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Commit3f14a1c

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Use raw image as the input to find num mm tokens
Signed-off-by: Chang Liu (Enterprise Products) <9713593+chang-l@users.noreply.github.com>
1 parent89889fb commit3f14a1c

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3 files changed

+17
-27
lines changed

3 files changed

+17
-27
lines changed

‎tensorrt_llm/inputs/multimodal.py‎

Lines changed: 2 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -505,19 +505,14 @@ def find_mm_token_lengths(mm_data: Dict[str, Any],
505505
ifisinstance(item,torch.Tensor):
506506
item=ToPILImage()(item)
507507
num_tokens=input_processor.get_num_tokens_per_image(
508-
image_width=item.width,
509-
image_height=item.height,
510-
)
508+
image=item, )
511509
modality_token_lengths.append(num_tokens)
512510
elifmodality=="video":
513511
assertisinstance(item,list),"Video must be a list of frames"
514512
ifisinstance(item[0],torch.Tensor):
515513
item= [ToPILImage()(frame)forframeinitem]
516514
num_tokens=input_processor.get_num_tokens_per_video(
517-
video_width=item[0].width,
518-
video_height=item[0].height,
519-
num_frames=len(item),
520-
)
515+
video=item, )
521516
modality_token_lengths.append(num_tokens)
522517
else:
523518
# TODO: add audio support if needed

‎tensorrt_llm/inputs/registry.py‎

Lines changed: 10 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -3,6 +3,7 @@
33
fromtypingimport (Any,Callable,Dict,List,Optional,Protocol,Tuple,Type,
44
TypeVar)
55

6+
fromPILimportImage
67
fromtorchimportTensor,nn
78

89
from .._utilsimportnvtx_range_debug
@@ -114,8 +115,7 @@ def get_num_multimodal_tokens(self):
114115
defget_num_tokens_per_image(
115116
self,
116117
*,
117-
image_width:int,
118-
image_height:int,
118+
image:Image.Image,
119119
**kwargs,
120120
):
121121
"""
@@ -126,16 +126,16 @@ def get_num_tokens_per_image(
126126
127127
Subclasses can override this method to provide custom logic to calculate the number of tokens.
128128
"""
129+
image_height=image.height
130+
image_width=image.width
129131
image_size= (image_height,image_width)
130132
returnself.get_num_multimodal_tokens([image_size],
131133
**kwargs)["num_image_tokens"][0]
132134

133135
defget_num_tokens_per_video(
134136
self,
135137
*,
136-
video_width:int,
137-
video_height:int,
138-
num_frames:int,
138+
video:List[Image.Image],
139139
**kwargs,
140140
):
141141
"""
@@ -146,15 +146,18 @@ def get_num_tokens_per_video(
146146
147147
Subclasses can override this method to provide custom logic to calculate the number of tokens.
148148
"""
149+
video_width=video[0].width
150+
video_height=video[0].height
151+
num_frames=len(video)
149152
video_size= (num_frames,video_height,video_width)
150153
try:
151154
num_video_tokens=self.get_num_multimodal_tokens(
152155
video_sizes=[video_size],**kwargs)["num_video_tokens"][0]
153156
returnnum_video_tokens
154157
exceptException:
155158
# Fallback: treat video as sequence of frames
156-
num_tokens_per_frame=self.get_num_tokens_per_image(
157-
image_width=video_width,image_height=video_height,**kwargs)
159+
num_tokens_per_frame=self.get_num_tokens_per_image(image=video[0],
160+
**kwargs)
158161
temporal_patch_size=self.temporal_patch_sizeifhasattr(
159162
self,'temporal_patch_size')else1
160163
returnnum_tokens_per_frame*num_frames//temporal_patch_size

‎tests/unittest/_torch/multimodal/test_find_num_image_tokens.py‎

Lines changed: 5 additions & 13 deletions
Original file line numberDiff line numberDiff line change
@@ -136,13 +136,10 @@ def test_get_num_tokens_per_image(model_key, multimodal_model_configs):
136136
# Get predicted number of tokens using get_num_tokens_per_image
137137
ifmodel_type=='llava_next':
138138
predicted_num_tokens=input_processor.get_num_tokens_per_image(
139-
image_width=image_width,image_height=image_height)
139+
image=test_image)
140140
elifmodel_type=='qwen2_5_vl':
141141
predicted_num_tokens=input_processor.get_num_tokens_per_image(
142-
image_width=image_width,
143-
image_height=image_height,
144-
num_frames=1,
145-
do_resize=True)
142+
image=test_image)
146143
else:
147144
raiseValueError(f"Unsupported model type:{model_type}")
148145

@@ -235,7 +232,6 @@ def test_get_num_tokens_per_video(model_key, multimodal_model_configs):
235232
test_video=load_video(test_video_url,num_frames=8,format="pil")
236233
# load_video returns a list of frames, we only have one video
237234
video_width,video_height=test_video[0].size
238-
num_frames=len(test_video)
239235

240236
# Get actual embedding tensor for this image
241237
actual_embedding=SharedTensorContainer.from_dict(
@@ -245,17 +241,13 @@ def test_get_num_tokens_per_video(model_key, multimodal_model_configs):
245241
# The first dimension should be the number of image tokens
246242
actual_num_tokens=actual_embedding.shape[0]
247243

248-
# Get predicted number of tokens usingget_num_tokens_per_image
244+
# Get predicted number of tokens usingget_num_tokens_per_video
249245
ifmodel_type=='llava_next':
250246
predicted_num_tokens=input_processor.get_num_tokens_per_video(
251-
video_width=video_width,
252-
video_height=video_height,
253-
num_frames=num_frames)
247+
video=test_video)
254248
elifmodel_type=='qwen2_5_vl':
255249
predicted_num_tokens=input_processor.get_num_tokens_per_video(
256-
video_width=video_width,
257-
video_height=video_height,
258-
num_frames=num_frames)
250+
video=test_video)
259251

260252
# The key assertion: predicted should match actual
261253
assertpredicted_num_tokens==actual_num_tokens, \

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