


"""simple docstring"""

import unittest

import numpy as np
import torch

from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()





class    lowerCamelCase__						(		unittest.TestCase    ):
      @property
      def SCREAMING_SNAKE_CASE_	(		self	:	Tuple							):






       '''simple docstring'''


       torch.manual_seed(0							)
       __lowercase									=	UNetaDModel(
           block_out_channels=(3_2, 6_4)      ,       layers_per_block=2      ,       sample_size=3_2      ,       in_channels=3      ,       out_channels=3      ,       down_block_types=("""DownBlock2D""", """AttnDownBlock2D""")      ,       up_block_types=("""AttnUpBlock2D""", """UpBlock2D""")      ,       )
       return model






      def SCREAMING_SNAKE_CASE_	(		self	:	Dict							):






       '''simple docstring'''


       __lowercase									=	self.dummy_uncond_unet
       __lowercase									=	PNDMScheduler()

       __lowercase									=	PNDMPipeline(unet=A_      ,       scheduler=A_							)
       pndm.to(A_							)
       pndm.set_progress_bar_config(disable=A_							)

       __lowercase									=	torch.manual_seed(0							)
       __lowercase									=	pndm(generator=A_      ,       num_inference_steps=2_0      ,       output_type="""numpy"""							).images

       __lowercase									=	torch.manual_seed(0							)
       __lowercase									=	pndm(generator=A_      ,       num_inference_steps=2_0      ,       output_type="""numpy"""      ,       return_dict=A_							)[0]

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

       assert image.shape == (1, 3_2, 3_2, 3)
       __lowercase									=	np.array([1.0, 1.0, 0.0, 1.0, 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    lowerCamelCase__						(		unittest.TestCase    ):
      def SCREAMING_SNAKE_CASE_	(		self	:	List[str]							):






       '''simple docstring'''


       __lowercase									=	"""google/ddpm-cifar10-32"""

       __lowercase									=	UNetaDModel.from_pretrained(A_							)
       __lowercase									=	PNDMScheduler()

       __lowercase									=	PNDMPipeline(unet=A_      ,       scheduler=A_							)
       pndm.to(A_							)
       pndm.set_progress_bar_config(disable=A_							)
       __lowercase									=	torch.manual_seed(0							)
       __lowercase									=	pndm(generator=A_      ,       output_type="""numpy"""							).images

       __lowercase									=	image[0, -3:, -3:, -1]

       assert image.shape == (1, 3_2, 3_2, 3)
       __lowercase									=	np.array([0.15_64, 0.1_46_45, 0.14_06, 0.1_47_15, 0.1_24_25, 0.1_40_45, 0.1_31_15, 0.1_21_75, 0.1_25]							)

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




"""simple docstring"""

def lowerCAmelCase_      (				UpperCamelCase__	: str				,   UpperCamelCase__	: str ):






 """simple docstring"""







 assert x is not None
 assert y is not None

 __lowercase									=	len(UpperCamelCase__ )
 __lowercase									=	len(UpperCamelCase__ )

 # declaring the array for storing the dp values
 __lowercase									=	[[0] * (n + 1) for _ in range(m + 1 )]  # noqa: E741

 for i in range(1				,   m + 1 ):
  for j in range(1				,   n + 1 ):
   __lowercase									=	1 if x[i - 1] == y[j - 1] else 0

   __lowercase									=	max(l[i - 1][j]				,   l[i][j - 1]				,   l[i - 1][j - 1] + match )

 __lowercase									=	""""""
 __lowercase							,		__lowercase									=	m, n
 while i > 0 and j > 0:
  __lowercase									=	1 if x[i - 1] == y[j - 1] else 0

  if l[i][j] == l[i - 1][j - 1] + match:
   if match == 1:
    __lowercase									=	x[i - 1] + seq
   i -= 1
   j -= 1
  elif l[i][j] == l[i - 1][j]:
   i -= 1
  else:
   j -= 1

 return l[m][n], seq


if __name__ == "__main__":
       UpperCAmelCase__  							="AGGTAB"
       UpperCAmelCase__  							="GXTXAYB"
       UpperCAmelCase__  							=4
       UpperCAmelCase__  							="GTAB"

       UpperCAmelCase__							,      UpperCAmelCase__  							=longest_common_subsequence(a, b)
       print("len =", ln, ", sub-sequence =", subseq)
       import doctest

       doctest.testmod()
