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)
  
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) without return types