def MaxPoolUndo(images, targets, grad, maxes, subsX, startX, strideX, outputsX):
 assert (targets.shape == images.shape)
 _ConvNet.MaxPoolUndo(images.p_mat, grad.p_mat, maxes.p_mat, targets.p_mat, subsX, startX, strideX, outputsX)

def MaxPoolUndo ( images , targets , grad , maxes , subsX , startX , strideX , outputsX ) : assert ( targets . shape == images . shape ) _ConvNet . MaxPoolUndo ( images . p_mat , grad . p_mat , maxes . p_mat , targets . p_mat , subsX , startX , strideX , outputsX )
images - grad - cudamat of deltas/gradients of loss wrt layer outputs .