code: def test_syevjBatched(self):
      lda, m = self.a.shape
  
      na = numpy.stack([self.a, self.a + numpy.diag(numpy.ones(m))])
      a = cupy.array(na, order=self.order)
  
      w, v = cusolver.syevj(a, UPLO=self.UPLO, with_eigen_vector=True)
  
      # check eignvalue equation
      batch_size = a.shape[0]
      for i in range(batch_size):
          testing.assert_allclose(
              na[i].dot(v[i].get()), w[i] * v[i], rtol=1e-3, atol=1e-4
          )
  
      # check arbitrary batch dimension shape
      na = numpy.stack([na, na, na])
      a = cupy.array(na, order=self.order)
  
      w, v = cusolver.syevj(a, UPLO=self.UPLO, with_eigen_vector=True)
  
      assert v.shape == a.shape
      assert w.shape == a.shape[:-1]
  
imports: import numpy
  import pytest
  import cupy
  from cupyx import cusolver
  from cupy import testing
  from cupy._core import _routines_linalg
  import cupyx
label_desc: Use image node_id 3 for calling the TestSyevj obj's underlying member method code with example usage: obj.test_syevjBatched() without return types