class_docstr: Runs a graph with sub-graphs that need to run sequentially. Each sub-graph
  takes its inputs from the outputs of the previous sub-graph.
class_docstr_tok: ["Runs","a","graph","with","sub-graphs","that","need","to","run","sequentially",".","Each","sub-graph","takes","its","inputs","from","the","outputs","of","the","previous","sub-graph","."]
docstr: Postprocess the outputs of the Session.run(). Move the outputs of
  sub-graphs to next ones and return the output of the last sub-graph.
  
  :param fvals: A list of fetched values returned by Session.run()
  :return: A dictionary of fetched values returned by the last sub-graph.
docstr_tok: ["Postprocess","the","outputs","of","the","Session.run","(",")",".","Move","the","outputs","of","sub-graphs","to","next","ones","and","return","the","output","of","the","last","sub-graph",".",":","param","fvals",":","A","list","of","fetched","values","returned","by","Session.run","(",")",":","return",":","A","dictionary","of","fetched","values","returned","by","the","last","sub-graph","."]
code: def proc_fvals(self, fvals):
      """
      Postprocess the outputs of the Session.run(). Move the outputs of
      sub-graphs to next ones and return the output of the last sub-graph.
  
      :param fvals: A list of fetched values returned by Session.run()
      :return: A dictionary of fetched values returned by the last sub-graph.
      """
      inputs = self.inputs
      outputs = self.outputs
  
      # Move data to the next sub-graph for the next step
      cur = 0
      for i in range(len(inputs) - 1):
          if not self.active_gpus[i]:
              self.next_vals[i + 1] = None
              continue
          self.next_vals[i + 1] = OrderedDict()
          for k in outputs[i]:
              self.next_vals[i + 1][k] = fvals[cur]
              cur += 1
          if i == 0:
              self.next_vals[0] = None
  
      # Return the output of the last sub-graph
      last_fvals = OrderedDict()
      if self.active_gpus[-1]:
          assert cur + len(outputs[-1]) == len(fvals)
          for k in outputs[-1]:
              last_fvals[k] = fvals[cur]
              cur += 1
      return last_fvals
  
imports: from collections import OrderedDict
label_desc: Use image node_id 4 for calling the RunnerMultiGPU obj's underlying member method code with example usage: obj.proc_fvals(fvals) and returns: last_fvals