




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 						_A (  unittest.TestCase				):






  def  __a      (  self		:     List[Any]				)		->   str:






       """simple docstring"""







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






  def  __a      (  self		:     Optional[int]				)		->   int:






       """simple docstring"""







       lowercase      ,	lowercase :       Optional[int]       =			FlaxStableDiffusionPipeline.from_pretrained(
           '''stabilityai/stable-diffusion-2'''				,						revision='''bf16'''				,						dtype=jnp.bfloataa				,						)

       lowercase :       List[Any]       =			'''A painting of a squirrel eating a burger'''
       lowercase :       List[Any]       =			jax.device_count()
       lowercase :       Any       =			num_samples * [prompt]
       lowercase :       Optional[Any]       =			sd_pipe.prepare_inputs(_A				)

       lowercase :       Union[str, Any]       =			replicate(_A				)
       lowercase :       Dict       =			shard(_A				)

       lowercase :       int       =			jax.random.PRNGKey(0				)
       lowercase :       str       =			jax.random.split(_A				,						jax.device_count()				)

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

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

       lowercase :       str       =			jnp.asarray(jax.device_get(image_slice.flatten()				)				)
       lowercase :       Union[str, Any]       =			jnp.array([0.4_238, 0.4_414, 0.4_395, 0.4_453, 0.4_629, 0.4_590, 0.4_531, 0.45_508, 0.4_512]				)
       print(f"""output_slice: {output_slice}"""				)
       assert jnp.abs(output_slice - expected_slice				).max() < 1E-2






  def  __a      (  self		:     int				)		->   Dict:






       """simple docstring"""







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

       lowercase :       Optional[int]       =			'''A painting of a squirrel eating a burger'''
       lowercase :       List[str]       =			jax.device_count()
       lowercase :       str       =			num_samples * [prompt]
       lowercase :       Optional[int]       =			sd_pipe.prepare_inputs(_A				)

       lowercase :       Optional[int]       =			replicate(_A				)
       lowercase :       Tuple       =			shard(_A				)

       lowercase :       List[str]       =			jax.random.PRNGKey(0				)
       lowercase :       List[Any]       =			jax.random.split(_A				,						jax.device_count()				)

       lowercase :       Union[str, Any]       =			sd_pipe(_A				,						_A				,						_A				,						num_inference_steps=25				,						jit=_A				)[0]
       assert images.shape == (jax.device_count(), 1, 768, 768, 3)

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

       lowercase :       Dict       =			jnp.asarray(jax.device_get(image_slice.flatten()				)				)
       lowercase :       List[Any]       =			jnp.array([0.4_336, 0.42_969, 0.4_453, 0.4_199, 0.4_297, 0.4_531, 0.4_434, 0.4_434, 0.4_297]				)
       print(f"""output_slice: {output_slice}"""				)
       assert jnp.abs(output_slice - expected_slice				).max() < 1E-2





import os
from collections.abc import Iterator






def  snake_case(    __magic_name__ = "."   )			->							Iterator[str]:





     '''simple docstring'''


     for dir_path, dir_names, filenames in os.walk(__magic_name__   ):
          lowercase :       Tuple       =			[d for d in dir_names if d != '''scripts''' and d[0] not in '''._''']
          for filename in filenames:
               if filename == "__init__.py":
                    continue
               if os.path.splitext(__magic_name__   )[1] in (".py", ".ipynb"):
                    yield os.path.join(__magic_name__			,		__magic_name__   ).lstrip('''./'''   )






def  snake_case(    __magic_name__   )			->							Dict:





     '''simple docstring'''


     return F"""{i * '  '}*""" if i else "\n##"






def  snake_case(    __magic_name__			,		__magic_name__   )			->							str:





     '''simple docstring'''


     lowercase :       Dict       =			old_path.split(os.sep   )
     for i, new_part in enumerate(new_path.split(os.sep   )   ):
          if (i + 1 > len(__magic_name__   ) or old_parts[i] != new_part) and new_part:
               print(F"""{md_prefix(__magic_name__   )} {new_part.replace('_'			,		' '   ).title()}"""   )
     return new_path






def  snake_case(    __magic_name__ = "."   )			->							None:





     '''simple docstring'''


     lowercase :       str       =			''''''
     for filepath in sorted(good_file_paths(__magic_name__   )   ):
          lowercase      ,	lowercase :       Optional[int]       =			os.path.split(__magic_name__   )
          if filepath != old_path:
               lowercase :       str       =			print_path(__magic_name__			,		__magic_name__   )
          lowercase :       Optional[int]       =			(filepath.count(os.sep   ) + 1) if filepath else 0
          lowercase :       Optional[Any]       =			F"""{filepath}/{filename}""".replace(''' '''			,		'''%20'''   )
          lowercase :       List[str]       =			os.path.splitext(filename.replace('''_'''			,		''' '''   ).title()   )[0]
          print(F"""{md_prefix(__magic_name__   )} [{filename}]({url})"""   )


if __name__ == "__main__":
 print_directory_md('.')