[fix(externalize)] Skip fully-specialised dims in submodule re-export#7
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[fix(externalize)] Skip fully-specialised dims in submodule re-export#7gokulkrishna98 wants to merge 1 commit into
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When externalising an SDPA submodule, ``_dynamic_shapes_from_node`` requested a Dim for every SymInt in the upstream FakeTensor's shape — including SymInts whose ``.node.expr`` had been specialised to a literal int by the parent program. Those re-exported as an unbounded ``Dim(min=1)`` and ``torch.export`` rejected the submodule with ``L['key'].size()[2] <= IntInfinity()`` whenever a model used a static query length and a dynamic KV-context length (the prefill / decode shape used by hybrid linear-attention models). Skip SymInts whose expr is already a number — they are static dims and should not appear in ``dynamic_shapes`` at all. Signed-off-by: gokulkrishna98 <gokulkrishna98@users.noreply.github.com>
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