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fix pin_memory with different latent sampling method

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flamelaw
2022-11-21 10:15:46 +09:00
parent 2d22d72cda
commit 5b57f61ba4
3 changed files with 24 additions and 11 deletions
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5
modules/hypernetworks/hypernetwork.py
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@@ -416,7 +416,10 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
pin_memory = shared.opts.pin_memory
ds = modules.textual_inversion.dataset.PersonalizedBase(data_root=data_root, width=training_width, height=training_height, repeats=shared.opts.training_image_repeats_per_epoch, placeholder_token=hypernetwork_name, model=shared.sd_model, cond_model=shared.sd_model.cond_stage_model, device=devices.device, template_file=template_file, include_cond=True, batch_size=batch_size, gradient_step=gradient_step, shuffle_tags=shuffle_tags, tag_drop_out=tag_drop_out, latent_sampling_method=latent_sampling_method)
dl = modules.textual_inversion.dataset.PersonalizedDataLoader(ds, batch_size=ds.batch_size, pin_memory=pin_memory)
latent_sampling_method = ds.latent_sampling_method
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.cond_stage_model.to(devices.cpu)