61 transformer blocks › 60 MoE blocks › Mixture of experts › Shared expert
Activated gate
×tensorself.act_fn(self.gate_proj(x))
The SiLU-activated gate features.
- shape
- [B batch, T positions, 2048 shared d_ff]
Sources
Contextual evidence from SiLU
The dense feed-forward network is a SwiGLU MLP: down(silu(gate x) ⊙ up x).
mlp · moonshotai/Kimi-K2-Instruct / modeling_deepseek.py
Pinned revision fd1984e2b7a3 ↗ · lines 374–390
Read code excerpt
class DeepseekV3MLP(nn.Module):
def __init__(self, config, hidden_size=None, intermediate_size=None):
super().__init__()
self.config = config
self.hidden_size = config.hidden_size if hidden_size is None else hidden_size
self.intermediate_size = (
config.intermediate_size if intermediate_size is None else intermediate_size
)
self.gate_proj = nn.Linear(self.hidden_size, self.intermediate_size, bias=False)
self.up_proj = nn.Linear(self.hidden_size, self.intermediate_size, bias=False)
self.down_proj = nn.Linear(self.intermediate_size, self.hidden_size, bias=False)
self.act_fn = ACT2FN[config.hidden_act]
def forward(self, x):
down_proj = self.down_proj(self.act_fn(self.gate_proj(x)) * self.up_proj(x))
return down_proj