# dgl.udf.NodeBatch.data¶

property NodeBatch.data

Return a view of the node features for the nodes in the batch.

Examples

The following example uses PyTorch backend.

>>> import dgl
>>> import torch

>>> # Instantiate a graph and set a feature 'h'
>>> g = dgl.graph((torch.tensor([0, 1, 1]), torch.tensor([1, 1, 0])))
>>> g.ndata['h'] = torch.ones(2, 1)

>>> # Define a UDF that computes the sum of the messages received and the original feature
>>> # for each node
>>> def node_udf(nodes):
>>>     # nodes.data['h'] is a tensor of shape (N, 1),
>>>     # nodes.mailbox['m'] is a tensor of shape (N, D, 1),
>>>     # where N is the number of nodes in the batch,
>>>     # D is the number of messages received per node for this node batch
>>>     return {'h': nodes.data['h'] + nodes.mailbox['m'].sum(1)}

>>> # Use node UDF in message passing
>>> import dgl.function as fn
>>> g.update_all(fn.copy_u('h', 'm'), node_udf)
>>> g.ndata['h']
tensor([[2.],
[3.]])