[Bugfix] Fix HYV3 shared_mlp prefix for compressed-tensors ignore matching

HYV3MoEFused built its shared expert (shared_mlp) as an HYV3FeedForward
with `prefix=f"{prefix}"`, omitting the `.shared_mlp` segment. The Linear
layers inside it (gate_up_proj, down_proj) register their parameters under
`...mlp.shared_mlp.<proj>.*` (the attribute name is appended by nn.Module
regardless of the prefix argument), but CompressedTensorsConfig ignores
Linears by matching the *prefix* against its `ignore` list. With the
missing segment the ignore check saw `...mlp.down_proj` instead of
`...mlp.shared_mlp.down_proj`, so a `re:.*shared_mlp.*` ignore entry
failed to match.

Consequence: the shared expert was built as a quantized Linear expecting
weight_packed/scale/shape, while real W4A16 hy_v3 checkpoints (produced
by llm-compressor) correctly keep shared_mlp in BF16 as `.weight`. This
raised `KeyError: '...mlp.shared_mlp.down_proj.weight'` at load time.

Fix: pass `prefix=f"{prefix}.shared_mlp"` so the ignore check matches the
real parameter registration path and the shared expert is built
unquantized (UnquantizedLinearMethod), aligning with the BF16 checkpoint.
Parameter registration names are unchanged.

Co-authored-by: xu_xiaoyi@hotmail.com
Signed-off-by: Xiaoyi Xu <xu_xiaoyi@hotmail.com>

Author: DCoEngine

vllm/model_executor/models/hy_v3.py

@@ -171,7 +171,7 @@ def __init__(
                 intermediate_size=config.expert_hidden_dim * config.num_shared_experts,
                 hidden_act=config.hidden_act,
                 quant_config=quant_config,
-                prefix=f"{prefix}",
+                prefix=f"{prefix}.shared_mlp",
                 reduce_results=False,
             )
         else: