

import gc
import unittest

from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
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   lowercase_   (  unittest.TestCase					):



      def 						UpperCamelCase_		(      self				:    Dict		)   ->					Optional[int]:
        # clean up the VRAM after each test
        super().tearDown()
        gc.collect()



      def 						UpperCamelCase_		(      self				:    Any		)   ->					Tuple:
        _snake_case,					_snake_case						=							FlaxControlNetModel.from_pretrained(
            '''lllyasviel/sd-controlnet-canny'''      , from_pt=A__      , dtype=jnp.bfloataa		)
        _snake_case,					_snake_case						=							FlaxStableDiffusionControlNetPipeline.from_pretrained(
            '''runwayml/stable-diffusion-v1-5'''      , controlnet=A__      , from_pt=A__      , dtype=jnp.bfloataa		)
        _snake_case						=							controlnet_params

        _snake_case						=							'''bird'''
        _snake_case						=							jax.device_count()
        _snake_case						=							pipe.prepare_text_inputs([prompts] * num_samples		)

        _snake_case						=							load_image(
            '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/bird_canny.png'''		)
        _snake_case						=							pipe.prepare_image_inputs([canny_image] * num_samples		)

        _snake_case						=							jax.random.PRNGKey(0		)
        _snake_case						=							jax.random.split(A__      , jax.device_count()		)

        _snake_case						=							replicate(A__		)
        _snake_case						=							shard(A__		)
        _snake_case						=							shard(A__		)

        _snake_case						=							pipe(
            prompt_ids=A__      , image=A__      , params=A__      , prng_seed=A__      , num_inference_steps=50      , jit=A__      , ).images
        assert images.shape == (jax.device_count(), 1, 768, 512, 3)

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

        _snake_case						=							jnp.asarray(jax.device_get(image_slice.flatten()		)		)
        _snake_case						=							jnp.array(
            [0.16_7969, 0.11_6699, 0.08_1543, 0.15_4297, 0.13_2812, 0.10_8887, 0.16_9922, 0.16_9922, 0.20_5078]		)
        print(f"""output_slice: {output_slice}"""		)
        assert jnp.abs(output_slice - expected_slice		).max() < 1e-2







      def 						UpperCamelCase_		(      self				:    str		)   ->					Optional[int]:
        _snake_case,					_snake_case						=							FlaxControlNetModel.from_pretrained(
            '''lllyasviel/sd-controlnet-openpose'''      , from_pt=A__      , dtype=jnp.bfloataa		)
        _snake_case,					_snake_case						=							FlaxStableDiffusionControlNetPipeline.from_pretrained(
            '''runwayml/stable-diffusion-v1-5'''      , controlnet=A__      , from_pt=A__      , dtype=jnp.bfloataa		)
        _snake_case						=							controlnet_params

        _snake_case						=							'''Chef in the kitchen'''
        _snake_case						=							jax.device_count()
        _snake_case						=							pipe.prepare_text_inputs([prompts] * num_samples		)

        _snake_case						=							load_image(
            '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/pose.png'''		)
        _snake_case						=							pipe.prepare_image_inputs([pose_image] * num_samples		)

        _snake_case						=							jax.random.PRNGKey(0		)
        _snake_case						=							jax.random.split(A__      , jax.device_count()		)

        _snake_case						=							replicate(A__		)
        _snake_case						=							shard(A__		)
        _snake_case						=							shard(A__		)

        _snake_case						=							pipe(
            prompt_ids=A__      , image=A__      , params=A__      , prng_seed=A__      , num_inference_steps=50      , jit=A__      , ).images
        assert images.shape == (jax.device_count(), 1, 768, 512, 3)

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

        _snake_case						=							jnp.asarray(jax.device_get(image_slice.flatten()		)		)
        _snake_case						=							jnp.array(
            [[0.27_1484, 0.26_1719, 0.27_5391, 0.27_7344, 0.27_9297, 0.29_1016, 0.29_4922, 0.30_2734, 0.30_2734]]		)
        print(f"""output_slice: {output_slice}"""		)
        assert jnp.abs(output_slice - expected_slice		).max() < 1e-2




from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter



def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase = 1 / sqrt(2					)					)							->     IIRFilter:



  """simple docstring"""






  _snake_case						=							tau * frequency / samplerate
  _snake_case						=							sin(_UpperCamelCase					)
  _snake_case						=							cos(_UpperCamelCase					)
  _snake_case						=							_sin / (2 * q_factor)

  _snake_case						=							(1 - _cos) / 2
  _snake_case						=							1 - _cos

  _snake_case						=							1 + alpha
  _snake_case						=							-2 * _cos
  _snake_case						=							1 - alpha

  _snake_case						=							IIRFilter(2					)
  filt.set_coefficients([aa, aa, aa]			,	[ba, ba, ba]					)
  return filt



def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase = 1 / sqrt(2					)					)							->     IIRFilter:



  """simple docstring"""






  _snake_case						=							tau * frequency / samplerate
  _snake_case						=							sin(_UpperCamelCase					)
  _snake_case						=							cos(_UpperCamelCase					)
  _snake_case						=							_sin / (2 * q_factor)

  _snake_case						=							(1 + _cos) / 2
  _snake_case						=							-1 - _cos

  _snake_case						=							1 + alpha
  _snake_case						=							-2 * _cos
  _snake_case						=							1 - alpha

  _snake_case						=							IIRFilter(2					)
  filt.set_coefficients([aa, aa, aa]			,	[ba, ba, ba]					)
  return filt



def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase = 1 / sqrt(2					)					)							->     IIRFilter:



  """simple docstring"""






  _snake_case						=							tau * frequency / samplerate
  _snake_case						=							sin(_UpperCamelCase					)
  _snake_case						=							cos(_UpperCamelCase					)
  _snake_case						=							_sin / (2 * q_factor)

  _snake_case						=							_sin / 2
  _snake_case						=							0
  _snake_case						=							-ba

  _snake_case						=							1 + alpha
  _snake_case						=							-2 * _cos
  _snake_case						=							1 - alpha

  _snake_case						=							IIRFilter(2					)
  filt.set_coefficients([aa, aa, aa]			,	[ba, ba, ba]					)
  return filt



def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase = 1 / sqrt(2					)					)							->     IIRFilter:



  """simple docstring"""






  _snake_case						=							tau * frequency / samplerate
  _snake_case						=							sin(_UpperCamelCase					)
  _snake_case						=							cos(_UpperCamelCase					)
  _snake_case						=							_sin / (2 * q_factor)

  _snake_case						=							1 - alpha
  _snake_case						=							-2 * _cos
  _snake_case						=							1 + alpha

  _snake_case						=							IIRFilter(2					)
  filt.set_coefficients([ba, ba, ba]			,	[ba, ba, ba]					)
  return filt



def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase = 1 / sqrt(2					)			,	)							->     IIRFilter:



  """simple docstring"""






  _snake_case						=							tau * frequency / samplerate
  _snake_case						=							sin(_UpperCamelCase					)
  _snake_case						=							cos(_UpperCamelCase					)
  _snake_case						=							_sin / (2 * q_factor)
  _snake_case						=							10 ** (gain_db / 40)

  _snake_case						=							1 + alpha * big_a
  _snake_case						=							-2 * _cos
  _snake_case						=							1 - alpha * big_a
  _snake_case						=							1 + alpha / big_a
  _snake_case						=							-2 * _cos
  _snake_case						=							1 - alpha / big_a

  _snake_case						=							IIRFilter(2					)
  filt.set_coefficients([aa, aa, aa]			,	[ba, ba, ba]					)
  return filt



def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase = 1 / sqrt(2					)			,	)							->     IIRFilter:



  """simple docstring"""






  _snake_case						=							tau * frequency / samplerate
  _snake_case						=							sin(_UpperCamelCase					)
  _snake_case						=							cos(_UpperCamelCase					)
  _snake_case						=							_sin / (2 * q_factor)
  _snake_case						=							10 ** (gain_db / 40)
  _snake_case						=							(big_a + 1) - (big_a - 1) * _cos
  _snake_case						=							(big_a + 1) + (big_a - 1) * _cos
  _snake_case						=							(big_a - 1) - (big_a + 1) * _cos
  _snake_case						=							(big_a - 1) + (big_a + 1) * _cos
  _snake_case						=							2 * sqrt(_UpperCamelCase					) * alpha

  _snake_case						=							big_a * (pmc + aaa)
  _snake_case						=							2 * big_a * mpc
  _snake_case						=							big_a * (pmc - aaa)
  _snake_case						=							ppmc + aaa
  _snake_case						=							-2 * pmpc
  _snake_case						=							ppmc - aaa

  _snake_case						=							IIRFilter(2					)
  filt.set_coefficients([aa, aa, aa]			,	[ba, ba, ba]					)
  return filt



def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase = 1 / sqrt(2					)			,	)							->     IIRFilter:



  """simple docstring"""






  _snake_case						=							tau * frequency / samplerate
  _snake_case						=							sin(_UpperCamelCase					)
  _snake_case						=							cos(_UpperCamelCase					)
  _snake_case						=							_sin / (2 * q_factor)
  _snake_case						=							10 ** (gain_db / 40)
  _snake_case						=							(big_a + 1) - (big_a - 1) * _cos
  _snake_case						=							(big_a + 1) + (big_a - 1) * _cos
  _snake_case						=							(big_a - 1) - (big_a + 1) * _cos
  _snake_case						=							(big_a - 1) + (big_a + 1) * _cos
  _snake_case						=							2 * sqrt(_UpperCamelCase					) * alpha

  _snake_case						=							big_a * (ppmc + aaa)
  _snake_case						=							-2 * big_a * pmpc
  _snake_case						=							big_a * (ppmc - aaa)
  _snake_case						=							pmc + aaa
  _snake_case						=							2 * mpc
  _snake_case						=							pmc - aaa

  _snake_case						=							IIRFilter(2					)
  filt.set_coefficients([aa, aa, aa]			,	[ba, ba, ba]					)
  return filt

