





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  __A       (  unittest.TestCase      ):


    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=__lowercase				,	cache_dir=__lowercase							)

            lowerCamelCase			=[t[-1] for t in os.walk(os.path.join(__lowercase				,	os.listdir(__lowercase							)[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  __A       (  unittest.TestCase      ):


    def _snake_case    (						self							):
        lowerCamelCase			=FlaxStableDiffusionPipeline.from_pretrained(
            """hf-internal-testing/tiny-stable-diffusion-pipe"""				,	safety_checker=__lowercase							)

        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(__lowercase							)

        # shard inputs and rng
        lowerCamelCase			=replicate(__lowercase							)
        lowerCamelCase			=jax.random.split(__lowercase				,	__lowercase							)
        lowerCamelCase			=shard(__lowercase							)

        lowerCamelCase			=pipeline(__lowercase				,	__lowercase				,	__lowercase				,	__lowercase				,	jit=__lowercase							).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_5_1_4_7_4_5							) < 1E-3
            assert np.abs(np.abs(__lowercase				,	dtype=np.floataa							).sum() - 49947.875							) < 5E-1

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


    def _snake_case    (						self							):
        lowerCamelCase			=FlaxStableDiffusionPipeline.from_pretrained(
            """CompVis/stable-diffusion-v1-4"""				,	revision="""flax"""				,	safety_checker=__lowercase							)

        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			=50

        lowerCamelCase			=jax.device_count()
        lowerCamelCase			=num_samples * [prompt]
        lowerCamelCase			=pipeline.prepare_inputs(__lowercase							)

        # shard inputs and rng
        lowerCamelCase			=replicate(__lowercase							)
        lowerCamelCase			=jax.random.split(__lowercase				,	__lowercase							)
        lowerCamelCase			=shard(__lowercase							)

        lowerCamelCase			=pipeline(__lowercase				,	__lowercase				,	__lowercase				,	__lowercase				,	jit=__lowercase							).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_5_6_5_2_4_0_1)							) < 1E-3
            assert np.abs((np.abs(__lowercase				,	dtype=np.floataa							).sum() - 2383808.2)							) < 5E-1


    def _snake_case    (						self							):
        lowerCamelCase			=FlaxStableDiffusionPipeline.from_pretrained(
            """CompVis/stable-diffusion-v1-4"""				,	revision="""bf16"""				,	dtype=jnp.bfloataa				,	safety_checker=__lowercase							)

        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			=50

        lowerCamelCase			=jax.device_count()
        lowerCamelCase			=num_samples * [prompt]
        lowerCamelCase			=pipeline.prepare_inputs(__lowercase							)

        # shard inputs and rng
        lowerCamelCase			=replicate(__lowercase							)
        lowerCamelCase			=jax.random.split(__lowercase				,	__lowercase							)
        lowerCamelCase			=shard(__lowercase							)

        lowerCamelCase			=pipeline(__lowercase				,	__lowercase				,	__lowercase				,	__lowercase				,	jit=__lowercase							).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_4_0_0_3_9_0_6)							) < 1E-3
            assert np.abs((np.abs(__lowercase				,	dtype=np.floataa							).sum() - 2373516.75)							) < 5E-1


    def _snake_case    (						self							):
        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			=50

        lowerCamelCase			=jax.device_count()
        lowerCamelCase			=num_samples * [prompt]
        lowerCamelCase			=pipeline.prepare_inputs(__lowercase							)

        # shard inputs and rng
        lowerCamelCase			=replicate(__lowercase							)
        lowerCamelCase			=jax.random.split(__lowercase				,	__lowercase							)
        lowerCamelCase			=shard(__lowercase							)

        lowerCamelCase			=pipeline(__lowercase				,	__lowercase				,	__lowercase				,	__lowercase				,	jit=__lowercase							).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_4_0_0_3_9_0_6)							) < 1E-3
            assert np.abs((np.abs(__lowercase				,	dtype=np.floataa							).sum() - 2373516.75)							) < 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=__lowercase				,	steps_offset=1				,	)

        lowerCamelCase			=FlaxStableDiffusionPipeline.from_pretrained(
            """CompVis/stable-diffusion-v1-4"""				,	revision="""bf16"""				,	dtype=jnp.bfloataa				,	scheduler=__lowercase				,	safety_checker=__lowercase				,	)
        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			=50

        lowerCamelCase			=jax.device_count()
        lowerCamelCase			=num_samples * [prompt]
        lowerCamelCase			=pipeline.prepare_inputs(__lowercase							)

        # shard inputs and rng
        lowerCamelCase			=replicate(__lowercase							)
        lowerCamelCase			=jax.random.split(__lowercase				,	__lowercase							)
        lowerCamelCase			=shard(__lowercase							)

        lowerCamelCase			=pipeline(__lowercase				,	__lowercase				,	__lowercase				,	__lowercase				,	jit=__lowercase							).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_4_5_0_4_3_9_4_5)							) < 1E-3
            assert np.abs((np.abs(__lowercase				,	dtype=np.floataa							).sum() - 2347693.5)							) < 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							)				,	__lowercase							)

        lowerCamelCase			=FlaxStableDiffusionPipeline.from_pretrained(
            """CompVis/stable-diffusion-v1-4"""				,	revision="""bf16"""				,	dtype=jnp.bfloataa				,	safety_checker=__lowercase				,	)

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

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

        lowerCamelCase			=replicate(__lowercase							)
        lowerCamelCase			=pipeline.prepare_inputs(__lowercase							)
        lowerCamelCase			=shard(__lowercase							)
        lowerCamelCase			=pipeline(__lowercase				,	__lowercase				,	__lowercase				,	jit=__lowercase							).images
        assert images_eff.shape == (num_samples, 1, 512, 512, 3)
        lowerCamelCase			=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 pytest
import requests

from datasets.utils.file_utils import http_head

from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline





@pytest.mark.integration
def        _lowercase   (  )  ->					str:
				with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT			):
								with pytest.raises(_UpperCAmelCase			):
												requests.request("""GET"""     , """https://huggingface.co"""			)
								with pytest.raises(requests.exceptions.ConnectTimeout			):
												requests.request("""GET"""     , """https://huggingface.co"""     , timeout=1.0			)





@pytest.mark.integration
def        _lowercase   (  )  ->					Union[str, Any]:
				with offline(OfflineSimulationMode.CONNECTION_FAILS			):
								with pytest.raises(requests.exceptions.ConnectionError			):
												requests.request("""GET"""     , """https://huggingface.co"""			)





def        _lowercase   (  )  ->					int:
				with offline(OfflineSimulationMode.HF_DATASETS_OFFLINE_SET_TO_1			):
								with pytest.raises(_UpperCAmelCase			):
												http_head("""https://huggingface.co"""			)





