code: def reshape_and_detach(target: Tensor, new_value: Tensor) -> None:
      """Detach and reshape `new_value` to match `target`."""
      return new_value.detach().clone().view(target.shape).to(target)
  
imports: import math
  from abc import abstractmethod
  from typing import Any, Dict, List, Mapping, Optional, Tuple
  import pyro
  import torch
  from botorch.acquisition.objective import PosteriorTransform
  from botorch.models.gpytorch import BatchedMultiOutputGPyTorchModel
  from botorch.models.transforms.input import InputTransform
  from botorch.models.transforms.outcome import OutcomeTransform
  from botorch.models.utils import validate_input_scaling
  from botorch.models.utils.gpytorch_modules import MIN_INFERRED_NOISE_LEVEL
  from botorch.posteriors.fully_bayesian import GaussianMixturePosterior, MCMC_DIM
  from gpytorch.constraints import GreaterThan
  from gpytorch.distributions.multivariate_normal import MultivariateNormal
  from gpytorch.kernels import MaternKernel, ScaleKernel
  from gpytorch.kernels.kernel import dist, Kernel
  from gpytorch.likelihoods.gaussian_likelihood import FixedNoiseGaussianLikelihood, GaussianLikelihood
  from gpytorch.likelihoods.likelihood import Likelihood
  from gpytorch.means.constant_mean import ConstantMean
  from gpytorch.means.mean import Mean
  from gpytorch.models.exact_gp import ExactGP
  from pyro.ops.integrator import register_exception_handler
  from torch import Tensor
label_desc: Use image node_id 5 for calling a global function with example usage: reshape_and_detach(target, new_value) and returns: new_value