[Type Hints] nn.GraphSizeNorm (pyg-team#5729)

Co-authored-by: Matthias Fey <matthias.fey@tu-dortmund.de>

CHANGELOG.md

@@ -43,7 +43,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Support `in_channels` with `tuple` in `GENConv` for bipartite message passing ([#5627](https://github.com/pyg-team/pytorch_geometric/pull/5627), [#5641](https://github.com/pyg-team/pytorch_geometric/pull/5641))
 - Handle cases of not having enough possible negative edges in `RandomLinkSplit` ([#5642](https://github.com/pyg-team/pytorch_geometric/pull/5642))
 - Fix `RGCN+pyg-lib` for `LongTensor` input ([#5610](https://github.com/pyg-team/pytorch_geometric/pull/5610))
-- Improved type hint support ([#5603](https://github.com/pyg-team/pytorch_geometric/pull/5603), [#5659](https://github.com/pyg-team/pytorch_geometric/pull/5659), [#5664](https://github.com/pyg-team/pytorch_geometric/pull/5664), [#5665](https://github.com/pyg-team/pytorch_geometric/pull/5665), [#5666](https://github.com/pyg-team/pytorch_geometric/pull/5666), [#5667](https://github.com/pyg-team/pytorch_geometric/pull/5667), [#5668](https://github.com/pyg-team/pytorch_geometric/pull/5668), [#5669](https://github.com/pyg-team/pytorch_geometric/pull/5669), [#5673](https://github.com/pyg-team/pytorch_geometric/pull/5673), [#5675](https://github.com/pyg-team/pytorch_geometric/pull/5675), [#5673](https://github.com/pyg-team/pytorch_geometric/pull/5676), [#5678](https://github.com/pyg-team/pytorch_geometric/pull/5678), [#5682](https://github.com/pyg-team/pytorch_geometric/pull/5682), [#5683](https://github.com/pyg-team/pytorch_geometric/pull/5683), [#5684](https://github.com/pyg-team/pytorch_geometric/pull/5684), [#5685](https://github.com/pyg-team/pytorch_geometric/pull/5685), [#5687](https://github.com/pyg-team/pytorch_geometric/pull/5687), [#5688](https://github.com/pyg-team/pytorch_geometric/pull/5688), [#5695](https://github.com/pyg-team/pytorch_geometric/pull/5695), [#5699](https://github.com/pyg-team/pytorch_geometric/pull/5699), [#5701] (https://github.com/pyg-team/pytorch_geometric/pull/5701), [#5702](https://github.com/pyg-team/pytorch_geometric/pull/5702), [#5703](https://github.com/pyg-team/pytorch_geometric/pull/5703), [#5706](https://github.com/pyg-team/pytorch_geometric/pull/5706), [#5707](https://github.com/pyg-team/pytorch_geometric/pull/5707), [#5710](https://github.com/pyg-team/pytorch_geometric/pull/5710), [#5714](https://github.com/pyg-team/pytorch_geometric/pull/5714)), [#5722](https://github.com/pyg-team/pytorch_geometric/pull/5722))
+- Improved type hint support ([#5603](https://github.com/pyg-team/pytorch_geometric/pull/5603), [#5659](https://github.com/pyg-team/pytorch_geometric/pull/5659), [#5664](https://github.com/pyg-team/pytorch_geometric/pull/5664), [#5665](https://github.com/pyg-team/pytorch_geometric/pull/5665), [#5666](https://github.com/pyg-team/pytorch_geometric/pull/5666), [#5667](https://github.com/pyg-team/pytorch_geometric/pull/5667), [#5668](https://github.com/pyg-team/pytorch_geometric/pull/5668), [#5669](https://github.com/pyg-team/pytorch_geometric/pull/5669), [#5673](https://github.com/pyg-team/pytorch_geometric/pull/5673), [#5675](https://github.com/pyg-team/pytorch_geometric/pull/5675), [#5673](https://github.com/pyg-team/pytorch_geometric/pull/5676), [#5678](https://github.com/pyg-team/pytorch_geometric/pull/5678), [#5682](https://github.com/pyg-team/pytorch_geometric/pull/5682), [#5683](https://github.com/pyg-team/pytorch_geometric/pull/5683), [#5684](https://github.com/pyg-team/pytorch_geometric/pull/5684), [#5685](https://github.com/pyg-team/pytorch_geometric/pull/5685), [#5687](https://github.com/pyg-team/pytorch_geometric/pull/5687), [#5688](https://github.com/pyg-team/pytorch_geometric/pull/5688), [#5695](https://github.com/pyg-team/pytorch_geometric/pull/5695), [#5699](https://github.com/pyg-team/pytorch_geometric/pull/5699), [#5701] (https://github.com/pyg-team/pytorch_geometric/pull/5701), [#5702](https://github.com/pyg-team/pytorch_geometric/pull/5702), [#5703](https://github.com/pyg-team/pytorch_geometric/pull/5703), [#5706](https://github.com/pyg-team/pytorch_geometric/pull/5706), [#5707](https://github.com/pyg-team/pytorch_geometric/pull/5707), [#5710](https://github.com/pyg-team/pytorch_geometric/pull/5710), [#5714](https://github.com/pyg-team/pytorch_geometric/pull/5714)), [#5722](https://github.com/pyg-team/pytorch_geometric/pull/5722), [#5729](https://github.com/pyg-team/pytorch_geometric/pull/5729))
 - Avoid modifying `mode_kwargs` in `MultiAggregation` ([#5601](https://github.com/pyg-team/pytorch_geometric/pull/5601))
 - Changed `BatchNorm` to allow for batches of size one during training ([#5530](https://github.com/pyg-team/pytorch_geometric/pull/5530), [#5614](https://github.com/pyg-team/pytorch_geometric/pull/5614))
 - Integrated better temporal sampling support by requiring that local neighborhoods are sorted according to time ([#5516](https://github.com/pyg-team/pytorch_geometric/issues/5516), [#5602](https://github.com/pyg-team/pytorch_geometric/issues/5602))

test/nn/norm/test_graph_size_norm.py

@@ -1,10 +1,19 @@
 import torch
 
 from torch_geometric.nn import GraphSizeNorm
+from torch_geometric.testing import is_full_test
 
 
 def test_graph_size_norm():
+    x = torch.randn(100, 16)
     batch = torch.repeat_interleave(torch.full((10, ), 10, dtype=torch.long))
+
     norm = GraphSizeNorm()
-    out = norm(torch.randn(100, 16), batch)
+    assert str(norm) == 'GraphSizeNorm()'
+
+    out = norm(x, batch)
     assert out.size() == (100, 16)
+
+    if is_full_test():
+        jit = torch.jit.script(norm)
+        assert torch.allclose(jit(x, batch), out)

torch_geometric/nn/norm/graph_size_norm.py

@@ -1,6 +1,8 @@
 import torch
 import torch.nn as nn
+from torch import Tensor
 
+from torch_geometric.typing import OptTensor
 from torch_geometric.utils import degree
 
 
@@ -16,10 +18,13 @@ class GraphSizeNorm(nn.Module):
     def __init__(self):
         super().__init__()
 
-    def forward(self, x, batch=None):
+    def forward(self, x: Tensor, batch: OptTensor = None) -> Tensor:
         """"""
         if batch is None:
             batch = torch.zeros(x.size(0), dtype=torch.long, device=x.device)
 
         inv_sqrt_deg = degree(batch, dtype=x.dtype).pow(-0.5)
         return x * inv_sqrt_deg.index_select(0, batch).view(-1, 1)
+
+    def __repr__(self) -> str:
+        return f'{self.__class__.__name__}()'