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public static final class AutoMlImageClassificationInputs.Builder extends GeneratedMessageV3.Builder<AutoMlImageClassificationInputs.Builder> implements AutoMlImageClassificationInputsOrBuilder
Protobuf type
google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationInputs
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > AutoMlImageClassificationInputs.BuilderImplements
AutoMlImageClassificationInputsOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Type | Description |
Descriptor |
Methods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public AutoMlImageClassificationInputs.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
AutoMlImageClassificationInputs.Builder |
build()
public AutoMlImageClassificationInputs build()
Type | Description |
AutoMlImageClassificationInputs |
buildPartial()
public AutoMlImageClassificationInputs buildPartial()
Type | Description |
AutoMlImageClassificationInputs |
clear()
public AutoMlImageClassificationInputs.Builder clear()
Type | Description |
AutoMlImageClassificationInputs.Builder |
clearBaseModelId()
public AutoMlImageClassificationInputs.Builder clearBaseModelId()
The ID of the base
model. If it is specified, the new model will be
trained based on the base
model. Otherwise, the new model will be
trained from scratch. The base
model must be in the same
Project and Location as the new Model to train, and have the same
modelType.
string base_model_id = 2;
Type | Description |
AutoMlImageClassificationInputs.Builder | This builder for chaining. |
clearBudgetMilliNodeHours()
public AutoMlImageClassificationInputs.Builder clearBudgetMilliNodeHours()
The training budget of creating this model, expressed in milli node
hours i.e. 1,000 value in this field means 1 node hour. The actual
metadata.costMilliNodeHours will be equal or less than this value.
If further model training ceases to provide any improvements, it will
stop without using the full budget and the metadata.successfulStopReason
will be model-converged
.
Note, node_hour = actual_hour * number_of_nodes_involved.
For modelType cloud
(default), the budget must be between 8,000
and 800,000 milli node hours, inclusive. The default value is 192,000
which represents one day in wall time, considering 8 nodes are used.
For model types mobile-tf-low-latency-1
, mobile-tf-versatile-1
,
mobile-tf-high-accuracy-1
, the training budget must be between
1,000 and 100,000 milli node hours, inclusive.
The default value is 24,000 which represents one day in wall time on a
single node that is used.
int64 budget_milli_node_hours = 3;
Type | Description |
AutoMlImageClassificationInputs.Builder | This builder for chaining. |
clearDisableEarlyStopping()
public AutoMlImageClassificationInputs.Builder clearDisableEarlyStopping()
Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Classification might stop training before the entire training budget has been used.
bool disable_early_stopping = 4;
Type | Description |
AutoMlImageClassificationInputs.Builder | This builder for chaining. |
clearField(Descriptors.FieldDescriptor field)
public AutoMlImageClassificationInputs.Builder clearField(Descriptors.FieldDescriptor field)
Name | Description |
field | FieldDescriptor |
Type | Description |
AutoMlImageClassificationInputs.Builder |
clearModelType()
public AutoMlImageClassificationInputs.Builder clearModelType()
.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationInputs.ModelType model_type = 1;
Type | Description |
AutoMlImageClassificationInputs.Builder | This builder for chaining. |
clearMultiLabel()
public AutoMlImageClassificationInputs.Builder clearMultiLabel()
If false, a single-label (multi-class) Model will be trained (i.e. assuming that for each image just up to one annotation may be applicable). If true, a multi-label Model will be trained (i.e. assuming that for each image multiple annotations may be applicable).
bool multi_label = 5;
Type | Description |
AutoMlImageClassificationInputs.Builder | This builder for chaining. |
clearOneof(Descriptors.OneofDescriptor oneof)
public AutoMlImageClassificationInputs.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Name | Description |
oneof | OneofDescriptor |
Type | Description |
AutoMlImageClassificationInputs.Builder |
clone()
public AutoMlImageClassificationInputs.Builder clone()
Type | Description |
AutoMlImageClassificationInputs.Builder |
getBaseModelId()
public String getBaseModelId()
The ID of the base
model. If it is specified, the new model will be
trained based on the base
model. Otherwise, the new model will be
trained from scratch. The base
model must be in the same
Project and Location as the new Model to train, and have the same
modelType.
string base_model_id = 2;
Type | Description |
String | The baseModelId. |
getBaseModelIdBytes()
public ByteString getBaseModelIdBytes()
The ID of the base
model. If it is specified, the new model will be
trained based on the base
model. Otherwise, the new model will be
trained from scratch. The base
model must be in the same
Project and Location as the new Model to train, and have the same
modelType.
string base_model_id = 2;
Type | Description |
ByteString | The bytes for baseModelId. |
getBudgetMilliNodeHours()
public long getBudgetMilliNodeHours()
The training budget of creating this model, expressed in milli node
hours i.e. 1,000 value in this field means 1 node hour. The actual
metadata.costMilliNodeHours will be equal or less than this value.
If further model training ceases to provide any improvements, it will
stop without using the full budget and the metadata.successfulStopReason
will be model-converged
.
Note, node_hour = actual_hour * number_of_nodes_involved.
For modelType cloud
(default), the budget must be between 8,000
and 800,000 milli node hours, inclusive. The default value is 192,000
which represents one day in wall time, considering 8 nodes are used.
For model types mobile-tf-low-latency-1
, mobile-tf-versatile-1
,
mobile-tf-high-accuracy-1
, the training budget must be between
1,000 and 100,000 milli node hours, inclusive.
The default value is 24,000 which represents one day in wall time on a
single node that is used.
int64 budget_milli_node_hours = 3;
Type | Description |
long | The budgetMilliNodeHours. |
getDefaultInstanceForType()
public AutoMlImageClassificationInputs getDefaultInstanceForType()
Type | Description |
AutoMlImageClassificationInputs |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Type | Description |
Descriptor |
getDisableEarlyStopping()
public boolean getDisableEarlyStopping()
Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Classification might stop training before the entire training budget has been used.
bool disable_early_stopping = 4;
Type | Description |
boolean | The disableEarlyStopping. |
getModelType()
public AutoMlImageClassificationInputs.ModelType getModelType()
.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationInputs.ModelType model_type = 1;
Type | Description |
AutoMlImageClassificationInputs.ModelType | The modelType. |
getModelTypeValue()
public int getModelTypeValue()
.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationInputs.ModelType model_type = 1;
Type | Description |
int | The enum numeric value on the wire for modelType. |
getMultiLabel()
public boolean getMultiLabel()
If false, a single-label (multi-class) Model will be trained (i.e. assuming that for each image just up to one annotation may be applicable). If true, a multi-label Model will be trained (i.e. assuming that for each image multiple annotations may be applicable).
bool multi_label = 5;
Type | Description |
boolean | The multiLabel. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Type | Description |
FieldAccessorTable |
isInitialized()
public final boolean isInitialized()
Type | Description |
boolean |
mergeFrom(AutoMlImageClassificationInputs other)
public AutoMlImageClassificationInputs.Builder mergeFrom(AutoMlImageClassificationInputs other)
Name | Description |
other | AutoMlImageClassificationInputs |
Type | Description |
AutoMlImageClassificationInputs.Builder |
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public AutoMlImageClassificationInputs.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
AutoMlImageClassificationInputs.Builder |
Type | Description |
IOException |
mergeFrom(Message other)
public AutoMlImageClassificationInputs.Builder mergeFrom(Message other)
Name | Description |
other | Message |
Type | Description |
AutoMlImageClassificationInputs.Builder |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final AutoMlImageClassificationInputs.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
AutoMlImageClassificationInputs.Builder |
setBaseModelId(String value)
public AutoMlImageClassificationInputs.Builder setBaseModelId(String value)
The ID of the base
model. If it is specified, the new model will be
trained based on the base
model. Otherwise, the new model will be
trained from scratch. The base
model must be in the same
Project and Location as the new Model to train, and have the same
modelType.
string base_model_id = 2;
Name | Description |
value | String The baseModelId to set. |
Type | Description |
AutoMlImageClassificationInputs.Builder | This builder for chaining. |
setBaseModelIdBytes(ByteString value)
public AutoMlImageClassificationInputs.Builder setBaseModelIdBytes(ByteString value)
The ID of the base
model. If it is specified, the new model will be
trained based on the base
model. Otherwise, the new model will be
trained from scratch. The base
model must be in the same
Project and Location as the new Model to train, and have the same
modelType.
string base_model_id = 2;
Name | Description |
value | ByteString The bytes for baseModelId to set. |
Type | Description |
AutoMlImageClassificationInputs.Builder | This builder for chaining. |
setBudgetMilliNodeHours(long value)
public AutoMlImageClassificationInputs.Builder setBudgetMilliNodeHours(long value)
The training budget of creating this model, expressed in milli node
hours i.e. 1,000 value in this field means 1 node hour. The actual
metadata.costMilliNodeHours will be equal or less than this value.
If further model training ceases to provide any improvements, it will
stop without using the full budget and the metadata.successfulStopReason
will be model-converged
.
Note, node_hour = actual_hour * number_of_nodes_involved.
For modelType cloud
(default), the budget must be between 8,000
and 800,000 milli node hours, inclusive. The default value is 192,000
which represents one day in wall time, considering 8 nodes are used.
For model types mobile-tf-low-latency-1
, mobile-tf-versatile-1
,
mobile-tf-high-accuracy-1
, the training budget must be between
1,000 and 100,000 milli node hours, inclusive.
The default value is 24,000 which represents one day in wall time on a
single node that is used.
int64 budget_milli_node_hours = 3;
Name | Description |
value | long The budgetMilliNodeHours to set. |
Type | Description |
AutoMlImageClassificationInputs.Builder | This builder for chaining. |
setDisableEarlyStopping(boolean value)
public AutoMlImageClassificationInputs.Builder setDisableEarlyStopping(boolean value)
Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Classification might stop training before the entire training budget has been used.
bool disable_early_stopping = 4;
Name | Description |
value | boolean The disableEarlyStopping to set. |
Type | Description |
AutoMlImageClassificationInputs.Builder | This builder for chaining. |
setField(Descriptors.FieldDescriptor field, Object value)
public AutoMlImageClassificationInputs.Builder setField(Descriptors.FieldDescriptor field, Object value)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
AutoMlImageClassificationInputs.Builder |
setModelType(AutoMlImageClassificationInputs.ModelType value)
public AutoMlImageClassificationInputs.Builder setModelType(AutoMlImageClassificationInputs.ModelType value)
.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationInputs.ModelType model_type = 1;
Name | Description |
value | AutoMlImageClassificationInputs.ModelType The modelType to set. |
Type | Description |
AutoMlImageClassificationInputs.Builder | This builder for chaining. |
setModelTypeValue(int value)
public AutoMlImageClassificationInputs.Builder setModelTypeValue(int value)
.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationInputs.ModelType model_type = 1;
Name | Description |
value | int The enum numeric value on the wire for modelType to set. |
Type | Description |
AutoMlImageClassificationInputs.Builder | This builder for chaining. |
setMultiLabel(boolean value)
public AutoMlImageClassificationInputs.Builder setMultiLabel(boolean value)
If false, a single-label (multi-class) Model will be trained (i.e. assuming that for each image just up to one annotation may be applicable). If true, a multi-label Model will be trained (i.e. assuming that for each image multiple annotations may be applicable).
bool multi_label = 5;
Name | Description |
value | boolean The multiLabel to set. |
Type | Description |
AutoMlImageClassificationInputs.Builder | This builder for chaining. |
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public AutoMlImageClassificationInputs.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Name | Description |
field | FieldDescriptor |
index | int |
value | Object |
Type | Description |
AutoMlImageClassificationInputs.Builder |
setUnknownFields(UnknownFieldSet unknownFields)
public final AutoMlImageClassificationInputs.Builder setUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
AutoMlImageClassificationInputs.Builder |