feat(bigquery): update the API

#### bigquery:v2 The following keys were added: - schemas.ArimaForecastingMetrics.properties.arimaFittingMetrics.deprecated - schemas.ArimaForecastingMetrics.properties.hasDrift.deprecated - schemas.ArimaForecastingMetrics.properties.nonSeasonalOrder.deprecated - schemas.ArimaForecastingMetrics.properties.seasonalPeriods.deprecated - schemas.ArimaForecastingMetrics.properties.timeSeriesId.deprecated - schemas.Model.properties.bestTrialId.deprecated - schemas.TrainingOptions.properties.activationFn.description - schemas.TrainingOptions.properties.activationFn.type - schemas.TrainingOptions.properties.autoClassWeights.description - schemas.TrainingOptions.properties.autoClassWeights.type - schemas.TrainingOptions.properties.budgetHours.description - schemas.TrainingOptions.properties.budgetHours.format - schemas.TrainingOptions.properties.budgetHours.type - schemas.TrainingOptions.properties.fitIntercept.description - schemas.TrainingOptions.properties.fitIntercept.type - schemas.TrainingOptions.properties.l1RegActivation.description - schemas.TrainingOptions.properties.l1RegActivation.format - schemas.TrainingOptions.properties.l1RegActivation.type - schemas.TrainingOptions.properties.modelRegistry.description - schemas.TrainingOptions.properties.modelRegistry.enum - schemas.TrainingOptions.properties.modelRegistry.enumDescriptions - schemas.TrainingOptions.properties.modelRegistry.type - schemas.TrainingOptions.properties.numPrincipalComponents.description - schemas.TrainingOptions.properties.numPrincipalComponents.format - schemas.TrainingOptions.properties.numPrincipalComponents.type - schemas.TrainingOptions.properties.optimizer.description - schemas.TrainingOptions.properties.optimizer.type - schemas.TrainingOptions.properties.pcaExplainedVarianceRatio.description - schemas.TrainingOptions.properties.pcaExplainedVarianceRatio.format - schemas.TrainingOptions.properties.pcaExplainedVarianceRatio.type - schemas.TrainingOptions.properties.pcaSolver.description - schemas.TrainingOptions.properties.pcaSolver.enum - schemas.TrainingOptions.properties.pcaSolver.enumDescriptions - schemas.TrainingOptions.properties.pcaSolver.type - schemas.TrainingOptions.properties.scaleFeatures.description - schemas.TrainingOptions.properties.scaleFeatures.type - schemas.TrainingOptions.properties.standardizeFeatures.description - schemas.TrainingOptions.properties.standardizeFeatures.type - schemas.TrainingOptions.properties.vertexAiModelVersionAliases.description - schemas.TrainingOptions.properties.vertexAiModelVersionAliases.items.type - schemas.TrainingOptions.properties.vertexAiModelVersionAliases.type - schemas.TrainingRun.properties.trainingStartTime.deprecated The following keys were changed: - schemas.Model.properties.featureColumns.description
googleapis · Jul 13, 2023 · c6dd02d · c6dd02d
1 parent 62fca56
commit c6dd02d
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Showing 2 changed files with 141 additions and 3 deletions.
diff --git a/discovery/bigquery-v2.json b/discovery/bigquery-v2.json
@@ -1710,7 +1710,7 @@
       }
     }
   },
-  "revision": "20230624",
+  "revision": "20230708",
   "rootUrl": "https://bigquery.googleapis.com/",
   "schemas": {
     "AggregateClassificationMetrics": {
@@ -1855,6 +1855,7 @@
       "id": "ArimaForecastingMetrics",
       "properties": {
         "arimaFittingMetrics": {
+          "deprecated": true,
           "description": "Arima model fitting metrics.",
           "items": {
             "$ref": "ArimaFittingMetrics"
@@ -1869,20 +1870,23 @@
           "type": "array"
         },
         "hasDrift": {
+          "deprecated": true,
           "description": "Whether Arima model fitted with drift or not. It is always false when d is not 1.",
           "items": {
             "type": "boolean"
           },
           "type": "array"
         },
         "nonSeasonalOrder": {
+          "deprecated": true,
           "description": "Non-seasonal order.",
           "items": {
             "$ref": "ArimaOrder"
           },
           "type": "array"
         },
         "seasonalPeriods": {
+          "deprecated": true,
           "description": "Seasonal periods. Repeated because multiple periods are supported for one time series.",
           "items": {
             "enum": [
@@ -1908,6 +1912,7 @@
           "type": "array"
         },
         "timeSeriesId": {
+          "deprecated": true,
           "description": "Id to differentiate different time series for the large-scale case.",
           "items": {
             "type": "string"
@@ -5057,6 +5062,7 @@
       "id": "Model",
       "properties": {
         "bestTrialId": {
+          "deprecated": true,
           "description": "The best trial_id across all training runs.",
           "format": "int64",
           "type": "string"
@@ -5092,7 +5098,7 @@
           "type": "string"
         },
         "featureColumns": {
-          "description": "Output only. Input feature columns that were used to train this model.",
+          "description": "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.",
           "items": {
             "$ref": "StandardSqlField"
           },
@@ -7084,6 +7090,10 @@
       "description": "Options used in model training.",
       "id": "TrainingOptions",
       "properties": {
+        "activationFn": {
+          "description": "Activation function of the neural nets.",
+          "type": "string"
+        },
         "adjustStepChanges": {
           "description": "If true, detect step changes and make data adjustment in the input time series.",
           "type": "boolean"
@@ -7106,6 +7116,10 @@
           "format": "int64",
           "type": "string"
         },
+        "autoClassWeights": {
+          "description": "Whether to calculate class weights automatically based on the popularity of each label.",
+          "type": "boolean"
+        },
         "batchSize": {
           "description": "Batch size for dnn models.",
           "format": "int64",
@@ -7125,6 +7139,11 @@
           ],
           "type": "string"
         },
+        "budgetHours": {
+          "description": "Budget in hours for AutoML training.",
+          "format": "double",
+          "type": "number"
+        },
         "calculatePValues": {
           "description": "Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.",
           "type": "boolean"
@@ -7282,6 +7301,10 @@
           ],
           "type": "string"
         },
+        "fitIntercept": {
+          "description": "Whether the model should include intercept during model training.",
+          "type": "boolean"
+        },
         "hiddenUnits": {
           "description": "Hidden units for dnn models.",
           "items": {
@@ -7535,6 +7558,11 @@
           ],
           "type": "string"
         },
+        "l1RegActivation": {
+          "description": "L1 regularization coefficient to activations.",
+          "format": "double",
+          "type": "number"
+        },
         "l1Regularization": {
           "description": "L1 regularization coefficient.",
           "format": "double",
@@ -7626,6 +7654,18 @@
           "format": "int64",
           "type": "string"
         },
+        "modelRegistry": {
+          "description": "The model registry.",
+          "enum": [
+            "MODEL_REGISTRY_UNSPECIFIED",
+            "VERTEX_AI"
+          ],
+          "enumDescriptions": [
+            "",
+            "Vertex AI."
+          ],
+          "type": "string"
+        },
         "modelUri": {
           "description": "Google Cloud Storage URI from which the model was imported. Only applicable for imported models.",
           "type": "string"
@@ -7649,6 +7689,11 @@
           "format": "int64",
           "type": "string"
         },
+        "numPrincipalComponents": {
+          "description": "Number of principal components to keep in the PCA model. Must be <= the number of features.",
+          "format": "int64",
+          "type": "string"
+        },
         "numTrials": {
           "description": "Number of trials to run this hyperparameter tuning job.",
           "format": "int64",
@@ -7668,11 +7713,44 @@
           ],
           "type": "string"
         },
+        "optimizer": {
+          "description": "Optimizer used for training the neural nets.",
+          "type": "string"
+        },
+        "pcaExplainedVarianceRatio": {
+          "description": "The minimum ratio of cumulative explained variance that needs to be given by the PCA model.",
+          "format": "double",
+          "type": "number"
+        },
+        "pcaSolver": {
+          "description": "The solver for PCA.",
+          "enum": [
+            "UNSPECIFIED",
+            "FULL",
+            "RANDOMIZED",
+            "AUTO"
+          ],
+          "enumDescriptions": [
+            "",
+            "Full eigen-decoposition.",
+            "Randomized SVD.",
+            "Auto."
+          ],
+          "type": "string"
+        },
         "sampledShapleyNumPaths": {
           "description": "Number of paths for the sampled Shapley explain method.",
           "format": "int64",
           "type": "string"
         },
+        "scaleFeatures": {
+          "description": "If true, scale the feature values by dividing the feature standard deviation. Currently only apply to PCA.",
+          "type": "boolean"
+        },
+        "standardizeFeatures": {
+          "description": "Whether to standardize numerical features. Default to true.",
+          "type": "boolean"
+        },
         "subsample": {
           "description": "Subsample fraction of the training data to grow tree to prevent overfitting for boosted tree models.",
           "format": "double",
@@ -7733,6 +7811,13 @@
           "description": "User column specified for matrix factorization models.",
           "type": "string"
         },
+        "vertexAiModelVersionAliases": {
+          "description": "The version aliases to apply in Vertex AI model registry. Always overwrite if the version aliases exists in a existing model.",
+          "items": {
+            "type": "string"
+          },
+          "type": "array"
+        },
         "walsAlpha": {
           "description": "Hyperparameter for matrix factoration when implicit feedback type is specified.",
           "format": "double",
@@ -7796,6 +7881,7 @@
           "readOnly": true
         },
         "trainingStartTime": {
+          "deprecated": true,
           "description": "Output only. The start time of this training run, in milliseconds since epoch.",
           "format": "int64",
           "readOnly": true,

diff --git a/src/apis/bigquery/v2.ts b/src/apis/bigquery/v2.ts
@@ -2509,7 +2509,7 @@ export namespace bigquery_v2 {
      */
     expirationTime?: string | null;
     /**
-     * Output only. Input feature columns that were used to train this model.
+     * 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.
      */
     featureColumns?: Schema$StandardSqlField[];
     /**
@@ -3741,6 +3741,10 @@ export namespace bigquery_v2 {
    * Options used in model training.
    */
   export interface Schema$TrainingOptions {
+    /**
+     * Activation function of the neural nets.
+     */
+    activationFn?: string | null;
     /**
      * If true, detect step changes and make data adjustment in the input time series.
      */
@@ -3761,6 +3765,10 @@ export namespace bigquery_v2 {
      * The min value of the sum of non-seasonal p and q.
      */
     autoArimaMinOrder?: string | null;
+    /**
+     * Whether to calculate class weights automatically based on the popularity of each label.
+     */
+    autoClassWeights?: boolean | null;
     /**
      * Batch size for dnn models.
      */
@@ -3769,6 +3777,10 @@ export namespace bigquery_v2 {
      * Booster type for boosted tree models.
      */
     boosterType?: string | null;
+    /**
+     * Budget in hours for AutoML training.
+     */
+    budgetHours?: number | null;
     /**
      * Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.
      */
@@ -3837,6 +3849,10 @@ export namespace bigquery_v2 {
      * Feedback type that specifies which algorithm to run for matrix factorization.
      */
     feedbackType?: string | null;
+    /**
+     * Whether the model should include intercept during model training.
+     */
+    fitIntercept?: boolean | null;
     /**
      * Hidden units for dnn models.
      */
@@ -3885,6 +3901,10 @@ export namespace bigquery_v2 {
      * The method used to initialize the centroids for kmeans algorithm.
      */
     kmeansInitializationMethod?: string | null;
+    /**
+     * L1 regularization coefficient to activations.
+     */
+    l1RegActivation?: number | null;
     /**
      * L1 regularization coefficient.
      */
@@ -3941,6 +3961,10 @@ export namespace bigquery_v2 {
      * Minimum sum of instance weight needed in a child for boosted tree models.
      */
     minTreeChildWeight?: string | null;
+    /**
+     * The model registry.
+     */
+    modelRegistry?: string | null;
     /**
      * Google Cloud Storage URI from which the model was imported. Only applicable for imported models.
      */
@@ -3961,6 +3985,10 @@ export namespace bigquery_v2 {
      * Number of parallel trees constructed during each iteration for boosted tree models.
      */
     numParallelTree?: string | null;
+    /**
+     * Number of principal components to keep in the PCA model. Must be <= the number of features.
+     */
+    numPrincipalComponents?: string | null;
     /**
      * Number of trials to run this hyperparameter tuning job.
      */
@@ -3969,10 +3997,30 @@ export namespace bigquery_v2 {
      * Optimization strategy for training linear regression models.
      */
     optimizationStrategy?: string | null;
+    /**
+     * Optimizer used for training the neural nets.
+     */
+    optimizer?: string | null;
+    /**
+     * The minimum ratio of cumulative explained variance that needs to be given by the PCA model.
+     */
+    pcaExplainedVarianceRatio?: number | null;
+    /**
+     * The solver for PCA.
+     */
+    pcaSolver?: string | null;
     /**
      * Number of paths for the sampled Shapley explain method.
      */
     sampledShapleyNumPaths?: string | null;
+    /**
+     * If true, scale the feature values by dividing the feature standard deviation. Currently only apply to PCA.
+     */
+    scaleFeatures?: boolean | null;
+    /**
+     * Whether to standardize numerical features. Default to true.
+     */
+    standardizeFeatures?: boolean | null;
     /**
      * Subsample fraction of the training data to grow tree to prevent overfitting for boosted tree models.
      */
@@ -4013,6 +4061,10 @@ export namespace bigquery_v2 {
      * User column specified for matrix factorization models.
      */
     userColumn?: string | null;
+    /**
+     * The version aliases to apply in Vertex AI model registry. Always overwrite if the version aliases exists in a existing model.
+     */
+    vertexAiModelVersionAliases?: string[] | null;
     /**
      * Hyperparameter for matrix factoration when implicit feedback type is specified.
      */