ZIBEE/bi_150-vllm
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Upgrade to vllm 0.17.0 corex v4.1 overlay

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LZiBee
2026-04-29 19:38:22 +08:00
parent 8fac6062e4
commit 938d0854a5
430 changed files with 35969 additions and 14511 deletions
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11
vllm/model_executor/models/minimax_m2.py
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@@ -88,7 +88,7 @@ class MiniMaxM2MoE(nn.Module):
self.use_routing_bias = getattr(config, "use_routing_bias", False)
if self.use_routing_bias:
self.e_score_correction_bias = nn.Parameter(
torch.empty(config.num_local_experts, dtype=torch.float32)
torch.empty(config.num_local_experts, dtype=torch.get_default_dtype())
)
self.e_score_correction_bias.weight_loader = (
MiniMaxM2MoE.ebias_weight_loader
@@ -107,13 +107,14 @@ class MiniMaxM2MoE(nn.Module):
renormalize=True,
quant_config=quant_config,
prefix=f"{prefix}.experts",
router_logits_dtype=torch.float32,
)
self.gate = ReplicatedLinear(
config.hidden_size,
config.num_local_experts,
bias=False,
# params_dtype=torch.float32,
params_dtype=torch.float32,
quant_config=None,
prefix=f"{prefix}.gate",
)
@@ -121,7 +122,6 @@ class MiniMaxM2MoE(nn.Module):
@staticmethod
def ebias_weight_loader(param: nn.Parameter, loaded_weight: torch.Tensor) -> None:
assert param.size() == loaded_weight.size()
# param.data.copy_(loaded_weight.to(torch.float32))
param.data.copy_(loaded_weight)
def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
@@ -129,10 +129,9 @@ class MiniMaxM2MoE(nn.Module):
hidden_states = hidden_states.view(-1, hidden_dim)
# router_logits: (num_tokens, n_experts)
# router_logits, _ = self.gate(hidden_states.to(torch.float32))
router_logits, _ = self.gate(hidden_states)
router_logits, _ = self.gate(hidden_states.to(torch.float32))
final_hidden_states = self.experts(
hidden_states=hidden_states, router_logits=router_logits
hidden_states=hidden_states, router_logits=router_logits.to(hidden_states.dtype)
)
final_hidden_states = final_hidden_states
if self.tp_size > 1: