Class DeployClient
azureml.deploy.DeployClient(host, auth=None, use=None)
Defines the factory for creating Deployment Clients.
Basic Usage Module implementation plugin with use
property:
Find and Load module from an import reference:
from azureml.deploy import DeployClient
from azureml.deploy.server import MLServer
host = 'http://localhost:12800'
ctx = ('username', 'password')
mls_client = DeployClient(host, use=MLServer, auth=ctx)
Find and Load module as defined by use from namespace str:
host = 'http://localhost:12800'
ctx = ('username', 'password')
mls_client = DeployClient(host, use=MLServer, auth=ctx)
mls_client = DeployClient(host, use='azureml.deploy.server.MLServer',
auth=ctx)
Find and Load module from a file/path tuple:
host = 'http://localhost:12800'
ctx = ('username', 'password')
use = ('azureml.deploy.server.MLServer', '/path/to/mlserver.py')
mls_client = DeployClient(host, use=use, auth=ctx)
Create a new Deployment Client.
Arguments
host
Server HTTP/HTTPS endpoint, including the port number.
auth
(optional) Authentication context. Not all deployment clients require authentication. The auth is required for MLServer
use
(required) Deployment implementation to use (ex) use='MLServer' to use The ML Server.
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