class_docstr: Test the Polynomial kernel.
class_docstr_tok: ["Test","the","Polynomial","kernel","."]
code: def testShapesAreCorrectBroadcast(self):
      k = polynomial.Polynomial(
          bias_amplitude=np.ones([2, 1, 1], np.float32),
          slope_amplitude=np.ones([1, 3, 1], np.float32),
      )
      self.assertAllEqual(
          [2, 3, 2, 4, 5],
          # `--'  |  `--'
          #  |   |    `- matrix shape
          #  |   `- from input batch shapes
          #  `- from broadcasting kernel params
          k.matrix(
              np.ones([2, 4, 3], np.float32),
              np.ones([2, 5, 3], np.float32),
          ).shape,
      )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math.psd_kernels import polynomial
label_desc: Use image node_id 13 for calling the PolynomialTest obj's underlying member method code with example usage: obj.testShapesAreCorrectBroadcast() without return types