class_docstr: Test the abstract base class behaviors.
class_docstr_tok: ["Test","the","abstract","base","class","behaviors","."]
code: def testMatrixOutputWithDynamicShapes(self):
      params_2_dynamic = tf1.placeholder_with_default(
          [1.0, 2.0], shape=None
      )
      k = TestKernel(params_2_dynamic)  # batch_shape [2]
      x, _, z = self.createKernelInputs()
      apply_op = k.matrix(x, z)  # shape [3, 3]  # shape [4, 3]
      self.assertAllEqual([2, 3, 4], self.evaluate(apply_op).shape)
  
      params_21_dynamic = tf1.placeholder_with_default(
          [[1.0], [2.0]], shape=None
      )
      k = TestKernel(params_21_dynamic)  # shape [2, 1]
      batch_x, _, batch_z = self.createKernelInputs(batched=True)
      apply_op = k.matrix(
          batch_x, batch_z  # shape [5, 3, 3]
      )  # shape [5, 4, 3]
      self.assertAllEqual([2, 5, 3, 4], self.evaluate(apply_op).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 14 for calling the PositiveSemidefiniteKernelTest obj's underlying member method code with example usage: obj.testMatrixOutputWithDynamicShapes() without return types