fix

Author: xadupre

onnx_diagnostic/_command_lines_parser.py

@@ -1233,9 +1233,11 @@ def _size(name):
         use_tensor=True,
         exc=False,
     ):
-        data.append(post_process_run_aligned_obs(obs))
-        df = pandas.DataFrame(data)
-        df.to_excel(args.output)
+        pobs = post_process_run_aligned_obs(obs)
+        data.append(pobs)
+        if "initializer" not in pobs and "placeholder" not in pobs:
+            df = pandas.DataFrame(data)
+            df.to_excel(args.output)
     print("-- done")
 
 

onnx_diagnostic/helpers/ort_session.py

@@ -502,11 +502,8 @@ def run_dlpack(
             if not v.is_contiguous():
                 v = v.contiguous()
             if v.dtype == torch.bool:
-                # It does not work with dlpack
-                # unless onnxruntime updates the version it is using.
-                v = ORTC.OrtValue.ortvalue_from_numpy_with_onnx_type(
-                    v.detach().numpy(), onnx.TensorProto.BOOL
-                )
+                v = v.to(torch.uint8)
+                v = ORTC.OrtValue.from_dlpack(v.__dlpack__(), True)
             else:
                 v = ORTC.OrtValue.from_dlpack(v.__dlpack__(), False)
             input_names.append(k)

onnx_diagnostic/torch_onnx/sbs.py

@@ -563,8 +563,10 @@ def _loop_cmp(
             print(f"[run_aligned-nx] +inp: {inp.name}: {string_type(v, **str_kws)}")
 
     placeholders = {node.name for node in ep.graph.nodes if node.op == "placeholder"}
+    ep_state_dict = {**ep.state_dict, **dict(ep.named_buffers())}
     placeholders_to_state_dict = {
-        f"p_{name.replace('.', '_')}": name for name in ep.state_dict
+        **{f"p_{name.replace('.', '_')}": name for name in ep.state_dict},
+        **{f"b_{name.replace('.', '_')}": name for name, _ in ep.named_buffers()},
     }
     for n in onnx_results:
         if n not in placeholders:
@@ -622,7 +624,7 @@ def _loop_cmp(
                     f"Unable to find placeholder {node.name!r} in "
                     f"{sorted(placeholders_to_state_dict)}"
                 )
-                torch_results[node.name] = ep.state_dict[placeholders_to_state_dict[node.name]]
+                torch_results[node.name] = ep_state_dict[placeholders_to_state_dict[node.name]]
                 if verbose:
                     print(f"[run_aligned-ep] +plh: {node.name}={string_type(t, **str_kws)}")
                 yield (