diff --git a/automl/snippets/list_operation_status.js b/automl/snippets/list_operation_status.js
index 4894d001e7e..49c98effd01 100644
--- a/automl/snippets/list_operation_status.js
+++ b/automl/snippets/list_operation_status.js
@@ -32,7 +32,7 @@ function main(projectId = 'YOUR_PROJECT_ID', location = 'us-central1') {
     // Construct request
     const request = {
       name: client.locationPath(projectId, location),
-      filter: '',
+      filter: `worksOn=projects/${projectId}/locations/${location}/models/*`,
     };
 
     const [response] = await client.operationsClient.listOperations(request);
diff --git a/automl/snippets/test/automlTablesDataset.v1beta1.test.js b/automl/snippets/test/automlTablesDataset.v1beta1.test.js
deleted file mode 100644
index ab3e8d30973..00000000000
--- a/automl/snippets/test/automlTablesDataset.v1beta1.test.js
+++ /dev/null
@@ -1,135 +0,0 @@
-// Copyright 2019 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';
-
-const {assert} = require('chai');
-const {describe, it} = require('mocha');
-const {execSync} = require('child_process');
-
-/** Tests for AutoML Tables "Dataset API" sample. */
-
-const cmdDataset = 'node automlTablesDataset.js';
-
-// TODO(developer): Before running the test cases, set the environment variables
-// PROJECT_ID, REGION_NAME and change the values of datasetId,
-// bigQueryDatasetId, importDataCsv, outputGcsUri, outputGcsUri and
-// outputBigQueryUri.
-//const projectId = process.env.PROJECT_ID;
-//const computeRegion = process.env.REGION_NAME;
-const datasetName = 'test_table_dataset';
-const filter = 'tablesDatasetMetadata:*';
-const datasetId = 'TBL2246891593778855936';
-const bigQueryDatasetId = 'TBL5314616996204118016';
-const importDataCsv = 'gs://automl-tables/input/train.csv';
-const updateDatasetDisplayName = 'test_table_dataset_01';
-const dataTypeCode = 'CATEGORY';
-const outputGcsUri = 'gs://automl-tables/export-data/';
-const outputBigQueryUri = 'bq://automl-tables-bg-output';
-
-const exec = cmd => execSync(cmd, {encoding: 'utf8'});
-
-describe('Tables DatasetAPI', () => {
-  it.skip('should create, import, update and delete a dataset', async () => {
-    // Create dataset
-    let output = exec(`${cmdDataset} create-dataset "${datasetName}"`);
-    const parsedOut = output.split('\n');
-    const outputDatasetId = parsedOut[1].split(':')[1].trim();
-    assert.match(output, /Dataset display name:/);
-
-    // Import data
-    output = exec(
-      `${cmdDataset} import-data "${outputDatasetId}" "${importDataCsv}"`
-    );
-    assert.match(output, /Processing import.../);
-
-    // Update dataset
-    output = exec(
-      `${cmdDataset} update-dataset "${outputDatasetId}"` +
-        ` "${updateDatasetDisplayName}"`
-    );
-    assert.match(output, /Dataset Id:/);
-
-    // Delete dataset
-    output = exec(`${cmdDataset} delete-dataset "${outputDatasetId}"`);
-    assert.match(output, /Dataset delete details:/);
-  });
-
-  it.skip('should list datasets', async () => {
-    // List dataset
-    const output = exec(`${cmdDataset} list-datasets "${filter}"`);
-    assert.match(output, /Dataset Id:/);
-  });
-
-  it.skip('should get preexisting dataset', async () => {
-    // Get dataset
-    const output = exec(`${cmdDataset} get-dataset "${datasetId}"`);
-    assert.match(output, /Dataset Id:/);
-  });
-
-  it.skip('should get,list,update tablespec and columnspec', async () => {
-    // List table
-    let output = exec(
-      `${cmdDataset} list-table-specs` + ` "${datasetId}" "${filter}"`
-    );
-    let parsedOut = output.split('\n');
-    const outputTableId = parsedOut[1].split(':')[1].trim().split('/')[7];
-    assert.match(output, /Table Id:/);
-
-    // Get table
-    output = exec(
-      `${cmdDataset} get-table-spec` + ` "${datasetId}" "${outputTableId}"`
-    );
-    assert.match(output, /Table Id:/);
-
-    // List column
-    output = exec(
-      `${cmdDataset} list-column-specs` + ` "${datasetId}" "${outputTableId}"`
-    );
-    parsedOut = output.split('\n');
-    const outputColumnId = parsedOut[1].split(':')[1].trim().split('/')[9];
-    assert.match(output, /Column Id:/);
-
-    // Get column
-    output = exec(
-      `${cmdDataset} get-column-spec` +
-        ` "${datasetId}" "${outputTableId}" "${outputColumnId}"`
-    );
-    assert.match(output, /Column Id:/);
-
-    // Update column
-    output = exec(
-      `${cmdDataset} update-column-spec` +
-        ` "${datasetId}" "${outputTableId}" "${outputColumnId}" "${dataTypeCode}"`
-    );
-    assert.match(output, /Column Id:/);
-  });
-
-  it.skip('should export CSV dataset', async () => {
-    // Export data to csv
-    const output = exec(
-      `${cmdDataset} export-data-to-csv` + ` "${datasetId}" "${outputGcsUri}"`
-    );
-    assert.match(output, /Processing export.../);
-  });
-
-  it.skip('should export BigQuery dataset', async () => {
-    // Export data to bigquery
-    const output = exec(
-      `${cmdDataset} export-data-to-bigquery` +
-        ` "${bigQueryDatasetId}" "${outputBigQueryUri}"`
-    );
-    assert.match(output, /Processing export.../);
-  });
-});
diff --git a/automl/snippets/test/automlTablesModel.v1beta1.test.js b/automl/snippets/test/automlTablesModel.v1beta1.test.js
deleted file mode 100644
index 494e65d572b..00000000000
--- a/automl/snippets/test/automlTablesModel.v1beta1.test.js
+++ /dev/null
@@ -1,120 +0,0 @@
-// Copyright 2019 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';
-
-const {assert} = require('chai');
-const {describe, it} = require('mocha');
-const {execSync} = require('child_process');
-
-/** Tests for AutoML Tables "Model API" sample. */
-
-const cmdModel = 'node automlTablesModel.js';
-
-// TODO(developer): Before running the test cases, set the environment variables
-// PROJECT_ID, REGION_NAME and change the values of datasetId, tableId,
-// columnId, bqOutputUri, deployModelId and undeployModelId.
-//const projectId = process.env.PROJECT_ID;
-//const computeRegion = process.env.REGION_NAME;
-const datasetId = 'TBL2246891593778855936';
-const testModelName = 'test_tables_model';
-const tableId = '2071233616125362176';
-const columnId = '773141392279994368';
-const trainBudget = '1000';
-const bqOutputUri = 'bq://automl-tables-bg-output';
-const deployModelId = 'TBL4704590352927948800';
-const undeployModelId = 'TBL4508824506625687552';
-const filter = 'tablesModelMetadata:*';
-
-const exec = cmd => execSync(cmd, {encoding: 'utf8'});
-
-describe('Tables ModelAPI', () => {
-  it.skip('should create a model', async () => {
-    // Create model
-    let output = exec(
-      `${cmdModel} create-model "${datasetId}" "${tableId}" "${columnId}"` +
-        ` "${testModelName}" "${trainBudget}"`
-    );
-    const operationName = output.split('\n')[0].split(':')[1].trim();
-    assert.match(output, /Training started.../);
-
-    output = exec(`${cmdModel} get-operation-status "${operationName}"`);
-    assert.match(output, /Operation details:/);
-  });
-
-  it.skip(`should list models, get and delete a model. list, get, export and display
-     model evaluations from preexisting models`, async () => {
-    // List models
-    let output = exec(`${cmdModel} list-models "${filter}"`);
-    const parsedOut = output.split('\n');
-    const ouputModelId = parsedOut[3].split(':')[1].trim();
-    assert.match(output, /List of models:/);
-
-    // Get model
-    output = exec(`${cmdModel} get-model "${ouputModelId}"`);
-    assert.match(output, /Model name:/);
-
-    // List model evaluations
-    output = exec(`${cmdModel} list-model-evaluations "${ouputModelId}"`);
-    const parsedModelEvaluation = output.split('\n');
-    const modelEvaluationId = parsedModelEvaluation[2].split(':')[1].trim();
-    assert.match(output, /Model evaluation Id:/);
-
-    // Get model evaluation
-    output = exec(
-      `${cmdModel} get-model-evaluation "${ouputModelId}"` +
-        ` "${modelEvaluationId}"`
-    );
-    assert.match(output, /Model evaluation Id:/);
-
-    // Display evaluation
-    output = exec(`${cmdModel} display-evaluation "${ouputModelId}"`);
-    assert.match(output, /Model Evaluation ID:/);
-
-    // Export evaluated examples
-    output = exec(
-      `${cmdModel} export-evaluated-examples "${ouputModelId}"` +
-        ` "${bqOutputUri}"`
-    );
-    assert.match(output, /Operation name:/);
-
-    // Delete model
-    output = exec(`${cmdModel} delete-model "${ouputModelId}"`);
-    assert.match(output, /Model delete details:/);
-  });
-
-  it.skip('should deploy the model', async () => {
-    // Deploy model
-    const output = exec(`${cmdModel} deploy-model "${deployModelId}"`);
-    assert.match(output, /Name:/);
-  });
-
-  it.skip('should undeploy the model', async () => {
-    // Undeploy model
-    const output = exec(`${cmdModel} undeploy-model "${undeployModelId}"`);
-    assert.match(output, /Name:/);
-  });
-
-  it.skip('should list and get operation status', async () => {
-    // List operations status
-    let output = exec(`${cmdModel} list-operations-status `);
-    const operationFullId = output.split('\n')[3].split(':')[1].trim();
-    assert.match(output, /Operation details:/);
-
-    // Get operation status
-    // Poll operation status, here confirming that operation is not complete yet
-    output = exec(`${cmdModel} get-operation-status "${operationFullId}"`);
-    assert.match(output, /Operation details:/);
-  });
-});
diff --git a/automl/snippets/test/automlTranslation.test.js b/automl/snippets/test/automlTranslation.test.js
deleted file mode 100644
index 1317ff6f84e..00000000000
--- a/automl/snippets/test/automlTranslation.test.js
+++ /dev/null
@@ -1,91 +0,0 @@
-// Copyright 2020 Google LLC
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//      http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-'use strict';
-
-const {assert} = require('chai');
-const {describe, it} = require('mocha');
-const cp = require('child_process');
-const uuid = require('uuid');
-
-const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
-
-const automl = require('@google-cloud/automl');
-
-const cmdDataset = 'node translate/automlTranslateCreateDataset.js';
-const cmdModel = 'node translate/automlTranslateCreateModel.js';
-const cmdPredict = 'node translate/automlTranslatePredict.js';
-
-const projectId = process.env.AUTOML_PROJECT_ID || 'cdpe-automl-tests';
-const datasetId = process.env.TRANSLATION_DATASET_ID;
-const modelId = process.env.TRANSLATION_MODEL_ID;
-
-const samplePredictionText = './translate/resources/testInput.txt';
-
-describe('Translate AutoML sample tests', () => {
-  it('should create and delete a dataset', async () => {
-    const datasetDisplayName = `test_${uuid
-      .v4()
-      .replace(/-/g, '_')
-      .substring(0, 20)}`;
-
-    // Create dataset
-    let output = execSync(
-      `${cmdDataset} "${projectId}" "${datasetDisplayName}"`
-    );
-
-    //extract dataset id from the output
-    const newDatasetId = output.split('\n')[1].split(':')[1].trim();
-    assert.match(output, /Dataset id:/);
-
-    // Delete the created dataset
-    output = execSync(
-      `node delete_dataset.js ${projectId} us-central1 ${newDatasetId}`
-    );
-    assert.match(output, /Dataset deleted/);
-  });
-
-  it.skip('should create model and cancel the training operation', async () => {
-    // create a model with pre-existing dataset
-    const output = execSync(
-      `${cmdModel} ${projectId} us-central1 ${datasetId} translate_test_model`
-    );
-    assert.match(output, /Training started../);
-  });
-
-  it('should run Prediction from translation model', async () => {
-    // Verify the model is deployed before trying to predict
-    const client = new automl.AutoMlClient();
-
-    const modelFullId = {
-      name: client.modelPath(projectId, 'us-central1', modelId),
-    };
-
-    const [response] = await client.getModel(modelFullId);
-    if (response.deploymentState !== 'DEPLOYED') {
-      // Deploy model if it is not deployed
-      const [operation] = await client.deployModel(modelFullId);
-
-      // Wait for operation to complete.
-      const [response] = await operation.promise();
-      console.log(`Model deployment finished. ${response}`);
-    }
-
-    // Run prediction on 'testInput.txt' in resources folder
-    const output = execSync(
-      `${cmdPredict} "${projectId}" us-central1 "${modelId}" "${samplePredictionText}" "False"`
-    );
-    assert.match(output, /Translated Content:/);
-  });
-});
diff --git a/automl/snippets/test/automlVideoIntelligenceClassificationDataset.v1beta1.test.js b/automl/snippets/test/automlVideoIntelligenceClassificationDataset.v1beta1.test.js
deleted file mode 100644
index 3f6fc832dc8..00000000000
--- a/automl/snippets/test/automlVideoIntelligenceClassificationDataset.v1beta1.test.js
+++ /dev/null
@@ -1,77 +0,0 @@
-// Copyright 2019 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';
-
-const {assert} = require('chai');
-const {describe, it} = require('mocha');
-const {execSync} = require('child_process');
-
-/** Tests for AutoML Video Intelligence Classification "Dataset API" sample. */
-
-const cmdDataset = 'node automlVideoIntelligenceDataset.js';
-
-// TODO(developer): Before running the test cases,
-// set the environment variables PROJECT_ID, REGION_NAME and
-// change the value of datasetId
-const projectId = process.env.PROJECT_ID;
-//const computeRegion = process.env.REGION_NAME;
-const bucket = projectId + '-video';
-const datasetName = 'test_video_dataset';
-const filter = 'videoClassificationDatasetMetadata:*';
-const datasetId = 'VCN1802794449273618432';
-const importDataCsv = 'gs://automl-video-demo-data/hmdb_split1.csv';
-
-const exec = cmd => execSync(cmd, {encoding: 'utf8'});
-
-describe.skip('DatasetAPI', () => {
-  it('should create, import and delete a dataset', async () => {
-    // Create dataset
-    let output = exec(`${cmdDataset} create-dataset "${datasetName}"`);
-    const parsedOut = output.split('\n');
-    const outputDatasetId = parsedOut[1].split(':')[1].trim();
-    assert.match(output, /Dataset display name:/);
-
-    // Import data
-    output = exec(
-      `${cmdDataset} import-data "${outputDatasetId}" "${importDataCsv}"`
-    );
-    assert.match(output, /Processing import.../);
-
-    // Delete dataset
-    output = exec(`${cmdDataset} delete-dataset "${outputDatasetId}"`);
-    assert.match(output, /Dataset delete details:/);
-  });
-
-  it('should list datasets', async () => {
-    // List dataset
-    const output = exec(`${cmdDataset} list-datasets "${filter}"`);
-    assert.match(output, /List of datasets:/);
-  });
-
-  it('should get preexisting dataset', async () => {
-    // Get dataset
-    const output = exec(`${cmdDataset} get-dataset "${datasetId}"`);
-    assert.match(output, /Dataset display name:/);
-  });
-
-  it('should export dataset', async () => {
-    // Export data
-    const outputUri = 'gs://' + bucket + '/' + datasetId;
-    const output = exec(
-      `${cmdDataset} export-data "${datasetId}" "${outputUri}"`
-    );
-    assert.match(output, /Processing export.../);
-  });
-});
diff --git a/automl/snippets/test/automlVideoIntelligenceClassificationModel.v1beta1.test.js b/automl/snippets/test/automlVideoIntelligenceClassificationModel.v1beta1.test.js
deleted file mode 100644
index 85ac1c4bca4..00000000000
--- a/automl/snippets/test/automlVideoIntelligenceClassificationModel.v1beta1.test.js
+++ /dev/null
@@ -1,94 +0,0 @@
-// Copyright 2019 Google LLC
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     https://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-'use strict';
-
-const {assert} = require('chai');
-const {describe, it} = require('mocha');
-const {execSync} = require('child_process');
-
-/** Tests for AutoML Video Intelligence Classification "Model API" sample. */
-
-const cmdModel = 'node automlVideoIntelligenceModel.js';
-
-// TODO(developer): Before running the test cases,
-// set the environment variables PROJECT_ID, REGION_NAME and
-// change the values of datasetId
-//const projectId = process.env.PROJECT_ID;
-//const computeRegion = process.env.REGION_NAME;
-const filter = 'videoClassificationModelMetadata:*';
-const datasetId = 'VCN1653190499151904768';
-const testModelName = 'test_video_model';
-
-const exec = cmd => execSync(cmd, {encoding: 'utf8'});
-
-describe.skip('Video Intelligence ModelAPI', () => {
-  it('should create a model', async () => {
-    // Create model
-    let output = exec(
-      `${cmdModel} create-model "${datasetId}" "${testModelName}"`
-    );
-    const operationName = output.split('\n')[0].split(':')[1].trim();
-    assert.match(output, /Training started.../);
-
-    output = exec(`${cmdModel} get-operation-status "${operationName}"`);
-    assert.match(output, /Operation details:/);
-  });
-
-  it(`should list models, get and delete a model. list, get and display model
-    evaluations from preexisting models`, async () => {
-    // List models
-    let output = exec(`${cmdModel} list-models "${filter}"`);
-    const parsedOut = output.split('\n');
-    const ouputModelId = parsedOut[3].split(':')[1].trim();
-    assert.match(output, /List of models:/);
-
-    // Get model
-    output = exec(`${cmdModel} get-model "${ouputModelId}"`);
-    assert.match(output, /Model name:/);
-
-    // List model evaluations
-    output = exec(`${cmdModel} list-model-evaluations "${ouputModelId}"`);
-    const parsedModelEvaluation = output.split('\n');
-    const modelEvaluationId = parsedModelEvaluation[3].split(':')[1].trim();
-    assert.match(output, /Model evaluation Id:/);
-
-    // Get model evaluation
-    output = exec(
-      `${cmdModel} get-model-evaluation "${ouputModelId}" ` +
-        `"${modelEvaluationId}"`
-    );
-    assert.match(output, /Model evaluation Id:/);
-
-    // Display evaluation
-    output = exec(`${cmdModel} display-evaluation "${ouputModelId}"`);
-    assert.match(output, /Model Evaluation ID:/);
-
-    // Delete model
-    output = exec(`${cmdModel} delete-model "${ouputModelId}"`);
-    assert.match(output, /Model delete details:/);
-  });
-
-  it('should list and get operation status', async () => {
-    // List operation status
-    let output = exec(`${cmdModel} list-operations-status`);
-    const operationFullId = output.split('\n')[3].split(':')[1].trim();
-    assert.match(output, /Operation details:/);
-
-    // Get operation status
-    // Poll operation status, here confirming that operation is not complete yet
-    output = exec(`${cmdModel} get-operation-status "${operationFullId}"`);
-    assert.match(output, /Operation details:/);
-  });
-});
diff --git a/automl/snippets/test/automlVideoIntelligenceClassificationPredict.v1beta1.test.js b/automl/snippets/test/automlVideoIntelligenceClassificationPredict.v1beta1.test.js
deleted file mode 100644
index 68788d4a8db..00000000000
--- a/automl/snippets/test/automlVideoIntelligenceClassificationPredict.v1beta1.test.js
+++ /dev/null
@@ -1,45 +0,0 @@
-// Copyright 2019 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';
-
-const {assert} = require('chai');
-const {describe, it} = require('mocha');
-const {execSync} = require('child_process');
-
-/** Tests for AutoML Video Intelligence Classification "Prediction API" sample.
- */
-
-const cmdPredict = 'node automlVideoIntelligencePrediction.js';
-
-// TODO(developer): Before running the test cases,
-// set the environment variables PROJECT_ID, REGION_NAME and
-// change the values of modelId, inputUri and outputUriPrefix
-//const projectId = process.env.PROJECT_ID;
-//const computeRegion = process.env.REGION_NAME;
-const modelId = 'VCN5018751611309129728';
-const inputUri = 'gs://video-intelligence/input-csv/annotateVideo.csv';
-const outputUriPrefix = 'gs://video-intelligence/';
-
-const exec = cmd => execSync(cmd, {encoding: 'utf8'});
-
-describe.skip('Video Intelligence PredictionAPI', () => {
-  it('should run prediction from preexisting model', async () => {
-    // Run prediction on 'annotate_video.csv' from gcs inputUri
-    const output = exec(
-      `${cmdPredict} predict "${modelId}" "${inputUri}" "${outputUriPrefix}"`
-    );
-    assert.match(output, /Operation name:/);
-  });
-});
diff --git a/automl/snippets/test/automlVision.test.js b/automl/snippets/test/automlVision.test.js
deleted file mode 100644
index f5de798c4b1..00000000000
--- a/automl/snippets/test/automlVision.test.js
+++ /dev/null
@@ -1,132 +0,0 @@
-// Copyright 2018 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
-//
-//      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.
-
-'use strict';
-
-const path = require('path');
-const {assert} = require('chai');
-const {describe, it} = require('mocha');
-const cp = require('child_process');
-
-const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
-
-const cmdDataset = 'node vision/automlVisionDataset.js';
-const cmdModel = 'node vision/automlVisionModel.js';
-const cmdPredict = 'node vision/automlVisionPredict.js';
-
-const testDataSetName = 'testDataSet';
-const dummyDataSet = 'dummyDataSet';
-const testModelName = 'dummyModel';
-const testImgPath = './resources/';
-const sampleImage2 = path.join(testImgPath, 'testImage2.jpg');
-
-describe('auto ml vision', () => {
-  it.skip('should create, list, and delete a dataset', async () => {
-    // Check to see that this dataset does not yet exist
-    let output = execSync(`${cmdDataset} list-datasets`);
-    assert.strictEqual(output.includes(testDataSetName), false);
-
-    // Create dataset
-    output = execSync(`${cmdDataset} create-dataset -n "${testDataSetName}"`);
-    const dataSetId = output.split('\n')[1].split(':')[1].trim();
-    assert.match(output, new RegExp(testDataSetName));
-
-    // Delete dataset
-    output = execSync(`${cmdDataset} delete-dataset -i "${dataSetId}"`);
-    assert.match(output, /Dataset deleted./);
-  });
-
-  // See : https://github.com/GoogleCloudPlatform/python-docs-samples/blob/master/vision/automl/model_test.py
-  // We make two models running this test, see hard-coded workaround below
-  it.skip('should create a dataset, import data, and start making a model', async () => {
-    // Check to see that this dataset does not yet exist
-    let output = execSync(`${cmdDataset} list-datasets`);
-    assert.strictEqual(output.includes(dummyDataSet), false);
-
-    // Create dataset
-    output = execSync(`${cmdDataset} create-dataset -n "${dummyDataSet}"`);
-    const dataSetId = output.split('\n')[1].split(':')[1].trim();
-    assert.match(output, new RegExp(dummyDataSet));
-
-    // Import Data
-    output = execSync(
-      `${cmdDataset} import-data -i "${dataSetId}" -p "gs://nodejs-docs-samples-vcm/flowerTraindata20lines.csv"`
-    );
-    assert.match(output, /Data imported./);
-
-    // Check to make sure model doesn't already exist
-    output = execSync(`${cmdModel} list-models`);
-    assert.notMatch(output, new RegExp(testModelName));
-
-    // begin training dataset, getting operation ID for next operation
-    output = execSync(`
-      ${cmdModel} create-model -i "${dataSetId}" -m "${testModelName}" -t "2"`);
-    const operationName = output
-      .split('\n')[0]
-      .split(':')[1]
-      .split('/')
-      .pop()
-      .trim();
-    assert.match(output, /Training started.../);
-
-    // poll operation status, here confirming that operation is not complete yet
-    output = execSync(
-      `${cmdModel} get-operation-status -i "${dataSetId}" -o "${operationName}"`
-    );
-    assert.match(output, /done: false/);
-  });
-
-  it.skip('should display evaluation from prexisting model', async () => {
-    const flowersModelId = 'ICN723541179344731436';
-    const flowersDisplayName = 'flowersTest';
-
-    // Confirm dataset exists
-    let output = execSync(`${cmdDataset} list-datasets`);
-    assert.match(output, new RegExp(flowersDisplayName));
-
-    // List model evaluations, confirm model exists
-    output = execSync(
-      `${cmdModel} list-model-evaluations -a "${flowersModelId}"`
-    );
-
-    // Display evaluation
-    output = execSync(`${cmdModel} display-evaluation -a "${flowersModelId}"`);
-    assert.match(output, /Model Precision/);
-  });
-
-  it.skip('should run Prediction from prexisting model', async () => {
-    const donotdeleteModelId = 'ICN723541179344731436';
-    const flowersDisplayName = 'flowers';
-
-    // Confirm dataset exists
-    let output = execSync(`${cmdDataset} list-datasets`);
-    assert.match(output, new RegExp(flowersDisplayName));
-
-    // List model evaluations, confirm model exists
-    output = execSync(
-      `${cmdModel} list-model-evaluations -a "${donotdeleteModelId}"`
-    );
-    // Run prediction on 'testImage.jpg' in resources folder
-    output = execSync(
-      `${cmdPredict} predict -i "${donotdeleteModelId}" -f "${sampleImage2}" -s "0.5"`
-    );
-    assert.match(output, /dandelion/);
-  });
-
-  // List datasets
-  it('should list datasets', async () => {
-    const output = execSync(`${cmdDataset} list-datasets`);
-    assert.match(output, /List of datasets:/);
-  });
-});
diff --git a/automl/snippets/test/language_sentiment_analysis_create_model.test.js b/automl/snippets/test/language_sentiment_analysis_create_model.test.js
index d8320354909..39994297c5e 100644
--- a/automl/snippets/test/language_sentiment_analysis_create_model.test.js
+++ b/automl/snippets/test/language_sentiment_analysis_create_model.test.js
@@ -20,21 +20,22 @@ const {AutoMlClient} = require('@google-cloud/automl').v1;
 
 const cp = require('child_process');
 
-const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
-
 const CREATE_MODEL_REGION_TAG = 'language_sentiment_analysis_create_model';
 const LOCATION = 'us-central1';
-const DATASET_ID = 'TST8765214337653538816';
+const DATASET_ID = 'TST00000000000000000';
 
 describe('Automl Natural Language Sentiment Analysis Create Model Test', () => {
   const client = new AutoMlClient();
 
-  it.skip('should create a model', async () => {
+  it('should create a model', async () => {
+    // As sentimental analysis does not let you cancel model creation, instead try
+    // to create a model from a nonexistent dataset, but other elements of the
+    // request were valid.
     const projectId = await client.getProjectId();
-    const create_output = execSync(
-      `node ${CREATE_MODEL_REGION_TAG}.js ${projectId} ${LOCATION} ${DATASET_ID} sentiment_test_create_model`
-    );
+    const args = [CREATE_MODEL_REGION_TAG, projectId, LOCATION, DATASET_ID];
+    const output = cp.spawnSync('node', args, {encoding: 'utf8'});
 
-    assert.match(create_output, /Training started/);
+    assert.match(output.stderr, /NOT_FOUND/);
+    assert.match(output.stderr, /does not exist/);
   });
 });
diff --git a/automl/snippets/test/language_text_classification_create_model.test.js b/automl/snippets/test/language_text_classification_create_model.test.js
index 9827244b9c2..d90352e680c 100644
--- a/automl/snippets/test/language_text_classification_create_model.test.js
+++ b/automl/snippets/test/language_text_classification_create_model.test.js
@@ -20,21 +20,19 @@ const {AutoMlClient} = require('@google-cloud/automl').v1;
 
 const cp = require('child_process');
 
-const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
-
 const CREATE_MODEL_REGION_TAG = 'language_text_classification_create_model';
 const LOCATION = 'us-central1';
-const DATASET_ID = 'TCN4742936920458264576';
+const DATASET_ID = 'TCN00000000000000000';
 
 describe('Automl Natural Language Text Classification Create Model Test', () => {
   const client = new AutoMlClient();
 
-  it.skip('should create a model', async () => {
+  it('should create a model', async () => {
     const projectId = await client.getProjectId();
-    const create_output = execSync(
-      `node ${CREATE_MODEL_REGION_TAG}.js ${projectId} ${LOCATION} ${DATASET_ID} classification_test_create_model`
-    );
+    const args = [CREATE_MODEL_REGION_TAG, projectId, LOCATION, DATASET_ID];
+    const output = cp.spawnSync('node', args, {encoding: 'utf8'});
 
-    assert.match(create_output, /Training started/);
+    assert.match(output.stderr, /NOT_FOUND/);
+    assert.match(output.stderr, /Dataset does not exist./);
   });
 });
diff --git a/automl/snippets/test/list_operation_status.test.js b/automl/snippets/test/list_operation_status.test.js
index e3bda7bac91..f8ec88528e8 100644
--- a/automl/snippets/test/list_operation_status.test.js
+++ b/automl/snippets/test/list_operation_status.test.js
@@ -28,12 +28,12 @@ const LOCATION = 'us-central1';
 describe('Automl List Operation Status Tests', () => {
   const client = new AutoMlClient();
 
-  it.skip('should list operation status', async () => {
+  it('should list operation status', async () => {
     const projectId = await client.getProjectId();
 
     const list_output = execSync(
       `node ${LIST_OPERATION_STATUS_REGION_TAG}.js ${projectId} ${LOCATION} `
     );
-    assert.match(list_output, /Operation details/);
+    assert.match(list_output, /List of operation status:/);
   });
 });
diff --git a/automl/snippets/test/video-classification-create-model.beta.test.js b/automl/snippets/test/video-classification-create-model.beta.test.js
index 5c6aeb51f2f..68642281358 100644
--- a/automl/snippets/test/video-classification-create-model.beta.test.js
+++ b/automl/snippets/test/video-classification-create-model.beta.test.js
@@ -20,21 +20,22 @@ const {AutoMlClient} = require('@google-cloud/automl').v1beta1;
 
 const cp = require('child_process');
 
-const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
-
 const CREATE_MODEL_REGION_TAG = 'beta/video-classification-create-model';
 const LOCATION = 'us-central1';
-const DATASET_ID = 'VCN6097385712296919040';
+const DATASET_ID = 'VCN0000000000000000000';
 
 describe('Automl Video Classification Create Model Test', () => {
   const client = new AutoMlClient();
 
-  it.skip('should create a model', async () => {
+  it('should create a model', async () => {
+    // As video classification does not let you cancel model creation, instead try
+    // to create a model from a nonexistent dataset, but other elements of the
+    // request were valid.
     const projectId = await client.getProjectId();
-    const create_output = execSync(
-      `node ${CREATE_MODEL_REGION_TAG}.js ${projectId} ${LOCATION} ${DATASET_ID} video_test_create_model`
-    );
+    const args = [CREATE_MODEL_REGION_TAG, projectId, LOCATION, DATASET_ID];
+    const output = cp.spawnSync('node', args, {encoding: 'utf8'});
 
-    assert.match(create_output, /Training started/);
+    assert.match(output.stderr, /NOT_FOUND/);
+    assert.match(output.stderr, /Dataset does not exist./);
   });
 });
diff --git a/automl/snippets/test/video-object-tracking-create-model.beta.test.js b/automl/snippets/test/video-object-tracking-create-model.beta.test.js
index fb1845b4803..68021fe9a88 100644
--- a/automl/snippets/test/video-object-tracking-create-model.beta.test.js
+++ b/automl/snippets/test/video-object-tracking-create-model.beta.test.js
@@ -20,21 +20,22 @@ const {AutoMlClient} = require('@google-cloud/automl').v1beta1;
 
 const cp = require('child_process');
 
-const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
-
 const CREATE_MODEL_REGION_TAG = 'beta/video-object-tracking-create-model';
 const LOCATION = 'us-central1';
-const DATASET_ID = 'VOT9082518000266903552';
+const DATASET_ID = 'VOT0000000000000000000';
 
 describe('Automl Video Object Tracking Create Model Test', () => {
   const client = new AutoMlClient();
 
-  it.skip('should create a model', async () => {
+  it('should create a model', async () => {
+    // As object detection does not let you cancel model creation, instead try
+    // to create a model from a nonexistent dataset, but other elements of the
+    // request were valid.
     const projectId = await client.getProjectId();
-    const create_output = execSync(
-      `node ${CREATE_MODEL_REGION_TAG}.js ${projectId} ${LOCATION} ${DATASET_ID} video_test_create_model`
-    );
+    const args = [CREATE_MODEL_REGION_TAG, projectId, LOCATION, DATASET_ID];
+    const output = cp.spawnSync('node', args, {encoding: 'utf8'});
 
-    assert.match(create_output, /Training started/);
+    assert.match(output.stderr, /NOT_FOUND/);
+    assert.match(output.stderr, /Dataset does not exist./);
   });
 });
diff --git a/automl/snippets/test/vision_classification_create_model.test.js b/automl/snippets/test/vision_classification_create_model.test.js
index f2b3906d8ef..59b9a79e288 100644
--- a/automl/snippets/test/vision_classification_create_model.test.js
+++ b/automl/snippets/test/vision_classification_create_model.test.js
@@ -20,21 +20,22 @@ const {AutoMlClient} = require('@google-cloud/automl').v1;
 
 const cp = require('child_process');
 
-const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
-
 const CREATE_MODEL_REGION_TAG = 'vision_classification_create_model';
 const LOCATION = 'us-central1';
-const DATASET_ID = 'ICN6257835245115015168';
+const DATASET_ID = 'ICN000000000000000000';
 
 describe('Automl Vision Classification Create Model Tests', () => {
   const client = new AutoMlClient();
 
-  it.skip('should create a model', async () => {
+  it('should create a model', async () => {
+    // As vision classification does not let you cancel model creation, instead try
+    // to create a model from a nonexistent dataset, but other elements of the
+    // request were valid.
     const projectId = await client.getProjectId();
-    const create_output = execSync(
-      `node ${CREATE_MODEL_REGION_TAG}.js ${projectId} ${LOCATION} ${DATASET_ID} classification_test_create_model`
-    );
+    const args = [CREATE_MODEL_REGION_TAG, projectId, LOCATION, DATASET_ID];
+    const output = cp.spawnSync('node', args, {encoding: 'utf8'});
 
-    assert.match(create_output, /Training started/);
+    assert.match(output.stderr, /NOT_FOUND/);
+    assert.match(output.stderr, /Dataset does not exist./);
   });
 });
diff --git a/automl/snippets/test/vision_object_detection_create_model.test.js b/automl/snippets/test/vision_object_detection_create_model.test.js
index 2c53feea98c..a867bc1e533 100644
--- a/automl/snippets/test/vision_object_detection_create_model.test.js
+++ b/automl/snippets/test/vision_object_detection_create_model.test.js
@@ -20,21 +20,22 @@ const {AutoMlClient} = require('@google-cloud/automl').v1;
 
 const cp = require('child_process');
 
-const execSync = cmd => cp.execSync(cmd, {encoding: 'utf-8'});
-
 const CREATE_MODEL_REGION_TAG = 'vision_object_detection_create_model';
 const LOCATION = 'us-central1';
-const DATASET_ID = 'IOD4700715673951666176';
+const DATASET_ID = 'IOD0000000000000000000';
 
 describe('Automl Vision Object Detection Create Model Test', () => {
   const client = new AutoMlClient();
 
-  it.skip('should create a model', async () => {
+  it('should create a model', async () => {
+    // As object detection does not let you cancel model creation, instead try
+    // to create a model from a nonexistent dataset, but other elements of the
+    // request were valid.
     const projectId = await client.getProjectId();
-    const create_output = execSync(
-      `node ${CREATE_MODEL_REGION_TAG}.js ${projectId} ${LOCATION} ${DATASET_ID} object_test_create_model`
-    );
+    const args = [CREATE_MODEL_REGION_TAG, projectId, LOCATION, DATASET_ID];
+    const output = cp.spawnSync('node', args, {encoding: 'utf8'});
 
-    assert.match(create_output, /Training started/);
+    assert.match(output.stderr, /NOT_FOUND/);
+    assert.match(output.stderr, /Dataset does not exist./);
   });
 });
diff --git a/automl/snippets/vision/automlVisionDataset.js b/automl/snippets/vision/automlVisionDataset.js
deleted file mode 100644
index 1854ab3eb75..00000000000
--- a/automl/snippets/vision/automlVisionDataset.js
+++ /dev/null
@@ -1,290 +0,0 @@
-// Copyright 2018 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.
-
-/**
- * This application demonstrates how to perform basic operations on dataset
- * with the Google AutoML Vision API.
- *
- * For more information, see the documentation at
- * https://cloud.google.com/vision/automl/docs/
- */
-
-'use strict';
-
-function createDataset(projectId, computeRegion, datasetName, multiLabel) {
-  // [START automl_vision_create_dataset]
-  async function automlVisionCreateDataset() {
-    const automl = require('@google-cloud/automl').v1beta1;
-
-    const client = new automl.AutoMlClient();
-
-    /**
-     * TODO(developer): Uncomment the following line before running the sample.
-     */
-    // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
-    // const computeRegion = `region-name, e.g. "us-central1"`;
-    // const datasetName = `name of the dataset to create, e.g. “myDataset”`;
-    // const multiLabel = `type of classification problem, true for multilabel and false for multiclass e.g. "false"`;
-
-    // A resource that represents Google Cloud Platform location.
-    const projectLocation = client.locationPath(projectId, computeRegion);
-
-    // Classification type is assigned based on multilabel value.
-    let classificationType = 'MULTICLASS';
-    if (multiLabel) {
-      classificationType = 'MULTILABEL';
-    }
-
-    // Specify the text classification type for the dataset.
-    const datasetMetadata = {
-      classificationType: classificationType,
-    };
-
-    // Set dataset name and metadata.
-    const myDataset = {
-      displayName: datasetName,
-      imageClassificationDatasetMetadata: datasetMetadata,
-    };
-
-    // Create a dataset with the dataset metadata in the region.
-    const [dataset] = await client.createDataset({
-      parent: projectLocation,
-      dataset: myDataset,
-    });
-    // Display the dataset information.
-    console.log(`Dataset name: ${dataset.name}`);
-    console.log(`Dataset id: ${dataset.name.split('/').pop(-1)}`);
-    console.log(`Dataset display name: ${dataset.displayName}`);
-    console.log(`Dataset example count: ${dataset.exampleCount}`);
-    console.log('Image Classification type:');
-    console.log(
-      `\t ${dataset.imageClassificationDatasetMetadata.classificationType}`
-    );
-    console.log('Dataset create time:');
-    console.log(`\tseconds: ${dataset.createTime.seconds}`);
-    console.log(`\tnanos: ${dataset.createTime.nanos}`);
-  }
-
-  automlVisionCreateDataset().catch(console.error);
-  // [END automl_vision_create_dataset]
-}
-
-function listDatasets(projectId, computeRegion, filter) {
-  // [START automl_vision_list_datasets]
-  async function automlVisionListDatasets() {
-    const automl = require('@google-cloud/automl').v1beta1;
-
-    const client = new automl.AutoMlClient();
-    /**
-     * TODO(developer): Uncomment the following line before running the sample.
-     */
-    // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
-    // const computeRegion = `region-name, e.g. "us-central1"`;
-    // const filter = `filter expressions, must specify field e.g. “imageClassificationModelMetadata:*”`;
-
-    // A resource that represents Google Cloud Platform location.
-    const projectLocation = client.locationPath(projectId, computeRegion);
-
-    // List all the datasets available in the region by applying filter.
-    const [datasets] = await client.listDatasets({
-      parent: projectLocation,
-      filter: filter,
-    });
-    console.log('List of datasets:');
-    datasets.forEach(dataset => {
-      console.log(`Dataset name: ${dataset.name}`);
-      console.log(`Dataset Id: ${dataset.name.split('/').pop(-1)}`);
-      console.log(`Dataset display name: ${dataset.displayName}`);
-      console.log(`Dataset example count: ${dataset.exampleCount}`);
-      console.log('Image Classification type:');
-      console.log(
-        '\t',
-        dataset.imageClassificationDatasetMetadata.classificationType
-      );
-      console.log('Dataset create time: ');
-      console.log(`\tseconds: ${dataset.createTime.seconds}`);
-      console.log(`\tnanos: ${dataset.createTime.nanos}`);
-      console.log('\n');
-    });
-  }
-
-  automlVisionListDatasets().catch(console.error);
-  // [END automl_vision_list_datasets]
-}
-
-function importData(projectId, computeRegion, datasetId, path) {
-  // [START automl_vision_import_data]
-  async function automlVisionImportData() {
-    const automl = require('@google-cloud/automl').v1beta1;
-
-    const client = new automl.AutoMlClient();
-
-    /**
-     * TODO(developer): Uncomment the following line before running the sample.
-     */
-    // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
-    // const computeRegion = `region-name, e.g. "us-central1"`;
-    // const datasetId = `Id of the dataset`;
-    // const path = `string or array of .csv paths in AutoML Vision CSV format, e.g. “gs://myproject/traindata.csv”;`
-
-    // Get the full path of the dataset.
-    const datasetFullId = client.datasetPath(
-      projectId,
-      computeRegion,
-      datasetId
-    );
-
-    // Get one or more Google Cloud Storage URI(s).
-    const inputUris = path.split(',');
-    const inputConfig = {
-      gcsSource: {
-        inputUris: inputUris,
-      },
-    };
-
-    // Import the dataset from the input URI.
-    const [operation] = await client.importData({
-      name: datasetFullId,
-      inputConfig: inputConfig,
-    });
-    console.log('Processing import...');
-
-    const [, , response] = await operation.promise();
-
-    // The final result of the operation.
-    if (response.done) {
-      console.log('Data imported.');
-    }
-  }
-
-  automlVisionImportData().catch(console.error);
-  // [END automl_vision_import_data]
-}
-
-function deleteDataset(projectId, computeRegion, datasetId) {
-  // [START automl_vision_delete_dataset]
-  async function automlVisionDeleteDataset() {
-    const automl = require('@google-cloud/automl').v1beta1;
-
-    const client = new automl.AutoMlClient();
-
-    /**
-     * TODO(developer): Uncomment the following line before running the sample.
-     */
-    // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
-    // const computeRegion = `region-name, e.g. "us-central1"`;
-    // const datasetId = `Id of the dataset`;
-
-    // Get the full path of the dataset.
-    const datasetFullId = client.datasetPath(
-      projectId,
-      computeRegion,
-      datasetId
-    );
-
-    // Delete a dataset.
-    const [operation] = await client.deleteDataset({name: datasetFullId});
-    const [, , response] = await operation.promise();
-    // The final result of the operation.
-    if (response.done) {
-      console.log('Dataset deleted.');
-    }
-  }
-
-  automlVisionDeleteDataset().catch(console.error);
-  // [END automl_vision_delete_dataset]
-}
-
-require(`yargs`) // eslint-disable-line
-  .demand(1)
-  .options({
-    computeRegion: {
-      alias: 'c',
-      type: 'string',
-      default: 'us-central1',
-      requiresArg: true,
-      description: 'region name e.g. "us-central1"',
-    },
-    datasetName: {
-      alias: 'n',
-      type: 'string',
-      default: 'testDataSet',
-      requiresArg: true,
-      description: 'Name of the Dataset',
-    },
-    datasetId: {
-      alias: 'i',
-      type: 'string',
-      requiresArg: true,
-      description: 'Id of the dataset',
-    },
-    filter: {
-      alias: 'f',
-      default: 'image_classification_dataset_metadata:*',
-      type: 'string',
-      requiresArg: false,
-      description: 'Name of the Dataset to search for',
-    },
-    multilabel: {
-      alias: 'm',
-      type: 'string',
-      default: false,
-      requiresArg: true,
-      description:
-        'Type of the classification problem, ' +
-        'False - MULTICLASS, True - MULTILABEL.',
-    },
-    path: {
-      alias: 'p',
-      type: 'string',
-      global: true,
-      default: 'gs://nodejs-docs-samples-vcm/flowerTraindataMini.csv',
-      requiresArg: true,
-      description: 'URI or local path to input .csv, or array of .csv paths',
-    },
-    projectId: {
-      alias: 'z',
-      type: 'string',
-      default: process.env.GCLOUD_PROJECT,
-      requiresArg: true,
-      description: 'The GCLOUD_PROJECT string, e.g. "my-gcloud-project"',
-    },
-  })
-  .command('create-dataset', 'creates a new Dataset', {}, opts =>
-    createDataset(
-      opts.projectId,
-      opts.computeRegion,
-      opts.datasetName,
-      opts.multilabel
-    )
-  )
-  .command('list-datasets', 'list all Datasets', {}, opts =>
-    listDatasets(opts.projectId, opts.computeRegion, opts.filter)
-  )
-  .command('delete-dataset', 'Delete a dataset', {}, opts =>
-    deleteDataset(opts.projectId, opts.computeRegion, opts.datasetId)
-  )
-  .command('import-data', 'Import labeled items into dataset', {}, opts =>
-    importData(opts.projectId, opts.computeRegion, opts.datasetId, opts.path)
-  )
-  .example('node $0 create-dataset -n "newDataSet"')
-  .example('node $0 list-datasets -f "image_classification_dataset_metadata:*"')
-  .example('node $0 delete-dataset -i "DATASETID"')
-  .example(
-    'node $0 import-data -i "dataSetId" -p "gs://myproject/mytraindata.csv"'
-  )
-  .wrap(120)
-  .recommendCommands()
-  .help()
-  .strict().argv;
diff --git a/automl/snippets/vision/automlVisionModel.js b/automl/snippets/vision/automlVisionModel.js
deleted file mode 100644
index 5ce83f31463..00000000000
--- a/automl/snippets/vision/automlVisionModel.js
+++ /dev/null
@@ -1,489 +0,0 @@
-// Copyright 2018 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.
-
-/**
- * This application demonstrates how to perform basic operations on dataset
- * with the Google AutoML Vision API.
- *
- * For more information, see the documentation at
- * https://cloud.google.com/vision/automl/docs/
- */
-
-'use strict';
-
-function createModel(
-  projectId,
-  computeRegion,
-  datasetId,
-  modelName,
-  trainBudget
-) {
-  // [START automl_vision_create_model]
-  async function automlVisionCreateModel() {
-    const automl = require('@google-cloud/automl').v1beta1;
-
-    const client = new automl.AutoMlClient();
-
-    /**
-     * TODO(developer): Uncomment the following line before running the sample.
-     */
-    // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
-    // const computeRegion = `region-name, e.g. "us-central1"`;
-    // const datasetId = `Id of the dataset`;
-    // const modelName = `Name of the model, e.g. "myModel"`;
-    // const trainBudget = `Budget for training model, e.g. 50`;
-
-    // A resource that represents Google Cloud Platform location.
-    const projectLocation = client.locationPath(projectId, computeRegion);
-
-    // Check train budget condition.
-    if (trainBudget === 0) {
-      trainBudget = {};
-    } else {
-      trainBudget = {trainBudget: trainBudget};
-    }
-
-    // Set model name and model metadata for the dataset.
-    const myModel = {
-      displayName: modelName,
-      datasetId: datasetId,
-      imageClassificationModelMetadata: trainBudget,
-    };
-
-    // Create a model with the model metadata in the region.
-    const [operation, initialApiResponse] = await client.createModel({
-      parent: projectLocation,
-      model: myModel,
-    });
-    console.log('Training operation name: ', initialApiResponse.name);
-    console.log('Training started...');
-    const [model] = await operation.promise();
-
-    // Retrieve deployment state.
-    let deploymentState = '';
-    if (model.deploymentState === 1) {
-      deploymentState = 'deployed';
-    } else if (model.deploymentState === 2) {
-      deploymentState = 'undeployed';
-    }
-
-    // Display the model information.
-    console.log(`Model name: ${model.name}`);
-    console.log(`Model id: ${model.name.split('/').pop(-1)}`);
-    console.log(`Model display name: ${model.displayName}`);
-    console.log('Model create time:');
-    console.log(`\tseconds: ${model.createTime.seconds}`);
-    console.log(`\tnanos: ${model.createTime.nanos}`);
-    console.log(`Model deployment state: ${deploymentState}`);
-  }
-
-  automlVisionCreateModel().catch(console.error);
-  // [END automl_vision_create_model]
-}
-
-function listModels(projectId, computeRegion, filter) {
-  // [START automl_vision_list_models]
-  async function automlVisinListModels() {
-    const automl = require('@google-cloud/automl');
-
-    const client = new automl.v1beta1.AutoMlClient();
-
-    /**
-     * TODO(developer): Uncomment the following line before running the sample.
-     */
-    // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
-    // const computeRegion = `region-name, e.g. "us-central1"`;
-    // const filter = `filter expressions, must specify field, e.g. “imageClassificationModelMetadata:*”`;
-
-    // A resource that represents Google Cloud Platform location.
-    const projectLocation = client.locationPath(projectId, computeRegion);
-
-    // List all the models available in the region by applying filter.
-    const [models] = await client.listModels({
-      parent: projectLocation,
-      filter: filter,
-    });
-
-    // Display the model information.
-    console.log('List of models:');
-    models.forEach(model => {
-      console.log(`Model name: ${model.name}`);
-      console.log(`Model id: ${model.name.split('/').pop(-1)}`);
-      console.log(`Model display name: ${model.displayName}`);
-      console.log(`Model dataset id: ${model.datasetId}`);
-      if (model.modelMetadata === 'translationModelMetadata') {
-        console.log('Translation model metadata:');
-        console.log(
-          `\tBase model: ${model.translationModelMetadata.baseModel}`
-        );
-        console.log(
-          `\tSource language code: ${model.translationModelMetadata.sourceLanguageCode}`
-        );
-        console.log(
-          `\tTarget language code: ${model.translationModelMetadata.targetLanguageCode}`
-        );
-      } else if (model.modelMetadata === 'textClassificationModelMetadata') {
-        console.log(
-          `Text classification model metadata: ${model.textClassificationModelMetadata}`
-        );
-      } else if (model.modelMetadata === 'imageClassificationModelMetadata') {
-        console.log('Image classification model metadata:');
-        console.log(
-          `\tBase model id: ${model.imageClassificationModelMetadata.baseModelId}`
-        );
-        console.log(
-          `\tTrain budget: ${model.imageClassificationModelMetadata.trainBudget}`
-        );
-        console.log(
-          `\tTrain cost: ${model.imageClassificationModelMetadata.trainCost}`
-        );
-        console.log(
-          `\tStop reason: ${model.imageClassificationModelMetadata.stopReason}`
-        );
-      }
-      console.log('Model create time:');
-      console.log(`\tseconds: ${model.createTime.seconds}`);
-      console.log(`\tnanos: ${model.createTime.nanos}`);
-      console.log('Model update time:');
-      console.log(`\tseconds: ${model.updateTime.seconds}`);
-      console.log(`\tnanos: ${model.updateTime.nanos}`);
-      console.log(`Model deployment state: ${model.deploymentState}`);
-      console.log('\n');
-    });
-  }
-
-  automlVisinListModels().catch(console.error);
-  // [END automl_vision_list_models]
-}
-
-function getModel(projectId, computeRegion, modelId) {
-  // [START automl_vision_get_model]
-
-  async function automlVisionGetModel() {
-    const automl = require('@google-cloud/automl').v1beta1;
-
-    const client = new automl.AutoMlClient();
-
-    /**
-     * TODO(developer): Uncomment the following line before running the sample.
-     */
-    // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
-    // const computeRegion = `region-name, e.g. "us-central1"`;
-    // const modelId = `id of the model, e.g. “ICN12345”`;
-
-    // Get the full path of the model.
-    const modelFullId = client.modelPath(projectId, computeRegion, modelId);
-
-    // Get complete detail of the model.
-    const [model] = await client.getModel({name: modelFullId});
-
-    // Display the model information.
-    console.log(`Model name: ${model.name}`);
-    console.log(`Model id: ${model.name.split('/').pop(-1)}`);
-    console.log(`Model display name: ${model.displayName}`);
-    console.log(`Model dataset id: ${model.datasetId}`);
-    if (model.modelMetadata === 'translationModelMetadata') {
-      console.log('Translation model metadata:');
-      console.log(`\tBase model: ${model.translationModelMetadata.baseModel}`);
-      console.log(
-        `\tSource language code: ${model.translationModelMetadata.sourceLanguageCode}`
-      );
-      console.log(
-        `\tTarget language code: ${model.translationModelMetadata.targetLanguageCode}`
-      );
-    } else if (model.modelMetadata === 'textClassificationModelMetadata') {
-      console.log(
-        `Text classification model metadata: ${model.textClassificationModelMetadata}`
-      );
-    } else if (model.modelMetadata === 'imageClassificationModelMetadata') {
-      console.log('Image classification model metadata:');
-      console.log(
-        `\tBase model id: ${model.imageClassificationModelMetadata.baseModelId}`
-      );
-      console.log(
-        `\tTrain budget: ${model.imageClassificationModelMetadata.trainBudget}`
-      );
-      console.log(
-        `\tTrain cost: ${model.imageClassificationModelMetadata.trainCost}`
-      );
-      console.log(
-        `\tStop reason: ${model.imageClassificationModelMetadata.stopReason}`
-      );
-    }
-    console.log('Model create time:');
-    console.log(`\tseconds: ${model.createTime.seconds}`);
-    console.log(`\tnanos: ${model.createTime.nanos}`);
-    console.log('Model update time:');
-    console.log(`\tseconds: ${model.updateTime.seconds}`);
-    console.log(`\tnanos: ${model.updateTime.nanos}`);
-    console.log(`Model deployment state: ${model.deploymentState}`);
-  }
-
-  automlVisionGetModel().catch(console.error);
-  // [END automl_vision_get_model]
-}
-
-function listModelEvaluations(projectId, computeRegion, modelId, filter) {
-  // [START automl_vision_list_model_evaluations]
-  async function automlVisionListModelEvalution() {
-    const automl = require('@google-cloud/automl').v1beta1;
-    const util = require('util');
-
-    const client = new automl.AutoMlClient();
-    /**
-     * TODO(developer): Uncomment the following line before running the sample.
-     */
-    // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
-    // const computeRegion = `region-name, e.g. "us-central1"`;
-    // const modelId = `id of the model, e.g. “ICN12345”`;
-    // const filter = `filter expressions, must specify field, e.g. “imageClassificationModelMetadata:*”`;
-
-    // Get the full path of the model.
-    const modelFullId = client.modelPath(projectId, computeRegion, modelId);
-
-    // List all the model evaluations in the model by applying filter.
-    const [elements] = await client.listModelEvaluations({
-      parent: modelFullId,
-      filter: filter,
-    });
-    elements.forEach(element => {
-      console.log(util.inspect(element, false, null));
-    });
-  }
-
-  automlVisionListModelEvalution().catch(console.error);
-  // [END automl_vision_list_model_evaluations]
-}
-
-function displayEvaluation(projectId, computeRegion, modelId, filter) {
-  // [START automl_vision_display_evaluation]
-  async function automlVisionDisplayEvalution() {
-    const automl = require('@google-cloud/automl').v1beta1;
-    const math = require('mathjs');
-
-    const client = new automl.AutoMlClient();
-
-    /**
-     * TODO(developer): Uncomment the following line before running the sample.
-     */
-    // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
-    // const computeRegion = `region-name, e.g. "us-central1"`;
-    // const modelId = `id of the model, e.g. “ICN12345”`;
-    // const filter = `filter expressions, must specify field, e.g. “imageClassificationModelMetadata:*”`;
-
-    // Get the full path of the model.
-    const modelFullId = client.modelPath(projectId, computeRegion, modelId);
-
-    // List all the model evaluations in the model by applying filter.
-    const [response] = await client.listModelEvaluations({
-      parent: modelFullId,
-      filter: filter,
-    });
-    response.forEach(async element => {
-      // There is evaluation for each class in a model and for overall model.
-      // Get only the evaluation of overall model.
-      if (!element.annotationSpecId) {
-        const modelEvaluationId = element.name.split('/').pop(-1);
-
-        // Resource name for the model evaluation.
-        const modelEvaluationFullId = client.modelEvaluationPath(
-          projectId,
-          computeRegion,
-          modelId,
-          modelEvaluationId
-        );
-
-        let modelEvaluation = null;
-
-        (async () => {
-          [modelEvaluation] = await client.getModelEvaluation({
-            name: modelEvaluationFullId,
-          });
-        })();
-        const classMetrics = modelEvaluation.classificationEvaluationMetrics;
-        const confidenceMetricsEntries = classMetrics.confidenceMetricsEntry;
-
-        // Showing model score based on threshold of 0.5
-        confidenceMetricsEntries.forEach(confidenceMetricsEntry => {
-          if (confidenceMetricsEntry.confidenceThreshold === 0.5) {
-            console.log(
-              'Precision and recall are based on a score threshold of 0.5'
-            );
-            console.log(
-              'Model Precision: %',
-              math.round(confidenceMetricsEntry.precision * 100, 2)
-            );
-            console.log(
-              'Model Recall: %',
-              math.round(confidenceMetricsEntry.recall * 100, 2)
-            );
-            console.log(
-              'Model F1 score: %',
-              math.round(confidenceMetricsEntry.f1Score * 100, 2)
-            );
-            console.log(
-              'Model Precision@1: %',
-              math.round(confidenceMetricsEntry.precisionAt1 * 100, 2)
-            );
-            console.log(
-              'Model Recall@1: %',
-              math.round(confidenceMetricsEntry.recallAt1 * 100, 2)
-            );
-            console.log(
-              'Model F1 score@1: %',
-              math.round(confidenceMetricsEntry.f1ScoreAt1 * 100, 2)
-            );
-          }
-        });
-      }
-    });
-  }
-
-  automlVisionDisplayEvalution().catch(console.error);
-  // [END automl_vision_display_evaluation]
-}
-
-function deleteModel(projectId, computeRegion, modelId) {
-  // [START automl_vision_delete_model]
-  async function automlVisionDeleteModel() {
-    const automl = require('@google-cloud/automl').v1beta1;
-
-    const client = new automl.AutoMlClient();
-
-    /**
-     * TODO(developer): Uncomment the following line before running the sample.
-     */
-    // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
-    // const computeRegion = `region-name, e.g. "us-central1"`;
-    // const modelId = `id of the model, e.g. “ICN12345”`;
-
-    // Get the full path of the model.
-    const modelFullId = client.modelPath(projectId, computeRegion, modelId);
-
-    // Delete a model.
-    const [operation] = await client.deleteModel({name: modelFullId});
-    const [, , response] = await operation.promise();
-    // The final result of the operation.
-    if (response.done) {
-      console.log('Model deleted.');
-    }
-  }
-
-  automlVisionDeleteModel().catch(console.error);
-  // [END automl_vision_delete_model]
-}
-
-require(`yargs`) // eslint-disable-line
-  .demand(1)
-  .options({
-    computeRegion: {
-      alias: 'c',
-      type: 'string',
-      default: 'us-central1',
-      requiresArg: true,
-      description: 'region name e.g. "us-central1"',
-    },
-    datasetId: {
-      alias: 'i',
-      type: 'string',
-      requiresArg: true,
-      description: 'Id of the dataset',
-    },
-    filter: {
-      alias: 'f',
-      default: '',
-      type: 'string',
-      requiresArg: true,
-      description: 'Name of the Dataset to search for',
-    },
-    modelName: {
-      alias: 'm',
-      type: 'string',
-      default: false,
-      requiresArg: true,
-      description: 'Name of the model',
-    },
-    modelId: {
-      alias: 'a',
-      type: 'string',
-      default: '',
-      requiresArg: true,
-      description: 'Id of the model',
-    },
-    modelEvaluationId: {
-      alias: 'e',
-      type: 'string',
-      default: '',
-      requiresArg: true,
-      description: 'Id of the model evaluation',
-    },
-    projectId: {
-      alias: 'z',
-      type: 'string',
-      default: process.env.GCLOUD_PROJECT,
-      requiresArg: true,
-      description: 'The GCLOUD_PROJECT string, e.g. "my-gcloud-project"',
-    },
-    trainBudget: {
-      alias: 't',
-      type: 'string',
-      default: '',
-      requiresArg: true,
-      description: 'Budget for training the model',
-    },
-  })
-  .command('create-model', 'creates a new Model', {}, opts =>
-    createModel(
-      opts.projectId,
-      opts.computeRegion,
-      opts.datasetId,
-      opts.modelName,
-      opts.trainBudget
-    )
-  )
-  .command('list-models', 'list all Models', {}, opts =>
-    listModels(opts.projectId, opts.computeRegion, opts.filter)
-  )
-  .command('get-model', 'Get a Model', {}, opts =>
-    getModel(opts.projectId, opts.computeRegion, opts.modelId)
-  )
-  .command('list-model-evaluations', 'List model evaluations', {}, opts =>
-    listModelEvaluations(
-      opts.projectId,
-      opts.computeRegion,
-      opts.modelId,
-      opts.filter
-    )
-  )
-  .command('display-evaluation', 'Display evaluation', {}, opts =>
-    displayEvaluation(
-      opts.projectId,
-      opts.computeRegion,
-      opts.modelId,
-      opts.filter
-    )
-  )
-  .command('delete-model', 'Delete a Model', {}, opts =>
-    deleteModel(opts.projectId, opts.computeRegion, opts.modelId)
-  )
-  .example('node $0 create-model -i "datasetId" -m "myModelName" -t "2"')
-  .example('node $0 list-models -f "image_classification_dataset_metadata:*"')
-  .example('node $0 get-model -a "ModelID"')
-  .example('node $0 list-model-evaluations -a "ModelID"')
-  .example('node $0 display-evaluation -a "ModelId"')
-  .example('node $0 delete-model -a "ModelID"')
-  .wrap(120)
-  .recommendCommands()
-  .help()
-  .strict().argv;
diff --git a/automl/snippets/vision/automlVisionPredict.js b/automl/snippets/vision/automlVisionPredict.js
deleted file mode 100644
index 62da6fead21..00000000000
--- a/automl/snippets/vision/automlVisionPredict.js
+++ /dev/null
@@ -1,133 +0,0 @@
-// Copyright 2018 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.
-
-/**
- * This application demonstrates how to perform basic operations on dataset
- * with the Google AutoML Natural Language API.
- *
- * For more information, see the documentation at
- * https://cloud.google.com/natural-language/automl/docs/
- */
-
-'use strict';
-
-function predict(projectId, computeRegion, modelId, filePath, scoreThreshold) {
-  // [START automl_vision_predict]
-  async function automlVisionPredict() {
-    const automl = require('@google-cloud/automl').v1beta1;
-    const fs = require('fs');
-
-    // Create client for prediction service.
-    const client = new automl.PredictionServiceClient();
-
-    /**
-     * TODO(developer): Uncomment the following line before running the sample.
-     */
-    // const projectId = `The GCLOUD_PROJECT string, e.g. "my-gcloud-project"`;
-    // const computeRegion = `region-name, e.g. "us-central1"`;
-    // const modelId = `id of the model, e.g. “ICN12345”`;
-    // const filePath = `local text file path of content to be classified, e.g. "./resources/test.txt"`;
-    // const scoreThreshold = `value between 0.0 and 1.0, e.g. "0.5"`;
-
-    // Get the full path of the model.
-    const modelFullId = client.modelPath(projectId, computeRegion, modelId);
-
-    // Read the file content for prediction.
-    const content = fs.readFileSync(filePath, 'base64');
-
-    const params = {};
-
-    if (scoreThreshold) {
-      params.score_threshold = scoreThreshold;
-    }
-
-    // Set the payload by giving the content and type of the file.
-    const payload = {};
-    payload.image = {imageBytes: content};
-
-    // params is additional domain-specific parameters.
-    // currently there is no additional parameters supported.
-    const [response] = await client.predict({
-      name: modelFullId,
-      payload: payload,
-      params: params,
-    });
-    console.log('Prediction results:');
-    response.payload.forEach(result => {
-      console.log(`Predicted class name: ${result.displayName}`);
-      console.log(`Predicted class score: ${result.classification.score}`);
-    });
-  }
-
-  automlVisionPredict().catch(console.error);
-  // [END automl_vision_predict]
-}
-
-require(`yargs`) // eslint-disable-line
-  .demand(1)
-  .options({
-    computeRegion: {
-      alias: 'c',
-      type: 'string',
-      default: 'us-central1',
-      requiresArg: true,
-      description: 'region name e.g. "us-central1"',
-    },
-    filePath: {
-      alias: 'f',
-      default: './resources/testImage.jpg',
-      type: 'string',
-      requiresArg: true,
-      description: 'local text file path of the content to be classified',
-    },
-    modelId: {
-      alias: 'i',
-      //default: ``,
-      type: 'string',
-      requiresArg: true,
-      description: 'Id of the model which will be used for text classification',
-    },
-    projectId: {
-      alias: 'z',
-      type: 'string',
-      default: process.env.GCLOUD_PROJECT,
-      requiresArg: true,
-      description: 'The GCLOUD_PROJECT string, e.g. "my-gcloud-project"',
-    },
-    scoreThreshold: {
-      alias: 's',
-      type: 'string',
-      default: '0.5',
-      requiresArg: true,
-      description:
-        'A value from 0.0 to 1.0.  When the model makes predictions for an image it will' +
-        'only produce results that have at least this confidence score threshold.  Default is .5',
-    },
-  })
-  .command('predict', 'classify the content', {}, opts =>
-    predict(
-      opts.projectId,
-      opts.computeRegion,
-      opts.modelId,
-      opts.filePath,
-      opts.scoreThreshold
-    )
-  )
-  .example(
-    'node $0 predict -i "modelId" -f "./resources/testImage.jpg" -s "0.5"'
-  )
-  .wrap(120)
-  .recommendCommands()
-  .help()
-  .strict().argv;
diff --git a/automl/snippets/vision/object-detection/get-operation-status.v1beta1.js b/automl/snippets/vision/object-detection/get-operation-status.v1beta1.js
deleted file mode 100644
index addb460c31b..00000000000
--- a/automl/snippets/vision/object-detection/get-operation-status.v1beta1.js
+++ /dev/null
@@ -1,56 +0,0 @@
-// Copyright 2019 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';
-function main(operationFullId = 'OPERATION_FULL_ID') {
-  // [START automl_vision_object_detection_get_operation_status]
-  /**
-   * Demonstrates using the AutoML client to get operation status.
-   * TODO(developer): Uncomment the following lines before running the sample.
-   */
-  // const operationFullId = '[OPERATION_FULL_ID]'
-  // eg., "projects/<projectId>/locations/us-central1/operations/<operationId>",
-  // `Full name of an operation`;
-
-  //Imports the Google Cloud Automl library
-  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;
-
-  // Instantiates a client
-  const automlClient = new AutoMlClient();
-  async function getOperationStatus() {
-    // Get the latest state of a long-running operation.
-    const [response] = await automlClient.operationsClient.getOperation({
-      name: operationFullId,
-    });
-    console.log('Operation details:');
-    console.log(`\tName: ${response.name}`);
-    console.log('\tMetadata:');
-    console.log(`\t\tType Url: ${response.metadata.typeUrl}`);
-    console.log(`\tDone: ${response.done}`);
-
-    if (response.response) {
-      console.log('\tResponse:');
-      console.log(`\t\tType Url: ${response.response.typeUrl}`);
-    }
-
-    if (response.error) {
-      console.log('\tResponse:');
-      console.log(`\t\tError code: ${response.error.code}`);
-      console.log(`\t\tError message: ${response.error.message}`);
-    }
-  }
-  getOperationStatus();
-  // [END automl_vision_object_detection_get_operation_status]
-}
-main(...process.argv.slice(2));
diff --git a/automl/snippets/vision/resources/flowerTraindata20lines.csv b/automl/snippets/vision/resources/flowerTraindata20lines.csv
deleted file mode 100644
index a0617c06e9d..00000000000
--- a/automl/snippets/vision/resources/flowerTraindata20lines.csv
+++ /dev/null
@@ -1,19 +0,0 @@
-gs://nodejs-docs-samples-vcm/daisy/14354051035_1037b30421_n.jpg,daisy
-gs://nodejs-docs-samples-vcm/daisy/5586977262_6b24412805_n.jpg,daisy
-gs://nodejs-docs-samples-vcm/daisy/14707111433_cce08ee007.jpg,daisy
-gs://nodejs-docs-samples-vcm/daisy/2488902131_3417698611_n.jpg,daisy
-gs://nodejs-docs-samples-vcm/daisy/506348009_9ecff8b6ef.jpg,daisy
-gs://nodejs-docs-samples-vcm/daisy/2331133004_582772d58f_m.jpg,daisy
-gs://nodejs-docs-samples-vcm/daisy/4511693548_20f9bd2b9c_m.jpg,daisy
-gs://nodejs-docs-samples-vcm/daisy/12601254324_3cb62c254a_m.jpg,daisy
-gs://nodejs-docs-samples-vcm/daisy/2473825306_62fd5f8785_n.jpg,daisy
-gs://nodejs-docs-samples-vcm/dandelion/18089878729_907ed2c7cd_m.jpg,dandelion
-gs://nodejs-docs-samples-vcm/dandelion/284497199_93a01f48f6.jpg,dandelion
-gs://nodejs-docs-samples-vcm/dandelion/3554992110_81d8c9b0bd_m.jpg,dandelion
-gs://nodejs-docs-samples-vcm/dandelion/4558536575_d43a611bd4_n.jpg,dandelion
-gs://nodejs-docs-samples-vcm/dandelion/15782158700_3b9bf7d33e_m.jpg,dandelion
-gs://nodejs-docs-samples-vcm/dandelion/8754822932_948afc7cef.jpg,dandelion
-gs://nodejs-docs-samples-vcm/dandelion/2229906591_e953785d13.jpg,dandelion
-gs://nodejs-docs-samples-vcm/dandelion/3991962484_085ba2da94.jpg,dandelion
-gs://nodejs-docs-samples-vcm/dandelion/4500964841_b1142b50fb_n.jpg,dandelion
-gs://nodejs-docs-samples-vcm/dandelion/7808545612_546cfca610_m.jpg,dandelion
diff --git a/automl/snippets/vision/resources/songbird.jpg b/automl/snippets/vision/resources/songbird.jpg
deleted file mode 100644
index f10312d084e..00000000000
Binary files a/automl/snippets/vision/resources/songbird.jpg and /dev/null differ
diff --git a/automl/snippets/vision/resources/testImage.jpg b/automl/snippets/vision/resources/testImage.jpg
deleted file mode 100644
index 852c4635210..00000000000
Binary files a/automl/snippets/vision/resources/testImage.jpg and /dev/null differ
diff --git a/automl/snippets/vision/resources/testImage2.jpg b/automl/snippets/vision/resources/testImage2.jpg
deleted file mode 100644
index 674a1aa4ea7..00000000000
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