

def bprop(self, error, alpha=1.0, beta=0.0):
    for l in reversed(self._layers):
        altered_tensor = l.be.distribute_data(error, l.parallelism)
        if altered_tensor:
            l.revert_list.append(altered_tensor)
        if ((type(l.prev_layer) is BranchNode) or (l is self._layers[0])):
            error = l.bprop(error, alpha, beta)
        else:
            error = tensor.bprop(error)
        for tensor in l.revert_list:
            l.be.revert_tensor(tensor)
    return self._layers[0].deltas

dataset/ETHPy150Open NervanaSystems/neon/neon/layers/container.py Sequential.bprop/VarMisuse@109/134 `l`->`tensor`