
import gc
import unittest

from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
					import jax
					import jax.numpy as jnp
					from flax.jax_utils import replicate
					from flax.training.common_utils import shard





@slow
@require_flax
class 							UpperCAmelCase				(  unittest.TestCase  ):




	'''simple docstring'''





	def     UpperCamelCase_  (	self :			int			):
					# clean up the VRAM after each test
					super().tearDown()
					gc.collect()







	def     UpperCamelCase_  (	self :			Optional[int]			):
					__A             =			load_image(
					    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
					    "/sd2-inpaint/init_image.png"			)
					__A             =			load_image(
					    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd2-inpaint/mask.png"			)

					__A             =			"xvjiarui/stable-diffusion-2-inpainting"
					__A      ,							__A             =			FlaxStableDiffusionInpaintPipeline.from_pretrained(A							,safety_checker=A			)

					__A             =			"Face of a yellow cat, high resolution, sitting on a park bench"

					__A             =			jax.random.PRNGKey(0			)
					__A             =			50

					__A             =			jax.device_count()
					__A             =			num_samples * [prompt]
					__A             =			num_samples * [init_image]
					__A             =			num_samples * [mask_image]
					__A      ,							__A      ,							__A             =			pipeline.prepare_inputs(A							,A							,A			)

					# shard inputs and rng
					__A             =			replicate(A			)
					__A             =			jax.random.split(A							,jax.device_count()			)
					__A             =			shard(A			)
					__A             =			shard(A			)
					__A             =			shard(A			)

					__A             =			pipeline(
					    A							,A							,A							,A							,A							,A							,jit=A			)

					__A             =			output.images.reshape(A							,5_12							,5_12							,3			)

					__A             =			images[0, 2_53:2_56, 2_53:2_56, -1]

					__A             =			jnp.asarray(jax.device_get(image_slice.flatten()			)			)
					__A             =			jnp.array(
					    [0.3_61_13_07, 0.37_64_97_36, 0.3_75_74_08, 0.38_21_39_53, 0.39_29_51_67, 0.3_84_16_31, 0.41_55_49_78, 0.4_13_74_75, 0.4_21_70_84]			)
					print(f'''output_slice: {output_slice}'''			)
					assert jnp.abs(output_slice - expected_slice			).max() < 1E-2


from math import log

from scipy.constants import Boltzmann, physical_constants

SCREAMING_SNAKE_CASE							:Dict										=    300  # TEMPERATURE (unit = K)


def 						UpperCAmelCase      (     a_		,       a_		,       a_		,       )		->     float:







				"""simple docstring"""



				if donor_conc <= 0:
								raise ValueError("Donor concentration should be positive"						)
				elif acceptor_conc <= 0:
								raise ValueError("Acceptor concentration should be positive"						)
				elif intrinsic_conc <= 0:
								raise ValueError("Intrinsic concentration should be positive"						)
				elif donor_conc <= intrinsic_conc:
								raise ValueError(
								    "Donor concentration should be greater than intrinsic concentration"						)
				elif acceptor_conc <= intrinsic_conc:
								raise ValueError(
								    "Acceptor concentration should be greater than intrinsic concentration"						)
				else:
								return (
								    Boltzmann
								    * T
								    * log((donor_conc * acceptor_conc) / intrinsic_conc**2						)
								    / physical_constants["electron volt"][0]
								)


if __name__ == "__main__":
					import doctest

					doctest.testmod()
