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[BUGFIX] Pixtral cannot be loaded with --limit-mm-per-prompt 0 (#33406) #28

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Merged
varun-sundar-rabindranath merged 1 commit into from
Feb 6, 2026
Merged

[BUGFIX] Pixtral cannot be loaded with --limit-mm-per-prompt 0 (#33406) #28

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14 changes: 9 additions & 5 deletions vllm/model_executor/models/pixtral.py
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Original file line number Diff line number Diff line change
Expand Up @@ -70,7 +70,7 @@
SupportsPP,
)
from .module_mapping import MultiModelKeys
from .utils import init_vllm_registered_model, maybe_prefix
from .utils import StageMissingLayer, init_vllm_registered_model, maybe_prefix
from .vision import (
VisionEncoderInfo,
VisionFeatureSelectStrategy,
Expand All @@ -93,6 +93,10 @@
PATCH_MERGE = "patch_merge"


def _is_layer_none_or_staged(layer: nn.Module) -> bool:
return layer is None or isinstance(layer, StageMissingLayer)


class PixtralImagePixelInputs(TensorSchema):
"""
Dimensions:
Expand Down Expand Up @@ -542,7 +546,7 @@ def llm_weights_generator():
# Single pass over weights
for name, w in weights:
if is_vision_encoder_weights((name, w)):
if self.vision_encoder is None:
if _is_layer_none_or_staged(self.vision_encoder):
continue
# Load vision encoder weights directly
trimmed_name = ".".join(name.split(".")[1:])
Expand All @@ -551,23 +555,23 @@ def llm_weights_generator():
with torch.no_grad():
default_weight_loader(param, w)
elif is_patch_merger((name, w)):
if self.patch_merger is None:
if _is_layer_none_or_staged(self.patch_merger):
continue
# Load vision patch merger weights directly
trimmed_name = ".".join(name.split(".")[1:])
param = patch_merger_dict[trimmed_name]
with torch.no_grad():
default_weight_loader(param, w)
elif is_pre_mm_projector_norm((name, w)):
if self.pre_mm_projector_norm is None:
if _is_layer_none_or_staged(self.pre_mm_projector_norm):
continue
# Load vision pre_mm_projector_norm weights directly
trimmed_name = ".".join(name.split(".")[1:])
param = pre_mm_projector_norm_dict[trimmed_name]
with torch.no_grad():
default_weight_loader(param, w)
elif is_vision_lang_adapter_weights((name, w)):
if self.vision_language_adapter is None:
if _is_layer_none_or_staged(self.vision_language_adapter):
continue
# Load vision-language adapter weights directly
trimmed_name = ".".join(name.split(".")[1:])
Expand Down