Class TablesModelMetadata (2.43.0) 

public final class TablesModelMetadata extends GeneratedMessageV3 implements TablesModelMetadataOrBuilder

Model metadata specific to AutoML Tables.

Protobuf type google.cloud.automl.v1beta1.TablesModelMetadata

Inheritance

Object > AbstractMessageLite<MessageType,BuilderType> > AbstractMessage > GeneratedMessageV3 > TablesModelMetadata

Static Fields

DISABLE_EARLY_STOPPING_FIELD_NUMBER

public static final int DISABLE_EARLY_STOPPING_FIELD_NUMBER
Field Value
Type Description
int

INPUT_FEATURE_COLUMN_SPECS_FIELD_NUMBER

public static final int INPUT_FEATURE_COLUMN_SPECS_FIELD_NUMBER
Field Value
Type Description
int

OPTIMIZATION_OBJECTIVE_FIELD_NUMBER

public static final int OPTIMIZATION_OBJECTIVE_FIELD_NUMBER
Field Value
Type Description
int

OPTIMIZATION_OBJECTIVE_PRECISION_VALUE_FIELD_NUMBER

public static final int OPTIMIZATION_OBJECTIVE_PRECISION_VALUE_FIELD_NUMBER
Field Value
Type Description
int

OPTIMIZATION_OBJECTIVE_RECALL_VALUE_FIELD_NUMBER

public static final int OPTIMIZATION_OBJECTIVE_RECALL_VALUE_FIELD_NUMBER
Field Value
Type Description
int

TABLES_MODEL_COLUMN_INFO_FIELD_NUMBER

public static final int TABLES_MODEL_COLUMN_INFO_FIELD_NUMBER
Field Value
Type Description
int

TARGET_COLUMN_SPEC_FIELD_NUMBER

public static final int TARGET_COLUMN_SPEC_FIELD_NUMBER
Field Value
Type Description
int

TRAIN_BUDGET_MILLI_NODE_HOURS_FIELD_NUMBER

public static final int TRAIN_BUDGET_MILLI_NODE_HOURS_FIELD_NUMBER
Field Value
Type Description
int

TRAIN_COST_MILLI_NODE_HOURS_FIELD_NUMBER

public static final int TRAIN_COST_MILLI_NODE_HOURS_FIELD_NUMBER
Field Value
Type Description
int

Static Methods

getDefaultInstance()

public static TablesModelMetadata getDefaultInstance()
Returns
Type Description
TablesModelMetadata

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
Type Description
Descriptor

newBuilder()

public static TablesModelMetadata.Builder newBuilder()
Returns
Type Description
TablesModelMetadata.Builder

newBuilder(TablesModelMetadata prototype)

public static TablesModelMetadata.Builder newBuilder(TablesModelMetadata prototype)
Parameter
Name Description
prototype TablesModelMetadata
Returns
Type Description
TablesModelMetadata.Builder

parseDelimitedFrom(InputStream input)

public static TablesModelMetadata parseDelimitedFrom(InputStream input)
Parameter
Name Description
input InputStream
Returns
Type Description
TablesModelMetadata
Exceptions
Type Description
IOException

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static TablesModelMetadata parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input InputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
TablesModelMetadata
Exceptions
Type Description
IOException

parseFrom(byte[] data)

public static TablesModelMetadata parseFrom(byte[] data)
Parameter
Name Description
data byte[]
Returns
Type Description
TablesModelMetadata
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

public static TablesModelMetadata parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data byte[]
extensionRegistry ExtensionRegistryLite
Returns
Type Description
TablesModelMetadata
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteString data)

public static TablesModelMetadata parseFrom(ByteString data)
Parameter
Name Description
data ByteString
Returns
Type Description
TablesModelMetadata
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

public static TablesModelMetadata parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data ByteString
extensionRegistry ExtensionRegistryLite
Returns
Type Description
TablesModelMetadata
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(CodedInputStream input)

public static TablesModelMetadata parseFrom(CodedInputStream input)
Parameter
Name Description
input CodedInputStream
Returns
Type Description
TablesModelMetadata
Exceptions
Type Description
IOException

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public static TablesModelMetadata parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input CodedInputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
TablesModelMetadata
Exceptions
Type Description
IOException

parseFrom(InputStream input)

public static TablesModelMetadata parseFrom(InputStream input)
Parameter
Name Description
input InputStream
Returns
Type Description
TablesModelMetadata
Exceptions
Type Description
IOException

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static TablesModelMetadata parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input InputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
TablesModelMetadata
Exceptions
Type Description
IOException

parseFrom(ByteBuffer data)

public static TablesModelMetadata parseFrom(ByteBuffer data)
Parameter
Name Description
data ByteBuffer
Returns
Type Description
TablesModelMetadata
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

public static TablesModelMetadata parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data ByteBuffer
extensionRegistry ExtensionRegistryLite
Returns
Type Description
TablesModelMetadata
Exceptions
Type Description
InvalidProtocolBufferException

parser()

public static Parser<TablesModelMetadata> parser()
Returns
Type Description
Parser<TablesModelMetadata>

Methods

equals(Object obj)

public boolean equals(Object obj)
Parameter
Name Description
obj Object
Returns
Type Description
boolean
Overrides

getAdditionalOptimizationObjectiveConfigCase()

public TablesModelMetadata.AdditionalOptimizationObjectiveConfigCase getAdditionalOptimizationObjectiveConfigCase()
Returns
Type Description
TablesModelMetadata.AdditionalOptimizationObjectiveConfigCase

getDefaultInstanceForType()

public TablesModelMetadata getDefaultInstanceForType()
Returns
Type Description
TablesModelMetadata

getDisableEarlyStopping()

public boolean getDisableEarlyStopping()

Use the entire training budget. This disables the early stopping feature. By default, the early stopping feature is enabled, which means that AutoML Tables might stop training before the entire training budget has been used.

bool disable_early_stopping = 12;

Returns
Type Description
boolean

The disableEarlyStopping.

getInputFeatureColumnSpecs(int index)

public ColumnSpec getInputFeatureColumnSpecs(int index)

Column specs of the dataset's primary table's columns, on which the model is trained and which are used as the input for predictions. The

target_column as well as, according to dataset's state upon model creation,

weight_column, and

ml_use_column must never be included here.

Only 3 fields are used:

  • name - May be set on CreateModel, if set only the columns specified are used, otherwise all primary table's columns (except the ones listed above) are used for the training and prediction input.

  • display_name - Output only.

  • data_type - Output only.

repeated .google.cloud.automl.v1beta1.ColumnSpec input_feature_column_specs = 3;

Parameter
Name Description
index int
Returns
Type Description
ColumnSpec

getInputFeatureColumnSpecsCount()

public int getInputFeatureColumnSpecsCount()

Column specs of the dataset's primary table's columns, on which the model is trained and which are used as the input for predictions. The

target_column as well as, according to dataset's state upon model creation,

weight_column, and

ml_use_column must never be included here.

Only 3 fields are used:

  • name - May be set on CreateModel, if set only the columns specified are used, otherwise all primary table's columns (except the ones listed above) are used for the training and prediction input.

  • display_name - Output only.

  • data_type - Output only.

repeated .google.cloud.automl.v1beta1.ColumnSpec input_feature_column_specs = 3;

Returns
Type Description
int

getInputFeatureColumnSpecsList()

public List<ColumnSpec> getInputFeatureColumnSpecsList()

Column specs of the dataset's primary table's columns, on which the model is trained and which are used as the input for predictions. The

target_column as well as, according to dataset's state upon model creation,

weight_column, and

ml_use_column must never be included here.

Only 3 fields are used:

  • name - May be set on CreateModel, if set only the columns specified are used, otherwise all primary table's columns (except the ones listed above) are used for the training and prediction input.

  • display_name - Output only.

  • data_type - Output only.

repeated .google.cloud.automl.v1beta1.ColumnSpec input_feature_column_specs = 3;

Returns
Type Description
List<ColumnSpec>

getInputFeatureColumnSpecsOrBuilder(int index)

public ColumnSpecOrBuilder getInputFeatureColumnSpecsOrBuilder(int index)

Column specs of the dataset's primary table's columns, on which the model is trained and which are used as the input for predictions. The

target_column as well as, according to dataset's state upon model creation,

weight_column, and

ml_use_column must never be included here.

Only 3 fields are used:

  • name - May be set on CreateModel, if set only the columns specified are used, otherwise all primary table's columns (except the ones listed above) are used for the training and prediction input.

  • display_name - Output only.

  • data_type - Output only.

repeated .google.cloud.automl.v1beta1.ColumnSpec input_feature_column_specs = 3;

Parameter
Name Description
index int
Returns
Type Description
ColumnSpecOrBuilder

getInputFeatureColumnSpecsOrBuilderList()

public List<? extends ColumnSpecOrBuilder> getInputFeatureColumnSpecsOrBuilderList()

Column specs of the dataset's primary table's columns, on which the model is trained and which are used as the input for predictions. The

target_column as well as, according to dataset's state upon model creation,

weight_column, and

ml_use_column must never be included here.

Only 3 fields are used:

  • name - May be set on CreateModel, if set only the columns specified are used, otherwise all primary table's columns (except the ones listed above) are used for the training and prediction input.

  • display_name - Output only.

  • data_type - Output only.

repeated .google.cloud.automl.v1beta1.ColumnSpec input_feature_column_specs = 3;

Returns
Type Description
List<? extends com.google.cloud.automl.v1beta1.ColumnSpecOrBuilder>

getOptimizationObjective()

public String getOptimizationObjective()

Objective function the model is optimizing towards. The training process creates a model that maximizes/minimizes the value of the objective function over the validation set.

The supported optimization objectives depend on the prediction type. If the field is not set, a default objective function is used.

CLASSIFICATION_BINARY: "MAXIMIZE_AU_ROC" (default) - Maximize the area under the receiver operating characteristic (ROC) curve. "MINIMIZE_LOG_LOSS" - Minimize log loss. "MAXIMIZE_AU_PRC" - Maximize the area under the precision-recall curve. "MAXIMIZE_PRECISION_AT_RECALL" - Maximize precision for a specified recall value. "MAXIMIZE_RECALL_AT_PRECISION" - Maximize recall for a specified precision value.

CLASSIFICATION_MULTI_CLASS : "MINIMIZE_LOG_LOSS" (default) - Minimize log loss.

REGRESSION: "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).

string optimization_objective = 4;

Returns
Type Description
String

The optimizationObjective.

getOptimizationObjectiveBytes()

public ByteString getOptimizationObjectiveBytes()

Objective function the model is optimizing towards. The training process creates a model that maximizes/minimizes the value of the objective function over the validation set.

The supported optimization objectives depend on the prediction type. If the field is not set, a default objective function is used.

CLASSIFICATION_BINARY: "MAXIMIZE_AU_ROC" (default) - Maximize the area under the receiver operating characteristic (ROC) curve. "MINIMIZE_LOG_LOSS" - Minimize log loss. "MAXIMIZE_AU_PRC" - Maximize the area under the precision-recall curve. "MAXIMIZE_PRECISION_AT_RECALL" - Maximize precision for a specified recall value. "MAXIMIZE_RECALL_AT_PRECISION" - Maximize recall for a specified precision value.

CLASSIFICATION_MULTI_CLASS : "MINIMIZE_LOG_LOSS" (default) - Minimize log loss.

REGRESSION: "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).

string optimization_objective = 4;

Returns
Type Description
ByteString

The bytes for optimizationObjective.

getOptimizationObjectivePrecisionValue()

public float getOptimizationObjectivePrecisionValue()

Required when optimization_objective is "MAXIMIZE_RECALL_AT_PRECISION". Must be between 0 and 1, inclusive.

float optimization_objective_precision_value = 18;

Returns
Type Description
float

The optimizationObjectivePrecisionValue.

getOptimizationObjectiveRecallValue()

public float getOptimizationObjectiveRecallValue()

Required when optimization_objective is "MAXIMIZE_PRECISION_AT_RECALL". Must be between 0 and 1, inclusive.

float optimization_objective_recall_value = 17;

Returns
Type Description
float

The optimizationObjectiveRecallValue.

getParserForType()

public Parser<TablesModelMetadata> getParserForType()
Returns
Type Description
Parser<TablesModelMetadata>
Overrides

getSerializedSize()

public int getSerializedSize()
Returns
Type Description
int
Overrides

getTablesModelColumnInfo(int index)

public TablesModelColumnInfo getTablesModelColumnInfo(int index)

Output only. Auxiliary information for each of the input_feature_column_specs with respect to this particular model.

repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 5;

Parameter
Name Description
index int
Returns
Type Description
TablesModelColumnInfo

getTablesModelColumnInfoCount()

public int getTablesModelColumnInfoCount()

Output only. Auxiliary information for each of the input_feature_column_specs with respect to this particular model.

repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 5;

Returns
Type Description
int

getTablesModelColumnInfoList()

public List<TablesModelColumnInfo> getTablesModelColumnInfoList()

Output only. Auxiliary information for each of the input_feature_column_specs with respect to this particular model.

repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 5;

Returns
Type Description
List<TablesModelColumnInfo>

getTablesModelColumnInfoOrBuilder(int index)

public TablesModelColumnInfoOrBuilder getTablesModelColumnInfoOrBuilder(int index)

Output only. Auxiliary information for each of the input_feature_column_specs with respect to this particular model.

repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 5;

Parameter
Name Description
index int
Returns
Type Description
TablesModelColumnInfoOrBuilder

getTablesModelColumnInfoOrBuilderList()

public List<? extends TablesModelColumnInfoOrBuilder> getTablesModelColumnInfoOrBuilderList()

Output only. Auxiliary information for each of the input_feature_column_specs with respect to this particular model.

repeated .google.cloud.automl.v1beta1.TablesModelColumnInfo tables_model_column_info = 5;

Returns
Type Description
List<? extends com.google.cloud.automl.v1beta1.TablesModelColumnInfoOrBuilder>

getTargetColumnSpec()

public ColumnSpec getTargetColumnSpec()

Column spec of the dataset's primary table's column the model is predicting. Snapshotted when model creation started. Only 3 fields are used: name - May be set on CreateModel, if it's not then the ColumnSpec corresponding to the current target_column_spec_id of the dataset the model is trained from is used. If neither is set, CreateModel will error. display_name - Output only. data_type - Output only.

.google.cloud.automl.v1beta1.ColumnSpec target_column_spec = 2;

Returns
Type Description
ColumnSpec

The targetColumnSpec.

getTargetColumnSpecOrBuilder()

public ColumnSpecOrBuilder getTargetColumnSpecOrBuilder()

Column spec of the dataset's primary table's column the model is predicting. Snapshotted when model creation started. Only 3 fields are used: name - May be set on CreateModel, if it's not then the ColumnSpec corresponding to the current target_column_spec_id of the dataset the model is trained from is used. If neither is set, CreateModel will error. display_name - Output only. data_type - Output only.

.google.cloud.automl.v1beta1.ColumnSpec target_column_spec = 2;

Returns
Type Description
ColumnSpecOrBuilder

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;

Returns
Type Description
long

The trainBudgetMilliNodeHours.

getTrainCostMilliNodeHours()

public long getTrainCostMilliNodeHours()

Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget.

int64 train_cost_milli_node_hours = 7;

Returns
Type Description
long

The trainCostMilliNodeHours.

hasOptimizationObjectivePrecisionValue()

public boolean hasOptimizationObjectivePrecisionValue()

Required when optimization_objective is "MAXIMIZE_RECALL_AT_PRECISION". Must be between 0 and 1, inclusive.

float optimization_objective_precision_value = 18;

Returns
Type Description
boolean

Whether the optimizationObjectivePrecisionValue field is set.

hasOptimizationObjectiveRecallValue()

public boolean hasOptimizationObjectiveRecallValue()

Required when optimization_objective is "MAXIMIZE_PRECISION_AT_RECALL". Must be between 0 and 1, inclusive.

float optimization_objective_recall_value = 17;

Returns
Type Description
boolean

Whether the optimizationObjectiveRecallValue field is set.

hasTargetColumnSpec()

public boolean hasTargetColumnSpec()

Column spec of the dataset's primary table's column the model is predicting. Snapshotted when model creation started. Only 3 fields are used: name - May be set on CreateModel, if it's not then the ColumnSpec corresponding to the current target_column_spec_id of the dataset the model is trained from is used. If neither is set, CreateModel will error. display_name - Output only. data_type - Output only.

.google.cloud.automl.v1beta1.ColumnSpec target_column_spec = 2;

Returns
Type Description
boolean

Whether the targetColumnSpec field is set.

hashCode()

public int hashCode()
Returns
Type Description
int
Overrides

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Type Description
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

newBuilderForType()

public TablesModelMetadata.Builder newBuilderForType()
Returns
Type Description
TablesModelMetadata.Builder

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

protected TablesModelMetadata.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Parameter
Name Description
parent BuilderParent
Returns
Type Description
TablesModelMetadata.Builder
Overrides

newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Parameter
Name Description
unused UnusedPrivateParameter
Returns
Type Description
Object
Overrides

toBuilder()

public TablesModelMetadata.Builder toBuilder()
Returns
Type Description
TablesModelMetadata.Builder

writeTo(CodedOutputStream output)

public void writeTo(CodedOutputStream output)
Parameter
Name Description
output CodedOutputStream
Overrides
Exceptions
Type Description
IOException