use of com.google.cloud.aiplatform.v1.Dataset in project java-aiplatform by googleapis.
the class DatasetServiceClientTest method listDataItemsTest.
@Test
public void listDataItemsTest() throws Exception {
DataItem responsesElement = DataItem.newBuilder().build();
ListDataItemsResponse expectedResponse = ListDataItemsResponse.newBuilder().setNextPageToken("").addAllDataItems(Arrays.asList(responsesElement)).build();
mockDatasetService.addResponse(expectedResponse);
DatasetName parent = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]");
ListDataItemsPagedResponse pagedListResponse = client.listDataItems(parent);
List<DataItem> resources = Lists.newArrayList(pagedListResponse.iterateAll());
Assert.assertEquals(1, resources.size());
Assert.assertEquals(expectedResponse.getDataItemsList().get(0), resources.get(0));
List<AbstractMessage> actualRequests = mockDatasetService.getRequests();
Assert.assertEquals(1, actualRequests.size());
ListDataItemsRequest actualRequest = ((ListDataItemsRequest) actualRequests.get(0));
Assert.assertEquals(parent.toString(), actualRequest.getParent());
Assert.assertTrue(channelProvider.isHeaderSent(ApiClientHeaderProvider.getDefaultApiClientHeaderKey(), GaxGrpcProperties.getDefaultApiClientHeaderPattern()));
}
use of com.google.cloud.aiplatform.v1.Dataset in project java-aiplatform by googleapis.
the class DatasetServiceClientTest method listDatasetsTest.
@Test
public void listDatasetsTest() throws Exception {
Dataset responsesElement = Dataset.newBuilder().build();
ListDatasetsResponse expectedResponse = ListDatasetsResponse.newBuilder().setNextPageToken("").addAllDatasets(Arrays.asList(responsesElement)).build();
mockDatasetService.addResponse(expectedResponse);
LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
ListDatasetsPagedResponse pagedListResponse = client.listDatasets(parent);
List<Dataset> resources = Lists.newArrayList(pagedListResponse.iterateAll());
Assert.assertEquals(1, resources.size());
Assert.assertEquals(expectedResponse.getDatasetsList().get(0), resources.get(0));
List<AbstractMessage> actualRequests = mockDatasetService.getRequests();
Assert.assertEquals(1, actualRequests.size());
ListDatasetsRequest actualRequest = ((ListDatasetsRequest) actualRequests.get(0));
Assert.assertEquals(parent.toString(), actualRequest.getParent());
Assert.assertTrue(channelProvider.isHeaderSent(ApiClientHeaderProvider.getDefaultApiClientHeaderKey(), GaxGrpcProperties.getDefaultApiClientHeaderPattern()));
}
use of com.google.cloud.aiplatform.v1.Dataset in project java-aiplatform by googleapis.
the class CreateTrainingPipelineVideoObjectTrackingSample method createTrainingPipelineVideoObjectTracking.
static void createTrainingPipelineVideoObjectTracking(String trainingPipelineVideoObjectTracking, String datasetId, String modelDisplayName, String project) 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_video_object_tracking_1.0.0.yaml";
LocationName locationName = LocationName.of(project, location);
AutoMlVideoObjectTrackingInputs trainingTaskInputs = AutoMlVideoObjectTrackingInputs.newBuilder().setModelType(ModelType.CLOUD).build();
InputDataConfig inputDataConfig = InputDataConfig.newBuilder().setDatasetId(datasetId).build();
Model modelToUpload = Model.newBuilder().setDisplayName(modelDisplayName).build();
TrainingPipeline trainingPipeline = TrainingPipeline.newBuilder().setDisplayName(trainingPipelineVideoObjectTracking).setTrainingTaskDefinition(trainingTaskDefinition).setTrainingTaskInputs(ValueConverter.toValue(trainingTaskInputs)).setInputDataConfig(inputDataConfig).setModelToUpload(modelToUpload).build();
TrainingPipeline createTrainingPipelineResponse = pipelineServiceClient.createTrainingPipeline(locationName, trainingPipeline);
System.out.println("Create Training Pipeline Video Object Tracking Response");
System.out.format("Name: %s\n", createTrainingPipelineResponse.getName());
System.out.format("Display Name: %s\n", createTrainingPipelineResponse.getDisplayName());
System.out.format("Training Task Definition %s\n", createTrainingPipelineResponse.getTrainingTaskDefinition());
System.out.format("Training Task Inputs: %s\n", createTrainingPipelineResponse.getTrainingTaskInputs().toString());
System.out.format("Training Task Metadata: %s\n", createTrainingPipelineResponse.getTrainingTaskMetadata().toString());
System.out.format("State: %s\n", createTrainingPipelineResponse.getState().toString());
System.out.format("Create Time: %s\n", createTrainingPipelineResponse.getCreateTime().toString());
System.out.format("StartTime %s\n", createTrainingPipelineResponse.getStartTime().toString());
System.out.format("End Time: %s\n", createTrainingPipelineResponse.getEndTime().toString());
System.out.format("Update Time: %s\n", createTrainingPipelineResponse.getUpdateTime().toString());
System.out.format("Labels: %s\n", createTrainingPipelineResponse.getLabelsMap().toString());
InputDataConfig inputDataConfigResponse = createTrainingPipelineResponse.getInputDataConfig();
System.out.println("Input Data config");
System.out.format("Dataset Id: %s\n", inputDataConfigResponse.getDatasetId());
System.out.format("Annotations Filter: %s\n", inputDataConfigResponse.getAnnotationsFilter());
FractionSplit fractionSplit = inputDataConfigResponse.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 = inputDataConfigResponse.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 = inputDataConfigResponse.getPredefinedSplit();
System.out.println("Predefined Split");
System.out.format("Key: %s\n", predefinedSplit.getKey());
TimestampSplit timestampSplit = inputDataConfigResponse.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 = createTrainingPipelineResponse.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().toString());
System.out.format("Supported Input Storage Formats: %s\n", modelResponse.getSupportedInputStorageFormatsList().toString());
System.out.format("Supported Output Storage Formats: %s\n", modelResponse.getSupportedOutputStorageFormatsList().toString());
System.out.format("Create Time: %s\n", modelResponse.getCreateTime());
System.out.format("Update Time: %s\n", modelResponse.getUpdateTime());
System.out.format("Labels: %s\n", modelResponse.getLabelsMap());
Status status = createTrainingPipelineResponse.getError();
System.out.println("Error");
System.out.format("Code: %s\n", status.getCode());
System.out.format("Message: %s\n", status.getMessage());
}
}
use of com.google.cloud.aiplatform.v1.Dataset in project java-aiplatform by googleapis.
the class CreateTrainingPipelineImageClassificationSample method createTrainingPipelineImageClassificationSample.
static void createTrainingPipelineImageClassificationSample(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_classification_1.0.0.yaml";
LocationName locationName = LocationName.of(project, location);
AutoMlImageClassificationInputs autoMlImageClassificationInputs = AutoMlImageClassificationInputs.newBuilder().setModelType(ModelType.CLOUD).setMultiLabel(false).setBudgetMilliNodeHours(8000).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(autoMlImageClassificationInputs)).setInputDataConfig(trainingInputDataConfig).setModelToUpload(model).build();
TrainingPipeline trainingPipelineResponse = pipelineServiceClient.createTrainingPipeline(locationName, trainingPipeline);
System.out.println("Create Training Pipeline Image Classification 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());
}
}
use of com.google.cloud.aiplatform.v1.Dataset 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());
}
}
Aggregations