diff --git a/tests/end2end/test_end2end_bnn_pynq.py b/tests/end2end/test_end2end_bnn_pynq.py
index d0a9aa1c073d4f93e48b0d7d1ece17e1c288f56a..a6e7ad642222936775293ec145e845ef111dd4d3 100644
--- a/tests/end2end/test_end2end_bnn_pynq.py
+++ b/tests/end2end/test_end2end_bnn_pynq.py
@@ -347,6 +347,8 @@ class TestEnd2End:
         assert os.path.isfile(chkpt_preproc_name)
         # join preprocessing and core model
         pre_model = ModelWrapper(chkpt_preproc_name)
+        pre_model = pre_model.transform(InferShapes())
+        pre_model = pre_model.transform(FoldConstants())
         model = model.transform(MergeONNXModels(pre_model))
         # add input quantization annotation: UINT8 for all BNN-PYNQ models
         global_inp_name = model.graph.input[0].name
diff --git a/tests/end2end/test_end2end_mobilenet_v1.py b/tests/end2end/test_end2end_mobilenet_v1.py
index 6e11a30a410c5a76e1b056277346a6b88a7ec1bf..79263a7099b91fb0dbaa10871f7859690ab9e4c2 100644
--- a/tests/end2end/test_end2end_mobilenet_v1.py
+++ b/tests/end2end/test_end2end_mobilenet_v1.py
@@ -101,6 +101,7 @@ def test_end2end_mobilenet_export():
     # set input finn datatype to UINT8
     preproc_model.set_tensor_datatype(preproc_model.graph.input[0].name, DataType.UINT8)
     preproc_model = preproc_model.transform(InferShapes())
+    preproc_model = preproc_model.transform(FoldConstants())
     preproc_model = preproc_model.transform(GiveUniqueNodeNames())
     preproc_model = preproc_model.transform(GiveUniqueParameterTensors())
     preproc_model = preproc_model.transform(GiveReadableTensorNames())