tf.estimator.FinalExporter

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This class exports the serving graph and checkpoints at the end.

Inherits From: Exporter

tf.estimator.FinalExporter(
    name, serving_input_receiver_fn, assets_extra=None, as_text=False
)

This class performs a single export at the end of training.

Args:

• name: unique name of this Exporter that is going to be used in the export path.
• serving_input_receiver_fn: a function that takes no arguments and returns a ServingInputReceiver.
• 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 {'my_asset_file.txt': '/path/to/my_asset_file.txt'}.
• as_text: whether to write the SavedModel proto in text format. Defaults to False.

Attributes:

• name: Directory name.

  A directory name under the export base directory where exports of this type are written. Should not be None nor empty.

Raises:

• ValueError: if any arguments is invalid.

Methods

export

View source

export(
    estimator, export_path, checkpoint_path, eval_result, is_the_final_export
)

Exports the given Estimator to a specific format.

Args:

• estimator: the Estimator to export.
• 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.evaluate on 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 Exporter to tf.estimator.train_and_evaluate is_the_final_export is always False if TrainSpec.max_steps is None.

Returns:

The string path to the exported directory or None if export is skipped.