Examples with LocationName com.google.cloud.aiplatform.v1beta1.LocationName used on opensource projects

Example 11 with LocationName

use of com.google.cloud.aiplatform.v1beta1.LocationName in project java-aiplatform by googleapis.

the class CreateDatasetVideoSample method createDatasetSample.

static void createDatasetSample(String datasetVideoDisplayName, String project) throws IOException, InterruptedException, ExecutionException, TimeoutException {
    DatasetServiceSettings datasetServiceSettings = DatasetServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DatasetServiceClient datasetServiceClient = DatasetServiceClient.create(datasetServiceSettings)) {
        String location = "us-central1";
        String metadataSchemaUri = "gs://google-cloud-aiplatform/schema/dataset/metadata/video_1.0.0.yaml";
        LocationName locationName = LocationName.of(project, location);
        Dataset dataset = Dataset.newBuilder().setDisplayName(datasetVideoDisplayName).setMetadataSchemaUri(metadataSchemaUri).build();
        OperationFuture<Dataset, CreateDatasetOperationMetadata> datasetFuture = datasetServiceClient.createDatasetAsync(locationName, dataset);
        System.out.format("Operation name: %s\n", datasetFuture.getInitialFuture().get().getName());
        System.out.println("Waiting for operation to finish...");
        Dataset datasetResponse = datasetFuture.get(300, TimeUnit.SECONDS);
        System.out.println("Create Dataset Video Response");
        System.out.format("Name: %s\n", datasetResponse.getName());
        System.out.format("Display Name: %s\n", datasetResponse.getDisplayName());
        System.out.format("Metadata Schema Uri: %s\n", datasetResponse.getMetadataSchemaUri());
        System.out.format("Metadata: %s\n", datasetResponse.getMetadata());
        System.out.format("Create Time: %s\n", datasetResponse.getCreateTime());
        System.out.format("Update Time: %s\n", datasetResponse.getUpdateTime());
        System.out.format("Labels: %s\n", datasetResponse.getLabelsMap());
    }
}

Example 12 with LocationName

use of com.google.cloud.aiplatform.v1beta1.LocationName in project java-aiplatform by googleapis.

the class CreateEndpointSample method createEndpointSample.

static void createEndpointSample(String project, String endpointDisplayName) throws IOException, InterruptedException, ExecutionException, TimeoutException {
    EndpointServiceSettings endpointServiceSettings = EndpointServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (EndpointServiceClient endpointServiceClient = EndpointServiceClient.create(endpointServiceSettings)) {
        String location = "us-central1";
        LocationName locationName = LocationName.of(project, location);
        Endpoint endpoint = Endpoint.newBuilder().setDisplayName(endpointDisplayName).build();
        OperationFuture<Endpoint, CreateEndpointOperationMetadata> endpointFuture = endpointServiceClient.createEndpointAsync(locationName, endpoint);
        System.out.format("Operation name: %s\n", endpointFuture.getInitialFuture().get().getName());
        System.out.println("Waiting for operation to finish...");
        Endpoint endpointResponse = endpointFuture.get(300, TimeUnit.SECONDS);
        System.out.println("Create Endpoint Response");
        System.out.format("Name: %s\n", endpointResponse.getName());
        System.out.format("Display Name: %s\n", endpointResponse.getDisplayName());
        System.out.format("Description: %s\n", endpointResponse.getDescription());
        System.out.format("Labels: %s\n", endpointResponse.getLabelsMap());
        System.out.format("Create Time: %s\n", endpointResponse.getCreateTime());
        System.out.format("Update Time: %s\n", endpointResponse.getUpdateTime());
    }
}

Example 13 with LocationName

use of com.google.cloud.aiplatform.v1beta1.LocationName in project java-aiplatform by googleapis.

the class CreateHyperparameterTuningJobSample method createHyperparameterTuningJobSample.

static void createHyperparameterTuningJobSample(String project, String displayName, String containerImageUri) throws IOException {
    JobServiceSettings settings = JobServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    String location = "us-central1";
    // the "close" method on the client to safely clean up any remaining background resources.
    try (JobServiceClient client = JobServiceClient.create(settings)) {
        StudySpec.MetricSpec metric0 = StudySpec.MetricSpec.newBuilder().setMetricId("accuracy").setGoal(StudySpec.MetricSpec.GoalType.MAXIMIZE).build();
        StudySpec.ParameterSpec.DoubleValueSpec doubleValueSpec = StudySpec.ParameterSpec.DoubleValueSpec.newBuilder().setMinValue(0.001).setMaxValue(0.1).build();
        StudySpec.ParameterSpec parameter0 = StudySpec.ParameterSpec.newBuilder().setParameterId("lr").setDoubleValueSpec(doubleValueSpec).build();
        StudySpec studySpec = StudySpec.newBuilder().addMetrics(metric0).addParameters(parameter0).build();
        MachineSpec machineSpec = MachineSpec.newBuilder().setMachineType("n1-standard-4").setAcceleratorType(AcceleratorType.NVIDIA_TESLA_K80).setAcceleratorCount(1).build();
        ContainerSpec containerSpec = ContainerSpec.newBuilder().setImageUri(containerImageUri).build();
        WorkerPoolSpec workerPoolSpec0 = WorkerPoolSpec.newBuilder().setMachineSpec(machineSpec).setReplicaCount(1).setContainerSpec(containerSpec).build();
        CustomJobSpec trialJobSpec = CustomJobSpec.newBuilder().addWorkerPoolSpecs(workerPoolSpec0).build();
        HyperparameterTuningJob hyperparameterTuningJob = HyperparameterTuningJob.newBuilder().setDisplayName(displayName).setMaxTrialCount(2).setParallelTrialCount(1).setMaxFailedTrialCount(1).setStudySpec(studySpec).setTrialJobSpec(trialJobSpec).build();
        LocationName parent = LocationName.of(project, location);
        HyperparameterTuningJob response = client.createHyperparameterTuningJob(parent, hyperparameterTuningJob);
        System.out.format("response: %s\n", response);
        System.out.format("Name: %s\n", response.getName());
    }
}

Example 14 with LocationName

use of com.google.cloud.aiplatform.v1beta1.LocationName in project java-aiplatform by googleapis.

the class CreateTrainingPipelineCustomTrainingManagedDatasetSample method createTrainingPipelineCustomTrainingManagedDatasetSample.

static void createTrainingPipelineCustomTrainingManagedDatasetSample(String project, String displayName, String modelDisplayName, String datasetId, String annotationSchemaUri, String trainingContainerSpecImageUri, String modelContainerSpecImageUri, String baseOutputUriPrefix) throws IOException {
    PipelineServiceSettings settings = PipelineServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    String location = "us-central1";
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PipelineServiceClient client = PipelineServiceClient.create(settings)) {
        JsonArray jsonArgs = new JsonArray();
        jsonArgs.add("--model-dir=$(AIP_MODEL_DIR)");
        // training_task_inputs
        JsonObject jsonTrainingContainerSpec = new JsonObject();
        jsonTrainingContainerSpec.addProperty("imageUri", trainingContainerSpecImageUri);
        // AIP_MODEL_DIR is set by the service according to baseOutputDirectory.
        jsonTrainingContainerSpec.add("args", jsonArgs);
        JsonObject jsonMachineSpec = new JsonObject();
        jsonMachineSpec.addProperty("machineType", "n1-standard-8");
        JsonObject jsonTrainingWorkerPoolSpec = new JsonObject();
        jsonTrainingWorkerPoolSpec.addProperty("replicaCount", 1);
        jsonTrainingWorkerPoolSpec.add("machineSpec", jsonMachineSpec);
        jsonTrainingWorkerPoolSpec.add("containerSpec", jsonTrainingContainerSpec);
        JsonArray jsonWorkerPoolSpecs = new JsonArray();
        jsonWorkerPoolSpecs.add(jsonTrainingWorkerPoolSpec);
        JsonObject jsonBaseOutputDirectory = new JsonObject();
        jsonBaseOutputDirectory.addProperty("outputUriPrefix", baseOutputUriPrefix);
        JsonObject jsonTrainingTaskInputs = new JsonObject();
        jsonTrainingTaskInputs.add("workerPoolSpecs", jsonWorkerPoolSpecs);
        jsonTrainingTaskInputs.add("baseOutputDirectory", jsonBaseOutputDirectory);
        Value.Builder trainingTaskInputsBuilder = Value.newBuilder();
        JsonFormat.parser().merge(jsonTrainingTaskInputs.toString(), trainingTaskInputsBuilder);
        Value trainingTaskInputs = trainingTaskInputsBuilder.build();
        // model_to_upload
        ModelContainerSpec modelContainerSpec = ModelContainerSpec.newBuilder().setImageUri(modelContainerSpecImageUri).build();
        Model model = Model.newBuilder().setDisplayName(modelDisplayName).setContainerSpec(modelContainerSpec).build();
        GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(baseOutputUriPrefix).build();
        // input_data_config
        InputDataConfig inputDataConfig = InputDataConfig.newBuilder().setDatasetId(datasetId).setAnnotationSchemaUri(annotationSchemaUri).setGcsDestination(gcsDestination).build();
        // training_task_definition
        String customTaskDefinition = "gs://google-cloud-aiplatform/schema/trainingjob/definition/custom_task_1.0.0.yaml";
        TrainingPipeline trainingPipeline = TrainingPipeline.newBuilder().setDisplayName(displayName).setInputDataConfig(inputDataConfig).setTrainingTaskDefinition(customTaskDefinition).setTrainingTaskInputs(trainingTaskInputs).setModelToUpload(model).build();
        LocationName parent = LocationName.of(project, location);
        TrainingPipeline response = client.createTrainingPipeline(parent, trainingPipeline);
        System.out.format("response: %s\n", response);
        System.out.format("Name: %s\n", response.getName());
    }
}

Example 15 with LocationName

use of com.google.cloud.aiplatform.v1beta1.LocationName in project java-aiplatform by googleapis.

the class CreateTrainingPipelineImageObjectDetectionSample method createTrainingPipelineImageObjectDetectionSample.

static void createTrainingPipelineImageObjectDetectionSample(String project, String trainingPipelineDisplayName, String datasetId, String modelDisplayName) throws IOException {
    PipelineServiceSettings pipelineServiceSettings = PipelineServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PipelineServiceClient pipelineServiceClient = PipelineServiceClient.create(pipelineServiceSettings)) {
        String location = "us-central1";
        String trainingTaskDefinition = "gs://google-cloud-aiplatform/schema/trainingjob/definition/" + "automl_image_object_detection_1.0.0.yaml";
        LocationName locationName = LocationName.of(project, location);
        AutoMlImageObjectDetectionInputs autoMlImageObjectDetectionInputs = AutoMlImageObjectDetectionInputs.newBuilder().setModelType(ModelType.CLOUD_HIGH_ACCURACY_1).setBudgetMilliNodeHours(20000).setDisableEarlyStopping(false).build();
        InputDataConfig trainingInputDataConfig = InputDataConfig.newBuilder().setDatasetId(datasetId).build();
        Model model = Model.newBuilder().setDisplayName(modelDisplayName).build();
        TrainingPipeline trainingPipeline = TrainingPipeline.newBuilder().setDisplayName(trainingPipelineDisplayName).setTrainingTaskDefinition(trainingTaskDefinition).setTrainingTaskInputs(ValueConverter.toValue(autoMlImageObjectDetectionInputs)).setInputDataConfig(trainingInputDataConfig).setModelToUpload(model).build();
        TrainingPipeline trainingPipelineResponse = pipelineServiceClient.createTrainingPipeline(locationName, trainingPipeline);
        System.out.println("Create Training Pipeline Image Object Detection 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());
        }
        Status status = trainingPipelineResponse.getError();
        System.out.println("Error");
        System.out.format("Code: %s\n", status.getCode());
        System.out.format("Message: %s\n", status.getMessage());
    }
}