bugfix

test/utils/test_ffi.py

+import torch
+from torch_cluster.functions.utils.ffi import ffi_serial
+
+
+def test_serial_cpu():
+    row = torch.LongTensor([0, 0, 1, 1, 1, 2, 2, 2, 3, 3])
+    col = torch.LongTensor([1, 2, 0, 2, 3, 0, 1, 3, 1, 2])
+    degree = torch.LongTensor([2, 3, 3, 2])
+    cluster = ffi_serial(row, col, degree)
+    expected_cluster = [0, 0, 2, 2]
+    assert cluster.tolist() == expected_cluster
+
+    weight = torch.Tensor([1, 2, 1, 3, 2, 2, 3, 3, 2, 3])
+    cluster = ffi_serial(row, col, degree, weight)
+    expected_cluster = [0, 1, 0, 1]
+    assert cluster.tolist() == expected_cluster

torch_cluster/functions/utils/ffi.py

@@ -12,7 +12,8 @@ def _get_typed_func(name, tensor):
     return getattr(ffi, 'cluster_{}_{}{}'.format(name, cuda, typename))
 
 
-def ffi_serial(output, row, col, degree, weight=None):
+def ffi_serial(row, col, degree, weight=None):
+    output = row.new(degree.size(0)).fill_(-1)
     if weight is None:
         func = _get_func('serial', row)
         func(output, row, col, degree)

torch_cluster/src/serial_cpu.c

@@ -11,7 +11,7 @@
   int64_t e = 0, row_value, col_value, value; \
   while(e < THLongTensor_nElement(row)) { \
     row_value = row_data[e]; \
-    if (output_data[row_value] >= 0) { \
+    if (output_data[row_value] < 0) { \
       col_value = -1; \
       SELECT \
       if (col_value < 0) { \