




import gc
import unittest

from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, 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 		snake_case	(			self ):
							# clean up the VRAM after each test
							super().tearDown()
							gc.collect()






				def 		snake_case	(			self ):
							SCREAMING_SNAKE_CASE_  ,    SCREAMING_SNAKE_CASE_   : List[Any]					  =      FlaxStableDiffusionPipeline.from_pretrained(
							    'stabilityai/stable-diffusion-2'      ,revision='bf16'      ,dtype=jnp.bfloataa      ,)

							SCREAMING_SNAKE_CASE_   : List[str]					  =      'A painting of a squirrel eating a burger'
							SCREAMING_SNAKE_CASE_   : str					  =      jax.device_count()
							SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      num_samples * [prompt]
							SCREAMING_SNAKE_CASE_   : Any					  =      sd_pipe.prepare_inputs(snake_case__ )

							SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      replicate(snake_case__ )
							SCREAMING_SNAKE_CASE_   : Optional[int]					  =      shard(snake_case__ )

							SCREAMING_SNAKE_CASE_   : Optional[int]					  =      jax.random.PRNGKey(0 )
							SCREAMING_SNAKE_CASE_   : Dict					  =      jax.random.split(snake_case__      ,jax.device_count() )

							SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      sd_pipe(snake_case__      ,snake_case__      ,snake_case__      ,num_inference_steps=25      ,jit=snake_case__ )[0]
							assert images.shape == (jax.device_count(), 1, 768, 768, 3)

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

							SCREAMING_SNAKE_CASE_   : List[str]					  =      jnp.asarray(jax.device_get(image_slice.flatten() ) )
							SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      jnp.array([0.4238, 0.4414, 0.4395, 0.4453, 0.4629, 0.4590, 0.4531, 0.45508, 0.4512] )
							print(F'output_slice: {output_slice}' )
							assert jnp.abs(output_slice - expected_slice ).max() < 1E-2






				def 		snake_case	(			self ):
							SCREAMING_SNAKE_CASE_   : Dict					  =      'stabilityai/stable-diffusion-2'
							SCREAMING_SNAKE_CASE_  ,    SCREAMING_SNAKE_CASE_   : List[Any]					  =      FlaxDPMSolverMultistepScheduler.from_pretrained(snake_case__      ,subfolder='scheduler' )
							SCREAMING_SNAKE_CASE_  ,    SCREAMING_SNAKE_CASE_   : Optional[int]					  =      FlaxStableDiffusionPipeline.from_pretrained(
							    snake_case__      ,scheduler=snake_case__      ,revision='bf16'      ,dtype=jnp.bfloataa      ,)
							SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      scheduler_params

							SCREAMING_SNAKE_CASE_   : Tuple					  =      'A painting of a squirrel eating a burger'
							SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      jax.device_count()
							SCREAMING_SNAKE_CASE_   : Tuple					  =      num_samples * [prompt]
							SCREAMING_SNAKE_CASE_   : List[str]					  =      sd_pipe.prepare_inputs(snake_case__ )

							SCREAMING_SNAKE_CASE_   : List[Any]					  =      replicate(snake_case__ )
							SCREAMING_SNAKE_CASE_   : Any					  =      shard(snake_case__ )

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

							SCREAMING_SNAKE_CASE_   : Dict					  =      sd_pipe(snake_case__      ,snake_case__      ,snake_case__      ,num_inference_steps=25      ,jit=snake_case__ )[0]
							assert images.shape == (jax.device_count(), 1, 768, 768, 3)

							SCREAMING_SNAKE_CASE_   : List[str]					  =      images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:] )
							SCREAMING_SNAKE_CASE_   : Tuple					  =      images[0, 253:256, 253:256, -1]

							SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      jnp.asarray(jax.device_get(image_slice.flatten() ) )
							SCREAMING_SNAKE_CASE_   : List[Any]					  =      jnp.array([0.4336, 0.42969, 0.4453, 0.4199, 0.4297, 0.4531, 0.4434, 0.4434, 0.4297] )
							print(F'output_slice: {output_slice}' )
							assert jnp.abs(output_slice - expected_slice ).max() < 1E-2









from typing import List

from .keymap import KEYMAP, get_character




def 		lowerCAmelCase_ (						lowerCamelCase ):

				def decorator(lowerCamelCase ):
								__magic_name__						:						str										=getattr(lowerCamelCase						,  """handle_key"""						,  [] )
								handle += [key]
								setattr(lowerCamelCase						,  """handle_key"""						,  lowerCamelCase )
								return func

				return decorator




def 		lowerCAmelCase_ (						*lowerCamelCase ):

				def decorator(lowerCamelCase ):
								__magic_name__						:						Dict										=getattr(lowerCamelCase						,  """handle_key"""						,  [] )
								handle += keys
								setattr(lowerCamelCase						,  """handle_key"""						,  lowerCamelCase )
								return func

				return decorator




class 		__A   (      UpperCamelCase__      ):

						def __new__(		cls :Dict     ,			__snake_case :Optional[Any]     ,			__snake_case :Union[str, Any]     ,			__snake_case :List[str]			):
										'''simple docstring'''

										__magic_name__						:						int										=super().__new__(cls     ,			__snake_case     ,			__snake_case     ,			__snake_case			)
										if not hasattr(__snake_case     ,			"""key_handler"""			):
														setattr(__snake_case     ,			"""key_handler"""     ,			{}			)
										setattr(__snake_case     ,			"""handle_input"""     ,			KeyHandler.handle_input			)

										for value in attrs.values():
														__magic_name__						:						int										=getattr(__snake_case     ,			"""handle_key"""     ,			[]			)
														for key in handled_keys:
																		__magic_name__						:						List[str]										=value
										return new_cls


						@staticmethod
						def      A__    (		cls :Optional[int]			):
										'''simple docstring'''

										__magic_name__						:						Union[str, Any]										=get_character()
										if char != KEYMAP["undefined"]:
														__magic_name__						:						Optional[int]										=ord(__snake_case			)
										__magic_name__						:						int										=cls.key_handler.get(__snake_case			)
										if handler:
														__magic_name__						:						Dict										=char
														return handler(cls			)
										else:
														return None




def 		lowerCAmelCase_ (						cls ):
				return KeyHandler(cls.__name__						,  cls.__bases__						,  cls.__dict__.copy() )




