

def grad(self, inputs, gout):
    (x,) = inputs
    (gz,) = gout
    gx = dense_from_sparse(gz)
    gx = tensor.patternbroadcast(gx, x.broadcastable)
    return (gx,)

dataset/ETHPy150Open rizar/attention-lvcsr/libs/Theano/theano/sparse/basic.py SparseFromDense.grad/original