com.google.api.services.bigquery.model.Model Maven / Gradle / Ivy
/*
* Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
* in compliance with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software distributed under the License
* is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
* or implied. See the License for the specific language governing permissions and limitations under
* the License.
*/
/*
* This code was generated by https://github.com/googleapis/google-api-java-client-services/
* Modify at your own risk.
*/
package com.google.api.services.bigquery.model;
/**
* Model definition for Model.
*
* This is the Java data model class that specifies how to parse/serialize into the JSON that is
* transmitted over HTTP when working with the BigQuery API. For a detailed explanation see:
* https://developers.google.com/api-client-library/java/google-http-java-client/json
*
*
* @author Google, Inc.
*/
@SuppressWarnings("javadoc")
public final class Model extends com.google.api.client.json.GenericJson {
/**
* The best trial_id across all training runs.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key @com.google.api.client.json.JsonString
private java.lang.Long bestTrialId;
/**
* Output only. The time when this model was created, in millisecs since the epoch.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key @com.google.api.client.json.JsonString
private java.lang.Long creationTime;
/**
* Output only. The default trial_id to use in TVFs when the trial_id is not passed in. For
* single-objective [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, this is the best
* trial ID. For multi-objective [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, this is the
* smallest trial ID among all Pareto optimal trials.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key @com.google.api.client.json.JsonString
private java.lang.Long defaultTrialId;
/**
* Optional. A user-friendly description of this model.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.String description;
/**
* Custom encryption configuration (e.g., Cloud KMS keys). This shows the encryption configuration
* of the model data while stored in BigQuery storage. This field can be used with PatchModel to
* update encryption key for an already encrypted model.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private EncryptionConfiguration encryptionConfiguration;
/**
* Output only. A hash of this resource.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.String etag;
/**
* Optional. The time when this model expires, in milliseconds since the epoch. If not present,
* the model will persist indefinitely. Expired models will be deleted and their storage
* reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to
* set a default expirationTime on newly created models.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key @com.google.api.client.json.JsonString
private java.lang.Long expirationTime;
/**
* Output only. Input feature columns for the model inference. If the model is trained with
* TRANSFORM clause, these are the input of the TRANSFORM clause.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.util.List featureColumns;
/**
* Optional. A descriptive name for this model.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.String friendlyName;
/**
* Output only. All hyperparameter search spaces in this model.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private HparamSearchSpaces hparamSearchSpaces;
/**
* Output only. Trials of a [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) model sorted by trial_id.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.util.List hparamTrials;
static {
// hack to force ProGuard to consider HparamTuningTrial used, since otherwise it would be stripped out
// see https://github.com/google/google-api-java-client/issues/543
com.google.api.client.util.Data.nullOf(HparamTuningTrial.class);
}
/**
* Output only. Label columns that were used to train this model. The output of the model will
* have a "predicted_" prefix to these columns.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.util.List labelColumns;
/**
* The labels associated with this model. You can use these to organize and group your models.
* Label keys and values can be no longer than 63 characters, can only contain lowercase letters,
* numeric characters, underscores and dashes. International characters are allowed. Label values
* are optional. Label keys must start with a letter and each label in the list must have a
* different key.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.util.Map labels;
/**
* Output only. The time when this model was last modified, in millisecs since the epoch.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key @com.google.api.client.json.JsonString
private java.lang.Long lastModifiedTime;
/**
* Output only. The geographic location where the model resides. This value is inherited from the
* dataset.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.String location;
/**
* Required. Unique identifier for this model.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private ModelReference modelReference;
/**
* Output only. Type of the model resource.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.lang.String modelType;
/**
* Output only. For single-objective [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, it only contains
* the best trial. For multi-objective [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, it contains all
* Pareto optimal trials sorted by trial_id.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key @com.google.api.client.json.JsonString
private java.util.List optimalTrialIds;
/**
* Output only. Remote model info
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private RemoteModelInfo remoteModelInfo;
/**
* Information for all training runs in increasing order of start_time.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.util.List trainingRuns;
/**
* Output only. This field will be populated if a TRANSFORM clause was used to train a model.
* TRANSFORM clause (if used) takes feature_columns as input and outputs transform_columns.
* transform_columns then are used to train the model.
* The value may be {@code null}.
*/
@com.google.api.client.util.Key
private java.util.List transformColumns;
/**
* The best trial_id across all training runs.
* @return value or {@code null} for none
*/
public java.lang.Long getBestTrialId() {
return bestTrialId;
}
/**
* The best trial_id across all training runs.
* @param bestTrialId bestTrialId or {@code null} for none
*/
public Model setBestTrialId(java.lang.Long bestTrialId) {
this.bestTrialId = bestTrialId;
return this;
}
/**
* Output only. The time when this model was created, in millisecs since the epoch.
* @return value or {@code null} for none
*/
public java.lang.Long getCreationTime() {
return creationTime;
}
/**
* Output only. The time when this model was created, in millisecs since the epoch.
* @param creationTime creationTime or {@code null} for none
*/
public Model setCreationTime(java.lang.Long creationTime) {
this.creationTime = creationTime;
return this;
}
/**
* Output only. The default trial_id to use in TVFs when the trial_id is not passed in. For
* single-objective [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, this is the best
* trial ID. For multi-objective [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, this is the
* smallest trial ID among all Pareto optimal trials.
* @return value or {@code null} for none
*/
public java.lang.Long getDefaultTrialId() {
return defaultTrialId;
}
/**
* Output only. The default trial_id to use in TVFs when the trial_id is not passed in. For
* single-objective [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, this is the best
* trial ID. For multi-objective [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, this is the
* smallest trial ID among all Pareto optimal trials.
* @param defaultTrialId defaultTrialId or {@code null} for none
*/
public Model setDefaultTrialId(java.lang.Long defaultTrialId) {
this.defaultTrialId = defaultTrialId;
return this;
}
/**
* Optional. A user-friendly description of this model.
* @return value or {@code null} for none
*/
public java.lang.String getDescription() {
return description;
}
/**
* Optional. A user-friendly description of this model.
* @param description description or {@code null} for none
*/
public Model setDescription(java.lang.String description) {
this.description = description;
return this;
}
/**
* Custom encryption configuration (e.g., Cloud KMS keys). This shows the encryption configuration
* of the model data while stored in BigQuery storage. This field can be used with PatchModel to
* update encryption key for an already encrypted model.
* @return value or {@code null} for none
*/
public EncryptionConfiguration getEncryptionConfiguration() {
return encryptionConfiguration;
}
/**
* Custom encryption configuration (e.g., Cloud KMS keys). This shows the encryption configuration
* of the model data while stored in BigQuery storage. This field can be used with PatchModel to
* update encryption key for an already encrypted model.
* @param encryptionConfiguration encryptionConfiguration or {@code null} for none
*/
public Model setEncryptionConfiguration(EncryptionConfiguration encryptionConfiguration) {
this.encryptionConfiguration = encryptionConfiguration;
return this;
}
/**
* Output only. A hash of this resource.
* @return value or {@code null} for none
*/
public java.lang.String getEtag() {
return etag;
}
/**
* Output only. A hash of this resource.
* @param etag etag or {@code null} for none
*/
public Model setEtag(java.lang.String etag) {
this.etag = etag;
return this;
}
/**
* Optional. The time when this model expires, in milliseconds since the epoch. If not present,
* the model will persist indefinitely. Expired models will be deleted and their storage
* reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to
* set a default expirationTime on newly created models.
* @return value or {@code null} for none
*/
public java.lang.Long getExpirationTime() {
return expirationTime;
}
/**
* Optional. The time when this model expires, in milliseconds since the epoch. If not present,
* the model will persist indefinitely. Expired models will be deleted and their storage
* reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to
* set a default expirationTime on newly created models.
* @param expirationTime expirationTime or {@code null} for none
*/
public Model setExpirationTime(java.lang.Long expirationTime) {
this.expirationTime = expirationTime;
return this;
}
/**
* Output only. Input feature columns for the model inference. If the model is trained with
* TRANSFORM clause, these are the input of the TRANSFORM clause.
* @return value or {@code null} for none
*/
public java.util.List getFeatureColumns() {
return featureColumns;
}
/**
* Output only. Input feature columns for the model inference. If the model is trained with
* TRANSFORM clause, these are the input of the TRANSFORM clause.
* @param featureColumns featureColumns or {@code null} for none
*/
public Model setFeatureColumns(java.util.List featureColumns) {
this.featureColumns = featureColumns;
return this;
}
/**
* Optional. A descriptive name for this model.
* @return value or {@code null} for none
*/
public java.lang.String getFriendlyName() {
return friendlyName;
}
/**
* Optional. A descriptive name for this model.
* @param friendlyName friendlyName or {@code null} for none
*/
public Model setFriendlyName(java.lang.String friendlyName) {
this.friendlyName = friendlyName;
return this;
}
/**
* Output only. All hyperparameter search spaces in this model.
* @return value or {@code null} for none
*/
public HparamSearchSpaces getHparamSearchSpaces() {
return hparamSearchSpaces;
}
/**
* Output only. All hyperparameter search spaces in this model.
* @param hparamSearchSpaces hparamSearchSpaces or {@code null} for none
*/
public Model setHparamSearchSpaces(HparamSearchSpaces hparamSearchSpaces) {
this.hparamSearchSpaces = hparamSearchSpaces;
return this;
}
/**
* Output only. Trials of a [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) model sorted by trial_id.
* @return value or {@code null} for none
*/
public java.util.List getHparamTrials() {
return hparamTrials;
}
/**
* Output only. Trials of a [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) model sorted by trial_id.
* @param hparamTrials hparamTrials or {@code null} for none
*/
public Model setHparamTrials(java.util.List hparamTrials) {
this.hparamTrials = hparamTrials;
return this;
}
/**
* Output only. Label columns that were used to train this model. The output of the model will
* have a "predicted_" prefix to these columns.
* @return value or {@code null} for none
*/
public java.util.List getLabelColumns() {
return labelColumns;
}
/**
* Output only. Label columns that were used to train this model. The output of the model will
* have a "predicted_" prefix to these columns.
* @param labelColumns labelColumns or {@code null} for none
*/
public Model setLabelColumns(java.util.List labelColumns) {
this.labelColumns = labelColumns;
return this;
}
/**
* The labels associated with this model. You can use these to organize and group your models.
* Label keys and values can be no longer than 63 characters, can only contain lowercase letters,
* numeric characters, underscores and dashes. International characters are allowed. Label values
* are optional. Label keys must start with a letter and each label in the list must have a
* different key.
* @return value or {@code null} for none
*/
public java.util.Map getLabels() {
return labels;
}
/**
* The labels associated with this model. You can use these to organize and group your models.
* Label keys and values can be no longer than 63 characters, can only contain lowercase letters,
* numeric characters, underscores and dashes. International characters are allowed. Label values
* are optional. Label keys must start with a letter and each label in the list must have a
* different key.
* @param labels labels or {@code null} for none
*/
public Model setLabels(java.util.Map labels) {
this.labels = labels;
return this;
}
/**
* Output only. The time when this model was last modified, in millisecs since the epoch.
* @return value or {@code null} for none
*/
public java.lang.Long getLastModifiedTime() {
return lastModifiedTime;
}
/**
* Output only. The time when this model was last modified, in millisecs since the epoch.
* @param lastModifiedTime lastModifiedTime or {@code null} for none
*/
public Model setLastModifiedTime(java.lang.Long lastModifiedTime) {
this.lastModifiedTime = lastModifiedTime;
return this;
}
/**
* Output only. The geographic location where the model resides. This value is inherited from the
* dataset.
* @return value or {@code null} for none
*/
public java.lang.String getLocation() {
return location;
}
/**
* Output only. The geographic location where the model resides. This value is inherited from the
* dataset.
* @param location location or {@code null} for none
*/
public Model setLocation(java.lang.String location) {
this.location = location;
return this;
}
/**
* Required. Unique identifier for this model.
* @return value or {@code null} for none
*/
public ModelReference getModelReference() {
return modelReference;
}
/**
* Required. Unique identifier for this model.
* @param modelReference modelReference or {@code null} for none
*/
public Model setModelReference(ModelReference modelReference) {
this.modelReference = modelReference;
return this;
}
/**
* Output only. Type of the model resource.
* @return value or {@code null} for none
*/
public java.lang.String getModelType() {
return modelType;
}
/**
* Output only. Type of the model resource.
* @param modelType modelType or {@code null} for none
*/
public Model setModelType(java.lang.String modelType) {
this.modelType = modelType;
return this;
}
/**
* Output only. For single-objective [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, it only contains
* the best trial. For multi-objective [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, it contains all
* Pareto optimal trials sorted by trial_id.
* @return value or {@code null} for none
*/
public java.util.List getOptimalTrialIds() {
return optimalTrialIds;
}
/**
* Output only. For single-objective [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, it only contains
* the best trial. For multi-objective [hyperparameter tuning](https://cloud.google.com/bigquery-
* ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models, it contains all
* Pareto optimal trials sorted by trial_id.
* @param optimalTrialIds optimalTrialIds or {@code null} for none
*/
public Model setOptimalTrialIds(java.util.List optimalTrialIds) {
this.optimalTrialIds = optimalTrialIds;
return this;
}
/**
* Output only. Remote model info
* @return value or {@code null} for none
*/
public RemoteModelInfo getRemoteModelInfo() {
return remoteModelInfo;
}
/**
* Output only. Remote model info
* @param remoteModelInfo remoteModelInfo or {@code null} for none
*/
public Model setRemoteModelInfo(RemoteModelInfo remoteModelInfo) {
this.remoteModelInfo = remoteModelInfo;
return this;
}
/**
* Information for all training runs in increasing order of start_time.
* @return value or {@code null} for none
*/
public java.util.List getTrainingRuns() {
return trainingRuns;
}
/**
* Information for all training runs in increasing order of start_time.
* @param trainingRuns trainingRuns or {@code null} for none
*/
public Model setTrainingRuns(java.util.List trainingRuns) {
this.trainingRuns = trainingRuns;
return this;
}
/**
* Output only. This field will be populated if a TRANSFORM clause was used to train a model.
* TRANSFORM clause (if used) takes feature_columns as input and outputs transform_columns.
* transform_columns then are used to train the model.
* @return value or {@code null} for none
*/
public java.util.List getTransformColumns() {
return transformColumns;
}
/**
* Output only. This field will be populated if a TRANSFORM clause was used to train a model.
* TRANSFORM clause (if used) takes feature_columns as input and outputs transform_columns.
* transform_columns then are used to train the model.
* @param transformColumns transformColumns or {@code null} for none
*/
public Model setTransformColumns(java.util.List transformColumns) {
this.transformColumns = transformColumns;
return this;
}
@Override
public Model set(String fieldName, Object value) {
return (Model) super.set(fieldName, value);
}
@Override
public Model clone() {
return (Model) super.clone();
}
}