public static final class BatchPredictionJob.InstanceConfig extends GeneratedMessageV3 implements BatchPredictionJob.InstanceConfigOrBuilder
Configuration defining how to transform batch prediction input instances to
the instances that the Model accepts.
Protobuf type google.cloud.aiplatform.v1beta1.BatchPredictionJob.InstanceConfig
Static Fields
public static final int EXCLUDED_FIELDS_FIELD_NUMBER
Field Value
public static final int INCLUDED_FIELDS_FIELD_NUMBER
Field Value
public static final int INSTANCE_TYPE_FIELD_NUMBER
Field Value
public static final int KEY_FIELD_FIELD_NUMBER
Field Value
Static Methods
public static BatchPredictionJob.InstanceConfig getDefaultInstance()
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public static final Descriptors.Descriptor getDescriptor()
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public static BatchPredictionJob.InstanceConfig.Builder newBuilder()
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public static BatchPredictionJob.InstanceConfig.Builder newBuilder(BatchPredictionJob.InstanceConfig prototype)
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public static BatchPredictionJob.InstanceConfig parseDelimitedFrom(InputStream input)
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public static BatchPredictionJob.InstanceConfig parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
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public static BatchPredictionJob.InstanceConfig parseFrom(byte[] data)
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| Name | Description |
| data | byte[]
|
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public static BatchPredictionJob.InstanceConfig parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
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public static BatchPredictionJob.InstanceConfig parseFrom(ByteString data)
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public static BatchPredictionJob.InstanceConfig parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
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public static BatchPredictionJob.InstanceConfig parseFrom(CodedInputStream input)
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public static BatchPredictionJob.InstanceConfig parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
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public static BatchPredictionJob.InstanceConfig parseFrom(InputStream input)
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public static BatchPredictionJob.InstanceConfig parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
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public static BatchPredictionJob.InstanceConfig parseFrom(ByteBuffer data)
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public static BatchPredictionJob.InstanceConfig parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
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public static Parser<BatchPredictionJob.InstanceConfig> parser()
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Methods
public boolean equals(Object obj)
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Overrides
public BatchPredictionJob.InstanceConfig getDefaultInstanceForType()
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public String getExcludedFields(int index)
Fields that will be excluded in the prediction instance that is
sent to the Model.
Excluded will be attached to the batch prediction output if key_field
is not specified.
When excluded_fields is populated, included_fields must be empty.
The input must be JSONL with objects at each line, CSV, BigQuery
or TfRecord.
repeated string excluded_fields = 4;
| Name | Description |
| index | int
The index of the element to return.
|
Returns
| Type | Description |
| String | The excludedFields at the given index.
|
public ByteString getExcludedFieldsBytes(int index)
Fields that will be excluded in the prediction instance that is
sent to the Model.
Excluded will be attached to the batch prediction output if key_field
is not specified.
When excluded_fields is populated, included_fields must be empty.
The input must be JSONL with objects at each line, CSV, BigQuery
or TfRecord.
repeated string excluded_fields = 4;
| Name | Description |
| index | int
The index of the value to return.
|
Returns
| Type | Description |
| ByteString | The bytes of the excludedFields at the given index.
|
public int getExcludedFieldsCount()
Fields that will be excluded in the prediction instance that is
sent to the Model.
Excluded will be attached to the batch prediction output if key_field
is not specified.
When excluded_fields is populated, included_fields must be empty.
The input must be JSONL with objects at each line, CSV, BigQuery
or TfRecord.
repeated string excluded_fields = 4;
| Type | Description |
| int | The count of excludedFields.
|
public ProtocolStringList getExcludedFieldsList()
Fields that will be excluded in the prediction instance that is
sent to the Model.
Excluded will be attached to the batch prediction output if key_field
is not specified.
When excluded_fields is populated, included_fields must be empty.
The input must be JSONL with objects at each line, CSV, BigQuery
or TfRecord.
repeated string excluded_fields = 4;
public String getIncludedFields(int index)
Fields that will be included in the prediction instance that is
sent to the Model.
If instance_type is array, the order of field names in
included_fields also determines the order of the values in the array.
When included_fields is populated, excluded_fields must be empty.
The input must be JSONL with objects at each line, CSV, BigQuery
or TfRecord.
repeated string included_fields = 3;
| Name | Description |
| index | int
The index of the element to return.
|
Returns
| Type | Description |
| String | The includedFields at the given index.
|
public ByteString getIncludedFieldsBytes(int index)
Fields that will be included in the prediction instance that is
sent to the Model.
If instance_type is array, the order of field names in
included_fields also determines the order of the values in the array.
When included_fields is populated, excluded_fields must be empty.
The input must be JSONL with objects at each line, CSV, BigQuery
or TfRecord.
repeated string included_fields = 3;
| Name | Description |
| index | int
The index of the value to return.
|
Returns
| Type | Description |
| ByteString | The bytes of the includedFields at the given index.
|
public int getIncludedFieldsCount()
Fields that will be included in the prediction instance that is
sent to the Model.
If instance_type is array, the order of field names in
included_fields also determines the order of the values in the array.
When included_fields is populated, excluded_fields must be empty.
The input must be JSONL with objects at each line, CSV, BigQuery
or TfRecord.
repeated string included_fields = 3;
| Type | Description |
| int | The count of includedFields.
|
public ProtocolStringList getIncludedFieldsList()
Fields that will be included in the prediction instance that is
sent to the Model.
If instance_type is array, the order of field names in
included_fields also determines the order of the values in the array.
When included_fields is populated, excluded_fields must be empty.
The input must be JSONL with objects at each line, CSV, BigQuery
or TfRecord.
repeated string included_fields = 3;
public String getInstanceType()
The format of the instance that the Model accepts. Vertex AI will
convert compatible
batch prediction input instance formats
to the specified format.
Supported values are:
object: Each input is converted to JSON object format.
- For
bigquery, each row is converted to an object.
- For
jsonl, each line of the JSONL input must be an object.
- Does not apply to
csv, file-list, tf-record, or
tf-record-gzip.
array: Each input is converted to JSON array format.
- For
bigquery, each row is converted to an array. The order
of columns is determined by the BigQuery column order, unless
included_fields is populated.
included_fields must be populated for specifying field orders.
- For
jsonl, if each line of the JSONL input is an object,
included_fields must be populated for specifying field orders.
- Does not apply to
csv, file-list, tf-record, or
tf-record-gzip.
If not specified, Vertex AI converts the batch prediction input as
follows:
- For
bigquery and csv, the behavior is the same as array. The
order of columns is the same as defined in the file or table, unless
included_fields is populated.
- For
jsonl, the prediction instance format is determined by
each line of the input.
- For
tf-record/tf-record-gzip, each record will be converted to
an object in the format of {"b64": <value>}, where <value> is
the Base64-encoded string of the content of the record.
- For
file-list, each file in the list will be converted to an
object in the format of {"b64": <value>}, where <value> is
the Base64-encoded string of the content of the file.
string instance_type = 1;
| Type | Description |
| String | The instanceType.
|
public ByteString getInstanceTypeBytes()
The format of the instance that the Model accepts. Vertex AI will
convert compatible
batch prediction input instance formats
to the specified format.
Supported values are:
object: Each input is converted to JSON object format.
- For
bigquery, each row is converted to an object.
- For
jsonl, each line of the JSONL input must be an object.
- Does not apply to
csv, file-list, tf-record, or
tf-record-gzip.
array: Each input is converted to JSON array format.
- For
bigquery, each row is converted to an array. The order
of columns is determined by the BigQuery column order, unless
included_fields is populated.
included_fields must be populated for specifying field orders.
- For
jsonl, if each line of the JSONL input is an object,
included_fields must be populated for specifying field orders.
- Does not apply to
csv, file-list, tf-record, or
tf-record-gzip.
If not specified, Vertex AI converts the batch prediction input as
follows:
- For
bigquery and csv, the behavior is the same as array. The
order of columns is the same as defined in the file or table, unless
included_fields is populated.
- For
jsonl, the prediction instance format is determined by
each line of the input.
- For
tf-record/tf-record-gzip, each record will be converted to
an object in the format of {"b64": <value>}, where <value> is
the Base64-encoded string of the content of the record.
- For
file-list, each file in the list will be converted to an
object in the format of {"b64": <value>}, where <value> is
the Base64-encoded string of the content of the file.
string instance_type = 1;
| Type | Description |
| ByteString | The bytes for instanceType.
|
public String getKeyField()
The name of the field that is considered as a key.
The values identified by the key field is not included in the transformed
instances that is sent to the Model. This is similar to
specifying this name of the field in excluded_fields. In addition,
the batch prediction output will not include the instances. Instead the
output will only include the value of the key field, in a field named
key in the output:
- For
jsonl output format, the output will have a key field
instead of the instance field.
- For
csv/bigquery output format, the output will have have a key
column instead of the instance feature columns.
The input must be JSONL with objects at each line, CSV, BigQuery
or TfRecord.
string key_field = 2;
| Type | Description |
| String | The keyField.
|
public ByteString getKeyFieldBytes()
The name of the field that is considered as a key.
The values identified by the key field is not included in the transformed
instances that is sent to the Model. This is similar to
specifying this name of the field in excluded_fields. In addition,
the batch prediction output will not include the instances. Instead the
output will only include the value of the key field, in a field named
key in the output:
- For
jsonl output format, the output will have a key field
instead of the instance field.
- For
csv/bigquery output format, the output will have have a key
column instead of the instance feature columns.
The input must be JSONL with objects at each line, CSV, BigQuery
or TfRecord.
string key_field = 2;
public Parser<BatchPredictionJob.InstanceConfig> getParserForType()
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Overrides
public int getSerializedSize()
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Overrides
public final UnknownFieldSet getUnknownFields()
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protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
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public final boolean isInitialized()
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Overrides
public BatchPredictionJob.InstanceConfig.Builder newBuilderForType()
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protected BatchPredictionJob.InstanceConfig.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
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protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
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Overrides
public BatchPredictionJob.InstanceConfig.Builder toBuilder()
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public void writeTo(CodedOutputStream output)
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Overrides
Exceptions
