


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 							A   (	unittest.TestCase							):
					'''simple docstring'''






					def   lowerCamelCase__					(self   :						int		)						->       int:




							"""simple docstring"""


							super().tearDown()
							gc.collect()

					def   lowerCamelCase__					(self   :						Tuple		)						->       Optional[int]:




							"""simple docstring"""


							lowercase__					      =		FlaxControlNetModel.from_pretrained(
							    """lllyasviel/sd-controlnet-canny"""				, from_pt=lowerCamelCase__				, dtype=jnp.bfloataa		)
							lowercase__					      =		FlaxStableDiffusionControlNetPipeline.from_pretrained(
							    """runwayml/stable-diffusion-v1-5"""				, controlnet=lowerCamelCase__				, from_pt=lowerCamelCase__				, dtype=jnp.bfloataa		)
							lowercase__					      =		controlnet_params

							lowercase__					      =		'''bird'''
							lowercase__					      =		jax.device_count()
							lowercase__					      =		pipe.prepare_text_inputs([prompts] * num_samples		)

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

							lowercase__					      =		jax.random.PRNGKey(0		)
							lowercase__					      =		jax.random.split(lowerCamelCase__				, jax.device_count()		)

							lowercase__					      =		replicate(lowerCamelCase__		)
							lowercase__					      =		shard(lowerCamelCase__		)
							lowercase__					      =		shard(lowerCamelCase__		)

							lowercase__					      =		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)

							lowercase__					      =		images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]		)
							lowercase__					      =		images[0, 253:256, 253:256, -1]

							lowercase__					      =		jnp.asarray(jax.device_get(image_slice.flatten()		)		)
							lowercase__					      =		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   lowerCamelCase__					(self   :						Optional[Any]		)						->       str:




							"""simple docstring"""


							lowercase__					      =		FlaxControlNetModel.from_pretrained(
							    """lllyasviel/sd-controlnet-openpose"""				, from_pt=lowerCamelCase__				, dtype=jnp.bfloataa		)
							lowercase__					      =		FlaxStableDiffusionControlNetPipeline.from_pretrained(
							    """runwayml/stable-diffusion-v1-5"""				, controlnet=lowerCamelCase__				, from_pt=lowerCamelCase__				, dtype=jnp.bfloataa		)
							lowercase__					      =		controlnet_params

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

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

							lowercase__					      =		jax.random.PRNGKey(0		)
							lowercase__					      =		jax.random.split(lowerCamelCase__				, jax.device_count()		)

							lowercase__					      =		replicate(lowerCamelCase__		)
							lowercase__					      =		shard(lowerCamelCase__		)
							lowercase__					      =		shard(lowerCamelCase__		)

							lowercase__					      =		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)

							lowercase__					      =		images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]		)
							lowercase__					      =		images[0, 253:256, 253:256, -1]

							lowercase__					      =		jnp.asarray(jax.device_get(image_slice.flatten()		)		)
							lowercase__					      =		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





from __future__ import annotations

from collections import deque



class 							A   :
					'''simple docstring'''






					def __init__(self   :						Any				, _UpperCAmelCase   :						list[str]		)						->       Optional[int]:




							"""simple docstring"""


							lowercase__					      =		[]
							self.adlist.append(
							    {"""value""": """""", """next_states""": [], """fail_state""": 0, """output""": []}		)

							for keyword in keywords:
									self.add_keyword(_UpperCAmelCase		)
							self.set_fail_transitions()

					def   lowerCamelCase__					(self   :						List[str]				, _UpperCAmelCase   :						int				, _UpperCAmelCase   :						str		)						->       int | None:




							"""simple docstring"""


							for state in self.adlist[current_state]["next_states"]:
									if char == self.adlist[state]["value"]:
											return state
							return None

					def   lowerCamelCase__					(self   :						List[Any]				, _UpperCAmelCase   :						str		)						->       None:




							"""simple docstring"""


							lowercase__					      =		0
							for character in keyword:
									lowercase__					      =		self.find_next_state(_UpperCAmelCase				, _UpperCAmelCase		)
									if next_state is None:
											self.adlist.append(
											    {
											        """value""": character,
											        """next_states""": [],
											        """fail_state""": 0,
											        """output""": [],
											    }		)
											self.adlist[current_state]["next_states"].append(len(self.adlist		) - 1		)
											lowercase__					      =		len(self.adlist		) - 1
									else:
											lowercase__					      =		next_state
							self.adlist[current_state]["output"].append(_UpperCAmelCase		)

					def   lowerCamelCase__					(self   :						Any		)						->       None:




							"""simple docstring"""


							lowercase__					      =		deque()
							for node in self.adlist[0]["next_states"]:
									q.append(_UpperCAmelCase		)
									lowercase__					      =		0
							while q:
									lowercase__					      =		q.popleft()
									for child in self.adlist[r]["next_states"]:
											q.append(_UpperCAmelCase		)
											lowercase__					      =		self.adlist[r]["""fail_state"""]
											while (
											    self.find_next_state(_UpperCAmelCase				, self.adlist[child]["""value"""]		) is None
											    and state != 0
											):
													lowercase__					      =		self.adlist[state]["""fail_state"""]
											lowercase__					      =		self.find_next_state(
											    _UpperCAmelCase				, self.adlist[child]["""value"""]		)
											if self.adlist[child]["fail_state"] is None:
													lowercase__					      =		0
											lowercase__					      =		(
											    self.adlist[child]["""output"""]
											    + self.adlist[self.adlist[child]["""fail_state"""]]["""output"""]
											)


					def   lowerCamelCase__					(self   :						List[str]				, _UpperCAmelCase   :						str		)						->       dict[str, list[int]]:




							"""simple docstring"""


							lowercase__					      =		{}  # returns a dict with keywords and list of its occurrences
							lowercase__					      =		0
							for i in range(len(_UpperCAmelCase		)		):
									while (
									    self.find_next_state(_UpperCAmelCase				, string[i]		) is None
									    and current_state != 0
									):
											lowercase__					      =		self.adlist[current_state]["""fail_state"""]
									lowercase__					      =		self.find_next_state(_UpperCAmelCase				, string[i]		)
									if next_state is None:
											lowercase__					      =		0
									else:
											lowercase__					      =		next_state
											for key in self.adlist[current_state]["output"]:
													if key not in result:
															lowercase__					      =		[]
													result[key].append(i - len(_UpperCAmelCase		) + 1		)
							return result


if __name__ == "__main__":
	import doctest

	doctest.testmod()

