are there any tutorials available about export_savedmodel
?
I have gone through this article on tensorflow.org and unittest code on github.com, and still have no idea about how to construct the parameter serving_input_fn
of function export_savedmodel
Do it like this:
your_feature_spec = {
"some_feature": tf.FixedLenFeature([], dtype=tf.string, default_value=""),
"some_feature": tf.VarLenFeature(dtype=tf.string),
}
def _serving_input_receiver_fn():
serialized_tf_example = tf.placeholder(dtype=tf.string, shape=None,
name='input_example_tensor')
# key (e.g. 'examples') should be same with the inputKey when you
# buid the request for prediction
receiver_tensors = {'examples': serialized_tf_example}
features = tf.parse_example(serialized_tf_example, your_feature_spec)
return tf.estimator.export.ServingInputReceiver(features, receiver_tensors)
estimator.export_savedmodel(export_dir, _serving_input_receiver_fn)
Then you can request the served model with "predict" signature name by batch.
Source: https://www.tensorflow.org/guide/saved_model#prepare_serving_inputs