
import unittest

import numpy as np

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available

from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs


if is_torch_available():
     import torch

if is_vision_available():
     from PIL import Image

     from transformers import PoolFormerImageProcessor

class       _snake_case   (	unittest.TestCase							):


 def __init__(					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_=7					,  SCREAMING_SNAKE_CASE_=3					,  SCREAMING_SNAKE_CASE_=30					,  SCREAMING_SNAKE_CASE_=4_00					,  SCREAMING_SNAKE_CASE_=True					,  SCREAMING_SNAKE_CASE_=None					,  SCREAMING_SNAKE_CASE_=0.9					,  SCREAMING_SNAKE_CASE_=None					,  SCREAMING_SNAKE_CASE_=True					,  SCREAMING_SNAKE_CASE_=[0.5, 0.5, 0.5]					,  SCREAMING_SNAKE_CASE_=[0.5, 0.5, 0.5]					,  ):


   '''simple docstring'''




   lowercase__  :   Dict    		=      size if size is not None else {"""shortest_edge""": 30}
   lowercase__  :   List[Any]    		=      crop_size if crop_size is not None else {"""height""": 30, """width""": 30}
   lowercase__  :   List[str]    		=      parent
   lowercase__  :   Tuple    		=      batch_size
   lowercase__  :   List[str]    		=      num_channels
   lowercase__  :   Optional[Any]    		=      min_resolution
   lowercase__  :   Tuple    		=      max_resolution
   lowercase__  :   str    		=      do_resize_and_center_crop
   lowercase__  :   Union[str, Any]    		=      size
   lowercase__  :   Tuple    		=      crop_pct
   lowercase__  :   List[str]    		=      crop_size
   lowercase__  :   Union[str, Any]    		=      do_normalize
   lowercase__  :   Optional[Any]    		=      image_mean
   lowercase__  :   int    		=      image_std



 def      lowercase__     (					self):


   '''simple docstring'''




   return {
       "size": self.size,
       "do_resize_and_center_crop": self.do_resize_and_center_crop,
       "crop_pct": self.crop_pct,
       "crop_size": self.crop_size,
       "do_normalize": self.do_normalize,
       "image_mean": self.image_mean,
       "image_std": self.image_std,
   }

@require_torch
@require_vision
class       _snake_case   (	UpperCAmelCase_  ,						unittest.TestCase							):
 __lowerCAmelCase  :     Any        =			PoolFormerImageProcessor if is_vision_available() else None


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   Union[str, Any]    		=      PoolFormerImageProcessingTester(self)


 @property
 def      lowercase__     (					self):


   '''simple docstring'''




   return self.image_processor_tester.prepare_image_processor_dict()


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   Dict    		=      self.image_processing_class(**self.image_processor_dict)
   self.assertTrue(hasattr(SCREAMING_SNAKE_CASE_					,  """do_resize_and_center_crop"""))
   self.assertTrue(hasattr(SCREAMING_SNAKE_CASE_					,  """size"""))
   self.assertTrue(hasattr(SCREAMING_SNAKE_CASE_					,  """crop_pct"""))
   self.assertTrue(hasattr(SCREAMING_SNAKE_CASE_					,  """do_normalize"""))
   self.assertTrue(hasattr(SCREAMING_SNAKE_CASE_					,  """image_mean"""))
   self.assertTrue(hasattr(SCREAMING_SNAKE_CASE_					,  """image_std"""))


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   Optional[int]    		=      self.image_processing_class.from_dict(self.image_processor_dict)
   self.assertEqual(image_processor.size					,  {"""shortest_edge""": 30})
   self.assertEqual(image_processor.crop_size					,  {"""height""": 30, """width""": 30})

   lowercase__  :   Optional[Any]    		=      self.image_processing_class.from_dict(self.image_processor_dict					,  size=42					,  crop_size=84)
   self.assertEqual(image_processor.size					,  {"""shortest_edge""": 42})
   self.assertEqual(image_processor.crop_size					,  {"""height""": 84, """width""": 84})


 def      lowercase__     (					self):


   '''simple docstring'''




   pass


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   List[str]    		=      self.image_processing_class(**self.image_processor_dict)
   # create random PIL images
   lowercase__  :   int    		=      prepare_image_inputs(self.image_processor_tester					,  equal_resolution=SCREAMING_SNAKE_CASE_)
   for image in image_inputs:
     self.assertIsInstance(SCREAMING_SNAKE_CASE_					,  Image.Image)

   # Test not batched input
   lowercase__  :   Tuple    		=      image_processing(image_inputs[0]					,  return_tensors="""pt""").pixel_values

   self.assertEqual(
       encoded_images.shape					,  (
           1,
           self.image_processor_tester.num_channels,
           self.image_processor_tester.crop_size["""height"""],
           self.image_processor_tester.crop_size["""width"""],
       )					,  )

   # Test batched
   lowercase__  :   str    		=      image_processing(SCREAMING_SNAKE_CASE_					,  return_tensors="""pt""").pixel_values
   self.assertEqual(
       encoded_images.shape					,  (
           self.image_processor_tester.batch_size,
           self.image_processor_tester.num_channels,
           self.image_processor_tester.crop_size["""height"""],
           self.image_processor_tester.crop_size["""width"""],
       )					,  )


 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   List[Any]    		=      self.image_processing_class(**self.image_processor_dict)
   # create random numpy tensors
   lowercase__  :   Optional[int]    		=      prepare_image_inputs(self.image_processor_tester					,  equal_resolution=SCREAMING_SNAKE_CASE_					,  numpify=SCREAMING_SNAKE_CASE_)
   for image in image_inputs:
     self.assertIsInstance(SCREAMING_SNAKE_CASE_					,  np.ndarray)

   # Test not batched input
   lowercase__  :   Optional[int]    		=      image_processing(image_inputs[0]					,  return_tensors="""pt""").pixel_values
   self.assertEqual(
       encoded_images.shape					,  (
           1,
           self.image_processor_tester.num_channels,
           self.image_processor_tester.crop_size["""height"""],
           self.image_processor_tester.crop_size["""width"""],
       )					,  )

   # Test batched
   lowercase__  :   str    		=      image_processing(SCREAMING_SNAKE_CASE_					,  return_tensors="""pt""").pixel_values
   self.assertEqual(
       encoded_images.shape					,  (
           self.image_processor_tester.batch_size,
           self.image_processor_tester.num_channels,
           self.image_processor_tester.crop_size["""height"""],
           self.image_processor_tester.crop_size["""width"""],
       )					,  )



 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   List[Any]    		=      self.image_processing_class(**self.image_processor_dict)
   # create random PyTorch tensors
   lowercase__  :   Optional[Any]    		=      prepare_image_inputs(self.image_processor_tester					,  equal_resolution=SCREAMING_SNAKE_CASE_					,  torchify=SCREAMING_SNAKE_CASE_)
   for image in image_inputs:
     self.assertIsInstance(SCREAMING_SNAKE_CASE_					,  torch.Tensor)

   # Test not batched input
   lowercase__  :   List[str]    		=      image_processing(image_inputs[0]					,  return_tensors="""pt""").pixel_values
   self.assertEqual(
       encoded_images.shape					,  (
           1,
           self.image_processor_tester.num_channels,
           self.image_processor_tester.crop_size["""height"""],
           self.image_processor_tester.crop_size["""width"""],
       )					,  )

   # Test batched
   lowercase__  :   str    		=      image_processing(SCREAMING_SNAKE_CASE_					,  return_tensors="""pt""").pixel_values
   self.assertEqual(
       encoded_images.shape					,  (
           self.image_processor_tester.batch_size,
           self.image_processor_tester.num_channels,
           self.image_processor_tester.crop_size["""height"""],
           self.image_processor_tester.crop_size["""width"""],
       )					,  )








from __future__ import annotations

import math
import random
from collections.abc import Collection
from typing import overload



class       _snake_case   :


 def __init__(					self					,  SCREAMING_SNAKE_CASE_ = None):


   '''simple docstring'''




   if components is None:
     lowercase__  :   List[str]    		=      []
   lowercase__  :   Dict    		=      list(SCREAMING_SNAKE_CASE_)


 def __len__(					self):


   '''simple docstring'''




   return len(self.__components)


 def __str__(					self):


   '''simple docstring'''




   return "(" + ",".join(map(SCREAMING_SNAKE_CASE_					,  self.__components)) + ")"


 def __add__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   Optional[Any]    		=      len(self)
   if size == len(SCREAMING_SNAKE_CASE_):
     lowercase__  :   List[str]    		=      [self.__components[i] + other.component(SCREAMING_SNAKE_CASE_) for i in range(SCREAMING_SNAKE_CASE_)]
     return Vector(SCREAMING_SNAKE_CASE_)
   else:
     raise Exception("""must have the same size""")


 def __sub__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   List[Any]    		=      len(self)
   if size == len(SCREAMING_SNAKE_CASE_):
     lowercase__  :   Optional[Any]    		=      [self.__components[i] - other.component(SCREAMING_SNAKE_CASE_) for i in range(SCREAMING_SNAKE_CASE_)]
     return Vector(SCREAMING_SNAKE_CASE_)
   else:  # error case
     raise Exception("""must have the same size""")


 @overload
 def __mul__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   ...


 @overload
 def __mul__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   ...


 def __mul__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if isinstance(SCREAMING_SNAKE_CASE_					,  (float, int)):
     lowercase__  :   Optional[int]    		=      [c * other for c in self.__components]
     return Vector(SCREAMING_SNAKE_CASE_)
   elif isinstance(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_) and len(self) == len(SCREAMING_SNAKE_CASE_):
     lowercase__  :   Dict    		=      len(self)
     lowercase__  :   Optional[Any]    		=      [self.__components[i] * other.component(SCREAMING_SNAKE_CASE_) for i in range(SCREAMING_SNAKE_CASE_)]
     return sum(SCREAMING_SNAKE_CASE_)
   else:  # error case
     raise Exception("""invalid operand!""")


 def      lowercase__     (					self):


   '''simple docstring'''




   return Vector(self.__components)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if isinstance(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_) and -len(self.__components) <= i < len(self.__components):
     return self.__components[i]
   else:
     raise Exception("""index out of range""")


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   assert -len(self.__components) <= pos < len(self.__components)
   lowercase__  :   List[Any]    		=      value


 def      lowercase__     (					self):


   '''simple docstring'''




   if len(self.__components) == 0:
     raise Exception("""Vector is empty""")
   lowercase__  :   Union[str, Any]    		=      [c**2 for c in self.__components]
   return math.sqrt(sum(SCREAMING_SNAKE_CASE_))



 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_ = False):


   '''simple docstring'''




   lowercase__  :   Union[str, Any]    		=      self * other
   lowercase__  :   Optional[Any]    		=      self.euclidean_length() * other.euclidean_length()
   if deg:
     return math.degrees(math.acos(num / den))
   else:
     return math.acos(num / den)

def 		UpperCamelCase	(      lowercase_   )		->	Vector:


  '''simple docstring'''






  assert isinstance(lowercase_ , lowercase_   )
  return Vector([0] * dimension   )

def 		UpperCamelCase	(      lowercase_ , lowercase_   )		->	Vector:


  '''simple docstring'''






  assert isinstance(lowercase_ , lowercase_   ) and (isinstance(lowercase_ , lowercase_   ))
  lowercase__  :   Union[str, Any]    		=      [0] * dimension
  lowercase__  :   Any    		=      1
  return Vector(lowercase_   )

def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_   )		->	Vector:


  '''simple docstring'''






  assert (
      isinstance(lowercase_ , lowercase_   )
      and isinstance(lowercase_ , lowercase_   )
      and (isinstance(lowercase_ , (int, float)   ))
  )
  return x * scalar + y

def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_   )		->	Vector:


  '''simple docstring'''






  random.seed(lowercase_   )
  lowercase__  :   int    		=      [random.randint(lowercase_ , lowercase_   ) for _ in range(lowercase_   )]
  return Vector(lowercase_   )



class       _snake_case   :


 def __init__(					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   List[Any]    		=      matrix
   lowercase__  :   Any    		=      w
   lowercase__  :   Any    		=      h


 def __str__(					self):


   '''simple docstring'''




   lowercase__  :   str    		=      """"""
   for i in range(self.__height):
     ans += "|"
     for j in range(self.__width):
       if j < self.__width - 1:
         ans += str(self.__matrix[i][j]) + ","
       else:
         ans += str(self.__matrix[i][j]) + "|\n"
   return ans


 def __add__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if self.__width == other.width() and self.__height == other.height():
     lowercase__  :   Tuple    		=      []
     for i in range(self.__height):
       lowercase__  :   Tuple    		=      [
           self.__matrix[i][j] + other.component(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
           for j in range(self.__width)
       ]
       matrix.append(SCREAMING_SNAKE_CASE_)
     return Matrix(SCREAMING_SNAKE_CASE_					,  self.__width					,  self.__height)
   else:
     raise Exception("""matrix must have the same dimension!""")


 def __sub__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if self.__width == other.width() and self.__height == other.height():
     lowercase__  :   Optional[int]    		=      []
     for i in range(self.__height):
       lowercase__  :   List[str]    		=      [
           self.__matrix[i][j] - other.component(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
           for j in range(self.__width)
       ]
       matrix.append(SCREAMING_SNAKE_CASE_)
     return Matrix(SCREAMING_SNAKE_CASE_					,  self.__width					,  self.__height)
   else:
     raise Exception("""matrices must have the same dimension!""")


 @overload
 def __mul__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   ...


 @overload
 def __mul__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   ...


 def __mul__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if isinstance(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):  # matrix-vector
     if len(SCREAMING_SNAKE_CASE_) == self.__width:
       lowercase__  :   List[Any]    		=      zero_vector(self.__height)
       for i in range(self.__height):
         lowercase__  :   Union[str, Any]    		=      [
             self.__matrix[i][j] * other.component(SCREAMING_SNAKE_CASE_)
             for j in range(self.__width)
         ]
         ans.change_component(SCREAMING_SNAKE_CASE_					,  sum(SCREAMING_SNAKE_CASE_))
       return ans
     else:
       raise Exception(
           """vector must have the same size as the """
           """number of columns of the matrix!""")
   elif isinstance(SCREAMING_SNAKE_CASE_					,  (int, float)):  # matrix-scalar
     lowercase__  :   Tuple    		=      [
         [self.__matrix[i][j] * other for j in range(self.__width)]
         for i in range(self.__height)
     ]
     return Matrix(SCREAMING_SNAKE_CASE_					,  self.__width					,  self.__height)
   return None


 def      lowercase__     (					self):


   '''simple docstring'''




   return self.__height


 def      lowercase__     (					self):


   '''simple docstring'''




   return self.__width


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if 0 <= x < self.__height and 0 <= y < self.__width:
     return self.__matrix[x][y]
   else:
     raise Exception("""change_component: indices out of bounds""")


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if 0 <= x < self.__height and 0 <= y < self.__width:
     lowercase__  :   Tuple    		=      value
   else:
     raise Exception("""change_component: indices out of bounds""")


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if self.__height != self.__width:
     raise Exception("""Matrix is not square""")
   lowercase__  :   List[Any]    		=      self.__matrix[:x] + self.__matrix[x + 1 :]
   for i in range(len(SCREAMING_SNAKE_CASE_)):
     lowercase__  :   List[str]    		=      minor[i][:y] + minor[i][y + 1 :]
   return Matrix(SCREAMING_SNAKE_CASE_					,  self.__width - 1					,  self.__height - 1).determinant()


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if self.__height != self.__width:
     raise Exception("""Matrix is not square""")
   if 0 <= x < self.__height and 0 <= y < self.__width:
     return (-1) ** (x + y) * self.minor(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
   else:
     raise Exception("""Indices out of bounds""")



 def      lowercase__     (					self):


   '''simple docstring'''




   if self.__height != self.__width:
     raise Exception("""Matrix is not square""")
   if self.__height < 1:
     raise Exception("""Matrix has no element""")
   elif self.__height == 1:
     return self.__matrix[0][0]
   elif self.__height == 2:
     return (
         self.__matrix[0][0] * self.__matrix[1][1]
         - self.__matrix[0][1] * self.__matrix[1][0]
     )
   else:
     lowercase__  :   Optional[int]    		=      [
         self.__matrix[0][y] * self.cofactor(0					,  SCREAMING_SNAKE_CASE_) for y in range(self.__width)
     ]
     return sum(SCREAMING_SNAKE_CASE_)

def 		UpperCamelCase	(      lowercase_   )		->	Matrix:


  '''simple docstring'''






  lowercase__  :   list[list[float]]    		=      [[0] * n for _ in range(lowercase_   )]
  return Matrix(lowercase_ , lowercase_ , lowercase_   )



def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_ , lowercase_   )		->	Matrix:


  '''simple docstring'''






  random.seed(lowercase_   )
  lowercase__  :   list[list[float]]    		=      [
      [random.randint(lowercase_ , lowercase_   ) for _ in range(lowercase_   )] for _ in range(lowercase_   )
  ]
  return Matrix(lowercase_ , lowercase_ , lowercase_   )






