




import logging
import os
from logging import (
    CRITICAL,  # NOQA
    DEBUG,  # NOQA
    ERROR,  # NOQA
    FATAL,  # NOQA
    INFO,  # NOQA
    NOTSET,  # NOQA
    WARN,  # NOQA
    WARNING,  # NOQA
)
from typing import Optional

from tqdm import auto as tqdm_lib


__UpperCamelCase   :			Any          = {
    "debug": logging.DEBUG,
    "info": logging.INFO,
    "warning": logging.WARNING,
    "error": logging.ERROR,
    "critical": logging.CRITICAL,
}

__UpperCamelCase   :			List[Any]          = logging.WARNING





def 						__A						(      ) ->			Tuple:
	a									=				os.getenv("""DATASETS_VERBOSITY"""				,     __lowerCamelCase       )
	if env_level_str:
		if env_level_str in log_levels:
			return log_levels[env_level_str]
		else:
			logging.getLogger().warning(
			    f'Unknown option DATASETS_VERBOSITY={env_level_str}, '
			    f'has to be one of: { ", ".join(log_levels.keys()       ) }'       )
	return _default_log_level





def 						__A						(      ) ->			str:
	return __name__.split("""."""       )[0]





def 						__A						(      ) ->			logging.Logger:
	return logging.getLogger(_get_library_name()       )





def 						__A						(      ) ->			None:
	# Apply our default configuration to the library root logger.
	a									=				_get_library_root_logger()
	library_root_logger.setLevel(_get_default_logging_level()       )





def 						__A						(      ) ->			None:
	a									=				_get_library_root_logger()
	library_root_logger.setLevel(logging.NOTSET       )





def 						__A						(      __lowerCamelCase = None       ) ->			logging.Logger:
	if name is None:
		a									=				_get_library_name()
	return logging.getLogger(__lowerCamelCase       )





def 						__A						(      ) ->			int:
	return _get_library_root_logger().getEffectiveLevel()





def 						__A						(      __lowerCamelCase       ) ->			None:
	_get_library_root_logger().setLevel(__lowerCamelCase       )





def 						__A						(      ) ->			Optional[Any]:
	return set_verbosity(__lowerCamelCase       )





def 						__A						(      ) ->			List[Any]:
	return set_verbosity(__lowerCamelCase       )





def 						__A						(      ) ->			str:
	return set_verbosity(__lowerCamelCase       )





def 						__A						(      ) ->			Union[str, Any]:
	return set_verbosity(__lowerCamelCase       )





def 						__A						(      ) ->			None:
	a									=				False





def 						__A						(      ) ->			None:
	a									=				True


# Configure the library root logger at the module level (singleton-like)
_configure_library_root_logger()

class 						__lowerCAmelCase      :
							def __init__(		self		:List[Any]						, *__magic_name__		:Union[str, Any]						, **__magic_name__		:Any							):  # pylint: disable=unused-argument







								'''simple docstring'''







								a									=				args[0] if args else None
							def __iter__(		self		:str							):







								'''simple docstring'''







								return iter(self._iterator							)
							def __getattr__(		self		:str						, __magic_name__		:Union[str, Any]							):







								'''simple docstring'''







								def empty_fn(*__magic_name__		:Optional[int]						, **__magic_name__		:List[str]							):  # pylint: disable=unused-argument
									return

								return empty_fn
							def __enter__(		self		:str							):







								'''simple docstring'''







								return self





							def __exit__(		self		:Optional[int]						, __magic_name__		:Dict						, __magic_name__		:List[str]						, __magic_name__		:Optional[int]							):







								'''simple docstring'''







								return







__UpperCamelCase   :			Dict          = True

class 						__lowerCAmelCase      :
							def __call__(		self		:List[Any]						, *__magic_name__		:Optional[int]						, __magic_name__		:List[Any]=False						, **__magic_name__		:int							):







								'''simple docstring'''







								if _tqdm_active and not disable:
									return tqdm_lib.tqdm(*__magic_name__						, **__magic_name__							)
								else:
									return EmptyTqdm(*__magic_name__						, **__magic_name__							)
							def  lowerCamelCase__				(		self		:str						, *__magic_name__		:List[str]						, **__magic_name__		:int							):







								'''simple docstring'''







								a									=				None
								if _tqdm_active:
									return tqdm_lib.tqdm.set_lock(*__magic_name__						, **__magic_name__							)





							def  lowerCamelCase__				(		self		:List[Any]							):







								'''simple docstring'''







								if _tqdm_active:
									return tqdm_lib.tqdm.get_lock()







__UpperCamelCase   :			Tuple          = _tqdm_cls()





def 						__A						(      ) ->			bool:
	global _tqdm_active
	return bool(_tqdm_active       )





def 						__A						(      ) ->			str:
	global _tqdm_active
	a									=				True





def 						__A						(      ) ->			Dict:
	global _tqdm_active
	a									=				False







import gc
import unittest

from parameterized import parameterized

from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow


if is_flax_available():
		import jax
		import jax.numpy as jnp

@slow
@require_flax
class 						__lowerCAmelCase      (      unittest.TestCase					):
							def  lowerCamelCase__				(		self		:Tuple						, __magic_name__		:int						, __magic_name__		:Optional[Any]							):







								'''simple docstring'''







								return F'gaussian_noise_s={seed}_shape={"_".join([str(__magic_name__							) for s in shape]							)}.npy'
							def  lowerCamelCase__				(		self		:List[str]							):







								'''simple docstring'''







								super().tearDown()
								gc.collect()
							def  lowerCamelCase__				(		self		:int						, __magic_name__		:List[str]=0						, __magic_name__		:List[Any]=(4, 4, 64, 64)						, __magic_name__		:Optional[int]=False							):







								'''simple docstring'''







								a									=				jnp.bfloataa if fpaa else jnp.floataa
								a									=				jnp.array(load_hf_numpy(self.get_file_format(__magic_name__						, __magic_name__							)							)						, dtype=__magic_name__							)
								return image
							def  lowerCamelCase__				(		self		:Any						, __magic_name__		:int=False						, __magic_name__		:List[str]="CompVis/stable-diffusion-v1-4"							):







								'''simple docstring'''







								a									=				jnp.bfloataa if fpaa else jnp.floataa
								a									=				"""bf16""" if fpaa else None

								a							,					a									=				FlaxUNetaDConditionModel.from_pretrained(
								    __magic_name__						, subfolder="""unet"""						, dtype=__magic_name__						, revision=__magic_name__							)
								return model, params
							def  lowerCamelCase__				(		self		:Optional[Any]						, __magic_name__		:Union[str, Any]=0						, __magic_name__		:Any=(4, 77, 768)						, __magic_name__		:Optional[Any]=False							):







								'''simple docstring'''







								a									=				jnp.bfloataa if fpaa else jnp.floataa
								a									=				jnp.array(load_hf_numpy(self.get_file_format(__magic_name__						, __magic_name__							)							)						, dtype=__magic_name__							)
								return hidden_states
							@parameterized.expand(
							    [
							        # fmt: off
							        [83, 4, [-0.2323, -0.1304, 0.0813, -0.3093, -0.0919, -0.1571, -0.1125, -0.5806]],
							        [17, 0.55, [-0.0831, -0.2443, 0.0901, -0.0919, 0.3396, 0.0103, -0.3743, 0.0701]],
							        [8, 0.89, [-0.4863, 0.0859, 0.0875, -0.1658, 0.9199, -0.0114, 0.4839, 0.4639]],
							        [3, 1000, [-0.5649, 0.2402, -0.5518, 0.1248, 1.1328, -0.2443, -0.0325, -1.0078]],
							        # fmt: on
							    ]							)
							def  lowerCamelCase__				(		self		:Optional[Any]						, __magic_name__		:str						, __magic_name__		:Optional[Any]						, __magic_name__		:Optional[int]							):







								'''simple docstring'''







								a							,					a									=				self.get_unet_model(model_id="""CompVis/stable-diffusion-v1-4"""						, fpaa=__magic_name__							)
								a									=				self.get_latents(__magic_name__						, fpaa=__magic_name__							)
								a									=				self.get_encoder_hidden_states(__magic_name__						, fpaa=__magic_name__							)

								a									=				model.apply(
								    {"""params""": params}						, __magic_name__						, jnp.array(__magic_name__						, dtype=jnp.intaa							)						, encoder_hidden_states=__magic_name__						, ).sample

								assert sample.shape == latents.shape

								a									=				jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())							)						, dtype=jnp.floataa							)
								a									=				jnp.array(__magic_name__						, dtype=jnp.floataa							)

								# Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, in the same hardware
								assert jnp.allclose(__magic_name__						, __magic_name__						, atol=1E-2							)





							@parameterized.expand(
							    [
							        # fmt: off
							        [83, 4, [0.1514, 0.0807, 0.1624, 0.1016, -0.1896, 0.0263, 0.0677, 0.2310]],
							        [17, 0.55, [0.1164, -0.0216, 0.0170, 0.1589, -0.3120, 0.1005, -0.0581, -0.1458]],
							        [8, 0.89, [-0.1758, -0.0169, 0.1004, -0.1411, 0.1312, 0.1103, -0.1996, 0.2139]],
							        [3, 1000, [0.1214, 0.0352, -0.0731, -0.1562, -0.0994, -0.0906, -0.2340, -0.0539]],
							        # fmt: on
							    ]							)
							def  lowerCamelCase__				(		self		:Optional[Any]						, __magic_name__		:List[Any]						, __magic_name__		:int						, __magic_name__		:str							):







								'''simple docstring'''







								a							,					a									=				self.get_unet_model(model_id="""stabilityai/stable-diffusion-2"""						, fpaa=__magic_name__							)
								a									=				self.get_latents(__magic_name__						, shape=(4, 4, 96, 96)						, fpaa=__magic_name__							)
								a									=				self.get_encoder_hidden_states(__magic_name__						, shape=(4, 77, 1024)						, fpaa=__magic_name__							)

								a									=				model.apply(
								    {"""params""": params}						, __magic_name__						, jnp.array(__magic_name__						, dtype=jnp.intaa							)						, encoder_hidden_states=__magic_name__						, ).sample

								assert sample.shape == latents.shape

								a									=				jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())							)						, dtype=jnp.floataa							)
								a									=				jnp.array(__magic_name__						, dtype=jnp.floataa							)

								# Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, on the same hardware
								assert jnp.allclose(__magic_name__						, __magic_name__						, atol=1E-2							)

