class_docstr: Exporter for converting models to their caffe2 init and predict nets.
  Does not rely on c2_prepared, but rather splits the ONNX model into
  the init and predict nets directly.
class_docstr_tok: ["Exporter","for","converting","models","to","their","caffe2","init","and","predict","nets",".","Does","not","rely","on","c2_prepared",",","but","rather","splits","the","ONNX","model","into","the","init","and","predict","nets","directly","."]
code: def postprocess_output(
      self,
      init_net,
      predict_net,
      workspace,
      output_names: List[str],
      model,
  ):
      model_out = model(*self.dummy_model_input)
      res = model.output_layer.export_to_caffe2(
          workspace, init_net, predict_net, model_out, *output_names
      )
      final_output_names = [str(output) for output in res]
      return (res, final_output_names)
  
imports: import os
  from typing import Dict, List
  from caffe2.python import core, workspace
  from pytext.config import ConfigBase
  from pytext.config.field_config import FeatureConfig, FloatVectorConfig
  from pytext.config.module_config import ExporterType
  from pytext.exporters.exporter import ModelExporter
  from pytext.fields import FieldMeta
  from pytext.utils import mobile_onnx
  from pytext.utils.file_io import PathManager
label_desc: Use image node_id 2 for calling the InitPredictNetExporter obj's underlying member method code with example usage: obj.postprocess_output(init_net, predict_net, workspace, output_names, model) and returns: res,  final_output_names