


'''simple docstring'''



from typing import Dict, List, Optional, Union

import numpy as np

from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType

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,
    is_valid_image,
    to_numpy_array,
    valid_images,
)
from ...utils import logging


if is_vision_available():
		import PIL

__A		=logging.get_logger(__name__)







def       _UpperCamelCase (						UpperCamelCase__   ):
			if isinstance(UpperCamelCase__	, (list, tuple)   ) and isinstance(videos[0]	, (list, tuple)   ) and is_valid_image(videos[0][0]   ):
						return videos

			elif isinstance(UpperCamelCase__	, (list, tuple)   ) and is_valid_image(videos[0]   ):
						return [videos]

			elif is_valid_image(UpperCamelCase__   ):
						return [[videos]]

			raise ValueError(f'''Could not make batched video from {videos}'''   )


class 						_snake_case   (       a__		):
					lowerCAmelCase :Optional[int]						=   ['''pixel_values''']




					def __init__( self							,							_lowerCamelCase = True							,							_lowerCamelCase = None							,							_lowerCamelCase = PILImageResampling.BILINEAR							,							_lowerCamelCase = True							,							_lowerCamelCase = None							,							_lowerCamelCase = True							,							_lowerCamelCase = 1 / 255							,							_lowerCamelCase = True							,							_lowerCamelCase = True							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							**_lowerCamelCase							,							):
								super().__init__(**_lowerCamelCase)
								UpperCAmelCase__					:   Tuple       				=       size if size is not None else {"""shortest_edge""": 256}
								UpperCAmelCase__					:   int       				=       get_size_dict(_lowerCamelCase							,							default_to_square=_lowerCamelCase)
								UpperCAmelCase__					:   Union[str, Any]       				=       crop_size if crop_size is not None else {"""height""": 224, """width""": 224}
								UpperCAmelCase__					:   Union[str, Any]       				=       get_size_dict(_lowerCamelCase							,							param_name="""crop_size""")

								UpperCAmelCase__					:   Optional[int]       				=       do_resize
								UpperCAmelCase__					:   List[Any]       				=       size
								UpperCAmelCase__					:   Tuple       				=       do_center_crop
								UpperCAmelCase__					:   Dict       				=       crop_size
								UpperCAmelCase__					:   List[Any]       				=       resample
								UpperCAmelCase__					:   Dict       				=       do_rescale
								UpperCAmelCase__					:   Optional[Any]       				=       rescale_factor
								UpperCAmelCase__					:   List[str]       				=       offset
								UpperCAmelCase__					:   int       				=       do_normalize
								UpperCAmelCase__					:   int       				=       image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
								UpperCAmelCase__					:   Union[str, Any]       				=       image_std if image_std is not None else IMAGENET_STANDARD_STD




					def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase							,							_lowerCamelCase = PILImageResampling.BILINEAR							,							_lowerCamelCase = None							,							**_lowerCamelCase							,							):
								UpperCAmelCase__					:   Union[str, Any]       				=       get_size_dict(_lowerCamelCase							,							default_to_square=_lowerCamelCase)
								if "shortest_edge" in size:
											UpperCAmelCase__					:   Union[str, Any]       				=       get_resize_output_image_size(_lowerCamelCase							,							size["""shortest_edge"""]							,							default_to_square=_lowerCamelCase)
								elif "height" in size and "width" in size:
											UpperCAmelCase__					:   List[str]       				=       (size["""height"""], size["""width"""])
								else:
											raise ValueError(f'''Size must have \'height\' and \'width\' or \'shortest_edge\' as keys. Got {size.keys()}''')
								return resize(_lowerCamelCase							,							size=_lowerCamelCase							,							resample=_lowerCamelCase							,							data_format=_lowerCamelCase							,							**_lowerCamelCase)




					def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase							,							_lowerCamelCase = None							,							**_lowerCamelCase							,							):
								UpperCAmelCase__					:   Optional[int]       				=       get_size_dict(_lowerCamelCase)
								if "height" not in size or "width" not in size:
											raise ValueError(f'''Size must have \'height\' and \'width\' as keys. Got {size.keys()}''')
								return center_crop(_lowerCamelCase							,							size=(size["""height"""], size["""width"""])							,							data_format=_lowerCamelCase							,							**_lowerCamelCase)




					def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase							,							_lowerCamelCase = True							,							_lowerCamelCase = None							,							**_lowerCamelCase							,							):
								UpperCAmelCase__					:   List[str]       				=       image.astype(np.floataa)
								if offset:
											UpperCAmelCase__					:   str       				=       image - (scale / 2)
								return rescale(_lowerCamelCase							,							scale=_lowerCamelCase							,							data_format=_lowerCamelCase							,							**_lowerCamelCase)




					def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase							,							_lowerCamelCase							,							_lowerCamelCase = None							,							**_lowerCamelCase							,							):
								return normalize(_lowerCamelCase							,							mean=_lowerCamelCase							,							std=_lowerCamelCase							,							data_format=_lowerCamelCase							,							**_lowerCamelCase)




					def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = ChannelDimension.FIRST							,							):
								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_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.""")

								if offset and not do_rescale:
											raise ValueError("""For offset, do_rescale must also be set to True.""")

								# All transformations expect numpy arrays.
								UpperCAmelCase__					:   Dict       				=       to_numpy_array(_lowerCamelCase)

								if do_resize:
											UpperCAmelCase__					:   Any       				=       self.resize(image=_lowerCamelCase							,							size=_lowerCamelCase							,							resample=_lowerCamelCase)

								if do_center_crop:
											UpperCAmelCase__					:   Optional[int]       				=       self.center_crop(_lowerCamelCase							,							size=_lowerCamelCase)

								if do_rescale:
											UpperCAmelCase__					:   Any       				=       self.rescale(image=_lowerCamelCase							,							scale=_lowerCamelCase							,							offset=_lowerCamelCase)

								if do_normalize:
											UpperCAmelCase__					:   Any       				=       self.normalize(image=_lowerCamelCase							,							mean=_lowerCamelCase							,							std=_lowerCamelCase)

								UpperCAmelCase__					:   Dict       				=       to_channel_dimension_format(_lowerCamelCase							,							_lowerCamelCase)
								return image




					def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = None							,							_lowerCamelCase = ChannelDimension.FIRST							,							**_lowerCamelCase							,							):
								UpperCAmelCase__					:   Optional[int]       				=       do_resize if do_resize is not None else self.do_resize
								UpperCAmelCase__					:   str       				=       resample if resample is not None else self.resample
								UpperCAmelCase__					:   Union[str, Any]       				=       do_center_crop if do_center_crop is not None else self.do_center_crop
								UpperCAmelCase__					:   Dict       				=       do_rescale if do_rescale is not None else self.do_rescale
								UpperCAmelCase__					:   List[str]       				=       rescale_factor if rescale_factor is not None else self.rescale_factor
								UpperCAmelCase__					:   Union[str, Any]       				=       offset if offset is not None else self.offset
								UpperCAmelCase__					:   int       				=       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__					:   List[Any]       				=       size if size is not None else self.size
								UpperCAmelCase__					:   Optional[int]       				=       get_size_dict(_lowerCamelCase							,							default_to_square=_lowerCamelCase)
								UpperCAmelCase__					:   List[str]       				=       crop_size if crop_size is not None else self.crop_size
								UpperCAmelCase__					:   Any       				=       get_size_dict(_lowerCamelCase							,							param_name="""crop_size""")

								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.""")

								UpperCAmelCase__					:   Any       				=       make_batched(_lowerCamelCase)

								UpperCAmelCase__					:   List[str]       				=       [
								    [
								        self._preprocess_image(
								            image=_lowerCamelCase							,							do_resize=_lowerCamelCase							,							size=_lowerCamelCase							,							resample=_lowerCamelCase							,							do_center_crop=_lowerCamelCase							,							crop_size=_lowerCamelCase							,							do_rescale=_lowerCamelCase							,							rescale_factor=_lowerCamelCase							,							offset=_lowerCamelCase							,							do_normalize=_lowerCamelCase							,							image_mean=_lowerCamelCase							,							image_std=_lowerCamelCase							,							data_format=_lowerCamelCase							,							)
								        for img in video
								    ]
								    for video in videos
								]

								UpperCAmelCase__					:   int       				=       {"""pixel_values""": videos}
								return BatchFeature(data=_lowerCamelCase							,							tensor_type=_lowerCamelCase)



'''simple docstring'''



import unittest

from .lib import (
    Matrix,
    Vector,
    axpy,
    square_zero_matrix,
    unit_basis_vector,
    zero_vector,
)


class 						_snake_case   (       unittest.TestCase		):




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   str       				=       Vector([1, 2, 3])
								self.assertEqual(x.component(0)							,							1)
								self.assertEqual(x.component(2)							,							3)
								UpperCAmelCase__					:   List[str]       				=       Vector()




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   Any       				=       Vector([0, 0, 0, 0, 0, 1])
								self.assertEqual(str(_lowerCamelCase)							,							"""(0,0,0,0,0,1)""")




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   Optional[int]       				=       Vector([1, 2, 3, 4])
								self.assertEqual(len(_lowerCamelCase)							,							4)




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   List[str]       				=       Vector([1, 2])
								UpperCAmelCase__					:   Optional[int]       				=       Vector([1, 2, 3, 4, 5])
								UpperCAmelCase__					:   Optional[Any]       				=       Vector([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
								UpperCAmelCase__					:   Union[str, Any]       				=       Vector([1, -1, 1, -1, 2, -3, 4, -5])
								self.assertAlmostEqual(x.euclidean_length()							,							2.236							,							3)
								self.assertAlmostEqual(y.euclidean_length()							,							7.416							,							3)
								self.assertEqual(z.euclidean_length()							,							0)
								self.assertAlmostEqual(w.euclidean_length()							,							7.616							,							3)




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   int       				=       Vector([1, 2, 3])
								UpperCAmelCase__					:   Optional[Any]       				=       Vector([1, 1, 1])
								self.assertEqual((x + y).component(0)							,							2)
								self.assertEqual((x + y).component(1)							,							3)
								self.assertEqual((x + y).component(2)							,							4)




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   Optional[int]       				=       Vector([1, 2, 3])
								UpperCAmelCase__					:   Dict       				=       Vector([1, 1, 1])
								self.assertEqual((x - y).component(0)							,							0)
								self.assertEqual((x - y).component(1)							,							1)
								self.assertEqual((x - y).component(2)							,							2)




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   Tuple       				=       Vector([1, 2, 3])
								UpperCAmelCase__					:   Optional[int]       				=       Vector([2, -1, 4])  # for test of dot product
								UpperCAmelCase__					:   Any       				=       Vector([1, -2, -1])
								self.assertEqual(str(x * 3.0)							,							"""(3.0,6.0,9.0)""")
								self.assertEqual((a * b)							,							0)




					def 			snake_case__  ( self):
								self.assertEqual(str(zero_vector(10)).count("""0""")							,							10)




					def 			snake_case__  ( self):
								self.assertEqual(str(unit_basis_vector(3							,							1))							,							"""(0,1,0)""")




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   Any       				=       Vector([1, 2, 3])
								UpperCAmelCase__					:   List[str]       				=       Vector([1, 0, 1])
								self.assertEqual(str(axpy(2							,							_lowerCamelCase							,							_lowerCamelCase))							,							"""(3,4,7)""")




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   Optional[int]       				=       Vector([1, 0, 0, 0, 0, 0])
								UpperCAmelCase__					:   Optional[int]       				=       x.copy()
								self.assertEqual(str(_lowerCamelCase)							,							str(_lowerCamelCase))




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   str       				=       Vector([1, 0, 0])
								x.change_component(0							,							0)
								x.change_component(1							,							1)
								self.assertEqual(str(_lowerCamelCase)							,							"""(0,1,0)""")




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   str       				=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]							,							3							,							3)
								self.assertEqual("""|1,2,3|\n|2,4,5|\n|6,7,8|\n"""							,							str(_lowerCamelCase))




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   List[str]       				=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]							,							3							,							3)
								UpperCAmelCase__					:   Dict       				=       [[-3, -14, -10], [-5, -10, -5], [-2, -1, 0]]
								for x in range(a.height()):
											for y in range(a.width()):
														self.assertEqual(minors[x][y]							,							a.minor(_lowerCamelCase							,							_lowerCamelCase))




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   Any       				=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]							,							3							,							3)
								UpperCAmelCase__					:   Tuple       				=       [[-3, 14, -10], [5, -10, 5], [-2, 1, 0]]
								for x in range(a.height()):
											for y in range(a.width()):
														self.assertEqual(cofactors[x][y]							,							a.cofactor(_lowerCamelCase							,							_lowerCamelCase))




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   Any       				=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]							,							3							,							3)
								self.assertEqual(-5							,							a.determinant())




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   str       				=       Matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]]							,							3							,							3)
								UpperCAmelCase__					:   List[Any]       				=       Vector([1, 2, 3])
								self.assertEqual("""(14,32,50)"""							,							str(a * x))
								self.assertEqual("""|2,4,6|\n|8,10,12|\n|14,16,18|\n"""							,							str(a * 2))




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   Union[str, Any]       				=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]							,							3							,							3)
								a.change_component(0							,							2							,							5)
								self.assertEqual("""|1,2,5|\n|2,4,5|\n|6,7,8|\n"""							,							str(_lowerCamelCase))




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   Any       				=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]							,							3							,							3)
								self.assertEqual(7							,							a.component(2							,							1)							,							0.01)




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   str       				=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]							,							3							,							3)
								UpperCAmelCase__					:   List[Any]       				=       Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 10]]							,							3							,							3)
								self.assertEqual("""|2,4,10|\n|4,8,10|\n|12,14,18|\n"""							,							str(a + b))




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   List[Any]       				=       Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]							,							3							,							3)
								UpperCAmelCase__					:   Dict       				=       Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 10]]							,							3							,							3)
								self.assertEqual("""|0,0,-4|\n|0,0,0|\n|0,0,-2|\n"""							,							str(a - b))




					def 			snake_case__  ( self):
								self.assertEqual(
								    """|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n"""							,							str(square_zero_matrix(5))							,							)


if __name__ == "__main__":
		unittest.main()