If you’ve successfully trained your first custom AutoML neuronal translation model, the next step is to integrate it into your application.
Here’s a python3 utility class that easily allows you to translate using your custom model:
class GNTMAutoMLTranslationDriver(object): """ Custom AutoML model translator. Usage example (be sure to use your own model here!): >>> translator = GNTMAutoMLTranslationDriver('myproject-101472', 'TRL455090968000816104449') >>> translator.translate("This is a translation test") """ def __init__(self, project_id, model_id): self.client = automl_v1beta1.PredictionServiceClient() self._name = 'projects/{}/locations/us-central1/models/{}'.format(project_id, model_id) def translate(self, engl): payload = {'text_snippet': {'content': engl}} params = {} request = self.client.predict(self._name, payload, params) return request.payload[0].translation.translated_content.content
See the class documentation for a usage example. Most of the code is also present in the official AutoML example, but I had to figure out some parts for myself, e.g. how to extract the string from the protobuf (request.payload[0].translation.translated_content.content
).
Also note that AutoML is currently in Beta and therefore the API might change without prior notice.