Include model in log file. Exclude directory.

1 files changed, 9 insertions, 13 deletions

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 68648550..ce7e4f5d 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -231,26 +231,22 @@ def write_loss(log_directory, filename, step, epoch_len, 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)

+def save_settings_to_file(model_name, model_hash, 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):

     # Starting index of preview-related arguments.

-    border_index = 16

+    border_index = 18

     # Get a list of the argument names.

-    arg_names = inspect.getfullargspec(save_settings_to_file).args

-    

+    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[:border_index]  # Include all arguments up until the preview-related ones.

     if preview_from_txt2img:

-        names.extend(arg_names[border_index:])  # Include all remaining arguments if `preview_from_txt2img` is True.

-

+        names.extend(arg_names[border_index:])  # Include preview-related arguments if applicable.

     # Build the settings string.

     settings_str = "datetime : " + datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S") + "\n"

     for name in names:

-        value = locals()[name]

-        settings_str += f"{name}: {value}\n"

-

+        if name != 'log_directory': # It's useless and redundant to save log_directory.

+            value = locals()[name]

+            settings_str += f"{name}: {value}\n"

+    # Create or append to the file.

     with open(os.path.join(log_directory, 'settings.txt'), "a+") as fout:

         fout.write(settings_str + "\n\n")

 

@@ -333,7 +329,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
     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_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)

+            save_settings_to_file(checkpoint.model_name, '[{}]'.format(checkpoint.hash), 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