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 __init__(self, model, epochs, flatten_output=False):
      self.model = model
      self.epochs = epochs
      self.flatten_output = flatten_output
      self.init_weights = None
      self.scaler = StandardScaler()
  
imports: import numpy
  import sklearn
  import sklearn.ensemble
  from sklearn.preprocessing import StandardScaler
label_desc: Use image node_id 1 to create a new KerasWrap object  with example: obj = KerasWrap(model, epochs, flatten_output)