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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 > ImageClassificationModelMetadataImplements
ImageClassificationModelMetadataOrBuilderStatic Fields
BASE_MODEL_ID_FIELD_NUMBER
public static final int BASE_MODEL_ID_FIELD_NUMBER
Type | Description |
int |
MODEL_TYPE_FIELD_NUMBER
public static final int MODEL_TYPE_FIELD_NUMBER
Type | Description |
int |
NODE_COUNT_FIELD_NUMBER
public static final int NODE_COUNT_FIELD_NUMBER
Type | Description |
int |
NODE_QPS_FIELD_NUMBER
public static final int NODE_QPS_FIELD_NUMBER
Type | Description |
int |
STOP_REASON_FIELD_NUMBER
public static final int STOP_REASON_FIELD_NUMBER
Type | Description |
int |
TRAIN_BUDGET_FIELD_NUMBER
public static final int TRAIN_BUDGET_FIELD_NUMBER
Type | Description |
int |
TRAIN_COST_FIELD_NUMBER
public static final int TRAIN_COST_FIELD_NUMBER
Type | Description |
int |
Static Methods
getDefaultInstance()
public static ImageClassificationModelMetadata getDefaultInstance()
Type | Description |
ImageClassificationModelMetadata |
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Type | Description |
Descriptor |
newBuilder()
public static ImageClassificationModelMetadata.Builder newBuilder()
Type | Description |
ImageClassificationModelMetadata.Builder |
newBuilder(ImageClassificationModelMetadata prototype)
public static ImageClassificationModelMetadata.Builder newBuilder(ImageClassificationModelMetadata prototype)
Name | Description |
prototype | ImageClassificationModelMetadata |
Type | Description |
ImageClassificationModelMetadata.Builder |
parseDelimitedFrom(InputStream input)
public static ImageClassificationModelMetadata parseDelimitedFrom(InputStream input)
Name | Description |
input | InputStream |
Type | Description |
ImageClassificationModelMetadata |
Type | Description |
IOException |
parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ImageClassificationModelMetadata parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Name | Description |
input | InputStream |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ImageClassificationModelMetadata |
Type | Description |
IOException |
parseFrom(byte[] data)
public static ImageClassificationModelMetadata parseFrom(byte[] data)
Name | Description |
data | byte[] |
Type | Description |
ImageClassificationModelMetadata |
Type | Description |
InvalidProtocolBufferException |
parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static ImageClassificationModelMetadata parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
Name | Description |
data | byte[] |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ImageClassificationModelMetadata |
Type | Description |
InvalidProtocolBufferException |
parseFrom(ByteString data)
public static ImageClassificationModelMetadata parseFrom(ByteString data)
Name | Description |
data | ByteString |
Type | Description |
ImageClassificationModelMetadata |
Type | Description |
InvalidProtocolBufferException |
parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static ImageClassificationModelMetadata parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
Name | Description |
data | ByteString |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ImageClassificationModelMetadata |
Type | Description |
InvalidProtocolBufferException |
parseFrom(CodedInputStream input)
public static ImageClassificationModelMetadata parseFrom(CodedInputStream input)
Name | Description |
input | CodedInputStream |
Type | Description |
ImageClassificationModelMetadata |
Type | Description |
IOException |
parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static ImageClassificationModelMetadata parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ImageClassificationModelMetadata |
Type | Description |
IOException |
parseFrom(InputStream input)
public static ImageClassificationModelMetadata parseFrom(InputStream input)
Name | Description |
input | InputStream |
Type | Description |
ImageClassificationModelMetadata |
Type | Description |
IOException |
parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ImageClassificationModelMetadata parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Name | Description |
input | InputStream |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ImageClassificationModelMetadata |
Type | Description |
IOException |
parseFrom(ByteBuffer data)
public static ImageClassificationModelMetadata parseFrom(ByteBuffer data)
Name | Description |
data | ByteBuffer |
Type | Description |
ImageClassificationModelMetadata |
Type | Description |
InvalidProtocolBufferException |
parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static ImageClassificationModelMetadata parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Name | Description |
data | ByteBuffer |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ImageClassificationModelMetadata |
Type | Description |
InvalidProtocolBufferException |
parser()
public static Parser<ImageClassificationModelMetadata> parser()
Type | Description |
Parser<ImageClassificationModelMetadata> |
Methods
equals(Object obj)
public boolean equals(Object obj)
Name | Description |
obj | Object |
Type | Description |
boolean |
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;
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;
Type | Description |
ByteString | The bytes for baseModelId. |
getDefaultInstanceForType()
public ImageClassificationModelMetadata getDefaultInstanceForType()
Type | Description |
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;
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;
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;
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;
Type | Description |
double | The nodeQps. |
getParserForType()
public Parser<ImageClassificationModelMetadata> getParserForType()
Type | Description |
Parser<ImageClassificationModelMetadata> |
getSerializedSize()
public int getSerializedSize()
Type | Description |
int |
getStopReason()
public String getStopReason()
Output only. The reason that this create model operation stopped,
e.g. BUDGET_REACHED
, MODEL_CONVERGED
.
string stop_reason = 5;
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;
Type | Description |
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;
Type | Description |
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;
Type | Description |
long | The trainCost. |
getUnknownFields()
public final UnknownFieldSet getUnknownFields()
Type | Description |
UnknownFieldSet |
hashCode()
public int hashCode()
Type | Description |
int |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Type | Description |
FieldAccessorTable |
isInitialized()
public final boolean isInitialized()
Type | Description |
boolean |
newBuilderForType()
public ImageClassificationModelMetadata.Builder newBuilderForType()
Type | Description |
ImageClassificationModelMetadata.Builder |
newBuilderForType(GeneratedMessageV3.BuilderParent parent)
protected ImageClassificationModelMetadata.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Name | Description |
parent | BuilderParent |
Type | Description |
ImageClassificationModelMetadata.Builder |
newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Name | Description |
unused | UnusedPrivateParameter |
Type | Description |
Object |
toBuilder()
public ImageClassificationModelMetadata.Builder toBuilder()
Type | Description |
ImageClassificationModelMetadata.Builder |
writeTo(CodedOutputStream output)
public void writeTo(CodedOutputStream output)
Name | Description |
output | CodedOutputStream |
Type | Description |
IOException |