



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

													_lowerCamelCase   	=					[t[-1] for t in os.walk(os.path.join(__lowerCAmelCase					,							os.listdir(__lowerCAmelCase )[0]					,							'''snapshots''' ) )]
													_lowerCamelCase   	=					[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       snake_case__   (     self ):
									_lowerCamelCase	,  _lowerCamelCase   	=					FlaxStableDiffusionPipeline.from_pretrained(
									    '''hf-internal-testing/tiny-stable-diffusion-pipe'''					,							safety_checker=__lowerCAmelCase )

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

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

									_lowerCamelCase   	=					jax.device_count()
									_lowerCamelCase   	=					num_samples * [prompt]
									_lowerCamelCase   	=					pipeline.prepare_inputs(__lowerCAmelCase )

									# shard inputs and rng
									_lowerCamelCase   	=					replicate(__lowerCAmelCase )
									_lowerCamelCase   	=					jax.random.split(__lowerCAmelCase					,							__lowerCAmelCase )
									_lowerCamelCase   	=					shard(__lowerCAmelCase )

									_lowerCamelCase   	=					pipeline(__lowerCAmelCase					,							__lowerCAmelCase					,							__lowerCAmelCase					,							__lowerCAmelCase					,							jit=__lowerCAmelCase ).images

									assert images.shape == (num_samples, 1, 6_4, 6_4, 3)
									if jax.device_count() == 8:
													assert np.abs(np.abs(images[0, 0, :2, :2, -2:]					,							dtype=np.floataa ).sum() - 4.1_5_1_4_7_4_5 ) < 1e-3
													assert np.abs(np.abs(__lowerCAmelCase					,							dtype=np.floataa ).sum() - 4_9_9_4_7.8_7_5 ) < 5e-1

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

					def       snake_case__   (     self ):
									_lowerCamelCase	,  _lowerCamelCase   	=					FlaxStableDiffusionPipeline.from_pretrained(
									    '''CompVis/stable-diffusion-v1-4'''					,							revision='''flax'''					,							safety_checker=__lowerCAmelCase )

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

									_lowerCamelCase   	=					jax.random.PRNGKey(0 )
									_lowerCamelCase   	=					5_0

									_lowerCamelCase   	=					jax.device_count()
									_lowerCamelCase   	=					num_samples * [prompt]
									_lowerCamelCase   	=					pipeline.prepare_inputs(__lowerCAmelCase )

									# shard inputs and rng
									_lowerCamelCase   	=					replicate(__lowerCAmelCase )
									_lowerCamelCase   	=					jax.random.split(__lowerCAmelCase					,							__lowerCAmelCase )
									_lowerCamelCase   	=					shard(__lowerCAmelCase )

									_lowerCamelCase   	=					pipeline(__lowerCAmelCase					,							__lowerCAmelCase					,							__lowerCAmelCase					,							__lowerCAmelCase					,							jit=__lowerCAmelCase ).images

									assert images.shape == (num_samples, 1, 5_1_2, 5_1_2, 3)
									if jax.device_count() == 8:
													assert np.abs((np.abs(images[0, 0, :2, :2, -2:]					,							dtype=np.floataa ).sum() - 0.0_5_6_5_2_4_0_1) ) < 1e-3
													assert np.abs((np.abs(__lowerCAmelCase					,							dtype=np.floataa ).sum() - 2_3_8_3_8_0_8.2) ) < 5e-1

					def       snake_case__   (     self ):
									_lowerCamelCase	,  _lowerCamelCase   	=					FlaxStableDiffusionPipeline.from_pretrained(
									    '''CompVis/stable-diffusion-v1-4'''					,							revision='''bf16'''					,							dtype=jnp.bfloataa					,							safety_checker=__lowerCAmelCase )

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

									_lowerCamelCase   	=					jax.random.PRNGKey(0 )
									_lowerCamelCase   	=					5_0

									_lowerCamelCase   	=					jax.device_count()
									_lowerCamelCase   	=					num_samples * [prompt]
									_lowerCamelCase   	=					pipeline.prepare_inputs(__lowerCAmelCase )

									# shard inputs and rng
									_lowerCamelCase   	=					replicate(__lowerCAmelCase )
									_lowerCamelCase   	=					jax.random.split(__lowerCAmelCase					,							__lowerCAmelCase )
									_lowerCamelCase   	=					shard(__lowerCAmelCase )

									_lowerCamelCase   	=					pipeline(__lowerCAmelCase					,							__lowerCAmelCase					,							__lowerCAmelCase					,							__lowerCAmelCase					,							jit=__lowerCAmelCase ).images

									assert images.shape == (num_samples, 1, 5_1_2, 5_1_2, 3)
									if jax.device_count() == 8:
													assert np.abs((np.abs(images[0, 0, :2, :2, -2:]					,							dtype=np.floataa ).sum() - 0.0_4_0_0_3_9_0_6) ) < 1e-3
													assert np.abs((np.abs(__lowerCAmelCase					,							dtype=np.floataa ).sum() - 2_3_7_3_5_1_6.7_5) ) < 5e-1

					def       snake_case__   (     self ):
									_lowerCamelCase	,  _lowerCamelCase   	=					FlaxStableDiffusionPipeline.from_pretrained(
									    '''CompVis/stable-diffusion-v1-4'''					,							revision='''bf16'''					,							dtype=jnp.bfloataa )

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

									_lowerCamelCase   	=					jax.random.PRNGKey(0 )
									_lowerCamelCase   	=					5_0

									_lowerCamelCase   	=					jax.device_count()
									_lowerCamelCase   	=					num_samples * [prompt]
									_lowerCamelCase   	=					pipeline.prepare_inputs(__lowerCAmelCase )

									# shard inputs and rng
									_lowerCamelCase   	=					replicate(__lowerCAmelCase )
									_lowerCamelCase   	=					jax.random.split(__lowerCAmelCase					,							__lowerCAmelCase )
									_lowerCamelCase   	=					shard(__lowerCAmelCase )

									_lowerCamelCase   	=					pipeline(__lowerCAmelCase					,							__lowerCAmelCase					,							__lowerCAmelCase					,							__lowerCAmelCase					,							jit=__lowerCAmelCase ).images

									assert images.shape == (num_samples, 1, 5_1_2, 5_1_2, 3)
									if jax.device_count() == 8:
													assert np.abs((np.abs(images[0, 0, :2, :2, -2:]					,							dtype=np.floataa ).sum() - 0.0_4_0_0_3_9_0_6) ) < 1e-3
													assert np.abs((np.abs(__lowerCAmelCase					,							dtype=np.floataa ).sum() - 2_3_7_3_5_1_6.7_5) ) < 5e-1

					def       snake_case__   (     self ):
									_lowerCamelCase   	=					FlaxDDIMScheduler(
									    beta_start=0.0_0_0_8_5					,							beta_end=0.0_1_2					,							beta_schedule='''scaled_linear'''					,							set_alpha_to_one=__lowerCAmelCase					,							steps_offset=1					,							)

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

									_lowerCamelCase   	=					scheduler_state

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

									_lowerCamelCase   	=					jax.random.PRNGKey(0 )
									_lowerCamelCase   	=					5_0

									_lowerCamelCase   	=					jax.device_count()
									_lowerCamelCase   	=					num_samples * [prompt]
									_lowerCamelCase   	=					pipeline.prepare_inputs(__lowerCAmelCase )

									# shard inputs and rng
									_lowerCamelCase   	=					replicate(__lowerCAmelCase )
									_lowerCamelCase   	=					jax.random.split(__lowerCAmelCase					,							__lowerCAmelCase )
									_lowerCamelCase   	=					shard(__lowerCAmelCase )

									_lowerCamelCase   	=					pipeline(__lowerCAmelCase					,							__lowerCAmelCase					,							__lowerCAmelCase					,							__lowerCAmelCase					,							jit=__lowerCAmelCase ).images

									assert images.shape == (num_samples, 1, 5_1_2, 5_1_2, 3)
									if jax.device_count() == 8:
													assert np.abs((np.abs(images[0, 0, :2, :2, -2:]					,							dtype=np.floataa ).sum() - 0.0_4_5_0_4_3_9_4_5) ) < 1e-3
													assert np.abs((np.abs(__lowerCAmelCase					,							dtype=np.floataa ).sum() - 2_3_4_7_6_9_3.5) ) < 5e-1





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

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

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

									_lowerCamelCase   	=					replicate(__lowerCAmelCase )
									_lowerCamelCase   	=					pipeline.prepare_inputs(__lowerCAmelCase )
									_lowerCamelCase   	=					shard(__lowerCAmelCase )
									_lowerCamelCase   	=					pipeline(__lowerCAmelCase					,							__lowerCAmelCase					,							__lowerCAmelCase					,							jit=__lowerCAmelCase ).images
									assert images.shape == (num_samples, 1, 5_1_2, 5_1_2, 3)
									_lowerCamelCase   	=					images[2, 0, 2_5_6, 1_0:1_7, 1]

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

									_lowerCamelCase   	=					replicate(__lowerCAmelCase )
									_lowerCamelCase   	=					pipeline.prepare_inputs(__lowerCAmelCase )
									_lowerCamelCase   	=					shard(__lowerCAmelCase )
									_lowerCamelCase   	=					pipeline(__lowerCAmelCase					,							__lowerCAmelCase					,							__lowerCAmelCase					,							jit=__lowerCAmelCase ).images
									assert images_eff.shape == (num_samples, 1, 5_1_2, 5_1_2, 3)
									_lowerCamelCase   	=					images[2, 0, 2_5_6, 1_0:1_7, 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

"""simple docstring"""


from transformers import BertTokenizerFast

from .custom_tokenization import CustomTokenizer


class 							a					(		lowerCAmelCase_ ):
    _snake_case  :	Dict  				=				CustomTokenizer
    pass
