From 006756f9cd6258eae418e9209cfc13f940ec53e1 Mon Sep 17 00:00:00 2001 From: Fampai <> Date: Mon, 31 Oct 2022 07:26:08 -0400 Subject: [PATCH] Added TI training optimizations option to use xattention optimizations when training option to unload vae when training --- modules/shared.py | 3 ++- modules/textual_inversion/textual_inversion.py | 9 +++++++++ modules/textual_inversion/ui.py | 7 +++++-- 3 files changed, 16 insertions(+), 3 deletions(-) diff --git a/modules/shared.py b/modules/shared.py index fb84afd8d..4c3d0ce7f 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -256,11 +256,12 @@ options_templates.update(options_section(('system', "System"), { })) options_templates.update(options_section(('training', "Training"), { - "unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training hypernetwork. Saves VRAM."), + "unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training if possible. Saves VRAM."), "dataset_filename_word_regex": OptionInfo("", "Filename word regex"), "dataset_filename_join_string": OptionInfo(" ", "Filename join string"), "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(500, "Save an csv containing the loss to log directory every N steps, 0 to disable"), + "training_xattention_optimizations": OptionInfo(False, "Use cross attention optimizations while training"), })) options_templates.update(options_section(('sd', "Stable Diffusion"), { diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 17dfb2239..b0a1d26b9 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -214,6 +214,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt') log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%m-%d"), embedding_name) + unload = shared.opts.unload_models_when_training if save_embedding_every > 0: embedding_dir = os.path.join(log_directory, "embeddings") @@ -238,6 +239,8 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc 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=embedding_name, model=shared.sd_model, device=devices.device, template_file=template_file, batch_size=batch_size) + if unload: + shared.sd_model.first_stage_model.to(devices.cpu) hijack = sd_hijack.model_hijack @@ -303,6 +306,9 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc if images_dir is not None and steps_done % create_image_every == 0: forced_filename = f'{embedding_name}-{steps_done}' last_saved_image = os.path.join(images_dir, forced_filename) + + shared.sd_model.first_stage_model.to(devices.device) + p = processing.StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, do_not_save_grid=True, @@ -330,6 +336,9 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc processed = processing.process_images(p) image = processed.images[0] + if unload: + shared.sd_model.first_stage_model.to(devices.cpu) + shared.state.current_image = image if save_image_with_stored_embedding and os.path.exists(last_saved_file) and embedding_yet_to_be_embedded: diff --git a/modules/textual_inversion/ui.py b/modules/textual_inversion/ui.py index e712284d1..d679e6f4e 100644 --- a/modules/textual_inversion/ui.py +++ b/modules/textual_inversion/ui.py @@ -25,8 +25,10 @@ def train_embedding(*args): assert not shared.cmd_opts.lowvram, 'Training models with lowvram not possible' + apply_optimizations = shared.opts.training_xattention_optimizations try: - sd_hijack.undo_optimizations() + if not apply_optimizations: + sd_hijack.undo_optimizations() embedding, filename = modules.textual_inversion.textual_inversion.train_embedding(*args) @@ -38,5 +40,6 @@ Embedding saved to {html.escape(filename)} except Exception: raise finally: - sd_hijack.apply_optimizations() + if not apply_optimizations: + sd_hijack.apply_optimizations()