

"""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    snake_case     (    unittest.TestCase  ):

				def 							lowercase_					(     self							:    List[Any]					,  UpperCamelCase__							:    int					,  UpperCamelCase__							:    str)->       int:



						'''simple docstring'''


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

				def 							lowercase_					(     self							:    Union[str, Any])->       int:



						'''simple docstring'''


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

				def 							lowercase_					(     self							:    List[Any]					,  UpperCamelCase__							:    Union[str, Any]=0					,  UpperCamelCase__							:    str=(4, 4, 6_4, 6_4)					,  UpperCamelCase__							:    List[str]=False)->       Tuple:



						'''simple docstring'''


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

				def 							lowercase_					(     self							:    Dict					,  UpperCamelCase__							:    List[Any]=False					,  UpperCamelCase__							:    Union[str, Any]="CompVis/stable-diffusion-v1-4")->       Optional[Any]:



						'''simple docstring'''


						__lowerCAmelCase:	Tuple   				=      jnp.bfloataa if fpaa else jnp.floataa
						__lowerCAmelCase:	Any   				=      """bf16""" if fpaa else None

						__lowerCAmelCase:	Any   				=      FlaxUNetaDConditionModel.from_pretrained(
						    _UpperCamelCase					,  subfolder="unet"					,  dtype=_UpperCamelCase					,  revision=_UpperCamelCase)
						return model, params

				def 							lowercase_					(     self							:    Union[str, Any]					,  UpperCamelCase__							:    Dict=0					,  UpperCamelCase__							:    Tuple=(4, 7_7, 7_6_8)					,  UpperCamelCase__							:    int=False)->       List[Any]:



						'''simple docstring'''


						__lowerCAmelCase:	List[str]   				=      jnp.bfloataa if fpaa else jnp.floataa
						__lowerCAmelCase:	Dict   				=      jnp.array(load_hf_numpy(self.get_file_format(_UpperCamelCase					,  _UpperCamelCase))					,  dtype=_UpperCamelCase)
						return hidden_states

				@parameterized.expand(
				    [
				        # fmt: off
				        [8_3, 4, [-0.2323, -0.1304, 0.0813, -0.3093, -0.0919, -0.1571, -0.1125, -0.5806]],
				        [1_7, 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, 1_0_0_0, [-0.5649, 0.2402, -0.5518, 0.1248, 1.1328, -0.2443, -0.0325, -1.0078]],
				        # fmt: on
				    ])
				def 							lowercase_					(     self							:    Optional[int]					,  UpperCamelCase__							:    List[Any]					,  UpperCamelCase__							:    Tuple					,  UpperCamelCase__							:    Any)->       List[Any]:



						'''simple docstring'''


						__lowerCAmelCase:	List[Any]   				=      self.get_unet_model(model_id="CompVis/stable-diffusion-v1-4"					,  fpaa=_UpperCamelCase)
						__lowerCAmelCase:	Optional[Any]   				=      self.get_latents(_UpperCamelCase					,  fpaa=_UpperCamelCase)
						__lowerCAmelCase:	Tuple   				=      self.get_encoder_hidden_states(_UpperCamelCase					,  fpaa=_UpperCamelCase)

						__lowerCAmelCase:	Optional[int]   				=      model.apply(
						    {"params": params}					,  _UpperCamelCase					,  jnp.array(_UpperCamelCase					,  dtype=jnp.intaa)					,  encoder_hidden_states=_UpperCamelCase					,  ).sample

						assert sample.shape == latents.shape

						__lowerCAmelCase:	Optional[int]   				=      jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten()))					,  dtype=jnp.floataa)
						__lowerCAmelCase:	int   				=      jnp.array(_UpperCamelCase					,  dtype=jnp.floataa)

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




				@parameterized.expand(
				    [
				        # fmt: off
				        [8_3, 4, [0.1514, 0.0807, 0.1624, 0.1016, -0.1896, 0.0263, 0.0677, 0.2310]],
				        [1_7, 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, 1_0_0_0, [0.1214, 0.0352, -0.0731, -0.1562, -0.0994, -0.0906, -0.2340, -0.0539]],
				        # fmt: on
				    ])
				def 							lowercase_					(     self							:    Any					,  UpperCamelCase__							:    Optional[Any]					,  UpperCamelCase__							:    Any					,  UpperCamelCase__							:    Optional[int])->       int:



						'''simple docstring'''


						__lowerCAmelCase:	Optional[int]   				=      self.get_unet_model(model_id="stabilityai/stable-diffusion-2"					,  fpaa=_UpperCamelCase)
						__lowerCAmelCase:	Tuple   				=      self.get_latents(_UpperCamelCase					,  shape=(4, 4, 9_6, 9_6)					,  fpaa=_UpperCamelCase)
						__lowerCAmelCase:	Tuple   				=      self.get_encoder_hidden_states(_UpperCamelCase					,  shape=(4, 7_7, 1_0_2_4)					,  fpaa=_UpperCamelCase)

						__lowerCAmelCase:	Union[str, Any]   				=      model.apply(
						    {"params": params}					,  _UpperCamelCase					,  jnp.array(_UpperCamelCase					,  dtype=jnp.intaa)					,  encoder_hidden_states=_UpperCamelCase					,  ).sample

						assert sample.shape == latents.shape

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

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






"""simple docstring"""


from __future__ import annotations

from decimal import Decimal
from math import *  # noqa: F403

from sympy import diff






def    a__   (   __SCREAMING_SNAKE_CASE ,			__SCREAMING_SNAKE_CASE ,			__SCREAMING_SNAKE_CASE = 1_0**-1_0			)     ->     float:
		__lowerCAmelCase:	Union[str, Any]   				=      a
		while True:
				__lowerCAmelCase:	Optional[int]   				=      Decimal(__SCREAMING_SNAKE_CASE			) - (
				    Decimal(eval(__SCREAMING_SNAKE_CASE			)			) / Decimal(eval(str(diff(__SCREAMING_SNAKE_CASE			)			)			)			)  # noqa: S307
				)
				# This number dictates the accuracy of the answer
				if abs(eval(__SCREAMING_SNAKE_CASE			)			) < precision:  # noqa: S307
						return float(__SCREAMING_SNAKE_CASE			)


# Let's Execute
if __name__ == "__main__":
			# Find root of trigonometric function
			# Find value of pi
			print(F'''The root of sin(x) = 0 is {newton_raphson("sin(x)", 2)}''')
			# Find root of polynomial
			print(F'''The root of x**2 - 5*x + 2 = 0 is {newton_raphson("x**2 - 5*x + 2", 0.4)}''')
			# Find Square Root of 5
			print(F'''The root of log(x) - 1 = 0 is {newton_raphson("log(x) - 1", 2)}''')
			# Exponential Roots
			print(F'''The root of exp(x) - 1 = 0 is {newton_raphson("exp(x) - 1", 0)}''')


