






"""simple docstring"""



_lowerCAmelCase	:	dict[str, float]				=      {
    "km/h": 1.0,
    "m/s": 3.6,
    "mph": 1.60_93_44,
    "knot": 1.8_52,
}

_lowerCAmelCase	:	dict[str, float]				=      {
    "km/h": 1.0,
    "m/s": 0.2_77_77_77_78,
    "mph": 0.6_21_37_11_92,
    "knot": 0.5_39_95_68_03,
}


def 	SCREAMING_SNAKE_CASE__       (  snake_case       : float			,					snake_case       : str			,					snake_case       : str				)->		float:






     '''simple docstring'''



     if unit_to not in speed_chart or unit_from not in speed_chart_inverse:
          UpperCAmelCase__						:    Tuple							=							(
              f'Incorrect \'from_type\' or \'to_type\' value: {unit_from!r}, {unit_to!r}\n'
              f'Valid values are: {", ".join(snake_case				)}'
          )
          raise ValueError(snake_case				)
     return round(speed * speed_chart[unit_from] * speed_chart_inverse[unit_to]			,					3				)


if __name__ == "__main__":
 import doctest

 doctest.testmod()










"""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 			lowerCAmelCase__			(    unittest.TestCase   ):
   def       __a							(		self      :	Optional[int]							):


        '''simple docstring'''
        # clean up the VRAM after each test
        super().tearDown()
        gc.collect()




   def       __a							(		self      :	List[str]							):


        '''simple docstring'''
        UpperCAmelCase__						:    Optional[int]							=							load_image(
            "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
            "/sd2-inpaint/init_image.png"							)
        UpperCAmelCase__						:    Any							=							load_image(
            "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd2-inpaint/mask.png"							)

        UpperCAmelCase__						:    str							=							"xvjiarui/stable-diffusion-2-inpainting"
        UpperCAmelCase__							,				UpperCAmelCase__						:    List[Any]							=							FlaxStableDiffusionInpaintPipeline.from_pretrained(snake_case__							,			safety_checker=snake_case__							)

        UpperCAmelCase__						:    List[str]							=							"Face of a yellow cat, high resolution, sitting on a park bench"

        UpperCAmelCase__						:    List[str]							=							jax.random.PRNGKey(0							)
        UpperCAmelCase__						:    Optional[int]							=							5_0

        UpperCAmelCase__						:    List[Any]							=							jax.device_count()
        UpperCAmelCase__						:    int							=							num_samples * [prompt]
        UpperCAmelCase__						:    str							=							num_samples * [init_image]
        UpperCAmelCase__						:    Optional[Any]							=							num_samples * [mask_image]
        UpperCAmelCase__							,				UpperCAmelCase__							,				UpperCAmelCase__						:    Optional[int]							=							pipeline.prepare_inputs(snake_case__							,			snake_case__							,			snake_case__							)

        # shard inputs and rng
        UpperCAmelCase__						:    Dict							=							replicate(snake_case__							)
        UpperCAmelCase__						:    Dict							=							jax.random.split(snake_case__							,			jax.device_count()							)
        UpperCAmelCase__						:    List[str]							=							shard(snake_case__							)
        UpperCAmelCase__						:    str							=							shard(snake_case__							)
        UpperCAmelCase__						:    Optional[int]							=							shard(snake_case__							)

        UpperCAmelCase__						:    Dict							=							pipeline(
            snake_case__							,			snake_case__							,			snake_case__							,			snake_case__							,			snake_case__							,			snake_case__							,			jit=snake_case__							)

        UpperCAmelCase__						:    List[str]							=							output.images.reshape(snake_case__							,			5_1_2							,			5_1_2							,			3							)

        UpperCAmelCase__						:    Tuple							=							images[0, 2_5_3:2_5_6, 2_5_3:2_5_6, -1]

        UpperCAmelCase__						:    str							=							jnp.asarray(jax.device_get(image_slice.flatten()							)							)
        UpperCAmelCase__						:    int							=							jnp.array(
            [0.361_1307, 0.3764_9736, 0.375_7408, 0.3821_3953, 0.3929_5167, 0.384_1631, 0.4155_4978, 0.413_7475, 0.421_7084]							)
        print(f'output_slice: {output_slice}'							)
        assert jnp.abs(output_slice - expected_slice							).max() < 1e-2


