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| author | TinkTheBoush <TinkTheBoush@github.com> | 2022-11-04 10:39:03 +0000 |
|---|---|---|
| committer | TinkTheBoush <TinkTheBoush@github.com> | 2022-11-04 10:39:03 +0000 |
| commit | 821e2b883dbb42a187bc37379175cd55b7cd7e81 (patch) | |
| tree | dae5c1757dbdc7130ebe16012c6d1bcf36f37223 /modules/hypernetworks | |
| parent | af6fba247553e670ef5e2dcc1866279f9f065d6d (diff) | |
| download | stable-diffusion-webui-gfx803-821e2b883dbb42a187bc37379175cd55b7cd7e81.tar.gz stable-diffusion-webui-gfx803-821e2b883dbb42a187bc37379175cd55b7cd7e81.tar.bz2 stable-diffusion-webui-gfx803-821e2b883dbb42a187bc37379175cd55b7cd7e81.zip | |
change option position to Training setting
Diffstat (limited to 'modules/hypernetworks')
| -rw-r--r-- | modules/hypernetworks/hypernetwork.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 7630fb81..a11e01d6 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -331,7 +331,7 @@ def report_statistics(loss_info:dict): -def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log_directory, training_width, training_height, steps, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, shuffle_tags, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
+def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log_directory, training_width, training_height, steps, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
# images allows training previews to have infotext. Importing it at the top causes a circular import problem.
from modules import images
@@ -376,7 +376,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log # dataset loading may take a while, so input validations and early returns should be done before this
shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."
with torch.autocast("cuda"):
- 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, shuffle_tags=shuffle_tags, model=shared.sd_model, device=devices.device, template_file=template_file, include_cond=True, batch_size=batch_size)
+ 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, device=devices.device, template_file=template_file, include_cond=True, batch_size=batch_size)
if unload:
shared.sd_model.cond_stage_model.to(devices.cpu)
|