def call(self, graph, feat):
        r"""Compute Graph Isomorphism Network layer.

        Parameters
        ----------
        graph : DGLGraph
            The graph.
        feat : tf.Tensor or pair of tf.Tensor
            If a tf.Tensor is given, the input feature of shape :math:`(N, D_{in})` where
            :math:`D_{in}` is size of input feature, :math:`N` is the number of nodes.
            If a pair of tf.Tensor is given, the pair must contain two tensors of shape
            :math:`(N_{in}, D_{in})` and :math:`(N_{out}, D_{in})`.
            If ``apply_func`` is not None, :math:`D_{in}` should
            fit the input dimensionality requirement of ``apply_func``.

        Returns
        -------
        tf.Tensor
            The output feature of shape :math:`(N, D_{out})` where
            :math:`D_{out}` is the output dimensionality of ``apply_func``.
            If ``apply_func`` is None, :math:`D_{out}` should be the same
            as input dimensionality.
        """
        with graph.local_scope():
            feat_src, feat_dst = expand_as_pair(feat, graph)
            graph.srcdata["h"] = feat_src
            graph.update_all(fn.copy_u("h", "m"), self._reducer("m", "neigh"))
            rst = (1 + self.eps) * feat_dst + graph.dstdata["neigh"]
            if self.apply_func is not None:
                rst = self.apply_func(rst)
            return rst
Compute Graph Isomorphism Network layer.

        Parameters
        ----------
        graph : DGLGraph
            The graph.
        feat : tf.Tensor or pair of tf.Tensor
            If a tf.Tensor is given, the input feature of shape :math:`(N, D_{in})` where
            :math:`D_{in}` is size of input feature, :math:`N` is the number of nodes.
            If a pair of tf.Tensor is given, the pair must contain two tensors of shape
            :math:`(N_{in}, D_{in})` and :math:`(N_{out}, D_{in})`.
            If ``apply_func`` is not None, :math:`D_{in}` should
            fit the input dimensionality requirement of ``apply_func``.

        Returns
        -------
        tf.Tensor
            The output feature of shape :math:`(N, D_{out})` where
            :math:`D_{out}` is the output dimensionality of ``apply_func``.
            If ``apply_func`` is None, :math:`D_{out}` should be the same
            as input dimensionality.
        
python/dgl/nn/tensorflow/conv/ginconv.py