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[torch.compile] support all attention backends (#10558)

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Signed-off-by: youkaichao <youkaichao@gmail.com>
This commit is contained in:
youkaichao
2024-11-22 14:04:42 -08:00
committed by GitHub
parent db100c5cde
commit eebad39f26
77 changed files with 876 additions and 648 deletions
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15
vllm/model_executor/models/gemma2.py
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@@ -95,7 +95,8 @@ class Gemma2Attention(nn.Module):
rope_theta: float,
cache_config: Optional[CacheConfig] = None,
quant_config: Optional[QuantizationConfig] = None,
attn_logits_soft_cap: Optional[float] = None) -> None:
attn_logits_soft_cap: Optional[float] = None,
prefix: str = "") -> None:
super().__init__()
self.layer_idx = layer_idx
self.config = config
@@ -154,7 +155,8 @@ class Gemma2Attention(nn.Module):
num_kv_heads=self.num_kv_heads,
cache_config=cache_config,
quant_config=quant_config,
logits_soft_cap=attn_logits_soft_cap)
logits_soft_cap=attn_logits_soft_cap,
prefix=f"{prefix}.attn")
def forward(
self,
@@ -179,6 +181,7 @@ class Gemma2DecoderLayer(nn.Module):
config: Gemma2Config,
cache_config: Optional[CacheConfig] = None,
quant_config: Optional[QuantizationConfig] = None,
prefix: str = "",
) -> None:
super().__init__()
self.hidden_size = config.hidden_size
@@ -194,6 +197,7 @@ class Gemma2DecoderLayer(nn.Module):
cache_config=cache_config,
quant_config=quant_config,
attn_logits_soft_cap=config.attn_logit_softcapping,
prefix=f"{prefix}.self_attn",
)
self.hidden_size = config.hidden_size
self.mlp = Gemma2MLP(
@@ -257,8 +261,11 @@ class Gemma2Model(nn.Module):
)
self.start_layer, self.end_layer, self.layers = make_layers(
config.num_hidden_layers,
lambda prefix: Gemma2DecoderLayer(int(prefix.split(".")[
-1]), config, cache_config, quant_config),
lambda prefix: Gemma2DecoderLayer(int(prefix.split(".")[-1]),
config,
cache_config,
quant_config,
prefix=prefix),
prefix=f"{prefix}.layers")
self.norm = GemmaRMSNorm(config.hidden_size, eps=config.rms_norm_eps)