAMING_SNAKE_CASE_: Any     			=round(val / multiple ) * multiple

      if max_val is not None and x > max_val:
         SCREAMING_SNAKE_CASE_: Tuple     			=math.floor(val / multiple ) * multiple

      if x < min_val:
         SCREAMING_SNAKE_CASE_: Tuple     			=math.ceil(val / multiple ) * multiple

      return x

   SCREAMING_SNAKE_CASE_: Optional[int]     			=(output_size, output_size) if isinstance(_lowercase							,			_lowercase ) else output_size

   SCREAMING_SNAKE_CASE_			,		SCREAMING_SNAKE_CASE_: str     			=get_image_size(_lowercase )
   SCREAMING_SNAKE_CASE_			,		SCREAMING_SNAKE_CASE_: Any     			=output_size

   # determine new height and width
   SCREAMING_SNAKE_CASE_: Tuple     			=output_height / input_height
   SCREAMING_SNAKE_CASE_: Tuple     			=output_width / input_width

   if keep_aspect_ratio:
      # scale as little as possible
      if abs(1 - scale_width ) < abs(1 - scale_height ):
         # fit width
         SCREAMING_SNAKE_CASE_: Tuple     			=scale_width
      else:
         # fit height
         SCREAMING_SNAKE_CASE_: Any     			=scale_height

   SCREAMING_SNAKE_CASE_: Any     			=constraint_to_multiple_of(scale_height * input_height							,			multiple=_lowercase )
   SCREAMING_SNAKE_CASE_: Optional[int]     			=constraint_to_multiple_of(scale_width * input_width							,			multiple=_lowercase )

   return (new_height, new_width)
class 					a	(  UpperCAmelCase__       ):
  UpperCamelCase	:				List[Any]     						=					['pixel_values']



  def __init__(						self :					int       ,		lowerCAmelCase :					bool = True       ,		lowerCAmelCase :					Dict[str, int] = None       ,		lowerCAmelCase :					PILImageResampling = PILImageResampling.BILINEAR       ,		lowerCAmelCase :					bool = False       ,		lowerCAmelCase :					int = 1       ,		lowerCAmelCase :					bool = True       ,		lowerCAmelCase :					Union[int, float] = 1 / 255       ,		lowerCAmelCase :					bool = True       ,		lowerCAmelCase :					Optional[Union[float, List[float]]] = None       ,		lowerCAmelCase :					Optional[Union[float, List[float]]] = None       ,		**lowerCAmelCase :					Optional[int]       ,		)     ->					None:


     '''simple docstring'''




     super().__init__(**__A		)
     SCREAMING_SNAKE_CASE_: Tuple     			=size if size is not None else {"""height""": 384, """width""": 384}
     SCREAMING_SNAKE_CASE_: int     			=get_size_dict(__A		)
     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=do_resize
     SCREAMING_SNAKE_CASE_: int     			=size
     SCREAMING_SNAKE_CASE_: Optional[Any]     			=keep_aspect_ratio
     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=ensure_multiple_of
     SCREAMING_SNAKE_CASE_: List[Any]     			=resample
     SCREAMING_SNAKE_CASE_: Optional[int]     			=do_rescale
     SCREAMING_SNAKE_CASE_: Dict     			=rescale_factor
     SCREAMING_SNAKE_CASE_: int     			=do_normalize
     SCREAMING_SNAKE_CASE_: Dict     			=image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
     SCREAMING_SNAKE_CASE_: List[Any]     			=image_std if image_std is not None else IMAGENET_STANDARD_STD



  def 	lowerCamelCase__       (						self :					Dict       ,		lowerCAmelCase :					np.ndarray       ,		lowerCAmelCase :					Dict[str, int]       ,		lowerCAmelCase :					bool = False       ,		lowerCAmelCase :					int = 1       ,		lowerCAmelCase :					PILImageResampling = PILImageResampling.BICUBIC       ,		lowerCAmelCase :					Optional[Union[str, ChannelDimension]] = None       ,		**lowerCAmelCase :					Union[str, Any]       ,		)     ->					np.ndarray:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: List[str]     			=get_size_dict(__A		)
     if "height" not in size or "width" not in size:
        raise ValueError(f'''The size dictionary must contain the keys \'height\' and \'width\'. Got {size.keys()}'''		)
     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=get_resize_output_image_size(
         __A       ,		output_size=(size["""height"""], size["""width"""])       ,		keep_aspect_ratio=__A       ,		multiple=__A       ,		)
     return resize(__A       ,		size=__A       ,		resample=__A       ,		data_format=__A       ,		**__A		)



  def 	lowerCamelCase__       (						self :					Optional[int]       ,		lowerCAmelCase :					np.ndarray       ,		lowerCAmelCase :					Union[int, float]       ,		lowerCAmelCase :					Optional[Union[str, ChannelDimension]] = None       ,		**lowerCAmelCase :					List[str]       ,		)     ->					Optional[int]:


     '''simple docstring'''




     return rescale(__A       ,		scale=__A       ,		data_format=__A       ,		**__A		)



  def 	lowerCamelCase__       (						self :					Optional[int]       ,		lowerCAmelCase :					np.ndarray       ,		lowerCAmelCase :					Union[float, List[float]]       ,		lowerCAmelCase :					Union[float, List[float]]       ,		lowerCAmelCase :					Optional[Union[str, ChannelDimension]] = None       ,		**lowerCAmelCase :					Optional[Any]       ,		)     ->					np.ndarray:


     '''simple docstring'''




     return normalize(__A       ,		mean=__A       ,		std=__A       ,		data_format=__A       ,		**__A		)



  def 	lowerCamelCase__       (						self :					Any       ,		lowerCAmelCase :					ImageInput       ,		lowerCAmelCase :					bool = None       ,		lowerCAmelCase :					int = None       ,		lowerCAmelCase :					bool = None       ,		lowerCAmelCase :					int = None       ,		lowerCAmelCase :					PILImageResampling = None       ,		lowerCAmelCase :					bool = None       ,		lowerCAmelCase :					float = None       ,		lowerCAmelCase :					bool = None       ,		lowerCAmelCase :					Optional[Union[float, List[float]]] = None       ,		lowerCAmelCase :					Optional[Union[float, List[float]]] = None       ,		lowerCAmelCase :					Optional[Union[str, TensorType]] = None       ,		lowerCAmelCase :					ChannelDimension = ChannelDimension.FIRST       ,		**lowerCAmelCase :					Tuple       ,		)     ->					PIL.Image.Image:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: str     			=do_resize if do_resize is not None else self.do_resize
     SCREAMING_SNAKE_CASE_: Any     			=size if size is not None else self.size
     SCREAMING_SNAKE_CASE_: List[str]     			=get_size_dict(__A		)
     SCREAMING_SNAKE_CASE_: int     			=keep_aspect_ratio if keep_aspect_ratio is not None else self.keep_aspect_ratio
     SCREAMING_SNAKE_CASE_: Dict     			=ensure_multiple_of if ensure_multiple_of is not None else self.ensure_multiple_of
     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=resample if resample is not None else self.resample
     SCREAMING_SNAKE_CASE_: Optional[Any]     			=do_rescale if do_rescale is not None else self.do_rescale
     SCREAMING_SNAKE_CASE_: List[str]     			=rescale_factor if rescale_factor is not None else self.rescale_factor
     SCREAMING_SNAKE_CASE_: Tuple     			=do_normalize if do_normalize is not None else self.do_normalize
     SCREAMING_SNAKE_CASE_: List[Any]     			=image_mean if image_mean is not None else self.image_mean
     SCREAMING_SNAKE_CASE_: Any     			=image_std if image_std is not None else self.image_std

     SCREAMING_SNAKE_CASE_: Tuple     			=make_list_of_images(__A		)

     if not valid_images(__A		):
        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 or resample is None:
        raise ValueError("""Size and resample must be specified if do_resize 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."""		)

     # All transformations expect numpy arrays.
     SCREAMING_SNAKE_CASE_: Dict     			=[to_numpy_array(__A		) for image in images]

     if do_resize:
        SCREAMING_SNAKE_CASE_: Optional[Any]     			=[self.resize(image=__A       ,		size=__A       ,		resample=__A		) for image in images]

     if do_rescale:
        SCREAMING_SNAKE_CASE_: Optional[Any]     			=[self.rescale(image=__A       ,		scale=__A		) for image in images]

     if do_normalize:
        SCREAMING_SNAKE_CASE_: Tuple     			=[self.normalize(image=__A       ,		mean=__A       ,		std=__A		) for image in images]

     SCREAMING_SNAKE_CASE_: Optional[Any]     			=[to_channel_dimension_format(__A       ,		__A		) for image in images]

     SCREAMING_SNAKE_CASE_: Tuple     			={"""pixel_values""": images}
     return BatchFeature(data=__A       ,		tensor_type=__A		)





  def 	lowerCamelCase__       (						self :					Union[str, Any]       ,		lowerCAmelCase :					int       ,		lowerCAmelCase :					List[Tuple] = None		)     ->					str:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Any     			=outputs.logits

     # Resize logits and compute semantic segmentation maps
     if target_sizes is not None:
        if len(__A		) != len(__A		):
           raise ValueError(
               """Make sure that you pass in as many target sizes as the batch dimension of the logits"""		)

        if is_torch_tensor(__A		):
           SCREAMING_SNAKE_CASE_: int     			=target_sizes.numpy()

        SCREAMING_SNAKE_CASE_: str     			=[]

        for idx in range(len(__A		)		):
           SCREAMING_SNAKE_CASE_: str     			=torch.nn.functional.interpolate(
               logits[idx].unsqueeze(dim=0		)       ,		size=target_sizes[idx]       ,		mode="""bilinear"""       ,		align_corners=__A		)
           SCREAMING_SNAKE_CASE_: Any     			=resized_logits[0].argmax(dim=0		)
           semantic_segmentation.append(__A		)
     else:
        SCREAMING_SNAKE_CASE_: Optional[Any]     			=logits.argmax(dim=1		)
        SCREAMING_SNAKE_CASE_: Optional[Any]     			=[semantic_segmentation[i] for i in range(semantic_segmentation.shape[0]		)]

     return semantic_segmentation








"""simple docstring"""
from __future__ import annotations

import math
import random
from typing import Any
class 					a	:



  def __init__(						self :					str		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: list[Any]     			=[]
     SCREAMING_SNAKE_CASE_: int     			=0
     SCREAMING_SNAKE_CASE_: int     			=0



  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					bool:


     '''simple docstring'''




     return self.head == self.tail



  def 	lowerCamelCase__       (						self :					Tuple       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     self.data.append(lowerCAmelCase		)
     SCREAMING_SNAKE_CASE_: List[str]     			=self.tail + 1



  def 	lowerCamelCase__       (						self :					int		)     ->					Any:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: int     			=self.data[self.head]
     SCREAMING_SNAKE_CASE_: Optional[int]     			=self.head + 1
     return ret



  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					int:


     '''simple docstring'''




     return self.tail - self.head





  def 	lowerCamelCase__       (						self :					str		)     ->					None:


     '''simple docstring'''




     print(self.data		)
     print("""**************"""		)
     print(self.data[self.head : self.tail]		)







class 					a	:



  def __init__(						self :					Union[str, Any]       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Dict     			=data
     SCREAMING_SNAKE_CASE_: MyNode | None     			=None
     SCREAMING_SNAKE_CASE_: MyNode | None     			=None
     SCREAMING_SNAKE_CASE_: int     			=1



  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					Any:


     '''simple docstring'''




     return self.data



  def 	lowerCamelCase__       (						self :					List[Any]		)     ->					MyNode | None:


     '''simple docstring'''




     return self.left



  def 	lowerCamelCase__       (						self :					Dict		)     ->					MyNode | None:


     '''simple docstring'''




     return self.right



  def 	lowerCamelCase__       (						self :					Any		)     ->					int:


     '''simple docstring'''




     return self.height



  def 	lowerCamelCase__       (						self :					Any       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Optional[Any]     			=data



  def 	lowerCamelCase__       (						self :					Dict       ,		lowerCAmelCase :					MyNode | None		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Tuple     			=node



  def 	lowerCamelCase__       (						self :					List[Any]       ,		lowerCAmelCase :					MyNode | None		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: str     			=node





  def 	lowerCamelCase__       (						self :					int       ,		lowerCAmelCase :					int		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Any     			=height







def      __magic_name__				(							lowercase ):
   if node is None:
      return 0
   return node.get_height()





def      __magic_name__				(							lowercase							,			lowercase ):
   if a > b:
      return a
   return b





def      __magic_name__				(							lowercase ):
   print("""left rotation node:"""							,			node.get_data() )
   SCREAMING_SNAKE_CASE_: List[Any]     			=node.get_left()
   assert ret is not None
   node.set_left(ret.get_right() )
   ret.set_right(lowercase )
   SCREAMING_SNAKE_CASE_: Tuple     			=my_max(get_height(node.get_right() )							,			get_height(node.get_left() ) ) + 1
   node.set_height(lowercase )
   SCREAMING_SNAKE_CASE_: int     			=my_max(get_height(ret.get_right() )							,			get_height(ret.get_left() ) ) + 1
   ret.set_height(lowercase )
   return ret





def      __magic_name__				(							lowercase ):
   print("""right rotation node:"""							,			node.get_data() )
   SCREAMING_SNAKE_CASE_: List[Any]     			=node.get_right()
   assert ret is not None
   node.set_right(ret.get_left() )
   ret.set_left(lowercase )
   SCREAMING_SNAKE_CASE_: List[Any]     			=my_max(get_height(node.get_right() )							,			get_height(node.get_left() ) ) + 1
   node.set_height(lowercase )
   SCREAMING_SNAKE_CASE_: Optional[int]     			=my_max(get_height(ret.get_right() )							,			get_height(ret.get_left() ) ) + 1
   ret.set_height(lowercase )
   return ret





def      __magic_name__				(							lowercase ):
   SCREAMING_SNAKE_CASE_: Any     			=node.get_left()
   assert left_child is not None
   node.set_left(left_rotation(lowercase ) )
   return right_rotation(lowercase )





def      __magic_name__				(							lowercase ):
   SCREAMING_SNAKE_CASE_: Dict     			=node.get_right()
   assert right_child is not None
   node.set_right(right_rotation(lowercase ) )
   return left_rotation(lowercase )





def      __magic_name__				(							lowercase							,			lowercase ):
   if node is None:
      return MyNode(lowercase )
   if data < node.get_data():
      node.set_left(insert_node(node.get_left()							,			lowercase ) )
      if (
          get_height(node.get_left() ) - get_height(node.get_right() ) == 2
      ):  # an unbalance detected
         SCREAMING_SNAKE_CASE_: Union[str, Any]     			=node.get_left()
         assert left_child is not None
         if (
             data < left_child.get_data()
         ):  # new node is the left child of the left child
            SCREAMING_SNAKE_CASE_: Any     			=right_rotation(lowercase )
         else:
            SCREAMING_SNAKE_CASE_: List[Any]     			=lr_rotation(lowercase )
   else:
      node.set_right(insert_node(node.get_right()							,			lowercase ) )
      if get_height(node.get_right() ) - get_height(node.get_left() ) == 2:
         SCREAMING_SNAKE_CASE_: Tuple     			=node.get_right()
         assert right_child is not None
         if data < right_child.get_data():
            SCREAMING_SNAKE_CASE_: Optional[Any]     			=rl_rotation(lowercase )
         else:
            SCREAMING_SNAKE_CASE_: Optional[int]     			=left_rotation(lowercase )
   SCREAMING_SNAKE_CASE_: Tuple     			=my_max(get_height(node.get_right() )							,			get_height(node.get_left() ) ) + 1
   node.set_height(lowercase )
   return node





def      __magic_name__				(							lowercase ):
   while True:
      SCREAMING_SNAKE_CASE_: Dict     			=root.get_right()
      if right_child is None:
         break
      SCREAMING_SNAKE_CASE_: str     			=right_child
   return root.get_data()





def      __magic_name__				(							lowercase ):
   while True:
      SCREAMING_SNAKE_CASE_: str     			=root.get_left()
      if left_child is None:
         break
      SCREAMING_SNAKE_CASE_: Dict     			=left_child
   return root.get_data()





def      __magic_name__				(							lowercase							,			lowercase ):
   SCREAMING_SNAKE_CASE_: str     			=root.get_left()
   SCREAMING_SNAKE_CASE_: List[Any]     			=root.get_right()
   if root.get_data() == data:
      if left_child is not None and right_child is not None:
         SCREAMING_SNAKE_CASE_: Union[str, Any]     			=get_left_most(lowercase )
         root.set_data(lowercase )
         root.set_right(del_node(lowercase							,			lowercase ) )
      elif left_child is not None:
         SCREAMING_SNAKE_CASE_: Optional[int]     			=left_child
      elif right_child is not None:
         SCREAMING_SNAKE_CASE_: Any     			=right_child
      else:
         return None
   elif root.get_data() > data:
      if left_child is None:
         print("""No such data""" )
         return root
      else:
         root.set_left(del_node(lowercase							,			lowercase ) )
   else:  # root.get_data() < data
      if right_child is None:
         return root
      else:
         root.set_right(del_node(lowercase							,			lowercase ) )

   if get_height(lowercase ) - get_height(lowercase ) == 2:
      assert right_child is not None
      if get_height(right_child.get_right() ) > get_height(right_child.get_left() ):
         SCREAMING_SNAKE_CASE_: Tuple     			=left_rotation(lowercase )
      else:
         SCREAMING_SNAKE_CASE_: Optional[Any]     			=rl_rotation(lowercase )
   elif get_height(lowercase ) - get_height(lowercase ) == -2:
      assert left_child is not None
      if get_height(left_child.get_left() ) > get_height(left_child.get_right() ):
         SCREAMING_SNAKE_CASE_: Optional[Any]     			=right_rotation(lowercase )
      else:
         SCREAMING_SNAKE_CASE_: str     			=lr_rotation(lowercase )
   SCREAMING_SNAKE_CASE_: str     			=my_max(get_height(root.get_right() )							,			get_height(root.get_left() ) ) + 1
   root.set_height(lowercase )
   return root
class 					a	:



  def __init__(						self :					int		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: MyNode | None     			=None



  def 	lowerCamelCase__       (						self :					List[Any]		)     ->					int:


     '''simple docstring'''




     return get_height(self.root		)



  def 	lowerCamelCase__       (						self :					Optional[int]       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     print("""insert:""" + str(lowerCAmelCase		)		)
     SCREAMING_SNAKE_CASE_: Tuple     			=insert_node(self.root       ,		lowerCAmelCase		)



  def 	lowerCamelCase__       (						self :					List[Any]       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     print("""delete:""" + str(lowerCAmelCase		)		)
     if self.root is None:
        print("""Tree is empty!"""		)
        return
     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=del_node(self.root       ,		lowerCAmelCase		)





  def __str__(						self :					List[str]       ,		)     ->					str:  # a level traversale, gives a more intuitive look on the tree


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: List[Any]     			=""""""
     SCREAMING_SNAKE_CASE_: str     			=MyQueue()
     q.push(self.root		)
     SCREAMING_SNAKE_CASE_: List[str]     			=self.get_height()
     if layer == 0:
        return output
     SCREAMING_SNAKE_CASE_: int     			=0
     while not q.is_empty():
        SCREAMING_SNAKE_CASE_: int     			=q.pop()
        SCREAMING_SNAKE_CASE_: List[Any]     			=""" """ * int(math.pow(2       ,		layer - 1		)		)
        output += space
        if node is None:
           output += "*"
           q.push(lowerCAmelCase		)
           q.push(lowerCAmelCase		)
        else:
           output += str(node.get_data()		)
           q.push(node.get_left()		)
           q.push(node.get_right()		)
        output += space
        SCREAMING_SNAKE_CASE_: List[Any]     			=cnt + 1
        for i in range(100		):
           if cnt == math.pow(2       ,		lowerCAmelCase		) - 1:
              SCREAMING_SNAKE_CASE_: int     			=layer - 1
              if layer == 0:
                 output += "\n*************************************"
                 return output
              output += "\n"
              break
     output += "\n*************************************"
     return output







def      __magic_name__				(							):
   import doctest

   doctest.testmod()


if __name__ == "__main__":
   _test()
   _UpperCAmelCase     =			AVLtree()
   _UpperCAmelCase     =			list(range(1_0))
   random.shuffle(lst)
   for i in lst:
      t.insert(i)
      print(str(t))
   random.shuffle(lst)
   for i in lst:
      t.del_node(i)
      print(str(t))



