class_docstr: Estimator class based on scikit-learn estimators.
  
  See https://scikit-learn.org/stable/developers/develop.html
class_docstr_tok: ["Estimator","class","based","on","scikit-learn","estimators",".","See","https",":","\/\/scikit-learn.org\/stable\/developers\/develop.html"]
code: def fit_predict(
      self, X: jax.Array, y: jax.Array
  ) -> jax.Array:  # pylint: disable=invalid-name
      if not self.check_is_fitted():
          raise RuntimeError(
              "Model is not yet fit! Call `AutoBNN.fit(X, y)` first."
          )
      self.fit(X, y)
      return self.predict(X)
  
imports: from typing import Any, Mapping, Optional, Sequence
  import jax
  import jax.numpy
  from jaxtyping import ArrayLike, PyTree
  from tensorflow_probability.python.experimental.autobnn import bnn
  from tensorflow_probability.python.experimental.autobnn import likelihoods
  from tensorflow_probability.python.experimental.autobnn import models
  from tensorflow_probability.python.experimental.autobnn import training_util
label_desc: Use image node_id 6 for calling the _AutoBnnEstimator obj's underlying member method code with example usage: obj.fit_predict(X, y) and returns: self