I had the same problem, and couldn’t find any answer to it. So I checked out the torch.onnx docs, and saw that onnx already has an operator for L-normalization (LpNormalization). Then I edited the torch/onnx/symbolic.py file and added a mapping from tensor norm to that operator:
def norm(g, self, p, dim, keepdim):
    return g.op("LpNormalization", self, p_i=p, axis_i=dim)

Additionally, I had to replace this:
x = F.normalize(x, p=2, dim=1)
with this:
x = x / (x.norm(p=2, dim=1, keepdim=True) + 1e-12).expand_as(x)
to avoid having to export clamp_min as well.
That seemed to work for me, hope it helps!