

class 							UpperCAmelCase_						:
							"""simple docstring"""







							def __init__(     self			,				_a			,				_a=None			,				_a=None			)       ->       List[str]:
												_a      :       List[Any]   =						data
												_a      :       List[str]   =						previous
												_a      :       Union[str, Any]   =						next_node


							def __str__(     self			)       ->       str:
												return F"""{self.data}"""


							def 							__lowercase							(     self			)       ->       int:
												return self.data


							def 							__lowercase							(     self			)       ->       Union[str, Any]:
												return self.next




							def 							__lowercase							(     self			)       ->       str:
												return self.previous



class 							UpperCAmelCase_						:
							"""simple docstring"""







							def __init__(     self			,				_a			)       ->       str:
												_a      :       int   =						head


							def __iter__(     self			)       ->       List[Any]:
												return self




							def 							__lowercase							(     self			)       ->       Optional[int]:
												if not self.current:
																	raise StopIteration
												else:
																	_a      :       Optional[int]   =						self.current.get_data()
																	_a      :       Dict   =						self.current.get_next()
																	return value



class 							UpperCAmelCase_						:
							"""simple docstring"""







							def __init__(     self			)       ->       str:
												_a      :       Tuple   =						None  # First node in list
												_a      :       List[str]   =						None  # Last node in list


							def __str__(     self			)       ->       List[str]:
												_a      :       Optional[int]   =						self.head
												_a      :       int   =						[]
												while current is not None:
																	nodes.append(current.get_data()			)
																	_a      :       Optional[Any]   =						current.get_next()
												return " ".join(str(_a			) for node in nodes			)


							def __contains__(     self			,				_a			)       ->       Union[str, Any]:
												_a      :       Optional[Any]   =						self.head
												while current:
																	if current.get_data() == value:
																						return True
																	_a      :       Optional[Any]   =						current.get_next()
												return False


							def __iter__(     self			)       ->       Dict:
												return LinkedListIterator(self.head			)


							def 							__lowercase							(     self			)       ->       Any:
												if self.head:
																	return self.head.get_data()
												return None


							def 							__lowercase							(     self			)       ->       Tuple:
												if self.tail:
																	return self.tail.get_data()
												return None


							def 							__lowercase							(     self			,				_a			)       ->       None:
												if self.head is None:
																	_a      :       str   =						node
																	_a      :       Tuple   =						node
												else:
																	self.insert_before_node(self.head			,				_a			)


							def 							__lowercase							(     self			,				_a			)       ->       None:
												if self.head is None:
																	self.set_head(_a			)
												else:
																	self.insert_after_node(self.tail			,				_a			)


							def 							__lowercase							(     self			,				_a			)       ->       None:
												_a      :       str   =						Node(_a			)
												if self.head is None:
																	self.set_head(_a			)
												else:
																	self.set_tail(_a			)


							def 							__lowercase							(     self			,				_a			,				_a			)       ->       None:
												_a      :       List[str]   =						node
												_a      :       str   =						node.previous

												if node.get_previous() is None:
																	_a      :       Optional[int]   =						node_to_insert
												else:
																	_a      :       List[str]   =						node_to_insert

												_a      :       List[str]   =						node_to_insert


							def 							__lowercase							(     self			,				_a			,				_a			)       ->       None:
												_a      :       Union[str, Any]   =						node
												_a      :       List[str]   =						node.next

												if node.get_next() is None:
																	_a      :       Any   =						node_to_insert
												else:
																	_a      :       List[str]   =						node_to_insert

												_a      :       Union[str, Any]   =						node_to_insert


							def 							__lowercase							(     self			,				_a			,				_a			)       ->       None:
												_a      :       List[Any]   =						1
												_a      :       Any   =						Node(_a			)
												_a      :       Any   =						self.head
												while node:
																	if current_position == position:
																						self.insert_before_node(_a			,				_a			)
																						return
																	current_position += 1
																	_a      :       Tuple   =						node.next
												self.insert_after_node(self.tail			,				_a			)


							def 							__lowercase							(     self			,				_a			)       ->       Node:
												_a      :       Optional[Any]   =						self.head
												while node:
																	if node.get_data() == item:
																						return node
																	_a      :       Any   =						node.get_next()
												raise Exception('''Node not found'''			)


							def 							__lowercase							(     self			,				_a			)       ->       Union[str, Any]:
												if (node := self.get_node(_a			)) is not None:
																	if node == self.head:
																						_a      :       Optional[Any]   =						self.head.get_next()

																	if node == self.tail:
																						_a      :       Any   =						self.tail.get_previous()

																	self.remove_node_pointers(_a			)


							@staticmethod
							def 							__lowercase							(     _a			)       ->       None:
												if node.get_next():
																	_a      :       Optional[int]   =						node.previous

												if node.get_previous():
																	_a      :       List[Any]   =						node.next

												_a      :       Optional[int]   =						None
												_a      :       Tuple   =						None




							def 							__lowercase							(     self			)       ->       str:
												return self.head is None



def   __UpperCAmelCase					(      )     ->	None:

					"""simple docstring"""



if __name__ == "__main__":
			import doctest

			doctest.testmod()




'''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 convert_to_rgb, 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


if is_vision_available():
						import PIL


__lowercase        =    logging.get_logger(__name__)






class 							a__(   lowerCAmelCase__      ):


			'''simple docstring'''






			UpperCAmelCase_     :	List[Any]						=			['''pixel_values''']



			def __init__(  self			,       __lowerCAmelCase = True			,       __lowerCAmelCase = None			,       __lowerCAmelCase = PILImageResampling.BICUBIC			,       __lowerCAmelCase = True			,       __lowerCAmelCase = 1 / 255			,       __lowerCAmelCase = True			,       __lowerCAmelCase = None			,       __lowerCAmelCase = None			,       __lowerCAmelCase = True			,       **__lowerCAmelCase			,       ):




					"""simple docstring"""


					super().__init__(**__lowerCAmelCase)
					lowerCAmelCase     =    size if size is not None else {"""height""": 384, """width""": 384}
					lowerCAmelCase     =    get_size_dict(__lowerCAmelCase			,       default_to_square=__lowerCAmelCase)

					lowerCAmelCase     =    do_resize
					lowerCAmelCase     =    size
					lowerCAmelCase     =    resample
					lowerCAmelCase     =    do_rescale
					lowerCAmelCase     =    rescale_factor
					lowerCAmelCase     =    do_normalize
					lowerCAmelCase     =    image_mean if image_mean is not None else OPENAI_CLIP_MEAN
					lowerCAmelCase     =    image_std if image_std is not None else OPENAI_CLIP_STD
					lowerCAmelCase     =    do_convert_rgb



			def 				a_			(  self			,       __lowerCAmelCase			,       __lowerCAmelCase			,       __lowerCAmelCase = PILImageResampling.BICUBIC			,       __lowerCAmelCase = None			,       **__lowerCAmelCase			,       ):




					"""simple docstring"""


					lowerCAmelCase     =    get_size_dict(__lowerCAmelCase			,       default_to_square=__lowerCAmelCase)
					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()}")
					lowerCAmelCase     =    (size["""height"""], size["""width"""])
					return resize(__lowerCAmelCase			,       size=__lowerCAmelCase			,       resample=__lowerCAmelCase			,       data_format=__lowerCAmelCase			,       **__lowerCAmelCase)



			def 				a_			(  self			,       __lowerCAmelCase			,       __lowerCAmelCase			,       __lowerCAmelCase = None			,       **__lowerCAmelCase			,       ):




					"""simple docstring"""


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



			def 				a_			(  self			,       __lowerCAmelCase			,       __lowerCAmelCase			,       __lowerCAmelCase			,       __lowerCAmelCase = None			,       **__lowerCAmelCase			,       ):




					"""simple docstring"""


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







			def 				a_			(  self			,       __lowerCAmelCase			,       __lowerCAmelCase = None			,       __lowerCAmelCase = None			,       __lowerCAmelCase = None			,       __lowerCAmelCase = None			,       __lowerCAmelCase = None			,       __lowerCAmelCase = None			,       __lowerCAmelCase = None			,       __lowerCAmelCase = None			,       __lowerCAmelCase = None			,       __lowerCAmelCase = None			,       __lowerCAmelCase = ChannelDimension.FIRST			,       **__lowerCAmelCase			,       ):




					"""simple docstring"""


					lowerCAmelCase     =    do_resize if do_resize is not None else self.do_resize
					lowerCAmelCase     =    resample if resample is not None else self.resample
					lowerCAmelCase     =    do_rescale if do_rescale is not None else self.do_rescale
					lowerCAmelCase     =    rescale_factor if rescale_factor is not None else self.rescale_factor
					lowerCAmelCase     =    do_normalize if do_normalize is not None else self.do_normalize
					lowerCAmelCase     =    image_mean if image_mean is not None else self.image_mean
					lowerCAmelCase     =    image_std if image_std is not None else self.image_std
					lowerCAmelCase     =    do_convert_rgb if do_convert_rgb is not None else self.do_convert_rgb

					lowerCAmelCase     =    size if size is not None else self.size
					lowerCAmelCase     =    get_size_dict(__lowerCAmelCase			,       default_to_square=__lowerCAmelCase)

					lowerCAmelCase     =    make_list_of_images(__lowerCAmelCase)

					if not valid_images(__lowerCAmelCase):
							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.""")

					# PIL RGBA images are converted to RGB
					if do_convert_rgb:
							lowerCAmelCase     =    [convert_to_rgb(__lowerCAmelCase) for image in images]

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

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

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

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

					lowerCAmelCase     =    [to_channel_dimension_format(__lowerCAmelCase			,       __lowerCAmelCase) for image in images]

					lowerCAmelCase     =    BatchFeature(data={"""pixel_values""": images}			,       tensor_type=__lowerCAmelCase)

					return encoded_outputs




