public final class ImageObjectDetectionModelMetadata extends GeneratedMessageV3 implements ImageObjectDetectionModelMetadataOrBuilder
Model metadata specific to image object detection.
Protobuf type google.cloud.automl.v1.ImageObjectDetectionModelMetadata
Inherited Members
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT)
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT,int)
com.google.protobuf.GeneratedMessageV3.<T>emptyList(java.lang.Class<T>)
com.google.protobuf.GeneratedMessageV3.internalGetMapFieldReflection(int)
Static Fields
public static final int MODEL_TYPE_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int NODE_COUNT_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int NODE_QPS_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int STOP_REASON_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int TRAIN_BUDGET_MILLI_NODE_HOURS_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int TRAIN_COST_MILLI_NODE_HOURS_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
Static Methods
public static ImageObjectDetectionModelMetadata getDefaultInstance()
public static final Descriptors.Descriptor getDescriptor()
public static ImageObjectDetectionModelMetadata.Builder newBuilder()
public static ImageObjectDetectionModelMetadata.Builder newBuilder(ImageObjectDetectionModelMetadata prototype)
public static ImageObjectDetectionModelMetadata parseDelimitedFrom(InputStream input)
public static ImageObjectDetectionModelMetadata parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ImageObjectDetectionModelMetadata parseFrom(byte[] data)
| Parameter |
|---|
| Name | Description |
data | byte[]
|
public static ImageObjectDetectionModelMetadata parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static ImageObjectDetectionModelMetadata parseFrom(ByteString data)
public static ImageObjectDetectionModelMetadata parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static ImageObjectDetectionModelMetadata parseFrom(CodedInputStream input)
public static ImageObjectDetectionModelMetadata parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static ImageObjectDetectionModelMetadata parseFrom(InputStream input)
public static ImageObjectDetectionModelMetadata parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ImageObjectDetectionModelMetadata parseFrom(ByteBuffer data)
public static ImageObjectDetectionModelMetadata parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static Parser<ImageObjectDetectionModelMetadata> parser()
Methods
public boolean equals(Object obj)
| Parameter |
|---|
| Name | Description |
obj | Object
|
Overrides
public ImageObjectDetectionModelMetadata getDefaultInstanceForType()
public String getModelType()
Optional. Type of the model. The available values are:
cloud-high-accuracy-1 - (default) A model to be used via prediction
calls to AutoML API. Expected to have a higher latency, but
should also have a higher prediction quality than other
models.cloud-low-latency-1 - A model to be used via prediction
calls to AutoML API. Expected to have low latency, but may
have lower prediction quality than other models.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.
string model_type = 1 [(.google.api.field_behavior) = OPTIONAL];
| Returns |
|---|
| Type | Description |
String | The modelType.
|
public ByteString getModelTypeBytes()
Optional. Type of the model. The available values are:
cloud-high-accuracy-1 - (default) A model to be used via prediction
calls to AutoML API. Expected to have a higher latency, but
should also have a higher prediction quality than other
models.cloud-low-latency-1 - A model to be used via prediction
calls to AutoML API. Expected to have low latency, but may
have lower prediction quality than other models.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.
string model_type = 1 [(.google.api.field_behavior) = OPTIONAL];
| Returns |
|---|
| Type | Description |
ByteString | The bytes for modelType.
|
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 qps_per_node field.
int64 node_count = 3 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns |
|---|
| Type | Description |
long | The nodeCount.
|
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 = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns |
|---|
| Type | Description |
double | The nodeQps.
|
public Parser<ImageObjectDetectionModelMetadata> getParserForType()
Overrides
public int getSerializedSize()
| Returns |
|---|
| Type | Description |
int | |
Overrides
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.
|
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.
|
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-high-accuracy-1(default) and cloud-low-latency-1,
the train 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.
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 = 6 [(.google.api.field_behavior) = OPTIONAL];
| Returns |
|---|
| Type | Description |
long | The trainBudgetMilliNodeHours.
|
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 = 7 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Returns |
|---|
| Type | Description |
long | The trainCostMilliNodeHours.
|
| Returns |
|---|
| Type | Description |
int | |
Overrides
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Overrides
public final boolean isInitialized()
Overrides
public ImageObjectDetectionModelMetadata.Builder newBuilderForType()
protected ImageObjectDetectionModelMetadata.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Overrides
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Overrides
public ImageObjectDetectionModelMetadata.Builder toBuilder()
public void writeTo(CodedOutputStream output)
Overrides
