Class ImageClassificationModelMetadata (2.3.10)

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public final class ImageClassificationModelMetadata extends GeneratedMessageV3 implements ImageClassificationModelMetadataOrBuilder

Model metadata for image classification.

Protobuf type google.cloud.automl.v1beta1.ImageClassificationModelMetadata

Inheritance

Object > AbstractMessageLite<MessageType,BuilderType> > AbstractMessage > GeneratedMessageV3 > ImageClassificationModelMetadata

Static Fields

BASE_MODEL_ID_FIELD_NUMBER

public static final int BASE_MODEL_ID_FIELD_NUMBER
Field Value
TypeDescription
int

MODEL_TYPE_FIELD_NUMBER

public static final int MODEL_TYPE_FIELD_NUMBER
Field Value
TypeDescription
int

NODE_COUNT_FIELD_NUMBER

public static final int NODE_COUNT_FIELD_NUMBER
Field Value
TypeDescription
int

NODE_QPS_FIELD_NUMBER

public static final int NODE_QPS_FIELD_NUMBER
Field Value
TypeDescription
int

STOP_REASON_FIELD_NUMBER

public static final int STOP_REASON_FIELD_NUMBER
Field Value
TypeDescription
int

TRAIN_BUDGET_FIELD_NUMBER

public static final int TRAIN_BUDGET_FIELD_NUMBER
Field Value
TypeDescription
int

TRAIN_COST_FIELD_NUMBER

public static final int TRAIN_COST_FIELD_NUMBER
Field Value
TypeDescription
int

Static Methods

getDefaultInstance()

public static ImageClassificationModelMetadata getDefaultInstance()
Returns
TypeDescription
ImageClassificationModelMetadata

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
TypeDescription
Descriptor

newBuilder()

public static ImageClassificationModelMetadata.Builder newBuilder()
Returns
TypeDescription
ImageClassificationModelMetadata.Builder

newBuilder(ImageClassificationModelMetadata prototype)

public static ImageClassificationModelMetadata.Builder newBuilder(ImageClassificationModelMetadata prototype)
Parameter
NameDescription
prototypeImageClassificationModelMetadata
Returns
TypeDescription
ImageClassificationModelMetadata.Builder

parseDelimitedFrom(InputStream input)

public static ImageClassificationModelMetadata parseDelimitedFrom(InputStream input)
Parameter
NameDescription
inputInputStream
Returns
TypeDescription
ImageClassificationModelMetadata
Exceptions
TypeDescription
IOException

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static ImageClassificationModelMetadata parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ImageClassificationModelMetadata
Exceptions
TypeDescription
IOException

parseFrom(byte[] data)

public static ImageClassificationModelMetadata parseFrom(byte[] data)
Parameter
NameDescription
databyte[]
Returns
TypeDescription
ImageClassificationModelMetadata
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

public static ImageClassificationModelMetadata parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
databyte[]
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ImageClassificationModelMetadata
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(ByteString data)

public static ImageClassificationModelMetadata parseFrom(ByteString data)
Parameter
NameDescription
dataByteString
Returns
TypeDescription
ImageClassificationModelMetadata
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

public static ImageClassificationModelMetadata parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
dataByteString
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ImageClassificationModelMetadata
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(CodedInputStream input)

public static ImageClassificationModelMetadata parseFrom(CodedInputStream input)
Parameter
NameDescription
inputCodedInputStream
Returns
TypeDescription
ImageClassificationModelMetadata
Exceptions
TypeDescription
IOException

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public static ImageClassificationModelMetadata parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ImageClassificationModelMetadata
Exceptions
TypeDescription
IOException

parseFrom(InputStream input)

public static ImageClassificationModelMetadata parseFrom(InputStream input)
Parameter
NameDescription
inputInputStream
Returns
TypeDescription
ImageClassificationModelMetadata
Exceptions
TypeDescription
IOException

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static ImageClassificationModelMetadata parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ImageClassificationModelMetadata
Exceptions
TypeDescription
IOException

parseFrom(ByteBuffer data)

public static ImageClassificationModelMetadata parseFrom(ByteBuffer data)
Parameter
NameDescription
dataByteBuffer
Returns
TypeDescription
ImageClassificationModelMetadata
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

public static ImageClassificationModelMetadata parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
dataByteBuffer
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ImageClassificationModelMetadata
Exceptions
TypeDescription
InvalidProtocolBufferException

parser()

public static Parser<ImageClassificationModelMetadata> parser()
Returns
TypeDescription
Parser<ImageClassificationModelMetadata>

Methods

equals(Object obj)

public boolean equals(Object obj)
Parameter
NameDescription
objObject
Returns
TypeDescription
boolean
Overrides

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;

Returns
TypeDescription
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;

Returns
TypeDescription
ByteString

The bytes for baseModelId.

getDefaultInstanceForType()

public ImageClassificationModelMetadata getDefaultInstanceForType()
Returns
TypeDescription
ImageClassificationModelMetadata

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;

Returns
TypeDescription
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;

Returns
TypeDescription
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;

Returns
TypeDescription
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;

Returns
TypeDescription
double

The nodeQps.

getParserForType()

public Parser<ImageClassificationModelMetadata> getParserForType()
Returns
TypeDescription
Parser<ImageClassificationModelMetadata>
Overrides

getSerializedSize()

public int getSerializedSize()
Returns
TypeDescription
int
Overrides

getStopReason()

public String getStopReason()

Output only. The reason that this create model operation stopped, e.g. BUDGET_REACHED, MODEL_CONVERGED.

string stop_reason = 5;

Returns
TypeDescription
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;

Returns
TypeDescription
ByteString

The bytes for stopReason.

getTrainBudget()

public long getTrainBudget()

Required. The train budget of creating this model, expressed in hours. The actual train_cost will be equal or less than this value.

int64 train_budget = 2;

Returns
TypeDescription
long

The trainBudget.

getTrainCost()

public long getTrainCost()

Output only. The actual train cost of creating this model, expressed in hours. If this model is created from a base model, the train cost used to create the base model are not included.

int64 train_cost = 3;

Returns
TypeDescription
long

The trainCost.

getUnknownFields()

public final UnknownFieldSet getUnknownFields()
Returns
TypeDescription
UnknownFieldSet
Overrides

hashCode()

public int hashCode()
Returns
TypeDescription
int
Overrides

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

newBuilderForType()

public ImageClassificationModelMetadata.Builder newBuilderForType()
Returns
TypeDescription
ImageClassificationModelMetadata.Builder

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

protected ImageClassificationModelMetadata.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Parameter
NameDescription
parentBuilderParent
Returns
TypeDescription
ImageClassificationModelMetadata.Builder
Overrides

newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Parameter
NameDescription
unusedUnusedPrivateParameter
Returns
TypeDescription
Object
Overrides

toBuilder()

public ImageClassificationModelMetadata.Builder toBuilder()
Returns
TypeDescription
ImageClassificationModelMetadata.Builder

writeTo(CodedOutputStream output)

public void writeTo(CodedOutputStream output)
Parameter
NameDescription
outputCodedOutputStream
Overrides Exceptions
TypeDescription
IOException