[Bug]: Mismatch multi-modal placeholder of LLava-1.6-Mistral-7B

[jianghuyihei]

Your current environment

The output of `python collect_env.py`

Collecting environment information...
PyTorch version: 2.5.1+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.5 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.10.0 (default, Mar  3 2022, 09:58:08) [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.10.112-005.ali5000.alios7.x86_64-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 11.8.89
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA A100-SXM4-80GB
Nvidia driver version: 535.129.03
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.0
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                    x86_64
CPU op-mode(s):                  32-bit, 64-bit
Address sizes:                   46 bits physical, 57 bits virtual
Byte Order:                      Little Endian
CPU(s):                          128
On-line CPU(s) list:             0-127
Vendor ID:                       GenuineIntel
Model name:                      Intel(R) Xeon(R) Platinum 8369B CPU @ 2.90GHz
CPU family:                      6
Model:                           106
Thread(s) per core:              2
Core(s) per socket:              32
Socket(s):                       2
Stepping:                        6
CPU max MHz:                     3500.0000
CPU min MHz:                     800.0000
BogoMIPS:                        5800.00
Flags:                           fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq rdpid fsrm md_clear pconfig flush_l1d arch_capabilities
Virtualization:                  VT-x
L1d cache:                       3 MiB (64 instances)
L1i cache:                       2 MiB (64 instances)
L2 cache:                        80 MiB (64 instances)
L3 cache:                        96 MiB (2 instances)
NUMA node(s):                    2
NUMA node0 CPU(s):               0-31,64-95
NUMA node1 CPU(s):               32-63,96-127
Vulnerability Itlb multihit:     Not affected
Vulnerability L1tf:              Not affected
Vulnerability Mds:               Not affected
Vulnerability Meltdown:          Not affected
Vulnerability Spec store bypass: Vulnerable
Vulnerability Spectre v1:        Vulnerable: __user pointer sanitization and usercopy barriers only; no swapgs barriers
Vulnerability Spectre v2:        Vulnerable, IBPB: disabled, STIBP: disabled
Vulnerability Srbds:             Not affected
Vulnerability Tsx async abort:   Not affected

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-ml-py==12.560.30
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] pytorch_revgrad==0.2.0
[pip3] pyzmq==26.2.0
[pip3] torch==2.5.1
[pip3] torchao==0.7.0
[pip3] torchvision==0.20.1
[pip3] transformers==4.47.1
[pip3] triton==3.1.0
[conda] numpy                     1.26.4                   pypi_0    pypi
[conda] nvidia-cublas-cu12        12.4.5.8                 pypi_0    pypi
[conda] nvidia-cuda-cupti-cu12    12.4.127                 pypi_0    pypi
[conda] nvidia-cuda-nvrtc-cu12    12.4.127                 pypi_0    pypi
[conda] nvidia-cuda-runtime-cu12  12.4.127                 pypi_0    pypi
[conda] nvidia-cudnn-cu12         9.1.0.70                 pypi_0    pypi
[conda] nvidia-cufft-cu12         11.2.1.3                 pypi_0    pypi
[conda] nvidia-curand-cu12        10.3.5.147               pypi_0    pypi
[conda] nvidia-cusolver-cu12      11.6.1.9                 pypi_0    pypi
[conda] nvidia-cusparse-cu12      12.3.1.170               pypi_0    pypi
[conda] nvidia-ml-py              12.560.30                pypi_0    pypi
[conda] nvidia-nccl-cu12          2.21.5                   pypi_0    pypi
[conda] nvidia-nvjitlink-cu12     12.4.127                 pypi_0    pypi
[conda] nvidia-nvtx-cu12          12.4.127                 pypi_0    pypi
[conda] pytorch-revgrad           0.2.0                    pypi_0    pypi
[conda] pyzmq                     26.2.0                   pypi_0    pypi
[conda] torch                     2.5.1                    pypi_0    pypi
[conda] torchao                   0.7.0                    pypi_0    pypi
[conda] torchvision               0.20.1                   pypi_0    pypi
[conda] transformers              4.47.1                   pypi_0    pypi
[conda] triton                    3.1.0                    pypi_0    pypi
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.6.6.post1
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0    NIC0    NIC1    NIC2    NIC3    NIC4    NIC5    NIC6    NIC7    NIC8    NIC9    NIC10   NIC11   NIC12   NIC13   NIC14NIC15    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      PXB     PXB     PXB     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS  PXB      SYS     0-31,64-95      0               N/A
NIC0    PXB      X      PIX     PIX     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS  PIX      SYS
NIC1    PXB     PIX      X      PIX     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS  PIX      SYS
NIC2    PXB     PIX     PIX      X      SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS  PIX      SYS
NIC3    SYS     SYS     SYS     SYS      X      PIX     PIX     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS  SYS      PIX
NIC4    SYS     SYS     SYS     SYS     PIX      X      PIX     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS  SYS      PIX
NIC5    SYS     SYS     SYS     SYS     PIX     PIX      X      SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS  SYS      PIX
NIC6    SYS     SYS     SYS     SYS     SYS     SYS     SYS      X      PIX     PIX     SYS     SYS     SYS     PIX     SYS  SYS      SYS
NIC7    SYS     SYS     SYS     SYS     SYS     SYS     SYS     PIX      X      PIX     SYS     SYS     SYS     PIX     SYS  SYS      SYS
NIC8    SYS     SYS     SYS     SYS     SYS     SYS     SYS     PIX     PIX      X      SYS     SYS     SYS     PIX     SYS  SYS      SYS
NIC9    SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS      X      PIX     PIX     SYS     PIX  SYS      SYS
NIC10   SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     PIX      X      PIX     SYS     PIX  SYS      SYS
NIC11   SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     PIX     PIX      X      SYS     PIX  SYS      SYS
NIC12   SYS     SYS     SYS     SYS     SYS     SYS     SYS     PIX     PIX     PIX     SYS     SYS     SYS      X      SYS  SYS      SYS
NIC13   SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     PIX     PIX     PIX     SYS      X   SYS      SYS
NIC14   PXB     PIX     PIX     PIX     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS   X       SYS
NIC15   SYS     SYS     SYS     SYS     PIX     PIX     PIX     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS  SYS       X 

Legend:

  X    = Self
  SYS  = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
  NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
  PHB  = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
  PXB  = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
  PIX  = Connection traversing at most a single PCIe bridge
  NV#  = Connection traversing a bonded set of # NVLinks

NIC Legend:

  NIC0: mlx5_0
  NIC1: mlx5_1
  NIC2: mlx5_2
  NIC3: mlx5_3
  NIC4: mlx5_4
  NIC5: mlx5_5
  NIC6: mlx5_6
  NIC7: mlx5_7
  NIC8: mlx5_8
  NIC9: mlx5_9
  NIC10: mlx5_10
  NIC11: mlx5_11
  NIC12: mlx5_bond_0
  NIC13: mlx5_bond_1
  NIC14: mlx5_bond_2
  NIC15: mlx5_bond_3

NVIDIA_VISIBLE_DEVICES=3
NVIDIA_REQUIRE_CUDA=
NCCL_MIN_NCHANNELS=2
NCCL_VERSION=2
NVIDIA_DRIVER_CAPABILITIES=all
NCCL_DEBUG=INFO
NVIDIA_PRODUCT_NAME=CUDA
NCCL_NSOCKS_PERTHREAD=1
CUDA_VERSION=11.8.0
NCCL_MAX_NCHANNELS=2
NVIDIA_DISABLE_REQUIRE=1
NCCL_ASYNC_ERROR_HANDLING=1
NCCL_SOCKET_NTHREADS=2
LD_LIBRARY_PATH=/home/pai/envs/medical/lib/python3.10/site-packages/cv2/../../lib64:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/lib/x86_64-linux-gnu:/lib/x86_64-linux-gnu:/home/pai/lib:/home/pai/jre/lib/amd64/server:/home/pai/jre/lib/amd64/server
NCCL_LAUNCH_MODE=PARALLEL
CUDA_MODULE_LOADING=LAZY

Model Input Dumps

No response

🐛 Describe the bug

When I use LLava-1.6-Mistral-7B to infer multimodal data, using the following code:

outputs = model.generate_outputs(current_messages)

Then the error:
ValueError: Error in model execution (input dumped to /tmp/err_execute_model_input_20250103-120322.pkl): Attempted to assign 1272 = 1272 multimodal tokens to 1224 placeholders

I found the relevant issues like #8421 and #7996, but they didn't solve my problem.
The img size is (198, 176)

Before submitting a new issue...

• Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the documentation page, which can answer lots of frequently asked questions.

[DarkLight1337]

Ok I found the cause of this problem - it's due to the image resizing being based on float32 instead of float64, resulting in a mismatch between the processor's output (based on float32) and our calculations (based on float64).

[jianghuyihei]

Ok I found the cause of this problem - it's due to the image resizing being based on float32 instead of float64, resulting in a mismatch between the processor's output (based on float32) and our calculations (based on float64).

I am very sorry. I encountered a new problem after modifying the code. When the img size is (161, 184), an error message Attempted to assign 1128 = 1128 multimodal tokens to 1080 placeholders is reported. Should I open a new issue?

[youkaichao]

Ok I found the cause of this problem - it's due to the image resizing being based on float32 instead of float64, resulting in a mismatch between the processor's output (based on float32) and our calculations (based on float64).

I am very sorry. I encountered a new problem after modifying the code. When the img size is (161, 184), an error message Attempted to assign 1128 = 1128 multimodal tokens to 1080 placeholders is reported. Should I open a new issue?

cc @DarkLight1337

[DarkLight1337]

I already fixed it. See #11735 (comment)