Package com.google.cloud.automl.v1

Class ImageClassificationModelMetadata

java.lang.Object
com.google.protobuf.AbstractMessageLite
com.google.protobuf.AbstractMessage
com.google.protobuf.GeneratedMessage
com.google.cloud.automl.v1.ImageClassificationModelMetadata
All Implemented Interfaces:
ImageClassificationModelMetadataOrBuilder, com.google.protobuf.Message, com.google.protobuf.MessageLite, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Serializable
@Generated public final class ImageClassificationModelMetadata extends com.google.protobuf.GeneratedMessage implements ImageClassificationModelMetadataOrBuilder
 Model metadata for image classification.
Protobuf type google.cloud.automl.v1.ImageClassificationModelMetadata
See Also:

  • Field Details

    • BASE_MODEL_ID_FIELD_NUMBER

      public static final int BASE_MODEL_ID_FIELD_NUMBER
      See Also:

    • TRAIN_BUDGET_MILLI_NODE_HOURS_FIELD_NUMBER

      public static final int TRAIN_BUDGET_MILLI_NODE_HOURS_FIELD_NUMBER
      See Also:

    • TRAIN_COST_MILLI_NODE_HOURS_FIELD_NUMBER

      public static final int TRAIN_COST_MILLI_NODE_HOURS_FIELD_NUMBER
      See Also:

    • STOP_REASON_FIELD_NUMBER

      public static final int STOP_REASON_FIELD_NUMBER
      See Also:

    • MODEL_TYPE_FIELD_NUMBER

      public static final int MODEL_TYPE_FIELD_NUMBER
      See Also:

    • NODE_QPS_FIELD_NUMBER

      public static final int NODE_QPS_FIELD_NUMBER
      See Also:

    • NODE_COUNT_FIELD_NUMBER

      public static final int NODE_COUNT_FIELD_NUMBER
      See Also:

  • Method Details

    • getDescriptor

      public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage

    • 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 [(.google.api.field_behavior) = OPTIONAL];
      Specified by:
      getBaseModelId in interface ImageClassificationModelMetadataOrBuilder
      Returns:
      The baseModelId.

    • getBaseModelIdBytes

      public 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];
      Specified by:
      getBaseModelIdBytes in interface ImageClassificationModelMetadataOrBuilder
      Returns:
      The bytes for baseModelId.

    • getTrainBudgetMilliNodeHours

      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];
      Specified by:
      getTrainBudgetMilliNodeHours in interface ImageClassificationModelMetadataOrBuilder
      Returns:
      The trainBudgetMilliNodeHours.

    • getTrainCostMilliNodeHours

      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];
      Specified by:
      getTrainCostMilliNodeHours in interface ImageClassificationModelMetadataOrBuilder
      Returns:
      The trainCostMilliNodeHours.

    • getStopReason

      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];
      Specified by:
      getStopReason in interface ImageClassificationModelMetadataOrBuilder
      Returns:
      The stopReason.

    • getStopReasonBytes

      public 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];
      Specified by:
      getStopReasonBytes in interface ImageClassificationModelMetadataOrBuilder
      Returns:
      The bytes for stopReason.

    • 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][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];
      Specified by:
      getModelType in interface ImageClassificationModelMetadataOrBuilder
      Returns:
      The modelType.

    • getModelTypeBytes

      public 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];
      Specified by:
      getModelTypeBytes in interface ImageClassificationModelMetadataOrBuilder
      Returns:
      The bytes for modelType.

    • 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 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getNodeQps in interface ImageClassificationModelMetadataOrBuilder
      Returns:
      The nodeQps.

    • 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 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getNodeCount in interface ImageClassificationModelMetadataOrBuilder
      Returns:
      The nodeCount.

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessage

    • writeTo

      public void writeTo(com.google.protobuf.CodedOutputStream output) throws IOException
      Specified by:
      writeTo in interface com.google.protobuf.MessageLite
      Overrides:
      writeTo in class com.google.protobuf.GeneratedMessage
      Throws:
      IOException

    • getSerializedSize

      public int getSerializedSize()
      Specified by:
      getSerializedSize in interface com.google.protobuf.MessageLite
      Overrides:
      getSerializedSize in class com.google.protobuf.GeneratedMessage

    • equals

      public boolean equals(Object obj)
      Specified by:
      equals in interface com.google.protobuf.Message
      Overrides:
      equals in class com.google.protobuf.AbstractMessage

    • hashCode

      public int hashCode()
      Specified by:
      hashCode in interface com.google.protobuf.Message
      Overrides:
      hashCode in class com.google.protobuf.AbstractMessage

    • parseFrom

      public static ImageClassificationModelMetadata parseFrom(ByteBuffer data) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException

    • parseFrom

      public static ImageClassificationModelMetadata parseFrom(ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException

    • parseFrom

      public static ImageClassificationModelMetadata parseFrom(com.google.protobuf.ByteString data) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException

    • parseFrom

      public static ImageClassificationModelMetadata parseFrom(com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException

    • parseFrom

      public static ImageClassificationModelMetadata parseFrom(byte[] data) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException

    • parseFrom

      public static ImageClassificationModelMetadata parseFrom(byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException

    • parseFrom

      public static ImageClassificationModelMetadata parseFrom(InputStream input) throws IOException
      Throws:
      IOException

    • parseFrom

      public static ImageClassificationModelMetadata parseFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Throws:
      IOException

    • parseDelimitedFrom

      public static ImageClassificationModelMetadata parseDelimitedFrom(InputStream input) throws IOException
      Throws:
      IOException

    • parseDelimitedFrom

      public static ImageClassificationModelMetadata parseDelimitedFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Throws:
      IOException

    • parseFrom

      public static ImageClassificationModelMetadata parseFrom(com.google.protobuf.CodedInputStream input) throws IOException
      Throws:
      IOException

    • parseFrom

      public static ImageClassificationModelMetadata parseFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Throws:
      IOException

    • newBuilderForType

      public ImageClassificationModelMetadata.Builder newBuilderForType()
      Specified by:
      newBuilderForType in interface com.google.protobuf.Message
      Specified by:
      newBuilderForType in interface com.google.protobuf.MessageLite

    • newBuilder

      public static ImageClassificationModelMetadata.Builder newBuilder()

    • newBuilder

      public static ImageClassificationModelMetadata.Builder newBuilder(ImageClassificationModelMetadata prototype)

    • toBuilder

      public ImageClassificationModelMetadata.Builder toBuilder()
      Specified by:
      toBuilder in interface com.google.protobuf.Message
      Specified by:
      toBuilder in interface com.google.protobuf.MessageLite

    • newBuilderForType

      protected ImageClassificationModelMetadata.Builder newBuilderForType(com.google.protobuf.AbstractMessage.BuilderParent parent)
      Overrides:
      newBuilderForType in class com.google.protobuf.AbstractMessage

    • getDefaultInstance

      public static ImageClassificationModelMetadata getDefaultInstance()

    • parser

      public static com.google.protobuf.Parser<ImageClassificationModelMetadata> parser()

    • getParserForType

      public com.google.protobuf.Parser<ImageClassificationModelMetadata> getParserForType()
      Specified by:
      getParserForType in interface com.google.protobuf.Message
      Specified by:
      getParserForType in interface com.google.protobuf.MessageLite
      Overrides:
      getParserForType in class com.google.protobuf.GeneratedMessage

    • getDefaultInstanceForType

      public ImageClassificationModelMetadata getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder