class_docstr: A BNN where samples are polynomial functions.
class_docstr_tok: ["A","BNN","where","samples","are","polynomial","functions","."]
docstr: Return a string summarizing the structure of the BNN.
code: def summarize(self, params=None, full: bool = False) -> str:
      """Return a string summarizing the structure of the BNN."""
      return f"{self.shortname()}(degree={self.degree})"
  
imports: from flax import linen
  from flax.linen import initializers
  import jax
  import jax.numpy
  from tensorflow_probability.python.experimental.autobnn import bnn
  from tensorflow_probability.substrates.jax.distributions import lognormal
  from tensorflow_probability.substrates.jax.distributions import normal
  from tensorflow_probability.substrates.jax.distributions import student_t
  from tensorflow_probability.substrates.jax.distributions import uniform
label_desc: Use image node_id 4 for calling the PolynomialBNN obj's underlying member method code with example usage: obj.summarize(params, full) and returns: self, str, self, str