Inferred shape and existing shape differ in dimension 1 when trying to invoke InferStreamingMaxPool()

[lumawu]

Currently trying to port binarized Version of Alexnet to pynq board. I am leaning on the cnv_end2end notebook.
During the chapter 3: "Partitioning, Conversion to HLS Layers and Folding" I get the following error when invoking "model.transform(to_hls.InferStreamingMaxPool())":

RuntimeError: Inferred shape and existing shape differ in dimension 1: (11) vs (16)

Right before this, my model looks like this:

I don't see where in my model this is referring to, and I don't know how to fix it once located. Can someone help?