Package com.google.cloud.automl.v1

Class ImageClassificationModelMetadata

    • Field Detail

      • BASE_MODEL_ID_FIELD_NUMBER

        public static final int BASE_MODEL_ID_FIELD_NUMBER
        See Also:
        Constant Field Values

      • TRAIN_BUDGET_MILLI_NODE_HOURS_FIELD_NUMBER

        public static final int TRAIN_BUDGET_MILLI_NODE_HOURS_FIELD_NUMBER
        See Also:
        Constant Field Values

      • TRAIN_COST_MILLI_NODE_HOURS_FIELD_NUMBER

        public static final int TRAIN_COST_MILLI_NODE_HOURS_FIELD_NUMBER
        See Also:
        Constant Field Values

      • STOP_REASON_FIELD_NUMBER

        public static final int STOP_REASON_FIELD_NUMBER
        See Also:
        Constant Field Values

      • MODEL_TYPE_FIELD_NUMBER

        public static final int MODEL_TYPE_FIELD_NUMBER
        See Also:
        Constant Field Values

      • NODE_COUNT_FIELD_NUMBER

        public static final int NODE_COUNT_FIELD_NUMBER
        See Also:
        Constant Field Values

    • Method Detail

      • newInstance

        protected Object newInstance​(com.google.protobuf.GeneratedMessageV3.UnusedPrivateParameter unused)
        Overrides:
        newInstance in class com.google.protobuf.GeneratedMessageV3

      • getDescriptor

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

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3

      • 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.GeneratedMessageV3

      • 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.GeneratedMessageV3
        Throws:
        IOException

      • getSerializedSize

        public int getSerializedSize()
        Specified by:
        getSerializedSize in interface com.google.protobuf.MessageLite
        Overrides:
        getSerializedSize in class com.google.protobuf.GeneratedMessageV3

      • 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,
                                                         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

      • newBuilderForType

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

      • 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.GeneratedMessageV3.BuilderParent parent)
        Specified by:
        newBuilderForType in class com.google.protobuf.GeneratedMessageV3

      • 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.GeneratedMessageV3

      • getDefaultInstanceForType

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