code: def testBatch(self):
      for dtype in self.float_types:
          simple_array = np.array(
              [[[1.0, 0.0], [0.0, 5.0]]], dtype=dtype
          )  # shape (1, 2, 2)
          self._verifyCholesky(simple_array)
          self._verifyCholesky(np.vstack((simple_array, simple_array)))
          odd_sized_array = np.array(
              [[[4.0, -1.0, 2.0], [-1.0, 6.0, 0], [2.0, 0.0, 5.0]]],
              dtype=dtype,
          )
          self._verifyCholesky(
              np.vstack((odd_sized_array, odd_sized_array))
          )
  
          # Generate random positive-definite matrices.
          matrices = np.random.rand(10, 5, 5).astype(dtype)
          for i in range(10):
              matrices[i] = np.dot(matrices[i].T, matrices[i])
          self._verifyCholesky(matrices, atol=1e-4)
  
imports: import numpy
  from tensorflow.compiler.tests import xla_test
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import linalg_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 5 for calling the CholeskyOpTest obj's underlying member method code with example usage: obj.testBatch() without return types