





'''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 				a_       (    unittest.TestCase							):





     def 							lowercase__				(			self		: Any     ,				lowercase		: List[Any]     ,				lowercase		: List[Any]						):





        """simple docstring"""




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





     def 							lowercase__				(			self		: str						):





        """simple docstring"""




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





     def 							lowercase__				(			self		: int     ,				lowercase		: Union[str, Any]=0     ,				lowercase		: str=(4, 4, 64, 64)     ,				lowercase		: Optional[Any]=False						):





        """simple docstring"""




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





     def 							lowercase__				(			self		: Any     ,				lowercase		: int=False     ,				lowercase		: Tuple="CompVis/stable-diffusion-v1-4"						):





        """simple docstring"""




        lowercase_      :Tuple         =			jnp.bfloataa if fpaa else jnp.floataa
        lowercase_      :str         =			"bf16" if fpaa else None

        lowercase_      ,							lowercase_      :int         =			FlaxUNetaDConditionModel.from_pretrained(
            lowercase     ,				subfolder="unet"     ,				dtype=lowercase     ,				revision=lowercase						)
        return model, params





     def 							lowercase__				(			self		: int     ,				lowercase		: Dict=0     ,				lowercase		: int=(4, 77, 768)     ,				lowercase		: List[Any]=False						):





        """simple docstring"""




        lowercase_      :Optional[Any]         =			jnp.bfloataa if fpaa else jnp.floataa
        lowercase_      :Dict         =			jnp.array(load_hf_numpy(self.get_file_format(lowercase     ,				lowercase						)						)     ,				dtype=lowercase						)
        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, 1_000, [-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 							lowercase__				(			self		: List[Any]     ,				lowercase		: List[str]     ,				lowercase		: Optional[Any]     ,				lowercase		: List[str]						):





        """simple docstring"""




        lowercase_      ,							lowercase_      :int         =			self.get_unet_model(model_id="CompVis/stable-diffusion-v1-4"     ,				fpaa=lowercase						)
        lowercase_      :Union[str, Any]         =			self.get_latents(lowercase     ,				fpaa=lowercase						)
        lowercase_      :Optional[Any]         =			self.get_encoder_hidden_states(lowercase     ,				fpaa=lowercase						)

        lowercase_      :List[str]         =			model.apply(
            {"params": params}     ,				lowercase     ,				jnp.array(lowercase     ,				dtype=jnp.intaa						)     ,				encoder_hidden_states=lowercase     ,				).sample

        assert sample.shape == latents.shape

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

        # Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, in the same hardware
        assert jnp.allclose(lowercase     ,				lowercase     ,				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, 1_000, [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 							lowercase__				(			self		: Any     ,				lowercase		: List[Any]     ,				lowercase		: Optional[int]     ,				lowercase		: Any						):





        """simple docstring"""




        lowercase_      ,							lowercase_      :int         =			self.get_unet_model(model_id="stabilityai/stable-diffusion-2"     ,				fpaa=lowercase						)
        lowercase_      :str         =			self.get_latents(lowercase     ,				shape=(4, 4, 96, 96)     ,				fpaa=lowercase						)
        lowercase_      :List[Any]         =			self.get_encoder_hidden_states(lowercase     ,				shape=(4, 77, 1_024)     ,				fpaa=lowercase						)

        lowercase_      :int         =			model.apply(
            {"params": params}     ,				lowercase     ,				jnp.array(lowercase     ,				dtype=jnp.intaa						)     ,				encoder_hidden_states=lowercase     ,				).sample

        assert sample.shape == latents.shape

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

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









'''simple docstring'''


def 							UpperCAmelCase_  (						__lowerCamelCase : int | float | str			):
   try:
      lowercase_      :Optional[int]         =			float(__lowerCamelCase			)
   except ValueError:
      raise ValueError("Please enter a valid number"			)
   lowercase_      :Dict         =			decimal - int(__lowerCamelCase			)
   if fractional_part == 0:
      return int(__lowerCamelCase			), 1
   else:
      lowercase_      :Tuple         =			len(str(__lowerCamelCase			).split("."			)[1]			)
      lowercase_      :Optional[Any]         =			int(decimal * (10**number_of_frac_digits)			)
      lowercase_      :Dict         =			10**number_of_frac_digits
      lowercase_      ,							lowercase_      :Optional[int]         =			denominator, numerator
      while True:
         lowercase_      :Any         =			dividend % divisor
         if remainder == 0:
            break
         lowercase_      ,							lowercase_      :Optional[int]         =			divisor, remainder
      lowercase_      ,							lowercase_      :Optional[int]         =			numerator / divisor, denominator / divisor
      return int(__lowerCamelCase			), int(__lowerCamelCase			)


if __name__ == "__main__":
 print(F'''{decimal_to_fraction(2) = }''')
 print(F'''{decimal_to_fraction(89.0) = }''')
 print(F'''{decimal_to_fraction('67') = }''')
 print(F'''{decimal_to_fraction('45.0') = }''')
 print(F'''{decimal_to_fraction(1.5) = }''')
 print(F'''{decimal_to_fraction('6.25') = }''')
 print(F'''{decimal_to_fraction('78td') = }''')


