





'''simple docstring'''
from typing import Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, valid_images
from ...utils import TensorType, logging


__snake_case							   =  logging.get_logger(__name__)
class      lowercase			(							__lowercase      ):

		"""simple docstring"""

		_a									=       ['pixel_values']




		def __init__(	self					,     UpperCamelCase_ = True					,     UpperCamelCase_ = 1 / 255					,     UpperCamelCase_ = True					,     UpperCamelCase_ = 8					,     **UpperCamelCase_					,     ):

							'''simple docstring'''


							super().__init__(**__A							)

							UpperCamelCase__     :List[str]							      =				do_rescale
							UpperCamelCase__     :Optional[int]							      =				rescale_factor
							UpperCamelCase__     :str							      =				do_pad
							UpperCamelCase__     :int							      =				pad_size




		def 					lowerCAmelCase__       (	self					,     UpperCamelCase_					,     UpperCamelCase_					,     UpperCamelCase_ = None					,     **UpperCamelCase_							):

							'''simple docstring'''


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




		def 					lowerCAmelCase__       (	self					,     UpperCamelCase_					,     UpperCamelCase_					,     UpperCamelCase_ = None							):

							'''simple docstring'''


							UpperCamelCase__      ,       UpperCamelCase__     :Optional[Any]							      =				get_image_size(__A							)
							UpperCamelCase__     :Union[str, Any]							      =				(old_height // size + 1) * size - old_height
							UpperCamelCase__     :Union[str, Any]							      =				(old_width // size + 1) * size - old_width

							return pad(__A					,     ((0, pad_height), (0, pad_width))					,     mode='''symmetric'''					,     data_format=__A							)




		def 					lowerCAmelCase__       (	self					,     UpperCamelCase_					,     UpperCamelCase_ = None					,     UpperCamelCase_ = None					,     UpperCamelCase_ = None					,     UpperCamelCase_ = None					,     UpperCamelCase_ = None					,     UpperCamelCase_ = ChannelDimension.FIRST					,     **UpperCamelCase_					,     ):

							'''simple docstring'''


							UpperCamelCase__     :Optional[Any]							      =				do_rescale if do_rescale is not None else self.do_rescale
							UpperCamelCase__     :Dict							      =				rescale_factor if rescale_factor is not None else self.rescale_factor
							UpperCamelCase__     :int							      =				do_pad if do_pad is not None else self.do_pad
							UpperCamelCase__     :List[str]							      =				pad_size if pad_size is not None else self.pad_size

							UpperCamelCase__     :Dict							      =				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_rescale and rescale_factor is None:
												raise ValueError('''Rescale factor must be specified if do_rescale is True.'''							)

							# All transformations expect numpy arrays.
							UpperCamelCase__     :Optional[int]							      =				[to_numpy_array(__A							) for image in images]

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

							if do_pad:
												UpperCamelCase__     :Union[str, Any]							      =				[self.pad(__A					,     size=__A							) for image in images]

							UpperCamelCase__     :List[Any]							      =				[to_channel_dimension_format(__A					,     __A							) for image in images]

							UpperCamelCase__     :str							      =				{'''pixel_values''': images}
							return BatchFeature(data=__A					,     tensor_type=__A							)



'''simple docstring'''
class      lowercase			:

		"""simple docstring"""

		def __init__(	self					,     UpperCamelCase_							):

							'''simple docstring'''


							UpperCamelCase__     :Union[str, Any]							      =				n
							UpperCamelCase__     :Tuple							      =				[None] * self.n
							UpperCamelCase__     :str							      =				0  # index of the first element
							UpperCamelCase__     :List[Any]							      =				0
							UpperCamelCase__     :Dict							      =				0




		def __len__(	self							):

							'''simple docstring'''


							return self.size




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							return self.size == 0




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							return False if self.is_empty() else self.array[self.front]




		def 					lowerCAmelCase__       (	self					,     UpperCamelCase_							):

							'''simple docstring'''


							if self.size >= self.n:
												raise Exception('''QUEUE IS FULL'''							)

							UpperCamelCase__     :List[Any]							      =				data
							UpperCamelCase__     :List[Any]							      =				(self.rear + 1) % self.n
							self.size += 1
							return self




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							if self.size == 0:
												raise Exception('''UNDERFLOW'''							)

							UpperCamelCase__     :Dict							      =				self.array[self.front]
							UpperCamelCase__     :Union[str, Any]							      =				None
							UpperCamelCase__     :Union[str, Any]							      =				(self.front + 1) % self.n
							self.size -= 1
							return temp