code: def test_with_dynamic_dimensions(self, dct_type, norm, shape, dtype):
      # "ortho" normalization is not implemented for type I.
      if dct_type == 1 and norm == "ortho":
          return
      signals = np.random.rand(*shape).astype(dtype)
      n = np.random.randint(1, 2 * shape[-1])
      n = np.random.choice([None, n])
  
      @def_function.function
      def func(signals):
          return dct_ops.dct(signals, n=n, type=dct_type, norm=norm)
  
      # Trace with all undefined dimensions
      signals_spec = tensor_spec.TensorSpec([None] * len(shape), dtype)
      f = func.get_concrete_function(signals_spec)
      # Run with actual shape
      f(signals)
  
imports: import importlib
  import itertools
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops.signal import dct_ops
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 3 for calling the DCTOpsTest obj's underlying member method code with example usage: obj.test_with_dynamic_dimensions(dct_type, norm, shape, dtype) and returns: dct_ops