code: def get_model(A, y, lamb=0):
      """
      Regularized least-squares
      """
      n_col = A.shape[1]
      return np.linalg.lstsq(
          A.T.dot(A) + lamb * np.identity(n_col), A.T.dot(y), rcond=None
      )
  
imports: from __future__ import print_function
  import torch
  import numpy
  import pandas
  import torch.nn
  import torch.optim
  from torch.autograd import Variable
  from zoo.chronos.model.tcmf.data_loader import TCMFDataLoader
  from zoo.chronos.model.tcmf.local_model import TemporalConvNet, LocalModel
  from zoo.chronos.model.tcmf.time import TimeCovariates
  import copy
  import pickle
  import logging
label_desc: Use image node_id 1 for calling a global function with example usage: get_model(A, y, lamb) and returns: np