code: func (co *Context) ConvolutionBackwardBias(alpha float64, dyDesc *TensorDescriptor, dy Memory, beta float64, dbDesc *TensorDescriptor, db Memory) error {
  	// DOUBLECHECK: "cudnnConvolutionBackwardBias" returns Memory type in Parameter 6
  	var alphaC, betaC unsafe.Pointer
  	switch dyDesc.dataType {
  	case Float, Half:
  		var alphaF, betaF C.float
  		alphaF = C.float(float32(alpha))
  		betaF = C.float(float32(beta))
  		alphaC = unsafe.Pointer(&alphaF)
  		betaC = unsafe.Pointer(&betaF)
  	case Double:
  		var alphaF, betaF C.double
  		alphaF = C.double(alpha)
  		betaF = C.double(beta)
  		alphaC = unsafe.Pointer(&alphaF)
  		betaC = unsafe.Pointer(&betaF)
  	default:
  		return errors.Errorf("Unsupported data type: %v", dyDesc.dataType)
  	}
  	// call cudnnConvolutionBackwardBias
  	return result(C.cudnnConvolutionBackwardBias(co.internal, alphaC, dyDesc.internal, dy.Pointer(), betaC, dbDesc.internal, db.Pointer()))
  }
docs: // ConvolutionBackwardBias computes the convolution function gradient with respect to the bias, which is the sum of every element belonging to the same feature map across all of the images of the input tensor. Therefore, the number of elements produced is equal to the number of features maps of the input tensor.