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public static final class EvaluationJobConfig.Builder extends GeneratedMessageV3.Builder<EvaluationJobConfig.Builder> implements EvaluationJobConfigOrBuilder
Configures specific details of how a continuous evaluation job works. Provide this configuration when you create an EvaluationJob.
Protobuf type google.cloud.datalabeling.v1beta1.EvaluationJobConfig
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > EvaluationJobConfig.BuilderImplements
EvaluationJobConfigOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Returns | |
---|---|
Type | Description |
Descriptor |
Methods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public EvaluationJobConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters | |
---|---|
Name | Description |
field | FieldDescriptor |
value | Object |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
build()
public EvaluationJobConfig build()
Returns | |
---|---|
Type | Description |
EvaluationJobConfig |
buildPartial()
public EvaluationJobConfig buildPartial()
Returns | |
---|---|
Type | Description |
EvaluationJobConfig |
clear()
public EvaluationJobConfig.Builder clear()
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
clearBigqueryImportKeys()
public EvaluationJobConfig.Builder clearBigqueryImportKeys()
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
clearBoundingPolyConfig()
public EvaluationJobConfig.Builder clearBoundingPolyConfig()
Specify this field if your model version performs image object detection (bounding box detection).
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
clearEvaluationConfig()
public EvaluationJobConfig.Builder clearEvaluationConfig()
Required. Details for calculating evaluation metrics and creating
Evaulations. If your model version performs image object
detection, you must specify the boundingBoxEvaluationOptions
field within
this configuration. Otherwise, provide an empty object for this
configuration.
.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
clearEvaluationJobAlertConfig()
public EvaluationJobConfig.Builder clearEvaluationJobAlertConfig()
Optional. Configuration details for evaluation job alerts. Specify this field if you want to receive email alerts if the evaluation job finds that your predictions have low mean average precision during a run.
.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
clearExampleCount()
public EvaluationJobConfig.Builder clearExampleCount()
Required. The maximum number of predictions to sample and save to BigQuery
during each evaluation interval. This limit
overrides example_sample_percentage
: even if the service has not sampled
enough predictions to fulfill example_sample_perecentage
during an
interval, it stops sampling predictions when it meets this limit.
int32 example_count = 10;
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder | This builder for chaining. |
clearExampleSamplePercentage()
public EvaluationJobConfig.Builder clearExampleSamplePercentage()
Required. Fraction of predictions to sample and save to BigQuery during each evaluation interval. For example, 0.1 means 10% of predictions served by your model version get saved to BigQuery.
double example_sample_percentage = 11;
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder | This builder for chaining. |
clearField(Descriptors.FieldDescriptor field)
public EvaluationJobConfig.Builder clearField(Descriptors.FieldDescriptor field)
Parameter | |
---|---|
Name | Description |
field | FieldDescriptor |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
clearHumanAnnotationConfig()
public EvaluationJobConfig.Builder clearHumanAnnotationConfig()
Optional. Details for human annotation of your data. If you set
labelMissingGroundTruth to
true
for this evaluation job, then you must specify this field. If you
plan to provide your own ground truth labels, then omit this field.
Note that you must create an Instruction resource before you can
specify this field. Provide the name of the instruction resource in the
instruction
field within this configuration.
.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
clearHumanAnnotationRequestConfig()
public EvaluationJobConfig.Builder clearHumanAnnotationRequestConfig()
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
clearImageClassificationConfig()
public EvaluationJobConfig.Builder clearImageClassificationConfig()
Specify this field if your model version performs image classification or general classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
clearInputConfig()
public EvaluationJobConfig.Builder clearInputConfig()
Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:
dataType
must be one ofIMAGE
,TEXT
, orGENERAL_DATA
.annotationType
must be one ofIMAGE_CLASSIFICATION_ANNOTATION
,TEXT_CLASSIFICATION_ANNOTATION
,GENERAL_CLASSIFICATION_ANNOTATION
, orIMAGE_BOUNDING_BOX_ANNOTATION
(image object detection).- If your machine learning model performs classification, you must specify
classificationMetadata.isMultiLabel
. - You must specify
bigquerySource
(notgcsSource
).
.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
clearOneof(Descriptors.OneofDescriptor oneof)
public EvaluationJobConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter | |
---|---|
Name | Description |
oneof | OneofDescriptor |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
clearTextClassificationConfig()
public EvaluationJobConfig.Builder clearTextClassificationConfig()
Specify this field if your model version performs text classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
clone()
public EvaluationJobConfig.Builder clone()
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
containsBigqueryImportKeys(String key)
public boolean containsBigqueryImportKeys(String key)
Required. Prediction keys that tell Data Labeling Service where to find the data for evaluation in your BigQuery table. When the service samples prediction input and output from your model version and saves it to BigQuery, the data gets stored as JSON strings in the BigQuery table. These keys tell Data Labeling Service how to parse the JSON.
You can provide the following entries in this field:
data_json_key
: the data key for prediction input. You must provide either this key orreference_json_key
.reference_json_key
: the data reference key for prediction input. You must provide either this key ordata_json_key
.label_json_key
: the label key for prediction output. Required.label_score_json_key
: the score key for prediction output. Required.bounding_box_json_key
: the bounding box key for prediction output. Required if your model version perform image object detection.
map<string, string> bigquery_import_keys = 9;
Parameter | |
---|---|
Name | Description |
key | String |
Returns | |
---|---|
Type | Description |
boolean |
getBigqueryImportKeys()
public Map<String,String> getBigqueryImportKeys()
Use #getBigqueryImportKeysMap() instead.
Returns | |
---|---|
Type | Description |
Map<String,String> |
getBigqueryImportKeysCount()
public int getBigqueryImportKeysCount()
Required. Prediction keys that tell Data Labeling Service where to find the data for evaluation in your BigQuery table. When the service samples prediction input and output from your model version and saves it to BigQuery, the data gets stored as JSON strings in the BigQuery table. These keys tell Data Labeling Service how to parse the JSON.
You can provide the following entries in this field:
data_json_key
: the data key for prediction input. You must provide either this key orreference_json_key
.reference_json_key
: the data reference key for prediction input. You must provide either this key ordata_json_key
.label_json_key
: the label key for prediction output. Required.label_score_json_key
: the score key for prediction output. Required.bounding_box_json_key
: the bounding box key for prediction output. Required if your model version perform image object detection.
map<string, string> bigquery_import_keys = 9;
Returns | |
---|---|
Type | Description |
int |
getBigqueryImportKeysMap()
public Map<String,String> getBigqueryImportKeysMap()
Required. Prediction keys that tell Data Labeling Service where to find the data for evaluation in your BigQuery table. When the service samples prediction input and output from your model version and saves it to BigQuery, the data gets stored as JSON strings in the BigQuery table. These keys tell Data Labeling Service how to parse the JSON.
You can provide the following entries in this field:
data_json_key
: the data key for prediction input. You must provide either this key orreference_json_key
.reference_json_key
: the data reference key for prediction input. You must provide either this key ordata_json_key
.label_json_key
: the label key for prediction output. Required.label_score_json_key
: the score key for prediction output. Required.bounding_box_json_key
: the bounding box key for prediction output. Required if your model version perform image object detection.
map<string, string> bigquery_import_keys = 9;
Returns | |
---|---|
Type | Description |
Map<String,String> |
getBigqueryImportKeysOrDefault(String key, String defaultValue)
public String getBigqueryImportKeysOrDefault(String key, String defaultValue)
Required. Prediction keys that tell Data Labeling Service where to find the data for evaluation in your BigQuery table. When the service samples prediction input and output from your model version and saves it to BigQuery, the data gets stored as JSON strings in the BigQuery table. These keys tell Data Labeling Service how to parse the JSON.
You can provide the following entries in this field:
data_json_key
: the data key for prediction input. You must provide either this key orreference_json_key
.reference_json_key
: the data reference key for prediction input. You must provide either this key ordata_json_key
.label_json_key
: the label key for prediction output. Required.label_score_json_key
: the score key for prediction output. Required.bounding_box_json_key
: the bounding box key for prediction output. Required if your model version perform image object detection.
map<string, string> bigquery_import_keys = 9;
Parameters | |
---|---|
Name | Description |
key | String |
defaultValue | String |
Returns | |
---|---|
Type | Description |
String |
getBigqueryImportKeysOrThrow(String key)
public String getBigqueryImportKeysOrThrow(String key)
Required. Prediction keys that tell Data Labeling Service where to find the data for evaluation in your BigQuery table. When the service samples prediction input and output from your model version and saves it to BigQuery, the data gets stored as JSON strings in the BigQuery table. These keys tell Data Labeling Service how to parse the JSON.
You can provide the following entries in this field:
data_json_key
: the data key for prediction input. You must provide either this key orreference_json_key
.reference_json_key
: the data reference key for prediction input. You must provide either this key ordata_json_key
.label_json_key
: the label key for prediction output. Required.label_score_json_key
: the score key for prediction output. Required.bounding_box_json_key
: the bounding box key for prediction output. Required if your model version perform image object detection.
map<string, string> bigquery_import_keys = 9;
Parameter | |
---|---|
Name | Description |
key | String |
Returns | |
---|---|
Type | Description |
String |
getBoundingPolyConfig()
public BoundingPolyConfig getBoundingPolyConfig()
Specify this field if your model version performs image object detection (bounding box detection).
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;
Returns | |
---|---|
Type | Description |
BoundingPolyConfig | The boundingPolyConfig. |
getBoundingPolyConfigBuilder()
public BoundingPolyConfig.Builder getBoundingPolyConfigBuilder()
Specify this field if your model version performs image object detection (bounding box detection).
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;
Returns | |
---|---|
Type | Description |
BoundingPolyConfig.Builder |
getBoundingPolyConfigOrBuilder()
public BoundingPolyConfigOrBuilder getBoundingPolyConfigOrBuilder()
Specify this field if your model version performs image object detection (bounding box detection).
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;
Returns | |
---|---|
Type | Description |
BoundingPolyConfigOrBuilder |
getDefaultInstanceForType()
public EvaluationJobConfig getDefaultInstanceForType()
Returns | |
---|---|
Type | Description |
EvaluationJobConfig |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Returns | |
---|---|
Type | Description |
Descriptor |
getEvaluationConfig()
public EvaluationConfig getEvaluationConfig()
Required. Details for calculating evaluation metrics and creating
Evaulations. If your model version performs image object
detection, you must specify the boundingBoxEvaluationOptions
field within
this configuration. Otherwise, provide an empty object for this
configuration.
.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;
Returns | |
---|---|
Type | Description |
EvaluationConfig | The evaluationConfig. |
getEvaluationConfigBuilder()
public EvaluationConfig.Builder getEvaluationConfigBuilder()
Required. Details for calculating evaluation metrics and creating
Evaulations. If your model version performs image object
detection, you must specify the boundingBoxEvaluationOptions
field within
this configuration. Otherwise, provide an empty object for this
configuration.
.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;
Returns | |
---|---|
Type | Description |
EvaluationConfig.Builder |
getEvaluationConfigOrBuilder()
public EvaluationConfigOrBuilder getEvaluationConfigOrBuilder()
Required. Details for calculating evaluation metrics and creating
Evaulations. If your model version performs image object
detection, you must specify the boundingBoxEvaluationOptions
field within
this configuration. Otherwise, provide an empty object for this
configuration.
.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;
Returns | |
---|---|
Type | Description |
EvaluationConfigOrBuilder |
getEvaluationJobAlertConfig()
public EvaluationJobAlertConfig getEvaluationJobAlertConfig()
Optional. Configuration details for evaluation job alerts. Specify this field if you want to receive email alerts if the evaluation job finds that your predictions have low mean average precision during a run.
.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
Returns | |
---|---|
Type | Description |
EvaluationJobAlertConfig | The evaluationJobAlertConfig. |
getEvaluationJobAlertConfigBuilder()
public EvaluationJobAlertConfig.Builder getEvaluationJobAlertConfigBuilder()
Optional. Configuration details for evaluation job alerts. Specify this field if you want to receive email alerts if the evaluation job finds that your predictions have low mean average precision during a run.
.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
Returns | |
---|---|
Type | Description |
EvaluationJobAlertConfig.Builder |
getEvaluationJobAlertConfigOrBuilder()
public EvaluationJobAlertConfigOrBuilder getEvaluationJobAlertConfigOrBuilder()
Optional. Configuration details for evaluation job alerts. Specify this field if you want to receive email alerts if the evaluation job finds that your predictions have low mean average precision during a run.
.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
Returns | |
---|---|
Type | Description |
EvaluationJobAlertConfigOrBuilder |
getExampleCount()
public int getExampleCount()
Required. The maximum number of predictions to sample and save to BigQuery
during each evaluation interval. This limit
overrides example_sample_percentage
: even if the service has not sampled
enough predictions to fulfill example_sample_perecentage
during an
interval, it stops sampling predictions when it meets this limit.
int32 example_count = 10;
Returns | |
---|---|
Type | Description |
int | The exampleCount. |
getExampleSamplePercentage()
public double getExampleSamplePercentage()
Required. Fraction of predictions to sample and save to BigQuery during each evaluation interval. For example, 0.1 means 10% of predictions served by your model version get saved to BigQuery.
double example_sample_percentage = 11;
Returns | |
---|---|
Type | Description |
double | The exampleSamplePercentage. |
getHumanAnnotationConfig()
public HumanAnnotationConfig getHumanAnnotationConfig()
Optional. Details for human annotation of your data. If you set
labelMissingGroundTruth to
true
for this evaluation job, then you must specify this field. If you
plan to provide your own ground truth labels, then omit this field.
Note that you must create an Instruction resource before you can
specify this field. Provide the name of the instruction resource in the
instruction
field within this configuration.
.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
Returns | |
---|---|
Type | Description |
HumanAnnotationConfig | The humanAnnotationConfig. |
getHumanAnnotationConfigBuilder()
public HumanAnnotationConfig.Builder getHumanAnnotationConfigBuilder()
Optional. Details for human annotation of your data. If you set
labelMissingGroundTruth to
true
for this evaluation job, then you must specify this field. If you
plan to provide your own ground truth labels, then omit this field.
Note that you must create an Instruction resource before you can
specify this field. Provide the name of the instruction resource in the
instruction
field within this configuration.
.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
Returns | |
---|---|
Type | Description |
HumanAnnotationConfig.Builder |
getHumanAnnotationConfigOrBuilder()
public HumanAnnotationConfigOrBuilder getHumanAnnotationConfigOrBuilder()
Optional. Details for human annotation of your data. If you set
labelMissingGroundTruth to
true
for this evaluation job, then you must specify this field. If you
plan to provide your own ground truth labels, then omit this field.
Note that you must create an Instruction resource before you can
specify this field. Provide the name of the instruction resource in the
instruction
field within this configuration.
.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
Returns | |
---|---|
Type | Description |
HumanAnnotationConfigOrBuilder |
getHumanAnnotationRequestConfigCase()
public EvaluationJobConfig.HumanAnnotationRequestConfigCase getHumanAnnotationRequestConfigCase()
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.HumanAnnotationRequestConfigCase |
getImageClassificationConfig()
public ImageClassificationConfig getImageClassificationConfig()
Specify this field if your model version performs image classification or general classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
Returns | |
---|---|
Type | Description |
ImageClassificationConfig | The imageClassificationConfig. |
getImageClassificationConfigBuilder()
public ImageClassificationConfig.Builder getImageClassificationConfigBuilder()
Specify this field if your model version performs image classification or general classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
Returns | |
---|---|
Type | Description |
ImageClassificationConfig.Builder |
getImageClassificationConfigOrBuilder()
public ImageClassificationConfigOrBuilder getImageClassificationConfigOrBuilder()
Specify this field if your model version performs image classification or general classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
Returns | |
---|---|
Type | Description |
ImageClassificationConfigOrBuilder |
getInputConfig()
public InputConfig getInputConfig()
Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:
dataType
must be one ofIMAGE
,TEXT
, orGENERAL_DATA
.annotationType
must be one ofIMAGE_CLASSIFICATION_ANNOTATION
,TEXT_CLASSIFICATION_ANNOTATION
,GENERAL_CLASSIFICATION_ANNOTATION
, orIMAGE_BOUNDING_BOX_ANNOTATION
(image object detection).- If your machine learning model performs classification, you must specify
classificationMetadata.isMultiLabel
. - You must specify
bigquerySource
(notgcsSource
).
.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;
Returns | |
---|---|
Type | Description |
InputConfig | The inputConfig. |
getInputConfigBuilder()
public InputConfig.Builder getInputConfigBuilder()
Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:
dataType
must be one ofIMAGE
,TEXT
, orGENERAL_DATA
.annotationType
must be one ofIMAGE_CLASSIFICATION_ANNOTATION
,TEXT_CLASSIFICATION_ANNOTATION
,GENERAL_CLASSIFICATION_ANNOTATION
, orIMAGE_BOUNDING_BOX_ANNOTATION
(image object detection).- If your machine learning model performs classification, you must specify
classificationMetadata.isMultiLabel
. - You must specify
bigquerySource
(notgcsSource
).
.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;
Returns | |
---|---|
Type | Description |
InputConfig.Builder |
getInputConfigOrBuilder()
public InputConfigOrBuilder getInputConfigOrBuilder()
Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:
dataType
must be one ofIMAGE
,TEXT
, orGENERAL_DATA
.annotationType
must be one ofIMAGE_CLASSIFICATION_ANNOTATION
,TEXT_CLASSIFICATION_ANNOTATION
,GENERAL_CLASSIFICATION_ANNOTATION
, orIMAGE_BOUNDING_BOX_ANNOTATION
(image object detection).- If your machine learning model performs classification, you must specify
classificationMetadata.isMultiLabel
. - You must specify
bigquerySource
(notgcsSource
).
.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;
Returns | |
---|---|
Type | Description |
InputConfigOrBuilder |
getMutableBigqueryImportKeys()
public Map<String,String> getMutableBigqueryImportKeys()
Use alternate mutation accessors instead.
Returns | |
---|---|
Type | Description |
Map<String,String> |
getTextClassificationConfig()
public TextClassificationConfig getTextClassificationConfig()
Specify this field if your model version performs text classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
Returns | |
---|---|
Type | Description |
TextClassificationConfig | The textClassificationConfig. |
getTextClassificationConfigBuilder()
public TextClassificationConfig.Builder getTextClassificationConfigBuilder()
Specify this field if your model version performs text classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
Returns | |
---|---|
Type | Description |
TextClassificationConfig.Builder |
getTextClassificationConfigOrBuilder()
public TextClassificationConfigOrBuilder getTextClassificationConfigOrBuilder()
Specify this field if your model version performs text classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
Returns | |
---|---|
Type | Description |
TextClassificationConfigOrBuilder |
hasBoundingPolyConfig()
public boolean hasBoundingPolyConfig()
Specify this field if your model version performs image object detection (bounding box detection).
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;
Returns | |
---|---|
Type | Description |
boolean | Whether the boundingPolyConfig field is set. |
hasEvaluationConfig()
public boolean hasEvaluationConfig()
Required. Details for calculating evaluation metrics and creating
Evaulations. If your model version performs image object
detection, you must specify the boundingBoxEvaluationOptions
field within
this configuration. Otherwise, provide an empty object for this
configuration.
.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;
Returns | |
---|---|
Type | Description |
boolean | Whether the evaluationConfig field is set. |
hasEvaluationJobAlertConfig()
public boolean hasEvaluationJobAlertConfig()
Optional. Configuration details for evaluation job alerts. Specify this field if you want to receive email alerts if the evaluation job finds that your predictions have low mean average precision during a run.
.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
Returns | |
---|---|
Type | Description |
boolean | Whether the evaluationJobAlertConfig field is set. |
hasHumanAnnotationConfig()
public boolean hasHumanAnnotationConfig()
Optional. Details for human annotation of your data. If you set
labelMissingGroundTruth to
true
for this evaluation job, then you must specify this field. If you
plan to provide your own ground truth labels, then omit this field.
Note that you must create an Instruction resource before you can
specify this field. Provide the name of the instruction resource in the
instruction
field within this configuration.
.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
Returns | |
---|---|
Type | Description |
boolean | Whether the humanAnnotationConfig field is set. |
hasImageClassificationConfig()
public boolean hasImageClassificationConfig()
Specify this field if your model version performs image classification or general classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
Returns | |
---|---|
Type | Description |
boolean | Whether the imageClassificationConfig field is set. |
hasInputConfig()
public boolean hasInputConfig()
Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:
dataType
must be one ofIMAGE
,TEXT
, orGENERAL_DATA
.annotationType
must be one ofIMAGE_CLASSIFICATION_ANNOTATION
,TEXT_CLASSIFICATION_ANNOTATION
,GENERAL_CLASSIFICATION_ANNOTATION
, orIMAGE_BOUNDING_BOX_ANNOTATION
(image object detection).- If your machine learning model performs classification, you must specify
classificationMetadata.isMultiLabel
. - You must specify
bigquerySource
(notgcsSource
).
.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;
Returns | |
---|---|
Type | Description |
boolean | Whether the inputConfig field is set. |
hasTextClassificationConfig()
public boolean hasTextClassificationConfig()
Specify this field if your model version performs text classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
Returns | |
---|---|
Type | Description |
boolean | Whether the textClassificationConfig field is set. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns | |
---|---|
Type | Description |
FieldAccessorTable |
internalGetMapField(int number)
protected MapField internalGetMapField(int number)
Parameter | |
---|---|
Name | Description |
number | int |
Returns | |
---|---|
Type | Description |
MapField |
internalGetMutableMapField(int number)
protected MapField internalGetMutableMapField(int number)
Parameter | |
---|---|
Name | Description |
number | int |
Returns | |
---|---|
Type | Description |
MapField |
isInitialized()
public final boolean isInitialized()
Returns | |
---|---|
Type | Description |
boolean |
mergeBoundingPolyConfig(BoundingPolyConfig value)
public EvaluationJobConfig.Builder mergeBoundingPolyConfig(BoundingPolyConfig value)
Specify this field if your model version performs image object detection (bounding box detection).
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;
Parameter | |
---|---|
Name | Description |
value | BoundingPolyConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
mergeEvaluationConfig(EvaluationConfig value)
public EvaluationJobConfig.Builder mergeEvaluationConfig(EvaluationConfig value)
Required. Details for calculating evaluation metrics and creating
Evaulations. If your model version performs image object
detection, you must specify the boundingBoxEvaluationOptions
field within
this configuration. Otherwise, provide an empty object for this
configuration.
.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;
Parameter | |
---|---|
Name | Description |
value | EvaluationConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
mergeEvaluationJobAlertConfig(EvaluationJobAlertConfig value)
public EvaluationJobConfig.Builder mergeEvaluationJobAlertConfig(EvaluationJobAlertConfig value)
Optional. Configuration details for evaluation job alerts. Specify this field if you want to receive email alerts if the evaluation job finds that your predictions have low mean average precision during a run.
.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
Parameter | |
---|---|
Name | Description |
value | EvaluationJobAlertConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
mergeFrom(EvaluationJobConfig other)
public EvaluationJobConfig.Builder mergeFrom(EvaluationJobConfig other)
Parameter | |
---|---|
Name | Description |
other | EvaluationJobConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public EvaluationJobConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters | |
---|---|
Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
Exceptions | |
---|---|
Type | Description |
IOException |
mergeFrom(Message other)
public EvaluationJobConfig.Builder mergeFrom(Message other)
Parameter | |
---|---|
Name | Description |
other | Message |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
mergeHumanAnnotationConfig(HumanAnnotationConfig value)
public EvaluationJobConfig.Builder mergeHumanAnnotationConfig(HumanAnnotationConfig value)
Optional. Details for human annotation of your data. If you set
labelMissingGroundTruth to
true
for this evaluation job, then you must specify this field. If you
plan to provide your own ground truth labels, then omit this field.
Note that you must create an Instruction resource before you can
specify this field. Provide the name of the instruction resource in the
instruction
field within this configuration.
.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
Parameter | |
---|---|
Name | Description |
value | HumanAnnotationConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
mergeImageClassificationConfig(ImageClassificationConfig value)
public EvaluationJobConfig.Builder mergeImageClassificationConfig(ImageClassificationConfig value)
Specify this field if your model version performs image classification or general classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
Parameter | |
---|---|
Name | Description |
value | ImageClassificationConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
mergeInputConfig(InputConfig value)
public EvaluationJobConfig.Builder mergeInputConfig(InputConfig value)
Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:
dataType
must be one ofIMAGE
,TEXT
, orGENERAL_DATA
.annotationType
must be one ofIMAGE_CLASSIFICATION_ANNOTATION
,TEXT_CLASSIFICATION_ANNOTATION
,GENERAL_CLASSIFICATION_ANNOTATION
, orIMAGE_BOUNDING_BOX_ANNOTATION
(image object detection).- If your machine learning model performs classification, you must specify
classificationMetadata.isMultiLabel
. - You must specify
bigquerySource
(notgcsSource
).
.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;
Parameter | |
---|---|
Name | Description |
value | InputConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
mergeTextClassificationConfig(TextClassificationConfig value)
public EvaluationJobConfig.Builder mergeTextClassificationConfig(TextClassificationConfig value)
Specify this field if your model version performs text classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
Parameter | |
---|---|
Name | Description |
value | TextClassificationConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final EvaluationJobConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter | |
---|---|
Name | Description |
unknownFields | UnknownFieldSet |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
putAllBigqueryImportKeys(Map<String,String> values)
public EvaluationJobConfig.Builder putAllBigqueryImportKeys(Map<String,String> values)
Required. Prediction keys that tell Data Labeling Service where to find the data for evaluation in your BigQuery table. When the service samples prediction input and output from your model version and saves it to BigQuery, the data gets stored as JSON strings in the BigQuery table. These keys tell Data Labeling Service how to parse the JSON.
You can provide the following entries in this field:
data_json_key
: the data key for prediction input. You must provide either this key orreference_json_key
.reference_json_key
: the data reference key for prediction input. You must provide either this key ordata_json_key
.label_json_key
: the label key for prediction output. Required.label_score_json_key
: the score key for prediction output. Required.bounding_box_json_key
: the bounding box key for prediction output. Required if your model version perform image object detection.
map<string, string> bigquery_import_keys = 9;
Parameter | |
---|---|
Name | Description |
values | Map<String,String> |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
putBigqueryImportKeys(String key, String value)
public EvaluationJobConfig.Builder putBigqueryImportKeys(String key, String value)
Required. Prediction keys that tell Data Labeling Service where to find the data for evaluation in your BigQuery table. When the service samples prediction input and output from your model version and saves it to BigQuery, the data gets stored as JSON strings in the BigQuery table. These keys tell Data Labeling Service how to parse the JSON.
You can provide the following entries in this field:
data_json_key
: the data key for prediction input. You must provide either this key orreference_json_key
.reference_json_key
: the data reference key for prediction input. You must provide either this key ordata_json_key
.label_json_key
: the label key for prediction output. Required.label_score_json_key
: the score key for prediction output. Required.bounding_box_json_key
: the bounding box key for prediction output. Required if your model version perform image object detection.
map<string, string> bigquery_import_keys = 9;
Parameters | |
---|---|
Name | Description |
key | String |
value | String |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
removeBigqueryImportKeys(String key)
public EvaluationJobConfig.Builder removeBigqueryImportKeys(String key)
Required. Prediction keys that tell Data Labeling Service where to find the data for evaluation in your BigQuery table. When the service samples prediction input and output from your model version and saves it to BigQuery, the data gets stored as JSON strings in the BigQuery table. These keys tell Data Labeling Service how to parse the JSON.
You can provide the following entries in this field:
data_json_key
: the data key for prediction input. You must provide either this key orreference_json_key
.reference_json_key
: the data reference key for prediction input. You must provide either this key ordata_json_key
.label_json_key
: the label key for prediction output. Required.label_score_json_key
: the score key for prediction output. Required.bounding_box_json_key
: the bounding box key for prediction output. Required if your model version perform image object detection.
map<string, string> bigquery_import_keys = 9;
Parameter | |
---|---|
Name | Description |
key | String |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setBoundingPolyConfig(BoundingPolyConfig value)
public EvaluationJobConfig.Builder setBoundingPolyConfig(BoundingPolyConfig value)
Specify this field if your model version performs image object detection (bounding box detection).
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;
Parameter | |
---|---|
Name | Description |
value | BoundingPolyConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setBoundingPolyConfig(BoundingPolyConfig.Builder builderForValue)
public EvaluationJobConfig.Builder setBoundingPolyConfig(BoundingPolyConfig.Builder builderForValue)
Specify this field if your model version performs image object detection (bounding box detection).
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
.google.cloud.datalabeling.v1beta1.BoundingPolyConfig bounding_poly_config = 5;
Parameter | |
---|---|
Name | Description |
builderForValue | BoundingPolyConfig.Builder |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setEvaluationConfig(EvaluationConfig value)
public EvaluationJobConfig.Builder setEvaluationConfig(EvaluationConfig value)
Required. Details for calculating evaluation metrics and creating
Evaulations. If your model version performs image object
detection, you must specify the boundingBoxEvaluationOptions
field within
this configuration. Otherwise, provide an empty object for this
configuration.
.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;
Parameter | |
---|---|
Name | Description |
value | EvaluationConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setEvaluationConfig(EvaluationConfig.Builder builderForValue)
public EvaluationJobConfig.Builder setEvaluationConfig(EvaluationConfig.Builder builderForValue)
Required. Details for calculating evaluation metrics and creating
Evaulations. If your model version performs image object
detection, you must specify the boundingBoxEvaluationOptions
field within
this configuration. Otherwise, provide an empty object for this
configuration.
.google.cloud.datalabeling.v1beta1.EvaluationConfig evaluation_config = 2;
Parameter | |
---|---|
Name | Description |
builderForValue | EvaluationConfig.Builder |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setEvaluationJobAlertConfig(EvaluationJobAlertConfig value)
public EvaluationJobConfig.Builder setEvaluationJobAlertConfig(EvaluationJobAlertConfig value)
Optional. Configuration details for evaluation job alerts. Specify this field if you want to receive email alerts if the evaluation job finds that your predictions have low mean average precision during a run.
.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
Parameter | |
---|---|
Name | Description |
value | EvaluationJobAlertConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setEvaluationJobAlertConfig(EvaluationJobAlertConfig.Builder builderForValue)
public EvaluationJobConfig.Builder setEvaluationJobAlertConfig(EvaluationJobAlertConfig.Builder builderForValue)
Optional. Configuration details for evaluation job alerts. Specify this field if you want to receive email alerts if the evaluation job finds that your predictions have low mean average precision during a run.
.google.cloud.datalabeling.v1beta1.EvaluationJobAlertConfig evaluation_job_alert_config = 13;
Parameter | |
---|---|
Name | Description |
builderForValue | EvaluationJobAlertConfig.Builder |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setExampleCount(int value)
public EvaluationJobConfig.Builder setExampleCount(int value)
Required. The maximum number of predictions to sample and save to BigQuery
during each evaluation interval. This limit
overrides example_sample_percentage
: even if the service has not sampled
enough predictions to fulfill example_sample_perecentage
during an
interval, it stops sampling predictions when it meets this limit.
int32 example_count = 10;
Parameter | |
---|---|
Name | Description |
value | int The exampleCount to set. |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder | This builder for chaining. |
setExampleSamplePercentage(double value)
public EvaluationJobConfig.Builder setExampleSamplePercentage(double value)
Required. Fraction of predictions to sample and save to BigQuery during each evaluation interval. For example, 0.1 means 10% of predictions served by your model version get saved to BigQuery.
double example_sample_percentage = 11;
Parameter | |
---|---|
Name | Description |
value | double The exampleSamplePercentage to set. |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder | This builder for chaining. |
setField(Descriptors.FieldDescriptor field, Object value)
public EvaluationJobConfig.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters | |
---|---|
Name | Description |
field | FieldDescriptor |
value | Object |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setHumanAnnotationConfig(HumanAnnotationConfig value)
public EvaluationJobConfig.Builder setHumanAnnotationConfig(HumanAnnotationConfig value)
Optional. Details for human annotation of your data. If you set
labelMissingGroundTruth to
true
for this evaluation job, then you must specify this field. If you
plan to provide your own ground truth labels, then omit this field.
Note that you must create an Instruction resource before you can
specify this field. Provide the name of the instruction resource in the
instruction
field within this configuration.
.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
Parameter | |
---|---|
Name | Description |
value | HumanAnnotationConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setHumanAnnotationConfig(HumanAnnotationConfig.Builder builderForValue)
public EvaluationJobConfig.Builder setHumanAnnotationConfig(HumanAnnotationConfig.Builder builderForValue)
Optional. Details for human annotation of your data. If you set
labelMissingGroundTruth to
true
for this evaluation job, then you must specify this field. If you
plan to provide your own ground truth labels, then omit this field.
Note that you must create an Instruction resource before you can
specify this field. Provide the name of the instruction resource in the
instruction
field within this configuration.
.google.cloud.datalabeling.v1beta1.HumanAnnotationConfig human_annotation_config = 3;
Parameter | |
---|---|
Name | Description |
builderForValue | HumanAnnotationConfig.Builder |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setImageClassificationConfig(ImageClassificationConfig value)
public EvaluationJobConfig.Builder setImageClassificationConfig(ImageClassificationConfig value)
Specify this field if your model version performs image classification or general classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
Parameter | |
---|---|
Name | Description |
value | ImageClassificationConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setImageClassificationConfig(ImageClassificationConfig.Builder builderForValue)
public EvaluationJobConfig.Builder setImageClassificationConfig(ImageClassificationConfig.Builder builderForValue)
Specify this field if your model version performs image classification or general classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.ImageClassificationConfig image_classification_config = 4;
Parameter | |
---|---|
Name | Description |
builderForValue | ImageClassificationConfig.Builder |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setInputConfig(InputConfig value)
public EvaluationJobConfig.Builder setInputConfig(InputConfig value)
Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:
dataType
must be one ofIMAGE
,TEXT
, orGENERAL_DATA
.annotationType
must be one ofIMAGE_CLASSIFICATION_ANNOTATION
,TEXT_CLASSIFICATION_ANNOTATION
,GENERAL_CLASSIFICATION_ANNOTATION
, orIMAGE_BOUNDING_BOX_ANNOTATION
(image object detection).- If your machine learning model performs classification, you must specify
classificationMetadata.isMultiLabel
. - You must specify
bigquerySource
(notgcsSource
).
.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;
Parameter | |
---|---|
Name | Description |
value | InputConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setInputConfig(InputConfig.Builder builderForValue)
public EvaluationJobConfig.Builder setInputConfig(InputConfig.Builder builderForValue)
Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:
dataType
must be one ofIMAGE
,TEXT
, orGENERAL_DATA
.annotationType
must be one ofIMAGE_CLASSIFICATION_ANNOTATION
,TEXT_CLASSIFICATION_ANNOTATION
,GENERAL_CLASSIFICATION_ANNOTATION
, orIMAGE_BOUNDING_BOX_ANNOTATION
(image object detection).- If your machine learning model performs classification, you must specify
classificationMetadata.isMultiLabel
. - You must specify
bigquerySource
(notgcsSource
).
.google.cloud.datalabeling.v1beta1.InputConfig input_config = 1;
Parameter | |
---|---|
Name | Description |
builderForValue | InputConfig.Builder |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public EvaluationJobConfig.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters | |
---|---|
Name | Description |
field | FieldDescriptor |
index | int |
value | Object |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setTextClassificationConfig(TextClassificationConfig value)
public EvaluationJobConfig.Builder setTextClassificationConfig(TextClassificationConfig value)
Specify this field if your model version performs text classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
Parameter | |
---|---|
Name | Description |
value | TextClassificationConfig |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setTextClassificationConfig(TextClassificationConfig.Builder builderForValue)
public EvaluationJobConfig.Builder setTextClassificationConfig(TextClassificationConfig.Builder builderForValue)
Specify this field if your model version performs text classification.
annotationSpecSet
in this configuration must match
EvaluationJob.annotationSpecSet.
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in input_config.
.google.cloud.datalabeling.v1beta1.TextClassificationConfig text_classification_config = 8;
Parameter | |
---|---|
Name | Description |
builderForValue | TextClassificationConfig.Builder |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |
setUnknownFields(UnknownFieldSet unknownFields)
public final EvaluationJobConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter | |
---|---|
Name | Description |
unknownFields | UnknownFieldSet |
Returns | |
---|---|
Type | Description |
EvaluationJobConfig.Builder |