

def grad(self, inputs, gout):
    (x, y, p) = inputs
    (gz,) = inputs
    rval = [dot((p * gz), y), dot((p * gz).T, x), grad_not_implemented(self, 2, p)]
    return rval

dataset/ETHPy150Open rizar/attention-lvcsr/libs/Theano/theano/sparse/basic.py SamplingDot.grad/VarMisuse@29/32 `gout`->`inputs`