Function main

samples/prediction/prediction.py:75–154

(argv)

def main(argv):
    # If you previously ran this app with an earlier version of the API
    # or if you change the list of scopes below, revoke your app's permission
    # here: https://accounts.google.com/IssuedAuthSubTokens
    # Then re-run the app to re-authorize it.
    service, flags = sample_tools.init(
        argv,
        "prediction",
        "v1.6",
        __doc__,
        __file__,
        parents=[argparser],
        scope=(
            "https://www.googleapis.com/auth/prediction",
            "https://www.googleapis.com/auth/devstorage.read_only",
        ),
    )

    try:
        # Get access to the Prediction API.
        papi = service.trainedmodels()

        # List models.
        print_header("Fetching list of first ten models")
        result = papi.list(maxResults=10, project=flags.project_id).execute()
        print("List results:")
        pprint.pprint(result)

        # Start training request on a data set.
        print_header("Submitting model training request")
        body = {"id": flags.model_id, "storageDataLocation": flags.object_name}
        start = papi.insert(body=body, project=flags.project_id).execute()
        print("Training results:")
        pprint.pprint(start)

        # Wait for the training to complete.
        print_header("Waiting for training to complete")
        while True:
            status = papi.get(id=flags.model_id, project=flags.project_id).execute()
            state = status["trainingStatus"]
            print("Training state: " + state)
            if state == "DONE":
                break
            elif state == "RUNNING":
                time.sleep(SLEEP_TIME)
                continue
            else:
                raise Exception("Training Error: " + state)

            # Job has completed.
            print("Training completed:")
            pprint.pprint(status)
            break

        # Describe model.
        print_header("Fetching model description")
        result = papi.analyze(id=flags.model_id, project=flags.project_id).execute()
        print("Analyze results:")