public static final class AutoMlImageObjectDetectionInputs.Builder extends GeneratedMessageV3.Builder<AutoMlImageObjectDetectionInputs.Builder> implements AutoMlImageObjectDetectionInputsOrBuilder
Protobuf type
google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageObjectDetectionInputs
Methods
public AutoMlImageObjectDetectionInputs.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
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public AutoMlImageObjectDetectionInputs build()
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public AutoMlImageObjectDetectionInputs buildPartial()
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public AutoMlImageObjectDetectionInputs.Builder clear()
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public AutoMlImageObjectDetectionInputs.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 20,000
and 900,000 milli node hours, inclusive. The default value is 216,000
which represents one day in wall time, considering 9 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 = 2;
public AutoMlImageObjectDetectionInputs.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 Object Detection might stop training before the entire training
budget has been used.
bool disable_early_stopping = 3;
public AutoMlImageObjectDetectionInputs.Builder clearField(Descriptors.FieldDescriptor field)
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public AutoMlImageObjectDetectionInputs.Builder clearModelType()
.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageObjectDetectionInputs.ModelType model_type = 1;
public AutoMlImageObjectDetectionInputs.Builder clearOneof(Descriptors.OneofDescriptor oneof)
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public AutoMlImageObjectDetectionInputs.Builder clone()
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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 20,000
and 900,000 milli node hours, inclusive. The default value is 216,000
which represents one day in wall time, considering 9 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 = 2;
| Type | Description |
| long | The budgetMilliNodeHours.
|
public AutoMlImageObjectDetectionInputs getDefaultInstanceForType()
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public static final Descriptors.Descriptor getDescriptor()
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public Descriptors.Descriptor getDescriptorForType()
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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 Object Detection might stop training before the entire training
budget has been used.
bool disable_early_stopping = 3;
| Type | Description |
| boolean | The disableEarlyStopping.
|
public AutoMlImageObjectDetectionInputs.ModelType getModelType()
.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageObjectDetectionInputs.ModelType model_type = 1;
public int getModelTypeValue()
.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageObjectDetectionInputs.ModelType model_type = 1;
| Type | Description |
| int | The enum numeric value on the wire for modelType.
|
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
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public final boolean isInitialized()
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public AutoMlImageObjectDetectionInputs.Builder mergeFrom(AutoMlImageObjectDetectionInputs other)
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public AutoMlImageObjectDetectionInputs.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
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Exceptions
public AutoMlImageObjectDetectionInputs.Builder mergeFrom(Message other)
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public final AutoMlImageObjectDetectionInputs.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
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public AutoMlImageObjectDetectionInputs.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 20,000
and 900,000 milli node hours, inclusive. The default value is 216,000
which represents one day in wall time, considering 9 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 = 2;
| Name | Description |
| value | long
The budgetMilliNodeHours to set.
|
Returns
public AutoMlImageObjectDetectionInputs.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 Object Detection might stop training before the entire training
budget has been used.
bool disable_early_stopping = 3;
| Name | Description |
| value | boolean
The disableEarlyStopping to set.
|
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public AutoMlImageObjectDetectionInputs.Builder setField(Descriptors.FieldDescriptor field, Object value)
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public AutoMlImageObjectDetectionInputs.Builder setModelType(AutoMlImageObjectDetectionInputs.ModelType value)
.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageObjectDetectionInputs.ModelType model_type = 1;
public AutoMlImageObjectDetectionInputs.Builder setModelTypeValue(int value)
.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageObjectDetectionInputs.ModelType model_type = 1;
| Name | Description |
| value | int
The enum numeric value on the wire for modelType to set.
|
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public AutoMlImageObjectDetectionInputs.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
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public final AutoMlImageObjectDetectionInputs.Builder setUnknownFields(UnknownFieldSet unknownFields)
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