public static final class BatchPredictionJob.OutputConfig extends GeneratedMessageV3 implements BatchPredictionJob.OutputConfigOrBuilder
Configures the output of
BatchPredictionJob.
See
Model.supported_output_storage_formats
for supported output formats, and how predictions are expressed via any of
them.
Protobuf type google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig
Inherited Members
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT)
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT,int)
com.google.protobuf.GeneratedMessageV3.<T>emptyList(java.lang.Class<T>)
com.google.protobuf.GeneratedMessageV3.internalGetMapFieldReflection(int)
Static Fields
public static final int BIGQUERY_DESTINATION_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int GCS_DESTINATION_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int PREDICTIONS_FORMAT_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
Static Methods
public static BatchPredictionJob.OutputConfig getDefaultInstance()
public static final Descriptors.Descriptor getDescriptor()
public static BatchPredictionJob.OutputConfig.Builder newBuilder()
public static BatchPredictionJob.OutputConfig.Builder newBuilder(BatchPredictionJob.OutputConfig prototype)
public static BatchPredictionJob.OutputConfig parseDelimitedFrom(InputStream input)
public static BatchPredictionJob.OutputConfig parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static BatchPredictionJob.OutputConfig parseFrom(byte[] data)
| Parameter |
|---|
| Name | Description |
data | byte[]
|
public static BatchPredictionJob.OutputConfig parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static BatchPredictionJob.OutputConfig parseFrom(ByteString data)
public static BatchPredictionJob.OutputConfig parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static BatchPredictionJob.OutputConfig parseFrom(CodedInputStream input)
public static BatchPredictionJob.OutputConfig parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static BatchPredictionJob.OutputConfig parseFrom(InputStream input)
public static BatchPredictionJob.OutputConfig parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static BatchPredictionJob.OutputConfig parseFrom(ByteBuffer data)
public static BatchPredictionJob.OutputConfig parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static Parser<BatchPredictionJob.OutputConfig> parser()
Methods
public boolean equals(Object obj)
| Parameter |
|---|
| Name | Description |
obj | Object
|
Overrides
public BigQueryDestination getBigqueryDestination()
The BigQuery project or dataset location where the output is to be
written to. If project is provided, a new dataset is created with name
prediction_<model-display-name>_<job-create-time>
where <model-display-name> is made
BigQuery-dataset-name compatible (for example, most special characters
become underscores), and timestamp is in
YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset
two tables will be created, predictions, and errors.
If the Model has both
instance
and
prediction
schemata defined then the tables have columns as follows: The
predictions table contains instances for which the prediction
succeeded, it has columns as per a concatenation of the Model's
instance and prediction schemata. The errors table contains rows for
which the prediction has failed, it has instance columns, as per the
instance schema, followed by a single "errors" column, which as values
has google.rpc.Status
represented as a STRUCT, and containing only code and message.
.google.cloud.aiplatform.v1beta1.BigQueryDestination bigquery_destination = 3;
public BigQueryDestinationOrBuilder getBigqueryDestinationOrBuilder()
The BigQuery project or dataset location where the output is to be
written to. If project is provided, a new dataset is created with name
prediction_<model-display-name>_<job-create-time>
where <model-display-name> is made
BigQuery-dataset-name compatible (for example, most special characters
become underscores), and timestamp is in
YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset
two tables will be created, predictions, and errors.
If the Model has both
instance
and
prediction
schemata defined then the tables have columns as follows: The
predictions table contains instances for which the prediction
succeeded, it has columns as per a concatenation of the Model's
instance and prediction schemata. The errors table contains rows for
which the prediction has failed, it has instance columns, as per the
instance schema, followed by a single "errors" column, which as values
has google.rpc.Status
represented as a STRUCT, and containing only code and message.
.google.cloud.aiplatform.v1beta1.BigQueryDestination bigquery_destination = 3;
public BatchPredictionJob.OutputConfig getDefaultInstanceForType()
public BatchPredictionJob.OutputConfig.DestinationCase getDestinationCase()
public GcsDestination getGcsDestination()
The Cloud Storage location of the directory where the output is
to be written to. In the given directory a new directory is created.
Its name is prediction-<model-display-name>-<job-create-time>,
where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format.
Inside of it files predictions_0001.<extension>,
predictions_0002.<extension>, ..., predictions_N.<extension>
are created where <extension> depends on chosen
predictions_format,
and N may equal 0001 and depends on the total number of successfully
predicted instances. If the Model has both
instance
and
prediction
schemata defined then each such file contains predictions as per the
predictions_format.
If prediction for any instance failed (partially or completely), then
an additional errors_0001.<extension>, errors_0002.<extension>,...,
errors_N.<extension> files are created (N depends on total number
of failed predictions). These files contain the failed instances,
as per their schema, followed by an additional error field which as
value has google.rpc.Status
containing only code and message fields.
.google.cloud.aiplatform.v1beta1.GcsDestination gcs_destination = 2;
public GcsDestinationOrBuilder getGcsDestinationOrBuilder()
The Cloud Storage location of the directory where the output is
to be written to. In the given directory a new directory is created.
Its name is prediction-<model-display-name>-<job-create-time>,
where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format.
Inside of it files predictions_0001.<extension>,
predictions_0002.<extension>, ..., predictions_N.<extension>
are created where <extension> depends on chosen
predictions_format,
and N may equal 0001 and depends on the total number of successfully
predicted instances. If the Model has both
instance
and
prediction
schemata defined then each such file contains predictions as per the
predictions_format.
If prediction for any instance failed (partially or completely), then
an additional errors_0001.<extension>, errors_0002.<extension>,...,
errors_N.<extension> files are created (N depends on total number
of failed predictions). These files contain the failed instances,
as per their schema, followed by an additional error field which as
value has google.rpc.Status
containing only code and message fields.
.google.cloud.aiplatform.v1beta1.GcsDestination gcs_destination = 2;
public Parser<BatchPredictionJob.OutputConfig> getParserForType()
Overrides
public String getPredictionsFormat()
Required. The format in which Vertex AI gives the predictions, must be
one of the
Model's
supported_output_storage_formats.
string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];
| Returns |
|---|
| Type | Description |
String | The predictionsFormat.
|
public ByteString getPredictionsFormatBytes()
Required. The format in which Vertex AI gives the predictions, must be
one of the
Model's
supported_output_storage_formats.
string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];
| Returns |
|---|
| Type | Description |
ByteString | The bytes for predictionsFormat.
|
public int getSerializedSize()
| Returns |
|---|
| Type | Description |
int | |
Overrides
public boolean hasBigqueryDestination()
The BigQuery project or dataset location where the output is to be
written to. If project is provided, a new dataset is created with name
prediction_<model-display-name>_<job-create-time>
where <model-display-name> is made
BigQuery-dataset-name compatible (for example, most special characters
become underscores), and timestamp is in
YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset
two tables will be created, predictions, and errors.
If the Model has both
instance
and
prediction
schemata defined then the tables have columns as follows: The
predictions table contains instances for which the prediction
succeeded, it has columns as per a concatenation of the Model's
instance and prediction schemata. The errors table contains rows for
which the prediction has failed, it has instance columns, as per the
instance schema, followed by a single "errors" column, which as values
has google.rpc.Status
represented as a STRUCT, and containing only code and message.
.google.cloud.aiplatform.v1beta1.BigQueryDestination bigquery_destination = 3;
| Returns |
|---|
| Type | Description |
boolean | Whether the bigqueryDestination field is set.
|
public boolean hasGcsDestination()
The Cloud Storage location of the directory where the output is
to be written to. In the given directory a new directory is created.
Its name is prediction-<model-display-name>-<job-create-time>,
where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format.
Inside of it files predictions_0001.<extension>,
predictions_0002.<extension>, ..., predictions_N.<extension>
are created where <extension> depends on chosen
predictions_format,
and N may equal 0001 and depends on the total number of successfully
predicted instances. If the Model has both
instance
and
prediction
schemata defined then each such file contains predictions as per the
predictions_format.
If prediction for any instance failed (partially or completely), then
an additional errors_0001.<extension>, errors_0002.<extension>,...,
errors_N.<extension> files are created (N depends on total number
of failed predictions). These files contain the failed instances,
as per their schema, followed by an additional error field which as
value has google.rpc.Status
containing only code and message fields.
.google.cloud.aiplatform.v1beta1.GcsDestination gcs_destination = 2;
| Returns |
|---|
| Type | Description |
boolean | Whether the gcsDestination field is set.
|
| Returns |
|---|
| Type | Description |
int | |
Overrides
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Overrides
public final boolean isInitialized()
Overrides
public BatchPredictionJob.OutputConfig.Builder newBuilderForType()
protected BatchPredictionJob.OutputConfig.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Overrides
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Overrides
public BatchPredictionJob.OutputConfig.Builder toBuilder()
public void writeTo(CodedOutputStream output)
Overrides
