public final class ImageClassificationModelMetadata extends GeneratedMessageV3 implements ImageClassificationModelMetadataOrBuilder
Model metadata for image classification.
Protobuf type google.cloud.automl.v1.ImageClassificationModelMetadata
Static Fields
public static final int BASE_MODEL_ID_FIELD_NUMBER
Field Value
public static final int MODEL_TYPE_FIELD_NUMBER
Field Value
public static final int NODE_COUNT_FIELD_NUMBER
Field Value
public static final int NODE_QPS_FIELD_NUMBER
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public static final int STOP_REASON_FIELD_NUMBER
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public static final int TRAIN_BUDGET_MILLI_NODE_HOURS_FIELD_NUMBER
Field Value
public static final int TRAIN_COST_MILLI_NODE_HOURS_FIELD_NUMBER
Field Value
Static Methods
public static ImageClassificationModelMetadata getDefaultInstance()
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public static final Descriptors.Descriptor getDescriptor()
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public static ImageClassificationModelMetadata.Builder newBuilder()
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public static ImageClassificationModelMetadata.Builder newBuilder(ImageClassificationModelMetadata prototype)
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public static ImageClassificationModelMetadata parseDelimitedFrom(InputStream input)
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Exceptions
public static ImageClassificationModelMetadata parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
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public static ImageClassificationModelMetadata parseFrom(byte[] data)
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| Name | Description |
| data | byte[]
|
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public static ImageClassificationModelMetadata parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
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public static ImageClassificationModelMetadata parseFrom(ByteString data)
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public static ImageClassificationModelMetadata parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
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public static ImageClassificationModelMetadata parseFrom(CodedInputStream input)
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public static ImageClassificationModelMetadata parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
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public static ImageClassificationModelMetadata parseFrom(InputStream input)
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public static ImageClassificationModelMetadata parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
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public static ImageClassificationModelMetadata parseFrom(ByteBuffer data)
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public static ImageClassificationModelMetadata parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
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public static Parser<ImageClassificationModelMetadata> parser()
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Methods
public boolean equals(Object obj)
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Overrides
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 [(.google.api.field_behavior) = OPTIONAL];
| Type | Description |
| String | The baseModelId.
|
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 [(.google.api.field_behavior) = OPTIONAL];
| Type | Description |
| ByteString | The bytes for baseModelId.
|
public ImageClassificationModelMetadata getDefaultInstanceForType()
Returns
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 [(.google.api.field_behavior) = OPTIONAL];
| Type | Description |
| String | The modelType.
|
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 [(.google.api.field_behavior) = OPTIONAL];
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];
| 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 = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| double | The nodeQps.
|
public Parser<ImageClassificationModelMetadata> getParserForType()
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Overrides
public int getSerializedSize()
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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];
| 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];
| 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(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];
| 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 = 17 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| long | The trainCostMilliNodeHours.
|
public final UnknownFieldSet getUnknownFields()
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protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
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public final boolean isInitialized()
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Overrides
public ImageClassificationModelMetadata.Builder newBuilderForType()
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protected ImageClassificationModelMetadata.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
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protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
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Overrides
public ImageClassificationModelMetadata.Builder toBuilder()
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public void writeTo(CodedOutputStream output)
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Overrides
Exceptions
