How much GPU memory to run inference.py? about anytext HOT 5 CLOSED

So there is no difference between inference.py and demo.py for GPU memory requirement?

How to resize batch_size so it can run on the small amount of GPU memory, the tradeoff is a little bit longer to process? (I cannot find the batch_size configuration in the anytext_sd15.yaml)

Hi,
in inference.py, you can reduce image_count in params:

params = {
    "show_debug": True,
    "image_count": 2,    # <---- batch size
    "ddim_steps": 20,
}

in demo.py, the Image Count is in Parameters.

BTW, I am trying FP16 inference and it seems to have little difference in performance. It is possible that the GPU memory requirement can be reduced to below 10GB. I will push the updated code later.

from anytext.

Thank you @tyxsspa , I fetch the FP16 commit, and now I success to run demo.py on my 8GB GPU. 🥰🙏

from anytext.

24GB vram was suggested

Edit:
Just finish a run on inference.py which peak at 20.6GB VRAM

from anytext.

So there is no difference between inference.py and demo.py for GPU memory requirement?

How to resize batch_size so it can run on the small amount of GPU memory, the tradeoff is a little bit longer to process?
(I cannot find the batch_size configuration in the anytext_sd15.yaml)

from anytext.

So there is no difference between inference.py and demo.py for GPU memory requirement?
How to resize batch_size so it can run on the small amount of GPU memory, the tradeoff is a little bit longer to process? (I cannot find the batch_size configuration in the anytext_sd15.yaml)

Hi, in inference.py, you can reduce image_count in params:

params = {
    "show_debug": True,
    "image_count": 2,    # <---- batch size
    "ddim_steps": 20,
}

in demo.py, the Image Count is in Parameters.

BTW, I am trying FP16 inference and it seems to have little difference in performance. It is possible that the GPU memory requirement can be reduced to below 10GB. I will push the updated code later.

Cool I cannot wait to see the update 😉

from anytext.