[CustomOp] Add execute_node to QuantAvgPool2d custom op

src/finn/custom_op/quantavgpool2d.py

 import numpy as np
 from onnx import TensorProto, helper
+import onnxruntime as rt
 
 from finn.custom_op import CustomOp
 from finn.custom_op.im2col import compute_conv_output_dim
+from finn.core.datatype import DataType
 
 
 class QuantAvgPool2d(CustomOp):
@@ -54,7 +56,40 @@ class QuantAvgPool2d(CustomOp):
         model.set_tensor_datatype(node.output[0], dtype)
 
     def execute_node(self, context, graph):
-        pass
+        # create a standard average pooling node to help calculate the result
+        node = self.onnx_node
+        k = self.get_nodeattr("kernel")
+        s = self.get_nodeattr("stride")
+        ishape = context[node.input[0]].shape
+        oshape = context[node.output[0]].shape
+        inp = helper.make_tensor_value_info(node.input[0], TensorProto.FLOAT, ishape)
+        outp = helper.make_tensor_value_info(node.output[0], TensorProto.FLOAT, oshape)
+        node_avgpool = helper.make_node(
+            "AveragePool",
+            inputs=[node.input[0]],
+            outputs=[node.output[0]],
+            kernel_shape=[k, k],
+            strides=[s, s]
+        )
+        graph_avgpool = helper.make_graph(
+                nodes=[node_avgpool],
+                name="single-avgpool-exec",
+                inputs=[inp],
+                outputs=[outp],
+                )
+        model_avgpool = helper.make_model(graph_avgpool)
+        idict = {node.input[0] : context[node.input[0]]}
+        sess = rt.InferenceSession(model_avgpool.SerializeToString())
+        result_temp = sess.run(None, idict)
+        # remove scaling introduced by average
+        result_temp = (result_temp[0] * (k * k)).astype(int)
+        max_value = np.max(result_temp)
+        max_bit_width = int(max_value).bit_length()
+        shift_bits = max_bit_width - self.get_nodeattr("obits")
+        shift_array = np.ones(result_temp.shape, dtype=np.int) * shift_bits
+        result = np.right_shift(result_temp, shift_array)
+
+        context[node.output[0]] = result
 
     def verify_node(self):
         pass