



"""simple docstring"""






def 					snake_case__       (		__lowerCamelCase    :   int     ):
			"""simple docstring"""
			lowerCamelCase__		:		str		     =generate_pascal_triangle(__lowerCamelCase     )
			for row_idx in range(__lowerCamelCase     ):
						# Print left spaces
						for _ in range(num_rows - row_idx - 1     ):
									print(end=''' '''     )
						# Print row values
						for col_idx in range(row_idx + 1     ):
									if col_idx != row_idx:
												print(triangle[row_idx][col_idx]							,		end=''' '''     )
									else:
												print(triangle[row_idx][col_idx]							,		end=''''''     )
						print()






def 					snake_case__       (		__lowerCamelCase    :   int     ):
			"""simple docstring"""

			if not isinstance(__lowerCamelCase							,		__lowerCamelCase     ):
						raise TypeError('''The input value of \'num_rows\' should be \'int\''''     )

			if num_rows == 0:
						return []
			elif num_rows < 0:
						raise ValueError(
						    '''The input value of \'num_rows\' should be greater than or equal to 0'''     )

			lowerCamelCase__		:		list[list[int]]		     =[]
			for current_row_idx in range(__lowerCamelCase     ):
						lowerCamelCase__		:		Tuple		     =populate_current_row(__lowerCamelCase							,		__lowerCamelCase     )
						triangle.append(__lowerCamelCase     )
			return triangle






def 					snake_case__       (		__lowerCamelCase    :   list[list[int]]							,		__lowerCamelCase    :   int     ):
			"""simple docstring"""
			lowerCamelCase__		:		Tuple		     =[-1] * (current_row_idx + 1)
			# first and last elements of current row are equal to 1
			lowerCamelCase__     ,       lowerCamelCase__		:		List[str]		     =1, 1
			for current_col_idx in range(1							,		__lowerCamelCase     ):
						calculate_current_element(
						    __lowerCamelCase							,		__lowerCamelCase							,		__lowerCamelCase							,		__lowerCamelCase     )
			return current_row






def 					snake_case__       (		__lowerCamelCase    :   list[list[int]]							,		__lowerCamelCase    :   list[int]							,		__lowerCamelCase    :   int							,		__lowerCamelCase    :   int							,		):
			"""simple docstring"""
			lowerCamelCase__		:		int		     =triangle[current_row_idx - 1][current_col_idx - 1]
			lowerCamelCase__		:		Optional[Any]		     =triangle[current_row_idx - 1][current_col_idx]
			lowerCamelCase__		:		Optional[Any]		     =above_to_left_elt + above_to_right_elt






def 					snake_case__       (		__lowerCamelCase    :   int     ):
			"""simple docstring"""

			if not isinstance(__lowerCamelCase							,		__lowerCamelCase     ):
						raise TypeError('''The input value of \'num_rows\' should be \'int\''''     )

			if num_rows == 0:
						return []
			elif num_rows < 0:
						raise ValueError(
						    '''The input value of \'num_rows\' should be greater than or equal to 0'''     )

			lowerCamelCase__		:		list[list[int]]		     =[[1]]

			for row_index in range(1							,		__lowerCamelCase     ):
						lowerCamelCase__		:		List[Any]		     =[0] + result[-1] + [0]
						lowerCamelCase__		:		str		     =row_index + 1
						# Calculate the number of distinct elements in a row
						lowerCamelCase__		:		int		     =sum(divmod(__lowerCamelCase							,		2     )     )
						lowerCamelCase__		:		str		     =[
						    temp_row[i - 1] + temp_row[i] for i in range(1							,		distinct_elements + 1     )
						]
						lowerCamelCase__		:		Optional[Any]		     =row_first_half[: (row_index + 1) // 2]
						row_second_half.reverse()
						lowerCamelCase__		:		Union[str, Any]		     =row_first_half + row_second_half
						result.append(__lowerCamelCase     )

			return result






def 					snake_case__       (		):
			"""simple docstring"""
			from collections.abc import Callable
			from timeit import timeit

			def benchmark_a_function(__lowerCamelCase    :   Callable							,		__lowerCamelCase    :   int     ) -> None:
						lowerCamelCase__		:		List[str]		     =f'''{func.__name__}({value})'''
						lowerCamelCase__		:		Optional[Any]		     =timeit(f'''__main__.{call}'''							,		setup='''import __main__'''     )
						# print(f"{call:38} = {func(value)} -- {timing:.4f} seconds")
						print(f'''{call:38} -- {timing:.4f} seconds'''     )

			for value in range(15     ):  # (1, 7, 14):
						for func in (generate_pascal_triangle, generate_pascal_triangle_optimized):
									benchmark_a_function(__lowerCamelCase							,		__lowerCamelCase     )
						print()


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		benchmark()









"""simple docstring"""






import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device


_lowercase			:			Tuple										=						False

class 	__SCREAMING_SNAKE_CASE     (				unittest.TestCase       ):


					'''simple docstring'''





					pass





@slow
@require_torch_gpu
class 	__SCREAMING_SNAKE_CASE     (				unittest.TestCase       ):


					'''simple docstring'''





					def 		snake_case	(	self							:  List[Any]					)-> Dict:
								lowerCamelCase__		:		str		     =VersatileDiffusionImageVariationPipeline.from_pretrained('''shi-labs/versatile-diffusion'''					)
								pipe.to(lowerCamelCase					)
								pipe.set_progress_bar_config(disable=lowerCamelCase					)

								lowerCamelCase__		:		int		     =load_image(
								    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'''					)
								lowerCamelCase__		:		Dict		     =torch.manual_seed(0					)
								lowerCamelCase__		:		str		     =pipe(
								    image=lowerCamelCase,  generator=lowerCamelCase,  guidance_scale=7.5,  num_inference_steps=50,  output_type='''numpy''',  ).images

								lowerCamelCase__		:		Dict		     =image[0, 253:256, 253:256, -1]

								assert image.shape == (1, 512, 512, 3)
								lowerCamelCase__		:		List[Any]		     =np.array([0.0_441, 0.0_469, 0.0_507, 0.0_575, 0.0_632, 0.0_650, 0.0_865, 0.0_909, 0.0_945]					)

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




