[Test] Added unit test file which creates a graph with one streaming_fclayer_batch node

tests/test_layer_streaming_fclayer_batch.py

+import onnx
+from onnx import TensorProto, helper
+import numpy as np
+
+import finn.core.onnx_exec as oxe
+from finn.core.datatype import DataType
+from finn.core.modelwrapper import ModelWrapper
+
+
+def test_fclayer_batch():
+    inp = helper.make_tensor_value_info("inp", TensorProto.FLOAT, [1, 13, 64])
+    outp = helper.make_tensor_value_info("outp", TensorProto.FLOAT, [1, 32, 32])
+
+    FCLayer_node = helper.make_node(
+        "StreamingFCLayer_Batch",
+        ["inp", "weights", "thresh"],
+        ["outp"],
+        domain='finn',
+        backend='fpgadataflow',
+        resType="ap_resource_lut()",
+        MW=832,
+        MH=1024,
+        SIMD=64,
+        PE=32,
+        resDataType="Recast<XnorMul>",
+    )
+
+    graph = helper.make_graph(
+        nodes=[FCLayer_node], name="fclayer_graph", inputs=[inp], outputs=[outp], value_info=[
+            helper.make_tensor_value_info("weights", TensorProto.FLOAT, [64, 32, 416]),
+            helper.make_tensor_value_info("thresh", TensorProto.FLOAT, [32, 32, 1, 16, 1])]
+    )
+
+    model = helper.make_model(graph, producer_name="fclayer-model")
+    model = ModelWrapper(model)
+
+    # set the tensor datatypes (in this case: all to bipolar)
+    for tensor in graph.input:
+        model.set_tensor_datatype(tensor.name, DataType["BIPOLAR"])
+    for tensor in graph.output:
+        model.set_tensor_datatype(tensor.name, DataType["BIPOLAR"])
+
+    onnx.save(model.model, "fclayer-model.onnx")
+
+    # generate input data
+    input_tensor = np.random.randint(2, size=832)
+    input_tensor = (np.asarray(input_tensor, dtype=np.float32)).reshape(1,13,64)
+    print(input_tensor)
+