public static final class ImageClassificationModelMetadata.Builder extends com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder> implements ImageClassificationModelMetadataOrBuilder
Model metadata for image classification.Protobuf type
google.cloud.automl.v1.ImageClassificationModelMetadatagetAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMapFieldReflection, internalGetMutableMapField, internalGetMutableMapFieldReflection, isClean, markClean, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setUnknownFieldSetBuilder, setUnknownFieldsProto3findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toStringaddAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, newUninitializedMessageExceptionequals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitpublic static final com.google.protobuf.Descriptors.Descriptor getDescriptor()
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder>public ImageClassificationModelMetadata.Builder clear()
clear in interface com.google.protobuf.Message.Builderclear in interface com.google.protobuf.MessageLite.Builderclear in class com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder>public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
getDescriptorForType in interface com.google.protobuf.Message.BuildergetDescriptorForType in interface com.google.protobuf.MessageOrBuildergetDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder>public ImageClassificationModelMetadata getDefaultInstanceForType()
getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuildergetDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilderpublic ImageClassificationModelMetadata build()
build in interface com.google.protobuf.Message.Builderbuild in interface com.google.protobuf.MessageLite.Builderpublic ImageClassificationModelMetadata buildPartial()
buildPartial in interface com.google.protobuf.Message.BuilderbuildPartial in interface com.google.protobuf.MessageLite.Builderpublic ImageClassificationModelMetadata.Builder clone()
clone in interface com.google.protobuf.Message.Builderclone in interface com.google.protobuf.MessageLite.Builderclone in class com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder>public ImageClassificationModelMetadata.Builder setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
setField in interface com.google.protobuf.Message.BuildersetField in class com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder>public ImageClassificationModelMetadata.Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field)
clearField in interface com.google.protobuf.Message.BuilderclearField in class com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder>public ImageClassificationModelMetadata.Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)
clearOneof in interface com.google.protobuf.Message.BuilderclearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder>public ImageClassificationModelMetadata.Builder setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
setRepeatedField in interface com.google.protobuf.Message.BuildersetRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder>public ImageClassificationModelMetadata.Builder addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
addRepeatedField in interface com.google.protobuf.Message.BuilderaddRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder>public ImageClassificationModelMetadata.Builder mergeFrom(com.google.protobuf.Message other)
mergeFrom in interface com.google.protobuf.Message.BuildermergeFrom in class com.google.protobuf.AbstractMessage.Builder<ImageClassificationModelMetadata.Builder>public ImageClassificationModelMetadata.Builder mergeFrom(ImageClassificationModelMetadata other)
public final boolean isInitialized()
isInitialized in interface com.google.protobuf.MessageLiteOrBuilderisInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder>public ImageClassificationModelMetadata.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
mergeFrom in interface com.google.protobuf.Message.BuildermergeFrom in interface com.google.protobuf.MessageLite.BuildermergeFrom in class com.google.protobuf.AbstractMessage.Builder<ImageClassificationModelMetadata.Builder>IOExceptionpublic 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];getBaseModelId in interface ImageClassificationModelMetadataOrBuilderpublic com.google.protobuf.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];getBaseModelIdBytes in interface ImageClassificationModelMetadataOrBuilderpublic 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];value - The baseModelId to set.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];public ImageClassificationModelMetadata.Builder setBaseModelIdBytes(com.google.protobuf.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];value - The bytes for baseModelId to set.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];
getTrainBudgetMilliNodeHours in interface ImageClassificationModelMetadataOrBuilderpublic 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];
value - The trainBudgetMilliNodeHours to set.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];
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];
getTrainCostMilliNodeHours in interface ImageClassificationModelMetadataOrBuilderpublic 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];
value - The trainCostMilliNodeHours to set.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];
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];getStopReason in interface ImageClassificationModelMetadataOrBuilderpublic com.google.protobuf.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];getStopReasonBytes in interface ImageClassificationModelMetadataOrBuilderpublic 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];value - The stopReason to set.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];public ImageClassificationModelMetadata.Builder setStopReasonBytes(com.google.protobuf.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];value - The bytes for stopReason to set.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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];getModelType in interface ImageClassificationModelMetadataOrBuilderpublic com.google.protobuf.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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];getModelTypeBytes in interface ImageClassificationModelMetadataOrBuilderpublic 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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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];value - The modelType to set.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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];public ImageClassificationModelMetadata.Builder setModelTypeBytes(com.google.protobuf.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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][google.cloud.automl.v1.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];value - The bytes for modelType to set.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];getNodeQps in interface ImageClassificationModelMetadataOrBuilderpublic 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];value - The nodeQps to set.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];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];getNodeCount in interface ImageClassificationModelMetadataOrBuilderpublic 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];value - The nodeCount to set.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];public final ImageClassificationModelMetadata.Builder setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
setUnknownFields in interface com.google.protobuf.Message.BuildersetUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder>public final ImageClassificationModelMetadata.Builder mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
mergeUnknownFields in interface com.google.protobuf.Message.BuildermergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder>Copyright © 2025 Google LLC. All rights reserved.