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53 changes: 53 additions & 0 deletions ml_engine/online_prediction/scikit-xg-predict.py
Original file line number Diff line number Diff line change
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# Copyright 2018 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Examples of using the Cloud ML Engine's online prediction service,
modified for scikit-learn and XGBoost."""

import googleapiclient.discovery


# [START predict_json]
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 ([[float]]): List of input instances, where each input
instance is a list of floats.
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']
# [END predict_json]