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
code: def trace(self, x):
      print(
          f"Recompiling {self.config.get_project_name()} with tracing"
      )
      self.config.trace_output = True
      self.compile()
  
      top_function, ctype = self._get_top_function(x)
      n_samples = self._compute_n_samples(x)
      n_inputs = len(self.get_input_variables())
      n_outputs = len(self.get_output_variables())
  
      class TraceData(ctypes.Structure):
          _fields_ = [
              ("name", ctypes.c_char_p),
              ("data", ctypes.c_void_p),
          ]
  
      trace_output = {}
      layer_sizes = {}
      n_traced = 0
      for layer in self.get_layers():
          if layer.get_attr("function_cpp", None) and layer.get_attr(
              "trace", False
          ):
              n_traced += len(layer.get_variables())
              trace_output[layer.name] = []
              layer_sizes[
                  layer.name
              ] = layer.get_output_variable().shape
  
      collect_func = self._top_function_lib.collect_trace_output
      collect_func.argtypes = [ctypes.POINTER(TraceData)]
      collect_func.restype = None
      trace_data = (TraceData * n_traced)()
  
      alloc_func = self._top_function_lib.allocate_trace_storage
      alloc_func.argtypes = [ctypes.c_size_t]
      alloc_func.restype = None
  
      free_func = self._top_function_lib.free_trace_storage
      free_func.argtypes = None
      free_func.restype = None
  
      curr_dir = os.getcwd()
      os.chdir(self.config.get_output_dir() + "/firmware")
  
      output = []
      if n_samples == 1 and n_inputs == 1:
          x = [x]
  
      try:
          alloc_func(ctypes.sizeof(ctype))
  
          for i in range(n_samples):
              predictions = [
                  np.zeros(yj.size(), dtype=ctype)
                  for yj in self.get_output_variables()
              ]
              if n_inputs == 1:
                  inp = [np.asarray(x[i])]
              else:
                  inp = [np.asarray(xj[i]) for xj in x]
              argtuple = inp
              argtuple += predictions
              argtuple = tuple(argtuple)
              top_function(*argtuple)
              output.append(predictions)
              collect_func(trace_data)
              for trace in trace_data:
                  layer_name = str(trace.name, "utf-8")
                  layer_data = ctypes.cast(
                      trace.data, ctypes.POINTER(ctype)
                  )
                  np_array = np.ctypeslib.as_array(
                      layer_data, shape=layer_sizes[layer_name]
                  )
                  trace_output[layer_name].append(np.copy(np_array))
  
          for key in trace_output.keys():
              trace_output[key] = np.asarray(trace_output[key])
  
          # Convert to list of numpy arrays (one for each output)
          output = [
              np.asarray(
                  [
                      output[i_sample][i_output]
                      for i_sample in range(n_samples)
                  ]
              )
              for i_output in range(n_outputs)
          ]
  
          free_func()
      finally:
          os.chdir(curr_dir)
  
      if n_samples == 1 and n_outputs == 1:
          return output[0][0], trace_output
      elif n_outputs == 1:
          return output[0], trace_output
      elif n_samples == 1:
          return [output_i[0] for output_i in output], trace_output
      else:
          return output, trace_output
  
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 24 for calling the ModelGraph obj's underlying member method code with example usage: obj.trace(x) and returns: output,  trace_output, output,  trace_output, unknown,  trace_output, output,  trace_output