





import hashlib
import unittest

from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_timm,
    require_torch,
    require_vision,
    slow,
)

from .test_pipelines_common import ANY


if is_torch_available():
  import torch

if is_vision_available():
  from PIL import Image
else:






  class     lowercase__       :

     '''simple docstring'''


     @staticmethod
     def       UpperCamelCase__  (    *__magic_name__,		**__magic_name__							) ->      Optional[int]:






         """simple docstring"""
         pass




def 		lowerCAmelCase_    (  __UpperCAmelCase:			Tuple      )      ->	Optional[Any]:
    UpperCamelCase__							:				Optional[Any]          =      hashlib.mda(image.tobytes()      )
    return m.hexdigest()






@is_pipeline_test
@require_vision
@require_timm
@require_torch
class     lowercase__       (	unittest.TestCase				):

   '''simple docstring'''


   a						:							List[str]   		=		MODEL_FOR_DEPTH_ESTIMATION_MAPPING




   def       UpperCamelCase__  (    self,		__magic_name__,		__magic_name__,		__magic_name__							) ->      Optional[Any]:






       """simple docstring"""
       UpperCamelCase__							:				int          =      DepthEstimationPipeline(model=__lowerCAmelCase,		image_processor=__lowerCAmelCase							)
       return depth_estimator, [
           "./tests/fixtures/tests_samples/COCO/000000039769.png",
           "./tests/fixtures/tests_samples/COCO/000000039769.png",
       ]




   def       UpperCamelCase__  (    self,		__magic_name__,		__magic_name__							) ->      Any:






       """simple docstring"""
       UpperCamelCase__							:				str          =      depth_estimator('''./tests/fixtures/tests_samples/COCO/000000039769.png'''							)
       self.assertEqual({'''predicted_depth''': ANY(torch.Tensor							), '''depth''': ANY(Image.Image							)},		__lowerCAmelCase							)
       import datasets

       UpperCamelCase__							:				Union[str, Any]          =      datasets.load_dataset('''hf-internal-testing/fixtures_image_utils''',		'''image''',		split='''test'''							)
       UpperCamelCase__							:				Any          =      depth_estimator(
           [
               Image.open('''./tests/fixtures/tests_samples/COCO/000000039769.png'''							),
               '''http://images.cocodataset.org/val2017/000000039769.jpg''',
               # RGBA
               dataset[0]['''file'''],
               # LA
               dataset[1]['''file'''],
               # L
               dataset[2]['''file'''],
           ]							)
       self.assertEqual(
           [
               {'''predicted_depth''': ANY(torch.Tensor							), '''depth''': ANY(Image.Image							)},
               {'''predicted_depth''': ANY(torch.Tensor							), '''depth''': ANY(Image.Image							)},
               {'''predicted_depth''': ANY(torch.Tensor							), '''depth''': ANY(Image.Image							)},
               {'''predicted_depth''': ANY(torch.Tensor							), '''depth''': ANY(Image.Image							)},
               {'''predicted_depth''': ANY(torch.Tensor							), '''depth''': ANY(Image.Image							)},
           ],		__lowerCAmelCase,		)




   @require_tf
   @unittest.skip('''Depth estimation is not implemented in TF'''							)
   def       UpperCamelCase__  (    self							) ->      Dict:






       """simple docstring"""
       pass




   @slow
   @require_torch
   def       UpperCamelCase__  (    self							) ->      str:






       """simple docstring"""
       UpperCamelCase__							:				Any          =      '''Intel/dpt-large'''
       UpperCamelCase__							:				List[Any]          =      pipeline('''depth-estimation''',		model=__lowerCAmelCase							)
       UpperCamelCase__							:				int          =      depth_estimator('''http://images.cocodataset.org/val2017/000000039769.jpg'''							)
       UpperCamelCase__							:				str          =      hashimage(outputs['''depth''']							)

       # This seems flaky.
       # self.assertEqual(outputs["depth"], "1a39394e282e9f3b0741a90b9f108977")
       self.assertEqual(nested_simplify(outputs['''predicted_depth'''].max().item()							),		29.304							)
       self.assertEqual(nested_simplify(outputs['''predicted_depth'''].min().item()							),		2.662							)




   @require_torch
   def       UpperCamelCase__  (    self							) ->      Tuple:






       """simple docstring"""
       # This is highly irregular to have no small tests.
       self.skipTest('''There is not hf-internal-testing tiny model for either GLPN nor DPT'''							)


'''simple docstring'''

import unittest

from knapsack import knapsack as k



class 			UpperCAmelCase  (						unittest.TestCase					):





       '''simple docstring'''



       def _lowerCAmelCase(						self )  ->  Tuple:
        lowercase__				:    Optional[Any]  =					0
        lowercase__				:    Any  =					[0]
        lowercase__				:    List[Any]  =					[0]
        lowercase__				:    Optional[Any]  =					len(__lowerCAmelCase )
        self.assertEqual(k.knapsack(__lowerCAmelCase	,   __lowerCAmelCase	,   __lowerCAmelCase	,   __lowerCAmelCase )	,   0 )

        lowercase__				:    List[str]  =					[60]
        lowercase__				:    List[str]  =					[10]
        lowercase__				:    List[str]  =					len(__lowerCAmelCase )
        self.assertEqual(k.knapsack(__lowerCAmelCase	,   __lowerCAmelCase	,   __lowerCAmelCase	,   __lowerCAmelCase )	,   0 )

       def _lowerCAmelCase(						self )  ->  Optional[Any]:
        lowercase__				:    Optional[Any]  =					3
        lowercase__				:    List[Any]  =					[1, 2, 3]
        lowercase__				:    Union[str, Any]  =					[3, 2, 1]
        lowercase__				:    List[Any]  =					len(__lowerCAmelCase )
        self.assertEqual(k.knapsack(__lowerCAmelCase	,   __lowerCAmelCase	,   __lowerCAmelCase	,   __lowerCAmelCase )	,   5 )


       def _lowerCAmelCase(						self )  ->  Optional[Any]:
        lowercase__				:    int  =					50
        lowercase__				:    Any  =					[60, 100, 120]
        lowercase__				:    int  =					[10, 20, 30]
        lowercase__				:    Optional[Any]  =					len(__lowerCAmelCase )
        self.assertEqual(k.knapsack(__lowerCAmelCase	,   __lowerCAmelCase	,   __lowerCAmelCase	,   __lowerCAmelCase )	,   220 )


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

