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			):






    '''simple docstring'''




    def      _a    (    self ):
       super().tearDown()
       gc.collect()




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

       lowerCAmelCase_:							Any       =	'''bird'''
       lowerCAmelCase_:							str       =	jax.device_count()
       lowerCAmelCase_:							int       =	pipe.prepare_text_inputs([prompts] * num_samples )

       lowerCAmelCase_:							Optional[Any]       =	load_image(
           "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/bird_canny.png" )
       lowerCAmelCase_:							Union[str, Any]       =	pipe.prepare_image_inputs([canny_image] * num_samples )

       lowerCAmelCase_:							List[str]       =	jax.random.PRNGKey(0 )
       lowerCAmelCase_:							Tuple       =	jax.random.split(UpperCamelCase_       ,						jax.device_count() )

       lowerCAmelCase_:							Union[str, Any]       =	replicate(UpperCamelCase_ )
       lowerCAmelCase_:							Dict       =	shard(UpperCamelCase_ )
       lowerCAmelCase_:							str       =	shard(UpperCamelCase_ )

       lowerCAmelCase_:							List[Any]       =	pipe(
           prompt_ids=UpperCamelCase_       ,						image=UpperCamelCase_       ,						params=UpperCamelCase_       ,						prng_seed=UpperCamelCase_       ,						num_inference_steps=50       ,						jit=UpperCamelCase_       ,						).images
       assert images.shape == (jax.device_count(), 1, 768, 512, 3)

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

       lowerCAmelCase_:							Union[str, Any]       =	jnp.asarray(jax.device_get(image_slice.flatten() ) )
       lowerCAmelCase_:							int       =	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      _a    (    self ):
       lowerCAmelCase_:							Union[str, Any]       =	FlaxControlNetModel.from_pretrained(
           "lllyasviel/sd-controlnet-openpose"       ,						from_pt=UpperCamelCase_       ,						dtype=jnp.bfloataa )
       lowerCAmelCase_:							List[Any]       =	FlaxStableDiffusionControlNetPipeline.from_pretrained(
           "runwayml/stable-diffusion-v1-5"       ,						controlnet=UpperCamelCase_       ,						from_pt=UpperCamelCase_       ,						dtype=jnp.bfloataa )
       lowerCAmelCase_:							Any       =	controlnet_params

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

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

       lowerCAmelCase_:							Any       =	jax.random.PRNGKey(0 )
       lowerCAmelCase_:							Any       =	jax.random.split(UpperCamelCase_       ,						jax.device_count() )

       lowerCAmelCase_:							Optional[Any]       =	replicate(UpperCamelCase_ )
       lowerCAmelCase_:							Union[str, Any]       =	shard(UpperCamelCase_ )
       lowerCAmelCase_:							List[str]       =	shard(UpperCamelCase_ )

       lowerCAmelCase_:							Union[str, Any]       =	pipe(
           prompt_ids=UpperCamelCase_       ,						image=UpperCamelCase_       ,						params=UpperCamelCase_       ,						prng_seed=UpperCamelCase_       ,						num_inference_steps=50       ,						jit=UpperCamelCase_       ,						).images
       assert images.shape == (jax.device_count(), 1, 768, 512, 3)

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

       lowerCAmelCase_:							Any       =	jnp.asarray(jax.device_get(image_slice.flatten() ) )
       lowerCAmelCase_:							List[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

from collections import namedtuple
from dataclasses import dataclass
@dataclass
class   lowercase      :

		"""simple docstring"""

		_a       					=							42
		_a       					=							None
		_a       					=							None



__snake_case				 =	namedtuple('''CoinsDistribResult''', '''moves excess''')


def      a (     __a  )    ->      int:



					'''simple docstring'''






					if root is None:
										return 0

					# Validation
					def count_nodes(__a  ) -> int:
										if node is None:
															return 0

										return count_nodes(node.left  ) + count_nodes(node.right  ) + 1

					def count_coins(__a  ) -> int:
										if node is None:
															return 0

										return count_coins(node.left  ) + count_coins(node.right  ) + node.data

					if count_nodes(__a  ) != count_coins(__a  ):
										raise ValueError('''The nodes number should be same as the number of coins'''  )

					# Main calculation
					def get_distrib(__a  ) -> CoinsDistribResult:

										if node is None:
															return CoinsDistribResult(0					,   1  )

										UpperCamelCase__   ,							UpperCamelCase__  :Optional[Any]				   =					get_distrib(node.left  )
										UpperCamelCase__   ,							UpperCamelCase__  :Union[str, Any]				   =					get_distrib(node.right  )

										UpperCamelCase__  :Tuple				   =					1 - left_distrib_excess
										UpperCamelCase__  :Optional[int]				   =					1 - right_distrib_excess

										UpperCamelCase__  :int				   =					(
										    left_distrib_moves
										    + right_distrib_moves
										    + abs(__a  )
										    + abs(__a  )
										)
										UpperCamelCase__  :Optional[Any]				   =					node.data - coins_to_left - coins_to_right

										return CoinsDistribResult(__a					,   __a  )

					return get_distrib(__a  )[0]


if __name__ == "__main__":
		import doctest

		doctest.testmod()