
'''simple docstring'''







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 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											return F'''gaussian_noise_s={seed}_shape={'_'.join([str(__SCREAMING_SNAKE_CASE		) for s in shape]		)}.npy'''






					def 	_snake_case    (   self		):


											"""simple docstring"""





											super().tearDown()
											gc.collect()






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE=0				,							__SCREAMING_SNAKE_CASE=(4, 4, 64, 64)				,							__SCREAMING_SNAKE_CASE=False		):


											"""simple docstring"""





											lowercase_	:     Any													=       jnp.bfloataa if fpaa else jnp.floataa
											lowercase_	:     int													=       jnp.array(load_hf_numpy(self.get_file_format(__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE		)		)				,							dtype=__SCREAMING_SNAKE_CASE		)
											return image






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE=False				,							__SCREAMING_SNAKE_CASE="CompVis/stable-diffusion-v1-4"		):


											"""simple docstring"""





											lowercase_	:     Union[str, Any]													=       jnp.bfloataa if fpaa else jnp.floataa
											lowercase_	:     Union[str, Any]													=       '''bf16''' if fpaa else None

											lowercase_						, lowercase_	:     Dict													=       FlaxUNetaDConditionModel.from_pretrained(
											    __SCREAMING_SNAKE_CASE				,							subfolder='''unet'''				,							dtype=__SCREAMING_SNAKE_CASE				,							revision=__SCREAMING_SNAKE_CASE		)
											return model, params






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE=0				,							__SCREAMING_SNAKE_CASE=(4, 77, 7_68)				,							__SCREAMING_SNAKE_CASE=False		):


											"""simple docstring"""





											lowercase_	:     Optional[Any]													=       jnp.bfloataa if fpaa else jnp.floataa
											lowercase_	:     List[str]													=       jnp.array(load_hf_numpy(self.get_file_format(__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE		)		)				,							dtype=__SCREAMING_SNAKE_CASE		)
											return hidden_states






					@parameterized.expand(
					    [
					        # fmt: off
					        [83, 4, [-0.2_323, -0.1_304, 0.0_813, -0.3_093, -0.0_919, -0.1_571, -0.1_125, -0.5_806]],
					        [17, 0.55, [-0.0_831, -0.2_443, 0.0_901, -0.0_919, 0.3_396, 0.0_103, -0.3_743, 0.0_701]],
					        [8, 0.89, [-0.4_863, 0.0_859, 0.0_875, -0.1_658, 0.9_199, -0.0_114, 0.4_839, 0.4_639]],
					        [3, 10_00, [-0.5_649, 0.2_402, -0.5_518, 0.1_248, 1.1_328, -0.2_443, -0.0_325, -1.0_078]],
					        # fmt: on
					    ]		)
					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											lowercase_						, lowercase_	:     Tuple													=       self.get_unet_model(model_id='''CompVis/stable-diffusion-v1-4'''				,							fpaa=__SCREAMING_SNAKE_CASE		)
											lowercase_	:     Any													=       self.get_latents(__SCREAMING_SNAKE_CASE				,							fpaa=__SCREAMING_SNAKE_CASE		)
											lowercase_	:     Optional[Any]													=       self.get_encoder_hidden_states(__SCREAMING_SNAKE_CASE				,							fpaa=__SCREAMING_SNAKE_CASE		)

											lowercase_	:     Optional[Any]													=       model.apply(
											    {'''params''': params}				,							__SCREAMING_SNAKE_CASE				,							jnp.array(__SCREAMING_SNAKE_CASE				,							dtype=jnp.intaa		)				,							encoder_hidden_states=__SCREAMING_SNAKE_CASE				,							).sample

											assert sample.shape == latents.shape

											lowercase_	:     Dict													=       jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())		)				,							dtype=jnp.floataa		)
											lowercase_	:     Tuple													=       jnp.array(__SCREAMING_SNAKE_CASE				,							dtype=jnp.floataa		)

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






					@parameterized.expand(
					    [
					        # fmt: off
					        [83, 4, [0.1_514, 0.0_807, 0.1_624, 0.1_016, -0.1_896, 0.0_263, 0.0_677, 0.2_310]],
					        [17, 0.55, [0.1_164, -0.0_216, 0.0_170, 0.1_589, -0.3_120, 0.1_005, -0.0_581, -0.1_458]],
					        [8, 0.89, [-0.1_758, -0.0_169, 0.1_004, -0.1_411, 0.1_312, 0.1_103, -0.1_996, 0.2_139]],
					        [3, 10_00, [0.1_214, 0.0_352, -0.0_731, -0.1_562, -0.0_994, -0.0_906, -0.2_340, -0.0_539]],
					        # fmt: on
					    ]		)
					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											lowercase_						, lowercase_	:     Union[str, Any]													=       self.get_unet_model(model_id='''stabilityai/stable-diffusion-2'''				,							fpaa=__SCREAMING_SNAKE_CASE		)
											lowercase_	:     List[Any]													=       self.get_latents(__SCREAMING_SNAKE_CASE				,							shape=(4, 4, 96, 96)				,							fpaa=__SCREAMING_SNAKE_CASE		)
											lowercase_	:     Optional[Any]													=       self.get_encoder_hidden_states(__SCREAMING_SNAKE_CASE				,							shape=(4, 77, 10_24)				,							fpaa=__SCREAMING_SNAKE_CASE		)

											lowercase_	:     Optional[Any]													=       model.apply(
											    {'''params''': params}				,							__SCREAMING_SNAKE_CASE				,							jnp.array(__SCREAMING_SNAKE_CASE				,							dtype=jnp.intaa		)				,							encoder_hidden_states=__SCREAMING_SNAKE_CASE				,							).sample

											assert sample.shape == latents.shape

											lowercase_	:     Optional[int]													=       jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())		)				,							dtype=jnp.floataa		)
											lowercase_	:     List[Any]													=       jnp.array(__SCREAMING_SNAKE_CASE				,							dtype=jnp.floataa		)

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






"""simple docstring"""





def   _A  (  UpperCamelCase_     :       Any)	->						List[str]:
   '''simple docstring'''


   __lowercase		,__lowercase								=						[], []
   while len(UpperCamelCase_) > 1:
      __lowercase		,__lowercase								=						min(UpperCamelCase_), max(UpperCamelCase_)
      start.append(UpperCamelCase_)
      end.append(UpperCamelCase_)
      collection.remove(UpperCamelCase_)
      collection.remove(UpperCamelCase_)
   end.reverse()
   return start + collection + end


if __name__ == "__main__":
   _a       =							input('Enter numbers separated by a comma:\n').strip()
   _a       =							[int(item) for item in user_input.split(',')]
   print(*merge_sort(unsorted), sep=',')




