subtensor.py 文件源码

def grad(self, inputs, grads):
        global sparse_module_ref
        x, ilist = inputs
        gz, = grads
        assert len(inputs) == 2
        if self.sparse_grad:
            if x.type.ndim != 2:
                raise TypeError(
                    "AdvancedSubtensor1: you can't take the sparse grad"
                    " from a tensor with ndim != 2. ndim is " +
                    str(x.type.ndim))
            if sparse_module_ref is None:
                import theano.sparse as sparse_module_ref

            rval1 = [sparse_module_ref.construct_sparse_from_list(x, gz,
                                                                  ilist)]
        else:
            rval1 = [advanced_inc_subtensor1(x.zeros_like(), gz, ilist)]
        return rval1 + [DisconnectedType()()] * (len(inputs) - 1)