


'''simple docstring'''



import hashlib
import unittest
from typing import Dict

import numpy as np

from transformers import (
    MODEL_FOR_MASK_GENERATION_MAPPING,
    TF_MODEL_FOR_MASK_GENERATION_MAPPING,
    is_vision_available,
    pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_torch,
    require_vision,
    slow,
)


if is_vision_available():
 from PIL import Image
else:
 class 							__SCREAMING_SNAKE_CASE       :




       @staticmethod
       def  __UpperCamelCase							(  *lowerCamelCase ,   **lowerCamelCase      )							->Tuple:



          '''simple docstring'''
          pass



def    __UpperCAmelCase	(				SCREAMING_SNAKE_CASE__:	Image    )  ->			Union[str, Any]:

   """simple docstring"""
   __a				     =    hashlib.mda(image.tobytes()    )
   return m.hexdigest()[:10]



def    __UpperCAmelCase	(				SCREAMING_SNAKE_CASE__:	Image    )  ->			Tuple:

   """simple docstring"""
   __a				     =    np.array(SCREAMING_SNAKE_CASE__    )
   __a				     =    npimg.shape
   return {"hash": hashimage(SCREAMING_SNAKE_CASE__    ), "shape": shape}



@is_pipeline_test
@require_vision
@require_torch
class 							__SCREAMING_SNAKE_CASE       (							unittest.TestCase     ):
      __a  					=dict(
          (list(MODEL_FOR_MASK_GENERATION_MAPPING.items()     ) if MODEL_FOR_MASK_GENERATION_MAPPING else [])     )
      __a  					=dict(
          (list(TF_MODEL_FOR_MASK_GENERATION_MAPPING.items()     ) if TF_MODEL_FOR_MASK_GENERATION_MAPPING else [])     )




      def  __UpperCamelCase							(  self ,   lowerCamelCase ,   lowerCamelCase ,   lowerCamelCase      )							->Optional[Any]:



         '''simple docstring'''
         __a				     =    MaskGenerationPipeline(model=UpperCamelCase__ ,   image_processor=UpperCamelCase__      )
         return image_segmenter, [
             "./tests/fixtures/tests_samples/COCO/000000039769.png",
             "./tests/fixtures/tests_samples/COCO/000000039769.png",
         ]




      def  __UpperCamelCase							(  self ,   lowerCamelCase ,   lowerCamelCase      )							->List[Any]:



         '''simple docstring'''
         pass




      @require_tf
      @unittest.skip('Image segmentation not implemented in TF'      )
      def  __UpperCamelCase							(  self      )							->int:



         '''simple docstring'''
         pass




      @slow
      @require_torch
      def  __UpperCamelCase							(  self      )							->int:



         '''simple docstring'''
         __a				     =    pipeline('mask-generation' ,   model='facebook/sam-vit-huge'      )

         __a				     =    image_segmenter('http://images.cocodataset.org/val2017/000000039769.jpg' ,   points_per_batch=256      )

         # Shortening by hashing
         __a				     =    []
         for i, o in enumerate(outputs['masks']      ):
            new_outupt += [{"mask": mask_to_test_readable(UpperCamelCase__      ), "scores": outputs["scores"][i]}]

         # fmt: off
         self.assertEqual(
             nested_simplify(UpperCamelCase__ ,   decimals=4      ) ,   [
                 {'mask': {'hash': '115ad19f5f', 'shape': (480, 640)}, 'scores': 1.0444},
                 {'mask': {'hash': '6affa964c6', 'shape': (480, 640)}, 'scores': 1.021},
                 {'mask': {'hash': 'dfe28a0388', 'shape': (480, 640)}, 'scores': 1.0167},
                 {'mask': {'hash': 'c0a5f4a318', 'shape': (480, 640)}, 'scores': 1.0132},
                 {'mask': {'hash': 'fe8065c197', 'shape': (480, 640)}, 'scores': 1.0053},
                 {'mask': {'hash': 'e2d0b7a0b7', 'shape': (480, 640)}, 'scores': 0.9967},
                 {'mask': {'hash': '453c7844bd', 'shape': (480, 640)}, 'scores': 0.993},
                 {'mask': {'hash': '3d44f2926d', 'shape': (480, 640)}, 'scores': 0.9909},
                 {'mask': {'hash': '64033ddc3f', 'shape': (480, 640)}, 'scores': 0.9879},
                 {'mask': {'hash': '801064ff79', 'shape': (480, 640)}, 'scores': 0.9834},
                 {'mask': {'hash': '6172f276ef', 'shape': (480, 640)}, 'scores': 0.9716},
                 {'mask': {'hash': 'b49e60e084', 'shape': (480, 640)}, 'scores': 0.9612},
                 {'mask': {'hash': 'a811e775fd', 'shape': (480, 640)}, 'scores': 0.9599},
                 {'mask': {'hash': 'a6a8ebcf4b', 'shape': (480, 640)}, 'scores': 0.9552},
                 {'mask': {'hash': '9d8257e080', 'shape': (480, 640)}, 'scores': 0.9532},
                 {'mask': {'hash': '32de6454a8', 'shape': (480, 640)}, 'scores': 0.9516},
                 {'mask': {'hash': 'af3d4af2c8', 'shape': (480, 640)}, 'scores': 0.9499},
                 {'mask': {'hash': '3c6db475fb', 'shape': (480, 640)}, 'scores': 0.9483},
                 {'mask': {'hash': 'c290813fb9', 'shape': (480, 640)}, 'scores': 0.9464},
                 {'mask': {'hash': 'b6f0b8f606', 'shape': (480, 640)}, 'scores': 0.943},
                 {'mask': {'hash': '92ce16bfdf', 'shape': (480, 640)}, 'scores': 0.943},
                 {'mask': {'hash': 'c749b25868', 'shape': (480, 640)}, 'scores': 0.9408},
                 {'mask': {'hash': 'efb6cab859', 'shape': (480, 640)}, 'scores': 0.9335},
                 {'mask': {'hash': '1ff2eafb30', 'shape': (480, 640)}, 'scores': 0.9326},
                 {'mask': {'hash': '788b798e24', 'shape': (480, 640)}, 'scores': 0.9262},
                 {'mask': {'hash': 'abea804f0e', 'shape': (480, 640)}, 'scores': 0.8999},
                 {'mask': {'hash': '7b9e8ddb73', 'shape': (480, 640)}, 'scores': 0.8986},
                 {'mask': {'hash': 'cd24047c8a', 'shape': (480, 640)}, 'scores': 0.8984},
                 {'mask': {'hash': '6943e6bcbd', 'shape': (480, 640)}, 'scores': 0.8873},
                 {'mask': {'hash': 'b5f47c9191', 'shape': (480, 640)}, 'scores': 0.8871}
             ] ,   )
         # fmt: on






      @require_torch
      @slow
      def  __UpperCamelCase							(  self      )							->Union[str, Any]:



         '''simple docstring'''
         __a				     =    'facebook/sam-vit-huge'
         __a				     =    pipeline('mask-generation' ,   model=UpperCamelCase__      )

         __a				     =    image_segmenter(
             'http://images.cocodataset.org/val2017/000000039769.jpg' ,   pred_iou_thresh=1 ,   points_per_batch=256      )

         # Shortening by hashing
         __a				     =    []
         for i, o in enumerate(outputs['masks']      ):
            new_outupt += [{"mask": mask_to_test_readable(UpperCamelCase__      ), "scores": outputs["scores"][i]}]

         self.assertEqual(
             nested_simplify(UpperCamelCase__ ,   decimals=4      ) ,   [
                 {'mask': {'hash': '115ad19f5f', 'shape': (480, 640)}, 'scores': 1.0444},
                 {'mask': {'hash': '6affa964c6', 'shape': (480, 640)}, 'scores': 1.0210},
                 {'mask': {'hash': 'dfe28a0388', 'shape': (480, 640)}, 'scores': 1.0167},
                 {'mask': {'hash': 'c0a5f4a318', 'shape': (480, 640)}, 'scores': 1.0132},
                 {'mask': {'hash': 'fe8065c197', 'shape': (480, 640)}, 'scores': 1.0053},
             ] ,   )







'''simple docstring'''



def    __UpperCAmelCase	(				SCREAMING_SNAKE_CASE__:	int,					SCREAMING_SNAKE_CASE__:	bool = False    )  ->			bool:

   """simple docstring"""
   if n == 2:
      return True
   if not n % 2 or n < 2:
      return False
   if n > 5 and n % 10 not in (1, 3, 7, 9):  # can quickly check last digit
      return False
   if n > 3317044064679887385961981 and not allow_probable:
      raise ValueError(
          'Warning: upper bound of deterministic test is exceeded. '
          'Pass allow_probable=True to allow probabilistic test. '
          'A return value of True indicates a probable prime.'    )
   # array bounds provided by analysis
   __a				     =    [
       2047,
       1373653,
       25326001,
       3215031751,
       2152302898747,
       3474749660383,
       341550071728321,
       1,
       3825123056546413051,
       1,
       1,
       318665857834031151167461,
       3317044064679887385961981,
   ]

   __a				     =    [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41]
   for idx, _p in enumerate(SCREAMING_SNAKE_CASE__,					1    ):
      if n < _p:
         # then we have our last prime to check
         __a				     =    primes[:idx]
         break
   __a     ,			__a				     =    n - 1, 0
   # break up n -1 into a power of 2 (s) and
   # remaining odd component
   # essentially, solve for d * 2 ** s == n - 1
   while d % 2 == 0:
      d //= 2
      s += 1
   for prime in plist:
      __a				     =    False
      for r in range(SCREAMING_SNAKE_CASE__    ):
         __a				     =    pow(SCREAMING_SNAKE_CASE__,					d * 2**r,					SCREAMING_SNAKE_CASE__    )
         # see article for analysis explanation for m
         if (r == 0 and m == 1) or ((m + 1) % n == 0):
            __a				     =    True
            # this loop will not determine compositeness
            break
      if pr:
         continue
      # if pr is False, then the above loop never evaluated to true,
      # and the n MUST be composite
      return False
   return True



def    __UpperCAmelCase	(				)  ->			None:

   """simple docstring"""
   assert not miller_rabin(561    )
   assert miller_rabin(563    )
   # 2047

   assert not miller_rabin(838201    )
   assert miller_rabin(838207    )
   # 1_373_653

   assert not miller_rabin(17316001    )
   assert miller_rabin(17316017    )
   # 25_326_001

   assert not miller_rabin(3078386641    )
   assert miller_rabin(3078386653    )
   # 3_215_031_751

   assert not miller_rabin(1713045574801    )
   assert miller_rabin(1713045574819    )
   # 2_152_302_898_747

   assert not miller_rabin(2779799728307    )
   assert miller_rabin(2779799728327    )
   # 3_474_749_660_383

   assert not miller_rabin(113850023909441    )
   assert miller_rabin(113850023909527    )
   # 341_550_071_728_321

   assert not miller_rabin(1275041018848804351    )
   assert miller_rabin(1275041018848804391    )
   # 3_825_123_056_546_413_051

   assert not miller_rabin(79666464458507787791867    )
   assert miller_rabin(79666464458507787791951    )
   # 318_665_857_834_031_151_167_461

   assert not miller_rabin(552840677446647897660333    )
   assert miller_rabin(552840677446647897660359    )
   # 3_317_044_064_679_887_385_961_981
   # upper limit for probabilistic test


if __name__ == "__main__":
 test_miller_rabin()