






import gc
import unittest

from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, 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			):

					'''simple docstring'''

					def       lowerCAmelCase				(  self				:	str							)			->  Union[str, Any]:


												"""simple docstring"""

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



					def       lowerCAmelCase				(  self				:	List[Any]							)			->  Any:


												"""simple docstring"""

												__lowercase			,			__lowercase      :							Any				=     FlaxStableDiffusionPipeline.from_pretrained(
												    """stabilityai/stable-diffusion-2"""		,     revision="""bf16"""		,     dtype=jnp.bfloataa		,     )

												__lowercase      :							List[str]				=     """A painting of a squirrel eating a burger"""
												__lowercase      :							Any				=     jax.device_count()
												__lowercase      :							List[str]				=     num_samples * [prompt]
												__lowercase      :							Dict				=     sd_pipe.prepare_inputs(__a							)

												__lowercase      :							List[str]				=     replicate(__a							)
												__lowercase      :							Tuple				=     shard(__a							)

												__lowercase      :							Union[str, Any]				=     jax.random.PRNGKey(0							)
												__lowercase      :							int				=     jax.random.split(__a		,     jax.device_count()							)

												__lowercase      :							List[Any]				=     sd_pipe(__a		,     __a		,     __a		,     num_inference_steps=25		,     jit=__a							)[0]
												assert images.shape == (jax.device_count(), 1, 768, 768, 3)

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

												__lowercase      :							Optional[int]				=     jnp.asarray(jax.device_get(image_slice.flatten()							)							)
												__lowercase      :							Optional[int]				=     jnp.array([0.4238, 0.4414, 0.4395, 0.4453, 0.4629, 0.4590, 0.4531, 0.45508, 0.4512]							)
												print(F"output_slice: {output_slice}"							)
												assert jnp.abs(output_slice - expected_slice							).max() < 1E-2



					def       lowerCAmelCase				(  self				:	Any							)			->  str:


												"""simple docstring"""

												__lowercase      :							Optional[int]				=     """stabilityai/stable-diffusion-2"""
												__lowercase			,			__lowercase      :							List[str]				=     FlaxDPMSolverMultistepScheduler.from_pretrained(__a		,     subfolder="""scheduler"""							)
												__lowercase			,			__lowercase      :							Any				=     FlaxStableDiffusionPipeline.from_pretrained(
												    __a		,     scheduler=__a		,     revision="""bf16"""		,     dtype=jnp.bfloataa		,     )
												__lowercase      :							Optional[int]				=     scheduler_params

												__lowercase      :							Optional[int]				=     """A painting of a squirrel eating a burger"""
												__lowercase      :							Optional[Any]				=     jax.device_count()
												__lowercase      :							str				=     num_samples * [prompt]
												__lowercase      :							Any				=     sd_pipe.prepare_inputs(__a							)

												__lowercase      :							int				=     replicate(__a							)
												__lowercase      :							Tuple				=     shard(__a							)

												__lowercase      :							str				=     jax.random.PRNGKey(0							)
												__lowercase      :							Optional[int]				=     jax.random.split(__a		,     jax.device_count()							)

												__lowercase      :							str				=     sd_pipe(__a		,     __a		,     __a		,     num_inference_steps=25		,     jit=__a							)[0]
												assert images.shape == (jax.device_count(), 1, 768, 768, 3)

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

												__lowercase      :							Optional[int]				=     jnp.asarray(jax.device_get(image_slice.flatten()							)							)
												__lowercase      :							List[str]				=     jnp.array([0.4336, 0.42969, 0.4453, 0.4199, 0.4297, 0.4531, 0.4434, 0.4434, 0.4297]							)
												print(F"output_slice: {output_slice}"							)
												assert jnp.abs(output_slice - expected_slice							).max() < 1E-2







from __future__ import annotations
def       snake_case_		(     lowerCAmelCase_       :						str       ,       lowerCAmelCase_       :						list[str] | None = None      ):
							__lowercase      :							Tuple				=     word_bank or []
							# create a table
							__lowercase      :							int				=     len(lowerCAmelCase_      ) + 1

							__lowercase      :							list[list[list[str]]]				=     []
							for _ in range(lowerCAmelCase_      ):
														table.append([]      )
							# seed value
							__lowercase      :							Dict				=     [[]]  # because empty string has empty combination

							# iterate through the indices
							for i in range(lowerCAmelCase_      ):
														# condition
														if table[i] != []:
																					for word in word_bank:
																												# slice condition
																												if target[i : i + len(lowerCAmelCase_      )] == word:
																																			__lowercase      :							list[list[str]]				=     [
																																			    [word, *way] for way in table[i]
																																			]
																																			# adds the word to every combination the current position holds
																																			# now,push that combination to the table[i+len(word)]
																																			table[i + len(lowerCAmelCase_      )] += new_combinations

    # combinations are in reverse order so reverse for better output
							for combination in table[len(lowerCAmelCase_      )]:
														combination.reverse()

							return table[len(lowerCAmelCase_      )]


if __name__ == "__main__":
	print(all_construct('''jwajalapa''', ['''jwa''', '''j''', '''w''', '''a''', '''la''', '''lapa''']))
	print(all_construct('''rajamati''', ['''s''', '''raj''', '''amat''', '''raja''', '''ma''', '''i''', '''t''']))
	print(
	    all_construct(
	        '''hexagonosaurus''',
	        ['''h''', '''ex''', '''hex''', '''ag''', '''ago''', '''ru''', '''auru''', '''rus''', '''go''', '''no''', '''o''', '''s'''],
	    )
	)