code: def __init__(self, train_x, train_y, likelihood):
      super(MultitaskGPModel, self).__init__(
          train_x, train_y, likelihood
      )
      self.mean_module = MultitaskMean(ConstantMean(), num_tasks=2)
      self.base_kernel_list = [RBFKernel()]
      self.covar_module = LCMKernel(
          self.base_kernel_list, num_tasks=2, rank=1
      )
  
file_path: gpytorch/test/examples/test_lcm_kernel_regression.py
imports: import math
  import unittest
  import torch
  import gpytorch
  from gpytorch.distributions import MultitaskMultivariateNormal
  from gpytorch.kernels import LCMKernel, MultitaskKernel, RBFKernel
  from gpytorch.likelihoods import MultitaskGaussianLikelihood
  from gpytorch.means import ConstantMean, MultitaskMean
label_desc: Use image node_id 1 to create a new MultitaskGPModel object from inherited base classes: gpytorch.models with example: obj = MultitaskGPModel(train_x, train_y, likelihood)