A class representing a type of model export.
THIS CLASS IS DEPRECATED. See contrib/learn/README.md for general migration instructions.
Typically constructed by a utility function specific to the exporter, such as
name: The directory name under the export base directory where exports of this type will be written.
export_fn: A function that writes an export, given an estimator, a destination path, and optionally a checkpoint path and an evaluation result for that checkpoint. This export_fn() may be run repeatedly during continuous training, or just once at the end of fixed-length training. Note the export_fn() may choose whether or not to export based on the eval result or based on an internal timer or any other criterion, if exports are not desired for every checkpoint.
The signature of this function must be one of:
(estimator, export_path) -> export_path
(estimator, export_path, checkpoint_path) -> export_path
(estimator, export_path, checkpoint_path, eval_result) -> export_path
(estimator, export_path, checkpoint_path, eval_result, strip_default_attrs) -> export_path
strip_default_attrs: (Optional) Boolean. If set as True, default attrs in the
GraphDefwill be stripped on write. This is recommended for better forward compatibility of the resulting
@staticmethod __new__( cls, name, export_fn, strip_default_attrs=None )
export( estimator, export_path, checkpoint_path=None, eval_result=None )
Exports the given Estimator to a specific format.
estimator: the Estimator to export.
export_path: A string containing a directory where to write the export.
checkpoint_path: The checkpoint path to export. If None (the default), the strategy may locate a checkpoint (e.g. the most recent) by itself.
eval_result: The output of Estimator.evaluate on this checkpoint. This should be set only if checkpoint_path is provided (otherwise it is unclear which checkpoint this eval refers to).
The string path to the exported directory.
ValueError: if the export_fn does not have the required signature