From a662f6b9b1edae36d0be309842db607d7673c62b Mon Sep 17 00:00:00 2001
From: Mike <45373284+munkhuushmgl@users.noreply.github.com>
Date: Fri, 6 Nov 2020 11:36:59 -0800
Subject: [PATCH] samples: ucaip batch samples 4 of 6 (#19)

* samples: ucaip batch samples 4 of 6

* made requested changes

* fixed prediction test

* added missing resources
---
 aiplatform/snippets/pom.xml                   |   1 +
 aiplatform/snippets/resources/daisy.jpg       | Bin 0 -> 76076 bytes
 .../CreateTrainingPipelineSample.java         | 235 ++++++++++++++++++
 .../java/aiplatform/DeleteModelSample.java    |  63 +++++
 .../aiplatform/GetTrainingPipelineSample.java | 200 +++++++++++++++
 .../PredictCustomTrainedModelSample.java      |  76 ++++++
 .../java/aiplatform/UploadModelSample.java    |  89 +++++++
 .../CancelTrainingPipelineSampleTest.java     | 123 +++++++++
 .../GetTrainingPipelineSampleTest.java        |  75 ++++++
 .../PredictCustomTrainedModelSampleTest.java  |  82 ++++++
 .../aiplatform/UploadModelSampleTest.java     |  98 ++++++++
 11 files changed, 1042 insertions(+)
 create mode 100644 aiplatform/snippets/resources/daisy.jpg
 create mode 100644 aiplatform/snippets/src/main/java/aiplatform/CreateTrainingPipelineSample.java
 create mode 100644 aiplatform/snippets/src/main/java/aiplatform/DeleteModelSample.java
 create mode 100644 aiplatform/snippets/src/main/java/aiplatform/GetTrainingPipelineSample.java
 create mode 100644 aiplatform/snippets/src/main/java/aiplatform/PredictCustomTrainedModelSample.java
 create mode 100644 aiplatform/snippets/src/main/java/aiplatform/UploadModelSample.java
 create mode 100644 aiplatform/snippets/src/test/java/aiplatform/CancelTrainingPipelineSampleTest.java
 create mode 100644 aiplatform/snippets/src/test/java/aiplatform/GetTrainingPipelineSampleTest.java
 create mode 100644 aiplatform/snippets/src/test/java/aiplatform/PredictCustomTrainedModelSampleTest.java
 create mode 100644 aiplatform/snippets/src/test/java/aiplatform/UploadModelSampleTest.java

diff --git a/aiplatform/snippets/pom.xml b/aiplatform/snippets/pom.xml
index d9652815f2f..335f524539a 100644
--- a/aiplatform/snippets/pom.xml
+++ b/aiplatform/snippets/pom.xml
@@ -55,5 +55,6 @@
       <version>1.1</version>
       <scope>test</scope>
     </dependency>
+
   </dependencies>
 </project>
diff --git a/aiplatform/snippets/resources/daisy.jpg b/aiplatform/snippets/resources/daisy.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..ae01cae918365637aa3ac44bfb052fb86a964441
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diff --git a/aiplatform/snippets/src/main/java/aiplatform/CreateTrainingPipelineSample.java b/aiplatform/snippets/src/main/java/aiplatform/CreateTrainingPipelineSample.java
new file mode 100644
index 00000000000..5c310bfea7f
--- /dev/null
+++ b/aiplatform/snippets/src/main/java/aiplatform/CreateTrainingPipelineSample.java
@@ -0,0 +1,235 @@
+/*
+ * 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.
+ */
+
+package aiplatform;
+
+// [START aiplatform_create_training_pipeline_sample]
+
+import com.google.cloud.aiplatform.v1beta1.DeployedModelRef;
+import com.google.cloud.aiplatform.v1beta1.EnvVar;
+import com.google.cloud.aiplatform.v1beta1.ExplanationMetadata;
+import com.google.cloud.aiplatform.v1beta1.ExplanationParameters;
+import com.google.cloud.aiplatform.v1beta1.ExplanationSpec;
+import com.google.cloud.aiplatform.v1beta1.FilterSplit;
+import com.google.cloud.aiplatform.v1beta1.FractionSplit;
+import com.google.cloud.aiplatform.v1beta1.InputDataConfig;
+import com.google.cloud.aiplatform.v1beta1.LocationName;
+import com.google.cloud.aiplatform.v1beta1.Model;
+import com.google.cloud.aiplatform.v1beta1.Model.ExportFormat;
+import com.google.cloud.aiplatform.v1beta1.ModelContainerSpec;
+import com.google.cloud.aiplatform.v1beta1.PipelineServiceClient;
+import com.google.cloud.aiplatform.v1beta1.PipelineServiceSettings;
+import com.google.cloud.aiplatform.v1beta1.Port;
+import com.google.cloud.aiplatform.v1beta1.PredefinedSplit;
+import com.google.cloud.aiplatform.v1beta1.PredictSchemata;
+import com.google.cloud.aiplatform.v1beta1.SampledShapleyAttribution;
+import com.google.cloud.aiplatform.v1beta1.TimestampSplit;
+import com.google.cloud.aiplatform.v1beta1.TrainingPipeline;
+import com.google.protobuf.Any;
+import com.google.protobuf.Value;
+import com.google.protobuf.util.JsonFormat;
+import com.google.rpc.Status;
+import java.io.IOException;
+import java.util.List;
+
+public class CreateTrainingPipelineSample {
+
+  public static void main(String[] args) throws IOException {
+    // TODO(developer): Replace these variables before running the sample.
+    String trainingPipelineDisplayName = "YOUR_TRAINING_PIPELINE_DISPLAY_NAME";
+    String project = "YOUR_PROJECT_ID";
+    String datasetId = "YOUR_DATASET_ID";
+    String trainingTaskDefinition = "YOUR_TRAINING_TASK_DEFINITION";
+    String modelDisplayName = "YOUR_MODEL_DISPLAY_NAME";
+    createTrainingPipelineSample(
+        project, trainingPipelineDisplayName, datasetId, trainingTaskDefinition, modelDisplayName);
+  }
+
+  static void createTrainingPipelineSample(
+      String project,
+      String trainingPipelineDisplayName,
+      String datasetId,
+      String trainingTaskDefinition,
+      String modelDisplayName)
+      throws IOException {
+    PipelineServiceSettings pipelineServiceSettings =
+        PipelineServiceSettings.newBuilder()
+            .setEndpoint("us-central1-aiplatform.googleapis.com:443")
+            .build();
+
+    // Initialize client that will be used to send requests. This client only needs to be created
+    // once, and can be reused for multiple requests. After completing all of your requests, call
+    // the "close" method on the client to safely clean up any remaining background resources.
+    try (PipelineServiceClient pipelineServiceClient =
+        PipelineServiceClient.create(pipelineServiceSettings)) {
+      String location = "us-central1";
+      LocationName locationName = LocationName.of(project, location);
+
+      String jsonString =
+          "{\"multiLabel\": false, \"modelType\": \"CLOUD\", \"budgetMilliNodeHours\": 8000,"
+              + " \"disableEarlyStopping\": false}";
+      Value.Builder trainingTaskInputs = Value.newBuilder();
+      JsonFormat.parser().merge(jsonString, trainingTaskInputs);
+
+      InputDataConfig trainingInputDataConfig =
+          InputDataConfig.newBuilder().setDatasetId(datasetId).build();
+      Model model = Model.newBuilder().setDisplayName(modelDisplayName).build();
+      TrainingPipeline trainingPipeline =
+          TrainingPipeline.newBuilder()
+              .setDisplayName(trainingPipelineDisplayName)
+              .setTrainingTaskDefinition(trainingTaskDefinition)
+              .setTrainingTaskInputs(trainingTaskInputs)
+              .setInputDataConfig(trainingInputDataConfig)
+              .setModelToUpload(model)
+              .build();
+
+      TrainingPipeline trainingPipelineResponse =
+          pipelineServiceClient.createTrainingPipeline(locationName, trainingPipeline);
+
+      System.out.println("Create Training Pipeline Response");
+      System.out.format("Name: %s\n", trainingPipelineResponse.getName());
+      System.out.format("Display Name: %s\n", trainingPipelineResponse.getDisplayName());
+
+      System.out.format(
+          "Training Task Definition %s\n", trainingPipelineResponse.getTrainingTaskDefinition());
+      System.out.format(
+          "Training Task Inputs: %s\n", trainingPipelineResponse.getTrainingTaskInputs());
+      System.out.format(
+          "Training Task Metadata: %s\n", trainingPipelineResponse.getTrainingTaskMetadata());
+      System.out.format("State: %s\n", trainingPipelineResponse.getState());
+
+      System.out.format("Create Time: %s\n", trainingPipelineResponse.getCreateTime());
+      System.out.format("StartTime %s\n", trainingPipelineResponse.getStartTime());
+      System.out.format("End Time: %s\n", trainingPipelineResponse.getEndTime());
+      System.out.format("Update Time: %s\n", trainingPipelineResponse.getUpdateTime());
+      System.out.format("Labels: %s\n", trainingPipelineResponse.getLabelsMap());
+
+      InputDataConfig inputDataConfig = trainingPipelineResponse.getInputDataConfig();
+      System.out.println("Input Data Config");
+      System.out.format("Dataset Id: %s", inputDataConfig.getDatasetId());
+      System.out.format("Annotations Filter: %s\n", inputDataConfig.getAnnotationsFilter());
+
+      FractionSplit fractionSplit = inputDataConfig.getFractionSplit();
+      System.out.println("Fraction Split");
+      System.out.format("Training Fraction: %s\n", fractionSplit.getTrainingFraction());
+      System.out.format("Validation Fraction: %s\n", fractionSplit.getValidationFraction());
+      System.out.format("Test Fraction: %s\n", fractionSplit.getTestFraction());
+
+      FilterSplit filterSplit = inputDataConfig.getFilterSplit();
+      System.out.println("Filter Split");
+      System.out.format("Training Filter: %s\n", filterSplit.getTrainingFilter());
+      System.out.format("Validation Filter: %s\n", filterSplit.getValidationFilter());
+      System.out.format("Test Filter: %s\n", filterSplit.getTestFilter());
+
+      PredefinedSplit predefinedSplit = inputDataConfig.getPredefinedSplit();
+      System.out.println("Predefined Split");
+      System.out.format("Key: %s\n", predefinedSplit.getKey());
+
+      TimestampSplit timestampSplit = inputDataConfig.getTimestampSplit();
+      System.out.println("Timestamp Split");
+      System.out.format("Training Fraction: %s\n", timestampSplit.getTrainingFraction());
+      System.out.format("Validation Fraction: %s\n", timestampSplit.getValidationFraction());
+      System.out.format("Test Fraction: %s\n", timestampSplit.getTestFraction());
+      System.out.format("Key: %s\n", timestampSplit.getKey());
+
+      Model modelResponse = trainingPipelineResponse.getModelToUpload();
+      System.out.println("Model To Upload");
+      System.out.format("Name: %s\n", modelResponse.getName());
+      System.out.format("Display Name: %s\n", modelResponse.getDisplayName());
+      System.out.format("Description: %s\n", modelResponse.getDescription());
+
+      System.out.format("Metadata Schema Uri: %s\n", modelResponse.getMetadataSchemaUri());
+      System.out.format("Metadata: %s\n", modelResponse.getMetadata());
+      System.out.format("Training Pipeline: %s\n", modelResponse.getTrainingPipeline());
+      System.out.format("Artifact Uri: %s\n", modelResponse.getArtifactUri());
+
+      System.out.format(
+          "Supported Deployment Resources Types: %s\n",
+          modelResponse.getSupportedDeploymentResourcesTypesList());
+      System.out.format(
+          "Supported Input Storage Formats: %s\n",
+          modelResponse.getSupportedInputStorageFormatsList());
+      System.out.format(
+          "Supported Output Storage Formats: %s\n",
+          modelResponse.getSupportedOutputStorageFormatsList());
+
+      System.out.format("Create Time: %s\n", modelResponse.getCreateTime());
+      System.out.format("Update Time: %s\n", modelResponse.getUpdateTime());
+      System.out.format("Labels: %sn\n", modelResponse.getLabelsMap());
+
+      PredictSchemata predictSchemata = modelResponse.getPredictSchemata();
+      System.out.println("Predict Schemata");
+      System.out.format("Instance Schema Uri: %s\n", predictSchemata.getInstanceSchemaUri());
+      System.out.format("Parameters Schema Uri: %s\n", predictSchemata.getParametersSchemaUri());
+      System.out.format("Prediction Schema Uri: %s\n", predictSchemata.getPredictionSchemaUri());
+
+      for (ExportFormat exportFormat : modelResponse.getSupportedExportFormatsList()) {
+        System.out.println("Supported Export Format");
+        System.out.format("Id: %s\n", exportFormat.getId());
+      }
+
+      ModelContainerSpec modelContainerSpec = modelResponse.getContainerSpec();
+      System.out.println("Container Spec");
+      System.out.format("Image Uri: %s\n", modelContainerSpec.getImageUri());
+      System.out.format("Command: %s\n", modelContainerSpec.getCommandList());
+      System.out.format("Args: %s\n", modelContainerSpec.getArgsList());
+      System.out.format("Predict Route: %s\n", modelContainerSpec.getPredictRoute());
+      System.out.format("Health Route: %s\n", modelContainerSpec.getHealthRoute());
+
+      for (EnvVar envVar : modelContainerSpec.getEnvList()) {
+        System.out.println("Env");
+        System.out.format("Name: %s\n", envVar.getName());
+        System.out.format("Value: %s\n", envVar.getValue());
+      }
+
+      for (Port port : modelContainerSpec.getPortsList()) {
+        System.out.println("Port");
+        System.out.format("Container Port: %s\n", port.getContainerPort());
+      }
+
+      for (DeployedModelRef deployedModelRef : modelResponse.getDeployedModelsList()) {
+        System.out.println("Deployed Model");
+        System.out.format("Endpoint: %s\n", deployedModelRef.getEndpoint());
+        System.out.format("Deployed Model Id: %s\n", deployedModelRef.getDeployedModelId());
+      }
+
+      ExplanationSpec explanationSpec = modelResponse.getExplanationSpec();
+      System.out.println("Explanation Spec");
+
+      ExplanationParameters explanationParameters = explanationSpec.getParameters();
+      System.out.println("Parameters");
+
+      SampledShapleyAttribution sampledShapleyAttribution =
+          explanationParameters.getSampledShapleyAttribution();
+      System.out.println("Sampled Shapley Attribution");
+      System.out.format("Path Count: %s\n", sampledShapleyAttribution.getPathCount());
+
+      ExplanationMetadata explanationMetadata = explanationSpec.getMetadata();
+      System.out.println("Metadata");
+      System.out.format("Inputs: %s\n", explanationMetadata.getInputsMap());
+      System.out.format("Outputs: %s\n", explanationMetadata.getOutputsMap());
+      System.out.format(
+          "Feature Attributions Schema_uri: %s\n",
+          explanationMetadata.getFeatureAttributionsSchemaUri());
+
+      Status status = trainingPipelineResponse.getError();
+      System.out.println("Error");
+      System.out.format("Code: %s\n", status.getCode());
+      System.out.format("Message: %s\n", status.getMessage());
+    }
+  }
+}
+// [END aiplatform_create_training_pipeline_sample]
diff --git a/aiplatform/snippets/src/main/java/aiplatform/DeleteModelSample.java b/aiplatform/snippets/src/main/java/aiplatform/DeleteModelSample.java
new file mode 100644
index 00000000000..0a65dabfc0c
--- /dev/null
+++ b/aiplatform/snippets/src/main/java/aiplatform/DeleteModelSample.java
@@ -0,0 +1,63 @@
+/*
+ * 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.
+ */
+
+package aiplatform;
+
+// [START aiplatform_delete_model_sample]
+
+import com.google.api.gax.longrunning.OperationFuture;
+import com.google.cloud.aiplatform.v1beta1.DeleteOperationMetadata;
+import com.google.cloud.aiplatform.v1beta1.ModelName;
+import com.google.cloud.aiplatform.v1beta1.ModelServiceClient;
+import com.google.cloud.aiplatform.v1beta1.ModelServiceSettings;
+import com.google.protobuf.Empty;
+import java.io.IOException;
+import java.util.concurrent.ExecutionException;
+import java.util.concurrent.TimeUnit;
+import java.util.concurrent.TimeoutException;
+
+public class DeleteModelSample {
+  public static void main(String[] args)
+      throws IOException, ExecutionException, InterruptedException, TimeoutException {
+    // TODO(developer): Replace these variables before running the sample.
+    String project = "YOUR_PROJECT_ID";
+    String modelId = "YOUR_MODEL_ID";
+    deleteModel(project, modelId);
+  }
+
+  static void deleteModel(String project, String modelId)
+      throws IOException, ExecutionException, InterruptedException, TimeoutException {
+    ModelServiceSettings modelServiceSettings =
+        ModelServiceSettings.newBuilder()
+            .setEndpoint("us-central1-aiplatform.googleapis.com:443")
+            .build();
+
+    // Initialize client that will be used to send requests. This client only needs to be created
+    // once, and can be reused for multiple requests. After completing all of your requests, call
+    // the "close" method on the client to safely clean up any remaining background resources.
+    try (ModelServiceClient modelServiceClient = ModelServiceClient.create(modelServiceSettings)) {
+      String location = "us-central1";
+      ModelName modelName = ModelName.of(project, location, modelId);
+      OperationFuture<Empty, DeleteOperationMetadata> operationFuture =
+          modelServiceClient.deleteModelAsync(modelName);
+      System.out.format("Operation name: %s\n", operationFuture.getInitialFuture().get().getName());
+      System.out.println("Waiting for operation to finish...");
+      operationFuture.get(300, TimeUnit.SECONDS);
+      System.out.format("Deleted Model.");
+    }
+  }
+}
+// [END aiplatform_delete_model_sample]
diff --git a/aiplatform/snippets/src/main/java/aiplatform/GetTrainingPipelineSample.java b/aiplatform/snippets/src/main/java/aiplatform/GetTrainingPipelineSample.java
new file mode 100644
index 00000000000..c144212a8e2
--- /dev/null
+++ b/aiplatform/snippets/src/main/java/aiplatform/GetTrainingPipelineSample.java
@@ -0,0 +1,200 @@
+/*
+ * 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.
+ */
+
+package aiplatform;
+
+// [START aiplatform_get_training_pipeline_sample]
+
+import com.google.cloud.aiplatform.v1beta1.DeployedModelRef;
+import com.google.cloud.aiplatform.v1beta1.EnvVar;
+import com.google.cloud.aiplatform.v1beta1.ExplanationMetadata;
+import com.google.cloud.aiplatform.v1beta1.ExplanationParameters;
+import com.google.cloud.aiplatform.v1beta1.ExplanationSpec;
+import com.google.cloud.aiplatform.v1beta1.FilterSplit;
+import com.google.cloud.aiplatform.v1beta1.FractionSplit;
+import com.google.cloud.aiplatform.v1beta1.InputDataConfig;
+import com.google.cloud.aiplatform.v1beta1.Model;
+import com.google.cloud.aiplatform.v1beta1.ModelContainerSpec;
+import com.google.cloud.aiplatform.v1beta1.PipelineServiceClient;
+import com.google.cloud.aiplatform.v1beta1.PipelineServiceSettings;
+import com.google.cloud.aiplatform.v1beta1.Port;
+import com.google.cloud.aiplatform.v1beta1.PredefinedSplit;
+import com.google.cloud.aiplatform.v1beta1.PredictSchemata;
+import com.google.cloud.aiplatform.v1beta1.SampledShapleyAttribution;
+import com.google.cloud.aiplatform.v1beta1.TimestampSplit;
+import com.google.cloud.aiplatform.v1beta1.TrainingPipeline;
+import com.google.cloud.aiplatform.v1beta1.TrainingPipelineName;
+import com.google.rpc.Status;
+import java.io.IOException;
+
+public class GetTrainingPipelineSample {
+  public static void main(String[] args) throws IOException {
+    // TODO(developer): Replace these variables before running the sample.
+    String project = "YOUR_PROJECT_ID";
+    String trainingPipelineId = "YOUR_TRAINING_PIPELINE_ID";
+    getTrainingPipeline(project, trainingPipelineId);
+  }
+
+  static void getTrainingPipeline(String project, String trainingPipelineId) throws IOException {
+    PipelineServiceSettings pipelineServiceSettings =
+        PipelineServiceSettings.newBuilder()
+            .setEndpoint("us-central1-aiplatform.googleapis.com:443")
+            .build();
+
+    // Initialize client that will be used to send requests. This client only needs to be created
+    // once, and can be reused for multiple requests. After completing all of your requests, call
+    // the "close" method on the client to safely clean up any remaining background resources.
+    try (PipelineServiceClient pipelineServiceClient =
+        PipelineServiceClient.create(pipelineServiceSettings)) {
+      String location = "us-central1";
+      TrainingPipelineName trainingPipelineName =
+          TrainingPipelineName.of(project, location, trainingPipelineId);
+
+      TrainingPipeline trainingPipelineResponse =
+          pipelineServiceClient.getTrainingPipeline(trainingPipelineName);
+
+      System.out.println("Get Training Pipeline Response");
+      System.out.format("\tName: %s\n", trainingPipelineResponse.getName());
+      System.out.format("\tDisplay Name: %s\n", trainingPipelineResponse.getDisplayName());
+      System.out.format(
+          "\tTraining Task Definition: %s\n", trainingPipelineResponse.getTrainingTaskDefinition());
+      System.out.format(
+          "\tTraining Task Inputs: %s\n", trainingPipelineResponse.getTrainingTaskInputs());
+      System.out.format(
+          "\tTraining Task Metadata: %s\n", trainingPipelineResponse.getTrainingTaskMetadata());
+      System.out.format("\tState: %s\n", trainingPipelineResponse.getState());
+      System.out.format("\tCreate Time: %s\n", trainingPipelineResponse.getCreateTime());
+      System.out.format("\tStart Time: %s\n", trainingPipelineResponse.getStartTime());
+      System.out.format("\tEnd Time: %s\n", trainingPipelineResponse.getEndTime());
+      System.out.format("\tUpdate Time: %s\n", trainingPipelineResponse.getUpdateTime());
+      System.out.format("\tLabels: %s\n", trainingPipelineResponse.getLabelsMap());
+      InputDataConfig inputDataConfig = trainingPipelineResponse.getInputDataConfig();
+
+      System.out.println("\tInput Data Config");
+      System.out.format("\t\tDataset Id: %s\n", inputDataConfig.getDatasetId());
+      System.out.format("\t\tAnnotations Filter: %s\n", inputDataConfig.getAnnotationsFilter());
+      FractionSplit fractionSplit = inputDataConfig.getFractionSplit();
+
+      System.out.println("\t\tFraction Split");
+      System.out.format("\t\t\tTraining Fraction: %s\n", fractionSplit.getTrainingFraction());
+      System.out.format("\t\t\tValidation Fraction: %s\n", fractionSplit.getValidationFraction());
+      System.out.format("\t\t\tTest Fraction: %s\n", fractionSplit.getTestFraction());
+      FilterSplit filterSplit = inputDataConfig.getFilterSplit();
+
+      System.out.println("\t\tFilter Split");
+      System.out.format("\t\t\tTraining Filter: %s\n", filterSplit.getTrainingFilter());
+      System.out.format("\t\t\tValidation Filter: %s\n", filterSplit.getValidationFilter());
+      System.out.format("\t\t\tTest Filter: %s\n", filterSplit.getTestFilter());
+      PredefinedSplit predefinedSplit = inputDataConfig.getPredefinedSplit();
+
+      System.out.println("\t\tPredefined Split");
+      System.out.format("\t\t\tKey: %s\n", predefinedSplit.getKey());
+      TimestampSplit timestampSplit = inputDataConfig.getTimestampSplit();
+
+      System.out.println("\t\tTimestamp Split");
+      System.out.format("\t\t\tTraining Fraction: %s\n", timestampSplit.getTrainingFraction());
+      System.out.format("\t\t\tTest Fraction: %s\n", timestampSplit.getTestFraction());
+      System.out.format("\t\t\tValidation Fraction: %s\n", timestampSplit.getValidationFraction());
+      System.out.format("\t\t\tKey: %s\n", timestampSplit.getKey());
+      Model modelResponse = trainingPipelineResponse.getModelToUpload();
+
+      System.out.println("\t\tModel to upload");
+      System.out.format("\t\tName: %s\n", modelResponse.getName());
+      System.out.format("\t\tDisplay Name: %s\n", modelResponse.getDisplayName());
+      System.out.format("\t\tDescription: %s\n", modelResponse.getDescription());
+      System.out.format("\t\tMetadata Schema Uri: %s\n", modelResponse.getMetadataSchemaUri());
+      System.out.format("\t\tMeta Data: %s\n", modelResponse.getMetadata());
+      System.out.format("\t\tTraining Pipeline: %s\n", modelResponse.getTrainingPipeline());
+      System.out.format("\t\tArtifact Uri: %s\n", modelResponse.getArtifactUri());
+      System.out.format(
+          "\t\tSupported Deployment Resources Types: %s\n",
+          modelResponse.getSupportedDeploymentResourcesTypesList().toString());
+      System.out.format(
+          "\t\tSupported Input Storage Formats: %s\n",
+          modelResponse.getSupportedInputStorageFormatsList().toString());
+      System.out.format(
+          "\t\tSupported Output Storage Formats: %s\n",
+          modelResponse.getSupportedOutputStorageFormatsList().toString());
+      System.out.format("\t\tCreate Time: %s\n", modelResponse.getCreateTime());
+      System.out.format("\t\tUpdate Time: %s\n", modelResponse.getUpdateTime());
+      System.out.format("\t\tLabels: %s\n", modelResponse.getLabelsMap());
+      PredictSchemata predictSchemata = modelResponse.getPredictSchemata();
+
+      System.out.println("\tPredict Schemata");
+      System.out.format("\t\tInstance Schema Uri: %s\n", predictSchemata.getInstanceSchemaUri());
+      System.out.format(
+          "\t\tParameters Schema Uri: %s\n", predictSchemata.getParametersSchemaUri());
+      System.out.format(
+          "\t\tPrediction Schema Uri: %s\n", predictSchemata.getPredictionSchemaUri());
+
+      for (Model.ExportFormat supportedExportFormat :
+          modelResponse.getSupportedExportFormatsList()) {
+        System.out.println("\tSupported Export Format");
+        System.out.format("\t\tId: %s\n", supportedExportFormat.getId());
+      }
+      ModelContainerSpec containerSpec = modelResponse.getContainerSpec();
+
+      System.out.println("\tContainer Spec");
+      System.out.format("\t\tImage Uri: %s\n", containerSpec.getImageUri());
+      System.out.format("\t\tCommand: %s\n", containerSpec.getCommandList());
+      System.out.format("\t\tArgs: %s\n", containerSpec.getArgsList());
+      System.out.format("\t\tPredict Route: %s\n", containerSpec.getPredictRoute());
+      System.out.format("\t\tHealth Route: %s\n", containerSpec.getHealthRoute());
+
+      for (EnvVar envVar : containerSpec.getEnvList()) {
+        System.out.println("\t\tEnv");
+        System.out.format("\t\t\tName: %s\n", envVar.getName());
+        System.out.format("\t\t\tValue: %s\n", envVar.getValue());
+      }
+
+      for (Port port : containerSpec.getPortsList()) {
+        System.out.println("\t\tPort");
+        System.out.format("\t\t\tContainer Port: %s\n", port.getContainerPort());
+      }
+
+      for (DeployedModelRef deployedModelRef : modelResponse.getDeployedModelsList()) {
+        System.out.println("\tDeployed Model");
+        System.out.format("\t\tEndpoint: %s\n", deployedModelRef.getEndpoint());
+        System.out.format("\t\tDeployed Model Id: %s\n", deployedModelRef.getDeployedModelId());
+      }
+
+      ExplanationSpec explanationSpec = modelResponse.getExplanationSpec();
+      System.out.println("\tExplanation Spec");
+
+      ExplanationParameters explanationParameters = explanationSpec.getParameters();
+      System.out.println("\t\tParameters");
+
+      SampledShapleyAttribution sampledShapleyAttribution =
+          explanationParameters.getSampledShapleyAttribution();
+      System.out.println("\t\tSampled Shapley Attribution");
+      System.out.format("\t\t\tPath Count: %s\n", sampledShapleyAttribution.getPathCount());
+
+      ExplanationMetadata explanationMetadata = explanationSpec.getMetadata();
+      System.out.println("\t\tMetadata");
+      System.out.format("\t\t\tInput: %s\n", explanationMetadata.getInputsMap());
+      System.out.format("\t\t\tOutput: %s\n", explanationMetadata.getOutputsMap());
+      System.out.format(
+          "\t\t\tFeature Attributions Schema Uri: %s\n",
+          explanationMetadata.getFeatureAttributionsSchemaUri());
+
+      Status status = trainingPipelineResponse.getError();
+      System.out.println("\tError");
+      System.out.format("\t\tCode: %s\n", status.getCode());
+      System.out.format("\t\tMessage: %s\n", status.getMessage());
+    }
+  }
+}
+// [END aiplatform_get_training_pipeline_sample]
diff --git a/aiplatform/snippets/src/main/java/aiplatform/PredictCustomTrainedModelSample.java b/aiplatform/snippets/src/main/java/aiplatform/PredictCustomTrainedModelSample.java
new file mode 100644
index 00000000000..f2eb37ffb29
--- /dev/null
+++ b/aiplatform/snippets/src/main/java/aiplatform/PredictCustomTrainedModelSample.java
@@ -0,0 +1,76 @@
+/*
+ * 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.
+ */
+
+package aiplatform;
+
+// [START aiplatform_predict_custom_trained_model_sample]
+
+import com.google.cloud.aiplatform.v1beta1.EndpointName;
+import com.google.cloud.aiplatform.v1beta1.PredictRequest;
+import com.google.cloud.aiplatform.v1beta1.PredictResponse;
+import com.google.cloud.aiplatform.v1beta1.PredictionServiceClient;
+import com.google.cloud.aiplatform.v1beta1.PredictionServiceSettings;
+import com.google.protobuf.ListValue;
+import com.google.protobuf.Value;
+import com.google.protobuf.util.JsonFormat;
+import java.io.IOException;
+import java.util.List;
+
+public class PredictCustomTrainedModelSample {
+  public static void main(String[] args) throws IOException {
+    // TODO(developer): Replace these variables before running the sample.
+    String instance = "[{ “feature_column_a”: “value”, “feature_column_b”: “value”}]";
+    String project = "YOUR_PROJECT_ID";
+    String endpointId = "YOUR_ENDPOINT_ID";
+    predictCustomTrainedModel(project, endpointId, instance);
+  }
+
+  static void predictCustomTrainedModel(String project, String endpointId, String instance)
+      throws IOException {
+    PredictionServiceSettings predictionServiceSettings =
+        PredictionServiceSettings.newBuilder()
+            .setEndpoint("us-central1-prediction-aiplatform.googleapis.com:443")
+            .build();
+
+    // Initialize client that will be used to send requests. This client only needs to be created
+    // once, and can be reused for multiple requests. After completing all of your requests, call
+    // the "close" method on the client to safely clean up any remaining background resources.
+    try (PredictionServiceClient predictionServiceClient =
+        PredictionServiceClient.create(predictionServiceSettings)) {
+      String location = "us-central1";
+      EndpointName endpointName = EndpointName.of(project, location, endpointId);
+
+      ListValue.Builder listValue = ListValue.newBuilder();
+      JsonFormat.parser().merge(instance, listValue);
+      List<Value> instanceList = listValue.getValuesList();
+
+      PredictRequest predictRequest =
+          PredictRequest.newBuilder()
+              .setEndpoint(endpointName.toString())
+              .addAllInstances(instanceList)
+              .build();
+      PredictResponse predictResponse = predictionServiceClient.predict(predictRequest);
+
+      System.out.println("Predict Custom Trained model Response");
+      System.out.format("\tDeployed Model Id: %s\n", predictResponse.getDeployedModelId());
+      System.out.println("Predictions");
+      for (Value prediction : predictResponse.getPredictionsList()) {
+        System.out.format("\tPrediction: %s\n", prediction);
+      }
+    }
+  }
+}
+// [END aiplatform_predict_custom_trained_model_sample]
diff --git a/aiplatform/snippets/src/main/java/aiplatform/UploadModelSample.java b/aiplatform/snippets/src/main/java/aiplatform/UploadModelSample.java
new file mode 100644
index 00000000000..da6127c73bc
--- /dev/null
+++ b/aiplatform/snippets/src/main/java/aiplatform/UploadModelSample.java
@@ -0,0 +1,89 @@
+/*
+ * 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.
+ */
+
+package aiplatform;
+
+// [START aiplatform_upload_model_sample]
+
+import com.google.api.gax.longrunning.OperationFuture;
+import com.google.cloud.aiplatform.v1beta1.LocationName;
+import com.google.cloud.aiplatform.v1beta1.Model;
+import com.google.cloud.aiplatform.v1beta1.ModelContainerSpec;
+import com.google.cloud.aiplatform.v1beta1.ModelServiceClient;
+import com.google.cloud.aiplatform.v1beta1.ModelServiceSettings;
+import com.google.cloud.aiplatform.v1beta1.UploadModelOperationMetadata;
+import com.google.cloud.aiplatform.v1beta1.UploadModelResponse;
+import java.io.IOException;
+import java.util.concurrent.ExecutionException;
+import java.util.concurrent.TimeUnit;
+import java.util.concurrent.TimeoutException;
+
+public class UploadModelSample {
+  public static void main(String[] args)
+      throws InterruptedException, ExecutionException, TimeoutException, IOException {
+    // TODO(developer): Replace these variables before running the sample.
+    String project = "YOUR_PROJECT_ID";
+    String modelDisplayName = "YOUR_MODEL_DISPLAY_NAME";
+    String metadataSchemaUri =
+        "gs://google-cloud-aiplatform/schema/trainingjob/definition/custom_task_1.0.0.yaml";
+    String imageUri = "YOUR_IMAGE_URI";
+    String artifactUri = "gs://your-gcs-bucket/artifact_path";
+    uploadModel(project, modelDisplayName, metadataSchemaUri, imageUri, artifactUri);
+  }
+
+  static void uploadModel(
+      String project,
+      String modelDisplayName,
+      String metadataSchemaUri,
+      String imageUri,
+      String artifactUri)
+      throws IOException, InterruptedException, ExecutionException, TimeoutException {
+    ModelServiceSettings modelServiceSettings =
+        ModelServiceSettings.newBuilder()
+            .setEndpoint("us-central1-aiplatform.googleapis.com:443")
+            .build();
+
+    // Initialize client that will be used to send requests. This client only needs to be created
+    // once, and can be reused for multiple requests. After completing all of your requests, call
+    // the "close" method on the client to safely clean up any remaining background resources.
+    try (ModelServiceClient modelServiceClient = ModelServiceClient.create(modelServiceSettings)) {
+      String location = "us-central1";
+      LocationName locationName = LocationName.of(project, location);
+
+      ModelContainerSpec modelContainerSpec =
+          ModelContainerSpec.newBuilder().setImageUri(imageUri).build();
+
+      Model model =
+          Model.newBuilder()
+              .setDisplayName(modelDisplayName)
+              .setMetadataSchemaUri(metadataSchemaUri)
+              .setArtifactUri(artifactUri)
+              .setContainerSpec(modelContainerSpec)
+              .build();
+
+      OperationFuture<UploadModelResponse, UploadModelOperationMetadata> uploadModelResponseFuture =
+          modelServiceClient.uploadModelAsync(locationName, model);
+      System.out.format(
+          "Operation name: %s\n", uploadModelResponseFuture.getInitialFuture().get().getName());
+      System.out.println("Waiting for operation to finish...");
+      UploadModelResponse uploadModelResponse = uploadModelResponseFuture.get(5, TimeUnit.MINUTES);
+
+      System.out.println("Upload Model Response");
+      System.out.format("Model: %s\n", uploadModelResponse.getModel());
+    }
+  }
+}
+// [END aiplatform_upload_model_sample]
diff --git a/aiplatform/snippets/src/test/java/aiplatform/CancelTrainingPipelineSampleTest.java b/aiplatform/snippets/src/test/java/aiplatform/CancelTrainingPipelineSampleTest.java
new file mode 100644
index 00000000000..1f5066679ff
--- /dev/null
+++ b/aiplatform/snippets/src/test/java/aiplatform/CancelTrainingPipelineSampleTest.java
@@ -0,0 +1,123 @@
+/*
+ * 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.
+ */
+
+package aiplatform;
+
+import static com.google.common.truth.Truth.assertThat;
+import static junit.framework.TestCase.assertNotNull;
+
+import java.io.ByteArrayOutputStream;
+import java.io.IOException;
+import java.io.PrintStream;
+import java.util.UUID;
+import java.util.concurrent.ExecutionException;
+import java.util.concurrent.TimeUnit;
+import java.util.concurrent.TimeoutException;
+import org.junit.After;
+import org.junit.Before;
+import org.junit.BeforeClass;
+import org.junit.Test;
+
+public class CancelTrainingPipelineSampleTest {
+
+  private static final String PROJECT = System.getenv("UCAIP_PROJECT_ID");
+  private static final String DATASET_ID = System.getenv("TRAINING_PIPELINE_DATASET_ID");
+  private static final String TRAINING_TASK_DEFINITION =
+      "gs://google-cloud-aiplatform/schema/trainingjob/definition/"
+              + "automl_image_classification_1.0.0.yaml";
+  private static String TRAINING_PIPELINE_ID = null;
+  private ByteArrayOutputStream bout;
+  private PrintStream out;
+  private PrintStream originalPrintStream;
+
+  private static void requireEnvVar(String varName) {
+    String errorMessage =
+        String.format("Environment variable '%s' is required to perform these tests.", varName);
+    assertNotNull(errorMessage, System.getenv(varName));
+  }
+
+  @BeforeClass
+  public static void checkRequirements() {
+    requireEnvVar("GOOGLE_APPLICATION_CREDENTIALS");
+    requireEnvVar("UCAIP_PROJECT_ID");
+    requireEnvVar("TRAINING_PIPELINE_DATASET_ID");
+  }
+
+  @Before
+  public void setUp() {
+    bout = new ByteArrayOutputStream();
+    out = new PrintStream(bout);
+    originalPrintStream = System.out;
+    System.setOut(out);
+  }
+
+  @After
+  public void tearDown()
+      throws InterruptedException, ExecutionException, IOException, TimeoutException {
+    // Delete the Training Pipeline
+    DeleteTrainingPipelineSample.deleteTrainingPipelineSample(PROJECT, TRAINING_PIPELINE_ID);
+
+    // Assert
+    String deleteResponse = bout.toString();
+    assertThat(deleteResponse).contains("Deleted Training Pipeline.");
+    System.out.flush();
+    System.setOut(originalPrintStream);
+  }
+
+  @Test
+  public void cancelTrainingPipeline() throws IOException, InterruptedException {
+    // Act
+    String trainingPipelineDisplayName =
+        String.format(
+            "temp_create_training_pipeline_test_%s",
+            UUID.randomUUID().toString().replaceAll("-", "_").substring(0, 26));
+
+    String modelDisplayName =
+        String.format(
+            "temp_create_training_pipeline_model_test_%s",
+            UUID.randomUUID().toString().replaceAll("-", "_").substring(0, 26));
+
+    CreateTrainingPipelineSample.createTrainingPipelineSample(
+        PROJECT,
+        trainingPipelineDisplayName,
+        DATASET_ID,
+        TRAINING_TASK_DEFINITION,
+        modelDisplayName);
+
+    // Assert
+    String createTrainingPipelineResponse = bout.toString();
+    assertThat(createTrainingPipelineResponse).contains(DATASET_ID);
+    assertThat(createTrainingPipelineResponse).contains("Create Training Pipeline Response");
+    TRAINING_PIPELINE_ID =
+        createTrainingPipelineResponse
+            .split("Name: ")[1]
+            .split("trainingPipelines/")[1]
+            .split("\n")[0];
+
+    // Cancel the Training Pipeline
+    CancelTrainingPipelineSample.cancelTrainingPipelineSample(PROJECT, TRAINING_PIPELINE_ID);
+
+    // Assert
+    String cancelResponse = bout.toString();
+    assertThat(cancelResponse).contains("Cancelled the Training Pipeline");
+    TimeUnit.MINUTES.sleep(1);
+
+    // Get TrainingPipeline
+    GetTrainingPipelineSample.getTrainingPipeline(PROJECT, TRAINING_PIPELINE_ID);
+    String trainingPipelineResponse = bout.toString();
+    assertThat(trainingPipelineResponse).contains("Message: CANCELLED");
+  }
+}
diff --git a/aiplatform/snippets/src/test/java/aiplatform/GetTrainingPipelineSampleTest.java b/aiplatform/snippets/src/test/java/aiplatform/GetTrainingPipelineSampleTest.java
new file mode 100644
index 00000000000..41d5c09169c
--- /dev/null
+++ b/aiplatform/snippets/src/test/java/aiplatform/GetTrainingPipelineSampleTest.java
@@ -0,0 +1,75 @@
+/*
+ * 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.
+ */
+
+package aiplatform;
+
+import static com.google.common.truth.Truth.assertThat;
+import static junit.framework.TestCase.assertNotNull;
+
+import java.io.ByteArrayOutputStream;
+import java.io.IOException;
+import java.io.PrintStream;
+import org.junit.After;
+import org.junit.Before;
+import org.junit.BeforeClass;
+import org.junit.Test;
+
+public class GetTrainingPipelineSampleTest {
+
+  private static final String PROJECT = System.getenv("UCAIP_PROJECT_ID");
+  private static final String TRAINING_PIPELINE_ID = System.getenv("GET_TRAINING_PIPELINE_ID");
+  private ByteArrayOutputStream bout;
+  private PrintStream out;
+  private PrintStream originalPrintStream;
+
+  private static void requireEnvVar(String varName) {
+    String errorMessage =
+        String.format("Environment variable '%s' is required to perform these tests.", varName);
+    assertNotNull(errorMessage, System.getenv(varName));
+  }
+
+  @BeforeClass
+  public static void checkRequirements() {
+    requireEnvVar("GOOGLE_APPLICATION_CREDENTIALS");
+    requireEnvVar("UCAIP_PROJECT_ID");
+    requireEnvVar("GET_TRAINING_PIPELINE_ID");
+  }
+
+  @Before
+  public void setUp() {
+    bout = new ByteArrayOutputStream();
+    out = new PrintStream(bout);
+    originalPrintStream = System.out;
+    System.setOut(out);
+  }
+
+  @After
+  public void tearDown() {
+    System.out.flush();
+    System.setOut(originalPrintStream);
+  }
+
+  @Test
+  public void testGetTrainingPipelineSample() throws IOException {
+    // Act
+    GetTrainingPipelineSample.getTrainingPipeline(PROJECT, TRAINING_PIPELINE_ID);
+
+    // Assert
+    String got = bout.toString();
+    assertThat(got).contains(TRAINING_PIPELINE_ID);
+    assertThat(got).contains("Get Training Pipeline Response");
+  }
+}
diff --git a/aiplatform/snippets/src/test/java/aiplatform/PredictCustomTrainedModelSampleTest.java b/aiplatform/snippets/src/test/java/aiplatform/PredictCustomTrainedModelSampleTest.java
new file mode 100644
index 00000000000..eeeae9766d9
--- /dev/null
+++ b/aiplatform/snippets/src/test/java/aiplatform/PredictCustomTrainedModelSampleTest.java
@@ -0,0 +1,82 @@
+/*
+ * 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.
+ */
+
+package aiplatform;
+
+import static com.google.common.truth.Truth.assertThat;
+import static junit.framework.TestCase.assertNotNull;
+
+import com.google.protobuf.ByteString;
+import java.io.ByteArrayOutputStream;
+import java.io.IOException;
+import java.io.PrintStream;
+import java.nio.file.Files;
+import java.nio.file.Paths;
+import java.util.Base64;
+import org.junit.After;
+import org.junit.Before;
+import org.junit.BeforeClass;
+import org.junit.Test;
+
+public class PredictCustomTrainedModelSampleTest {
+
+  private static final String PROJECT = System.getenv("UCAIP_PROJECT_ID");
+  private static final String ENDPOINT_ID =
+      System.getenv("PREDICT_CUSTOM_TRAINED_MODEL_ENDPOINT_ID");
+  private ByteArrayOutputStream bout;
+  private PrintStream out;
+  private PrintStream originalPrintStream;
+
+  private static void requireEnvVar(String varName) {
+    String errorMessage =
+        String.format("Environment variable '%s' is required to perform these tests.", varName);
+    assertNotNull(errorMessage, System.getenv(varName));
+  }
+
+  @BeforeClass
+  public static void checkRequirements() {
+    requireEnvVar("GOOGLE_APPLICATION_CREDENTIALS");
+    requireEnvVar("UCAIP_PROJECT_ID");
+    requireEnvVar("PREDICT_CUSTOM_TRAINED_MODEL_ENDPOINT_ID");
+  }
+
+  @Before
+  public void setUp() {
+    bout = new ByteArrayOutputStream();
+    out = new PrintStream(bout);
+    originalPrintStream = System.out;
+    System.setOut(out);
+  }
+
+  @After
+  public void tearDown() {
+    System.out.flush();
+    System.setOut(originalPrintStream);
+  }
+
+  @Test
+  public void testPredictCustomTrainedModelSample() throws IOException {
+    // Act
+    ByteString content = ByteString.copyFrom(Files.readAllBytes(Paths.get("resources/daisy.jpg")));
+    String encoded = Base64.getEncoder().encodeToString(content.toByteArray());
+    String instance = "[{'image_bytes': {'b64': '" + encoded + "'}, 'key':'0'}]";
+    PredictCustomTrainedModelSample.predictCustomTrainedModel(PROJECT, ENDPOINT_ID, instance);
+
+    // Assert
+    String got = bout.toString();
+    assertThat(got).contains("Predict Custom Trained model Response");
+  }
+}
diff --git a/aiplatform/snippets/src/test/java/aiplatform/UploadModelSampleTest.java b/aiplatform/snippets/src/test/java/aiplatform/UploadModelSampleTest.java
new file mode 100644
index 00000000000..3ebae3b0d5c
--- /dev/null
+++ b/aiplatform/snippets/src/test/java/aiplatform/UploadModelSampleTest.java
@@ -0,0 +1,98 @@
+/*
+ * 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.
+ */
+
+package aiplatform;
+
+import static com.google.common.truth.Truth.assertThat;
+import static junit.framework.TestCase.assertNotNull;
+
+import java.io.ByteArrayOutputStream;
+import java.io.IOException;
+import java.io.PrintStream;
+import java.util.UUID;
+import java.util.concurrent.ExecutionException;
+import java.util.concurrent.TimeUnit;
+import java.util.concurrent.TimeoutException;
+import org.junit.After;
+import org.junit.Before;
+import org.junit.BeforeClass;
+import org.junit.Test;
+
+public class UploadModelSampleTest {
+
+  private static final String PROJECT = System.getenv("UCAIP_PROJECT_ID");
+  private static final String METADATASCHEMA_URI = "";
+  private static final String IMAGE_URI =
+      "gcr.io/cloud-ml-service-public/"
+              + "cloud-ml-online-prediction-model-server-cpu:"
+              + "v1_15py3cmle_op_images_20200229_0210_RC00";
+  private static final String ARTIFACT_URI = "gs://ucaip-samples-us-central1/model/explain/";
+  private ByteArrayOutputStream bout;
+  private PrintStream out;
+  private PrintStream originalPrintStream;
+  private String uploadedModelId;
+
+  private static void requireEnvVar(String varName) {
+    String errorMessage =
+        String.format("Environment variable '%s' is required to perform these tests.", varName);
+    assertNotNull(errorMessage, System.getenv(varName));
+  }
+
+  @BeforeClass
+  public static void checkRequirements() {
+    requireEnvVar("GOOGLE_APPLICATION_CREDENTIALS");
+    requireEnvVar("UCAIP_PROJECT_ID");
+  }
+
+  @Before
+  public void setUp() {
+    bout = new ByteArrayOutputStream();
+    out = new PrintStream(bout);
+    originalPrintStream = System.out;
+    System.setOut(out);
+  }
+
+  @After
+  public void tearDown()
+      throws InterruptedException, ExecutionException, TimeoutException, IOException {
+    // Cancel the Training Pipeline
+    DeleteModelSample.deleteModel(PROJECT, uploadedModelId);
+
+    // Assert
+    String deleteModelResponse = bout.toString();
+    assertThat(deleteModelResponse).contains("Deleted Model.");
+    TimeUnit.MINUTES.sleep(1);
+    System.out.flush();
+    System.setOut(originalPrintStream);
+  }
+
+  @Test
+  public void uploadModelSampleTest()
+      throws InterruptedException, ExecutionException, TimeoutException, IOException {
+    // Act
+    String modelDisplayName =
+        String.format(
+            "temp_upload_model_test_%s",
+            UUID.randomUUID().toString().replaceAll("-", "_").substring(0, 26));
+    UploadModelSample.uploadModel(
+        PROJECT, modelDisplayName, METADATASCHEMA_URI, IMAGE_URI, ARTIFACT_URI);
+
+    // Assert
+    String got = bout.toString();
+    assertThat(got).contains("Upload Model Response");
+    uploadedModelId = got.split("Model:")[1].split("models/")[1].split("\n")[0];
+  }
+}