在Stable Diffusion中,将cross attention layer的数据类型转换为float32通常是为了解决因数据类型不匹配或精度不足导致的问题,如NansException错误。根据提供的tips,以下是如何在PyTorch和TensorFlow中实现这一转换的详细步骤: 1. 确定需要转换为float32的数据部分 在Stable Diffusion模型中,cross attention layer的输出tensor...
Try setting the "Upcast cross attention layer to float32" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Use --disable-nan-check commandline argument to disable this check. 底膜采用的时SDXL,设置如下: 问题依然存在,请懂的大神指导一下!谢谢!
您可以尝试在Settings > Stable Diffusion中设置“Upcast cross attention layer to float32”选项来解决这...
ansException: A tensor with all NaNs was produced in Unet. This could be either because there's not enough precision to represent the picture, or because your video card does not support half type. Try setting the "Upcast cross attention layer to float32" option in Settings > Stable Diffus...
NansException: A tensor with all NaNs was produced in Unet. This could be either because there's not enough precision to represent the picture, or because your video card does not support half type. Try setting the "Upcast cross attention layer to float32" option in Settings > Stable Diff...
Try setting the "Upcast cross attention layer to float32" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Use --disable-nan-check commandline argument to disable this check. 这时需要关闭stable diffusion,如果是linux平台,需要在文件 webui-user.sh ...
NansException: A tensor with all NaNs was produced in Unet. This could be either because there's not enough precision to represent the picture, or because your video card does not support half type. Try setting the "Upcast cross attention layer to float32" option in Settings > Stable Diff...
Try setting the "Upcast cross attention layer to float32" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Use --disable-nan-check commandline argument to disable this check. 请关闭 WebUI,回到启动器,在「高级选项」内,关闭 “VAE 模型半精度优化...
NansException: A tensor with all NaNs was produced in Unet. This could be either because there's not enough precision to represent the picture, or because your video card does not support half type. Try setting the "Upcast cross attention layer to float32" option in Settings > Stable Diff...
Try setting the "Upcast cross attention layer to float32" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Use --disable-nan-check commandline argument to disable this check.在参数给: --no-half --disable-nan-check 添加进去都填好后保存修改...