error with empty sentences

[dafnevk]

Stroll gives the following error for documents with 'empty' sentences (this example document only contains punctuation):

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-5-3f6234a81ebe> in <module>
----> 1 doc = nlp( '.')

~/anaconda3/envs/filtbubtest/lib/python3.8/site-packages/stanza/pipeline/core.py in __call__(self, doc)
    164         assert any([isinstance(doc, str), isinstance(doc, list),
    165                     isinstance(doc, Document)]), 'input should be either str, list or Document'
--> 166         doc = self.process(doc)
    167         return doc
    168 

~/anaconda3/envs/filtbubtest/lib/python3.8/site-packages/stanza/pipeline/core.py in process(self, doc)
    158         for processor_name in PIPELINE_NAMES:
    159             if self.processors.get(processor_name):
--> 160                 doc = self.processors[processor_name].process(doc)
    161         return doc
    162 

~/filter-bubble/stroll/stroll/stanza.py in process(self, doc)
    112 
    113                 frame_labels, role_labels, \
--> 114                     frame_chance, role_chance = self.net.label(gs)
    115 
    116                 word_offset = 0

~/filter-bubble/stroll/stroll/model.py in label(self, gs)
    354 
    355     def label(self, gs):
--> 356         logitsf, logitsr = self(gs)
    357         logitsf = torch.softmax(logitsf, dim=1)
    358         logitsr = torch.softmax(logitsr, dim=1)

~/anaconda3/envs/filtbubtest/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
    725             result = self._slow_forward(*input, **kwargs)
    726         else:
--> 727             result = self.forward(*input, **kwargs)
    728         for hook in itertools.chain(
    729                 _global_forward_hooks.values(),

~/filter-bubble/stroll/stroll/model.py in forward(self, g)
    345 
    346         # Hidden layers, each of h_dims to h_dims
--> 347         g = self.kernel(g)
    348 
    349         # MLP output

~/anaconda3/envs/filtbubtest/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
    725             result = self._slow_forward(*input, **kwargs)
    726         else:
--> 727             result = self.forward(*input, **kwargs)
    728         for hook in itertools.chain(
    729                 _global_forward_hooks.values(),

~/filter-bubble/stroll/stroll/model.py in forward(self, graph)
    283         # and create a new output and hidden state for step t
    284         for l in range(self.num_layers):
--> 285             graph.update_all(rgcn_msg, rgcn_reduce, rgcn_apply)
    286 
    287         # Batchnorm

~/anaconda3/envs/filtbubtest/lib/python3.8/site-packages/dgl-0.6a210127-py3.8-linux-x86_64.egg/dgl/heterograph.py in update_all(self, message_func, reduce_func, apply_node_func, etype)
   4660         _, dtid = self._graph.metagraph.find_edge(etid)
   4661         g = self if etype is None else self[etype]
-> 4662         ndata = core.message_passing(g, message_func, reduce_func, apply_node_func)
   4663         self._set_n_repr(dtid, ALL, ndata)
   4664 

~/anaconda3/envs/filtbubtest/lib/python3.8/site-packages/dgl-0.6a210127-py3.8-linux-x86_64.egg/dgl/core.py in message_passing(g, mfunc, rfunc, afunc)
    286         else:
    287             orig_eid = g.edata.get(EID, None)
--> 288             msgdata = invoke_edge_udf(g, ALL, g.canonical_etypes[0], mfunc, orig_eid=orig_eid)
    289         # reduce phase
    290         if is_builtin(rfunc):

~/anaconda3/envs/filtbubtest/lib/python3.8/site-packages/dgl-0.6a210127-py3.8-linux-x86_64.egg/dgl/core.py in invoke_edge_udf(graph, eid, etype, func, orig_eid)
     80     ebatch = EdgeBatch(graph, eid if orig_eid is None else orig_eid,
     81                        etype, srcdata, edata, dstdata)
---> 82     return func(ebatch)
     83 
     84 def invoke_udf_reduce(graph, func, msgdata, *, orig_nid=None):

~/filter-bubble/stroll/stroll/model.py in rgcn_msg(edges)
    252             n = edges.data['norm']
    253             msg = torch.bmm(edges.src['output'].unsqueeze(1), w).squeeze()
--> 254             msg = torch.bmm(n.reshape(-1, 1, 1), msg.unsqueeze(1)).squeeze()
    255 
    256             return {'m': msg}

RuntimeError: Expected 3-dimensional tensor, but got 2-dimensional tensor for argument #2 'batch2' (while checking arguments for bmm)

I would say stroll should simply tag no SRLs for this sentence, but not throw an error