


'''simple docstring'''

import os
import tempfile
import unittest

import numpy as np

from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow


if is_flax_available():
 import jax
 import jax.numpy as jnp
 from flax.jax_utils import replicate
 from flax.training.common_utils import shard

 from diffusers import FlaxDDIMScheduler, FlaxDiffusionPipeline, FlaxStableDiffusionPipeline
@require_flax
class   __lowerCAmelCase						(unittest.TestCase     ):





      '''simple docstring'''






      def       UpperCamelCase__		(self    :    Optional[Any] ):

             '''simple docstring'''







             with tempfile.TemporaryDirectory() as tmpdirname:
                    # pipeline has Flax weights
                    lowercase__      			= FlaxDiffusionPipeline.from_pretrained(
                        '''hf-internal-testing/tiny-stable-diffusion-pipe'''   ,						safety_checker=UpperCamelCase   ,						cache_dir=UpperCamelCase )

                    lowercase__      			= [t[-1] for t in os.walk(os.path.join(UpperCamelCase   ,						os.listdir(UpperCamelCase )[0]   ,						'''snapshots''' ) )]
                    lowercase__      			= [item for sublist in all_root_files for item in sublist]

                    # None of the downloaded files should be a PyTorch file even if we have some here:
                    # https://huggingface.co/hf-internal-testing/tiny-stable-diffusion-pipe/blob/main/unet/diffusion_pytorch_model.bin
                    assert not any(f.endswith('''.bin''' ) for f in files )






@slow
@require_flax
class   __lowerCAmelCase						(unittest.TestCase     ):





      '''simple docstring'''






      def       UpperCamelCase__		(self    :    Tuple ):

             '''simple docstring'''







             lowercase__			,lowercase__      			= FlaxStableDiffusionPipeline.from_pretrained(
                 '''hf-internal-testing/tiny-stable-diffusion-pipe'''   ,						safety_checker=UpperCamelCase )

             lowercase__      			= (
                 '''A cinematic film still of Morgan Freeman starring as Jimi Hendrix, portrait, 40mm lens, shallow depth of'''
                 ''' field, close up, split lighting, cinematic'''
             )

             lowercase__      			= jax.random.PRNGKey(0 )
             lowercase__      			= 4

             lowercase__      			= jax.device_count()
             lowercase__      			= num_samples * [prompt]
             lowercase__      			= pipeline.prepare_inputs(UpperCamelCase )

             # shard inputs and rng
             lowercase__      			= replicate(UpperCamelCase )
             lowercase__      			= jax.random.split(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= shard(UpperCamelCase )

             lowercase__      			= pipeline(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						jit=UpperCamelCase ).images

             assert images.shape == (num_samples, 1, 64, 64, 3)
             if jax.device_count() == 8:
                    assert np.abs(np.abs(images[0, 0, :2, :2, -2:]   ,						dtype=np.floataa ).sum() - 4.1_51_47_45 ) < 1E-3
                    assert np.abs(np.abs(UpperCamelCase   ,						dtype=np.floataa ).sum() - 4_99_47.8_75 ) < 5E-1

             lowercase__      			= pipeline.numpy_to_pil(np.asarray(images.reshape((num_samples,) + images.shape[-3:] ) ) )
             assert len(UpperCamelCase ) == num_samples



      def       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







             lowercase__			,lowercase__      			= FlaxStableDiffusionPipeline.from_pretrained(
                 '''CompVis/stable-diffusion-v1-4'''   ,						revision='''flax'''   ,						safety_checker=UpperCamelCase )

             lowercase__      			= (
                 '''A cinematic film still of Morgan Freeman starring as Jimi Hendrix, portrait, 40mm lens, shallow depth of'''
                 ''' field, close up, split lighting, cinematic'''
             )

             lowercase__      			= jax.random.PRNGKey(0 )
             lowercase__      			= 50

             lowercase__      			= jax.device_count()
             lowercase__      			= num_samples * [prompt]
             lowercase__      			= pipeline.prepare_inputs(UpperCamelCase )

             # shard inputs and rng
             lowercase__      			= replicate(UpperCamelCase )
             lowercase__      			= jax.random.split(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= shard(UpperCamelCase )

             lowercase__      			= pipeline(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						jit=UpperCamelCase ).images

             assert images.shape == (num_samples, 1, 512, 512, 3)
             if jax.device_count() == 8:
                    assert np.abs((np.abs(images[0, 0, :2, :2, -2:]   ,						dtype=np.floataa ).sum() - 0.05_65_24_01) ) < 1E-3
                    assert np.abs((np.abs(UpperCamelCase   ,						dtype=np.floataa ).sum() - 2_38_38_08.2) ) < 5E-1



      def       UpperCamelCase__		(self    :    str ):

             '''simple docstring'''







             lowercase__			,lowercase__      			= FlaxStableDiffusionPipeline.from_pretrained(
                 '''CompVis/stable-diffusion-v1-4'''   ,						revision='''bf16'''   ,						dtype=jnp.bfloataa   ,						safety_checker=UpperCamelCase )

             lowercase__      			= (
                 '''A cinematic film still of Morgan Freeman starring as Jimi Hendrix, portrait, 40mm lens, shallow depth of'''
                 ''' field, close up, split lighting, cinematic'''
             )

             lowercase__      			= jax.random.PRNGKey(0 )
             lowercase__      			= 50

             lowercase__      			= jax.device_count()
             lowercase__      			= num_samples * [prompt]
             lowercase__      			= pipeline.prepare_inputs(UpperCamelCase )

             # shard inputs and rng
             lowercase__      			= replicate(UpperCamelCase )
             lowercase__      			= jax.random.split(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= shard(UpperCamelCase )

             lowercase__      			= pipeline(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						jit=UpperCamelCase ).images

             assert images.shape == (num_samples, 1, 512, 512, 3)
             if jax.device_count() == 8:
                    assert np.abs((np.abs(images[0, 0, :2, :2, -2:]   ,						dtype=np.floataa ).sum() - 0.04_00_39_06) ) < 1E-3
                    assert np.abs((np.abs(UpperCamelCase   ,						dtype=np.floataa ).sum() - 2_37_35_16.75) ) < 5E-1



      def       UpperCamelCase__		(self    :    str ):

             '''simple docstring'''







             lowercase__			,lowercase__      			= FlaxStableDiffusionPipeline.from_pretrained(
                 '''CompVis/stable-diffusion-v1-4'''   ,						revision='''bf16'''   ,						dtype=jnp.bfloataa )

             lowercase__      			= (
                 '''A cinematic film still of Morgan Freeman starring as Jimi Hendrix, portrait, 40mm lens, shallow depth of'''
                 ''' field, close up, split lighting, cinematic'''
             )

             lowercase__      			= jax.random.PRNGKey(0 )
             lowercase__      			= 50

             lowercase__      			= jax.device_count()
             lowercase__      			= num_samples * [prompt]
             lowercase__      			= pipeline.prepare_inputs(UpperCamelCase )

             # shard inputs and rng
             lowercase__      			= replicate(UpperCamelCase )
             lowercase__      			= jax.random.split(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= shard(UpperCamelCase )

             lowercase__      			= pipeline(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						jit=UpperCamelCase ).images

             assert images.shape == (num_samples, 1, 512, 512, 3)
             if jax.device_count() == 8:
                    assert np.abs((np.abs(images[0, 0, :2, :2, -2:]   ,						dtype=np.floataa ).sum() - 0.04_00_39_06) ) < 1E-3
                    assert np.abs((np.abs(UpperCamelCase   ,						dtype=np.floataa ).sum() - 2_37_35_16.75) ) < 5E-1



      def       UpperCamelCase__		(self    :    Union[str, Any] ):

             '''simple docstring'''







             lowercase__      			= FlaxDDIMScheduler(
                 beta_start=0.0_00_85   ,						beta_end=0.0_12   ,						beta_schedule='''scaled_linear'''   ,						set_alpha_to_one=UpperCamelCase   ,						steps_offset=1   ,						)

             lowercase__			,lowercase__      			= FlaxStableDiffusionPipeline.from_pretrained(
                 '''CompVis/stable-diffusion-v1-4'''   ,						revision='''bf16'''   ,						dtype=jnp.bfloataa   ,						scheduler=UpperCamelCase   ,						safety_checker=UpperCamelCase   ,						)
             lowercase__      			= scheduler.create_state()

             lowercase__      			= scheduler_state

             lowercase__      			= (
                 '''A cinematic film still of Morgan Freeman starring as Jimi Hendrix, portrait, 40mm lens, shallow depth of'''
                 ''' field, close up, split lighting, cinematic'''
             )

             lowercase__      			= jax.random.PRNGKey(0 )
             lowercase__      			= 50

             lowercase__      			= jax.device_count()
             lowercase__      			= num_samples * [prompt]
             lowercase__      			= pipeline.prepare_inputs(UpperCamelCase )

             # shard inputs and rng
             lowercase__      			= replicate(UpperCamelCase )
             lowercase__      			= jax.random.split(UpperCamelCase   ,						UpperCamelCase )
             lowercase__      			= shard(UpperCamelCase )

             lowercase__      			= pipeline(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						jit=UpperCamelCase ).images

             assert images.shape == (num_samples, 1, 512, 512, 3)
             if jax.device_count() == 8:
                    assert np.abs((np.abs(images[0, 0, :2, :2, -2:]   ,						dtype=np.floataa ).sum() - 0.0_45_04_39_45) ) < 1E-3
                    assert np.abs((np.abs(UpperCamelCase   ,						dtype=np.floataa ).sum() - 2_34_76_93.5) ) < 5E-1






      def       UpperCamelCase__		(self    :    str ):

             '''simple docstring'''







             lowercase__      			= (
                 '''A cinematic film still of Morgan Freeman starring as Jimi Hendrix, portrait, 40mm lens, shallow depth of'''
                 ''' field, close up, split lighting, cinematic'''
             )

             lowercase__      			= jax.device_count()
             lowercase__      			= num_samples * [prompt]
             lowercase__      			= jax.random.split(jax.random.PRNGKey(0 )   ,						UpperCamelCase )

             lowercase__			,lowercase__      			= FlaxStableDiffusionPipeline.from_pretrained(
                 '''CompVis/stable-diffusion-v1-4'''   ,						revision='''bf16'''   ,						dtype=jnp.bfloataa   ,						safety_checker=UpperCamelCase   ,						)

             lowercase__      			= replicate(UpperCamelCase )
             lowercase__      			= pipeline.prepare_inputs(UpperCamelCase )
             lowercase__      			= shard(UpperCamelCase )
             lowercase__      			= pipeline(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						jit=UpperCamelCase ).images
             assert images.shape == (num_samples, 1, 512, 512, 3)
             lowercase__      			= images[2, 0, 256, 10:17, 1]

             # With memory efficient attention
             lowercase__			,lowercase__      			= FlaxStableDiffusionPipeline.from_pretrained(
                 '''CompVis/stable-diffusion-v1-4'''   ,						revision='''bf16'''   ,						dtype=jnp.bfloataa   ,						safety_checker=UpperCamelCase   ,						use_memory_efficient_attention=UpperCamelCase   ,						)

             lowercase__      			= replicate(UpperCamelCase )
             lowercase__      			= pipeline.prepare_inputs(UpperCamelCase )
             lowercase__      			= shard(UpperCamelCase )
             lowercase__      			= pipeline(UpperCamelCase   ,						UpperCamelCase   ,						UpperCamelCase   ,						jit=UpperCamelCase ).images
             assert images_eff.shape == (num_samples, 1, 512, 512, 3)
             lowercase__      			= images[2, 0, 256, 10:17, 1]

             # I checked the results visually and they are very similar. However, I saw that the max diff is `1` and the `sum`
             # over the 8 images is exactly `256`, which is very suspicious. Testing a random slice for now.
             assert abs(slice_eff - slice ).max() < 1E-2






import math






def    lowerCamelCase__				(				__lowerCAmelCase  :  int				):




			"""simple docstring"""


			lowerCAmelCase_						=	0
			lowerCAmelCase_						=	0
			while num > 0:
						lowerCAmelCase_						=	num % 8
						lowerCAmelCase_						=	octal + (remainder * math.floor(math.pow(10    ,							__lowerCAmelCase				)				))
						counter += 1
						lowerCAmelCase_						=	math.floor(num / 8				)  # basically /= 8 without remainder if any
						# This formatting removes trailing '.0' from `octal`.
			return F"""0o{int(__lowerCAmelCase				)}"""






def    lowerCamelCase__				(				):




			"""simple docstring"""


			print("\n2 in octal is:"				)
			print(decimal_to_octal(2				)				)  # = 2
			print("\n8 in octal is:"				)
			print(decimal_to_octal(8				)				)  # = 10
			print("\n65 in octal is:"				)
			print(decimal_to_octal(65				)				)  # = 101
			print("\n216 in octal is:"				)
			print(decimal_to_octal(216				)				)  # = 330
			print("\n512 in octal is:"				)
			print(decimal_to_octal(512				)				)  # = 1000
			print("\n"				)


if __name__ == "__main__":
			main()



