





"""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 				_lowerCamelCase					(				unittest.TestCase       ):


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


						def 			snake_case_      (self						)       ->      Optional[Any]:
								UpperCamelCase      , UpperCamelCase      =		FlaxControlNetModel.from_pretrained(
								    "lllyasviel/sd-controlnet-canny"      ,							from_pt=__UpperCamelCase      ,							dtype=jnp.bfloataa						)
								UpperCamelCase      , UpperCamelCase      =		FlaxStableDiffusionControlNetPipeline.from_pretrained(
								    "runwayml/stable-diffusion-v1-5"      ,							controlnet=__UpperCamelCase      ,							from_pt=__UpperCamelCase      ,							dtype=jnp.bfloataa						)
								UpperCamelCase      =		controlnet_params

								UpperCamelCase      =		"bird"
								UpperCamelCase      =		jax.device_count()
								UpperCamelCase      =		pipe.prepare_text_inputs([prompts] * num_samples						)

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

								UpperCamelCase      =		jax.random.PRNGKey(0						)
								UpperCamelCase      =		jax.random.split(__UpperCamelCase      ,							jax.device_count()						)

								UpperCamelCase      =		replicate(__UpperCamelCase						)
								UpperCamelCase      =		shard(__UpperCamelCase						)
								UpperCamelCase      =		shard(__UpperCamelCase						)

								UpperCamelCase      =		pipe(
								    prompt_ids=__UpperCamelCase      ,							image=__UpperCamelCase      ,							params=__UpperCamelCase      ,							prng_seed=__UpperCamelCase      ,							num_inference_steps=50      ,							jit=__UpperCamelCase      ,							).images
								assert images.shape == (jax.device_count(), 1, 7_68, 5_12, 3)

								UpperCamelCase      =		images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]						)
								UpperCamelCase      =		images[0, 2_53:2_56, 2_53:2_56, -1]

								UpperCamelCase      =		jnp.asarray(jax.device_get(image_slice.flatten()						)						)
								UpperCamelCase      =		jnp.array(
								    [0.167969, 0.116699, 0.081543, 0.154297, 0.132812, 0.108887, 0.169922, 0.169922, 0.205078]						)
								print(F"output_slice: {output_slice}"						)
								assert jnp.abs(output_slice - expected_slice						).max() < 1e-2




						def 			snake_case_      (self						)       ->      List[Any]:
								UpperCamelCase      , UpperCamelCase      =		FlaxControlNetModel.from_pretrained(
								    "lllyasviel/sd-controlnet-openpose"      ,							from_pt=__UpperCamelCase      ,							dtype=jnp.bfloataa						)
								UpperCamelCase      , UpperCamelCase      =		FlaxStableDiffusionControlNetPipeline.from_pretrained(
								    "runwayml/stable-diffusion-v1-5"      ,							controlnet=__UpperCamelCase      ,							from_pt=__UpperCamelCase      ,							dtype=jnp.bfloataa						)
								UpperCamelCase      =		controlnet_params

								UpperCamelCase      =		"Chef in the kitchen"
								UpperCamelCase      =		jax.device_count()
								UpperCamelCase      =		pipe.prepare_text_inputs([prompts] * num_samples						)

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

								UpperCamelCase      =		jax.random.PRNGKey(0						)
								UpperCamelCase      =		jax.random.split(__UpperCamelCase      ,							jax.device_count()						)

								UpperCamelCase      =		replicate(__UpperCamelCase						)
								UpperCamelCase      =		shard(__UpperCamelCase						)
								UpperCamelCase      =		shard(__UpperCamelCase						)

								UpperCamelCase      =		pipe(
								    prompt_ids=__UpperCamelCase      ,							image=__UpperCamelCase      ,							params=__UpperCamelCase      ,							prng_seed=__UpperCamelCase      ,							num_inference_steps=50      ,							jit=__UpperCamelCase      ,							).images
								assert images.shape == (jax.device_count(), 1, 7_68, 5_12, 3)

								UpperCamelCase      =		images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]						)
								UpperCamelCase      =		images[0, 2_53:2_56, 2_53:2_56, -1]

								UpperCamelCase      =		jnp.asarray(jax.device_get(image_slice.flatten()						)						)
								UpperCamelCase      =		jnp.array(
								    [[0.271484, 0.261719, 0.275391, 0.277344, 0.279297, 0.291016, 0.294922, 0.302734, 0.302734]]						)
								print(F"output_slice: {output_slice}"						)
								assert jnp.abs(output_slice - expected_slice						).max() < 1e-2













"""simple docstring"""
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that there is no edge that connects
# vertices of same set.






def 					A__				(			UpperCamelCase       ):
							A		=  [False] * len(UpperCamelCase       )
							A		=  [-1] * len(UpperCamelCase       )

							def dfs(UpperCamelCase					,  UpperCamelCase       ):
														A		=  True
														A		=  c
														for u in graph[v]:
																					if not visited[u]:
																												dfs(UpperCamelCase					,  1 - c       )

							for i in range(len(UpperCamelCase       )       ):
														if not visited[i]:
																					dfs(UpperCamelCase					,  0       )

							for i in range(len(UpperCamelCase       )       ):
														for j in graph[i]:
																					if color[i] == color[j]:
																												return False

							return True


# Adjacency list of graph
_snake_case     :		str       						= {0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: []}
print(check_bipartite_dfs(graph))


