docstr: ...Test SVRG set_model
          
docstr_tok: ["...","Test","SVRG","set_model"]
code: def test_set_model(self):
      """...Test SVRG set_model"""
      X, y = self.simu_linreg_data(dtype=self.dtype)
      _, model_spars = self.get_dense_and_sparse_linreg_model(
          X, y, dtype=self.dtype
      )
      svrg = SVRG(variance_reduction="avg")
      msg = (
          "'avg' variance reduction cannot be used with sparse datasets. "
          "Please change `variance_reduction` before passing sparse data."
      )
      with catch_warnings(record=True) as w:
          simplefilter("always")
  
          svrg.set_model(model_spars)
          self.assertEqual(len(w), 1)
          self.assertTrue(issubclass(w[0].category, UserWarning))
          self.assertEqual(str(w[0].message), msg)
  
imports: import unittest
  from warnings import catch_warnings, simplefilter
  from itertools import product
  import numpy
  from scipy.linalg.special_matrices import toeplitz
  from scipy.sparse import csr_matrix
  from tick.linear_model import ModelLinReg, ModelLogReg, SimuLogReg
  from tick.prox import ProxL1, ProxL1w, ProxTV, ProxEquality, ProxElasticNet
  from tick.solver import SVRG
  from tick.solver.tests import TestSolver
  from tick.solver.build.solver import SVRG_VarianceReductionMethod_Last
  from tick.solver.build.solver import SVRG_VarianceReductionMethod_Average
  from tick.solver.build.solver import SVRG_VarianceReductionMethod_Random
  from tick.solver.build.solver import SVRG_StepType_Fixed
  from tick.solver.build.solver import SVRG_StepType_BarzilaiBorwein
  from tick.simulation import weights_sparse_gauss
label_desc: Use image node_id 7 for calling the SVRGTest obj's underlying member method code with example usage: obj.test_set_model() without return types