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/*
 * 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](/bigquery-ml/docs/reference/standard-sql/bigqueryml- * syntax-hp-tuning-overview) models, this is the best trial ID. For multi-objective * [hyperparameter tuning](/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](/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](/bigquery-ml/docs/reference/standard- * sql/bigqueryml-syntax-hp-tuning-overview) models, it only contains the best trial. For multi- * objective [hyperparameter tuning](/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](/bigquery-ml/docs/reference/standard-sql/bigqueryml- * syntax-hp-tuning-overview) models, this is the best trial ID. For multi-objective * [hyperparameter tuning](/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](/bigquery-ml/docs/reference/standard-sql/bigqueryml- * syntax-hp-tuning-overview) models, this is the best trial ID. For multi-objective * [hyperparameter tuning](/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](/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](/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](/bigquery-ml/docs/reference/standard- * sql/bigqueryml-syntax-hp-tuning-overview) models, it only contains the best trial. For multi- * objective [hyperparameter tuning](/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](/bigquery-ml/docs/reference/standard- * sql/bigqueryml-syntax-hp-tuning-overview) models, it only contains the best trial. For multi- * objective [hyperparameter tuning](/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(); } }




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