pub fn convolve2_gradient_nn<T>(
incoming_grad: &Array<T>,
original_signal: &Array<T>,
original_filter: &Array<T>,
convolved_output: &Array<T>,
strides: Dim4,
padding: Dim4,
dilation: Dim4,
grad_type: ConvGradientType,
) -> Array<T>where
T: HasAfEnum + RealFloating,Expand description
Backward pass gradient of 2D convolution
§Parameters
incoming_gradientgradients to be distributed in backwards passoriginal_signalinput signal to forward pass of convolution assumed structure of input is ( d0 x d1 x d2 x N )original_filterinput filter to forward pass of convolution assumed structure of input is ( d0 x d1 x d2 x N )convolved_outputoutput from forward pass of convolutionstridesare distance between consecutive elements along each dimension for original convolutionpaddingspecifies padding width along each dimension for original convolutiondilationspecifies filter dilation along each dimension for original convolutiongrad_typespecifies which gradient to return
§Return Values
Gradient Array w.r.t input generated from convolve2_nn