This class regularly exports the serving graph and checkpoints.
In addition to exporting, this class also garbage collects stale exports.
A directory name under the export base directory where exports of
this type are written. Should not be
None nor empty.
__init__( name, serving_input_receiver_fn, assets_extra=None, as_text=False, exports_to_keep=5 )
Exporter to use with
name: unique name of this
Exporterthat is going to be used in the export path.
serving_input_receiver_fn: a function that takes no arguments and returns a
assets_extra: An optional dict specifying how to populate the assets.extra directory within the exported SavedModel. Each key should give the destination path (including the filename) relative to the assets.extra directory. The corresponding value gives the full path of the source file to be copied. For example, the simple case of copying a single file without renaming it is specified as
as_text: whether to write the SavedModel proto in text format. Defaults to
exports_to_keep: Number of exports to keep. Older exports will be garbage-collected. Defaults to 5. Set to
Noneto disable garbage collection.
ValueError: if any arguments is invalid.
export( estimator, export_path, checkpoint_path, eval_result, is_the_final_export )
Exports the given
Estimator to a specific format.
export_path: A string containing a directory where to write the export.
checkpoint_path: The checkpoint path to export.
eval_result: The output of
Estimator.evaluateon this checkpoint.
is_the_final_export: This boolean is True when this is an export in the end of training. It is False for the intermediate exports during the training. When passing
is_the_final_exportis always False if
The string path to the exported directory or
None if export is skipped.