check output type

benchmark/python/utils/benchmark_utils.py

@@ -65,12 +65,15 @@ def run_benchmark(
 ):
     """Run benchmark with specified backends."""
     output = []
+    output_type = None
 
     with torch.no_grad():
         for backend in backends:
             match backend:
                 case Backends.TORCH_SPARSE_EAGER:
-                    output.append(torch_net(*sparse_inputs))
+                    sparse_out = torch_net(*sparse_inputs)
+                    output_type = sparse_out.layout
+                    output.append(sparse_out)
                     runtime_results.append(
                         timer(
                             "torch_net(*sparse_inputs)",
@@ -133,8 +136,14 @@ def run_benchmark(
                         output.append(
                             torch.sparse_csr_tensor(*sp_out, size=dense_out.shape)
                         )
+                        # Check MPACT and torch eager both return sparse csr output.
+                        if output_type:
+                            assert(output_type == torch.sparse_csr)
                     else:
                         output.append(torch.from_numpy(sp_out))
+                        # Check MPACT and torch eager both return dense output.
+                        if output_type:
+                            assert(output_type == torch.strided)
                     invoker, f = mpact_jit_compile(torch_net, *sparse_inputs)
                     compile_time_results.append(
                         timer(