About the evaluation time about video-chatgpt HOT 2 CLOSED

Hi @wyzjack,

Thanks for your interest in our work and for reaching out with your question.

Indeed, the ActivityNet-QA dataset is fairly large, containing around 8000 questions, which can make the inference process quite time-consuming, especially when run on a single GPU.

In our work, to expedite the inference, we divided the workload across multiple GPUs. We accomplished this by a simple hack and splitting the contents of the JSON file into smaller chunks, each of which was processed on a separate GPU. After the inference process, we combined the results from each GPU. In our experience, running the task on 4 or 8 GPUs can substantially decrease the inference time.

I hope this information is helpful. Let me know if you have any other questions!

from video-chatgpt.

Got it, thanks!

from video-chatgpt.