[Test] add thresholding test that triggers multi-inp error case

tests/fpgadataflow/test_fpgadataflow_thresholding.py

@@ -52,11 +52,13 @@ from finn.transformation.general import GiveUniqueNodeNames
 from finn.util.basic import gen_finn_dt_tensor
 from finn.util.pyverilator import axilite_read, axilite_write
 
-test_fpga_part = "xc7z020clg400-1"
+test_fpga_part = "xczu3eg-sbva484-1-e"
 target_clk_ns = 5
 
 
-def make_single_thresholding_modelwrapper(T, pe, idt, odt, actval, mem_mode):
+def make_single_thresholding_modelwrapper(
+    T, pe, idt, odt, actval, mem_mode, n_inp_vecs
+):
     NumChannels = T.shape[0]
 
     inp = helper.make_tensor_value_info("inp", TensorProto.FLOAT, [1, NumChannels])
@@ -78,6 +80,7 @@ def make_single_thresholding_modelwrapper(T, pe, idt, odt, actval, mem_mode):
         outputDataType=odt.name,
         ActVal=actval,
         mem_mode=mem_mode,
+        numInputVectors=[n_inp_vecs],
     )
     graph = helper.make_graph(
         nodes=[Thresholding_node],
@@ -115,10 +118,11 @@ def test_fpgadataflow_thresholding(idt, act, nf, ich, exec_mode, mem_mode):
     if nf == -1:
         nf = ich
     pe = ich // nf
+    n_inp_vecs = 2
     assert ich % pe == 0
 
     # generate input data
-    x = gen_finn_dt_tensor(idt, (1, ich))
+    x = gen_finn_dt_tensor(idt, (n_inp_vecs, ich))
 
     odt = act
     n_steps = act.get_num_possible_values() - 1
@@ -135,7 +139,9 @@ def test_fpgadataflow_thresholding(idt, act, nf, ich, exec_mode, mem_mode):
     else:
         actval = odt.min()
 
-    model = make_single_thresholding_modelwrapper(T, pe, idt, odt, actval, mem_mode)
+    model = make_single_thresholding_modelwrapper(
+        T, pe, idt, odt, actval, mem_mode, n_inp_vecs
+    )
 
     if exec_mode == "cppsim":
         model = model.transform(PrepareCppSim())
@@ -185,6 +191,7 @@ def test_fpgadataflow_thresholding(idt, act, nf, ich, exec_mode, mem_mode):
 
 @pytest.mark.vivado
 def test_runtime_thresholds_single_layer():
+    n_inp_vecs = 2
     mem_mode = "decoupled"
     act = DataType["INT4"]
     idt = DataType["INT16"]
@@ -194,7 +201,7 @@ def test_runtime_thresholds_single_layer():
     assert ich % pe == 0
 
     # generate input data
-    in_tensor = gen_finn_dt_tensor(idt, (1, ich))
+    in_tensor = gen_finn_dt_tensor(idt, (n_inp_vecs, ich))
 
     odt = act
     n_steps = act.get_num_possible_values() - 1
@@ -207,7 +214,9 @@ def test_runtime_thresholds_single_layer():
     else:
         actval = odt.min()
 
-    model = make_single_thresholding_modelwrapper(T, pe, idt, odt, actval, mem_mode)
+    model = make_single_thresholding_modelwrapper(
+        T, pe, idt, odt, actval, mem_mode, n_inp_vecs
+    )
     op_inst = getCustomOp(model.graph.node[0])
     op_inst.set_nodeattr("runtime_writeable_weights", 1)
     op_inst.make_weight_file(T, "decoupled_runtime", "old_weights.dat")