Class ImageClassificationModelMetadata.Builder

public static final class ImageClassificationModelMetadata.Builder extends GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder> implements ImageClassificationModelMetadataOrBuilder

Model metadata for image classification.

Protobuf type google.cloud.automl.v1beta1.ImageClassificationModelMetadata

Static Methods

getDescriptor()

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

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public ImageClassificationModelMetadata.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
ImageClassificationModelMetadata.Builder
Overrides

build()

public ImageClassificationModelMetadata build()
Returns
TypeDescription
ImageClassificationModelMetadata

buildPartial()

public ImageClassificationModelMetadata buildPartial()
Returns
TypeDescription
ImageClassificationModelMetadata

clear()

public ImageClassificationModelMetadata.Builder clear()
Returns
TypeDescription
ImageClassificationModelMetadata.Builder
Overrides

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;

Returns
TypeDescription
ImageClassificationModelMetadata.Builder

This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public ImageClassificationModelMetadata.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
NameDescription
fieldFieldDescriptor
Returns
TypeDescription
ImageClassificationModelMetadata.Builder
Overrides

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;

Returns
TypeDescription
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;

Returns
TypeDescription
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;

Returns
TypeDescription
ImageClassificationModelMetadata.Builder

This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public ImageClassificationModelMetadata.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
NameDescription
oneofOneofDescriptor
Returns
TypeDescription
ImageClassificationModelMetadata.Builder
Overrides

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;

Returns
TypeDescription
ImageClassificationModelMetadata.Builder

This builder for chaining.

clearTrainBudget()

public ImageClassificationModelMetadata.Builder clearTrainBudget()

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
ImageClassificationModelMetadata.Builder

This builder for chaining.

clearTrainCost()

public ImageClassificationModelMetadata.Builder clearTrainCost()

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
ImageClassificationModelMetadata.Builder

This builder for chaining.

clone()

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

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

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.

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.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeFrom(ImageClassificationModelMetadata other)

public ImageClassificationModelMetadata.Builder mergeFrom(ImageClassificationModelMetadata other)
Parameter
NameDescription
otherImageClassificationModelMetadata
Returns
TypeDescription
ImageClassificationModelMetadata.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public ImageClassificationModelMetadata.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ImageClassificationModelMetadata.Builder
Overrides Exceptions
TypeDescription
IOException

mergeFrom(Message other)

public ImageClassificationModelMetadata.Builder mergeFrom(Message other)
Parameter
NameDescription
otherMessage
Returns
TypeDescription
ImageClassificationModelMetadata.Builder
Overrides

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ImageClassificationModelMetadata.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
ImageClassificationModelMetadata.Builder
Overrides

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;

Parameter
NameDescription
valueString

The baseModelId to set.

Returns
TypeDescription
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;

Parameter
NameDescription
valueByteString

The bytes for baseModelId to set.

Returns
TypeDescription
ImageClassificationModelMetadata.Builder

This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public ImageClassificationModelMetadata.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
ImageClassificationModelMetadata.Builder
Overrides

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;

Parameter
NameDescription
valueString

The modelType to set.

Returns
TypeDescription
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;

Parameter
NameDescription
valueByteString

The bytes for modelType to set.

Returns
TypeDescription
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;

Parameter
NameDescription
valuelong

The nodeCount to set.

Returns
TypeDescription
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;

Parameter
NameDescription
valuedouble

The nodeQps to set.

Returns
TypeDescription
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
NameDescription
fieldFieldDescriptor
indexint
valueObject
Returns
TypeDescription
ImageClassificationModelMetadata.Builder
Overrides

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;

Parameter
NameDescription
valueString

The stopReason to set.

Returns
TypeDescription
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;

Parameter
NameDescription
valueByteString

The bytes for stopReason to set.

Returns
TypeDescription
ImageClassificationModelMetadata.Builder

This builder for chaining.

setTrainBudget(long value)

public ImageClassificationModelMetadata.Builder setTrainBudget(long value)

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;

Parameter
NameDescription
valuelong

The trainBudget to set.

Returns
TypeDescription
ImageClassificationModelMetadata.Builder

This builder for chaining.

setTrainCost(long value)

public ImageClassificationModelMetadata.Builder setTrainCost(long value)

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;

Parameter
NameDescription
valuelong

The trainCost to set.

Returns
TypeDescription
ImageClassificationModelMetadata.Builder

This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final ImageClassificationModelMetadata.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
ImageClassificationModelMetadata.Builder
Overrides