Website: https://thisanimedoesnotexist.ai/

The model can be downloaded here: https://www.gwern.net/Faces#tadne-download

Considering GLaSS already supports BigGAN and different SG2 models, I hope it wouldn't be too hard to add this great model too.

When I try the text-to-image task, I always run out of CUDA memory on single GPU. I try to set the device to 'cuda:0,1' but it doesn't work. I get error like this:

File "run.py", line 54, in <module>
    problem = GenerationProblem(config)
  File "/home/ubuntu/Documents/clip-glass/problem.py", line 9, in __init__
    self.generator = Generator(config)
  File "/home/ubuntu/Documents/clip-glass/generator.py", line 16, in __init__
    self.CLIP, clip_preprocess = clip.load("ViT-B/32", device=self.config.device, jit=False)
  File "/home/ubuntu/anaconda3/envs/lib/python3.7/site-packages/clip/clip.py", line 137, in load
    model = build_model(state_dict or model.state_dict()).to(device)
  File "/home/ubuntu/anaconda3/envs/lib/python3.7/site-packages/torch/nn/modules/module.py", line 600, in to
    device, dtype, non_blocking, convert_to_format = torch._C._nn._parse_to(*args, **kwargs)
RuntimeError: Invalid device string: 'cuda:0,1,'

I wonder how to set it on multi GPUs properly.

In the initialization command, generating the pytorch version string does not work for versions not included in suffix mapping dictionary. Before: pytorch_version = "1.7.1" + pytorch_suffix[version] if version in pytorch_suffix else "+cu110"

Fixed parentheses: pytorch_version = "1.7.1" + (pytorch_suffix[version] if version in pytorch_suffix else "+cu110")

The notebook is incredible and a great resource to go along with the research, great work!

Hi,

I tried your model in image captioning using the demo dog image but got a totally different results from your paper. I ran your script 5 times under the default setting and got the following results: ['the picture of the dog's body.\n\n"The dog's body is’] ['the picture of a dog with a bloated, bloated, bloa’] ["the picture of the puppy's body, with the body's b”] ["the picture of the dog's body, with a large, round”] ["the picture of the dog's body. The dog's body is c”] ['the picture of a dog with a large belly.\n\nâ¼\n\nâ¼\n\nâ¼\n’]

The captioning result shown in your paper is as follows.

Is there any setting modification I need to take for image captioning? Thank you.

Hi, first thanks for your job :) I don't know if it's an issue. When I select config "GPT-2", the output text of the prediction seems to be incomplete (example: "the picture of a man who is a man, a man who is a" ) --> seems like something is missing. Is this a bug? if not, is there a way to increase output length?

many thanks in advance

Thanks for your work. I found that the discriminator is helpful to improve the generation quality in StyleGAN setting. Why not use the BigGAN discriminator in the BigGAN setting?

Thanks.

Hello, When I run the following,

virtualenv --python=python3.6 env && . ./env/bin/activate

I get this output:

RuntimeError: failed to find interpreter for Builtin discover of python_spec='python3.6'

Thoughts?

your demo notebook worked for me yesterday but today it's giving me this: RuntimeError: Method 'forward' is not defined.

I really like your implementation! I don't think I changed anything in what I'm doing. any ideas?
i'm pretty much a noob, trying to learn this stuff. thanks in advance

how to complete image with text

example: I give an unfilled image from the middle down, then I write "same image but below, a sketch of the image"

and it generates an image of but half down is a sketch half up.

Hi! Love the project.

I'm in the OpenAI GPT-3 beta, and I was wondering if it's possible for clip-glass to support GPT-3 for the image-to-text task.

If it's possible, I'd love to help set that integration up but I'm not sure where to start.