export

FullyConnected.export(filepath)

Create a SavedModel artifact for inference (e.g. via TF-Serving).

This method lets you export a model to a lightweight SavedModel artifact that contains the model’s forward pass only (its call() method) and can be served via e.g. TF-Serving. The forward pass is registered under the name serve() (see example below).

The original code of the model (including any custom layers you may have used) is no longer necessary to reload the artifact – it is entirely standalone.

Parameters:

filepath – str or pathlib.Path object. Path where to save the artifact.

Example:

```python # Create the artifact model.export(“path/to/location”)

# Later, in a different process / environment… reloaded_artifact = tf.saved_model.load(“path/to/location”) predictions = reloaded_artifact.serve(input_data) ```

If you would like to customize your serving endpoints, you can use the lower-level keras.export.ExportArchive class. The export() method relies on ExportArchive internally.