


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  snake_case_     (unittest.TestCase   ):
					def 				lowerCamelCase__(   self     :Tuple    ,__snake_case     :Any    ,__snake_case     :Dict   )      ->					Union[str, Any]:
												return F'gaussian_noise_s={seed}_shape={"_".join([str(__snake_case   ) for s in shape]   )}.npy'
					def 				lowerCamelCase__(   self     :int   )      ->					List[Any]:
												# clean up the VRAM after each test
												super().tearDown()
												gc.collect()
					def 				lowerCamelCase__(   self     :List[Any]    ,__snake_case     :List[str]=0    ,__snake_case     :Union[str, Any]=(4, 4, 64, 64)    ,__snake_case     :Optional[int]=False   )      ->					str:
												a__    =  jnp.bfloataa if fpaa else jnp.floataa
												a__    =  jnp.array(load_hf_numpy(self.get_file_format(__snake_case    ,__snake_case   )   )    ,dtype=__snake_case   )
												return image
					def 				lowerCamelCase__(   self     :str    ,__snake_case     :Union[str, Any]=False    ,__snake_case     :List[str]="CompVis/stable-diffusion-v1-4"   )      ->					Optional[int]:
												a__    =  jnp.bfloataa if fpaa else jnp.floataa
												a__    =  'bf16' if fpaa else None

												a__   ,      a__    =  FlaxUNetaDConditionModel.from_pretrained(
												    __snake_case    ,subfolder='unet'    ,dtype=__snake_case    ,revision=__snake_case   )
												return model, params
					def 				lowerCamelCase__(   self     :int    ,__snake_case     :Union[str, Any]=0    ,__snake_case     :str=(4, 77, 7_68)    ,__snake_case     :str=False   )      ->					Optional[Any]:
												a__    =  jnp.bfloataa if fpaa else jnp.floataa
												a__    =  jnp.array(load_hf_numpy(self.get_file_format(__snake_case    ,__snake_case   )   )    ,dtype=__snake_case   )
												return hidden_states
					@parameterized.expand(
					    [
					        # fmt: off
					        [83, 4, [-0.23_23, -0.13_04, 0.08_13, -0.30_93, -0.09_19, -0.15_71, -0.11_25, -0.58_06]],
					        [17, 0.55, [-0.08_31, -0.24_43, 0.09_01, -0.09_19, 0.33_96, 0.01_03, -0.37_43, 0.07_01]],
					        [8, 0.89, [-0.48_63, 0.08_59, 0.08_75, -0.16_58, 0.91_99, -0.01_14, 0.48_39, 0.46_39]],
					        [3, 10_00, [-0.56_49, 0.24_02, -0.55_18, 0.12_48, 1.13_28, -0.24_43, -0.03_25, -1.00_78]],
					        # fmt: on
					    ]   )
					def 				lowerCamelCase__(   self     :Any    ,__snake_case     :Any    ,__snake_case     :Dict    ,__snake_case     :str   )      ->					Optional[int]:
												a__   ,      a__    =  self.get_unet_model(model_id='CompVis/stable-diffusion-v1-4'    ,fpaa=__snake_case   )
												a__    =  self.get_latents(__snake_case    ,fpaa=__snake_case   )
												a__    =  self.get_encoder_hidden_states(__snake_case    ,fpaa=__snake_case   )

												a__    =  model.apply(
												    {'params': params}    ,__snake_case    ,jnp.array(__snake_case    ,dtype=jnp.intaa   )    ,encoder_hidden_states=__snake_case    ,).sample

												assert sample.shape == latents.shape

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

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



					@parameterized.expand(
					    [
					        # fmt: off
					        [83, 4, [0.15_14, 0.08_07, 0.16_24, 0.10_16, -0.18_96, 0.02_63, 0.06_77, 0.23_10]],
					        [17, 0.55, [0.11_64, -0.02_16, 0.01_70, 0.15_89, -0.31_20, 0.10_05, -0.05_81, -0.14_58]],
					        [8, 0.89, [-0.17_58, -0.01_69, 0.10_04, -0.14_11, 0.13_12, 0.11_03, -0.19_96, 0.21_39]],
					        [3, 10_00, [0.12_14, 0.03_52, -0.07_31, -0.15_62, -0.09_94, -0.09_06, -0.23_40, -0.05_39]],
					        # fmt: on
					    ]   )
					def 				lowerCamelCase__(   self     :str    ,__snake_case     :List[str]    ,__snake_case     :int    ,__snake_case     :List[Any]   )      ->					Union[str, Any]:
												a__   ,      a__    =  self.get_unet_model(model_id='stabilityai/stable-diffusion-2'    ,fpaa=__snake_case   )
												a__    =  self.get_latents(__snake_case    ,shape=(4, 4, 96, 96)    ,fpaa=__snake_case   )
												a__    =  self.get_encoder_hidden_states(__snake_case    ,shape=(4, 77, 10_24)    ,fpaa=__snake_case   )

												a__    =  model.apply(
												    {'params': params}    ,__snake_case    ,jnp.array(__snake_case    ,dtype=jnp.intaa   )    ,encoder_hidden_states=__snake_case    ,).sample

												assert sample.shape == latents.shape

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

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








import unittest

from knapsack import greedy_knapsack as kp







class  snake_case_     (unittest.TestCase   ):
					def 				lowerCamelCase__(   self     :Optional[Any]   )      ->					Union[str, Any]:
												a__    =  [10, 20, 30, 40, 50, 60]
												a__    =  [2, 4, 6, 8, 10, 12]
												a__    =  1_00
												self.assertEqual(kp.calc_profit(__snake_case    ,__snake_case    ,__snake_case   )    ,2_10   )
					def 				lowerCamelCase__(   self     :str   )      ->					Optional[int]:
												self.assertRaisesRegex(__snake_case    ,'max_weight must greater than zero.'   )
					def 				lowerCamelCase__(   self     :Optional[Any]   )      ->					int:
												self.assertRaisesRegex(__snake_case    ,'Weight can not be negative.'   )
					def 				lowerCamelCase__(   self     :str   )      ->					List[str]:
												self.assertRaisesRegex(__snake_case    ,'Profit can not be negative.'   )
					def 				lowerCamelCase__(   self     :str   )      ->					Optional[Any]:
												self.assertRaisesRegex(__snake_case    ,'max_weight must greater than zero.'   )



					def 				lowerCamelCase__(   self     :int   )      ->					List[Any]:
												self.assertRaisesRegex(
												    __snake_case    ,'The length of profit and weight must be same.'   )


if __name__ == "__main__":
						unittest.main()




