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com.intel.analytics.bigdl.utils.tf

TensorflowSaver

object TensorflowSaver

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  15. def register(className: String, saver: BigDLToTensorflow): Unit

    Register a customized BigDL module saver.

    Register a customized BigDL module saver.

    className

    class name of the BigDL module

    saver

    customized saver

  16. def saveGraph[T](model: Graph[T], inputs: Seq[(String, Seq[Int])], path: String, byteOrder: ByteOrder = ByteOrder.LITTLE_ENDIAN, dataFormat: TensorflowDataFormat = TensorflowDataFormat.NHWC)(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Unit

    Save a graph model to protobuf files so that it can be used in tensorflow inference.

    Save a graph model to protobuf files so that it can be used in tensorflow inference.

    When save the model, placeholders will be added to the tf model as input nodes. So you need to pass in the names and shape for the placeholders. BigDL model doesn't have such information. The order of the placeholder information should be same as the inputs of the graph model

    model

    graph model instance

    inputs

    placeholder information

    path

    where to save

    byteOrder

    model byte order

    dataFormat

    model data format

  17. def saveGraphWithNodeDef[T](model: Graph[T], inputs: Seq[NodeDef], path: String, byteOrder: ByteOrder = ByteOrder.LITTLE_ENDIAN, extraNodes: Set[NodeDef] = Set()): Unit

    Save a graph model to protobuf files so that it can be used in tensorflow inference.

    Save a graph model to protobuf files so that it can be used in tensorflow inference.

    When save the model, placeholders will be added to the tf model as input nodes. So you need to pass in the names and shape for the placeholders. BigDL model doesn't have such information. The order of the placeholder information should be same as the inputs of the graph model

    model

    graph model instance

    inputs

    input node defs

    path

    where to save

    byteOrder

    model byte order

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