[MaxPool model] Created onnx graph with one max pool node

tests/max-pool-model.onnx

+finn-hls-onnx-model:

+p
+inout"StreamingMaxPool*
+ImgDim
*
+NumChannels
*
+PoolDim
*
+backend"fpgadataflow
:finnmax_pool_graphZ
+in
+

+
+
+b
+out
+

+
+
+r
+in
+finn_datatypeBIPOLARr
+out
+finn_datatypeBIPOLARB
\ No newline at end of file

tests/test_layer_streaming_maxpool.py

+# import onnx
+from onnx import TensorProto, helper
+
+from finn.core.datatype import DataType
+from finn.core.modelwrapper import ModelWrapper
+
+
+def test_layer_streaming_maxpool():
+    inp = helper.make_tensor_value_info("in", TensorProto.FLOAT, [2, 4, 4])
+    outp = helper.make_tensor_value_info("out", TensorProto.FLOAT, [2, 2, 2])
+
+    MaxPool_node = helper.make_node(
+        "StreamingMaxPool",
+        ["in"],
+        ["out"],
+        domain="finn",
+        backend="fpgadataflow",
+        ImgDim=4,
+        PoolDim=2,
+        NumChannels=2,
+    )
+
+    graph = helper.make_graph(
+        nodes=[MaxPool_node], name="max_pool_graph", inputs=[inp], outputs=[outp],
+    )
+    model = helper.make_model(graph, producer_name="finn-hls-onnx-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, "max-pool-model.onnx")