



import random
import unittest

import torch

from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import (
    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS,
    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin






@skip_mps
class    SCREAMING_SNAKE_CASE			(							lowerCamelCase__			,      lowerCamelCase__			,      unittest.TestCase					):
							__lowerCamelCase	:	Dict    =IFInpaintingSuperResolutionPipeline
							__lowerCamelCase	:	int    =TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {'width', 'height'}
							__lowerCamelCase	:	Dict    =TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS.union({'original_image'}					)
							__lowerCamelCase	:	str    =PipelineTesterMixin.required_optional_params - {'latents'}





							def 						UpperCamelCase_					(   self		:		Optional[int]	):

											'''simple docstring'''
											return self._get_superresolution_dummy_components()





							def 						UpperCamelCase_					(   self		:		Tuple      ,				__lowercase		:		Optional[Any]      ,				__lowercase		:		Union[str, Any]=0	):

											'''simple docstring'''
											if str(__lowercase	).startswith("""mps"""	):
															__a       =		torch.manual_seed(__lowercase	)
											else:
															__a       =		torch.Generator(device=__lowercase	).manual_seed(__lowercase	)

											__a       =		floats_tensor((1, 3, 16, 16)      ,				rng=random.Random(__lowercase	)	).to(__lowercase	)
											__a       =		floats_tensor((1, 3, 32, 32)      ,				rng=random.Random(__lowercase	)	).to(__lowercase	)
											__a       =		floats_tensor((1, 3, 32, 32)      ,				rng=random.Random(__lowercase	)	).to(__lowercase	)

											__a       =		{
											    """prompt""": """A painting of a squirrel eating a burger""",
											    """image""": image,
											    """original_image""": original_image,
											    """mask_image""": mask_image,
											    """generator""": generator,
											    """num_inference_steps""": 2,
											    """output_type""": """numpy""",
											}

											return inputs





							@unittest.skipIf(
							    torch_device != """cuda""" or not is_xformers_available()      ,				reason="""XFormers attention is only available with CUDA and `xformers` installed"""      ,				)
							def 						UpperCamelCase_					(   self		:		Optional[int]	):

											'''simple docstring'''
											self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3	)





							def 						UpperCamelCase_					(   self		:		List[str]	):

											'''simple docstring'''
											self._test_save_load_optional_components()





							@unittest.skipIf(torch_device != """cuda"""      ,				reason="""float16 requires CUDA"""	)
							def 						UpperCamelCase_					(   self		:		int	):

											'''simple docstring'''
											# Due to non-determinism in save load of the hf-internal-testing/tiny-random-t5 text encoder
											super().test_save_load_floataa(expected_max_diff=1E-1	)





							def 						UpperCamelCase_					(   self		:		Optional[Any]	):

											'''simple docstring'''
											self._test_attention_slicing_forward_pass(expected_max_diff=1E-2	)





							def 						UpperCamelCase_					(   self		:		Any	):

											'''simple docstring'''
											self._test_save_load_local()







							def 						UpperCamelCase_					(   self		:		List[Any]	):

											'''simple docstring'''
											self._test_inference_batch_single_identical(
											    expected_max_diff=1E-2      ,				)





from math import sqrt

def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			int    ):
				"""simple docstring"""







				if 1 < number < 4:
								# 2 and 3 are primes
								return True
				elif number < 2 or number % 2 == 0 or number % 3 == 0:
								# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
								return False

				# All primes number are in format of 6k +/- 1
				for i in range(5				,     int(sqrt(_SCREAMING_SNAKE_CASE    ) + 1    )				,     6    ):
								if number % i == 0 or number % (i + 2) == 0:
												return False
				return True

def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			int = 1_0001    ):
				"""simple docstring"""







				__a       =		0
				__a       =		1
				while count != nth and number < 3:
								number += 1
								if is_prime(_SCREAMING_SNAKE_CASE    ):
												count += 1
				while count != nth:
								number += 2
								if is_prime(_SCREAMING_SNAKE_CASE    ):
												count += 1
				return number


if __name__ == "__main__":
						print(F"""{solution() = }""")
