[MM][Bugfix] Replace PatchEmbed's conv3d to linear layer (#27418)

Signed-off-by: Isotr0py <mozf@mail2.sysu.edu.cn>
Co-authored-by: Roger Wang <hey@rogerw.io>
This commit is contained in:
Isotr0py
2025-10-24 15:32:47 +08:00
committed by GitHub
parent 88d3141ec6
commit 42efe609ba
6 changed files with 97 additions and 42 deletions

View File

@@ -25,6 +25,7 @@
# limitations under the License.
"""Inference-only Qwen2-VL model compatible with HuggingFace weights."""
import math
from collections.abc import Callable, Iterable, Mapping, Sequence
from functools import partial
from typing import Annotated, Any, Literal, TypeAlias
@@ -53,7 +54,11 @@ from vllm.distributed import parallel_state, tensor_model_parallel_all_gather
from vllm.distributed import utils as dist_utils
from vllm.logger import init_logger
from vllm.model_executor.layers.activation import QuickGELU
from vllm.model_executor.layers.linear import ColumnParallelLinear, RowParallelLinear
from vllm.model_executor.layers.linear import (
ColumnParallelLinear,
ReplicatedLinear,
RowParallelLinear,
)
from vllm.model_executor.layers.quantization import QuantizationConfig
from vllm.model_executor.layers.rotary_embedding.common import (
dispatch_rotary_emb_function,
@@ -100,7 +105,11 @@ from .utils import (
init_vllm_registered_model,
maybe_prefix,
)
from .vision import get_vit_attn_backend, run_dp_sharded_mrope_vision_model
from .vision import (
conv3d_to_linear_weight,
get_vit_attn_backend,
run_dp_sharded_mrope_vision_model,
)
logger = init_logger(__name__)
@@ -561,18 +570,15 @@ class Qwen2VisionPatchEmbed(nn.Module):
self.embed_dim = embed_dim
kernel_size = (temporal_patch_size, patch_size, patch_size)
self.proj = nn.Conv3d(
in_channels,
self.proj = ReplicatedLinear(
in_channels * math.prod(kernel_size),
embed_dim,
kernel_size=kernel_size,
stride=kernel_size,
bias=False,
return_bias=False,
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
L, C = x.shape
x = x.view(L, -1, self.temporal_patch_size, self.patch_size, self.patch_size)
x = self.proj(x).view(L, self.embed_dim)
x = self.proj(x)
return x
@@ -835,6 +841,9 @@ class Qwen2VisionTransformer(nn.Module):
loaded_params: set[str] = set()
for name, loaded_weight in weights:
if name.endswith("patch_embed.proj.weight"):
loaded_weight = conv3d_to_linear_weight(loaded_weight)
for param_name, weight_name, shard_id in stacked_params_mapping:
if weight_name not in name:
continue