kanshan/TensorRT-LLMs
1
0
Fork 0
mirror of https://github.com/NVIDIA/TensorRT-LLM.git synced 2026-01-13 22:18:36 +08:00
Code Issues Actions 1 Packages Projects Releases Wiki Activity

[https://nvbugs/5752687][fix] Choose register model config over root config for VLM (#10553)

Browse Source 
Signed-off-by: Faraz Khoubsirat <58580514+farazkh80@users.noreply.github.com>
This commit is contained in:
Faraz 2026-01-09 12:10:52 -05:00 committed by GitHub
parent d80f01d205
commit fdbdbba540
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 18 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

19
tensorrt_llm/inputs/registry.py
View File

@ -356,6 +356,20 @@ class BaseMultimodalDummyInputsBuilder(ABC):
def get_dummy_prompt(self, input_seq_len: int):
# TODO(yechank): We use the max resolution as starting point and keep reducing the resolution until the prompt length is less than the input sequence length.
# Need to find better way to calculate the dummy prompt length as this iteration may not be efficient.
# Use the registered model_type from the decorator if available,
# otherwise fall back to HuggingFace config's model_type.
# This ensures consistency between placeholder registration and lookup.
registered_model_type = getattr(self.__class__,
'_registered_model_type', None)
config_model_type = self.config.model_type
model_type = registered_model_type or config_model_type
logger.debug(
f"[get_dummy_prompt] registered_model_type={registered_model_type}, "
f"config.model_type={config_model_type}, using model_type={model_type}"
)
while self.image_max_dim >= self.image_min_dim:
image = self.get_dummy_image(max_width=self.image_max_dim,
max_height=self.image_max_dim)
@ -363,7 +377,7 @@ class BaseMultimodalDummyInputsBuilder(ABC):
test_mm_prompt = tensorrt_llm.inputs.utils.default_multimodal_input_loader(
tokenizer=self.tokenizer,
model_dir=self.model_path,
model_type=self.config.model_type,
model_type=model_type,
modality="image",
prompts=[""],
media=[[image]],
@ -565,6 +579,9 @@ def register_input_processor(
MULTIMODAL_PLACEHOLDER_REGISTRY.set_placeholder_metadata(
model_type, placeholder_metadata)
# Store model_type on processor class for use in get_dummy_prompt
processor_cls._registered_model_type = model_type
return model_cls
return wrapper