A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 5, 09:45 UTC
[Multimodal] Fix nested_tensors_equal: add length check for lists and tuple support (#38388)
Signed-off-by: khairulkabir1661 <khairulkabir1661@users.noreply.github.com> Co-authored-by: khairulkabir1661 <khairulkabir1661@users.noreply.github.com>
Khairul Kabir committed
Apr 8, 2026 at 21:40 UTC
490f17d0c7e21c3a4cd4c8e13b0e40840fc754c1
1 file changed
+21
-4
vllm/multimodal/inputs.py
+21
-4
@@ -238,12 +238,29 @@ def nested_tensors_equal(a: NestedTensors, b: NestedTensors) -> bool:
238
return isinstance(a, torch.Tensor) and torch.equal(b, a)
239
240
if isinstance(a, list):
241
- return isinstance(b, list) and all(
242
- nested_tensors_equal(a_, b_) for a_, b_ in zip(a, b)
241
+ return (
242
+ isinstance(b, list)
243
+ and len(a) == len(b)
244
+ and all(nested_tensors_equal(a_, b_) for a_, b_ in zip(a, b))
245
)
246
if isinstance(b, list):
245
- return isinstance(a, list) and all(
246
- nested_tensors_equal(b_, a_) for b_, a_ in zip(b, a)
247
+ return (
248
+ isinstance(a, list)
249
+ and len(b) == len(a)
250
+ and all(nested_tensors_equal(b_, a_) for b_, a_ in zip(b, a))
251
+ )
252
+
253
+ if isinstance(a, tuple):
254
+ return (
255
+ isinstance(b, tuple)
256
+ and len(a) == len(b)
257
+ and all(nested_tensors_equal(a_, b_) for a_, b_ in zip(a, b))
258
+ )
259
+ if isinstance(b, tuple):
260
+ return (
261
+ isinstance(a, tuple)
262
+ and len(b) == len(a)
263
+ and all(nested_tensors_equal(b_, a_) for b_, a_ in zip(b, a))
264
)
265
266
# Both a and b are scalars