docstr: Compile the trained model for faster inference.
  
  Parameters
  ----------
  model
      The native model that is expected to be compiled.
  path : str
      The path for saving the compiled model.
  input_types : list, default=None
      A list of tuples containing shape and element type info, e.g. [((1, 14), np.float32),].
      The list would be used as the input data for the model.
      The compiler would optimize the model to perform best with the given input type.
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code: def compile(model, path: str, input_types=None):
      """
      Compile the trained model for faster inference.
  
      Parameters
      ----------
      model
          The native model that is expected to be compiled.
      path : str
          The path for saving the compiled model.
      input_types : list, default=None
          A list of tuples containing shape and element type info, e.g. [((1, 14), np.float32),].
          The list would be used as the input data for the model.
          The compiler would optimize the model to perform best with the given input type.
      """
      AbstractNativeCompiler.save(model, path)
      return model
  
imports: import os
  import pickle
label_desc: Use image node_id 2 for calling the AbstractNativeCompiler obj's underlying member method code with example usage: obj.compile(model, path, input_types) and returns: model