tf.train.export_meta_graph(filename=None, meta_info_def=None, graph_def=None, saver_def=None, collection_list=None, as_text=False, graph=None, export_scope=None, clear_devices=False, **kwargs)

tf.train.export_meta_graph(filename=None, meta_info_def=None, graph_def=None, saver_def=None, collection_list=None, as_text=False, graph=None, export_scope=None, clear_devices=False, **kwargs)

See the guide: Variables > Exporting and Importing Meta Graphs

Returns MetaGraphDef proto. Optionally writes it to filename.

This function exports the graph, saver, and collection objects into MetaGraphDef protocol buffer with the intention of it being imported at a later time or location to restart training, run inference, or be a subgraph.

Args:

• filename: Optional filename including the path for writing the generated MetaGraphDef protocol buffer.
• meta_info_def: MetaInfoDef protocol buffer.
• graph_def: GraphDef protocol buffer.
• saver_def: SaverDef protocol buffer.
• collection_list: List of string keys to collect.
• as_text: If True, writes the MetaGraphDef as an ASCII proto.
• graph: The Graph to import into. If None, use the default graph.
• export_scope: Optional string. Name scope under which to extract the subgraph. The scope name will be striped from the node definitions for easy import later into new name scopes. If None, the whole graph is exported. graph_def and export_scope cannot both be specified.
• clear_devices: Whether or not to clear the device field for an Operation or Tensor during export. **kwargs: Optional keyed arguments.

Returns:

A MetaGraphDef proto.

Raises:

• ValueError: When the GraphDef is larger than 2GB.

Defined in tensorflow/python/training/saver.py.