1 files changed, 9 insertions, 5 deletions
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 2bed2ecb..68648550 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -230,18 +230,20 @@ def write_loss(log_directory, filename, step, epoch_len, values):
             **values,
         })
 
+# Note: hypernetwork.py has a nearly identical function of the same name. 
 def save_settings_to_file(initial_step, num_of_dataset_images, embedding_name, vectors_per_token, learn_rate, batch_size, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     checkpoint = sd_models.select_checkpoint()
     model_name = checkpoint.model_name
     model_hash = '[{}]'.format(checkpoint.hash)
-
+    # Starting index of preview-related arguments.
+    border_index = 16
     # Get a list of the argument names.
     arg_names = inspect.getfullargspec(save_settings_to_file).args
     
     # Create a list of the argument names to include in the settings string.
-    names = arg_names[:16]  # Include all arguments up until the preview-related ones.
+    names = arg_names[:border_index]  # Include all arguments up until the preview-related ones.
     if preview_from_txt2img:
-        names.extend(arg_names[16:])  # Include all remaining arguments if `preview_from_txt2img` is True.
+        names.extend(arg_names[border_index:])  # Include all remaining arguments if `preview_from_txt2img` is True.
 
     # Build the settings string.
     settings_str = "datetime : " + datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S") + "\n"
@@ -329,8 +331,10 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
     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=embedding_name, model=shared.sd_model, cond_model=shared.sd_model.cond_stage_model, device=devices.device, template_file=template_file, batch_size=batch_size, gradient_step=gradient_step, shuffle_tags=shuffle_tags, tag_drop_out=tag_drop_out, latent_sampling_method=latent_sampling_method)
-    if shared.opts.save_train_settings_to_txt:
-            save_settings_to_file(initial_step , len(ds) , embedding_name, len(embedding.vec) , learn_rate, batch_size, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height)
+
+    if shared.opts.save_training_settings_to_txt:
+            save_settings_to_file(initial_step, len(ds), embedding_name, len(embedding.vec), learn_rate, batch_size, data_root, log_directory, training_width, training_height, steps, create_image_every, save_embedding_every, template_file, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height)
+
     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)