





import unittest

import numpy as np
import torch

from diffusers import DDPMPipeline, DDPMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device


enable_full_determinism()

class 			A_ (unittest.TestCase    ):
	@property
	def   _lowercase       (					self	):






				'''simple docstring'''







				torch.manual_seed(0	)
				UpperCAmelCase     	=       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   _lowercase       (					self	):






				'''simple docstring'''







				UpperCAmelCase     	=       '''cpu'''
				UpperCAmelCase     	=       self.dummy_uncond_unet
				UpperCAmelCase     	=       DDPMScheduler()

				UpperCAmelCase     	=       DDPMPipeline(unet=_A							,      scheduler=_A	)
				ddpm.to(_A	)
				ddpm.set_progress_bar_config(disable=_A	)

				UpperCAmelCase     	=       torch.Generator(device=_A	).manual_seed(0	)
				UpperCAmelCase     	=       ddpm(generator=_A							,      num_inference_steps=2							,      output_type='''numpy'''	).images

				UpperCAmelCase     	=       torch.Generator(device=_A	).manual_seed(0	)
				UpperCAmelCase     	=       ddpm(generator=_A							,      num_inference_steps=2							,      output_type='''numpy'''							,      return_dict=_A	)[0]

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

				assert image.shape == (1, 3_2, 3_2, 3)
				UpperCAmelCase     	=       np.array(
				    [9.956E-01, 5.785E-01, 4.675E-01, 9.930E-01, 0.0, 1.0_00, 1.199E-03, 2.648E-04, 5.101E-04]	)

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







	def   _lowercase       (					self	):






				'''simple docstring'''







				UpperCAmelCase     	=       self.dummy_uncond_unet
				UpperCAmelCase     	=       DDPMScheduler(prediction_type='''sample'''	)

				UpperCAmelCase     	=       DDPMPipeline(unet=_A							,      scheduler=_A	)
				ddpm.to(_A	)
				ddpm.set_progress_bar_config(disable=_A	)

				UpperCAmelCase     	=       torch.manual_seed(0	)
				UpperCAmelCase     	=       ddpm(generator=_A							,      num_inference_steps=2							,      output_type='''numpy'''	).images

				UpperCAmelCase     	=       torch.manual_seed(0	)
				UpperCAmelCase     	=       ddpm(generator=_A							,      num_inference_steps=2							,      output_type='''numpy'''	)[0]

				UpperCAmelCase     	=       image[0, -3:, -3:, -1]
				UpperCAmelCase     	=       image_eps[0, -3:, -3:, -1]

				assert image.shape == (1, 3_2, 3_2, 3)
				UpperCAmelCase     	=       1E-2 if torch_device != '''mps''' else 3E-2
				assert np.abs(image_slice.flatten() - image_eps_slice.flatten()	).max() < tolerance

@slow
@require_torch_gpu
class 			A_ (unittest.TestCase    ):
	def   _lowercase       (					self	):






				'''simple docstring'''







				UpperCAmelCase     	=       '''google/ddpm-cifar10-32'''

				UpperCAmelCase     	=       UNetaDModel.from_pretrained(_A	)
				UpperCAmelCase     	=       DDPMScheduler.from_pretrained(_A	)

				UpperCAmelCase     	=       DDPMPipeline(unet=_A							,      scheduler=_A	)
				ddpm.to(_A	)
				ddpm.set_progress_bar_config(disable=_A	)

				UpperCAmelCase     	=       torch.manual_seed(0	)
				UpperCAmelCase     	=       ddpm(generator=_A							,      output_type='''numpy'''	).images

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

				assert image.shape == (1, 3_2, 3_2, 3)
				UpperCAmelCase     	=       np.array([0.42_00, 0.35_88, 0.19_39, 0.38_47, 0.33_82, 0.26_47, 0.41_55, 0.35_82, 0.33_85]	)
				assert np.abs(image_slice.flatten() - expected_slice	).max() < 1E-2










from math import floor, sqrt





def 		__SCREAMING_SNAKE_CASE						(       UpperCamelCase__				)						->       int:







			'''simple docstring'''

			UpperCAmelCase     	=       0.0
			UpperCAmelCase     	=       1.0
			UpperCAmelCase     	=       int(sqrt(UpperCamelCase__				)				)
			UpperCAmelCase     	=       root
			UpperCAmelCase     	=       0
			while integer_part != 2 * root:
						UpperCAmelCase     	=       denominator * integer_part - numerator
						UpperCAmelCase     	=       (n - numerator**2) / denominator
						UpperCAmelCase     	=       int((root + numerator) / denominator				)
						period += 1
			return period





def 		__SCREAMING_SNAKE_CASE						(       UpperCamelCase__ = 1_0000				)						->       int:







			'''simple docstring'''

			UpperCAmelCase     	=       0
			for i in range(2    ,    n + 1				):
						UpperCAmelCase     	=       sqrt(UpperCamelCase__				)
						if sr - floor(UpperCamelCase__				) != 0 and continuous_fraction_period(UpperCamelCase__				) % 2 == 1:
									count_odd_periods += 1
			return count_odd_periods


if __name__ == "__main__":
				print(F'{solution(int(input().strip()))}')



