[Test] Apply parallelism independent if it is HLS or RTL variant

tests/fpgadataflow/test_depthwise_convolution.py

@@ -56,7 +56,6 @@
 from finn.transformation.fpgadataflow.prepare_rtlsim import PrepareRTLSim
 from finn.transformation.fpgadataflow.set_exec_mode import SetExecMode
 from finn.transformation.fpgadataflow.specialize_layers import SpecializeLayers
-from finn.util.fpgadataflow import is_fpgadataflow_node
 
 
 def set_up_reference_model(act, idt, wdt, k, ifm_dim, ifm_ch, stride, padding):
@@ -182,21 +181,16 @@ def test_depthwise_conv_hw_cppsim(act, pe, k, stride, padding):
 
     new_model = model.transform(InferConvInpGen())
     new_model = new_model.transform(InferVectorVectorActivation())
-    # for cppsim set all layers to preferred impl style = "hls"
-    for node in new_model.graph.node:
-        if is_fpgadataflow_node(node):
-            inst = getCustomOp(node)
-            inst.set_nodeattr("preferred_impl_style", "hls")
 
     new_model = new_model.transform(SpecializeLayers())
 
     # set SIMD in ConvInputGen node and PE in VVAU node
 
     for n in new_model.graph.node:
-        if n.op_type == "ConvolutionInputGenerator_hls":
+        if n.op_type.startswith("ConvolutionInputGenerator"):
             convinputgen_node = getCustomOp(n)
             convinputgen_node.set_nodeattr("SIMD", pe)
-        elif n.op_type == "VectorVectorActivation_hls":
+        elif n.op_type.startswith("VectorVectorActivation"):
             vvau_node = getCustomOp(n)
             vvau_node.set_nodeattr("PE", pe)
     new_model = new_model.transform(SetExecMode("cppsim"))
@@ -234,13 +228,14 @@ def test_depthwise_conv_hw_rtlsim(act, pe, k, stride, padding):
     new_model = new_model.transform(InferVectorVectorActivation())
 
     new_model = new_model.transform(SpecializeLayers())
+
     # set SIMD in ConvInputGen node and PE in VVAU node
 
     for n in new_model.graph.node:
-        if n.op_type == "ConvolutionInputGenerator_rtl":
+        if n.op_type.startswith("ConvolutionInputGenerator"):
             convinputgen_node = getCustomOp(n)
             convinputgen_node.set_nodeattr("SIMD", pe)
-        elif n.op_type == "VectorVectorActivation_hls":
+        elif n.op_type.startswith("VectorVectorActivation"):
             vvau_node = getCustomOp(n)
             vvau_node.set_nodeattr("PE", pe)