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Example 16 with PipelineServiceSettings

use of com.google.cloud.aiplatform.v1.PipelineServiceSettings in project java-aiplatform by googleapis.

the class CreateTrainingPipelineSample method createTrainingPipelineSample.

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();
    // 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());
        }
        Status status = trainingPipelineResponse.getError();
        System.out.println("Error");
        System.out.format("Code: %s\n", status.getCode());
        System.out.format("Message: %s\n", status.getMessage());
    }
}
Also used : Status(com.google.rpc.Status) PredictSchemata(com.google.cloud.aiplatform.v1.PredictSchemata) TrainingPipeline(com.google.cloud.aiplatform.v1.TrainingPipeline) TimestampSplit(com.google.cloud.aiplatform.v1.TimestampSplit) Port(com.google.cloud.aiplatform.v1.Port) ExportFormat(com.google.cloud.aiplatform.v1.Model.ExportFormat) InputDataConfig(com.google.cloud.aiplatform.v1.InputDataConfig) LocationName(com.google.cloud.aiplatform.v1.LocationName) PredefinedSplit(com.google.cloud.aiplatform.v1.PredefinedSplit) FilterSplit(com.google.cloud.aiplatform.v1.FilterSplit) FractionSplit(com.google.cloud.aiplatform.v1.FractionSplit) ModelContainerSpec(com.google.cloud.aiplatform.v1.ModelContainerSpec) DeployedModelRef(com.google.cloud.aiplatform.v1.DeployedModelRef) Value(com.google.protobuf.Value) Model(com.google.cloud.aiplatform.v1.Model) PipelineServiceSettings(com.google.cloud.aiplatform.v1.PipelineServiceSettings) EnvVar(com.google.cloud.aiplatform.v1.EnvVar) PipelineServiceClient(com.google.cloud.aiplatform.v1.PipelineServiceClient)

Example 17 with PipelineServiceSettings

use of com.google.cloud.aiplatform.v1.PipelineServiceSettings in project java-aiplatform by googleapis.

the class CancelTrainingPipelineSample method cancelTrainingPipelineSample.

static void cancelTrainingPipelineSample(String project, String trainingPipelineId) 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";
        TrainingPipelineName trainingPipelineName = TrainingPipelineName.of(project, location, trainingPipelineId);
        pipelineServiceClient.cancelTrainingPipeline(trainingPipelineName);
        System.out.println("Cancelled the Training Pipeline");
    }
}
Also used : TrainingPipelineName(com.google.cloud.aiplatform.v1.TrainingPipelineName) PipelineServiceSettings(com.google.cloud.aiplatform.v1.PipelineServiceSettings) PipelineServiceClient(com.google.cloud.aiplatform.v1.PipelineServiceClient)

Aggregations

PipelineServiceClient (com.google.cloud.aiplatform.v1.PipelineServiceClient)17 PipelineServiceSettings (com.google.cloud.aiplatform.v1.PipelineServiceSettings)17 TrainingPipeline (com.google.cloud.aiplatform.v1.TrainingPipeline)15 Model (com.google.cloud.aiplatform.v1.Model)14 InputDataConfig (com.google.cloud.aiplatform.v1.InputDataConfig)13 LocationName (com.google.cloud.aiplatform.v1.LocationName)13 FilterSplit (com.google.cloud.aiplatform.v1.FilterSplit)11 FractionSplit (com.google.cloud.aiplatform.v1.FractionSplit)11 ModelContainerSpec (com.google.cloud.aiplatform.v1.ModelContainerSpec)11 PredefinedSplit (com.google.cloud.aiplatform.v1.PredefinedSplit)11 TimestampSplit (com.google.cloud.aiplatform.v1.TimestampSplit)11 Status (com.google.rpc.Status)11 DeployedModelRef (com.google.cloud.aiplatform.v1.DeployedModelRef)9 EnvVar (com.google.cloud.aiplatform.v1.EnvVar)9 Port (com.google.cloud.aiplatform.v1.Port)9 PredictSchemata (com.google.cloud.aiplatform.v1.PredictSchemata)9 ExportFormat (com.google.cloud.aiplatform.v1.Model.ExportFormat)6 TrainingPipelineName (com.google.cloud.aiplatform.v1.TrainingPipelineName)4 Value (com.google.protobuf.Value)3 JsonArray (com.google.gson.JsonArray)2