"""simple docstring"""




import gc
import unittest

from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, 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     UpperCamelCase__(			unittest.TestCase ):





						def 				snake_case__	(       self     )					->				int:
													# clean up the VRAM after each test
													super().tearDown()
													gc.collect()





						def 				snake_case__	(       self     )					->				Any:
													A__	     =							load_image(
													    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
													    '/sd2-inpaint/init_image.png'     )
													A__	     =							load_image(
													    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd2-inpaint/mask.png'     )

													A__	     =							'xvjiarui/stable-diffusion-2-inpainting'
													A__	     =							FlaxStableDiffusionInpaintPipeline.from_pretrained(_lowercase		,safety_checker=_lowercase     )

													A__	     =							'Face of a yellow cat, high resolution, sitting on a park bench'

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

													A__	     =							jax.device_count()
													A__	     =							num_samples * [prompt]
													A__	     =							num_samples * [init_image]
													A__	     =							num_samples * [mask_image]
													A__	     =							pipeline.prepare_inputs(_lowercase		,_lowercase		,_lowercase     )

													# shard inputs and rng
													A__	     =							replicate(_lowercase     )
													A__	     =							jax.random.split(_lowercase		,jax.device_count()     )
													A__	     =							shard(_lowercase     )
													A__	     =							shard(_lowercase     )
													A__	     =							shard(_lowercase     )

													A__	     =							pipeline(
													    _lowercase		,_lowercase		,_lowercase		,_lowercase		,_lowercase		,_lowercase		,jit=_lowercase     )

													A__	     =							output.images.reshape(_lowercase		,5_12		,5_12		,3     )

													A__	     =							images[0, 2_53:2_56, 2_53:2_56, -1]

													A__	     =							jnp.asarray(jax.device_get(image_slice.flatten()     )     )
													A__	     =							jnp.array(
													    [0.3_6_1_1_3_0_7, 0.3_7_6_4_9_7_3_6, 0.3_7_5_7_4_0_8, 0.3_8_2_1_3_9_5_3, 0.3_9_2_9_5_1_6_7, 0.3_8_4_1_6_3_1, 0.4_1_5_5_4_9_7_8, 0.4_1_3_7_4_7_5, 0.4_2_1_7_0_8_4]     )
													print(f'''output_slice: {output_slice}'''     )
													assert jnp.abs(output_slice - expected_slice     ).max() < 1e-2






"""simple docstring"""




from __future__ import annotations

from math import pi
from typing import Protocol

import matplotlib.pyplot as plt
import numpy as np
class     UpperCamelCase__(			__A ):





						def 				snake_case__	(       self		,__UpperCAmelCase     )					->				float:
													return 0.0






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							A__	     =							min([-20, np.min(fft_results[1 : samplerate // 2 - 1]				)]				)
							A__	     =							max([20, np.max(fft_results[1 : samplerate // 2 - 1]				)]				)
							return lowest, highest






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							A__	     =							512
							A__	     =							[1] + [0] * (size - 1)
							A__	     =							[filter_type.process(UpperCamelCase__				) for item in inputs]

							A__	     =							[0] * (samplerate - size)  # zero-padding
							outputs += filler
							A__	     =							np.abs(np.fft.fft(UpperCamelCase__				)				)
							A__	     =							20 * np.logaa(UpperCamelCase__				)

							# Frequencies on log scale from 24 to nyquist frequency
							plt.xlim(24       ,    samplerate / 2 - 1				)
							plt.xlabel('Frequency (Hz)'				)
							plt.xscale('log'				)

							# Display within reasonable bounds
							A__	     =							get_bounds(UpperCamelCase__       ,    UpperCamelCase__				)
							plt.ylim(max([-80, bounds[0]]				)       ,    min([80, bounds[1]]				)				)
							plt.ylabel('Gain (dB)'				)

							plt.plot(UpperCamelCase__				)
							plt.show()






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							A__	     =							512
							A__	     =							[1] + [0] * (size - 1)
							A__	     =							[filter_type.process(UpperCamelCase__				) for item in inputs]

							A__	     =							[0] * (samplerate - size)  # zero-padding
							outputs += filler
							A__	     =							np.angle(np.fft.fft(UpperCamelCase__				)				)

							# Frequencies on log scale from 24 to nyquist frequency
							plt.xlim(24       ,    samplerate / 2 - 1				)
							plt.xlabel('Frequency (Hz)'				)
							plt.xscale('log'				)

							plt.ylim(-2 * pi       ,    2 * pi				)
							plt.ylabel('Phase shift (Radians)'				)
							plt.plot(np.unwrap(UpperCamelCase__       ,    -2 * pi				)				)
							plt.show()





