[Test] Change test for swg dws to verify result

tests/fpgadataflow/test_fpgadataflow_convinputgenerator.py

@@ -102,7 +102,7 @@ def make_single_slidingwindow_modelwrapper(
         Stride=stride,
         inputDataType=idt.name,
         outputDataType=odt.name,
-        depthwise=dw
+        depthwise=dw,
     )
     graph = helper.make_graph(
         nodes=[SlidingWindow_node],
@@ -138,14 +138,18 @@ def prepare_inputs(input_tensor):
 @pytest.mark.parametrize("exec_mode", ["cppsim", "rtlsim"])
 # input channel parallelism ("SIMD")
 @pytest.mark.parametrize("simd", [1, 2])
+# depthwise
+@pytest.mark.parametrize("dw", [0, 1])
 @pytest.mark.slow
 @pytest.mark.vivado
-def test_fpgadataflow_slidingwindow(idt, k, ifm_dim, ifm_ch, stride, exec_mode, simd):
+def test_fpgadataflow_slidingwindow(
+    idt, k, ifm_dim, ifm_ch, stride, exec_mode, simd, dw
+):
     ofm_dim = int(((ifm_dim - k) / stride) + 1)
 
     x = gen_finn_dt_tensor(idt, (1, ifm_dim, ifm_dim, ifm_ch))
     model = make_single_slidingwindow_modelwrapper(
-        k, ifm_ch, ifm_dim, ofm_dim, simd, stride, idt
+        k, ifm_ch, ifm_dim, ofm_dim, simd, stride, idt, dw
     )
 
     if exec_mode == "cppsim":
@@ -169,50 +173,12 @@ def test_fpgadataflow_slidingwindow(idt, k, ifm_dim, ifm_ch, stride, exec_mode,
         k, ifm_ch, ifm_dim, ofm_dim, simd, stride, idt
     )
     y_expected = oxe.execute_onnx(golden, input_dict)["outp"]
-    assert (y_produced == y_expected).all()
-    
-# input datatype
-@pytest.mark.parametrize("idt", [DataType.BIPOLAR, DataType.INT2])
-# kernel size
-@pytest.mark.parametrize("k", [2, 4])
-# input dimension
-@pytest.mark.parametrize("ifm_dim", [4, 6, 8])
-# input channels
-@pytest.mark.parametrize("ifm_ch", [2, 4]) 
-# Stride
-@pytest.mark.parametrize("stride", [1, 2])
-# execution mode
-@pytest.mark.parametrize("exec_mode", ["cppsim", "rtlsim"])
-# input channel parallelism ("SIMD")
-@pytest.mark.parametrize("simd", [1, 2])
-@pytest.mark.slow
-@pytest.mark.vivado
-def test_fpgadataflow_slidingwindow_dw(idt, k, ifm_dim, ifm_ch, stride, exec_mode, simd):
-    # set node attribute depthwise
-    dw = 1
-    ofm_dim = int(((ifm_dim - k) / stride) + 1)
-
-    x = gen_finn_dt_tensor(idt, (1, ifm_dim, ifm_dim, ifm_ch))
-    model = make_single_slidingwindow_modelwrapper(
-        k, ifm_ch, ifm_dim, ofm_dim, simd, stride, idt, dw
-    )
-
-    if exec_mode == "cppsim":
-        model = model.transform(SetExecMode("cppsim"))
-        model = model.transform(PrepareCppSim())
-        model = model.transform(CompileCppSim())
-    elif exec_mode == "rtlsim":
-        model = model.transform(SetExecMode("rtlsim"))
-        model = model.transform(GiveUniqueNodeNames())
-        model = model.transform(PrepareIP("xc7z020clg400-1", 5))
-        model = model.transform(HLSSynthIP())
-        model = model.transform(PrepareRTLSim())
+    if dw == 0:
+        assert (y_produced == y_expected).all()
     else:
-        raise Exception("Unknown exec_mode in test_fpgadataflow_slidingwindow")
-
-    # prepare input data
-    input_dict = prepare_inputs(x)
-    # execute model
-    y_produced = oxe.execute_onnx(model, input_dict)["outp"]
-    y_shape = (1, ofm_dim, ofm_dim, k*k*ifm_ch)
-    assert y_produced.shape == y_shape
+        y_expected = y_expected.reshape(
+            1, ofm_dim, ofm_dim, k * k, ifm_ch // simd, simd
+        )
+        y_expected = y_expected.transpose(0, 1, 2, 4, 3, 5)
+        y_expected = y_expected.reshape(1, ofm_dim, ofm_dim, ifm_ch * k * k)
+        assert (y_produced == y_expected).all()