feat(samples): adds samples for enhanced version of library (#16)

ai-platform/snippets/create-batch-prediction-job-video-classification.js

@@ -0,0 +1,110 @@
+/*
+ * 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(
+  batchPredictionDisplayName,
+  modelId,
+  gcsSourceUri,
+  gcsDestinationOutputUriPrefix,
+  project,
+  location = 'us-central1'
+) {
+  // [START aiplatform_create_batch_prediction_job_video_classification]
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.\
+   * (Not necessary if passing values as arguments)
+   */
+
+  // const batchPredictionDisplayName = 'YOUR_BATCH_PREDICTION_DISPLAY_NAME';
+  // const modelId = 'YOUR_MODEL_ID';
+  // const gcsSourceUri = 'YOUR_GCS_SOURCE_URI';
+  // const gcsDestinationOutputUriPrefix = 'YOUR_GCS_DEST_OUTPUT_URI_PREFIX';
+  //    eg. "gs://<your-gcs-bucket>/destination_path"
+  // const project = 'YOUR_PROJECT_ID';
+  // const location = 'YOUR_PROJECT_LOCATION';
+  const aiplatform = require('@google-cloud/aiplatform');
+  const {
+    params,
+  } = aiplatform.protos.google.cloud.aiplatform.v1beta1.schema.predict;
+
+  // Imports the Google Cloud Job Service Client library
+  const {JobServiceClient} = require('@google-cloud/aiplatform');
+
+  // Specifies the location of the api endpoint
+  const clientOptions = {
+    apiEndpoint: 'us-central1-aiplatform.googleapis.com',
+  };
+
+  // Instantiates a client
+  const jobServiceClient = new JobServiceClient(clientOptions);
+
+  async function createBatchPredictionJobVideoClassification() {
+    // Configure the parent resource
+    const parent = `projects/${project}/locations/${location}`;
+    const modelName = `projects/${project}/locations/${location}/models/${modelId}`;
+
+    // For more information on how to configure the model parameters object, see
+    // https://cloud.google.com/ai-platform-unified/docs/predictions/batch-predictions
+    const modelParamsObj = new params.VideoClassificationPredictionParams({
+      confidenceThreshold: 0.5,
+      maxPredictions: 1000,
+      segmentClassification: true,
+      shotClassification: true,
+      oneSecIntervalClassification: true,
+    });
+
+    const modelParameters = modelParamsObj.toValue();
+
+    const inputConfig = {
+      instancesFormat: 'jsonl',
+      gcsSource: {uris: [gcsSourceUri]},
+    };
+    const outputConfig = {
+      predictionsFormat: 'jsonl',
+      gcsDestination: {outputUriPrefix: gcsDestinationOutputUriPrefix},
+    };
+    const batchPredictionJob = {
+      displayName: batchPredictionDisplayName,
+      model: modelName,
+      modelParameters,
+      inputConfig,
+      outputConfig,
+    };
+    const request = {
+      parent,
+      batchPredictionJob,
+    };
+
+    // Create batch prediction job request
+    const [response] = await jobServiceClient.createBatchPredictionJob(request);
+
+    console.log('Create batch prediction job video classification response');
+    console.log(`Name : ${response.name}`);
+    console.log('Raw response:');
+    console.log(JSON.stringify(response, null, 2));
+  }
+  createBatchPredictionJobVideoClassification();
+  // [END aiplatform_create_batch_prediction_job_video_classification]
+}
+
+process.on('unhandledRejection', err => {
+  console.error(err.message);
+  process.exitCode = 1;
+});
+
+main(...process.argv.slice(2));

ai-platform/snippets/create-batch-prediction-job-video-object-tracking.js

@@ -0,0 +1,106 @@
+/*
+ * 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(
+  batchPredictionDisplayName,
+  modelId,
+  gcsSourceUri,
+  gcsDestinationOutputUriPrefix,
+  project,
+  location = 'us-central1'
+) {
+  // [START aiplatform_create_batch_prediction_job_video_object_tracking]
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.\
+   * (Not necessary if passing values as arguments)
+   */
+
+  // const batchPredictionDisplayName = 'YOUR_BATCH_PREDICTION_DISPLAY_NAME';
+  // const modelId = 'YOUR_MODEL_ID';
+  // const gcsSourceUri = 'YOUR_GCS_SOURCE_URI';
+  // const gcsDestinationOutputUriPrefix = 'YOUR_GCS_DEST_OUTPUT_URI_PREFIX';
+  //    eg. "gs://<your-gcs-bucket>/destination_path"
+  // const project = 'YOUR_PROJECT_ID';
+  // const location = 'YOUR_PROJECT_LOCATION';
+  const aiplatform = require('@google-cloud/aiplatform');
+  const {
+    params,
+  } = aiplatform.protos.google.cloud.aiplatform.v1beta1.schema.predict;
+
+  // Imports the Google Cloud Job Service Client library
+  const {JobServiceClient} = require('@google-cloud/aiplatform');
+
+  // Specifies the location of the api endpoint
+  const clientOptions = {
+    apiEndpoint: 'us-central1-aiplatform.googleapis.com',
+  };
+
+  // Instantiates a client
+  const jobServiceClient = new JobServiceClient(clientOptions);
+
+  async function createBatchPredictionJobVideoObjectTracking() {
+    // Configure the parent resource
+    const parent = `projects/${project}/locations/${location}`;
+    const modelName = `projects/${project}/locations/${location}/models/${modelId}`;
+
+    // For more information on how to configure the model parameters object, see
+    // https://cloud.google.com/ai-platform-unified/docs/predictions/batch-predictions
+    const modelParamsObj = new params.VideoObjectTrackingPredictionParams({
+      confidenceThreshold: 0.5,
+    });
+
+    const modelParameters = modelParamsObj.toValue();
+
+    const inputConfig = {
+      instancesFormat: 'jsonl',
+      gcsSource: {uris: [gcsSourceUri]},
+    };
+    const outputConfig = {
+      predictionsFormat: 'jsonl',
+      gcsDestination: {outputUriPrefix: gcsDestinationOutputUriPrefix},
+    };
+    const batchPredictionJob = {
+      displayName: batchPredictionDisplayName,
+      model: modelName,
+      modelParameters,
+      inputConfig,
+      outputConfig,
+    };
+    const request = {
+      parent,
+      batchPredictionJob,
+    };
+
+    // Create batch prediction job request
+    const [response] = await jobServiceClient.createBatchPredictionJob(request);
+
+    console.log('Create batch prediction job video object tracking response');
+    console.log(`Name : ${response.name}`);
+    console.log('Raw response:');
+    console.log(JSON.stringify(response, null, 2));
+  }
+  createBatchPredictionJobVideoObjectTracking();
+  // [END aiplatform_create_batch_prediction_job_video_object_tracking]
+}
+
+process.on('unhandledRejection', err => {
+  console.error(err.message);
+  process.exitCode = 1;
+});
+
+main(...process.argv.slice(2));

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

@@ -92,35 +92,9 @@ function main(
     );
 
     console.log('Create training pipeline image classification response');
-    console.log(`\tName : ${response.name}`);
-    console.log(`\tDisplay Name : ${response.displayName}`);
-    console.log(
-      `\tTraining task definition : ${response.trainingTaskDefinition}`
-    );
-    console.log(
-      `\tTraining task inputs : \
-        ${JSON.stringify(response.trainingTaskInputs)}`
-    );
-    console.log(
-      `\tTraining task metadata : \
-        ${JSON.stringify(response.trainingTaskMetadata)}`
-    );
-    console.log(`\tState ; ${response.state}`);
-    console.log(`\tCreate time : ${JSON.stringify(response.createTime)}`);
-    console.log(`\tStart time : ${JSON.stringify(response.startTime)}`);
-    console.log(`\tEnd time : ${JSON.stringify(response.endTime)}`);
-    console.log(`\tUpdate time : ${JSON.stringify(response.updateTime)}`);
-    console.log(`\tLabels : ${JSON.stringify(response.labels)}`);
-
-    const error = response.error;
-    console.log('\tError');
-    if (error === null) {
-      console.log('\t\tCode : {}');
-      console.log('\t\tMessage : {}');
-    } else {
-      console.log(`\t\tCode : ${error.code}`);
-      console.log(`\t\tMessage : ${error.message}`);
-    }
+    console.log(`Name : ${response.name}`);
+    console.log('Raw response:');
+    console.log(JSON.stringify(response, null, 2));
   }
 
   createTrainingPipelineImageClassification();

ai-platform/snippets/create-training-pipeline-image-object-detection.js

@@ -0,0 +1,102 @@
+/*
+ * 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(
+  datasetId,
+  modelDisplayName,
+  trainingPipelineDisplayName,
+  project,
+  location = 'us-central1'
+) {
+  // [START aiplatform_create_training_pipeline_image_object_detection]
+  /**
+   * TODO(developer): Uncomment these variables before running the sample.\
+   * (Not necessary if passing values as arguments)
+   */
+
+  // const datasetId = 'YOUR_DATASET_ID';
+  // const modelDisplayName = 'YOUR_MODEL_DISPLAY_NAME';
+  // const trainingPipelineDisplayName = 'YOUR_TRAINING_PIPELINE_DISPLAY_NAME';
+  // const project = 'YOUR_PROJECT_ID';
+  // const location = 'YOUR_PROJECT_LOCATION';
+
+  const aiplatform = require('@google-cloud/aiplatform');
+  const {
+    definition,
+  } = aiplatform.protos.google.cloud.aiplatform.v1beta1.schema.trainingjob;
+  const ModelType = definition.AutoMlImageObjectDetectionInputs.ModelType;
+
+  // Imports the Google Cloud Pipeline Service Client library
+  const {PipelineServiceClient} = aiplatform;
+
+  // Specifies the location of the api endpoint
+  const clientOptions = {
+    apiEndpoint: 'us-central1-aiplatform.googleapis.com',
+  };
+
+  // Instantiates a client
+  const pipelineServiceClient = new PipelineServiceClient(clientOptions);
+
+  async function createTrainingPipelineImageObjectDetection() {
+    // Configure the parent resource
+    const parent = `projects/${project}/locations/${location}`;
+
+    const trainingTaskInputsObj = new definition.AutoMlImageObjectDetectionInputs(
+      {
+        disableEarlyStopping: false,
+        modelType: ModelType.CLOUD_HIGH_ACCURACY_1,
+        budgetMilliNodeHours: 20000,
+      }
+    );
+
+    const trainingTaskInputs = trainingTaskInputsObj.toValue();
+    const modelToUpload = {displayName: modelDisplayName};
+    const inputDataConfig = {datasetId: datasetId};
+    const trainingPipeline = {
+      displayName: trainingPipelineDisplayName,
+      trainingTaskDefinition:
+        'gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_image_object_detection_1.0.0.yaml',
+      trainingTaskInputs,
+      inputDataConfig,
+      modelToUpload,
+    };
+    const request = {
+      parent,
+      trainingPipeline,
+    };
+
+    // Create training pipeline request
+    const [response] = await pipelineServiceClient.createTrainingPipeline(
+      request
+    );
+
+    console.log('Create training pipeline image object detection response');
+    console.log(`Name : ${response.name}`);
+    console.log('Raw response:');
+    console.log(JSON.stringify(response, null, 2));
+  }
+  createTrainingPipelineImageObjectDetection();
+  // [END aiplatform_create_training_pipeline_image_object_detection]
+}
+
+process.on('unhandledRejection', err => {
+  console.error(err.message);
+  process.exitCode = 1;
+});
+
+main(...process.argv.slice(2));