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fix(glm4_moe): load compressed-tensors NVFP4 expert checkpoints #430

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fix(glm4_moe): load compressed-tensors NVFP4 expert checkpoints #430

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24 changes: 24 additions & 0 deletions python/freetoken/models/glm4_moe/weight.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,6 +35,24 @@
),
desc="GLM NVFP4 experts",
)
# llm-compressor export (gesong2077/GLM-4.5-Air-NVFP4): weight_packed | weight_scale |
# weight_global_scale (quant-side global -> reciprocal at ingest). Same treatment glm5_next
# gives its compressed-tensors release. ``input_global_scale`` (the calibrated W4A4 activation
# scale) deliberately does not match: the routed-expert path is W4A16 and never quantizes
# activations.
_ROUTED_EXPERT_CT_KEY_RE = re.compile(
r"^model\.layers\.(?P<layer>\d+)\.mlp\.experts\.(?P<expert>\d+)\."
r"(?P<proj>gate_proj|up_proj|down_proj)\."
r"(?P<kind>weight_packed|weight_global_scale|weight_scale)$"
)
_NVFP4_CT_SOURCE_SPEC = Nvfp4ExpertSourceSpec(
key_pattern=_ROUTED_EXPERT_CT_KEY_RE,
proj_to_role={"gate_proj": "gate", "up_proj": "up", "down_proj": "down"},
layer_to_bank=_NVFP4_SOURCE_SPEC.layer_to_bank,
desc="GLM NVFP4 experts (compressed-tensors)",
kind_map={"weight_packed": "weight", "weight_global_scale": "weight_scale_2"},
global_reciprocal=True,
)


# --------------------------------------------------------------------------------------
Expand Down Expand Up @@ -191,6 +209,12 @@ def _iter_resident_weights(reader, config, primary) -> Iterator[tuple[str, torch
# Routed expert host banks (NVFP4) for the offload cache.
# --------------------------------------------------------------------------------------
def nvfp4_expert_spec(model_path: str, config):
"""The expert reader for this checkpoint's dialect: modelopt names, or the
compressed-tensors ones folded back onto them."""
quant = getattr(cached_load_hf_config(model_path), "quantization_config", None) or {}
get = quant.get if isinstance(quant, dict) else (lambda k, d=None: getattr(quant, k, d))
if str(get("quant_method") or "").lower() == "compressed-tensors":
return _NVFP4_CT_SOURCE_SPEC
return _NVFP4_SOURCE_SPEC


Expand Down