adjust tensor creation (#127)

csrc/cpu/fps_cpu.cpp

@@ -24,7 +24,7 @@ torch::Tensor fps_cpu(torch::Tensor src, torch::Tensor ptr, torch::Tensor ratio,
   auto out_ptr = deg.toType(torch::kFloat) * ratio;
   out_ptr = out_ptr.ceil().toType(torch::kLong).cumsum(0);
 
-  auto out = torch::empty(out_ptr[-1].data_ptr<int64_t>()[0], ptr.options());
+  auto out = torch::empty({out_ptr[-1].data_ptr<int64_t>()[0]}, ptr.options());
 
   auto ptr_data = ptr.data_ptr<int64_t>();
   auto out_ptr_data = out_ptr.data_ptr<int64_t>();

csrc/cpu/grid_cpu.cpp

@@ -35,7 +35,7 @@ torch::Tensor grid_cpu(torch::Tensor pos, torch::Tensor size,
   auto num_voxels = (end - start).true_divide(size).toType(torch::kLong) + 1;
   num_voxels = num_voxels.cumprod(0);
   num_voxels =
-      torch::cat({torch::ones(1, num_voxels.options()), num_voxels}, 0);
+      torch::cat({torch::ones({1}, num_voxels.options()), num_voxels}, 0);
   num_voxels = num_voxels.narrow(0, 0, size.size(0));
 
   auto out = pos.true_divide(size.view({1, -1})).toType(torch::kLong);

csrc/cuda/fps_cuda.cu

@@ -80,14 +80,14 @@ torch::Tensor fps_cuda(torch::Tensor src, torch::Tensor ptr,
   auto deg = ptr.narrow(0, 1, batch_size) - ptr.narrow(0, 0, batch_size);
   auto out_ptr = deg.toType(ratio.scalar_type()) * ratio;
   out_ptr = out_ptr.ceil().toType(torch::kLong).cumsum(0);
-  out_ptr = torch::cat({torch::zeros(1, ptr.options()), out_ptr}, 0);
+  out_ptr = torch::cat({torch::zeros({1}, ptr.options()), out_ptr}, 0);
 
   torch::Tensor start;
   if (random_start) {
     start = torch::rand(batch_size, src.options());
     start = (start * deg.toType(ratio.scalar_type())).toType(torch::kLong);
   } else {
-    start = torch::zeros(batch_size, ptr.options());
+    start = torch::zeros({batch_size}, ptr.options());
   }
 
   auto dist = torch::full(src.size(0), 5e4, src.options());
@@ -95,7 +95,7 @@ torch::Tensor fps_cuda(torch::Tensor src, torch::Tensor ptr,
   auto out_size = (int64_t *)malloc(sizeof(int64_t));
   cudaMemcpy(out_size, out_ptr[-1].data_ptr<int64_t>(), sizeof(int64_t),
              cudaMemcpyDeviceToHost);
-  auto out = torch::empty(out_size[0], out_ptr.options());
+  auto out = torch::empty({out_size[0]}, out_ptr.options());
 
   auto stream = at::cuda::getCurrentCUDAStream();
   auto scalar_type = src.scalar_type();

csrc/cuda/grid_cuda.cu

@@ -58,7 +58,7 @@ torch::Tensor grid_cuda(torch::Tensor pos, torch::Tensor size,
   auto start = optional_start.value();
   auto end = optional_end.value();
 
-  auto out = torch::empty(pos.size(0), pos.options().dtype(torch::kLong));
+  auto out = torch::empty({pos.size(0)}, pos.options().dtype(torch::kLong));
 
   auto stream = at::cuda::getCurrentCUDAStream();
   AT_DISPATCH_ALL_TYPES_AND(at::ScalarType::Half, pos.scalar_type(), "_", [&] {

csrc/cuda/knn_cuda.cu

@@ -115,7 +115,7 @@ torch::Tensor knn_cuda(const torch::Tensor x, const torch::Tensor y,
 
   cudaSetDevice(x.get_device());
 
-  auto row = torch::empty(y.size(0) * k, ptr_y.value().options());
+  auto row = torch::empty({y.size(0) * k}, ptr_y.value().options());
   auto col = torch::full(y.size(0) * k, -1, ptr_y.value().options());
 
   dim3 BLOCKS((y.size(0) + THREADS - 1) / THREADS);