

"""simple docstring"""




import unittest

import numpy as np
import torch

from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()


class 		_A       (			unittest.TestCase					):





      @property
      def 					_lowerCamelCase  (  self		)   ->					str:
         torch.manual_seed(0		)
         lowerCamelCase__						=			UNetaDModel(
             block_out_channels=(32, 64)    ,						layers_per_block=2    ,						sample_size=32    ,						in_channels=3    ,						out_channels=3    ,						down_block_types=("DownBlock2D", "AttnDownBlock2D")    ,						up_block_types=("AttnUpBlock2D", "UpBlock2D")    ,						)
         return model





      def 					_lowerCamelCase  (  self		)   ->					Optional[Any]:
         lowerCamelCase__						=			self.dummy_uncond_unet
         lowerCamelCase__						=			KarrasVeScheduler()

         lowerCamelCase__						=			KarrasVePipeline(unet=SCREAMING_SNAKE_CASE__    ,						scheduler=SCREAMING_SNAKE_CASE__		)
         pipe.to(SCREAMING_SNAKE_CASE__		)
         pipe.set_progress_bar_config(disable=SCREAMING_SNAKE_CASE__		)

         lowerCamelCase__						=			torch.manual_seed(0		)
         lowerCamelCase__						=			pipe(num_inference_steps=2    ,						generator=SCREAMING_SNAKE_CASE__    ,						output_type="numpy"		).images

         lowerCamelCase__						=			torch.manual_seed(0		)
         lowerCamelCase__						=			pipe(num_inference_steps=2    ,						generator=SCREAMING_SNAKE_CASE__    ,						output_type="numpy"    ,						return_dict=SCREAMING_SNAKE_CASE__		)[0]

         lowerCamelCase__						=			image[0, -3:, -3:, -1]
         lowerCamelCase__						=			image_from_tuple[0, -3:, -3:, -1]

         assert image.shape == (1, 32, 32, 3)
         lowerCamelCase__						=			np.array([0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]		)

         assert np.abs(image_slice.flatten() - expected_slice		).max() < 1e-2
         assert np.abs(image_from_tuple_slice.flatten() - expected_slice		).max() < 1e-2






@slow
@require_torch
class 		_A       (			unittest.TestCase					):





      def 					_lowerCamelCase  (  self		)   ->					Tuple:
         lowerCamelCase__						=			"google/ncsnpp-celebahq-256"
         lowerCamelCase__						=			UNetaDModel.from_pretrained(SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			KarrasVeScheduler()

         lowerCamelCase__						=			KarrasVePipeline(unet=SCREAMING_SNAKE_CASE__    ,						scheduler=SCREAMING_SNAKE_CASE__		)
         pipe.to(SCREAMING_SNAKE_CASE__		)
         pipe.set_progress_bar_config(disable=SCREAMING_SNAKE_CASE__		)

         lowerCamelCase__						=			torch.manual_seed(0		)
         lowerCamelCase__						=			pipe(num_inference_steps=20    ,						generator=SCREAMING_SNAKE_CASE__    ,						output_type="numpy"		).images

         lowerCamelCase__						=			image[0, -3:, -3:, -1]
         assert image.shape == (1, 256, 256, 3)
         lowerCamelCase__						=			np.array([0.5_78, 0.58_11, 0.59_24, 0.58_09, 0.5_87, 0.58_86, 0.58_61, 0.58_02, 0.5_86]		)

         assert np.abs(image_slice.flatten() - expected_slice		).max() < 1e-2







"""simple docstring"""




from __future__ import annotations

import bisect



def 	UpperCAmelCase__   (				A__	,    A__	,    A__ = 0	,    A__ = -1   )      ->      int:




   """simple docstring"""
   if hi < 0:
      lowerCamelCase__						=			len(A__   )

   while lo < hi:
      lowerCamelCase__						=			lo + (hi - lo) // 2
      if sorted_collection[mid] < item:
         lowerCamelCase__						=			mid + 1
      else:
         lowerCamelCase__						=			mid

   return lo



def 	UpperCAmelCase__   (				A__	,    A__	,    A__ = 0	,    A__ = -1   )      ->      int:




   """simple docstring"""
   if hi < 0:
      lowerCamelCase__						=			len(A__   )

   while lo < hi:
      lowerCamelCase__						=			lo + (hi - lo) // 2
      if sorted_collection[mid] <= item:
         lowerCamelCase__						=			mid + 1
      else:
         lowerCamelCase__						=			mid

   return lo



def 	UpperCAmelCase__   (				A__	,    A__	,    A__ = 0	,    A__ = -1   )      ->      None:




   """simple docstring"""
   sorted_collection.insert(bisect_left(A__	,    A__	,    A__	,    A__   )	,    A__   )



def 	UpperCAmelCase__   (				A__	,    A__	,    A__ = 0	,    A__ = -1   )      ->      None:




   """simple docstring"""
   sorted_collection.insert(bisect_right(A__	,    A__	,    A__	,    A__   )	,    A__   )



def 	UpperCAmelCase__   (				A__	,    A__   )      ->      int | None:




   """simple docstring"""
   lowerCamelCase__						=			0
   lowerCamelCase__						=			len(A__   ) - 1

   while left <= right:
      lowerCamelCase__						=			left + (right - left) // 2
      lowerCamelCase__						=			sorted_collection[midpoint]
      if current_item == item:
         return midpoint
      elif item < current_item:
         lowerCamelCase__						=			midpoint - 1
      else:
         lowerCamelCase__						=			midpoint + 1
   return None



def 	UpperCAmelCase__   (				A__	,    A__   )      ->      int | None:




   """simple docstring"""
   lowerCamelCase__						=			bisect.bisect_left(A__	,    A__   )
   if index != len(A__   ) and sorted_collection[index] == item:
      return index
   return None



def 	UpperCAmelCase__   (				A__	,    A__	,    A__	,    A__   )      ->      int | None:




   """simple docstring"""
   if right < left:
      return None

   lowerCamelCase__						=			left + (right - left) // 2

   if sorted_collection[midpoint] == item:
      return midpoint
   elif sorted_collection[midpoint] > item:
      return binary_search_by_recursion(A__	,    A__	,    A__	,    midpoint - 1   )
   else:
      return binary_search_by_recursion(A__	,    A__	,    midpoint + 1	,    A__   )


if __name__ == "__main__":
     SCREAMING_SNAKE_CASE_     :			Optional[Any]	  =			input('''Enter numbers separated by comma:\n''').strip()
     SCREAMING_SNAKE_CASE_     :			int	  =			sorted(int(item) for item in user_input.split(''','''))
     SCREAMING_SNAKE_CASE_     :			Optional[Any]	  =			int(input('''Enter a single number to be found in the list:\n'''))
     SCREAMING_SNAKE_CASE_     :			Dict	  =			binary_search(collection, target)
     if result is None:
          print(F'''{target} was not found in {collection}.''')
     else:
          print(F'''{target} was found at position {result} in {collection}.''')




