CaffeLoader

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

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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4. final def asInstanceOf[T0]: T0

   

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5. def clone(): AnyRef

   

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

   

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7. def equals(arg0: Any): Boolean

   

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8. def finalize(): Unit

   

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

   

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10. def hashCode(): Int

    

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11. final def isInstanceOf[T0]: Boolean

    

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

    

13. 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 binary and prototxt file

    load caffe model dynamically from binary and prototxt file

    T

    data type

    defPath

    prototxt file which illustrate 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

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

    

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15. final def notify(): Unit

    

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16. final def notifyAll(): Unit

    

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

    

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18. def toString(): String

    

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19. final def wait(): Unit

    

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

    

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

    

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