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feat: adds enhancements to library (#22)
* feat: adds enhancements to library * chore: changes to synth.py * fix: broken pack n' play test * fix: add enhanced types to ts compiler * fix: project enabled * fix: adds docstrings to toValue(), fromValue() functions * fix: removing any * fix: edits to synth.py per reviewer * fix: add more test coverage * chore: added comment about conversion interface Co-authored-by: Sofia Leon <[email protected]>
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‎ai-platform/snippets/create-training-pipeline-image-classification.js

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/*
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* Copyright 2020 Google LLC
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* https://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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function main(
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datasetId,
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modelDisplayName,
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trainingPipelineDisplayName,
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project,
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location = 'us-central1'
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) {
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// [START aiplatform_create_training_pipeline_image_classification]
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/**
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* TODO(developer): Uncomment these variables before running the sample.
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* (Not necessary if passing values as arguments)
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*/
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/*
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const datasetId = 'YOUR DATASET';
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const modelDisplayName = 'NEW MODEL NAME;
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const trainingPipelineDisplayName = 'NAME FOR TRAINING PIPELINE';
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const project = 'YOUR PROJECT ID';
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const location = 'us-central1';
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*/
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// Imports the Google Cloud Pipeline Service Client library
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const aiplatform = require('@google-cloud/aiplatform');
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const {
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definition,
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} = aiplatform.protos.google.cloud.aiplatform.v1beta1.schema.trainingjob;
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const ModelType = definition.AutoMlImageClassificationInputs.ModelType;
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// Specifies the location of the api endpoint
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const clientOptions = {
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apiEndpoint: 'us-central1-aiplatform.googleapis.com',
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};
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// Instantiates a client
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const pipelineServiceClient = new aiplatform.PipelineServiceClient(
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clientOptions
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);
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async function createTrainingPipelineImageClassification() {
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// Configure the parent resource
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const parent = `projects/${project}/locations/${location}`;
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// Values should match the input expected by your model.
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const trainingTaskInputsMessage = new definition.AutoMlImageClassificationInputs(
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{
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multiLabel: true,
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modelType: ModelType.CLOUD,
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budgetMilliNodeHours: 8000,
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disableEarlyStopping: false,
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}
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);
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const trainingTaskInputs = trainingTaskInputsMessage.toValue();
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const trainingTaskDefinition =
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'gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_image_classification_1.0.0.yaml';
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const modelToUpload = {displayName: modelDisplayName};
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const inputDataConfig = {datasetId: datasetId};
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const trainingPipeline = {
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displayName: trainingPipelineDisplayName,
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trainingTaskDefinition,
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trainingTaskInputs,
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inputDataConfig: inputDataConfig,
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modelToUpload: modelToUpload,
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};
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const request = {
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parent,
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trainingPipeline,
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};
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// Create training pipeline request
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const [response] = await pipelineServiceClient.createTrainingPipeline(
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request
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);
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console.log('Create training pipeline image classification response');
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console.log(`\tName : ${response.name}`);
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console.log(`\tDisplay Name : ${response.displayName}`);
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console.log(
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`\tTraining task definition : ${response.trainingTaskDefinition}`
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);
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console.log(
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`\tTraining task inputs : \
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${JSON.stringify(response.trainingTaskInputs)}`
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);
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console.log(
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`\tTraining task metadata : \
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${JSON.stringify(response.trainingTaskMetadata)}`
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);
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console.log(`\tState ; ${response.state}`);
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console.log(`\tCreate time : ${JSON.stringify(response.createTime)}`);
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console.log(`\tStart time : ${JSON.stringify(response.startTime)}`);
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console.log(`\tEnd time : ${JSON.stringify(response.endTime)}`);
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console.log(`\tUpdate time : ${JSON.stringify(response.updateTime)}`);
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console.log(`\tLabels : ${JSON.stringify(response.labels)}`);
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const error = response.error;
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console.log('\tError');
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if (error === null) {
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console.log('\t\tCode : {}');
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console.log('\t\tMessage : {}');
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} else {
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console.log(`\t\tCode : ${error.code}`);
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console.log(`\t\tMessage : ${error.message}`);
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}
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}
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createTrainingPipelineImageClassification();
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// [END aiplatform_create_training_pipeline_image_classification]
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}
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process.on('unhandledRejection', err => {
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console.error(err.message);
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process.exitCode = 1;
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});
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main(...process.argv.slice(2));

‎ai-platform/snippets/list-endpoints.js

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/**
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* Copyright 2020, Google, LLC.
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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function main(projectId, location = 'us-central1') {
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// [START aiplatform_list_endpoints]
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/**
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* TODO(developer): Uncomment these variables before running the sample.
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*/
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// const projectId = 'YOUR_PROJECT_ID';
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// const location = 'YOUR_PROJECT_LOCATION';
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const {EndpointServiceClient} = require('@google-cloud/aiplatform');
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// Specifies the location of the api endpoint
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const clientOptions = {
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apiEndpoint: 'us-central1-aiplatform.googleapis.com',
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};
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const client = new EndpointServiceClient(clientOptions);
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async function listEndpoints() {
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// Configure the parent resource
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const parent = `projects/${projectId}/locations/${location}`;
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const request = {
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parent,
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};
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// Get and print out a list of all the endpoints for this resource
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const [result] = await client.listEndpoints(request);
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for (const endpoint of result) {
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console.log(`\nEndpoint name: ${endpoint.name}`);
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console.log(`Display name: ${endpoint.displayName}`);
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if (endpoint.deployedModels[0]) {
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console.log(
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`First deployed model: ${endpoint.deployedModels[0].model}`
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);
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}
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}
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}
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listEndpoints();
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// [END aiplatform_list_endpoints]
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}
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main(...process.argv.slice(2)).catch(err => {
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console.error(err);
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process.exitCode = 1;
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});

‎ai-platform/snippets/package.json

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"@google-cloud/aiplatform": "^1.0.0"
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},
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"devDependencies": {
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"mocha": "^8.0.0"
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"chai": "^4.2.0",
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"mocha": "^8.0.0",
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"uuid": "^8.3.1"
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}
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}

‎ai-platform/snippets/predict-image-classification.js

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/*
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* Copyright 2020 Google LLC
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* https://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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function main(filename, endpointId, project, location = 'us-central1') {
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// [START aiplatform_predict_image_classification]
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/**
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* TODO(developer): Uncomment these variables before running the sample.\
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* (Not necessary if passing values as arguments)
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*/
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// const filename = "YOUR_PREDICTION_FILE_NAME";
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// const endpointId = "YOUR_ENDPOINT_ID";
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// const project = 'YOUR_PROJECT_ID';
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// const location = 'YOUR_PROJECT_LOCATION';
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const aiplatform = require('@google-cloud/aiplatform');
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const {
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instance,
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params,
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prediction,
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} = aiplatform.protos.google.cloud.aiplatform.v1beta1.schema.predict;
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// Imports the Google Cloud Prediction Service Client library
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const {PredictionServiceClient} = aiplatform;
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// Specifies the location of the api endpoint
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const clientOptions = {
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apiEndpoint: 'us-central1-prediction-aiplatform.googleapis.com',
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};
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// Instantiates a client
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const predictionServiceClient = new PredictionServiceClient(clientOptions);
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async function predictImageClassification() {
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// Configure the endpoint resource
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const endpoint = `projects/${project}/locations/${location}/endpoints/${endpointId}`;
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const parametersObj = new params.ImageClassificationPredictionParams({
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confidenceThreshold: 0.5,
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maxPredictions: 5,
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});
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const parameters = parametersObj.toValue();
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const fs = require('fs');
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const image = fs.readFileSync(filename, 'base64');
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const instanceObj = new instance.ImageClassificationPredictionInstance({
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content: image,
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});
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const instanceValue = instanceObj.toValue();
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const instances = [instanceValue];
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const request = {
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endpoint,
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instances,
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parameters,
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};
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// Predict request
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const [response] = await predictionServiceClient.predict(request);
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console.log('Predict image classification response');
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console.log(`\tDeployed model id : ${response.deployedModelId}`);
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const predictions = response.predictions;
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console.log('\tPredictions :');
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for (const predictionValue of predictions) {
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const predictionResultObj = prediction.ClassificationPredictionResult.fromValue(
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predictionValue
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);
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for (const [i, label] of predictionResultObj.displayNames.entries()) {
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console.log(`\tDisplay name: ${label}`);
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console.log(`\tConfidences: ${predictionResultObj.confidences[i]}`);
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console.log(`\tIDs: ${predictionResultObj.ids[i]}\n\n`);
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}
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}
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}
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predictImageClassification();
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// [END aiplatform_predict_image_classification]
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}
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process.on('unhandledRejection', err => {
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console.error(err.message);
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process.exitCode = 1;
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});
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main(...process.argv.slice(2));

‎ai-platform/snippets/resources/daisy.jpg

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‎ai-platform/snippets/test/create-training-pipeline-image-classification.test.js

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/*
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* Copyright 2020 Google LLC
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* https://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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const {assert} = require('chai');
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const {after, describe, it} = require('mocha');
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const uuid = require('uuid').v4;
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const cp = require('child_process');
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const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
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const aiplatform = require('@google-cloud/aiplatform');
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const clientOptions = {
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apiEndpoint: 'us-central1-aiplatform.googleapis.com',
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};
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const pipelineServiceClient = new aiplatform.PipelineServiceClient(
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clientOptions
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);
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const datasetId = process.env.TRAINING_PIPELINE_IMAGE_CLASS_DATASET_ID;
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const modelDisplayName = `temp_create_training_pipeline_image_classification_model_test${uuid()}`;
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const trainingPipelineDisplayName = `temp_create_training_pipeline_image_classification_test_${uuid()}`;
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const project = process.env.CAIP_PROJECT_ID;
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const location = process.env.LOCATION;
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let trainingPipelineId;
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describe('AI platform create training pipeline image classification', () => {
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it('should create a new image classification training pipeline', async () => {
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const stdout = execSync(
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`node ./create-training-pipeline-image-classification.js ${datasetId} ${modelDisplayName} ${trainingPipelineDisplayName} ${project} ${location}`
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);
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assert.match(stdout, /\/locations\/us-central1\/trainingPipelines\//);
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trainingPipelineId = stdout
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.split('/locations/us-central1/trainingPipelines/')[1]
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.split('\n')[0];
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});
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after('should cancel the training pipeline and delete it', async () => {
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const name = pipelineServiceClient.trainingPipelinePath(
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project,
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location,
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trainingPipelineId
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);
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const cancelRequest = {
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name,
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};
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pipelineServiceClient.cancelTrainingPipeline(cancelRequest).then(() => {
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const deleteRequest = {
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name,
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};
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return pipelineServiceClient.deleteTrainingPipeline(deleteRequest);
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});
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});
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});

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