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possibly make NaN check cheaper

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AUTOMATIC1111 2024-06-08 12:41:28 +03:00
parent 194c2620d6
commit 547778b10f
1 changed files with 4 additions and 4 deletions
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8
modules/devices.py
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@ -243,22 +243,22 @@ def test_for_nans(x, where):
if shared.cmd_opts.disable_nan_check:
return
if not torch.all(torch.isnan(x)).item():
if not torch.isnan(x[(0, ) * len(x.shape)]):
return
if where == "unet":
message = "A tensor with all NaNs was produced in Unet."
message = "A tensor with NaNs was produced in Unet."
if not shared.cmd_opts.no_half:
message += " 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 Diffusion or using the --no-half commandline argument to fix this."
elif where == "vae":
message = "A tensor with all NaNs was produced in VAE."
message = "A tensor with NaNs was produced in VAE."
if not shared.cmd_opts.no_half and not shared.cmd_opts.no_half_vae:
message += " This could be because there's not enough precision to represent the picture. Try adding --no-half-vae commandline argument to fix this."
else:
message = "A tensor with all NaNs was produced."
message = "A tensor with NaNs was produced."
message += " Use --disable-nan-check commandline argument to disable this check."