diff --git a/src/finn/custom_op/fpgadataflow/streamingmaxpool_batch.py b/src/finn/custom_op/fpgadataflow/streamingmaxpool_batch.py
index 83bc19030ebba66907e08c5b1e52d7c0ff9207a6..7334c913b6f85cad4835b6e65eb14c488432af6b 100644
--- a/src/finn/custom_op/fpgadataflow/streamingmaxpool_batch.py
+++ b/src/finn/custom_op/fpgadataflow/streamingmaxpool_batch.py
@@ -65,7 +65,12 @@ class StreamingMaxPool_Batch(HLSCustomOp):
         return ishape
 
     def get_folded_input_shape(self):
-        return self.get_normal_input_shape()
+        # even though there is no folding in the current hlslib op,
+        # insert a time multiplexing axis to remain compatible with the
+        # shapes produced by the rest of the dataflow pipeline
+        ret = list(self.get_normal_input_shape())
+        ret.insert(-1, 1)
+        return tuple(ret)
 
     def get_normal_output_shape(self):
         k = self.get_nodeattr("PoolDim")
@@ -79,9 +84,12 @@ class StreamingMaxPool_Batch(HLSCustomOp):
         return oshape
 
     def get_folded_output_shape(self):
-        # no folding for StreamingMaxPool
-        oshape = self.get_normal_output_shape()
-        return oshape
+        # even though there is no folding in the current hlslib op,
+        # insert a time multiplexing axis to remain compatible with the
+        # shapes produced by the rest of the dataflow pipeline
+        ret = list(self.get_normal_output_shape())
+        ret.insert(-1, 1)
+        return tuple(ret)
 
     def get_number_output_values(self):
         folded_oshape = self.get_folded_output_shape()