java.lang.Object
com.google.protobuf.AbstractMessageLite
com.google.protobuf.AbstractMessage
com.google.protobuf.GeneratedMessage
com.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs
All Implemented Interfaces:
AutoMlForecastingInputsOrBuilder, com.google.protobuf.Message, com.google.protobuf.MessageLite, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Serializable

@Generated public final class AutoMlForecastingInputs extends com.google.protobuf.GeneratedMessage implements AutoMlForecastingInputsOrBuilder
Protobuf type google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs
See Also:
  • Field Details

    • TARGET_COLUMN_FIELD_NUMBER

      public static final int TARGET_COLUMN_FIELD_NUMBER
      See Also:
    • TIME_SERIES_IDENTIFIER_COLUMN_FIELD_NUMBER

      public static final int TIME_SERIES_IDENTIFIER_COLUMN_FIELD_NUMBER
      See Also:
    • TIME_COLUMN_FIELD_NUMBER

      public static final int TIME_COLUMN_FIELD_NUMBER
      See Also:
    • TRANSFORMATIONS_FIELD_NUMBER

      public static final int TRANSFORMATIONS_FIELD_NUMBER
      See Also:
    • OPTIMIZATION_OBJECTIVE_FIELD_NUMBER

      public static final int OPTIMIZATION_OBJECTIVE_FIELD_NUMBER
      See Also:
    • TRAIN_BUDGET_MILLI_NODE_HOURS_FIELD_NUMBER

      public static final int TRAIN_BUDGET_MILLI_NODE_HOURS_FIELD_NUMBER
      See Also:
    • WEIGHT_COLUMN_FIELD_NUMBER

      public static final int WEIGHT_COLUMN_FIELD_NUMBER
      See Also:
    • TIME_SERIES_ATTRIBUTE_COLUMNS_FIELD_NUMBER

      public static final int TIME_SERIES_ATTRIBUTE_COLUMNS_FIELD_NUMBER
      See Also:
    • UNAVAILABLE_AT_FORECAST_COLUMNS_FIELD_NUMBER

      public static final int UNAVAILABLE_AT_FORECAST_COLUMNS_FIELD_NUMBER
      See Also:
    • AVAILABLE_AT_FORECAST_COLUMNS_FIELD_NUMBER

      public static final int AVAILABLE_AT_FORECAST_COLUMNS_FIELD_NUMBER
      See Also:
    • DATA_GRANULARITY_FIELD_NUMBER

      public static final int DATA_GRANULARITY_FIELD_NUMBER
      See Also:
    • FORECAST_HORIZON_FIELD_NUMBER

      public static final int FORECAST_HORIZON_FIELD_NUMBER
      See Also:
    • CONTEXT_WINDOW_FIELD_NUMBER

      public static final int CONTEXT_WINDOW_FIELD_NUMBER
      See Also:
    • EXPORT_EVALUATED_DATA_ITEMS_CONFIG_FIELD_NUMBER

      public static final int EXPORT_EVALUATED_DATA_ITEMS_CONFIG_FIELD_NUMBER
      See Also:
    • QUANTILES_FIELD_NUMBER

      public static final int QUANTILES_FIELD_NUMBER
      See Also:
    • VALIDATION_OPTIONS_FIELD_NUMBER

      public static final int VALIDATION_OPTIONS_FIELD_NUMBER
      See Also:
    • ADDITIONAL_EXPERIMENTS_FIELD_NUMBER

      public static final int ADDITIONAL_EXPERIMENTS_FIELD_NUMBER
      See Also:
  • Method Details

    • getDescriptor

      public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()
    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage
    • getTargetColumn

      public String getTargetColumn()
       The name of the column that the model is to predict.
       
      string target_column = 1;
      Specified by:
      getTargetColumn in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The targetColumn.
    • getTargetColumnBytes

      public com.google.protobuf.ByteString getTargetColumnBytes()
       The name of the column that the model is to predict.
       
      string target_column = 1;
      Specified by:
      getTargetColumnBytes in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The bytes for targetColumn.
    • getTimeSeriesIdentifierColumn

      public String getTimeSeriesIdentifierColumn()
       The name of the column that identifies the time series.
       
      string time_series_identifier_column = 2;
      Specified by:
      getTimeSeriesIdentifierColumn in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The timeSeriesIdentifierColumn.
    • getTimeSeriesIdentifierColumnBytes

      public com.google.protobuf.ByteString getTimeSeriesIdentifierColumnBytes()
       The name of the column that identifies the time series.
       
      string time_series_identifier_column = 2;
      Specified by:
      getTimeSeriesIdentifierColumnBytes in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The bytes for timeSeriesIdentifierColumn.
    • getTimeColumn

      public String getTimeColumn()
       The name of the column that identifies time order in the time series.
       
      string time_column = 3;
      Specified by:
      getTimeColumn in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The timeColumn.
    • getTimeColumnBytes

      public com.google.protobuf.ByteString getTimeColumnBytes()
       The name of the column that identifies time order in the time series.
       
      string time_column = 3;
      Specified by:
      getTimeColumnBytes in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The bytes for timeColumn.
    • getTransformationsList

      public List<AutoMlForecastingInputs.Transformation> getTransformationsList()
       Each transformation will apply transform function to given input column.
       And the result will be used for training.
       When creating transformation for BigQuery Struct column, the column should
       be flattened using "." as the delimiter.
       
      repeated .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation transformations = 4;
      Specified by:
      getTransformationsList in interface AutoMlForecastingInputsOrBuilder
    • getTransformationsOrBuilderList

      public List<? extends AutoMlForecastingInputs.TransformationOrBuilder> getTransformationsOrBuilderList()
       Each transformation will apply transform function to given input column.
       And the result will be used for training.
       When creating transformation for BigQuery Struct column, the column should
       be flattened using "." as the delimiter.
       
      repeated .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation transformations = 4;
      Specified by:
      getTransformationsOrBuilderList in interface AutoMlForecastingInputsOrBuilder
    • getTransformationsCount

      public int getTransformationsCount()
       Each transformation will apply transform function to given input column.
       And the result will be used for training.
       When creating transformation for BigQuery Struct column, the column should
       be flattened using "." as the delimiter.
       
      repeated .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation transformations = 4;
      Specified by:
      getTransformationsCount in interface AutoMlForecastingInputsOrBuilder
    • getTransformations

      public AutoMlForecastingInputs.Transformation getTransformations(int index)
       Each transformation will apply transform function to given input column.
       And the result will be used for training.
       When creating transformation for BigQuery Struct column, the column should
       be flattened using "." as the delimiter.
       
      repeated .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation transformations = 4;
      Specified by:
      getTransformations in interface AutoMlForecastingInputsOrBuilder
    • getTransformationsOrBuilder

      public AutoMlForecastingInputs.TransformationOrBuilder getTransformationsOrBuilder(int index)
       Each transformation will apply transform function to given input column.
       And the result will be used for training.
       When creating transformation for BigQuery Struct column, the column should
       be flattened using "." as the delimiter.
       
      repeated .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Transformation transformations = 4;
      Specified by:
      getTransformationsOrBuilder in interface AutoMlForecastingInputsOrBuilder
    • getOptimizationObjective

      public String getOptimizationObjective()
       Objective function the model is optimizing towards. The training process
       creates a model that optimizes the value of the objective
       function over the validation set.
      
       The supported optimization objectives:
      
       * "minimize-rmse" (default) - Minimize root-mean-squared error (RMSE).
      
       * "minimize-mae" - Minimize mean-absolute error (MAE).
      
       * "minimize-rmsle" - Minimize root-mean-squared log error (RMSLE).
      
       * "minimize-rmspe" - Minimize root-mean-squared percentage error (RMSPE).
      
       * "minimize-wape-mae" - Minimize the combination of weighted absolute
       percentage error (WAPE) and mean-absolute-error (MAE).
      
       * "minimize-quantile-loss" - Minimize the quantile loss at the quantiles
       defined in `quantiles`.
       
      string optimization_objective = 5;
      Specified by:
      getOptimizationObjective in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The optimizationObjective.
    • getOptimizationObjectiveBytes

      public com.google.protobuf.ByteString getOptimizationObjectiveBytes()
       Objective function the model is optimizing towards. The training process
       creates a model that optimizes the value of the objective
       function over the validation set.
      
       The supported optimization objectives:
      
       * "minimize-rmse" (default) - Minimize root-mean-squared error (RMSE).
      
       * "minimize-mae" - Minimize mean-absolute error (MAE).
      
       * "minimize-rmsle" - Minimize root-mean-squared log error (RMSLE).
      
       * "minimize-rmspe" - Minimize root-mean-squared percentage error (RMSPE).
      
       * "minimize-wape-mae" - Minimize the combination of weighted absolute
       percentage error (WAPE) and mean-absolute-error (MAE).
      
       * "minimize-quantile-loss" - Minimize the quantile loss at the quantiles
       defined in `quantiles`.
       
      string optimization_objective = 5;
      Specified by:
      getOptimizationObjectiveBytes in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The bytes for optimizationObjective.
    • getTrainBudgetMilliNodeHours

      public long getTrainBudgetMilliNodeHours()
       Required. The train budget of creating this model, expressed in milli node
       hours i.e. 1,000 value in this field means 1 node hour.
      
       The training cost of the model will not exceed this budget. The final cost
       will be attempted to be close to the budget, though may end up being (even)
       noticeably smaller - at the backend's discretion. This especially may
       happen when further model training ceases to provide any improvements.
      
       If the budget is set to a value known to be insufficient to train a
       model for the given dataset, the training won't be attempted and
       will error.
      
       The train budget must be between 1,000 and 72,000 milli node hours,
       inclusive.
       
      int64 train_budget_milli_node_hours = 6;
      Specified by:
      getTrainBudgetMilliNodeHours in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The trainBudgetMilliNodeHours.
    • getWeightColumn

      public String getWeightColumn()
       Column name that should be used as the weight column.
       Higher values in this column give more importance to the row
       during model training. The column must have numeric values between 0 and
       10000 inclusively; 0 means the row is ignored for training. If weight
       column field is not set, then all rows are assumed to have equal weight
       of 1.
       
      string weight_column = 7;
      Specified by:
      getWeightColumn in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The weightColumn.
    • getWeightColumnBytes

      public com.google.protobuf.ByteString getWeightColumnBytes()
       Column name that should be used as the weight column.
       Higher values in this column give more importance to the row
       during model training. The column must have numeric values between 0 and
       10000 inclusively; 0 means the row is ignored for training. If weight
       column field is not set, then all rows are assumed to have equal weight
       of 1.
       
      string weight_column = 7;
      Specified by:
      getWeightColumnBytes in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The bytes for weightColumn.
    • getTimeSeriesAttributeColumnsList

      public com.google.protobuf.ProtocolStringList getTimeSeriesAttributeColumnsList()
       Column names that should be used as attribute columns.
       The value of these columns does not vary as a function of time.
       For example, store ID or item color.
       
      repeated string time_series_attribute_columns = 19;
      Specified by:
      getTimeSeriesAttributeColumnsList in interface AutoMlForecastingInputsOrBuilder
      Returns:
      A list containing the timeSeriesAttributeColumns.
    • getTimeSeriesAttributeColumnsCount

      public int getTimeSeriesAttributeColumnsCount()
       Column names that should be used as attribute columns.
       The value of these columns does not vary as a function of time.
       For example, store ID or item color.
       
      repeated string time_series_attribute_columns = 19;
      Specified by:
      getTimeSeriesAttributeColumnsCount in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The count of timeSeriesAttributeColumns.
    • getTimeSeriesAttributeColumns

      public String getTimeSeriesAttributeColumns(int index)
       Column names that should be used as attribute columns.
       The value of these columns does not vary as a function of time.
       For example, store ID or item color.
       
      repeated string time_series_attribute_columns = 19;
      Specified by:
      getTimeSeriesAttributeColumns in interface AutoMlForecastingInputsOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The timeSeriesAttributeColumns at the given index.
    • getTimeSeriesAttributeColumnsBytes

      public com.google.protobuf.ByteString getTimeSeriesAttributeColumnsBytes(int index)
       Column names that should be used as attribute columns.
       The value of these columns does not vary as a function of time.
       For example, store ID or item color.
       
      repeated string time_series_attribute_columns = 19;
      Specified by:
      getTimeSeriesAttributeColumnsBytes in interface AutoMlForecastingInputsOrBuilder
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the timeSeriesAttributeColumns at the given index.
    • getUnavailableAtForecastColumnsList

      public com.google.protobuf.ProtocolStringList getUnavailableAtForecastColumnsList()
       Names of columns that are unavailable when a forecast is requested.
       This column contains information for the given entity (identified
       by the time_series_identifier_column) that is unknown before the forecast
       For example, actual weather on a given day.
       
      repeated string unavailable_at_forecast_columns = 20;
      Specified by:
      getUnavailableAtForecastColumnsList in interface AutoMlForecastingInputsOrBuilder
      Returns:
      A list containing the unavailableAtForecastColumns.
    • getUnavailableAtForecastColumnsCount

      public int getUnavailableAtForecastColumnsCount()
       Names of columns that are unavailable when a forecast is requested.
       This column contains information for the given entity (identified
       by the time_series_identifier_column) that is unknown before the forecast
       For example, actual weather on a given day.
       
      repeated string unavailable_at_forecast_columns = 20;
      Specified by:
      getUnavailableAtForecastColumnsCount in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The count of unavailableAtForecastColumns.
    • getUnavailableAtForecastColumns

      public String getUnavailableAtForecastColumns(int index)
       Names of columns that are unavailable when a forecast is requested.
       This column contains information for the given entity (identified
       by the time_series_identifier_column) that is unknown before the forecast
       For example, actual weather on a given day.
       
      repeated string unavailable_at_forecast_columns = 20;
      Specified by:
      getUnavailableAtForecastColumns in interface AutoMlForecastingInputsOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The unavailableAtForecastColumns at the given index.
    • getUnavailableAtForecastColumnsBytes

      public com.google.protobuf.ByteString getUnavailableAtForecastColumnsBytes(int index)
       Names of columns that are unavailable when a forecast is requested.
       This column contains information for the given entity (identified
       by the time_series_identifier_column) that is unknown before the forecast
       For example, actual weather on a given day.
       
      repeated string unavailable_at_forecast_columns = 20;
      Specified by:
      getUnavailableAtForecastColumnsBytes in interface AutoMlForecastingInputsOrBuilder
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the unavailableAtForecastColumns at the given index.
    • getAvailableAtForecastColumnsList

      public com.google.protobuf.ProtocolStringList getAvailableAtForecastColumnsList()
       Names of columns that are available and provided when a forecast
       is requested. These columns
       contain information for the given entity (identified by the
       time_series_identifier_column column) that is known at forecast.
       For example, predicted weather for a specific day.
       
      repeated string available_at_forecast_columns = 21;
      Specified by:
      getAvailableAtForecastColumnsList in interface AutoMlForecastingInputsOrBuilder
      Returns:
      A list containing the availableAtForecastColumns.
    • getAvailableAtForecastColumnsCount

      public int getAvailableAtForecastColumnsCount()
       Names of columns that are available and provided when a forecast
       is requested. These columns
       contain information for the given entity (identified by the
       time_series_identifier_column column) that is known at forecast.
       For example, predicted weather for a specific day.
       
      repeated string available_at_forecast_columns = 21;
      Specified by:
      getAvailableAtForecastColumnsCount in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The count of availableAtForecastColumns.
    • getAvailableAtForecastColumns

      public String getAvailableAtForecastColumns(int index)
       Names of columns that are available and provided when a forecast
       is requested. These columns
       contain information for the given entity (identified by the
       time_series_identifier_column column) that is known at forecast.
       For example, predicted weather for a specific day.
       
      repeated string available_at_forecast_columns = 21;
      Specified by:
      getAvailableAtForecastColumns in interface AutoMlForecastingInputsOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The availableAtForecastColumns at the given index.
    • getAvailableAtForecastColumnsBytes

      public com.google.protobuf.ByteString getAvailableAtForecastColumnsBytes(int index)
       Names of columns that are available and provided when a forecast
       is requested. These columns
       contain information for the given entity (identified by the
       time_series_identifier_column column) that is known at forecast.
       For example, predicted weather for a specific day.
       
      repeated string available_at_forecast_columns = 21;
      Specified by:
      getAvailableAtForecastColumnsBytes in interface AutoMlForecastingInputsOrBuilder
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the availableAtForecastColumns at the given index.
    • hasDataGranularity

      public boolean hasDataGranularity()
       Expected difference in time granularity between rows in the data.
       
      .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Granularity data_granularity = 22;
      Specified by:
      hasDataGranularity in interface AutoMlForecastingInputsOrBuilder
      Returns:
      Whether the dataGranularity field is set.
    • getDataGranularity

      public AutoMlForecastingInputs.Granularity getDataGranularity()
       Expected difference in time granularity between rows in the data.
       
      .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Granularity data_granularity = 22;
      Specified by:
      getDataGranularity in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The dataGranularity.
    • getDataGranularityOrBuilder

      public AutoMlForecastingInputs.GranularityOrBuilder getDataGranularityOrBuilder()
       Expected difference in time granularity between rows in the data.
       
      .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlForecastingInputs.Granularity data_granularity = 22;
      Specified by:
      getDataGranularityOrBuilder in interface AutoMlForecastingInputsOrBuilder
    • getForecastHorizon

      public long getForecastHorizon()
       The amount of time into the future for which forecasted values for the
       target are returned. Expressed in number of units defined by the
       `data_granularity` field.
       
      int64 forecast_horizon = 23;
      Specified by:
      getForecastHorizon in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The forecastHorizon.
    • getContextWindow

      public long getContextWindow()
       The amount of time into the past training and prediction data is used
       for model training and prediction respectively. Expressed in number of
       units defined by the `data_granularity` field.
       
      int64 context_window = 24;
      Specified by:
      getContextWindow in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The contextWindow.
    • hasExportEvaluatedDataItemsConfig

      public boolean hasExportEvaluatedDataItemsConfig()
       Configuration for exporting test set predictions to a BigQuery table. If
       this configuration is absent, then the export is not performed.
       
      .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.ExportEvaluatedDataItemsConfig export_evaluated_data_items_config = 15;
      Specified by:
      hasExportEvaluatedDataItemsConfig in interface AutoMlForecastingInputsOrBuilder
      Returns:
      Whether the exportEvaluatedDataItemsConfig field is set.
    • getExportEvaluatedDataItemsConfig

      public ExportEvaluatedDataItemsConfig getExportEvaluatedDataItemsConfig()
       Configuration for exporting test set predictions to a BigQuery table. If
       this configuration is absent, then the export is not performed.
       
      .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.ExportEvaluatedDataItemsConfig export_evaluated_data_items_config = 15;
      Specified by:
      getExportEvaluatedDataItemsConfig in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The exportEvaluatedDataItemsConfig.
    • getExportEvaluatedDataItemsConfigOrBuilder

      public ExportEvaluatedDataItemsConfigOrBuilder getExportEvaluatedDataItemsConfigOrBuilder()
       Configuration for exporting test set predictions to a BigQuery table. If
       this configuration is absent, then the export is not performed.
       
      .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.ExportEvaluatedDataItemsConfig export_evaluated_data_items_config = 15;
      Specified by:
      getExportEvaluatedDataItemsConfigOrBuilder in interface AutoMlForecastingInputsOrBuilder
    • getQuantilesList

      public List<Double> getQuantilesList()
       Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to
       5 quantiles are allowed of values between 0 and 1, exclusive. Required if
       the value of optimization_objective is minimize-quantile-loss. Represents
       the percent quantiles to use for that objective. Quantiles must be unique.
       
      repeated double quantiles = 16;
      Specified by:
      getQuantilesList in interface AutoMlForecastingInputsOrBuilder
      Returns:
      A list containing the quantiles.
    • getQuantilesCount

      public int getQuantilesCount()
       Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to
       5 quantiles are allowed of values between 0 and 1, exclusive. Required if
       the value of optimization_objective is minimize-quantile-loss. Represents
       the percent quantiles to use for that objective. Quantiles must be unique.
       
      repeated double quantiles = 16;
      Specified by:
      getQuantilesCount in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The count of quantiles.
    • getQuantiles

      public double getQuantiles(int index)
       Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to
       5 quantiles are allowed of values between 0 and 1, exclusive. Required if
       the value of optimization_objective is minimize-quantile-loss. Represents
       the percent quantiles to use for that objective. Quantiles must be unique.
       
      repeated double quantiles = 16;
      Specified by:
      getQuantiles in interface AutoMlForecastingInputsOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The quantiles at the given index.
    • getValidationOptions

      public String getValidationOptions()
       Validation options for the data validation component. The available options
       are:
      
       * "fail-pipeline" - default, will validate against the validation and
       fail the pipeline if it fails.
      
       * "ignore-validation" - ignore the results of the validation and continue
       
      string validation_options = 17;
      Specified by:
      getValidationOptions in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The validationOptions.
    • getValidationOptionsBytes

      public com.google.protobuf.ByteString getValidationOptionsBytes()
       Validation options for the data validation component. The available options
       are:
      
       * "fail-pipeline" - default, will validate against the validation and
       fail the pipeline if it fails.
      
       * "ignore-validation" - ignore the results of the validation and continue
       
      string validation_options = 17;
      Specified by:
      getValidationOptionsBytes in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The bytes for validationOptions.
    • getAdditionalExperimentsList

      public com.google.protobuf.ProtocolStringList getAdditionalExperimentsList()
       Additional experiment flags for the time series forcasting training.
       
      repeated string additional_experiments = 25;
      Specified by:
      getAdditionalExperimentsList in interface AutoMlForecastingInputsOrBuilder
      Returns:
      A list containing the additionalExperiments.
    • getAdditionalExperimentsCount

      public int getAdditionalExperimentsCount()
       Additional experiment flags for the time series forcasting training.
       
      repeated string additional_experiments = 25;
      Specified by:
      getAdditionalExperimentsCount in interface AutoMlForecastingInputsOrBuilder
      Returns:
      The count of additionalExperiments.
    • getAdditionalExperiments

      public String getAdditionalExperiments(int index)
       Additional experiment flags for the time series forcasting training.
       
      repeated string additional_experiments = 25;
      Specified by:
      getAdditionalExperiments in interface AutoMlForecastingInputsOrBuilder
      Parameters:
      index - The index of the element to return.
      Returns:
      The additionalExperiments at the given index.
    • getAdditionalExperimentsBytes

      public com.google.protobuf.ByteString getAdditionalExperimentsBytes(int index)
       Additional experiment flags for the time series forcasting training.
       
      repeated string additional_experiments = 25;
      Specified by:
      getAdditionalExperimentsBytes in interface AutoMlForecastingInputsOrBuilder
      Parameters:
      index - The index of the value to return.
      Returns:
      The bytes of the additionalExperiments at the given index.
    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessage
    • writeTo

      public void writeTo(com.google.protobuf.CodedOutputStream output) throws IOException
      Specified by:
      writeTo in interface com.google.protobuf.MessageLite
      Overrides:
      writeTo in class com.google.protobuf.GeneratedMessage
      Throws:
      IOException
    • getSerializedSize

      public int getSerializedSize()
      Specified by:
      getSerializedSize in interface com.google.protobuf.MessageLite
      Overrides:
      getSerializedSize in class com.google.protobuf.GeneratedMessage
    • equals

      public boolean equals(Object obj)
      Specified by:
      equals in interface com.google.protobuf.Message
      Overrides:
      equals in class com.google.protobuf.AbstractMessage
    • hashCode

      public int hashCode()
      Specified by:
      hashCode in interface com.google.protobuf.Message
      Overrides:
      hashCode in class com.google.protobuf.AbstractMessage
    • parseFrom

      public static AutoMlForecastingInputs parseFrom(ByteBuffer data) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException
    • parseFrom

      public static AutoMlForecastingInputs parseFrom(ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException
    • parseFrom

      public static AutoMlForecastingInputs parseFrom(com.google.protobuf.ByteString data) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException
    • parseFrom

      public static AutoMlForecastingInputs parseFrom(com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException
    • parseFrom

      public static AutoMlForecastingInputs parseFrom(byte[] data) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException
    • parseFrom

      public static AutoMlForecastingInputs parseFrom(byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException
    • parseFrom

      public static AutoMlForecastingInputs parseFrom(InputStream input) throws IOException
      Throws:
      IOException
    • parseFrom

      public static AutoMlForecastingInputs parseFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Throws:
      IOException
    • parseDelimitedFrom

      public static AutoMlForecastingInputs parseDelimitedFrom(InputStream input) throws IOException
      Throws:
      IOException
    • parseDelimitedFrom

      public static AutoMlForecastingInputs parseDelimitedFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Throws:
      IOException
    • parseFrom

      public static AutoMlForecastingInputs parseFrom(com.google.protobuf.CodedInputStream input) throws IOException
      Throws:
      IOException
    • parseFrom

      public static AutoMlForecastingInputs parseFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Throws:
      IOException
    • newBuilderForType

      public AutoMlForecastingInputs.Builder newBuilderForType()
      Specified by:
      newBuilderForType in interface com.google.protobuf.Message
      Specified by:
      newBuilderForType in interface com.google.protobuf.MessageLite
    • newBuilder

      public static AutoMlForecastingInputs.Builder newBuilder()
    • newBuilder

      public static AutoMlForecastingInputs.Builder newBuilder(AutoMlForecastingInputs prototype)
    • toBuilder

      public AutoMlForecastingInputs.Builder toBuilder()
      Specified by:
      toBuilder in interface com.google.protobuf.Message
      Specified by:
      toBuilder in interface com.google.protobuf.MessageLite
    • newBuilderForType

      protected AutoMlForecastingInputs.Builder newBuilderForType(com.google.protobuf.AbstractMessage.BuilderParent parent)
      Overrides:
      newBuilderForType in class com.google.protobuf.AbstractMessage
    • getDefaultInstance

      public static AutoMlForecastingInputs getDefaultInstance()
    • parser

      public static com.google.protobuf.Parser<AutoMlForecastingInputs> parser()
    • getParserForType

      public com.google.protobuf.Parser<AutoMlForecastingInputs> getParserForType()
      Specified by:
      getParserForType in interface com.google.protobuf.Message
      Specified by:
      getParserForType in interface com.google.protobuf.MessageLite
      Overrides:
      getParserForType in class com.google.protobuf.GeneratedMessage
    • getDefaultInstanceForType

      public AutoMlForecastingInputs getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder