Deployments Client

Importing
from gradient import DeploymentsClient
api_key='YOUR_API_KEY'
​
deployment_client = DeploymentsClient(api_key)
Select model to deploy
Get a model to deploy by either selecting experiment output or filtering based on some criteria from a project
model = models_client.list(experiment_id = experiment_id)[0]
Deployment parameters
deployment_param = {
    "deployment_type" : "Tensorflow Serving on K8s",
    "image_url": "tensorflow/serving:latest-gpu",
    "name": "sdk_tutorial",
    "machine_type": "K80",
    "instance_count": 2,
    "model_id" : model.id
}
Create the deployment
deployment_id = deployment_client.create(**deploy_param)
Start the deployment
deployment_client.start(deployment_id)
Stop a deployment
deployment_client.stop(deployment_id)
​

Models Client

Jobs Client

Last updated -2

Deployments Client

Importing

Select model to deploy

Deployment parameters

Create the deployment

Start the deployment

Stop a deployment

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