Enable support for sparse tensors for multi_tensor_apply (#6)

csrc/multi_tensor_apply.cuh

@@ -56,7 +56,7 @@ void multi_tensor_apply(
     for(int t = 0; t < tensor_lists[l].size(); t++)
     {
       // TODO:  Print which tensor fails.
-      bool contiguous_memory = tensor_lists[l][t].is_contiguous();
+      bool contiguous_memory = (tensor_lists[l][t].is_sparse()) ? tensor_lists[l][t]._values().is_contiguous() : tensor_lists[l][t].is_contiguous();
 #ifdef VERSION_GE_1_5
       contiguous_memory = (contiguous_memory || tensor_lists[l][t].is_contiguous(at::MemoryFormat::ChannelsLast));
 #endif
@@ -78,8 +78,15 @@ void multi_tensor_apply(
   for(int t = 0; t < ntensors; t++)
   {
     tl.sizes[loc_tensor_info] = tensor_lists[0][t].numel();
-    for(int d = 0; d < depth; d++)
-      tl.addresses[d][loc_tensor_info] = tensor_lists[d][t].data_ptr();
+    for(int d = 0; d < depth; d++) {
+      if (tensor_lists[d][t].is_sparse()) {
+        at::Tensor dst = at::zeros(tensor_lists[d][t].sizes(), tensor_lists[d][t].options().layout(at::kStrided));
+        dst.add_(tensor_lists[d][t]);
+        tl.addresses[d][loc_tensor_info] = dst.data_ptr();
+      } else {
+        tl.addresses[d][loc_tensor_info] = tensor_lists[d][t].data_ptr();
+      }
+    }
     loc_tensor_info++;
 
     int chunks_this_tensor = (tensor_lists[0][t].numel() + chunk_size - 1)/chunk_size;