Inference not working - Keyword tensor should have 2 or 3 dimensions, got 1

[signine]

trafficstars

I get the following error while running llava/eval/run_vila.py on a H100 gpu:

root@7513903dd8b0:/src/VILA# python -W ignore llava/eval/run_vila.py     --model-path Efficient-Large-Model/VILA1.5-3b     --conv-mode vicuna_v1     --query "<video>\n Please describe this video."     --video-file "tjx1PPFsa6A-Scene-049.mp4"
Fetching 17 files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████| 17/17 [00:00<00:00, 203142.93it/s]
Loading checkpoint shards: 100%|██████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:01<00:00,  1.47it/s]
no <image> tag found in input. Automatically append one at the beginning of text.
input:  <image>
<image>
<image>
<image>
<image>
<image>
<video>\n Please describe this video.
[WARNING] the auto inferred conversation mode is llava_v0, while `--conv-mode` is vicuna_v1, using vicuna_v1
torch.Size([6, 3, 384, 384])
Traceback (most recent call last):
  File "/src/VILA/llava/eval/run_vila.py", line 154, in <module>
    eval_model(args)
  File "/src/VILA/llava/eval/run_vila.py", line 116, in eval_model
    output_ids = model.generate(
                 ^^^^^^^^^^^^^^^
  File "/root/.pyenv/versions/3.11.8/lib/python3.11/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/src/VILA/llava/model/language_model/llava_llama.py", line 171, in generate
    outputs = self.llm.generate(
              ^^^^^^^^^^^^^^^^^^
  File "/root/.pyenv/versions/3.11.8/lib/python3.11/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/root/.pyenv/versions/3.11.8/lib/python3.11/site-packages/transformers/generation/utils.py", line 1764, in generate
    return self.sample(
           ^^^^^^^^^^^^
  File "/root/.pyenv/versions/3.11.8/lib/python3.11/site-packages/transformers/generation/utils.py", line 2924, in sample
    if stopping_criteria(input_ids, scores):
       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/.pyenv/versions/3.11.8/lib/python3.11/site-packages/transformers/generation/stopping_criteria.py", line 132, in __call__
    return any(criteria(input_ids, scores) for criteria in self)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/.pyenv/versions/3.11.8/lib/python3.11/site-packages/transformers/generation/stopping_criteria.py", line 132, in <genexpr>
    return any(criteria(input_ids, scores) for criteria in self)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/src/VILA/llava/mm_utils.py", line 298, in __call__
    outputs.append(self.call_for_batch(output_ids[i].unsqueeze(0), scores))
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/src/VILA/llava/mm_utils.py", line 279, in call_for_batch
    raise ValueError(
ValueError: Keyword tensor should have 2 or 3 dimensions, got 1

torch version is 2.0.1+cu118 and flash attention 2.4.2

[Efficient-Large-Language-Model]

Sorry, we merged a PR yesterday and it was problematic. We just rolled back. Could you pull and try again?

[franckmarineai]

also using torch 2.0.1+cu118 and flash attention 2.4.2 and got this error: Setting pad_token_id to eos_token_id:128001 for open-end generation. Traceback (most recent call last): File "/MarineAI/Nvidia-VILA/VILA/llava/eval/run_vila.py", line 154, in eval_model(args) File "/MarineAI/Nvidia-VILA/VILA/llava/eval/run_vila.py", line 116, in eval_model output_ids = model.generate( File "/MarineAI/fbarilla/anaconda3/envs/vila/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context return func(*args, **kwargs) File "/MarineAI/Nvidia-VILA/VILA/llava/model/language_model/llava_llama.py", line 171, in generate outputs = self.llm.generate( File "/MarineAI/fbarilla/anaconda3/envs/vila/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context return func(*args, **kwargs) File "/MarineAI/fbarilla/anaconda3/envs/vila/lib/python3.10/site-packages/transformers/generation/utils.py", line 1764, in generate return self.sample( File "/MarineAI/fbarilla/anaconda3/envs/vila/lib/python3.10/site-packages/transformers/generation/utils.py", line 2924, in sample if stopping_criteria(input_ids, scores): File "/MarineAI/fbarilla/anaconda3/envs/vila/lib/python3.10/site-packages/transformers/generation/stopping_criteria.py", line 132, in call return any(criteria(input_ids, scores) for criteria in self) File "/MarineAI/fbarilla/anaconda3/envs/vila/lib/python3.10/site-packages/transformers/generation/stopping_criteria.py", line 132, in return any(criteria(input_ids, scores) for criteria in self) File "/MarineAI/Nvidia-VILA/VILA/llava/mm_utils.py", line 287, in call outputs.append(self.call_for_batch(output_ids[i].unsqueeze(0), scores)) File "/MarineAI/Nvidia-VILA/VILA/llava/mm_utils.py", line 272, in call_for_batch if (output_ids[0, -keyword_id.shape[0] :] == keyword_id).all(): RuntimeError: The size of tensor a (2) must match the size of tensor b (3) at non-singleton dimension 0

[Efficient-Large-Language-Model]

Are you using llama3? If so, you need to pass --conv-mode=llama_3

[franckmarineai]

sorry, I did not pay attention to this parameter... works now. Thanks a lot

[signine]

@Efficient-Large-Language-Model Pulling the latest code worked for me. Thank you!