report whether CUDA is built

examples/hello-world.py

@@ -7,8 +7,14 @@
 import torch
 import sparseconvnet as scn
 
-# Use the GPU if there is one, otherwise CPU
-device = 'cuda:0' if torch.cuda.is_available() else 'cpu'
+
+# Use the GPU if there is one and sparseconvnet can use it, otherwise CPU
+use_cuda = torch.cuda.is_available() and scn.SCN.is_cuda_build()
+device = 'cuda:0' if use_cuda else 'cpu'
+if use_cuda:
+    print("Using CUDA.")
+else:
+    print("Not using CUDA.")
 
 model = scn.Sequential().add(
     scn.SparseVggNet(2, 1,

sparseconvnet/SCN/pybind.cpp

@@ -232,4 +232,5 @@ PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
         &CopyFeaturesHelper_updateGradInput, "");
 
   m.def("n_rulebook_bits", []() { return 8 * sizeof(Int); }, "");
+  m.def("is_cuda_build", &is_cuda_build, "");
 }

sparseconvnet/SCN/sparseconvnet.h

@@ -237,3 +237,4 @@ void CopyFeaturesHelper_updateOutput(at::Tensor &rules, at::Tensor &context,
                                      at::Tensor &Context);
 void CopyFeaturesHelper_updateGradInput(at::Tensor &rules, at::Tensor &dcontext,
                                         at::Tensor &dContext);
+bool is_cuda_build();

sparseconvnet/SCN/sparseconvnet_cpu.cpp

@@ -589,3 +589,5 @@ void CopyFeaturesHelper_updateGradInput(at::Tensor &rules, at::Tensor &dcontext,
                                         at::Tensor &dContext) {
   cpu_CopyFeaturesHelper_updateGradInput<float>(rules, dcontext, dContext);
 }
+
+bool is_cuda_build() {return false;}

sparseconvnet/SCN/sparseconvnet_cuda.cpp

@@ -819,3 +819,5 @@ void CopyFeaturesHelper_updateGradInput(at::Tensor &rules, at::Tensor &dcontext,
   else
     cpu_CopyFeaturesHelper_updateGradInput<float>(rules, dcontext, dContext);
 }
+
+bool is_cuda_build() {return true;}