defmodule Google.Cloud.Bigquery.V2.RemoteModelInfo.RemoteServiceType do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:REMOTE_SERVICE_TYPE_UNSPECIFIED, 0) field(:CLOUD_AI_TRANSLATE_V3, 1) field(:CLOUD_AI_VISION_V1, 2) field(:CLOUD_AI_NATURAL_LANGUAGE_V1, 3) field(:CLOUD_AI_SPEECH_TO_TEXT_V2, 7) end defmodule Google.Cloud.Bigquery.V2.Model.ModelType do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:MODEL_TYPE_UNSPECIFIED, 0) field(:LINEAR_REGRESSION, 1) field(:LOGISTIC_REGRESSION, 2) field(:KMEANS, 3) field(:MATRIX_FACTORIZATION, 4) field(:DNN_CLASSIFIER, 5) field(:TENSORFLOW, 6) field(:DNN_REGRESSOR, 7) field(:XGBOOST, 8) field(:BOOSTED_TREE_REGRESSOR, 9) field(:BOOSTED_TREE_CLASSIFIER, 10) field(:ARIMA, 11) field(:AUTOML_REGRESSOR, 12) field(:AUTOML_CLASSIFIER, 13) field(:PCA, 14) field(:DNN_LINEAR_COMBINED_CLASSIFIER, 16) field(:DNN_LINEAR_COMBINED_REGRESSOR, 17) field(:AUTOENCODER, 18) field(:ARIMA_PLUS, 19) field(:ARIMA_PLUS_XREG, 23) field(:RANDOM_FOREST_REGRESSOR, 24) field(:RANDOM_FOREST_CLASSIFIER, 25) field(:TENSORFLOW_LITE, 26) field(:ONNX, 28) field(:TRANSFORM_ONLY, 29) field(:CONTRIBUTION_ANALYSIS, 37) end defmodule Google.Cloud.Bigquery.V2.Model.LossType do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:LOSS_TYPE_UNSPECIFIED, 0) field(:MEAN_SQUARED_LOSS, 1) field(:MEAN_LOG_LOSS, 2) end defmodule Google.Cloud.Bigquery.V2.Model.DistanceType do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:DISTANCE_TYPE_UNSPECIFIED, 0) field(:EUCLIDEAN, 1) field(:COSINE, 2) end defmodule Google.Cloud.Bigquery.V2.Model.DataSplitMethod do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:DATA_SPLIT_METHOD_UNSPECIFIED, 0) field(:RANDOM, 1) field(:CUSTOM, 2) field(:SEQUENTIAL, 3) field(:NO_SPLIT, 4) field(:AUTO_SPLIT, 5) end defmodule Google.Cloud.Bigquery.V2.Model.DataFrequency do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:DATA_FREQUENCY_UNSPECIFIED, 0) field(:AUTO_FREQUENCY, 1) field(:YEARLY, 2) field(:QUARTERLY, 3) field(:MONTHLY, 4) field(:WEEKLY, 5) field(:DAILY, 6) field(:HOURLY, 7) field(:PER_MINUTE, 8) end defmodule Google.Cloud.Bigquery.V2.Model.HolidayRegion do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:HOLIDAY_REGION_UNSPECIFIED, 0) field(:GLOBAL, 1) field(:NA, 2) field(:JAPAC, 3) field(:EMEA, 4) field(:LAC, 5) field(:AE, 6) field(:AR, 7) field(:AT, 8) field(:AU, 9) field(:BE, 10) field(:BR, 11) field(:CA, 12) field(:CH, 13) field(:CL, 14) field(:CN, 15) field(:CO, 16) field(:CS, 17) field(:CZ, 18) field(:DE, 19) field(:DK, 20) field(:DZ, 21) field(:EC, 22) field(:EE, 23) field(:EG, 24) field(:ES, 25) field(:FI, 26) field(:FR, 27) field(:GB, 28) field(:GR, 29) field(:HK, 30) field(:HU, 31) field(:ID, 32) field(:IE, 33) field(:IL, 34) field(:IN, 35) field(:IR, 36) field(:IT, 37) field(:JP, 38) field(:KR, 39) field(:LV, 40) field(:MA, 41) field(:MX, 42) field(:MY, 43) field(:NG, 44) field(:NL, 45) field(:NO, 46) field(:NZ, 47) field(:PE, 48) field(:PH, 49) field(:PK, 50) field(:PL, 51) field(:PT, 52) field(:RO, 53) field(:RS, 54) field(:RU, 55) field(:SA, 56) field(:SE, 57) field(:SG, 58) field(:SI, 59) field(:SK, 60) field(:TH, 61) field(:TR, 62) field(:TW, 63) field(:UA, 64) field(:US, 65) field(:VE, 66) field(:VN, 67) field(:ZA, 68) end defmodule Google.Cloud.Bigquery.V2.Model.ColorSpace do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:COLOR_SPACE_UNSPECIFIED, 0) field(:RGB, 1) field(:HSV, 2) field(:YIQ, 3) field(:YUV, 4) field(:GRAYSCALE, 5) end defmodule Google.Cloud.Bigquery.V2.Model.LearnRateStrategy do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:LEARN_RATE_STRATEGY_UNSPECIFIED, 0) field(:LINE_SEARCH, 1) field(:CONSTANT, 2) end defmodule Google.Cloud.Bigquery.V2.Model.OptimizationStrategy do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:OPTIMIZATION_STRATEGY_UNSPECIFIED, 0) field(:BATCH_GRADIENT_DESCENT, 1) field(:NORMAL_EQUATION, 2) end defmodule Google.Cloud.Bigquery.V2.Model.FeedbackType do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:FEEDBACK_TYPE_UNSPECIFIED, 0) field(:IMPLICIT, 1) field(:EXPLICIT, 2) end defmodule Google.Cloud.Bigquery.V2.Model.SeasonalPeriod.SeasonalPeriodType do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:SEASONAL_PERIOD_TYPE_UNSPECIFIED, 0) field(:NO_SEASONALITY, 1) field(:DAILY, 2) field(:WEEKLY, 3) field(:MONTHLY, 4) field(:QUARTERLY, 5) field(:YEARLY, 6) field(:HOURLY, 7) end defmodule Google.Cloud.Bigquery.V2.Model.KmeansEnums.KmeansInitializationMethod do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:KMEANS_INITIALIZATION_METHOD_UNSPECIFIED, 0) field(:RANDOM, 1) field(:CUSTOM, 2) field(:KMEANS_PLUS_PLUS, 3) end defmodule Google.Cloud.Bigquery.V2.Model.BoostedTreeOptionEnums.BoosterType do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:BOOSTER_TYPE_UNSPECIFIED, 0) field(:GBTREE, 1) field(:DART, 2) end defmodule Google.Cloud.Bigquery.V2.Model.BoostedTreeOptionEnums.DartNormalizeType do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:DART_NORMALIZE_TYPE_UNSPECIFIED, 0) field(:TREE, 1) field(:FOREST, 2) end defmodule Google.Cloud.Bigquery.V2.Model.BoostedTreeOptionEnums.TreeMethod do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:TREE_METHOD_UNSPECIFIED, 0) field(:AUTO, 1) field(:EXACT, 2) field(:APPROX, 3) field(:HIST, 4) end defmodule Google.Cloud.Bigquery.V2.Model.HparamTuningEnums.HparamTuningObjective do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:HPARAM_TUNING_OBJECTIVE_UNSPECIFIED, 0) field(:MEAN_ABSOLUTE_ERROR, 1) field(:MEAN_SQUARED_ERROR, 2) field(:MEAN_SQUARED_LOG_ERROR, 3) field(:MEDIAN_ABSOLUTE_ERROR, 4) field(:R_SQUARED, 5) field(:EXPLAINED_VARIANCE, 6) field(:PRECISION, 7) field(:RECALL, 8) field(:ACCURACY, 9) field(:F1_SCORE, 10) field(:LOG_LOSS, 11) field(:ROC_AUC, 12) field(:DAVIES_BOULDIN_INDEX, 13) field(:MEAN_AVERAGE_PRECISION, 14) field(:NORMALIZED_DISCOUNTED_CUMULATIVE_GAIN, 15) field(:AVERAGE_RANK, 16) end defmodule Google.Cloud.Bigquery.V2.Model.CategoryEncodingMethod.EncodingMethod do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:ENCODING_METHOD_UNSPECIFIED, 0) field(:ONE_HOT_ENCODING, 1) field(:LABEL_ENCODING, 2) field(:DUMMY_ENCODING, 3) end defmodule Google.Cloud.Bigquery.V2.Model.PcaSolverOptionEnums.PcaSolver do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:UNSPECIFIED, 0) field(:FULL, 1) field(:RANDOMIZED, 2) field(:AUTO, 3) end defmodule Google.Cloud.Bigquery.V2.Model.ModelRegistryOptionEnums.ModelRegistry do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:MODEL_REGISTRY_UNSPECIFIED, 0) field(:VERTEX_AI, 1) end defmodule Google.Cloud.Bigquery.V2.Model.TrainingRun.TrainingOptions.ReservationAffinityType do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:RESERVATION_AFFINITY_TYPE_UNSPECIFIED, 0) field(:NO_RESERVATION, 1) field(:ANY_RESERVATION, 2) field(:SPECIFIC_RESERVATION, 3) end defmodule Google.Cloud.Bigquery.V2.Model.HparamTuningTrial.TrialStatus do @moduledoc false use Protobuf, enum: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:TRIAL_STATUS_UNSPECIFIED, 0) field(:NOT_STARTED, 1) field(:RUNNING, 2) field(:SUCCEEDED, 3) field(:FAILED, 4) field(:INFEASIBLE, 5) field(:STOPPED_EARLY, 6) end defmodule Google.Cloud.Bigquery.V2.RemoteModelInfo do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 oneof(:remote_service, 0) field(:endpoint, 1, type: :string, oneof: 0, deprecated: false) field(:remote_service_type, 2, type: Google.Cloud.Bigquery.V2.RemoteModelInfo.RemoteServiceType, json_name: "remoteServiceType", enum: true, oneof: 0, deprecated: false ) field(:connection, 3, type: :string, deprecated: false) field(:max_batching_rows, 4, type: :int64, json_name: "maxBatchingRows", deprecated: false) field(:remote_model_version, 5, type: :string, json_name: "remoteModelVersion", deprecated: false ) field(:speech_recognizer, 7, type: :string, json_name: "speechRecognizer", deprecated: false) end defmodule Google.Cloud.Bigquery.V2.TransformColumn do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:name, 1, type: :string, deprecated: false) field(:type, 2, type: Google.Cloud.Bigquery.V2.StandardSqlDataType, deprecated: false) field(:transform_sql, 3, type: :string, json_name: "transformSql", deprecated: false) end defmodule Google.Cloud.Bigquery.V2.Model.SeasonalPeriod do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 end defmodule Google.Cloud.Bigquery.V2.Model.KmeansEnums do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 end defmodule Google.Cloud.Bigquery.V2.Model.BoostedTreeOptionEnums do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 end defmodule Google.Cloud.Bigquery.V2.Model.HparamTuningEnums do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 end defmodule Google.Cloud.Bigquery.V2.Model.RegressionMetrics do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:mean_absolute_error, 1, type: Google.Protobuf.DoubleValue, json_name: "meanAbsoluteError" ) field(:mean_squared_error, 2, type: Google.Protobuf.DoubleValue, json_name: "meanSquaredError") field(:mean_squared_log_error, 3, type: Google.Protobuf.DoubleValue, json_name: "meanSquaredLogError" ) field(:median_absolute_error, 4, type: Google.Protobuf.DoubleValue, json_name: "medianAbsoluteError" ) field(:r_squared, 5, type: Google.Protobuf.DoubleValue, json_name: "rSquared") end defmodule Google.Cloud.Bigquery.V2.Model.AggregateClassificationMetrics do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:precision, 1, type: Google.Protobuf.DoubleValue) field(:recall, 2, type: Google.Protobuf.DoubleValue) field(:accuracy, 3, type: Google.Protobuf.DoubleValue) field(:threshold, 4, type: Google.Protobuf.DoubleValue) field(:f1_score, 5, type: Google.Protobuf.DoubleValue, json_name: "f1Score") field(:log_loss, 6, type: Google.Protobuf.DoubleValue, json_name: "logLoss") field(:roc_auc, 7, type: Google.Protobuf.DoubleValue, json_name: "rocAuc") end defmodule Google.Cloud.Bigquery.V2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:positive_class_threshold, 1, type: Google.Protobuf.DoubleValue, json_name: "positiveClassThreshold" ) field(:true_positives, 2, type: Google.Protobuf.Int64Value, json_name: "truePositives") field(:false_positives, 3, type: Google.Protobuf.Int64Value, json_name: "falsePositives") field(:true_negatives, 4, type: Google.Protobuf.Int64Value, json_name: "trueNegatives") field(:false_negatives, 5, type: Google.Protobuf.Int64Value, json_name: "falseNegatives") field(:precision, 6, type: Google.Protobuf.DoubleValue) field(:recall, 7, type: Google.Protobuf.DoubleValue) field(:f1_score, 8, type: Google.Protobuf.DoubleValue, json_name: "f1Score") field(:accuracy, 9, type: Google.Protobuf.DoubleValue) end defmodule Google.Cloud.Bigquery.V2.Model.BinaryClassificationMetrics do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:aggregate_classification_metrics, 1, type: Google.Cloud.Bigquery.V2.Model.AggregateClassificationMetrics, json_name: "aggregateClassificationMetrics" ) field(:binary_confusion_matrix_list, 2, repeated: true, type: Google.Cloud.Bigquery.V2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix, json_name: "binaryConfusionMatrixList" ) field(:positive_label, 3, type: :string, json_name: "positiveLabel") field(:negative_label, 4, type: :string, json_name: "negativeLabel") end defmodule Google.Cloud.Bigquery.V2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:predicted_label, 1, type: :string, json_name: "predictedLabel") field(:item_count, 2, type: Google.Protobuf.Int64Value, json_name: "itemCount") end defmodule Google.Cloud.Bigquery.V2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Row do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:actual_label, 1, type: :string, json_name: "actualLabel") field(:entries, 2, repeated: true, type: Google.Cloud.Bigquery.V2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry ) end defmodule Google.Cloud.Bigquery.V2.Model.MultiClassClassificationMetrics.ConfusionMatrix do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:confidence_threshold, 1, type: Google.Protobuf.DoubleValue, json_name: "confidenceThreshold" ) field(:rows, 2, repeated: true, type: Google.Cloud.Bigquery.V2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Row ) end defmodule Google.Cloud.Bigquery.V2.Model.MultiClassClassificationMetrics do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:aggregate_classification_metrics, 1, type: Google.Cloud.Bigquery.V2.Model.AggregateClassificationMetrics, json_name: "aggregateClassificationMetrics" ) field(:confusion_matrix_list, 2, repeated: true, type: Google.Cloud.Bigquery.V2.Model.MultiClassClassificationMetrics.ConfusionMatrix, json_name: "confusionMatrixList" ) end defmodule Google.Cloud.Bigquery.V2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:category, 1, type: :string) field(:count, 2, type: Google.Protobuf.Int64Value) end defmodule Google.Cloud.Bigquery.V2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:category_counts, 1, repeated: true, type: Google.Cloud.Bigquery.V2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount, json_name: "categoryCounts" ) end defmodule Google.Cloud.Bigquery.V2.Model.ClusteringMetrics.Cluster.FeatureValue do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 oneof(:value, 0) field(:feature_column, 1, type: :string, json_name: "featureColumn") field(:numerical_value, 2, type: Google.Protobuf.DoubleValue, json_name: "numericalValue", oneof: 0 ) field(:categorical_value, 3, type: Google.Cloud.Bigquery.V2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue, json_name: "categoricalValue", oneof: 0 ) end defmodule Google.Cloud.Bigquery.V2.Model.ClusteringMetrics.Cluster do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:centroid_id, 1, type: :int64, json_name: "centroidId") field(:feature_values, 2, repeated: true, type: Google.Cloud.Bigquery.V2.Model.ClusteringMetrics.Cluster.FeatureValue, json_name: "featureValues" ) field(:count, 3, type: Google.Protobuf.Int64Value) end defmodule Google.Cloud.Bigquery.V2.Model.ClusteringMetrics do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:davies_bouldin_index, 1, type: Google.Protobuf.DoubleValue, json_name: "daviesBouldinIndex" ) field(:mean_squared_distance, 2, type: Google.Protobuf.DoubleValue, json_name: "meanSquaredDistance" ) field(:clusters, 3, repeated: true, type: Google.Cloud.Bigquery.V2.Model.ClusteringMetrics.Cluster ) end defmodule Google.Cloud.Bigquery.V2.Model.RankingMetrics do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:mean_average_precision, 1, type: Google.Protobuf.DoubleValue, json_name: "meanAveragePrecision" ) field(:mean_squared_error, 2, type: Google.Protobuf.DoubleValue, json_name: "meanSquaredError") field(:normalized_discounted_cumulative_gain, 3, type: Google.Protobuf.DoubleValue, json_name: "normalizedDiscountedCumulativeGain" ) field(:average_rank, 4, type: Google.Protobuf.DoubleValue, json_name: "averageRank") end defmodule Google.Cloud.Bigquery.V2.Model.ArimaForecastingMetrics.ArimaSingleModelForecastingMetrics do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:non_seasonal_order, 1, type: Google.Cloud.Bigquery.V2.Model.ArimaOrder, json_name: "nonSeasonalOrder" ) field(:arima_fitting_metrics, 2, type: Google.Cloud.Bigquery.V2.Model.ArimaFittingMetrics, json_name: "arimaFittingMetrics" ) field(:has_drift, 3, type: Google.Protobuf.BoolValue, json_name: "hasDrift") field(:time_series_id, 4, type: :string, json_name: "timeSeriesId") field(:time_series_ids, 9, repeated: true, type: :string, json_name: "timeSeriesIds") field(:seasonal_periods, 5, repeated: true, type: Google.Cloud.Bigquery.V2.Model.SeasonalPeriod.SeasonalPeriodType, json_name: "seasonalPeriods", enum: true ) field(:has_holiday_effect, 6, type: Google.Protobuf.BoolValue, json_name: "hasHolidayEffect") field(:has_spikes_and_dips, 7, type: Google.Protobuf.BoolValue, json_name: "hasSpikesAndDips") field(:has_step_changes, 8, type: Google.Protobuf.BoolValue, json_name: "hasStepChanges") end defmodule Google.Cloud.Bigquery.V2.Model.ArimaForecastingMetrics do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:arima_single_model_forecasting_metrics, 6, repeated: true, type: Google.Cloud.Bigquery.V2.Model.ArimaForecastingMetrics.ArimaSingleModelForecastingMetrics, json_name: "arimaSingleModelForecastingMetrics" ) end defmodule Google.Cloud.Bigquery.V2.Model.DimensionalityReductionMetrics do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:total_explained_variance_ratio, 1, type: Google.Protobuf.DoubleValue, json_name: "totalExplainedVarianceRatio" ) end defmodule Google.Cloud.Bigquery.V2.Model.EvaluationMetrics do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 oneof(:metrics, 0) field(:regression_metrics, 1, type: Google.Cloud.Bigquery.V2.Model.RegressionMetrics, json_name: "regressionMetrics", oneof: 0 ) field(:binary_classification_metrics, 2, type: Google.Cloud.Bigquery.V2.Model.BinaryClassificationMetrics, json_name: "binaryClassificationMetrics", oneof: 0 ) field(:multi_class_classification_metrics, 3, type: Google.Cloud.Bigquery.V2.Model.MultiClassClassificationMetrics, json_name: "multiClassClassificationMetrics", oneof: 0 ) field(:clustering_metrics, 4, type: Google.Cloud.Bigquery.V2.Model.ClusteringMetrics, json_name: "clusteringMetrics", oneof: 0 ) field(:ranking_metrics, 5, type: Google.Cloud.Bigquery.V2.Model.RankingMetrics, json_name: "rankingMetrics", oneof: 0 ) field(:arima_forecasting_metrics, 6, type: Google.Cloud.Bigquery.V2.Model.ArimaForecastingMetrics, json_name: "arimaForecastingMetrics", oneof: 0 ) field(:dimensionality_reduction_metrics, 7, type: Google.Cloud.Bigquery.V2.Model.DimensionalityReductionMetrics, json_name: "dimensionalityReductionMetrics", oneof: 0 ) end defmodule Google.Cloud.Bigquery.V2.Model.DataSplitResult do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:training_table, 1, type: Google.Cloud.Bigquery.V2.TableReference, json_name: "trainingTable" ) field(:evaluation_table, 2, type: Google.Cloud.Bigquery.V2.TableReference, json_name: "evaluationTable" ) field(:test_table, 3, type: Google.Cloud.Bigquery.V2.TableReference, json_name: "testTable") end defmodule Google.Cloud.Bigquery.V2.Model.ArimaOrder do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:p, 1, type: Google.Protobuf.Int64Value) field(:d, 2, type: Google.Protobuf.Int64Value) field(:q, 3, type: Google.Protobuf.Int64Value) end defmodule Google.Cloud.Bigquery.V2.Model.ArimaFittingMetrics do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:log_likelihood, 1, type: Google.Protobuf.DoubleValue, json_name: "logLikelihood") field(:aic, 2, type: Google.Protobuf.DoubleValue) field(:variance, 3, type: Google.Protobuf.DoubleValue) end defmodule Google.Cloud.Bigquery.V2.Model.GlobalExplanation.Explanation do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:feature_name, 1, type: :string, json_name: "featureName") field(:attribution, 2, type: Google.Protobuf.DoubleValue) end defmodule Google.Cloud.Bigquery.V2.Model.GlobalExplanation do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:explanations, 1, repeated: true, type: Google.Cloud.Bigquery.V2.Model.GlobalExplanation.Explanation ) field(:class_label, 2, type: :string, json_name: "classLabel") end defmodule Google.Cloud.Bigquery.V2.Model.CategoryEncodingMethod do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 end defmodule Google.Cloud.Bigquery.V2.Model.PcaSolverOptionEnums do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 end defmodule Google.Cloud.Bigquery.V2.Model.ModelRegistryOptionEnums do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 end defmodule Google.Cloud.Bigquery.V2.Model.TrainingRun.TrainingOptions.LabelClassWeightsEntry do @moduledoc false use Protobuf, map: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:key, 1, type: :string) field(:value, 2, type: :double) end defmodule Google.Cloud.Bigquery.V2.Model.TrainingRun.TrainingOptions do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 oneof(:external_model_id, 0) field(:max_iterations, 1, type: :int64, json_name: "maxIterations") field(:loss_type, 2, type: Google.Cloud.Bigquery.V2.Model.LossType, json_name: "lossType", enum: true ) field(:learn_rate, 3, type: :double, json_name: "learnRate") field(:l1_regularization, 4, type: Google.Protobuf.DoubleValue, json_name: "l1Regularization") field(:l2_regularization, 5, type: Google.Protobuf.DoubleValue, json_name: "l2Regularization") field(:min_relative_progress, 6, type: Google.Protobuf.DoubleValue, json_name: "minRelativeProgress" ) field(:warm_start, 7, type: Google.Protobuf.BoolValue, json_name: "warmStart") field(:early_stop, 8, type: Google.Protobuf.BoolValue, json_name: "earlyStop") field(:input_label_columns, 9, repeated: true, type: :string, json_name: "inputLabelColumns") field(:data_split_method, 10, type: Google.Cloud.Bigquery.V2.Model.DataSplitMethod, json_name: "dataSplitMethod", enum: true ) field(:data_split_eval_fraction, 11, type: :double, json_name: "dataSplitEvalFraction") field(:data_split_column, 12, type: :string, json_name: "dataSplitColumn") field(:learn_rate_strategy, 13, type: Google.Cloud.Bigquery.V2.Model.LearnRateStrategy, json_name: "learnRateStrategy", enum: true ) field(:initial_learn_rate, 16, type: :double, json_name: "initialLearnRate") field(:label_class_weights, 17, repeated: true, type: Google.Cloud.Bigquery.V2.Model.TrainingRun.TrainingOptions.LabelClassWeightsEntry, json_name: "labelClassWeights", map: true ) field(:user_column, 18, type: :string, json_name: "userColumn") field(:item_column, 19, type: :string, json_name: "itemColumn") field(:distance_type, 20, type: Google.Cloud.Bigquery.V2.Model.DistanceType, json_name: "distanceType", enum: true ) field(:num_clusters, 21, type: :int64, json_name: "numClusters") field(:model_uri, 22, type: :string, json_name: "modelUri") field(:optimization_strategy, 23, type: Google.Cloud.Bigquery.V2.Model.OptimizationStrategy, json_name: "optimizationStrategy", enum: true ) field(:hidden_units, 24, repeated: true, type: :int64, json_name: "hiddenUnits") field(:batch_size, 25, type: :int64, json_name: "batchSize") field(:dropout, 26, type: Google.Protobuf.DoubleValue) field(:max_tree_depth, 27, type: :int64, json_name: "maxTreeDepth") field(:subsample, 28, type: :double) field(:min_split_loss, 29, type: Google.Protobuf.DoubleValue, json_name: "minSplitLoss") field(:booster_type, 60, type: Google.Cloud.Bigquery.V2.Model.BoostedTreeOptionEnums.BoosterType, json_name: "boosterType", enum: true ) field(:num_parallel_tree, 61, type: Google.Protobuf.Int64Value, json_name: "numParallelTree") field(:dart_normalize_type, 62, type: Google.Cloud.Bigquery.V2.Model.BoostedTreeOptionEnums.DartNormalizeType, json_name: "dartNormalizeType", enum: true ) field(:tree_method, 63, type: Google.Cloud.Bigquery.V2.Model.BoostedTreeOptionEnums.TreeMethod, json_name: "treeMethod", enum: true ) field(:min_tree_child_weight, 64, type: Google.Protobuf.Int64Value, json_name: "minTreeChildWeight" ) field(:colsample_bytree, 65, type: Google.Protobuf.DoubleValue, json_name: "colsampleBytree") field(:colsample_bylevel, 66, type: Google.Protobuf.DoubleValue, json_name: "colsampleBylevel") field(:colsample_bynode, 67, type: Google.Protobuf.DoubleValue, json_name: "colsampleBynode") field(:num_factors, 30, type: :int64, json_name: "numFactors") field(:feedback_type, 31, type: Google.Cloud.Bigquery.V2.Model.FeedbackType, json_name: "feedbackType", enum: true ) field(:wals_alpha, 32, type: Google.Protobuf.DoubleValue, json_name: "walsAlpha") field(:kmeans_initialization_method, 33, type: Google.Cloud.Bigquery.V2.Model.KmeansEnums.KmeansInitializationMethod, json_name: "kmeansInitializationMethod", enum: true ) field(:kmeans_initialization_column, 34, type: :string, json_name: "kmeansInitializationColumn") field(:time_series_timestamp_column, 35, type: :string, json_name: "timeSeriesTimestampColumn") field(:time_series_data_column, 36, type: :string, json_name: "timeSeriesDataColumn") field(:auto_arima, 37, type: Google.Protobuf.BoolValue, json_name: "autoArima") field(:non_seasonal_order, 38, type: Google.Cloud.Bigquery.V2.Model.ArimaOrder, json_name: "nonSeasonalOrder" ) field(:data_frequency, 39, type: Google.Cloud.Bigquery.V2.Model.DataFrequency, json_name: "dataFrequency", enum: true ) field(:calculate_p_values, 40, type: Google.Protobuf.BoolValue, json_name: "calculatePValues") field(:include_drift, 41, type: Google.Protobuf.BoolValue, json_name: "includeDrift") field(:holiday_region, 42, type: Google.Cloud.Bigquery.V2.Model.HolidayRegion, json_name: "holidayRegion", enum: true ) field(:holiday_regions, 71, repeated: true, type: Google.Cloud.Bigquery.V2.Model.HolidayRegion, json_name: "holidayRegions", enum: true ) field(:time_series_id_column, 43, type: :string, json_name: "timeSeriesIdColumn") field(:time_series_id_columns, 51, repeated: true, type: :string, json_name: "timeSeriesIdColumns" ) field(:forecast_limit_lower_bound, 99, type: :double, json_name: "forecastLimitLowerBound") field(:forecast_limit_upper_bound, 100, type: :double, json_name: "forecastLimitUpperBound") field(:horizon, 44, type: :int64) field(:auto_arima_max_order, 46, type: :int64, json_name: "autoArimaMaxOrder") field(:auto_arima_min_order, 83, type: :int64, json_name: "autoArimaMinOrder") field(:num_trials, 47, type: :int64, json_name: "numTrials") field(:max_parallel_trials, 48, type: :int64, json_name: "maxParallelTrials") field(:hparam_tuning_objectives, 54, repeated: true, type: Google.Cloud.Bigquery.V2.Model.HparamTuningEnums.HparamTuningObjective, json_name: "hparamTuningObjectives", enum: true ) field(:decompose_time_series, 50, type: Google.Protobuf.BoolValue, json_name: "decomposeTimeSeries" ) field(:clean_spikes_and_dips, 52, type: Google.Protobuf.BoolValue, json_name: "cleanSpikesAndDips" ) field(:adjust_step_changes, 53, type: Google.Protobuf.BoolValue, json_name: "adjustStepChanges") field(:enable_global_explain, 55, type: Google.Protobuf.BoolValue, json_name: "enableGlobalExplain" ) field(:sampled_shapley_num_paths, 56, type: :int64, json_name: "sampledShapleyNumPaths") field(:integrated_gradients_num_steps, 57, type: :int64, json_name: "integratedGradientsNumSteps" ) field(:category_encoding_method, 58, type: Google.Cloud.Bigquery.V2.Model.CategoryEncodingMethod.EncodingMethod, json_name: "categoryEncodingMethod", enum: true ) field(:tf_version, 70, type: :string, json_name: "tfVersion") field(:color_space, 72, type: Google.Cloud.Bigquery.V2.Model.ColorSpace, json_name: "colorSpace", enum: true ) field(:instance_weight_column, 73, type: :string, json_name: "instanceWeightColumn") field(:trend_smoothing_window_size, 74, type: :int64, json_name: "trendSmoothingWindowSize") field(:time_series_length_fraction, 75, type: :double, json_name: "timeSeriesLengthFraction") field(:min_time_series_length, 76, type: :int64, json_name: "minTimeSeriesLength") field(:max_time_series_length, 77, type: :int64, json_name: "maxTimeSeriesLength") field(:xgboost_version, 78, type: :string, json_name: "xgboostVersion") field(:approx_global_feature_contrib, 84, type: Google.Protobuf.BoolValue, json_name: "approxGlobalFeatureContrib" ) field(:fit_intercept, 85, type: Google.Protobuf.BoolValue, json_name: "fitIntercept") field(:num_principal_components, 86, type: :int64, json_name: "numPrincipalComponents") field(:pca_explained_variance_ratio, 87, type: :double, json_name: "pcaExplainedVarianceRatio") field(:scale_features, 88, type: Google.Protobuf.BoolValue, json_name: "scaleFeatures") field(:pca_solver, 89, type: Google.Cloud.Bigquery.V2.Model.PcaSolverOptionEnums.PcaSolver, json_name: "pcaSolver", enum: true ) field(:auto_class_weights, 90, type: Google.Protobuf.BoolValue, json_name: "autoClassWeights") field(:activation_fn, 91, type: :string, json_name: "activationFn") field(:optimizer, 92, type: :string) field(:budget_hours, 93, type: :double, json_name: "budgetHours") field(:standardize_features, 94, type: Google.Protobuf.BoolValue, json_name: "standardizeFeatures" ) field(:l1_reg_activation, 95, type: :double, json_name: "l1RegActivation") field(:model_registry, 96, type: Google.Cloud.Bigquery.V2.Model.ModelRegistryOptionEnums.ModelRegistry, json_name: "modelRegistry", enum: true ) field(:vertex_ai_model_version_aliases, 97, repeated: true, type: :string, json_name: "vertexAiModelVersionAliases" ) field(:dimension_id_columns, 104, repeated: true, type: :string, json_name: "dimensionIdColumns", deprecated: false ) field(:contribution_metric, 105, proto3_optional: true, type: :string, json_name: "contributionMetric" ) field(:is_test_column, 106, proto3_optional: true, type: :string, json_name: "isTestColumn") field(:min_apriori_support, 107, proto3_optional: true, type: :double, json_name: "minAprioriSupport" ) field(:hugging_face_model_id, 113, type: :string, json_name: "huggingFaceModelId", oneof: 0) field(:model_garden_model_name, 114, type: :string, json_name: "modelGardenModelName", oneof: 0) field(:endpoint_idle_ttl, 115, proto3_optional: true, type: Google.Protobuf.Duration, json_name: "endpointIdleTtl" ) field(:machine_type, 117, proto3_optional: true, type: :string, json_name: "machineType") field(:min_replica_count, 118, proto3_optional: true, type: :int64, json_name: "minReplicaCount" ) field(:max_replica_count, 119, proto3_optional: true, type: :int64, json_name: "maxReplicaCount" ) field(:reservation_affinity_type, 120, proto3_optional: true, type: Google.Cloud.Bigquery.V2.Model.TrainingRun.TrainingOptions.ReservationAffinityType, json_name: "reservationAffinityType", enum: true ) field(:reservation_affinity_key, 121, proto3_optional: true, type: :string, json_name: "reservationAffinityKey" ) field(:reservation_affinity_values, 122, repeated: true, type: :string, json_name: "reservationAffinityValues" ) end defmodule Google.Cloud.Bigquery.V2.Model.TrainingRun.IterationResult.ClusterInfo do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:centroid_id, 1, type: :int64, json_name: "centroidId") field(:cluster_radius, 2, type: Google.Protobuf.DoubleValue, json_name: "clusterRadius") field(:cluster_size, 3, type: Google.Protobuf.Int64Value, json_name: "clusterSize") end defmodule Google.Cloud.Bigquery.V2.Model.TrainingRun.IterationResult.ArimaResult.ArimaCoefficients do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:auto_regressive_coefficients, 1, repeated: true, type: :double, json_name: "autoRegressiveCoefficients" ) field(:moving_average_coefficients, 2, repeated: true, type: :double, json_name: "movingAverageCoefficients" ) field(:intercept_coefficient, 3, type: Google.Protobuf.DoubleValue, json_name: "interceptCoefficient" ) end defmodule Google.Cloud.Bigquery.V2.Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:non_seasonal_order, 1, type: Google.Cloud.Bigquery.V2.Model.ArimaOrder, json_name: "nonSeasonalOrder" ) field(:arima_coefficients, 2, type: Google.Cloud.Bigquery.V2.Model.TrainingRun.IterationResult.ArimaResult.ArimaCoefficients, json_name: "arimaCoefficients" ) field(:arima_fitting_metrics, 3, type: Google.Cloud.Bigquery.V2.Model.ArimaFittingMetrics, json_name: "arimaFittingMetrics" ) field(:has_drift, 4, type: Google.Protobuf.BoolValue, json_name: "hasDrift") field(:time_series_id, 5, type: :string, json_name: "timeSeriesId") field(:time_series_ids, 10, repeated: true, type: :string, json_name: "timeSeriesIds") field(:seasonal_periods, 6, repeated: true, type: Google.Cloud.Bigquery.V2.Model.SeasonalPeriod.SeasonalPeriodType, json_name: "seasonalPeriods", enum: true ) field(:has_holiday_effect, 7, type: Google.Protobuf.BoolValue, json_name: "hasHolidayEffect") field(:has_spikes_and_dips, 8, type: Google.Protobuf.BoolValue, json_name: "hasSpikesAndDips") field(:has_step_changes, 9, type: Google.Protobuf.BoolValue, json_name: "hasStepChanges") end defmodule Google.Cloud.Bigquery.V2.Model.TrainingRun.IterationResult.ArimaResult do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:arima_model_info, 1, repeated: true, type: Google.Cloud.Bigquery.V2.Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo, json_name: "arimaModelInfo" ) field(:seasonal_periods, 2, repeated: true, type: Google.Cloud.Bigquery.V2.Model.SeasonalPeriod.SeasonalPeriodType, json_name: "seasonalPeriods", enum: true ) end defmodule Google.Cloud.Bigquery.V2.Model.TrainingRun.IterationResult.PrincipalComponentInfo do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:principal_component_id, 1, type: Google.Protobuf.Int64Value, json_name: "principalComponentId" ) field(:explained_variance, 2, type: Google.Protobuf.DoubleValue, json_name: "explainedVariance") field(:explained_variance_ratio, 3, type: Google.Protobuf.DoubleValue, json_name: "explainedVarianceRatio" ) field(:cumulative_explained_variance_ratio, 4, type: Google.Protobuf.DoubleValue, json_name: "cumulativeExplainedVarianceRatio" ) end defmodule Google.Cloud.Bigquery.V2.Model.TrainingRun.IterationResult do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:index, 1, type: Google.Protobuf.Int32Value) field(:duration_ms, 4, type: Google.Protobuf.Int64Value, json_name: "durationMs") field(:training_loss, 5, type: Google.Protobuf.DoubleValue, json_name: "trainingLoss") field(:eval_loss, 6, type: Google.Protobuf.DoubleValue, json_name: "evalLoss") field(:learn_rate, 7, type: :double, json_name: "learnRate") field(:cluster_infos, 8, repeated: true, type: Google.Cloud.Bigquery.V2.Model.TrainingRun.IterationResult.ClusterInfo, json_name: "clusterInfos" ) field(:arima_result, 9, type: Google.Cloud.Bigquery.V2.Model.TrainingRun.IterationResult.ArimaResult, json_name: "arimaResult" ) field(:principal_component_infos, 10, repeated: true, type: Google.Cloud.Bigquery.V2.Model.TrainingRun.IterationResult.PrincipalComponentInfo, json_name: "principalComponentInfos" ) end defmodule Google.Cloud.Bigquery.V2.Model.TrainingRun do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:training_options, 1, type: Google.Cloud.Bigquery.V2.Model.TrainingRun.TrainingOptions, json_name: "trainingOptions", deprecated: false ) field(:start_time, 8, type: Google.Protobuf.Timestamp, json_name: "startTime", deprecated: false ) field(:results, 6, repeated: true, type: Google.Cloud.Bigquery.V2.Model.TrainingRun.IterationResult, deprecated: false ) field(:evaluation_metrics, 7, type: Google.Cloud.Bigquery.V2.Model.EvaluationMetrics, json_name: "evaluationMetrics", deprecated: false ) field(:data_split_result, 9, type: Google.Cloud.Bigquery.V2.Model.DataSplitResult, json_name: "dataSplitResult", deprecated: false ) field(:model_level_global_explanation, 11, type: Google.Cloud.Bigquery.V2.Model.GlobalExplanation, json_name: "modelLevelGlobalExplanation", deprecated: false ) field(:class_level_global_explanations, 12, repeated: true, type: Google.Cloud.Bigquery.V2.Model.GlobalExplanation, json_name: "classLevelGlobalExplanations", deprecated: false ) field(:vertex_ai_model_id, 14, type: :string, json_name: "vertexAiModelId") field(:vertex_ai_model_version, 15, type: :string, json_name: "vertexAiModelVersion", deprecated: false ) end defmodule Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace.DoubleRange do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:min, 1, type: Google.Protobuf.DoubleValue) field(:max, 2, type: Google.Protobuf.DoubleValue) end defmodule Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace.DoubleCandidates do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:candidates, 1, repeated: true, type: Google.Protobuf.DoubleValue) end defmodule Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 oneof(:search_space, 0) field(:range, 1, type: Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace.DoubleRange, oneof: 0 ) field(:candidates, 2, type: Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace.DoubleCandidates, oneof: 0 ) end defmodule Google.Cloud.Bigquery.V2.Model.IntHparamSearchSpace.IntRange do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:min, 1, type: Google.Protobuf.Int64Value) field(:max, 2, type: Google.Protobuf.Int64Value) end defmodule Google.Cloud.Bigquery.V2.Model.IntHparamSearchSpace.IntCandidates do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:candidates, 1, repeated: true, type: Google.Protobuf.Int64Value) end defmodule Google.Cloud.Bigquery.V2.Model.IntHparamSearchSpace do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 oneof(:search_space, 0) field(:range, 1, type: Google.Cloud.Bigquery.V2.Model.IntHparamSearchSpace.IntRange, oneof: 0) field(:candidates, 2, type: Google.Cloud.Bigquery.V2.Model.IntHparamSearchSpace.IntCandidates, oneof: 0 ) end defmodule Google.Cloud.Bigquery.V2.Model.StringHparamSearchSpace do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:candidates, 1, repeated: true, type: :string) end defmodule Google.Cloud.Bigquery.V2.Model.IntArrayHparamSearchSpace.IntArray do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:elements, 1, repeated: true, type: :int64) end defmodule Google.Cloud.Bigquery.V2.Model.IntArrayHparamSearchSpace do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:candidates, 1, repeated: true, type: Google.Cloud.Bigquery.V2.Model.IntArrayHparamSearchSpace.IntArray ) end defmodule Google.Cloud.Bigquery.V2.Model.HparamSearchSpaces do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:learn_rate, 2, type: Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace, json_name: "learnRate" ) field(:l1_reg, 3, type: Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace, json_name: "l1Reg" ) field(:l2_reg, 4, type: Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace, json_name: "l2Reg" ) field(:num_clusters, 26, type: Google.Cloud.Bigquery.V2.Model.IntHparamSearchSpace, json_name: "numClusters" ) field(:num_factors, 31, type: Google.Cloud.Bigquery.V2.Model.IntHparamSearchSpace, json_name: "numFactors" ) field(:hidden_units, 34, type: Google.Cloud.Bigquery.V2.Model.IntArrayHparamSearchSpace, json_name: "hiddenUnits" ) field(:batch_size, 37, type: Google.Cloud.Bigquery.V2.Model.IntHparamSearchSpace, json_name: "batchSize" ) field(:dropout, 38, type: Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace) field(:max_tree_depth, 41, type: Google.Cloud.Bigquery.V2.Model.IntHparamSearchSpace, json_name: "maxTreeDepth" ) field(:subsample, 42, type: Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace) field(:min_split_loss, 43, type: Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace, json_name: "minSplitLoss" ) field(:wals_alpha, 49, type: Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace, json_name: "walsAlpha" ) field(:booster_type, 56, type: Google.Cloud.Bigquery.V2.Model.StringHparamSearchSpace, json_name: "boosterType" ) field(:num_parallel_tree, 57, type: Google.Cloud.Bigquery.V2.Model.IntHparamSearchSpace, json_name: "numParallelTree" ) field(:dart_normalize_type, 58, type: Google.Cloud.Bigquery.V2.Model.StringHparamSearchSpace, json_name: "dartNormalizeType" ) field(:tree_method, 59, type: Google.Cloud.Bigquery.V2.Model.StringHparamSearchSpace, json_name: "treeMethod" ) field(:min_tree_child_weight, 60, type: Google.Cloud.Bigquery.V2.Model.IntHparamSearchSpace, json_name: "minTreeChildWeight" ) field(:colsample_bytree, 61, type: Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace, json_name: "colsampleBytree" ) field(:colsample_bylevel, 62, type: Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace, json_name: "colsampleBylevel" ) field(:colsample_bynode, 63, type: Google.Cloud.Bigquery.V2.Model.DoubleHparamSearchSpace, json_name: "colsampleBynode" ) field(:activation_fn, 67, type: Google.Cloud.Bigquery.V2.Model.StringHparamSearchSpace, json_name: "activationFn" ) field(:optimizer, 68, type: Google.Cloud.Bigquery.V2.Model.StringHparamSearchSpace) end defmodule Google.Cloud.Bigquery.V2.Model.HparamTuningTrial do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:trial_id, 1, type: :int64, json_name: "trialId") field(:start_time_ms, 2, type: :int64, json_name: "startTimeMs") field(:end_time_ms, 3, type: :int64, json_name: "endTimeMs") field(:hparams, 4, type: Google.Cloud.Bigquery.V2.Model.TrainingRun.TrainingOptions) field(:evaluation_metrics, 5, type: Google.Cloud.Bigquery.V2.Model.EvaluationMetrics, json_name: "evaluationMetrics" ) field(:status, 6, type: Google.Cloud.Bigquery.V2.Model.HparamTuningTrial.TrialStatus, enum: true ) field(:error_message, 7, type: :string, json_name: "errorMessage") field(:training_loss, 8, type: Google.Protobuf.DoubleValue, json_name: "trainingLoss") field(:eval_loss, 9, type: Google.Protobuf.DoubleValue, json_name: "evalLoss") field(:hparam_tuning_evaluation_metrics, 10, type: Google.Cloud.Bigquery.V2.Model.EvaluationMetrics, json_name: "hparamTuningEvaluationMetrics" ) end defmodule Google.Cloud.Bigquery.V2.Model.LabelsEntry do @moduledoc false use Protobuf, map: true, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:key, 1, type: :string) field(:value, 2, type: :string) end defmodule Google.Cloud.Bigquery.V2.Model do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:etag, 1, type: :string, deprecated: false) field(:model_reference, 2, type: Google.Cloud.Bigquery.V2.ModelReference, json_name: "modelReference", deprecated: false ) field(:creation_time, 5, type: :int64, json_name: "creationTime", deprecated: false) field(:last_modified_time, 6, type: :int64, json_name: "lastModifiedTime", deprecated: false) field(:description, 12, type: :string, deprecated: false) field(:friendly_name, 14, type: :string, json_name: "friendlyName", deprecated: false) field(:labels, 15, repeated: true, type: Google.Cloud.Bigquery.V2.Model.LabelsEntry, map: true) field(:expiration_time, 16, type: :int64, json_name: "expirationTime", deprecated: false) field(:location, 13, type: :string, deprecated: false) field(:encryption_configuration, 17, type: Google.Cloud.Bigquery.V2.EncryptionConfiguration, json_name: "encryptionConfiguration" ) field(:model_type, 7, type: Google.Cloud.Bigquery.V2.Model.ModelType, json_name: "modelType", enum: true, deprecated: false ) field(:training_runs, 9, repeated: true, type: Google.Cloud.Bigquery.V2.Model.TrainingRun, json_name: "trainingRuns" ) field(:feature_columns, 10, repeated: true, type: Google.Cloud.Bigquery.V2.StandardSqlField, json_name: "featureColumns", deprecated: false ) field(:label_columns, 11, repeated: true, type: Google.Cloud.Bigquery.V2.StandardSqlField, json_name: "labelColumns", deprecated: false ) field(:transform_columns, 26, repeated: true, type: Google.Cloud.Bigquery.V2.TransformColumn, json_name: "transformColumns", deprecated: false ) field(:hparam_search_spaces, 18, type: Google.Cloud.Bigquery.V2.Model.HparamSearchSpaces, json_name: "hparamSearchSpaces", deprecated: false ) field(:default_trial_id, 21, type: :int64, json_name: "defaultTrialId", deprecated: false) field(:hparam_trials, 20, repeated: true, type: Google.Cloud.Bigquery.V2.Model.HparamTuningTrial, json_name: "hparamTrials", deprecated: false ) field(:optimal_trial_ids, 22, repeated: true, type: :int64, json_name: "optimalTrialIds", deprecated: false ) field(:remote_model_info, 25, type: Google.Cloud.Bigquery.V2.RemoteModelInfo, json_name: "remoteModelInfo", deprecated: false ) end defmodule Google.Cloud.Bigquery.V2.GetModelRequest do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:project_id, 1, type: :string, json_name: "projectId", deprecated: false) field(:dataset_id, 2, type: :string, json_name: "datasetId", deprecated: false) field(:model_id, 3, type: :string, json_name: "modelId", deprecated: false) end defmodule Google.Cloud.Bigquery.V2.PatchModelRequest do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:project_id, 1, type: :string, json_name: "projectId", deprecated: false) field(:dataset_id, 2, type: :string, json_name: "datasetId", deprecated: false) field(:model_id, 3, type: :string, json_name: "modelId", deprecated: false) field(:model, 4, type: Google.Cloud.Bigquery.V2.Model, deprecated: false) end defmodule Google.Cloud.Bigquery.V2.DeleteModelRequest do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:project_id, 1, type: :string, json_name: "projectId", deprecated: false) field(:dataset_id, 2, type: :string, json_name: "datasetId", deprecated: false) field(:model_id, 3, type: :string, json_name: "modelId", deprecated: false) end defmodule Google.Cloud.Bigquery.V2.ListModelsRequest do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:project_id, 1, type: :string, json_name: "projectId", deprecated: false) field(:dataset_id, 2, type: :string, json_name: "datasetId", deprecated: false) field(:max_results, 3, type: Google.Protobuf.UInt32Value, json_name: "maxResults") field(:page_token, 4, type: :string, json_name: "pageToken") end defmodule Google.Cloud.Bigquery.V2.ListModelsResponse do @moduledoc false use Protobuf, protoc_gen_elixir_version: "0.15.0", syntax: :proto3 field(:models, 1, repeated: true, type: Google.Cloud.Bigquery.V2.Model) field(:next_page_token, 2, type: :string, json_name: "nextPageToken") end defmodule Google.Cloud.Bigquery.V2.ModelService.Service do @moduledoc false use GRPC.Service, name: "google.cloud.bigquery.v2.ModelService", protoc_gen_elixir_version: "0.15.0" rpc(:GetModel, Google.Cloud.Bigquery.V2.GetModelRequest, Google.Cloud.Bigquery.V2.Model) rpc( :ListModels, Google.Cloud.Bigquery.V2.ListModelsRequest, Google.Cloud.Bigquery.V2.ListModelsResponse ) rpc(:PatchModel, Google.Cloud.Bigquery.V2.PatchModelRequest, Google.Cloud.Bigquery.V2.Model) rpc(:DeleteModel, Google.Cloud.Bigquery.V2.DeleteModelRequest, Google.Protobuf.Empty) end defmodule Google.Cloud.Bigquery.V2.ModelService.Stub do @moduledoc false use GRPC.Stub, service: Google.Cloud.Bigquery.V2.ModelService.Service end