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model : add BailingMoeV2 support (#16063)
* add BailingMoeV2 support * update llm types * undo * undo * update llm types * add model collection link * update * almost working * correct group selection and rename n_group_exp * avoid large top_k and use argmax instead for now if we had something like argmax2 that would be equivalent, but this works fine until then * poke * skip group selection when there are no tokens * fix 1T conversion * hopefully fixed expert group selection third time's the charm? * make expert group selection generally available The new LLaDA2Moe model uses this method too, make it generally available regardless of architecture. * allow n_expert_groups to be 1 (Kimi K2) * address review suggestions
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@@ -102,6 +102,8 @@ class Keys:
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EXPERT_COUNT = "{arch}.expert_count"
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EXPERT_USED_COUNT = "{arch}.expert_used_count"
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EXPERT_SHARED_COUNT = "{arch}.expert_shared_count"
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EXPERT_GROUP_COUNT = "{arch}.expert_group_count"
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EXPERT_GROUP_USED_COUNT = "{arch}.expert_group_used_count"
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EXPERT_WEIGHTS_SCALE = "{arch}.expert_weights_scale"
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EXPERT_WEIGHTS_NORM = "{arch}.expert_weights_norm"
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EXPERT_GATING_FUNC = "{arch}.expert_gating_func"
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@@ -400,6 +402,7 @@ class MODEL_ARCH(IntEnum):
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WAVTOKENIZER_DEC = auto()
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PLM = auto()
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BAILINGMOE = auto()
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BAILINGMOE2 = auto()
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DOTS1 = auto()
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ARCEE = auto()
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ERNIE4_5 = auto()
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@@ -744,6 +747,7 @@ MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
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MODEL_ARCH.WAVTOKENIZER_DEC: "wavtokenizer-dec",
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MODEL_ARCH.PLM: "plm",
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MODEL_ARCH.BAILINGMOE: "bailingmoe",
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MODEL_ARCH.BAILINGMOE2: "bailingmoe2",
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MODEL_ARCH.DOTS1: "dots1",
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MODEL_ARCH.ARCEE: "arcee",
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MODEL_ARCH.ERNIE4_5: "ernie4_5",
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@@ -2533,6 +2537,35 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
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MODEL_TENSOR.FFN_DOWN_SHEXP,
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MODEL_TENSOR.FFN_UP_SHEXP,
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],
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MODEL_ARCH.BAILINGMOE2: [
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MODEL_TENSOR.TOKEN_EMBD,
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MODEL_TENSOR.OUTPUT_NORM,
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MODEL_TENSOR.OUTPUT,
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MODEL_TENSOR.ATTN_NORM,
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MODEL_TENSOR.ATTN_Q_NORM,
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MODEL_TENSOR.ATTN_K_NORM,
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MODEL_TENSOR.ATTN_QKV,
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MODEL_TENSOR.ATTN_OUT,
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MODEL_TENSOR.FFN_GATE_INP,
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MODEL_TENSOR.FFN_EXP_PROBS_B,
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MODEL_TENSOR.FFN_NORM,
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MODEL_TENSOR.FFN_GATE,
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MODEL_TENSOR.FFN_DOWN,
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MODEL_TENSOR.FFN_UP,
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MODEL_TENSOR.FFN_GATE_EXP,
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MODEL_TENSOR.FFN_DOWN_EXP,
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MODEL_TENSOR.FFN_UP_EXP,
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MODEL_TENSOR.FFN_GATE_SHEXP,
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MODEL_TENSOR.FFN_DOWN_SHEXP,
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MODEL_TENSOR.FFN_UP_SHEXP,
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MODEL_TENSOR.NEXTN_EH_PROJ,
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MODEL_TENSOR.NEXTN_EMBED_TOKENS,
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MODEL_TENSOR.NEXTN_ENORM,
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MODEL_TENSOR.NEXTN_HNORM,
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MODEL_TENSOR.NEXTN_SHARED_HEAD_HEAD,
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MODEL_TENSOR.NEXTN_SHARED_HEAD_NORM,
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MODEL_TENSOR.LAYER_OUT_NORM,
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],
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MODEL_ARCH.DOTS1: [
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MODEL_TENSOR.TOKEN_EMBD,
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MODEL_TENSOR.OUTPUT_NORM,
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