Convolution

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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. def apply(input: DifferentiableField, weights: DifferentiableField, border: libcog.BorderPolicy, stride: Int = 1, impl: ConvolutionalLayerPolicy = Best): DifferentiableField

   

   Create Compute/State Node pair.

   Create Compute/State Node pair. This selects between a spatial domain and frequency domain implementation depending on the impl policy and other parameters.

   input

   the input signal DifferentiableField

   weights

   the weight DifferentiableField for this convolution

   border

   the policy for supplying missing input values for border convolutions

   stride

   the downsample factor applied to the output of the convolution

   impl

   the policy for selecting the convolution implementation (spacial vs frequency domain)

   returns

   The convolutional Node. The associated ConvolutionalState node can be accessed as the in2 Node member of the returned node.

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18. var tuneForNvidiaMaxwell: Boolean

    

19. final def wait(): Unit

    

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