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[Core] Allow disabling TP sharding for parallel Linear layer (#23024)

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Signed-off-by: Isotr0py <mozf@mail2.sysu.edu.cn>
Signed-off-by: Isotr0py <2037008807@qq.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
This commit is contained in:
Isotr0py
2025-09-06 13:53:58 +08:00
committed by GitHub
parent 6432739ef1
commit 53b19ccdd5
7 changed files with 203 additions and 280 deletions
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71
vllm/model_executor/models/step3_vl.py
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@@ -21,7 +21,6 @@ from vllm.distributed import get_tensor_model_parallel_world_size
from vllm.model_executor.layers.activation import get_act_fn
from vllm.model_executor.layers.linear import (ColumnParallelLinear,
QKVParallelLinear,
ReplicatedLinear,
RowParallelLinear)
from vllm.model_executor.layers.quantization import QuantizationConfig
from vllm.model_executor.layers.sampler import SamplerOutput, get_sampler
@@ -667,35 +666,21 @@ class Step3VisionAttention(nn.Module):
self.q_size = self.num_heads * self.head_dim
if use_data_parallel:
self.qkv_proj = ReplicatedLinear(
self.embed_dim,
3 * self.q_size,
bias=True,
quant_config=quant_config,
prefix=prefix,
)
self.out_proj = ReplicatedLinear(
self.total_num_heads * self.head_dim,
self.embed_dim,
bias=True,
quant_config=quant_config,
prefix=prefix,
)
else:
self.qkv_proj = QKVParallelLinear(
self.embed_dim,
self.head_dim,
self.total_num_heads,
bias=True,
quant_config=quant_config,
prefix=prefix,
)
self.out_proj = RowParallelLinear(self.embed_dim,
self.embed_dim,
bias=True,
quant_config=quant_config,
prefix=prefix)
self.qkv_proj = QKVParallelLinear(
self.embed_dim,
self.head_dim,
self.total_num_heads,
bias=True,
quant_config=quant_config,
prefix=f"{prefix}.qkv_proj",
disable_tp=use_data_parallel,
)
self.out_proj = RowParallelLinear(self.embed_dim,
self.embed_dim,
bias=True,
quant_config=quant_config,
prefix=f"{prefix}.out_proj",
disable_tp=use_data_parallel)
def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
return tensor.view(bsz, seq_len, self.num_heads,
@@ -740,20 +725,18 @@ class Step3VisionMLP(nn.Module):
super().__init__()
self.config = config
self.activation_fn = get_act_fn(config.hidden_act)
cls_fc1 = (ReplicatedLinear
if use_data_parallel else ColumnParallelLinear)
self.fc1 = cls_fc1(config.hidden_size,
config.intermediate_size,
bias=True,
quant_config=quant_config,
prefix=prefix)
cls_fc2 = (ReplicatedLinear
if use_data_parallel else RowParallelLinear)
self.fc2 = cls_fc2(config.intermediate_size,
config.hidden_size,
bias=True,
quant_config=quant_config,
prefix=prefix)
self.fc1 = ColumnParallelLinear(config.hidden_size,
config.intermediate_size,
bias=True,
quant_config=quant_config,
prefix=f"{prefix}.fc1",
disable_tp=use_data_parallel)
self.fc2 = RowParallelLinear(config.intermediate_size,
config.hidden_size,
bias=True,
quant_config=quant_config,
prefix=f"{prefix}.fc2",
disable_tp=use_data_parallel)
def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
hidden_states, _ = self.fc1(hidden_states)