



import unittest

from transformers.image_processing_utils import get_size_dict



class 						_snake_case (     unittest.TestCase			):





 """simple docstring"""



 def lowercase_						(  self   )		->							str:




   """simple docstring"""







   _A          =      {'''wrong_key''': 2_2_4}
   with self.assertRaises(a   ):
     get_size_dict(a   )

   _A          =      {'''height''': 2_2_4}
   with self.assertRaises(a   ):
     get_size_dict(a   )

   _A          =      {'''width''': 2_2_4, '''shortest_edge''': 2_2_4}
   with self.assertRaises(a   ):
     get_size_dict(a   )

   # Test a dict with the correct keys is returned as is
   _A          =      {'''height''': 2_2_4, '''width''': 2_2_4}
   _A          =      get_size_dict(a   )
   self.assertEqual(a		,      a   )

   _A          =      {'''shortest_edge''': 2_2_4}
   _A          =      get_size_dict(a   )
   self.assertEqual(a		,      {'''shortest_edge''': 2_2_4}   )

   _A          =      {'''longest_edge''': 2_2_4, '''shortest_edge''': 2_2_4}
   _A          =      get_size_dict(a   )
   self.assertEqual(a		,      {'''longest_edge''': 2_2_4, '''shortest_edge''': 2_2_4}   )

   # Test a single int value which  represents (size, size)
   _A          =      get_size_dict(2_2_4   )
   self.assertEqual(a		,      {'''height''': 2_2_4, '''width''': 2_2_4}   )

   # Test a single int value which represents the shortest edge
   _A          =      get_size_dict(2_2_4		,      default_to_square=a   )
   self.assertEqual(a		,      {'''shortest_edge''': 2_2_4}   )

   # Test a tuple of ints which represents (height, width)
   _A          =      get_size_dict((1_5_0, 2_0_0)   )
   self.assertEqual(a		,      {'''height''': 1_5_0, '''width''': 2_0_0}   )

   # Test a tuple of ints which represents (width, height)
   _A          =      get_size_dict((1_5_0, 2_0_0)		,      height_width_order=a   )
   self.assertEqual(a		,      {'''height''': 2_0_0, '''width''': 1_5_0}   )

   # Test an int representing the shortest edge and max_size which represents the longest edge
   _A          =      get_size_dict(2_2_4		,      max_size=2_5_6		,      default_to_square=a   )
   self.assertEqual(a		,      {'''shortest_edge''': 2_2_4, '''longest_edge''': 2_5_6}   )

   # Test int with default_to_square=True and max_size fails
   with self.assertRaises(a   ):
     get_size_dict(2_2_4		,      max_size=2_5_6		,      default_to_square=a   )




import importlib.metadata
import subprocess
import sys




def       UpperCAmelCase__	(							__snake_case = False							)				->	List[Any]:
  _A          =      False
  if "IPython" in sys.modules:
    _A          =      '''google.colab''' in str(sys.modules['''IPython'''].get_ipython()							)

  if in_colab:
    if upgrade:
      _A          =      ['''pip''', '''install''', '''-U''', '''torch''']
      subprocess.run(__snake_case  ,			check=__snake_case							)
    # get the current version of torch
    _A          =      importlib.metadata.version('''torch'''							)
    _A          =      torch_version[: torch_version.rindex('''.'''							)]
    _A          =      F'''https://storage.googleapis.com/tpu-pytorch/wheels/colab/torch_xla-{torch_version_trunc}-cp37-cp37m-linux_x86_64.whl'''
    _A          =      ['''pip''', '''install''', xla_wheel]
    subprocess.run(__snake_case  ,			check=__snake_case							)
  else:
    raise RuntimeError('''`install_xla` utility works only on google colab.'''							)