class_docstr: Test the abstract base class behaviors.
class_docstr_tok: ["Test","the","abstract","base","class","behaviors","."]
code: def testMatrixOutputWithStaticShapes(self):
      k = TestKernel(PARAMS_0)  # batch_shape = []
      x, _, z = self.createKernelInputs()
      self.assertAllEqual(
          [3, 4], k.matrix(x, z).shape  # shape [3, 3]  # shape [4, 3]
      )
  
      k = TestKernel(PARAMS_2)  # batch_shape = [2]
      self.assertAllEqual(
          [2, 3, 4],
          k.matrix(x, z).shape,  # shape [3, 3]  # shape [4, 3]
      )
  
      k = TestKernel(PARAMS_2)  # batch_shape = [2]
      batch_x, _, batch_z = self.createKernelInputs(batched=True)
  
      with self.assertRaises(ERROR_TYPES):
          k.matrix(
              batch_x, batch_z  # shape = [5, 3, 3]
          )  # shape = [5, 4, 3]
  
      k = TestKernel(PARAMS_21)  # batch_shape = [2, 1]
      self.assertAllEqual(
          [2, 5, 3, 4],
          k.matrix(
              batch_x, batch_z  # shape = [5, 3, 3]  # shape = [5, 4, 3]
          ).shape,
      )
  
imports: import functools
  import operator
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math.psd_kernels import positive_semidefinite_kernel
  from tensorflow_probability.python.math.psd_kernels.internal import test_util
  from tensorflow_probability.python.math.psd_kernels.internal import util
label_desc: Use image node_id 13 for calling the PositiveSemidefiniteKernelTest obj's underlying member method code with example usage: obj.testMatrixOutputWithStaticShapes() without return types