[pkmandke]

tl;dr: module_input_spec={0: ...} on a decomposed SDPA module resolved to a SymInt from sym_size. prepare() then attached a FakeQuantize to a Python int and crashed on tensor.ndim. This fix skips non-float boundary values during prepare() in graph mode.

---

A module-level module_input_spec / module_output_spec that resolves to a
shape integer crashes prepare:

AttributeError: 'int' object has no attribute 'ndim'
  qparams_calculator.py:340  self._resolve_axis(tensor.ndim)

The prepared graph has activation_post_process_N(sym_size_int_M): a
FakeQuantize attached to a Python int.

Change/Fix

Skip non-floating-point values in _find_and_apply_module_level_spec (inputs and
outputs).

How it was found

module_input_spec={0: <fp8>} on a decomposed SDPA module, meant to quantize the
query. SDPA builds its causal mask from shape integers before touching the query,
so boundary input 0 ends up being a SymInt.

Tests

TestNonFloatModuleBoundary in test_graph_mode_quantizer.py, for the wildcard
and {0: spec} cases. Both fail before this change with the error above and
pass after.