class_docstr: The ModelGraph represents the network that is being processed by hls4ml.
  
  Args:
      config (dict):  The configuration dictionary
      layer_list (list(dict)):  The list contains a dictionary for each input layer
      inputs (list, optional):  The inputs to the model. If None, determined from layer_list
      outputs (list, optional):  The outputs to the model. If None, determined from layer_list
docstr: Compile the generated project and link the library into current environment.
  
  Users should call this function if they want to use `predict` functionality for simulation.
docstr_tok: ["Compile","the","generated","project","and","link","the","library","into","current","environment",".","Users","should","call","this","function","if","they","want","to","use","`","predict","`","functionality","for","simulation","."]
code: def compile(self):
      """Compile the generated project and link the library into current environment.
  
      Users should call this function if they want to use `predict` functionality for simulation.
      """
      self.write()
      self._compile()
  
imports: import ctypes
  import os
  import platform
  from collections import OrderedDict
  import numpy
  import numpy.ctypeslib
  from hls4ml.backends import get_backend
  from hls4ml.model.flow import get_flow
  from hls4ml.model.layers import layer_map
  from hls4ml.model.optimizer import get_available_passes, optimize_model
label_desc: Use image node_id 19 for calling the ModelGraph obj's underlying member method code with example usage: obj.compile() without return types