class_docstr: Export models for inference.
docstr: Initialise the export process.
  
  Args:
      config (PredictConfig): the config to use.
          The graph will be built with the tower function defined by this `PredictConfig`.
          Then the input / output names will be used to export models for inference.
docstr_tok: ["Initialise","the","export","process",".","Args",":","config","(","PredictConfig",")",":","the","config","to","use",".","The","graph","will","be","built","with","the","tower","function","defined","by","this","`","PredictConfig","`",".","Then","the","input","\/","output","names","will","be","used","to","export","models","for","inference","."]
code: def __init__(self, config):
      """Initialise the export process.
  
      Args:
          config (PredictConfig): the config to use.
              The graph will be built with the tower function defined by this `PredictConfig`.
              Then the input / output names will be used to export models for inference.
      """
      super(ModelExporter, self).__init__()
      self.config = config
  
file_path: tensorpack/tensorpack/tfutils/export.py
imports: import tensorflow
  from tensorflow.python.framework import graph_util
  from tensorflow.python.platform import gfile
  from tensorflow.python.tools import optimize_for_inference_lib
  from ..compat import tfv1
  from ..input_source import PlaceholderInput
  from ..tfutils.common import get_tensors_by_names, get_tf_version_tuple
  from ..tfutils.tower import PredictTowerContext
  from ..utils import logger
label_desc: Use image node_id 1 to create a new ModelExporter object from inherited base classes: object with example: obj = ModelExporter(config)