chicago taxi deploy model

deploy_model.py

def create_model(cloudml_client):
    """
    Creates a Model entity in AI Platform
    :param cloudml_client: discovery client
    """
    models = cloudml_client.projects().models()
    create_spec = {'name': model_name}

    models.create(body=create_spec,
                  parent=project_name).execute()


def deploy_version(cloudml_client, job_results):
    """
    Deploying the best trail's model to AI platform
    :param cloudml_client: discovery client
    :param job_results: response of the finished AI platform job
    """
    models = cloudml_client.projects().models()

    training_outputs = job_results['trainingOutput']
    version_spec = {
        "name": model_version,
        "isDefault": False,
        "runtimeVersion": training_outputs['builtInAlgorithmOutput']['runtimeVersion'],

        # Assuming the trials are sorted by performance (best is first)
        "deploymentUri": training_outputs['trials'][0]['builtInAlgorithmOutput']['modelPath'],
        "framework": training_outputs['builtInAlgorithmOutput']['framework'],
        "pythonVersion": training_outputs['builtInAlgorithmOutput']['pythonVersion'],
        "autoScaling": {
            'minNodes': 0
        }
    }

    versions = models.versions()
    response = versions.create(body=version_spec,
                    parent='{}/models/{}'.format(project_name, model_name)).execute()
    return response