[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>

vllm/model_executor/models/qwen2_5_vl.py

@@ -26,6 +26,7 @@
 # limitations under the License.
 """Inference-only Qwen2.5-VL model compatible with HuggingFace weights."""
 
+import math
 from collections.abc import Callable, Iterable, Mapping, Sequence
 from functools import lru_cache, partial
 from typing import Annotated, Any, Literal, TypeAlias
@@ -56,6 +57,7 @@ from vllm.model_executor.layers.linear import (
     ColumnParallelLinear,
     MergedColumnParallelLinear,
     QKVParallelLinear,
+    ReplicatedLinear,
     RowParallelLinear,
 )
 from vllm.model_executor.layers.quantization import QuantizationConfig
@@ -98,7 +100,11 @@ 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__)
 
@@ -532,18 +538,15 @@ class Qwen2_5_VisionPatchEmbed(nn.Module):
         self.hidden_size = hidden_size
 
         kernel_size = (temporal_patch_size, patch_size, patch_size)
-        self.proj = nn.Conv3d(
-            in_channels,
+        self.proj = ReplicatedLinear(
+            in_channels * math.prod(kernel_size),
             hidden_size,
-            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.hidden_size)
+        x = self.proj(x)
         return x
 
 
@@ -950,6 +953,9 @@ class Qwen2_5_VisionTransformer(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