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public static final class ImageClassificationModelMetadata.Builder extends GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder> implements ImageClassificationModelMetadataOrBuilderModel metadata for image classification.
Protobuf type google.cloud.automl.v1.ImageClassificationModelMetadata
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > ImageClassificationModelMetadata.BuilderImplements
ImageClassificationModelMetadataOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()| Returns | |
|---|---|
| Type | Description |
Descriptor |
|
Methods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public ImageClassificationModelMetadata.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
|
build()
public ImageClassificationModelMetadata build()| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata |
|
buildPartial()
public ImageClassificationModelMetadata buildPartial()| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata |
|
clear()
public ImageClassificationModelMetadata.Builder clear()| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
|
clearBaseModelId()
public ImageClassificationModelMetadata.Builder clearBaseModelId() Optional. The ID of the base model. If it is specified, the new model
will be created based on the base model. Otherwise, the new model will be
created from scratch. The base model must be in the same
project and location as the new model to create, and have the same
model_type.
string base_model_id = 1 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
clearField(Descriptors.FieldDescriptor field)
public ImageClassificationModelMetadata.Builder clearField(Descriptors.FieldDescriptor field)| Parameter | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
|
clearModelType()
public ImageClassificationModelMetadata.Builder clearModelType()Optional. Type of the model. The available values are:
cloud- Model to be used via prediction calls to AutoML API. This is the default value.mobile-low-latency-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-versatile-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards.mobile-high-accuracy-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.mobile-core-ml-low-latency-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-core-ml-versatile-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards.mobile-core-ml-high-accuracy-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.
string model_type = 7 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
clearNodeCount()
public ImageClassificationModelMetadata.Builder clearNodeCount()Output only. The number of nodes this model is deployed on. A node is an abstraction of a machine resource, which can handle online prediction QPS as given in the node_qps field.
int64 node_count = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
clearNodeQps()
public ImageClassificationModelMetadata.Builder clearNodeQps()Output only. An approximate number of online prediction QPS that can be supported by this model per each node on which it is deployed.
double node_qps = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
clearOneof(Descriptors.OneofDescriptor oneof)
public ImageClassificationModelMetadata.Builder clearOneof(Descriptors.OneofDescriptor oneof)| Parameter | |
|---|---|
| Name | Description |
oneof |
OneofDescriptor |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
|
clearStopReason()
public ImageClassificationModelMetadata.Builder clearStopReason() Output only. The reason that this create model operation stopped,
e.g. BUDGET_REACHED, MODEL_CONVERGED.
string stop_reason = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
clearTrainBudgetMilliNodeHours()
public ImageClassificationModelMetadata.Builder clearTrainBudgetMilliNodeHours() Optional. 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 actual
train_cost will be equal or less than this value. If further model
training ceases to provide any improvements, it will stop without using
full budget and the stop_reason will be MODEL_CONVERGED.
Note, node_hour = actual_hour * number_of_nodes_invovled.
For model type cloud(default), the train 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. For model type
mobile-low-latency-1, mobile-versatile-1, mobile-high-accuracy-1,
mobile-core-ml-low-latency-1, mobile-core-ml-versatile-1,
mobile-core-ml-high-accuracy-1, the train 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.
int64 train_budget_milli_node_hours = 16 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
clearTrainCostMilliNodeHours()
public ImageClassificationModelMetadata.Builder clearTrainCostMilliNodeHours()Output only. The actual train cost of creating this 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 = 17 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
clone()
public ImageClassificationModelMetadata.Builder clone()| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
|
getBaseModelId()
public String getBaseModelId() Optional. The ID of the base model. If it is specified, the new model
will be created based on the base model. Otherwise, the new model will be
created from scratch. The base model must be in the same
project and location as the new model to create, and have the same
model_type.
string base_model_id = 1 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
String |
The baseModelId. |
getBaseModelIdBytes()
public ByteString getBaseModelIdBytes() Optional. The ID of the base model. If it is specified, the new model
will be created based on the base model. Otherwise, the new model will be
created from scratch. The base model must be in the same
project and location as the new model to create, and have the same
model_type.
string base_model_id = 1 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes for baseModelId. |
getDefaultInstanceForType()
public ImageClassificationModelMetadata getDefaultInstanceForType()| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata |
|
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()| Returns | |
|---|---|
| Type | Description |
Descriptor |
|
getModelType()
public String getModelType()Optional. Type of the model. The available values are:
cloud- Model to be used via prediction calls to AutoML API. This is the default value.mobile-low-latency-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-versatile-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards.mobile-high-accuracy-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.mobile-core-ml-low-latency-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-core-ml-versatile-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards.mobile-core-ml-high-accuracy-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.
string model_type = 7 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
String |
The modelType. |
getModelTypeBytes()
public ByteString getModelTypeBytes()Optional. Type of the model. The available values are:
cloud- Model to be used via prediction calls to AutoML API. This is the default value.mobile-low-latency-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-versatile-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards.mobile-high-accuracy-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.mobile-core-ml-low-latency-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-core-ml-versatile-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards.mobile-core-ml-high-accuracy-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.
string model_type = 7 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes for modelType. |
getNodeCount()
public long getNodeCount()Output only. The number of nodes this model is deployed on. A node is an abstraction of a machine resource, which can handle online prediction QPS as given in the node_qps field.
int64 node_count = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
long |
The nodeCount. |
getNodeQps()
public double getNodeQps()Output only. An approximate number of online prediction QPS that can be supported by this model per each node on which it is deployed.
double node_qps = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
double |
The nodeQps. |
getStopReason()
public String getStopReason() Output only. The reason that this create model operation stopped,
e.g. BUDGET_REACHED, MODEL_CONVERGED.
string stop_reason = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
String |
The stopReason. |
getStopReasonBytes()
public ByteString getStopReasonBytes() Output only. The reason that this create model operation stopped,
e.g. BUDGET_REACHED, MODEL_CONVERGED.
string stop_reason = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes for stopReason. |
getTrainBudgetMilliNodeHours()
public long getTrainBudgetMilliNodeHours() Optional. 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 actual
train_cost will be equal or less than this value. If further model
training ceases to provide any improvements, it will stop without using
full budget and the stop_reason will be MODEL_CONVERGED.
Note, node_hour = actual_hour * number_of_nodes_invovled.
For model type cloud(default), the train 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. For model type
mobile-low-latency-1, mobile-versatile-1, mobile-high-accuracy-1,
mobile-core-ml-low-latency-1, mobile-core-ml-versatile-1,
mobile-core-ml-high-accuracy-1, the train 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.
int64 train_budget_milli_node_hours = 16 [(.google.api.field_behavior) = OPTIONAL];
| Returns | |
|---|---|
| Type | Description |
long |
The trainBudgetMilliNodeHours. |
getTrainCostMilliNodeHours()
public long getTrainCostMilliNodeHours()Output only. The actual train cost of creating this 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 = 17 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns | |
|---|---|
| Type | Description |
long |
The trainCostMilliNodeHours. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()| Returns | |
|---|---|
| Type | Description |
FieldAccessorTable |
|
isInitialized()
public final boolean isInitialized()| Returns | |
|---|---|
| Type | Description |
boolean |
|
mergeFrom(ImageClassificationModelMetadata other)
public ImageClassificationModelMetadata.Builder mergeFrom(ImageClassificationModelMetadata other)| Parameter | |
|---|---|
| Name | Description |
other |
ImageClassificationModelMetadata |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
|
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public ImageClassificationModelMetadata.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)| Parameters | |
|---|---|
| Name | Description |
input |
CodedInputStream |
extensionRegistry |
ExtensionRegistryLite |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
mergeFrom(Message other)
public ImageClassificationModelMetadata.Builder mergeFrom(Message other)| Parameter | |
|---|---|
| Name | Description |
other |
Message |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
|
mergeUnknownFields(UnknownFieldSet unknownFields)
public final ImageClassificationModelMetadata.Builder mergeUnknownFields(UnknownFieldSet unknownFields)| Parameter | |
|---|---|
| Name | Description |
unknownFields |
UnknownFieldSet |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
|
setBaseModelId(String value)
public ImageClassificationModelMetadata.Builder setBaseModelId(String value) Optional. The ID of the base model. If it is specified, the new model
will be created based on the base model. Otherwise, the new model will be
created from scratch. The base model must be in the same
project and location as the new model to create, and have the same
model_type.
string base_model_id = 1 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
StringThe baseModelId to set. |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
setBaseModelIdBytes(ByteString value)
public ImageClassificationModelMetadata.Builder setBaseModelIdBytes(ByteString value) Optional. The ID of the base model. If it is specified, the new model
will be created based on the base model. Otherwise, the new model will be
created from scratch. The base model must be in the same
project and location as the new model to create, and have the same
model_type.
string base_model_id = 1 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
ByteStringThe bytes for baseModelId to set. |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
setField(Descriptors.FieldDescriptor field, Object value)
public ImageClassificationModelMetadata.Builder setField(Descriptors.FieldDescriptor field, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
|
setModelType(String value)
public ImageClassificationModelMetadata.Builder setModelType(String value)Optional. Type of the model. The available values are:
cloud- Model to be used via prediction calls to AutoML API. This is the default value.mobile-low-latency-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-versatile-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards.mobile-high-accuracy-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.mobile-core-ml-low-latency-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-core-ml-versatile-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards.mobile-core-ml-high-accuracy-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.
string model_type = 7 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
StringThe modelType to set. |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
setModelTypeBytes(ByteString value)
public ImageClassificationModelMetadata.Builder setModelTypeBytes(ByteString value)Optional. Type of the model. The available values are:
cloud- Model to be used via prediction calls to AutoML API. This is the default value.mobile-low-latency-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-versatile-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards.mobile-high-accuracy-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.mobile-core-ml-low-latency-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards. Expected to have low latency, but may have lower prediction quality than other models.mobile-core-ml-versatile-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards.mobile-core-ml-high-accuracy-1- A model that, in addition to providing prediction via AutoML API, can also be exported (see AutoMl.ExportModel) and used on a mobile device with Core ML afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other models.
string model_type = 7 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
ByteStringThe bytes for modelType to set. |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
setNodeCount(long value)
public ImageClassificationModelMetadata.Builder setNodeCount(long value)Output only. The number of nodes this model is deployed on. A node is an abstraction of a machine resource, which can handle online prediction QPS as given in the node_qps field.
int64 node_count = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
value |
longThe nodeCount to set. |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
setNodeQps(double value)
public ImageClassificationModelMetadata.Builder setNodeQps(double value)Output only. An approximate number of online prediction QPS that can be supported by this model per each node on which it is deployed.
double node_qps = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
value |
doubleThe nodeQps to set. |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public ImageClassificationModelMetadata.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
index |
int |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
|
setStopReason(String value)
public ImageClassificationModelMetadata.Builder setStopReason(String value) Output only. The reason that this create model operation stopped,
e.g. BUDGET_REACHED, MODEL_CONVERGED.
string stop_reason = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
value |
StringThe stopReason to set. |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
setStopReasonBytes(ByteString value)
public ImageClassificationModelMetadata.Builder setStopReasonBytes(ByteString value) Output only. The reason that this create model operation stopped,
e.g. BUDGET_REACHED, MODEL_CONVERGED.
string stop_reason = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
value |
ByteStringThe bytes for stopReason to set. |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
setTrainBudgetMilliNodeHours(long value)
public ImageClassificationModelMetadata.Builder setTrainBudgetMilliNodeHours(long value) Optional. 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 actual
train_cost will be equal or less than this value. If further model
training ceases to provide any improvements, it will stop without using
full budget and the stop_reason will be MODEL_CONVERGED.
Note, node_hour = actual_hour * number_of_nodes_invovled.
For model type cloud(default), the train 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. For model type
mobile-low-latency-1, mobile-versatile-1, mobile-high-accuracy-1,
mobile-core-ml-low-latency-1, mobile-core-ml-versatile-1,
mobile-core-ml-high-accuracy-1, the train 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.
int64 train_budget_milli_node_hours = 16 [(.google.api.field_behavior) = OPTIONAL];
| Parameter | |
|---|---|
| Name | Description |
value |
longThe trainBudgetMilliNodeHours to set. |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
setTrainCostMilliNodeHours(long value)
public ImageClassificationModelMetadata.Builder setTrainCostMilliNodeHours(long value)Output only. The actual train cost of creating this 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 = 17 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Parameter | |
|---|---|
| Name | Description |
value |
longThe trainCostMilliNodeHours to set. |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
This builder for chaining. |
setUnknownFields(UnknownFieldSet unknownFields)
public final ImageClassificationModelMetadata.Builder setUnknownFields(UnknownFieldSet unknownFields)| Parameter | |
|---|---|
| Name | Description |
unknownFields |
UnknownFieldSet |
| Returns | |
|---|---|
| Type | Description |
ImageClassificationModelMetadata.Builder |
|