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upload-model.js
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upload-model.js
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/*
* 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(
modelDisplayName,
imageUri,
artifactUri,
project,
location = 'us-central1'
) {
// [START aiplatform_upload_model_sample]
/**
* TODO(developer): Uncomment these variables before running the sample.\
*/
// const modelDisplayName = 'YOUR_MODEL_DISPLAY_NAME';
// const metadataSchemaUri = 'YOUR_METADATA_SCHEMA_URI';
// const imageUri = 'YOUR_IMAGE_URI';
// const artifactUri = 'YOUR_ARTIFACT_URI';
// const project = 'YOUR_PROJECT_ID';
// const location = 'YOUR_PROJECT_LOCATION';
// Imports the Google Cloud Model Service Client library
const {ModelServiceClient} = require('@google-cloud/aiplatform');
// Specifies the location of the api endpoint
const clientOptions = {
apiEndpoint: 'us-central1-aiplatform.googleapis.com',
};
// Instantiates a client
const modelServiceClient = new ModelServiceClient(clientOptions);
async function uploadModel() {
// Configure the parent resources
const parent = `projects/${project}/locations/${location}`;
// Configure the model resources
const model = {
displayName: modelDisplayName,
metadataSchemaUri: '',
artifactUri: artifactUri,
containerSpec: {
imageUri: imageUri,
command: [],
args: [],
env: [],
ports: [],
predictRoute: '',
healthRoute: '',
},
};
const request = {
parent,
model,
};
console.log('PARENT AND MODEL');
console.log(parent, model);
// Upload Model request
const [response] = await modelServiceClient.uploadModel(request);
console.log(`Long running operation : ${response.name}`);
// Wait for operation to complete
await response.promise();
const result = response.result;
console.log('Upload model response ');
console.log(`\tModel : ${result.model}`);
}
uploadModel();
// [END aiplatform_upload_model_sample]
}
process.on('unhandledRejection', err => {
console.error(err.message);
process.exitCode = 1;
});
main(...process.argv.slice(2));