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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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16
vllm/model_executor/models/persimmon.py
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@@ -75,7 +75,8 @@ class PersimmonAttention(nn.Module):
def __init__(self,
config: PersimmonConfig,
cache_config: Optional[CacheConfig] = None,
quant_config: Optional[QuantizationConfig] = None):
quant_config: Optional[QuantizationConfig] = None,
prefix: str = ""):
super().__init__()
self.config = config
tensor_parallel_world_size = get_tensor_model_parallel_world_size()
@@ -122,7 +123,8 @@ class PersimmonAttention(nn.Module):
self.head_dim,
scale=self.scaling,
cache_config=cache_config,
quant_config=quant_config)
quant_config=quant_config,
prefix=f"{prefix}.attn")
def _split_heads(self, x: torch.Tensor) -> torch.Tensor:
# [seq_length, hidden_size] -> [seq_length, num_heads, head_dim]
@@ -167,12 +169,14 @@ class PersimmonDecoderLayer(nn.Module):
def __init__(self,
config: PersimmonConfig,
cache_config: Optional[CacheConfig] = None,
quant_config: Optional[QuantizationConfig] = None):
quant_config: Optional[QuantizationConfig] = None,
prefix: str = ""):
super().__init__()
self.hidden_size = config.hidden_size
self.self_attn = PersimmonAttention(config=config,
cache_config=cache_config,
quant_config=quant_config)
quant_config=quant_config,
prefix=f"{prefix}.self_attn")
self.mlp = PersimmonMLP(config, quant_config=quant_config)
self.input_layernorm = nn.LayerNorm(config.hidden_size,
eps=config.layer_norm_eps)
@@ -226,8 +230,8 @@ class PersimmonModel(nn.Module):
config.hidden_size)
self.start_layer, self.end_layer, self.layers = make_layers(
config.num_hidden_layers,
lambda prefix: PersimmonDecoderLayer(config, cache_config,
quant_config),
lambda prefix: PersimmonDecoderLayer(
config, cache_config, quant_config, prefix=prefix),
prefix=f"{prefix}.layers")
self.final_layernorm = nn.LayerNorm(config.hidden_size,
eps=config.layer_norm_eps)