predict-custom-trained-model.js

/*
 * Copyright 2020 Google LLC
 *
 * 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
 *
 *     https://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.
 */

'use strict';

async function main(filename, endpointId, project, location = 'us-central1') {
  // [START aiplatform_predict_custom_trained_model_sample]
  /**
   * TODO(developer): Uncomment these variables before running the sample.\
   * (Not necessary if passing values as arguments)
   */

  // const filename = "YOUR_PREDICTION_FILE_NAME";
  // const endpointId = "YOUR_ENDPOINT_ID";
  // const project = 'YOUR_PROJECT_ID';
  // const location = 'YOUR_PROJECT_LOCATION';
  const util = require('util');
  const {readFile} = require('fs');
  const readFileAsync = util.promisify(readFile);

  // Imports the Google Cloud Prediction Service Client library
  const {PredictionServiceClient} = require('@google-cloud/aiplatform');

  // Specifies the location of the api endpoint
  const clientOptions = {
    apiEndpoint: 'us-central1-aiplatform.googleapis.com',
  };

  // Instantiates a client
  const predictionServiceClient = new PredictionServiceClient(clientOptions);

  async function predictCustomTrainedModel() {
    // Configure the parent resource
    const endpoint = `projects/${project}/locations/${location}/endpoints/${endpointId}`;
    const parameters = {
      structValue: {
        fields: {},
      },
    };
    const instanceDict = await readFileAsync(filename, 'utf8');
    const instanceValue = JSON.parse(instanceDict);
    const instance = {
      structValue: {
        fields: {
          Age: {stringValue: instanceValue['Age']},
          Balance: {stringValue: instanceValue['Balance']},
          Campaign: {stringValue: instanceValue['Campaign']},
          Contact: {stringValue: instanceValue['Contact']},
          Day: {stringValue: instanceValue['Day']},
          Default: {stringValue: instanceValue['Default']},
          Deposit: {stringValue: instanceValue['Deposit']},
          Duration: {stringValue: instanceValue['Duration']},
          Housing: {stringValue: instanceValue['Housing']},
          Job: {stringValue: instanceValue['Job']},
          Loan: {stringValue: instanceValue['Loan']},
          MaritalStatus: {stringValue: instanceValue['MaritalStatus']},
          Month: {stringValue: instanceValue['Month']},
          PDays: {stringValue: instanceValue['PDays']},
          POutcome: {stringValue: instanceValue['POutcome']},
          Previous: {stringValue: instanceValue['Previous']},
        },
      },
    };

    const instances = [instance];
    const request = {
      endpoint,
      instances,
      parameters,
    };

    // Predict request
    const [response] = await predictionServiceClient.predict(request);

    console.log('Predict custom trained model response');
    console.log(`\tDeployed model id : ${response.deployedModelId}`);
    const predictions = response.predictions;
    console.log('\tPredictions :');
    for (const prediction of predictions) {
      console.log(`\t\tPrediction : ${JSON.stringify(prediction)}`);
    }
  }
  predictCustomTrainedModel();
  // [END aiplatform_predict_custom_trained_model_sample]
}

process.on('unhandledRejection', err => {
  console.error(err.message);
  process.exitCode = 1;
});

main(...process.argv.slice(2));