From 5b57f61ba47f8b11d19a5b46e7fb5a52458abae5 Mon Sep 17 00:00:00 2001 From: flamelaw Date: Mon, 21 Nov 2022 10:15:46 +0900 Subject: fix pin_memory with different latent sampling method --- modules/textual_inversion/textual_inversion.py | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) (limited to 'modules/textual_inversion/textual_inversion.py') diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 1d5e3a32..3036e48a 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -277,7 +277,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_ latent_sampling_method = ds.latent_sampling_method - dl = modules.textual_inversion.dataset.PersonalizedDataLoader(ds, batch_size=ds.batch_size, pin_memory=False) + dl = modules.textual_inversion.dataset.PersonalizedDataLoader(ds, latent_sampling_method=latent_sampling_method, batch_size=ds.batch_size, pin_memory=pin_memory) if unload: shared.sd_model.first_stage_model.to(devices.cpu) @@ -333,11 +333,6 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_ # go back until we reach gradient accumulation steps if (j + 1) % gradient_step != 0: continue - #print(f"grad:{embedding.vec.grad.detach().cpu().abs().mean().item():.7f}") - #scaler.unscale_(optimizer) - #print(f"grad:{embedding.vec.grad.detach().cpu().abs().mean().item():.7f}") - #torch.nn.utils.clip_grad_norm_(embedding.vec, max_norm=1.0) - #print(f"grad:{embedding.vec.grad.detach().cpu().abs().mean().item():.7f}") scaler.step(optimizer) scaler.update() embedding.step += 1 -- cgit v1.2.1