return C with batch

setup.py

@@ -2,7 +2,7 @@ from os import path as osp
 
 from setuptools import setup, find_packages
 
-__version__ = '0.2.0'
+__version__ = '0.2.1'
 url = 'https://github.com/rusty1s/pytorch_cluster'
 
 install_requires = ['cffi', 'torch-unique']

test/test_grid.py

@@ -50,7 +50,7 @@ def test_grid_cluster_cpu(tensor):
     output, C = grid_cluster(position, size, batch, fake_nodes=True)
     expected = torch.LongTensor([0, 5, 1, 0, 2, 6, 11, 7, 6, 8])
     assert output.tolist() == expected.tolist()
-    assert C == 6
+    assert C == 12
 
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason='no CUDA')
@@ -101,4 +101,4 @@ def test_grid_cluster_gpu(tensor):  # pragma: no cover
     output, C = grid_cluster(position, size, batch, fake_nodes=True)
     expected = torch.LongTensor([0, 5, 1, 0, 2, 6, 11, 7, 6, 8])
     assert output.cpu().tolist() == expected.tolist()
-    assert C == 6
+    assert C == 12

torch_cluster/__init__.py

 from .functions.grid import grid_cluster
 
-__version__ = '0.2.0'
+__version__ = '0.2.1'
 
 __all__ = ['grid_cluster', '__version__']

torch_cluster/functions/grid.py

@@ -50,7 +50,7 @@ def grid_cluster(position, size, batch=None, origin=None, fake_nodes=False):
     cluster = cluster.squeeze(dim=-1)
 
     if fake_nodes:
-        return cluster, C // c_max[0]
+        return cluster, C
 
     cluster, u = consecutive(cluster)
     return cluster, None if batch is None else (u / (C // c_max[0])).long()