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Example 11 with Model

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

the class GetModelEvaluationVideoClassificationSample method getModelEvaluationVideoClassification.

static void getModelEvaluationVideoClassification(String project, String modelId, String evaluationId) throws IOException {
    ModelServiceSettings modelServiceSettings = ModelServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (ModelServiceClient modelServiceClient = ModelServiceClient.create(modelServiceSettings)) {
        String location = "us-central1";
        ModelEvaluationName modelEvaluationName = ModelEvaluationName.of(project, location, modelId, evaluationId);
        ModelEvaluation modelEvaluation = modelServiceClient.getModelEvaluation(modelEvaluationName);
        System.out.println("Get Model Evaluation Video Classification Response");
        System.out.format("Name: %s\n", modelEvaluation.getName());
        System.out.format("Metrics Schema Uri: %s\n", modelEvaluation.getMetricsSchemaUri());
        System.out.format("Metrics: %s\n", modelEvaluation.getMetrics());
        System.out.format("Create Time: %s\n", modelEvaluation.getCreateTime());
        System.out.format("Slice Dimensions: %s\n", modelEvaluation.getSliceDimensionsList());
    }
}
Also used : ModelEvaluationName(com.google.cloud.aiplatform.v1.ModelEvaluationName) ModelEvaluation(com.google.cloud.aiplatform.v1.ModelEvaluation) ModelServiceSettings(com.google.cloud.aiplatform.v1.ModelServiceSettings) ModelServiceClient(com.google.cloud.aiplatform.v1.ModelServiceClient)

Example 12 with Model

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

the class GetModelEvaluationVideoObjectTrackingSample method getModelEvaluationVideoObjectTracking.

static void getModelEvaluationVideoObjectTracking(String project, String modelId, String evaluationId) throws IOException {
    ModelServiceSettings modelServiceSettings = ModelServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (ModelServiceClient modelServiceClient = ModelServiceClient.create(modelServiceSettings)) {
        String location = "us-central1";
        ModelEvaluationName modelEvaluationName = ModelEvaluationName.of(project, location, modelId, evaluationId);
        ModelEvaluation modelEvaluation = modelServiceClient.getModelEvaluation(modelEvaluationName);
        System.out.println("Get Model Evaluation Video Object Tracking Response");
        System.out.format("Name: %s\n", modelEvaluation.getName());
        System.out.format("Metrics Schema Uri: %s\n", modelEvaluation.getMetricsSchemaUri());
        System.out.format("Metrics: %s\n", modelEvaluation.getMetrics());
        System.out.format("Create Time: %s\n", modelEvaluation.getCreateTime());
        System.out.format("Slice Dimensions: %s\n", modelEvaluation.getSliceDimensionsList());
    }
}
Also used : ModelEvaluationName(com.google.cloud.aiplatform.v1.ModelEvaluationName) ModelEvaluation(com.google.cloud.aiplatform.v1.ModelEvaluation) ModelServiceSettings(com.google.cloud.aiplatform.v1.ModelServiceSettings) ModelServiceClient(com.google.cloud.aiplatform.v1.ModelServiceClient)

Example 13 with Model

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

the class GetModelSample method getModelSample.

static void getModelSample(String project, String modelId) throws IOException {
    ModelServiceSettings modelServiceSettings = ModelServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // 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);
        Model modelResponse = modelServiceClient.getModel(modelName);
        System.out.println("Get Model response");
        System.out.format("\tName: %s\n", modelResponse.getName());
        System.out.format("\tDisplay Name: %s\n", modelResponse.getDisplayName());
        System.out.format("\tDescription: %s\n", modelResponse.getDescription());
        System.out.format("\tMetadata Schema Uri: %s\n", modelResponse.getMetadataSchemaUri());
        System.out.format("\tMetadata: %s\n", modelResponse.getMetadata());
        System.out.format("\tTraining Pipeline: %s\n", modelResponse.getTrainingPipeline());
        System.out.format("\tArtifact Uri: %s\n", modelResponse.getArtifactUri());
        System.out.format("\tSupported Deployment Resources Types: %s\n", modelResponse.getSupportedDeploymentResourcesTypesList());
        System.out.format("\tSupported Input Storage Formats: %s\n", modelResponse.getSupportedInputStorageFormatsList());
        System.out.format("\tSupported Output Storage Formats: %s\n", modelResponse.getSupportedOutputStorageFormatsList());
        System.out.format("\tCreate Time: %s\n", modelResponse.getCreateTime());
        System.out.format("\tUpdate Time: %s\n", modelResponse.getUpdateTime());
        System.out.format("\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 (ExportFormat exportFormat : modelResponse.getSupportedExportFormatsList()) {
            System.out.println("\tSupported Export Format");
            System.out.format("\t\tId: %s\n", exportFormat.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());
        }
    }
}
Also used : PredictSchemata(com.google.cloud.aiplatform.v1.PredictSchemata) ModelName(com.google.cloud.aiplatform.v1.ModelName) ModelContainerSpec(com.google.cloud.aiplatform.v1.ModelContainerSpec) ModelServiceSettings(com.google.cloud.aiplatform.v1.ModelServiceSettings) Port(com.google.cloud.aiplatform.v1.Port) DeployedModelRef(com.google.cloud.aiplatform.v1.DeployedModelRef) Model(com.google.cloud.aiplatform.v1.Model) EnvVar(com.google.cloud.aiplatform.v1.EnvVar) ExportFormat(com.google.cloud.aiplatform.v1.Model.ExportFormat) ModelServiceClient(com.google.cloud.aiplatform.v1.ModelServiceClient)

Example 14 with Model

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

the class GetTrainingPipelineSample method getTrainingPipeline.

static void getTrainingPipeline(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);
        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());
        }
        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());
    }
}
Also used : Status(com.google.rpc.Status) PredictSchemata(com.google.cloud.aiplatform.v1.PredictSchemata) TrainingPipelineName(com.google.cloud.aiplatform.v1.TrainingPipelineName) TrainingPipeline(com.google.cloud.aiplatform.v1.TrainingPipeline) TimestampSplit(com.google.cloud.aiplatform.v1.TimestampSplit) Port(com.google.cloud.aiplatform.v1.Port) InputDataConfig(com.google.cloud.aiplatform.v1.InputDataConfig) 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) 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 15 with Model

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

the class ListModelEvaluationSliceSample method listModelEvaluationSliceSample.

static void listModelEvaluationSliceSample(String project, String modelId, String evaluationId) throws IOException {
    ModelServiceSettings modelServiceSettings = ModelServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (ModelServiceClient modelServiceClient = ModelServiceClient.create(modelServiceSettings)) {
        String location = "us-central1";
        ModelEvaluationName modelEvaluationName = ModelEvaluationName.of(project, location, modelId, evaluationId);
        for (ModelEvaluationSlice modelEvaluationSlice : modelServiceClient.listModelEvaluationSlices(modelEvaluationName).iterateAll()) {
            System.out.format("Model Evaluation Slice Name: %s\n", modelEvaluationSlice.getName());
            System.out.format("Metrics Schema Uri: %s\n", modelEvaluationSlice.getMetricsSchemaUri());
            System.out.format("Metrics: %s\n", modelEvaluationSlice.getMetrics());
            System.out.format("Create Time: %s\n", modelEvaluationSlice.getCreateTime());
            Slice slice = modelEvaluationSlice.getSlice();
            System.out.format("Slice Dimensions: %s\n", slice.getDimension());
            System.out.format("Slice Value: %s\n\n", slice.getValue());
        }
    }
}
Also used : ModelEvaluationName(com.google.cloud.aiplatform.v1.ModelEvaluationName) ModelEvaluationSlice(com.google.cloud.aiplatform.v1.ModelEvaluationSlice) Slice(com.google.cloud.aiplatform.v1.ModelEvaluationSlice.Slice) ModelServiceSettings(com.google.cloud.aiplatform.v1.ModelServiceSettings) ModelServiceClient(com.google.cloud.aiplatform.v1.ModelServiceClient) ModelEvaluationSlice(com.google.cloud.aiplatform.v1.ModelEvaluationSlice)

Aggregations

Test (org.junit.Test)52 Model (org.eclipse.xtext.valueconverter.bug250313.Model)30 LocationName (com.google.cloud.aiplatform.v1.LocationName)17 ModelServiceClient (com.google.cloud.aiplatform.v1.ModelServiceClient)17 ModelServiceSettings (com.google.cloud.aiplatform.v1.ModelServiceSettings)17 Model (com.google.cloud.aiplatform.v1.Model)16 AutoMlClient (com.google.cloud.automl.v1.AutoMlClient)16 Model (com.google.cloud.automl.v1.Model)16 ICompositeNode (org.eclipse.xtext.nodemodel.ICompositeNode)16 PipelineServiceClient (com.google.cloud.aiplatform.v1.PipelineServiceClient)14 PipelineServiceSettings (com.google.cloud.aiplatform.v1.PipelineServiceSettings)14 TrainingPipeline (com.google.cloud.aiplatform.v1.TrainingPipeline)14 Value (com.google.protobuf.Value)14 InputDataConfig (com.google.cloud.aiplatform.v1.InputDataConfig)13 ModelContainerSpec (com.google.cloud.aiplatform.v1.ModelContainerSpec)13 ArrayList (java.util.ArrayList)12 EndpointName (com.google.cloud.aiplatform.v1.EndpointName)11 FilterSplit (com.google.cloud.aiplatform.v1.FilterSplit)11 FractionSplit (com.google.cloud.aiplatform.v1.FractionSplit)11 PredefinedSplit (com.google.cloud.aiplatform.v1.PredefinedSplit)11