
"""simple docstring"""




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 		a__						(      unittest.TestCase						):
   def 			__magic_name__			(			self				):
          # clean up the VRAM after each test
          super().tearDown()
          gc.collect()
   def 			__magic_name__			(			self				):
          lowercase		,    lowercase    :				str       		=							FlaxControlNetModel.from_pretrained(
              "lllyasviel/sd-controlnet-canny"	,    from_pt=_a	,    dtype=jnp.bfloataa				)
          lowercase		,    lowercase    :				str       		=							FlaxStableDiffusionControlNetPipeline.from_pretrained(
              "runwayml/stable-diffusion-v1-5"	,    controlnet=_a	,    from_pt=_a	,    dtype=jnp.bfloataa				)
          lowercase    :				List[Any]       		=							controlnet_params

          lowercase    :				Any       		=							"bird"
          lowercase    :				Optional[int]       		=							jax.device_count()
          lowercase    :				int       		=							pipe.prepare_text_inputs([prompts] * num_samples				)

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

          lowercase    :				List[str]       		=							jax.random.PRNGKey(0				)
          lowercase    :				str       		=							jax.random.split(_a	,    jax.device_count()				)

          lowercase    :				List[Any]       		=							replicate(_a				)
          lowercase    :				Tuple       		=							shard(_a				)
          lowercase    :				Union[str, Any]       		=							shard(_a				)

          lowercase    :				str       		=							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)

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

          lowercase    :				Optional[int]       		=							jnp.asarray(jax.device_get(image_slice.flatten()				)				)
          lowercase    :				Dict       		=							jnp.array(
              [0.1_6_7_9_6_9, 0.1_1_6_6_9_9, 0.0_8_1_5_4_3, 0.1_5_4_2_9_7, 0.1_3_2_8_1_2, 0.1_0_8_8_8_7, 0.1_6_9_9_2_2, 0.1_6_9_9_2_2, 0.2_0_5_0_7_8]				)
          print(f"""output_slice: {output_slice}"""				)
          assert jnp.abs(output_slice - expected_slice				).max() < 1E-2

   def 			__magic_name__			(			self				):
          lowercase		,    lowercase    :				Union[str, Any]       		=							FlaxControlNetModel.from_pretrained(
              "lllyasviel/sd-controlnet-openpose"	,    from_pt=_a	,    dtype=jnp.bfloataa				)
          lowercase		,    lowercase    :				str       		=							FlaxStableDiffusionControlNetPipeline.from_pretrained(
              "runwayml/stable-diffusion-v1-5"	,    controlnet=_a	,    from_pt=_a	,    dtype=jnp.bfloataa				)
          lowercase    :				Optional[Any]       		=							controlnet_params

          lowercase    :				str       		=							"Chef in the kitchen"
          lowercase    :				List[Any]       		=							jax.device_count()
          lowercase    :				int       		=							pipe.prepare_text_inputs([prompts] * num_samples				)

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

          lowercase    :				List[str]       		=							jax.random.PRNGKey(0				)
          lowercase    :				Any       		=							jax.random.split(_a	,    jax.device_count()				)

          lowercase    :				int       		=							replicate(_a				)
          lowercase    :				List[Any]       		=							shard(_a				)
          lowercase    :				Union[str, Any]       		=							shard(_a				)

          lowercase    :				Union[str, Any]       		=							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)

          lowercase    :				Union[str, Any]       		=							images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]				)
          lowercase    :				Optional[Any]       		=							images[0, 253:256, 253:256, -1]

          lowercase    :				Any       		=							jnp.asarray(jax.device_get(image_slice.flatten()				)				)
          lowercase    :				Any       		=							jnp.array(
              [[0.2_7_1_4_8_4, 0.2_6_1_7_1_9, 0.2_7_5_3_9_1, 0.2_7_7_3_4_4, 0.2_7_9_2_9_7, 0.2_9_1_0_1_6, 0.2_9_4_9_2_2, 0.3_0_2_7_3_4, 0.3_0_2_7_3_4]]				)
          print(f"""output_slice: {output_slice}"""				)
          assert jnp.abs(output_slice - expected_slice				).max() < 1E-2




"""simple docstring"""




from __future__ import annotations


def   __magic_name__	(      __snake_case				:       list[int]  ) ->				list[int]:
       if len(__snake_case  ) == 0:
              return array

       lowercase		,    lowercase    :				Tuple       		=							min(__snake_case  ), max(__snake_case  )

       # Compute the variables
       lowercase    :				Optional[Any]       		=							_max - _min + 1
       lowercase		,    lowercase    :				List[str]       		=							[0] * holes_range, [0] * holes_range

       # Make the sorting.
       for i in array:
              lowercase    :				Tuple       		=							i - _min
              lowercase    :				str       		=							i
              holes_repeat[index] += 1

       # Makes the array back by replacing the numbers.
       lowercase    :				Union[str, Any]       		=							0
       for i in range(__snake_case  ):
              while holes_repeat[i] > 0:
                     lowercase    :				Tuple       		=							holes[i]
                     index += 1
                     holes_repeat[i] -= 1

    # Returns the sorted array.
       return array


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   _A			:       str   		=       input("""Enter numbers separated by comma:\n""")
   _A			:       Optional[Any]   		=       [int(x) for x in user_input.split(""",""")]
   print(pigeon_sort(unsorted))


