upgrade to PyTorch 1.10

Author: rusty1s

.github/workflows/testing.yml

@@ -11,7 +11,7 @@ jobs:
       matrix:
         os: [ubuntu-latest, windows-latest]
         python-version: [3.6]
-        torch-version: [1.8.0, 1.9.0]
+        torch-version: [1.9.0, 1.10.0]
 
     steps:
       - uses: actions/checkout@v2

csrc/cuda/segment_coo_cuda.cu

@@ -274,7 +274,7 @@ segment_coo_cuda(torch::Tensor src, torch::Tensor index,
         if (out.is_floating_point())
           out.true_divide_(count);
         else
-          out.floor_divide_(count);
+          out.div_(count, "floor");
       }
     });
   });

csrc/scatter.cpp

@@ -132,7 +132,7 @@ class ScatterMean : public torch::autograd::Function<ScatterMean> {
     if (out.is_floating_point())
       out.true_divide_(count);
     else
-      out.floor_divide_(count);
+      out.div_(count, "floor");
 
     ctx->save_for_backward({index, count});
     if (optional_out.has_value())

torch_scatter/scatter.py

@@ -38,7 +38,6 @@ def scatter_mul(src: torch.Tensor, index: torch.Tensor, dim: int = -1,
 def scatter_mean(src: torch.Tensor, index: torch.Tensor, dim: int = -1,
                  out: Optional[torch.Tensor] = None,
                  dim_size: Optional[int] = None) -> torch.Tensor:
-
     out = scatter_sum(src, index, dim, out, dim_size)
     dim_size = out.size(dim)
 
@@ -55,7 +54,7 @@ def scatter_mean(src: torch.Tensor, index: torch.Tensor, dim: int = -1,
     if out.is_floating_point():
         out.true_divide_(count)
     else:
-        out.floor_divide_(count)
+        out.div_(count, rounding_mode='floor')
     return out