model_id = "88"
# Get the various Model CRN details
HOST = os.getenv("CDSW_API_URL").split(":")[0] + "://" + os.getenv(
"CDSW_DOMAIN")
USERNAME = os.getenv("CDSW_PROJECT_URL").split("/")[
6] # args.username # "vdibia"
API_KEY = os.getenv("CDSW_API_KEY")
PROJECT_NAME = os.getenv("CDSW_PROJECT")
cml = CMLBootstrap(HOST, USERNAME, API_KEY, PROJECT_NAME)
latest_model = cml.get_model({
"id": model_id,
"latestModelDeployment": True,
"latestModelBuild": True
})
Model_CRN = latest_model["crn"]
Deployment_CRN = latest_model["latestModelDeployment"]["crn"]
# Read in the model metrics dict.
model_metrics = cdsw.read_metrics(model_crn=Model_CRN,
model_deployment_crn=Deployment_CRN)
# This is a handy way to unravel the dict into a big pandas dataframe.
metrics_df = pd.io.json.json_normalize(
model_metrics["metrics"]) # [metric_start_index:])
metrics_df.tail().T
"memoryMb":
2048,
"nvidiaGPUs":
0,
"replicationPolicy": {
"type": "fixed",
"numReplicas": 1
},
"environment": {}
}
new_model_details = cml.create_model(create_model_params)
access_key = new_model_details["accessKey"] # todo check for bad response
print("New model created with access key", access_key)
# Wait for the model to deploy.
is_deployed = False
while is_deployed == False:
model = cml.get_model({
"id": str(new_model_details["id"]),
"latestModelDeployment": True,
"latestModelBuild": True
})
if model["latestModelDeployment"]["status"] == 'deployed':
print("Model is deployed")
break
else:
print("Model deployment status .....",
model["latestModelDeployment"]["status"])
time.sleep(10)
USERNAME = os.getenv("CDSW_PROJECT_URL").split("/")[6]
API_KEY = os.getenv("CDSW_API_KEY")
PROJECT_NAME = os.getenv("CDSW_PROJECT")
cml = CMLBootstrap(HOST, USERNAME, API_KEY, PROJECT_NAME)
# Get newly deployed churn model details using cmlbootstrapAPI
models = cml.get_models({})
churn_model_details = [
model for model in models
if model["name"] == "Churn Model API Endpoint" and model["creator"]
["username"] == USERNAME and model["project"]["slug"] == PROJECT_NAME
][0]
latest_model = cml.get_model({
"id": churn_model_details["id"],
"latestModelDeployment": True,
"latestModelBuild": True,
})
Model_CRN = latest_model["crn"]
Deployment_CRN = latest_model["latestModelDeployment"]["crn"]
model_endpoint = (HOST.split("//")[0] + "//modelservice." +
HOST.split("//")[1] + "/model")
# This will randomly return True for input and increases the likelihood of returning
# true based on `percent`
def churn_error(item, percent):
if random.random() < percent:
return True
else: