public sealed class EvaluationJobConfig : IMessage<EvaluationJobConfig>, IEquatable<EvaluationJobConfig>, IDeepCloneable<EvaluationJobConfig>, IBufferMessage, IMessage
Configures specific details of how a continuous evaluation job works. Provide this configuration when you create an EvaluationJob.
Implements
IMessage<EvaluationJobConfig>, IEquatable<EvaluationJobConfig>, IDeepCloneable<EvaluationJobConfig>, IBufferMessage, IMessageNamespace
Google.Cloud.DataLabeling.V1Beta1Assembly
Google.Cloud.DataLabeling.V1Beta1.dll
Constructors
EvaluationJobConfig()
public EvaluationJobConfig()
EvaluationJobConfig(EvaluationJobConfig)
public EvaluationJobConfig(EvaluationJobConfig other)
Parameter | |
---|---|
Name | Description |
other | EvaluationJobConfig |
Properties
BigqueryImportKeys
public MapField<string, string> BigqueryImportKeys { get; }
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.
Property Value | |
---|---|
Type | Description |
MapField<String, String> |
BoundingPolyConfig
public BoundingPolyConfig BoundingPolyConfig { get; set; }
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.EvaluationJob.annotation_spec_set].
Property Value | |
---|---|
Type | Description |
BoundingPolyConfig |
EvaluationConfig
public EvaluationConfig EvaluationConfig { get; set; }
Required. Details for calculating evaluation metrics and creating
[Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. 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.
Property Value | |
---|---|
Type | Description |
EvaluationConfig |
EvaluationJobAlertConfig
public EvaluationJobAlertConfig EvaluationJobAlertConfig { get; set; }
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.
Property Value | |
---|---|
Type | Description |
EvaluationJobAlertConfig |
ExampleCount
public int ExampleCount { get; set; }
Required. The maximum number of predictions to sample and save to BigQuery
during each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. 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.
Property Value | |
---|---|
Type | Description |
Int32 |
ExampleSamplePercentage
public double ExampleSamplePercentage { get; set; }
Required. Fraction of predictions to sample and save to BigQuery during each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. For example, 0.1 means 10% of predictions served by your model version get saved to BigQuery.
Property Value | |
---|---|
Type | Description |
Double |
HumanAnnotationConfig
public HumanAnnotationConfig HumanAnnotationConfig { get; set; }
Optional. Details for human annotation of your data. If you set
[labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] 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][google.cloud.datalabeling.v1beta1.Instruction] resource before you can
specify this field. Provide the name of the instruction resource in the
instruction
field within this configuration.
Property Value | |
---|---|
Type | Description |
HumanAnnotationConfig |
HumanAnnotationRequestConfigCase
public EvaluationJobConfig.HumanAnnotationRequestConfigOneofCase HumanAnnotationRequestConfigCase { get; }
Property Value | |
---|---|
Type | Description |
EvaluationJobConfig.HumanAnnotationRequestConfigOneofCase |
ImageClassificationConfig
public ImageClassificationConfig ImageClassificationConfig { get; set; }
Specify this field if your model version performs image classification or general classification.
annotationSpecSet
in this configuration must match
[EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
Property Value | |
---|---|
Type | Description |
ImageClassificationConfig |
InputConfig
public InputConfig InputConfig { get; set; }
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
).
Property Value | |
---|---|
Type | Description |
InputConfig |
TextClassificationConfig
public TextClassificationConfig TextClassificationConfig { get; set; }
Specify this field if your model version performs text classification.
annotationSpecSet
in this configuration must match
[EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].
allowMultiLabel
in this configuration must match
classificationMetadata.isMultiLabel
in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].
Property Value | |
---|---|
Type | Description |
TextClassificationConfig |