






'''simple docstring'''







from sympy import diff, lambdify, symbols
from sympy.functions import *  # noqa: F403
def 						A__			(				__lowerCAmelCase		:			Tuple   ,    __lowerCAmelCase		:			str   ,    __lowerCAmelCase		:			Union[str, Any] = "x"   ,    __lowerCAmelCase		:			List[str] = 10**-10   ,    __lowerCAmelCase		:			Optional[int] = 1   ,    ):
						lowerCamelCase__         =  symbols(__lowerCAmelCase						)
						lowerCamelCase__         =  lambdify(__lowerCAmelCase   ,    __lowerCAmelCase						)
						lowerCamelCase__         =  lambdify(__lowerCAmelCase   ,    diff(__lowerCAmelCase   ,    __lowerCAmelCase						)						)

						lowerCamelCase__         =  starting_point

						while True:
												if diff_function(__lowerCAmelCase						) != 0:
																		lowerCamelCase__         =  prev_guess - multiplicity * func(__lowerCAmelCase						) / diff_function(
																		    __lowerCAmelCase						)
												else:
																		raise ZeroDivisionError("""Could not find root"""						) from None

												# Precision is checked by comparing the difference of consecutive guesses
												if abs(next_guess - prev_guess						) < precision:
																		return next_guess

												lowerCamelCase__         =  next_guess


# 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
							# Find fourth Root of 5
							print(F'The root of x**4 - 5 = 0 is {newton_raphson("x**4 -5", 0.4 +5J)}')

							# Find value of e
							print(
							    "The root of log(y) - 1 = 0 is ",
							    F'{newton_raphson("log(y) - 1", 2, variable="y")}',
							)

							# Exponential Roots
							print(
							    "The root of exp(x) - 1 = 0 is",
							    F'{newton_raphson("exp(x) - 1", 10, precision=0.005)}',
							)

							# Find root of cos(x)
							print(F'The root of cos(x) = 0 is {newton_raphson("cos(x)", 0)}')









'''simple docstring'''







import argparse

import OmegaConf
import torch

from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def 						A__			(				__lowerCAmelCase		:			str   ,    __lowerCAmelCase		:			Tuple   ,    __lowerCAmelCase		:			List[str]						):
						lowerCamelCase__         =  OmegaConf.load(__lowerCAmelCase						)
						lowerCamelCase__         =  torch.load(__lowerCAmelCase   ,    map_location="""cpu"""						)["""model"""]
						lowerCamelCase__         =  list(state_dict.keys()						)

						# extract state_dict for VQVAE
						lowerCamelCase__         =  {}
						lowerCamelCase__         =  """first_stage_model."""
						for key in keys:
												if key.startswith(__lowerCAmelCase						):
																		lowerCamelCase__         =  state_dict[key]

    # extract state_dict for UNetLDM
						lowerCamelCase__         =  {}
						lowerCamelCase__         =  """model.diffusion_model."""
						for key in keys:
												if key.startswith(__lowerCAmelCase						):
																		lowerCamelCase__         =  state_dict[key]

						lowerCamelCase__         =  config.model.params.first_stage_config.params
						lowerCamelCase__         =  config.model.params.unet_config.params

						lowerCamelCase__         =  VQModel(**__lowerCAmelCase						).eval()
						vqvae.load_state_dict(__lowerCAmelCase						)

						lowerCamelCase__         =  UNetLDMModel(**__lowerCAmelCase						).eval()
						unet.load_state_dict(__lowerCAmelCase						)

						lowerCamelCase__         =  DDIMScheduler(
						    timesteps=config.model.params.timesteps   ,    beta_schedule="""scaled_linear"""   ,    beta_start=config.model.params.linear_start   ,    beta_end=config.model.params.linear_end   ,    clip_sample=__lowerCAmelCase   ,    )

						lowerCamelCase__         =  LDMPipeline(__lowerCAmelCase   ,    __lowerCAmelCase   ,    __lowerCAmelCase						)
						pipeline.save_pretrained(__lowerCAmelCase						)


if __name__ == "__main__":
							UpperCamelCase    :      Optional[int]  			=		argparse.ArgumentParser()
							parser.add_argument('--checkpoint_path', type=str, required=True)
							parser.add_argument('--config_path', type=str, required=True)
							parser.add_argument('--output_path', type=str, required=True)
							UpperCamelCase    :      List[Any]  			=		parser.parse_args()

							convert_ldm_original(args.checkpoint_path, args.config_path, args.output_path)

