Package com.google.cloud.automl.v1beta1

Class ImageClassificationModelMetadata.Builder

    • Method Detail

      • 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.Builder<ImageClassificationModelMetadata.Builder>

      • getDescriptorForType

        public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
        Specified by:
        getDescriptorForType in interface com.google.protobuf.Message.Builder
        Specified by:
        getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
        Overrides:
        getDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder>

      • getDefaultInstanceForType

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

      • build

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

      • buildPartial

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

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<ImageClassificationModelMetadata.Builder>

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

      • setBaseModelId

        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;
        Parameters:
        value - The baseModelId to set.
        Returns:
        This builder for chaining.

      • 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:
        This builder for chaining.

      • setBaseModelIdBytes

        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;
        Parameters:
        value - The bytes for baseModelId to set.
        Returns:
        This builder for chaining.

      • 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;
        Specified by:
        getTrainBudget in interface ImageClassificationModelMetadataOrBuilder
        Returns:
        The trainBudget.

      • setTrainBudget

        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;
        Parameters:
        value - The trainBudget to set.
        Returns:
        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:
        This builder for chaining.

      • 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;
        Specified by:
        getTrainCost in interface ImageClassificationModelMetadataOrBuilder
        Returns:
        The trainCost.

      • setTrainCost

        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;
        Parameters:
        value - The trainCost to set.
        Returns:
        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:
        This builder for chaining.

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

      • setStopReason

        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;
        Parameters:
        value - The stopReason to set.
        Returns:
        This builder for chaining.

      • 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:
        This builder for chaining.

      • setStopReasonBytes

        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;
        Parameters:
        value - The bytes for stopReason to set.
        Returns:
        This builder for chaining.

      • 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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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;
        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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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;
        Specified by:
        getModelTypeBytes in interface ImageClassificationModelMetadataOrBuilder
        Returns:
        The bytes for modelType.

      • setModelType

        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][google.cloud.automl.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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;
        Parameters:
        value - The modelType to set.
        Returns:
        This builder for chaining.

      • 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][google.cloud.automl.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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:
        This builder for chaining.

      • setModelTypeBytes

        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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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.v1beta1.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;
        Parameters:
        value - The bytes for modelType to set.
        Returns:
        This builder for chaining.

      • 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;
        Specified by:
        getNodeQps in interface ImageClassificationModelMetadataOrBuilder
        Returns:
        The nodeQps.

      • setNodeQps

        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;
        Parameters:
        value - The nodeQps to set.
        Returns:
        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:
        This builder for chaining.

      • 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;
        Specified by:
        getNodeCount in interface ImageClassificationModelMetadataOrBuilder
        Returns:
        The nodeCount.

      • setNodeCount

        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;
        Parameters:
        value - The nodeCount to set.
        Returns:
        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:
        This builder for chaining.