





"""simple docstring"""




import gc
import unittest

from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
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						):






							def     __a   (   self      )	-> List[str]:
								# clean up the VRAM after each test
								super().tearDown()
								gc.collect()






							def     __a   (   self      )	-> Union[str, Any]:
								a,       a      :		Tuple	=				FlaxControlNetModel.from_pretrained(
								    "lllyasviel/sd-controlnet-canny"      ,					from_pt=lowerCAmelCase__      ,					dtype=jnp.bfloataa      )
								a,       a      :		int	=				FlaxStableDiffusionControlNetPipeline.from_pretrained(
								    "runwayml/stable-diffusion-v1-5"      ,					controlnet=lowerCAmelCase__      ,					from_pt=lowerCAmelCase__      ,					dtype=jnp.bfloataa      )
								a      :		str	=				controlnet_params

								a      :		Union[str, Any]	=				"bird"
								a      :		List[str]	=				jax.device_count()
								a      :		Union[str, Any]	=				pipe.prepare_text_inputs([prompts] * num_samples      )

								a      :		Tuple	=				load_image(
								    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/bird_canny.png"      )
								a      :		str	=				pipe.prepare_image_inputs([canny_image] * num_samples      )

								a      :		Union[str, Any]	=				jax.random.PRNGKey(0      )
								a      :		Any	=				jax.random.split(lowerCAmelCase__      ,					jax.device_count()      )

								a      :		Dict	=				replicate(lowerCAmelCase__      )
								a      :		List[str]	=				shard(lowerCAmelCase__      )
								a      :		List[Any]	=				shard(lowerCAmelCase__      )

								a      :		Any	=				pipe(
								    prompt_ids=lowerCAmelCase__      ,					image=lowerCAmelCase__      ,					params=lowerCAmelCase__      ,					prng_seed=lowerCAmelCase__      ,					num_inference_steps=50      ,					jit=lowerCAmelCase__      ,					).images
								assert images.shape == (jax.device_count(), 1, 768, 512, 3)

								a      :		str	=				images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]      )
								a      :		Optional[int]	=				images[0, 253:256, 253:256, -1]

								a      :		str	=				jnp.asarray(jax.device_get(image_slice.flatten()      )      )
								a      :		Dict	=				jnp.array(
								    [0.167_969, 0.116_699, 0.081_543, 0.154_297, 0.132_812, 0.108_887, 0.169_922, 0.169_922, 0.205_078]      )
								print(f"""output_slice: {output_slice}"""      )
								assert jnp.abs(output_slice - expected_slice      ).max() < 1E-2






							def     __a   (   self      )	-> str:
								a,       a      :		Any	=				FlaxControlNetModel.from_pretrained(
								    "lllyasviel/sd-controlnet-openpose"      ,					from_pt=lowerCAmelCase__      ,					dtype=jnp.bfloataa      )
								a,       a      :		Tuple	=				FlaxStableDiffusionControlNetPipeline.from_pretrained(
								    "runwayml/stable-diffusion-v1-5"      ,					controlnet=lowerCAmelCase__      ,					from_pt=lowerCAmelCase__      ,					dtype=jnp.bfloataa      )
								a      :		Dict	=				controlnet_params

								a      :		Any	=				"Chef in the kitchen"
								a      :		Optional[Any]	=				jax.device_count()
								a      :		Union[str, Any]	=				pipe.prepare_text_inputs([prompts] * num_samples      )

								a      :		Dict	=				load_image(
								    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/pose.png"      )
								a      :		List[Any]	=				pipe.prepare_image_inputs([pose_image] * num_samples      )

								a      :		Tuple	=				jax.random.PRNGKey(0      )
								a      :		Union[str, Any]	=				jax.random.split(lowerCAmelCase__      ,					jax.device_count()      )

								a      :		Dict	=				replicate(lowerCAmelCase__      )
								a      :		List[str]	=				shard(lowerCAmelCase__      )
								a      :		Any	=				shard(lowerCAmelCase__      )

								a      :		Any	=				pipe(
								    prompt_ids=lowerCAmelCase__      ,					image=lowerCAmelCase__      ,					params=lowerCAmelCase__      ,					prng_seed=lowerCAmelCase__      ,					num_inference_steps=50      ,					jit=lowerCAmelCase__      ,					).images
								assert images.shape == (jax.device_count(), 1, 768, 512, 3)

								a      :		Union[str, Any]	=				images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]      )
								a      :		Union[str, Any]	=				images[0, 253:256, 253:256, -1]

								a      :		Optional[Any]	=				jnp.asarray(jax.device_get(image_slice.flatten()      )      )
								a      :		List[Any]	=				jnp.array(
								    [[0.271_484, 0.261_719, 0.275_391, 0.277_344, 0.279_297, 0.291_016, 0.294_922, 0.302_734, 0.302_734]]      )
								print(f"""output_slice: {output_slice}"""      )
								assert jnp.abs(output_slice - expected_slice      ).max() < 1E-2









"""simple docstring"""





def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						int							,						SCREAMING_SNAKE_CASE     :						int			):







      '''simple docstring'''




      while b:
            lowerCAmelCase						,		lowerCAmelCase  						=       b, a % b
      return a


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						int							,						SCREAMING_SNAKE_CASE     :						int			):







      '''simple docstring'''




      return a if b == 0 else euclidean_gcd_recursive(SCREAMING_SNAKE_CASE							,						a % b			)


def 			UpperCAmelCase__							(  ):







      '''simple docstring'''




      print(F'euclidean_gcd(3, 5) = {euclidean_gcd(3							,						5			)}'			)
      print(F'euclidean_gcd(5, 3) = {euclidean_gcd(5							,						3			)}'			)
      print(F'euclidean_gcd(1, 3) = {euclidean_gcd(1							,						3			)}'			)
      print(F'euclidean_gcd(3, 6) = {euclidean_gcd(3							,						6			)}'			)
      print(F'euclidean_gcd(6, 3) = {euclidean_gcd(6							,						3			)}'			)

      print(F'euclidean_gcd_recursive(3, 5) = {euclidean_gcd_recursive(3							,						5			)}'			)
      print(F'euclidean_gcd_recursive(5, 3) = {euclidean_gcd_recursive(5							,						3			)}'			)
      print(F'euclidean_gcd_recursive(1, 3) = {euclidean_gcd_recursive(1							,						3			)}'			)
      print(F'euclidean_gcd_recursive(3, 6) = {euclidean_gcd_recursive(3							,						6			)}'			)
      print(F'euclidean_gcd_recursive(6, 3) = {euclidean_gcd_recursive(6							,						3			)}'			)


if __name__ == "__main__":
       main()






