class_docstr: Wrapper utility class that allows models to used in scikit-learn's
  ``GridSearchCV`` API. It follows the style of Keras' own wrapper.
  
  A future release of **baikal** plans to remove this class and instead
  include a custom ``GridSearchCV`` API, based on the original scikit-learn
  implementation, that can handle baikal models natively.
  
  Parameters
  ----------
  build_fn
      A function that takes no arguments and builds and returns a baikal Model.
  
      Note that, in order to specify which parameters of which steps to tune
      using a dictionary keyed by ``<step>__<parameter>``, you *must* pass a
      name to the appropriate steps when building the model in this function.
  
  params
      Dictionary mapping parameter names to their values. Valid parameter
      names are 'build_fn' and any parameter the wrapped model can take
      (in the form ``<step>__<parameter>``).
docstr: Get parameters for this estimator.
  
  Parameters
  ----------
  deep
      Unused. Kept for API compatibility purposes. It will always include
      any nested params.
  
  Returns
  -------
  params
      Parameter names mapped to their values.
docstr_tok: ["Get","parameters","for","this","estimator",".","Parameters","--","--","--","--","--","deep","Unused",".","Kept","for","API","compatibility","purposes",".","It","will","always","include","any","nested","params",".","Returns","--","--","--","-","params","Parameter","names","mapped","to","their","values","."]
code: def get_params(self, deep=True) -> Dict[str, Any]:
      """Get parameters for this estimator.
  
      Parameters
      ----------
      deep
          Unused. Kept for API compatibility purposes. It will always include
          any nested params.
  
      Returns
      -------
      params
          Parameter names mapped to their values.
      """
      params = self._model.get_params(deep=True)
      params["build_fn"] = self.build_fn
      return params
  
file_path: baikal/baikal/sklearn.py
imports: from typing import Dict, Any, Callable
  from baikal import Model
label_desc: Use image node_id 2 for calling the SKLearnWrapper obj's underlying member method code with example usage: obj.get_params(deep) and returns: params