Comments (3)
Hi @BlinkDL, look like the code for sampling is so inefficient that A100 cannot run 🤣 I will investigate this
from enhancing-transformers.
Hi @BlinkDL, I think the code is good for training but the sampling code has memory leak problem. For now, I think you can make this function return an empty dict {} to skip sampling during training phase
from enhancing-transformers.
The issues seem to be fixed as now I can train a very big GPT and generate images without getting OOM so I will close this for now
from enhancing-transformers.
Related Issues (18)
- Pre-norm and Post-norm HOT 6
- An inplace operation in the forward process HOT 1
- Reconstruction Visualization HOT 2
- stage2 transformer HOT 2
- stage1 pretraining HOT 7
- Model license HOT 4
- stage2 transform HOT 9
- about training loss HOT 1
- The question is done. HOT 1
- ImageNet version.
- Reconstruction results HOT 4
- Learning rate and scheduler for stage 1 training. HOT 1
- raise CalledProcessError(retcode, process.args, subprocess.CalledProcessError: Command '['where', 'cl']' returned non-zero exit status 1. HOT 5
- Results HOT 5
- Smaller images HOT 10
- Pretrained Stage 2 Transformer for ViT-VQGAN HOT 8
- Training time and number of GPUS HOT 6
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