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torchsparsegradutils/indexed_matmul.py

@@ -49,7 +49,7 @@ def segment_mm(a, b, seglen_a):
 
     # Ideally the conversions below to nested tensor would be handled natively
     nested_a = torch.nested.as_nested_tensor(torch.tensor_split(a, segidx_a, dim=0))
-    nested_b = torch.nested.as_nested_tensor(torch.split(b, 1, dim=0)).reshape((R,D1,D2))
+    nested_b = torch.nested.as_nested_tensor(torch.split(b, 1, dim=0)).reshape((R, D1, D2))
 
     # The actual gather matmul computation
     nested_ab = torch.matmul(nested_a, nested_b)
@@ -105,7 +105,7 @@ def gather_mm(a, b, idx_b):
     # Ideally the conversions below to nested tensor would be handled without for looops and without copy
     nested_a = torch.nested.as_nested_tensor([a[idx_b == i, :] for i in range(R)])
     src_idx_reshuffled = torch.cat([src_idx[idx_b == i] for i in range(R)])
-    nested_b = torch.nested.as_nested_tensor(torch.split(b, 1, dim=0)).reshape((R,D1,D2))
+    nested_b = torch.nested.as_nested_tensor(torch.split(b, 1, dim=0)).reshape((R, D1, D2))
 
     # The actual gather matmul computation
     nested_ab = torch.matmul(nested_a, nested_b)