diff --git a/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/java/com/google/cloud/automl/v1beta1/Tables.java b/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/java/com/google/cloud/automl/v1beta1/Tables.java
index d5688682a187..6f66bc9a263c 100644
--- a/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/java/com/google/cloud/automl/v1beta1/Tables.java
+++ b/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/java/com/google/cloud/automl/v1beta1/Tables.java
@@ -62,30 +62,34 @@ public static com.google.protobuf.Descriptors.FileDescriptor getDescriptor() {
+ "ate_time\030\007 \001(\0132\032.google.protobuf.Timesta"
+ "mp\032n\n\035TargetColumnCorrelationsEntry\022\013\n\003k"
+ "ey\030\001 \001(\t\022<\n\005value\030\002 \001(\0132-.google.cloud.a"
- + "utoml.v1beta1.CorrelationStats:\0028\001\"\211\003\n\023T"
+ + "utoml.v1beta1.CorrelationStats:\0028\001\"\226\004\n\023T"
+ "ablesModelMetadata\022C\n\022target_column_spec"
+ "\030\002 \001(\0132\'.google.cloud.automl.v1beta1.Col"
+ "umnSpec\022K\n\032input_feature_column_specs\030\003 "
+ "\003(\0132\'.google.cloud.automl.v1beta1.Column"
- + "Spec\022\036\n\026optimization_objective\030\004 \001(\t\022T\n\030"
- + "tables_model_column_info\030\005 \003(\01322.google."
- + "cloud.automl.v1beta1.TablesModelColumnIn"
- + "fo\022%\n\035train_budget_milli_node_hours\030\006 \001("
- + "\003\022#\n\033train_cost_milli_node_hours\030\007 \001(\003\022\036"
- + "\n\026disable_early_stopping\030\014 \001(\010\"\345\001\n\020Table"
- + "sAnnotation\022\r\n\005score\030\001 \001(\002\022E\n\023prediction"
- + "_interval\030\004 \001(\0132(.google.cloud.automl.v1"
- + "beta1.DoubleRange\022%\n\005value\030\002 \001(\0132\026.googl"
- + "e.protobuf.Value\022T\n\030tables_model_column_"
- + "info\030\003 \003(\01322.google.cloud.automl.v1beta1"
- + ".TablesModelColumnInfo\"j\n\025TablesModelCol"
- + "umnInfo\022\030\n\020column_spec_name\030\001 \001(\t\022\033\n\023col"
- + "umn_display_name\030\002 \001(\t\022\032\n\022feature_import"
- + "ance\030\003 \001(\002B\245\001\n\037com.google.cloud.automl.v"
- + "1beta1P\001ZAgoogle.golang.org/genproto/goo"
- + "gleapis/cloud/automl/v1beta1;automl\312\002\033Go"
- + "ogle\\Cloud\\AutoMl\\V1beta1\352\002\036Google::Clou"
- + "d::AutoML::V1beta1b\006proto3"
+ + "Spec\022\036\n\026optimization_objective\030\004 \001(\t\022-\n#"
+ + "optimization_objective_recall_value\030\021 \001("
+ + "\002H\000\0220\n&optimization_objective_precision_"
+ + "value\030\022 \001(\002H\000\022T\n\030tables_model_column_inf"
+ + "o\030\005 \003(\01322.google.cloud.automl.v1beta1.Ta"
+ + "blesModelColumnInfo\022%\n\035train_budget_mill"
+ + "i_node_hours\030\006 \001(\003\022#\n\033train_cost_milli_n"
+ + "ode_hours\030\007 \001(\003\022\036\n\026disable_early_stoppin"
+ + "g\030\014 \001(\010B*\n(additional_optimization_objec"
+ + "tive_config\"\345\001\n\020TablesAnnotation\022\r\n\005scor"
+ + "e\030\001 \001(\002\022E\n\023prediction_interval\030\004 \001(\0132(.g"
+ + "oogle.cloud.automl.v1beta1.DoubleRange\022%"
+ + "\n\005value\030\002 \001(\0132\026.google.protobuf.Value\022T\n"
+ + "\030tables_model_column_info\030\003 \003(\01322.google"
+ + ".cloud.automl.v1beta1.TablesModelColumnI"
+ + "nfo\"j\n\025TablesModelColumnInfo\022\030\n\020column_s"
+ + "pec_name\030\001 \001(\t\022\033\n\023column_display_name\030\002 "
+ + "\001(\t\022\032\n\022feature_importance\030\003 \001(\002B\245\001\n\037com."
+ + "google.cloud.automl.v1beta1P\001ZAgoogle.go"
+ + "lang.org/genproto/googleapis/cloud/autom"
+ + "l/v1beta1;automl\312\002\033Google\\Cloud\\AutoMl\\V"
+ + "1beta1\352\002\036Google::Cloud::AutoML::V1beta1b"
+ + "\006proto3"
};
com.google.protobuf.Descriptors.FileDescriptor.InternalDescriptorAssigner assigner =
new com.google.protobuf.Descriptors.FileDescriptor.InternalDescriptorAssigner() {
@@ -141,10 +145,13 @@ public com.google.protobuf.ExtensionRegistry assignDescriptors(
"TargetColumnSpec",
"InputFeatureColumnSpecs",
"OptimizationObjective",
+ "OptimizationObjectiveRecallValue",
+ "OptimizationObjectivePrecisionValue",
"TablesModelColumnInfo",
"TrainBudgetMilliNodeHours",
"TrainCostMilliNodeHours",
"DisableEarlyStopping",
+ "AdditionalOptimizationObjectiveConfig",
});
internal_static_google_cloud_automl_v1beta1_TablesAnnotation_descriptor =
getDescriptor().getMessageTypes().get(2);
diff --git a/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/java/com/google/cloud/automl/v1beta1/TablesModelMetadata.java b/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/java/com/google/cloud/automl/v1beta1/TablesModelMetadata.java
index c756b6906439..aa8324fd00ec 100644
--- a/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/java/com/google/cloud/automl/v1beta1/TablesModelMetadata.java
+++ b/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/java/com/google/cloud/automl/v1beta1/TablesModelMetadata.java
@@ -89,11 +89,11 @@ private TablesModelMetadata(
}
case 42:
{
- if (!((mutable_bitField0_ & 0x00000008) != 0)) {
+ if (!((mutable_bitField0_ & 0x00000020) != 0)) {
tablesModelColumnInfo_ =
new java.util.ArrayList<
com.google.cloud.automl.v1beta1.TablesModelColumnInfo>();
- mutable_bitField0_ |= 0x00000008;
+ mutable_bitField0_ |= 0x00000020;
}
tablesModelColumnInfo_.add(
input.readMessage(
@@ -116,6 +116,18 @@ private TablesModelMetadata(
disableEarlyStopping_ = input.readBool();
break;
}
+ case 141:
+ {
+ additionalOptimizationObjectiveConfigCase_ = 17;
+ additionalOptimizationObjectiveConfig_ = input.readFloat();
+ break;
+ }
+ case 149:
+ {
+ additionalOptimizationObjectiveConfigCase_ = 18;
+ additionalOptimizationObjectiveConfig_ = input.readFloat();
+ break;
+ }
default:
{
if (!parseUnknownField(input, unknownFields, extensionRegistry, tag)) {
@@ -133,7 +145,7 @@ private TablesModelMetadata(
if (((mutable_bitField0_ & 0x00000002) != 0)) {
inputFeatureColumnSpecs_ = java.util.Collections.unmodifiableList(inputFeatureColumnSpecs_);
}
- if (((mutable_bitField0_ & 0x00000008) != 0)) {
+ if (((mutable_bitField0_ & 0x00000020) != 0)) {
tablesModelColumnInfo_ = java.util.Collections.unmodifiableList(tablesModelColumnInfo_);
}
this.unknownFields = unknownFields.build();
@@ -157,6 +169,48 @@ public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
}
private int bitField0_;
+ private int additionalOptimizationObjectiveConfigCase_ = 0;
+ private java.lang.Object additionalOptimizationObjectiveConfig_;
+
+ public enum AdditionalOptimizationObjectiveConfigCase
+ implements com.google.protobuf.Internal.EnumLite {
+ OPTIMIZATION_OBJECTIVE_RECALL_VALUE(17),
+ OPTIMIZATION_OBJECTIVE_PRECISION_VALUE(18),
+ ADDITIONALOPTIMIZATIONOBJECTIVECONFIG_NOT_SET(0);
+ private final int value;
+
+ private AdditionalOptimizationObjectiveConfigCase(int value) {
+ this.value = value;
+ }
+ /** @deprecated Use {@link #forNumber(int)} instead. */
+ @java.lang.Deprecated
+ public static AdditionalOptimizationObjectiveConfigCase valueOf(int value) {
+ return forNumber(value);
+ }
+
+ public static AdditionalOptimizationObjectiveConfigCase forNumber(int value) {
+ switch (value) {
+ case 17:
+ return OPTIMIZATION_OBJECTIVE_RECALL_VALUE;
+ case 18:
+ return OPTIMIZATION_OBJECTIVE_PRECISION_VALUE;
+ case 0:
+ return ADDITIONALOPTIMIZATIONOBJECTIVECONFIG_NOT_SET;
+ default:
+ return null;
+ }
+ }
+
+ public int getNumber() {
+ return this.value;
+ }
+ };
+
+ public AdditionalOptimizationObjectiveConfigCase getAdditionalOptimizationObjectiveConfigCase() {
+ return AdditionalOptimizationObjectiveConfigCase.forNumber(
+ additionalOptimizationObjectiveConfigCase_);
+ }
+
public static final int TARGET_COLUMN_SPEC_FIELD_NUMBER = 2;
private com.google.cloud.automl.v1beta1.ColumnSpec targetColumnSpec_;
/**
@@ -374,6 +428,10 @@ public com.google.cloud.automl.v1beta1.ColumnSpecOrBuilder getInputFeatureColumn
* 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:
@@ -412,6 +470,10 @@ public java.lang.String getOptimizationObjective() {
* 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:
@@ -437,6 +499,42 @@ public com.google.protobuf.ByteString getOptimizationObjectiveBytes() {
}
}
+ public static final int OPTIMIZATION_OBJECTIVE_RECALL_VALUE_FIELD_NUMBER = 17;
+ /**
+ *
+ *
+ *
+ * Required when optimization_objective is "MAXIMIZE_PRECISION_AT_RECALL".
+ * Must be between 0 and 1, inclusive.
+ *
+ *
+ * float optimization_objective_recall_value = 17;
+ */
+ public float getOptimizationObjectiveRecallValue() {
+ if (additionalOptimizationObjectiveConfigCase_ == 17) {
+ return (java.lang.Float) additionalOptimizationObjectiveConfig_;
+ }
+ return 0F;
+ }
+
+ public static final int OPTIMIZATION_OBJECTIVE_PRECISION_VALUE_FIELD_NUMBER = 18;
+ /**
+ *
+ *
+ *
+ * Required when optimization_objective is "MAXIMIZE_RECALL_AT_PRECISION".
+ * Must be between 0 and 1, inclusive.
+ *
+ *
+ * float optimization_objective_precision_value = 18;
+ */
+ public float getOptimizationObjectivePrecisionValue() {
+ if (additionalOptimizationObjectiveConfigCase_ == 18) {
+ return (java.lang.Float) additionalOptimizationObjectiveConfig_;
+ }
+ return 0F;
+ }
+
public static final int TABLES_MODEL_COLUMN_INFO_FIELD_NUMBER = 5;
private java.util.List
tablesModelColumnInfo_;
@@ -608,6 +706,12 @@ public void writeTo(com.google.protobuf.CodedOutputStream output) throws java.io
if (disableEarlyStopping_ != false) {
output.writeBool(12, disableEarlyStopping_);
}
+ if (additionalOptimizationObjectiveConfigCase_ == 17) {
+ output.writeFloat(17, (float) ((java.lang.Float) additionalOptimizationObjectiveConfig_));
+ }
+ if (additionalOptimizationObjectiveConfigCase_ == 18) {
+ output.writeFloat(18, (float) ((java.lang.Float) additionalOptimizationObjectiveConfig_));
+ }
unknownFields.writeTo(output);
}
@@ -642,6 +746,16 @@ public int getSerializedSize() {
if (disableEarlyStopping_ != false) {
size += com.google.protobuf.CodedOutputStream.computeBoolSize(12, disableEarlyStopping_);
}
+ if (additionalOptimizationObjectiveConfigCase_ == 17) {
+ size +=
+ com.google.protobuf.CodedOutputStream.computeFloatSize(
+ 17, (float) ((java.lang.Float) additionalOptimizationObjectiveConfig_));
+ }
+ if (additionalOptimizationObjectiveConfigCase_ == 18) {
+ size +=
+ com.google.protobuf.CodedOutputStream.computeFloatSize(
+ 18, (float) ((java.lang.Float) additionalOptimizationObjectiveConfig_));
+ }
size += unknownFields.getSerializedSize();
memoizedSize = size;
return size;
@@ -669,6 +783,22 @@ public boolean equals(final java.lang.Object obj) {
if (getTrainBudgetMilliNodeHours() != other.getTrainBudgetMilliNodeHours()) return false;
if (getTrainCostMilliNodeHours() != other.getTrainCostMilliNodeHours()) return false;
if (getDisableEarlyStopping() != other.getDisableEarlyStopping()) return false;
+ if (!getAdditionalOptimizationObjectiveConfigCase()
+ .equals(other.getAdditionalOptimizationObjectiveConfigCase())) return false;
+ switch (additionalOptimizationObjectiveConfigCase_) {
+ case 17:
+ if (java.lang.Float.floatToIntBits(getOptimizationObjectiveRecallValue())
+ != java.lang.Float.floatToIntBits(other.getOptimizationObjectiveRecallValue()))
+ return false;
+ break;
+ case 18:
+ if (java.lang.Float.floatToIntBits(getOptimizationObjectivePrecisionValue())
+ != java.lang.Float.floatToIntBits(other.getOptimizationObjectivePrecisionValue()))
+ return false;
+ break;
+ case 0:
+ default:
+ }
if (!unknownFields.equals(other.unknownFields)) return false;
return true;
}
@@ -700,6 +830,19 @@ public int hashCode() {
hash = (53 * hash) + com.google.protobuf.Internal.hashLong(getTrainCostMilliNodeHours());
hash = (37 * hash) + DISABLE_EARLY_STOPPING_FIELD_NUMBER;
hash = (53 * hash) + com.google.protobuf.Internal.hashBoolean(getDisableEarlyStopping());
+ switch (additionalOptimizationObjectiveConfigCase_) {
+ case 17:
+ hash = (37 * hash) + OPTIMIZATION_OBJECTIVE_RECALL_VALUE_FIELD_NUMBER;
+ hash = (53 * hash) + java.lang.Float.floatToIntBits(getOptimizationObjectiveRecallValue());
+ break;
+ case 18:
+ hash = (37 * hash) + OPTIMIZATION_OBJECTIVE_PRECISION_VALUE_FIELD_NUMBER;
+ hash =
+ (53 * hash) + java.lang.Float.floatToIntBits(getOptimizationObjectivePrecisionValue());
+ break;
+ case 0:
+ default:
+ }
hash = (29 * hash) + unknownFields.hashCode();
memoizedHashCode = hash;
return hash;
@@ -864,7 +1007,7 @@ public Builder clear() {
if (tablesModelColumnInfoBuilder_ == null) {
tablesModelColumnInfo_ = java.util.Collections.emptyList();
- bitField0_ = (bitField0_ & ~0x00000008);
+ bitField0_ = (bitField0_ & ~0x00000020);
} else {
tablesModelColumnInfoBuilder_.clear();
}
@@ -874,6 +1017,8 @@ public Builder clear() {
disableEarlyStopping_ = false;
+ additionalOptimizationObjectiveConfigCase_ = 0;
+ additionalOptimizationObjectiveConfig_ = null;
return this;
}
@@ -919,10 +1064,16 @@ public com.google.cloud.automl.v1beta1.TablesModelMetadata buildPartial() {
result.inputFeatureColumnSpecs_ = inputFeatureColumnSpecsBuilder_.build();
}
result.optimizationObjective_ = optimizationObjective_;
+ if (additionalOptimizationObjectiveConfigCase_ == 17) {
+ result.additionalOptimizationObjectiveConfig_ = additionalOptimizationObjectiveConfig_;
+ }
+ if (additionalOptimizationObjectiveConfigCase_ == 18) {
+ result.additionalOptimizationObjectiveConfig_ = additionalOptimizationObjectiveConfig_;
+ }
if (tablesModelColumnInfoBuilder_ == null) {
- if (((bitField0_ & 0x00000008) != 0)) {
+ if (((bitField0_ & 0x00000020) != 0)) {
tablesModelColumnInfo_ = java.util.Collections.unmodifiableList(tablesModelColumnInfo_);
- bitField0_ = (bitField0_ & ~0x00000008);
+ bitField0_ = (bitField0_ & ~0x00000020);
}
result.tablesModelColumnInfo_ = tablesModelColumnInfo_;
} else {
@@ -932,6 +1083,8 @@ public com.google.cloud.automl.v1beta1.TablesModelMetadata buildPartial() {
result.trainCostMilliNodeHours_ = trainCostMilliNodeHours_;
result.disableEarlyStopping_ = disableEarlyStopping_;
result.bitField0_ = to_bitField0_;
+ result.additionalOptimizationObjectiveConfigCase_ =
+ additionalOptimizationObjectiveConfigCase_;
onBuilt();
return result;
}
@@ -1020,7 +1173,7 @@ public Builder mergeFrom(com.google.cloud.automl.v1beta1.TablesModelMetadata oth
if (!other.tablesModelColumnInfo_.isEmpty()) {
if (tablesModelColumnInfo_.isEmpty()) {
tablesModelColumnInfo_ = other.tablesModelColumnInfo_;
- bitField0_ = (bitField0_ & ~0x00000008);
+ bitField0_ = (bitField0_ & ~0x00000020);
} else {
ensureTablesModelColumnInfoIsMutable();
tablesModelColumnInfo_.addAll(other.tablesModelColumnInfo_);
@@ -1033,7 +1186,7 @@ public Builder mergeFrom(com.google.cloud.automl.v1beta1.TablesModelMetadata oth
tablesModelColumnInfoBuilder_.dispose();
tablesModelColumnInfoBuilder_ = null;
tablesModelColumnInfo_ = other.tablesModelColumnInfo_;
- bitField0_ = (bitField0_ & ~0x00000008);
+ bitField0_ = (bitField0_ & ~0x00000020);
tablesModelColumnInfoBuilder_ =
com.google.protobuf.GeneratedMessageV3.alwaysUseFieldBuilders
? getTablesModelColumnInfoFieldBuilder()
@@ -1052,6 +1205,22 @@ public Builder mergeFrom(com.google.cloud.automl.v1beta1.TablesModelMetadata oth
if (other.getDisableEarlyStopping() != false) {
setDisableEarlyStopping(other.getDisableEarlyStopping());
}
+ switch (other.getAdditionalOptimizationObjectiveConfigCase()) {
+ case OPTIMIZATION_OBJECTIVE_RECALL_VALUE:
+ {
+ setOptimizationObjectiveRecallValue(other.getOptimizationObjectiveRecallValue());
+ break;
+ }
+ case OPTIMIZATION_OBJECTIVE_PRECISION_VALUE:
+ {
+ setOptimizationObjectivePrecisionValue(other.getOptimizationObjectivePrecisionValue());
+ break;
+ }
+ case ADDITIONALOPTIMIZATIONOBJECTIVECONFIG_NOT_SET:
+ {
+ break;
+ }
+ }
this.mergeUnknownFields(other.unknownFields);
onChanged();
return this;
@@ -1082,6 +1251,22 @@ public Builder mergeFrom(
return this;
}
+ private int additionalOptimizationObjectiveConfigCase_ = 0;
+ private java.lang.Object additionalOptimizationObjectiveConfig_;
+
+ public AdditionalOptimizationObjectiveConfigCase
+ getAdditionalOptimizationObjectiveConfigCase() {
+ return AdditionalOptimizationObjectiveConfigCase.forNumber(
+ additionalOptimizationObjectiveConfigCase_);
+ }
+
+ public Builder clearAdditionalOptimizationObjectiveConfig() {
+ additionalOptimizationObjectiveConfigCase_ = 0;
+ additionalOptimizationObjectiveConfig_ = null;
+ onChanged();
+ return this;
+ }
+
private int bitField0_;
private com.google.cloud.automl.v1beta1.ColumnSpec targetColumnSpec_;
@@ -1966,6 +2151,10 @@ public com.google.cloud.automl.v1beta1.ColumnSpec.Builder addInputFeatureColumnS
* 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:
@@ -2004,6 +2193,10 @@ public java.lang.String getOptimizationObjective() {
* 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:
@@ -2042,6 +2235,10 @@ public com.google.protobuf.ByteString getOptimizationObjectiveBytes() {
* 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:
@@ -2078,6 +2275,10 @@ public Builder setOptimizationObjective(java.lang.String value) {
* 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:
@@ -2111,6 +2312,10 @@ public Builder clearOptimizationObjective() {
* 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:
@@ -2135,15 +2340,117 @@ public Builder setOptimizationObjectiveBytes(com.google.protobuf.ByteString valu
return this;
}
+ /**
+ *
+ *
+ *
+ * Required when optimization_objective is "MAXIMIZE_PRECISION_AT_RECALL".
+ * Must be between 0 and 1, inclusive.
+ *
+ *
+ * float optimization_objective_recall_value = 17;
+ */
+ public float getOptimizationObjectiveRecallValue() {
+ if (additionalOptimizationObjectiveConfigCase_ == 17) {
+ return (java.lang.Float) additionalOptimizationObjectiveConfig_;
+ }
+ return 0F;
+ }
+ /**
+ *
+ *
+ *
+ * Required when optimization_objective is "MAXIMIZE_PRECISION_AT_RECALL".
+ * Must be between 0 and 1, inclusive.
+ *
+ *
+ * float optimization_objective_recall_value = 17;
+ */
+ public Builder setOptimizationObjectiveRecallValue(float value) {
+ additionalOptimizationObjectiveConfigCase_ = 17;
+ additionalOptimizationObjectiveConfig_ = value;
+ onChanged();
+ return this;
+ }
+ /**
+ *
+ *
+ *
+ * Required when optimization_objective is "MAXIMIZE_PRECISION_AT_RECALL".
+ * Must be between 0 and 1, inclusive.
+ *
+ *
+ * float optimization_objective_recall_value = 17;
+ */
+ public Builder clearOptimizationObjectiveRecallValue() {
+ if (additionalOptimizationObjectiveConfigCase_ == 17) {
+ additionalOptimizationObjectiveConfigCase_ = 0;
+ additionalOptimizationObjectiveConfig_ = null;
+ onChanged();
+ }
+ return this;
+ }
+
+ /**
+ *
+ *
+ *
+ * Required when optimization_objective is "MAXIMIZE_RECALL_AT_PRECISION".
+ * Must be between 0 and 1, inclusive.
+ *
+ *
+ * float optimization_objective_precision_value = 18;
+ */
+ public float getOptimizationObjectivePrecisionValue() {
+ if (additionalOptimizationObjectiveConfigCase_ == 18) {
+ return (java.lang.Float) additionalOptimizationObjectiveConfig_;
+ }
+ return 0F;
+ }
+ /**
+ *
+ *
+ *
+ * Required when optimization_objective is "MAXIMIZE_RECALL_AT_PRECISION".
+ * Must be between 0 and 1, inclusive.
+ *
+ *
+ * float optimization_objective_precision_value = 18;
+ */
+ public Builder setOptimizationObjectivePrecisionValue(float value) {
+ additionalOptimizationObjectiveConfigCase_ = 18;
+ additionalOptimizationObjectiveConfig_ = value;
+ onChanged();
+ return this;
+ }
+ /**
+ *
+ *
+ *
+ * Required when optimization_objective is "MAXIMIZE_RECALL_AT_PRECISION".
+ * Must be between 0 and 1, inclusive.
+ *
+ *
+ * float optimization_objective_precision_value = 18;
+ */
+ public Builder clearOptimizationObjectivePrecisionValue() {
+ if (additionalOptimizationObjectiveConfigCase_ == 18) {
+ additionalOptimizationObjectiveConfigCase_ = 0;
+ additionalOptimizationObjectiveConfig_ = null;
+ onChanged();
+ }
+ return this;
+ }
+
private java.util.List
tablesModelColumnInfo_ = java.util.Collections.emptyList();
private void ensureTablesModelColumnInfoIsMutable() {
- if (!((bitField0_ & 0x00000008) != 0)) {
+ if (!((bitField0_ & 0x00000020) != 0)) {
tablesModelColumnInfo_ =
new java.util.ArrayList(
tablesModelColumnInfo_);
- bitField0_ |= 0x00000008;
+ bitField0_ |= 0x00000020;
}
}
@@ -2398,7 +2705,7 @@ public Builder addAllTablesModelColumnInfo(
public Builder clearTablesModelColumnInfo() {
if (tablesModelColumnInfoBuilder_ == null) {
tablesModelColumnInfo_ = java.util.Collections.emptyList();
- bitField0_ = (bitField0_ & ~0x00000008);
+ bitField0_ = (bitField0_ & ~0x00000020);
onChanged();
} else {
tablesModelColumnInfoBuilder_.clear();
@@ -2547,7 +2854,7 @@ public Builder removeTablesModelColumnInfo(int index) {
com.google.cloud.automl.v1beta1.TablesModelColumnInfo.Builder,
com.google.cloud.automl.v1beta1.TablesModelColumnInfoOrBuilder>(
tablesModelColumnInfo_,
- ((bitField0_ & 0x00000008) != 0),
+ ((bitField0_ & 0x00000020) != 0),
getParentForChildren(),
isClean());
tablesModelColumnInfo_ = null;
diff --git a/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/java/com/google/cloud/automl/v1beta1/TablesModelMetadataOrBuilder.java b/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/java/com/google/cloud/automl/v1beta1/TablesModelMetadataOrBuilder.java
index 7f6035e26d93..2e69f32df774 100644
--- a/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/java/com/google/cloud/automl/v1beta1/TablesModelMetadataOrBuilder.java
+++ b/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/java/com/google/cloud/automl/v1beta1/TablesModelMetadataOrBuilder.java
@@ -200,6 +200,10 @@ com.google.cloud.automl.v1beta1.ColumnSpecOrBuilder getInputFeatureColumnSpecsOr
* 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:
@@ -228,6 +232,10 @@ com.google.cloud.automl.v1beta1.ColumnSpecOrBuilder getInputFeatureColumnSpecsOr
* 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:
@@ -243,6 +251,30 @@ com.google.cloud.automl.v1beta1.ColumnSpecOrBuilder getInputFeatureColumnSpecsOr
*/
com.google.protobuf.ByteString getOptimizationObjectiveBytes();
+ /**
+ *
+ *
+ *
+ * Required when optimization_objective is "MAXIMIZE_PRECISION_AT_RECALL".
+ * Must be between 0 and 1, inclusive.
+ *
+ *
+ * float optimization_objective_recall_value = 17;
+ */
+ float getOptimizationObjectiveRecallValue();
+
+ /**
+ *
+ *
+ *
+ * Required when optimization_objective is "MAXIMIZE_RECALL_AT_PRECISION".
+ * Must be between 0 and 1, inclusive.
+ *
+ *
+ * float optimization_objective_precision_value = 18;
+ */
+ float getOptimizationObjectivePrecisionValue();
+
/**
*
*
@@ -353,4 +385,8 @@ com.google.cloud.automl.v1beta1.TablesModelColumnInfoOrBuilder getTablesModelCol
* bool disable_early_stopping = 12;
*/
boolean getDisableEarlyStopping();
+
+ public com.google.cloud.automl.v1beta1.TablesModelMetadata
+ .AdditionalOptimizationObjectiveConfigCase
+ getAdditionalOptimizationObjectiveConfigCase();
}
diff --git a/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/proto/google/cloud/automl/v1beta1/tables.proto b/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/proto/google/cloud/automl/v1beta1/tables.proto
index b6403d5724f9..1cf916367faf 100644
--- a/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/proto/google/cloud/automl/v1beta1/tables.proto
+++ b/google-api-grpc/proto-google-cloud-automl-v1beta1/src/main/proto/google/cloud/automl/v1beta1/tables.proto
@@ -142,6 +142,10 @@ message TablesModelMetadata {
// 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.
@@ -157,6 +161,19 @@ message TablesModelMetadata {
// "MINIMIZE_MAE" - Minimize mean-absolute error (MAE).
string optimization_objective = 4;
+ // Additional optimization objective configuration. Required for
+ // `MAXIMIZE_PRECISION_AT_RECALL` and `MAXIMIZE_RECALL_AT_PRECISION`,
+ // otherwise unused.
+ oneof additional_optimization_objective_config {
+ // Required when optimization_objective is "MAXIMIZE_PRECISION_AT_RECALL".
+ // Must be between 0 and 1, inclusive.
+ float optimization_objective_recall_value = 17;
+
+ // Required when optimization_objective is "MAXIMIZE_RECALL_AT_PRECISION".
+ // Must be between 0 and 1, inclusive.
+ float optimization_objective_precision_value = 18;
+ }
+
// Output only. Auxiliary information for each of the
// input_feature_column_specs with respect to this particular model.
repeated TablesModelColumnInfo tables_model_column_info = 5;
diff --git a/google-cloud-clients/google-cloud-automl/synth.metadata b/google-cloud-clients/google-cloud-automl/synth.metadata
index 25b3313943ee..2b6421e0a3c0 100644
--- a/google-cloud-clients/google-cloud-automl/synth.metadata
+++ b/google-cloud-clients/google-cloud-automl/synth.metadata
@@ -1,19 +1,19 @@
{
- "updateTime": "2019-06-27T07:33:51.353859Z",
+ "updateTime": "2019-07-11T07:33:58.144304Z",
"sources": [
{
"generator": {
"name": "artman",
- "version": "0.29.1",
- "dockerImage": "googleapis/artman@sha256:b2a73f4dda03ef8fcaa973e3ba26d0cf34091f6c22c70add663af325931aef4d"
+ "version": "0.29.4",
+ "dockerImage": "googleapis/artman@sha256:63f21e83cb92680b7001dc381069e962c9e6dee314fd8365ac554c07c89221fb"
}
},
{
"git": {
"name": "googleapis",
"remote": "https://github.com/googleapis/googleapis.git",
- "sha": "f46206aff84f4b2cde590f1e0791112214f07080",
- "internalRef": "255318896"
+ "sha": "c50d9e822e19e069b7e3758736ea58cb4f35267c",
+ "internalRef": "257512381"
}
}
],