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update ti folders

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Vladimir Mandic
2023-04-30 08:55:44 -04:00
parent 67c392027b
commit b23b6a6e2c
5 changed files with 8 additions and 7 deletions
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extensions-builtin/multidiffusion-upscaler-for-automatic1111
+1 -1
Submodule extensions-builtin/multidiffusion-upscaler-for-automatic1111 updated: 6931b89cb4...860f8a4051
extensions-builtin/sd-webui-controlnet
+1 -1
Submodule extensions-builtin/sd-webui-controlnet updated: 4d4b1f8c00...09d1fcbf4d
modules/lora
+1 -1
Submodule modules/lora updated: d52c524fc2...bc803e01c7
modules/shared.py
+2 -2
View File
@@ -252,8 +252,6 @@ options_templates.update(options_section(('system-paths', "System Paths"), {
"ckpt_dir": OptionInfo(os.path.join(paths.models_path, 'Stable-diffusion'), "Path to directory with stable diffusion checkpoints"),
"vae_dir": OptionInfo(os.path.join(paths.models_path, 'VAE'), "Path to directory with VAE files"),
"embeddings_dir": OptionInfo(os.path.join(paths.models_path, 'embeddings'), "Embeddings directory for textual inversion"),
"embeddings_templates_dir": OptionInfo(os.path.join(paths.script_path, 'train/templates'), "Embeddings train templates directory"),
"embeddings_train_log": OptionInfo(os.path.join(paths.script_path, 'train.csv'), "Embeddings train log file"),
"hypernetwork_dir": OptionInfo(os.path.join(paths.models_path, 'hypernetworks'), "Hypernetwork directory"),
"codeformer_models_path": OptionInfo(os.path.join(paths.models_path, 'Codeformer'), "Path to directory with codeformer model file(s)."),
"gfpgan_models_path": OptionInfo(os.path.join(paths.models_path, 'GFPGAN'), "Path to directory with GFPGAN model file(s)"),
@@ -351,6 +349,8 @@ options_templates.update(options_section(('training', "Training"), {
"save_training_settings_to_txt": OptionInfo(True, "Save textual inversion and hypernet settings to a text file whenever training starts."),
"dataset_filename_word_regex": OptionInfo("", "Filename word regex"),
"dataset_filename_join_string": OptionInfo(" ", "Filename join string"),
"embeddings_templates_dir": OptionInfo(os.path.join(paths.script_path, 'train', 'templates'), "Embeddings train templates directory"),
"embeddings_train_log": OptionInfo(os.path.join(paths.script_path, 'train', 'log', 'train.csv'), "Embeddings train log file"),
"training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),
"training_write_csv_every": OptionInfo(0, "Save an csv containing the loss to log directory every N steps, 0 to disable"),
"training_enable_tensorboard": OptionInfo(False, "Enable tensorboard logging."),
modules/textual_inversion/textual_inversion.py
+3 -2
View File
@@ -174,7 +174,7 @@ class EmbeddingDatabase:
if len(emb.shape) == 1:
emb = emb.unsqueeze(0)
else:
raise Exception(f"Couldn't identify {filename} as neither textual inversion embedding nor diffuser concept.")
raise RuntimeError(f"Couldn't identify {filename} as neither textual inversion embedding nor diffuser concept.")
vec = emb.detach().to(devices.device, dtype=torch.float32)
embedding = Embedding(vec, name)
@@ -347,7 +347,8 @@ def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, dat
assert log_directory, "Log directory is empty"
def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, use_weight, create_image_every, save_embedding_every, template_filename, 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):
def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, use_weight, create_image_every, save_embedding_every, template_filename, 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): # pylint: disable=unused_argument
save_embedding_every = save_embedding_every or 0
create_image_every = create_image_every or 0
template_file = textual_inversion_templates.get(template_filename, None)