class_docstr: The base optimizer class. Sets the rules to update weights
  when training a neural network.
class_docstr_tok: ["The","base","optimizer","class",".","Sets","the","rules","to","update","weights","when","training","a","neural","network","."]
docstr: Modifies the trainable parameters of the network layers, using
  the accumulated gradients and previous steps' history (moment, etc.).
code: def train(self):
      """Modifies the trainable parameters of the network layers, using
      the accumulated gradients and previous steps' history (moment, etc.).
      """
      self._internal.train()
  
imports: import neoml.PythonWrapper
label_desc: Use image node_id 2 for calling the Solver obj's underlying member method code with example usage: obj.train() without return types