Are gcloud ml-engine calls included in the google-cloud client library for python? I currently cannot find any documentation for it (though I see the natural language API). I am trying to replicate the following command in a jupyter notebook via the API and have not had any success:
gcloud ml-engine local predict --json-instances=XXX --model-dir=YYY
UPDATE w/ solution
with open('test.json') as data_file:
json_request = json.load(data_file)
response = predict_json(project = PROJECT_ID,
model= 'test_model',
instances = [json_request],
version = 'v1')
I believe what you are looking for can be found in the official documentation under the section "Requesting predictions" (be sure to click on the Python tab).
For your convenience:
def predict_json(project, model, instances, version=None):
"""Send json data to a deployed model for prediction.
Args:
project (str): project where the Cloud ML Engine Model is deployed.
model (str): model name.
instances ([Mapping[str: Any]]): Keys should be the names of Tensors
your deployed model expects as inputs. Values should be datatypes
convertible to Tensors, or (potentially nested) lists of datatypes
convertible to tensors.
version: str, version of the model to target.
Returns:
Mapping[str: any]: dictionary of prediction results defined by the
model.
"""
# Create the ML Engine service object.
# To authenticate set the environment variable
# GOOGLE_APPLICATION_CREDENTIALS=<path_to_service_account_file>
service = googleapiclient.discovery.build('ml', 'v1')
name = 'projects/{}/models/{}'.format(project, model)
if version is not None:
name += '/versions/{}'.format(version)
response = service.projects().predict(
name=name,
body={'instances': instances}
).execute()
if 'error' in response:
raise RuntimeError(response['error'])
return response['predictions']