diff --git a/tests/fpgadataflow/test_convert_to_hls_layers_cnv.py b/tests/fpgadataflow/test_convert_to_hls_layers_cnv.py
index c0fec7c42b7a93a082b6af190cf3441b1e20e04d..de358f0aa92abe67251382c793e3f23742a0a45e 100644
--- a/tests/fpgadataflow/test_convert_to_hls_layers_cnv.py
+++ b/tests/fpgadataflow/test_convert_to_hls_layers_cnv.py
@@ -44,7 +44,6 @@ from finn.util.test import get_test_model_trained
 from finn.transformation.double_to_single_float import DoubleToSingleFloat
 from finn.transformation.lower_convs_to_matmul import LowerConvsToMatMul
 from finn.transformation.bipolar_to_xnor import ConvertBipolarMatMulToXnorPopcount
-from finn.transformation.streamline.round_thresholds import RoundAndClipThresholds
 import finn.transformation.fpgadataflow.convert_to_hls_layers as to_hls
 from finn.transformation.fpgadataflow.codegen_npysim import CodeGen_npysim
 from finn.transformation.fpgadataflow.compile import Compile
@@ -68,9 +67,7 @@ def test_convert_to_hls_layers_cnv_w1a1():
     model = model.transform(MakeMaxPoolNHWC())
     model = model.transform(absorb.AbsorbTransposeIntoMultiThreshold())
     model = model.transform(ConvertBipolarMatMulToXnorPopcount())
-    model = model.transform(absorb.AbsorbAddIntoMultiThreshold())
-    model = model.transform(absorb.AbsorbMulIntoMultiThreshold())
-    model = model.transform(RoundAndClipThresholds())
+    model = model.transform(Streamline())
     model.save("golden.onnx")
     # load one of the test vectors
     fn = pk.resource_filename("finn", "data/cifar10/cifar10-test-data-class3.npz")