Comments (1)
Hi, Thank you for your interest. In this work, we only tested on V100 GPUs with 32GB memory.
If you want to use 16G GPU memory V100, there are also multiple tricks to reduce memory usage. For example, you can consider reducing stylegan model size to 256* 256 or you can use fewer stylegan features and reduce DatasetGAN input feature size as indicated in https://github.com/nv-tlabs/editGAN_release/blob/release_final/experiments/datasetgan_car.json#L6. or reduce ensemble model number as indicated https://github.com/nv-tlabs/editGAN_release/blob/release_final/experiments/datasetgan_car.json#L15.
However, it's out of the scope of our discussion of the current EditGAN project.
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Related Issues (20)
- add web demo/model to Huggingface
- command ninja -v returned non-zero HOT 3
- How to edit custom image of car HOT 4
- fail to run the app HOT 7
- how to convert the tensorflow checkpoint to pytorch? HOT 3
- generate new samples without the app tool HOT 1
- Hi! encoder training data! HOT 1
- ROI don't initialize
- The editing vector can not work well on different viewpoints HOT 2
- Question about style interpreter
- Question about editing of traffic flow heatmap
- Can I run this app on a server with GPU and use a computer to get the app by the ip address of the server?
- fail to run the app CUDA out of memory HOT 2
- FileNotFoundError: [Errno 2] No such file or directory: './static/results/current_editing_latent_cache.pickle'
- Cannot download DatasetGAN training images and annotations from Google Drive
- App not rendering properly HOT 7
- gpu out of memory HOT 5
- FileNotFoundError: [Errno 2] No such file or directory: './static/results/current_editing_latent_cache.pickle'
- Failure getting EditGAN to run in Colab HOT 12
- Can the CPU reason? HOT 1
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