class_docstr: A wrapper that allows us to set parameters in the constructor and do a reset before fitting.
      
class_docstr_tok: ["A","wrapper","that","allows","us","to","set","parameters","in","the","constructor","and","do","a","reset","before","fitting","."]
code: def fit(self, X, y, verbose=0):
      if self.init_weights is None:
          self.init_weights = self.model.get_weights()
      else:
          self.model.set_weights(self.init_weights)
      self.scaler.fit(X)
      return self.model.fit(X, y, epochs=self.epochs, verbose=verbose)
  
imports: import numpy
  import sklearn
  import sklearn.ensemble
  from sklearn.preprocessing import StandardScaler
label_desc: Use image node_id 2 for calling the KerasWrap obj's underlying member method code with example usage: obj.fit(X, y, verbose) and returns: self