def forward(self, graph, feat):
        r"""Compute max pooling.

        Parameters
        ----------
        graph : DGLGraph
            A DGLGraph or a batch of DGLGraphs.
        feat : torch.Tensor
            The input feature with shape :math:`(N, *)`, where
            :math:`N` is the number of nodes in the graph.

        Returns
        -------
        torch.Tensor
            The output feature with shape :math:`(B, *)`, where
            :math:`B` refers to the batch size.
        """
        with graph.local_scope():
            graph.ndata["h"] = feat
            readout = max_nodes(graph, "h")
            return readout
Compute max pooling.

        Parameters
        ----------
        graph : DGLGraph
            A DGLGraph or a batch of DGLGraphs.
        feat : torch.Tensor
            The input feature with shape :math:`(N, *)`, where
            :math:`N` is the number of nodes in the graph.

        Returns
        -------
        torch.Tensor
            The output feature with shape :math:`(B, *)`, where
            :math:`B` refers to the batch size.
        
python/dgl/nn/pytorch/glob.py