
"""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,
    get_resize_output_image_size,
    normalize,
    rescale,
    resize,
    to_channel_dimension_format,
)
from ...image_utils import (
    IMAGENET_STANDARD_MEAN,
    IMAGENET_STANDARD_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, logging


lowerCAmelCase__							=				logging.get_logger(__name__)





class  snake_case     (							__lowercase   ):
							UpperCAmelCase__						     =      ['''pixel_values''']

							def __init__(self       ,       SCREAMING_SNAKE_CASE_ = True       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = PILImageResampling.BILINEAR       ,       SCREAMING_SNAKE_CASE_ = True       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = True       ,       SCREAMING_SNAKE_CASE_ = 1 / 2_55       ,       SCREAMING_SNAKE_CASE_ = True       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = None       ,       **SCREAMING_SNAKE_CASE_       ,       ):

									"""simple docstring"""







									super().__init__(**SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = size if size is not None else {'''shortest_edge''': 2_56}
									SCREAMING_SNAKE_CASE_						 = get_size_dict(SCREAMING_SNAKE_CASE_       ,       default_to_square=SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = crop_size if crop_size is not None else {'''height''': 2_24, '''width''': 2_24}
									SCREAMING_SNAKE_CASE_						 = get_size_dict(SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = do_resize
									SCREAMING_SNAKE_CASE_						 = size
									SCREAMING_SNAKE_CASE_						 = resample
									SCREAMING_SNAKE_CASE_						 = do_center_crop
									SCREAMING_SNAKE_CASE_						 = crop_size
									SCREAMING_SNAKE_CASE_						 = do_rescale
									SCREAMING_SNAKE_CASE_						 = rescale_factor
									SCREAMING_SNAKE_CASE_						 = do_normalize
									SCREAMING_SNAKE_CASE_						 = image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
									SCREAMING_SNAKE_CASE_						 = image_std if image_std is not None else IMAGENET_STANDARD_STD

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_ = PILImageResampling.BICUBIC       ,       SCREAMING_SNAKE_CASE_ = None       ,       **SCREAMING_SNAKE_CASE_       ,       ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = get_size_dict(SCREAMING_SNAKE_CASE_       ,       default_to_square=SCREAMING_SNAKE_CASE_    )
									if "shortest_edge" not in size:
											raise ValueError(f'The `size` parameter must contain the key `shortest_edge`. Got {size.keys()}'    )
									SCREAMING_SNAKE_CASE_						 = get_resize_output_image_size(SCREAMING_SNAKE_CASE_       ,       size=size['''shortest_edge''']       ,       default_to_square=SCREAMING_SNAKE_CASE_    )
									return resize(SCREAMING_SNAKE_CASE_       ,       size=SCREAMING_SNAKE_CASE_       ,       resample=SCREAMING_SNAKE_CASE_       ,       data_format=SCREAMING_SNAKE_CASE_       ,       **SCREAMING_SNAKE_CASE_    )

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_ = None       ,       **SCREAMING_SNAKE_CASE_       ,       ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = get_size_dict(SCREAMING_SNAKE_CASE_    )
									return center_crop(SCREAMING_SNAKE_CASE_       ,       size=(size['''height'''], size['''width'''])       ,       data_format=SCREAMING_SNAKE_CASE_       ,       **SCREAMING_SNAKE_CASE_    )

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_ = None       ,       **SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







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

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_ = None       ,       **SCREAMING_SNAKE_CASE_       ,       ):

									"""simple docstring"""







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







							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = None       ,       SCREAMING_SNAKE_CASE_ = ChannelDimension.FIRST       ,       **SCREAMING_SNAKE_CASE_       ,       ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = do_resize if do_resize is not None else self.do_resize
									SCREAMING_SNAKE_CASE_						 = size if size is not None else self.size
									SCREAMING_SNAKE_CASE_						 = get_size_dict(SCREAMING_SNAKE_CASE_       ,       default_to_square=SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = resample if resample is not None else self.resample
									SCREAMING_SNAKE_CASE_						 = do_center_crop if do_center_crop is not None else self.do_center_crop
									SCREAMING_SNAKE_CASE_						 = crop_size if crop_size is not None else self.crop_size
									SCREAMING_SNAKE_CASE_						 = get_size_dict(SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = do_rescale if do_rescale is not None else self.do_rescale
									SCREAMING_SNAKE_CASE_						 = rescale_factor if rescale_factor is not None else self.rescale_factor
									SCREAMING_SNAKE_CASE_						 = do_normalize if do_normalize is not None else self.do_normalize
									SCREAMING_SNAKE_CASE_						 = image_mean if image_mean is not None else self.image_mean
									SCREAMING_SNAKE_CASE_						 = image_std if image_std is not None else self.image_std

									SCREAMING_SNAKE_CASE_						 = make_list_of_images(SCREAMING_SNAKE_CASE_    )

									if not valid_images(SCREAMING_SNAKE_CASE_    ):
											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.'''    )

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

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

									if do_center_crop:
											SCREAMING_SNAKE_CASE_						 = [self.center_crop(image=SCREAMING_SNAKE_CASE_       ,       size=SCREAMING_SNAKE_CASE_    ) for image in images]

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

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

									SCREAMING_SNAKE_CASE_						 = [to_channel_dimension_format(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ) for image in images]

									SCREAMING_SNAKE_CASE_						 = {'''pixel_values''': images}
									return BatchFeature(data=SCREAMING_SNAKE_CASE_       ,       tensor_type=SCREAMING_SNAKE_CASE_    )

"""simple docstring"""




from collections.abc import Sequence
from queue import Queue





class  snake_case     :

							def __init__(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_=None       ,       SCREAMING_SNAKE_CASE_=None    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = start
									SCREAMING_SNAKE_CASE_						 = end
									SCREAMING_SNAKE_CASE_						 = val
									SCREAMING_SNAKE_CASE_						 = (start + end) // 2
									SCREAMING_SNAKE_CASE_						 = left
									SCREAMING_SNAKE_CASE_						 = right







							def __repr__(self    ):

									"""simple docstring"""







									return f'SegmentTreeNode(start={self.start}, end={self.end}, val={self.val})'







class  snake_case     :

							def __init__(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = collection
									SCREAMING_SNAKE_CASE_						 = function
									if self.collection:
											SCREAMING_SNAKE_CASE_						 = self._build_tree(0       ,       len(SCREAMING_SNAKE_CASE_    ) - 1    )

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									self._update_tree(self.root       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									return self._query_range(self.root       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									if start == end:
											return SegmentTreeNode(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       self.collection[start]    )
									SCREAMING_SNAKE_CASE_						 = (start + end) // 2
									SCREAMING_SNAKE_CASE_						 = self._build_tree(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = self._build_tree(mid + 1       ,       SCREAMING_SNAKE_CASE_    )
									return SegmentTreeNode(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       self.fn(left.val       ,       right.val    )       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									if node.start == i and node.end == i:
											SCREAMING_SNAKE_CASE_						 = val
											return
									if i <= node.mid:
											self._update_tree(node.left       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )
									else:
											self._update_tree(node.right       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = self.fn(node.left.val       ,       node.right.val    )

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									if node.start == i and node.end == j:
											return node.val

									if i <= node.mid:
											if j <= node.mid:
													# range in left child tree
													return self._query_range(node.left       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )
											else:
													# range in left child tree and right child tree
													return self.fn(
													    self._query_range(node.left       ,       SCREAMING_SNAKE_CASE_       ,       node.mid    )       ,       self._query_range(node.right       ,       node.mid + 1       ,       SCREAMING_SNAKE_CASE_    )       ,       )
									else:
											# range in right child tree
											return self._query_range(node.right       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )







							def _lowercase					(self    ):

									"""simple docstring"""







									if self.root is not None:
											SCREAMING_SNAKE_CASE_						 = Queue()
											queue.put(self.root    )
											while not queue.empty():
													SCREAMING_SNAKE_CASE_						 = queue.get()
													yield node

													if node.left is not None:
															queue.put(node.left    )

													if node.right is not None:
															queue.put(node.right    )


if __name__ == "__main__":
						import operator

						for fn in [operator.add, max, min]:
												print('*' * 50)
												lowerCAmelCase__							=				SegmentTree([2, 1, 5, 3, 4], fn)
												for node in arr.traverse():
																		print(node)
												print()

												arr.update(1, 5)
												for node in arr.traverse():
																		print(node)
												print()

												print(arr.query_range(3, 4))  # 7
												print(arr.query_range(2, 2))  # 5
												print(arr.query_range(1, 3))  # 13
												print()