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keep textual inversion dataset latents in CPU memory to save a bit of VRAM

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AUTOMATIC
2022-10-02 22:59:01 +03:00
parent c7543d4940
commit 6785331e22
3 changed files with 7 additions and 2 deletions
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2
modules/textual_inversion/dataset.py
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@@ -8,6 +8,7 @@ from torchvision import transforms
import random
import tqdm
from modules import devices
class PersonalizedBase(Dataset):
@@ -47,6 +48,7 @@ class PersonalizedBase(Dataset):
torchdata = torch.moveaxis(torchdata, 2, 0)
init_latent = model.get_first_stage_encoding(model.encode_first_stage(torchdata.unsqueeze(dim=0))).squeeze()
init_latent = init_latent.to(devices.cpu)
self.dataset.append((init_latent, filename_tokens))