CaffeLoader

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1. final def !=(arg0: AnyRef): Boolean

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2. final def !=(arg0: Any): Boolean

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3. final def ##(): Int

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4. final def ==(arg0: AnyRef): Boolean

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6. final def asInstanceOf[T0]: T0

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7. def clone(): AnyRef

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8. final def eq(arg0: AnyRef): Boolean

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10. def finalize(): Unit

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11. final def getClass(): Class[_]

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12. def hashCode(): Int

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13. final def isInstanceOf[T0]: Boolean

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14. def load[T](model: Module[T], defPath: String, modelPath: String, matchAll: Boolean = true, customizedConverters: HashMap[String, Customizable[T]] = null)(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Module[T]

    Load weight for pre-defined model

    Load weight for pre-defined model

    T

    data type

    model

    pre-defined model

    defPath

    prototxt file which defines the network

    modelPath

    weight file which contains the parameters

    matchAll

    if we need to match all layers from prototxt in weight file

    customizedConverters

    customized converters

    ev

    tensor numeric

    returns

    pre-defined model populated with weights

15. def loadCaffe[T](defPath: String, modelPath: String, customizedConverters: HashMap[String, Customizable[T]] = null, outputNames: Array[String] = Array[String]())(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): (Module[T], ParallelCriterion[T])

    load caffe model dynamically from prototxt and binary files

    load caffe model dynamically from prototxt and binary files

    T

    data type

    defPath

    prototxt file which illustrates the caffe model structure

    modelPath

    binary file containing the weight and bias

    customizedConverters

    customized layer converter

    outputNames

    additional output layer names besides the default(layers without next nodes)

    returns

    created module (graph) and criterion

16. final def ne(arg0: AnyRef): Boolean

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17. final def notify(): Unit

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18. final def notifyAll(): Unit

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19. final def synchronized[T0](arg0: ⇒ T0): T0

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20. def toString(): String

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21. final def wait(): Unit

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22. final def wait(arg0: Long, arg1: Int): Unit

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23. final def wait(arg0: Long): Unit

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