code: def fit(
      self, x, y, validation_x=None, validation_y=None, **sklearn_kwargs
  ):
      self.sklearn.fit(x, y=y, **sklearn_kwargs)
      results = {
          "eval_metric": self.eval_metric,
          "train": self.evaluate(x, y),
      }
      if validation_x is not None and validation_y is not None:
          results["validate"] = self.evaluate(
              validation_x, validation_y
          )
      return results
  
imports: from __future__ import absolute_import
  import inspect
  import logging
  import warnings
  import lore
  import lore.estimators
  from lore.env import require
  from lore.util import timed, before_after_callbacks
  import sklearn
label_desc: Use image node_id 3 for calling the Base obj's underlying member method code with example usage: obj.fit(x, y, validation_x, validation_y) and returns: results