From 7080e1a11c4ac4cba37cbda2f8607e7d6bb20570 Mon Sep 17 00:00:00 2001 From: Disty0 Date: Fri, 22 Dec 2023 22:40:03 +0300 Subject: [PATCH 1/2] Fix convert_diffusers20_original_sd.py and add metadata & variant options --- tools/convert_diffusers20_original_sd.py | 20 ++++++++++++++++---- 1 file changed, 16 insertions(+), 4 deletions(-) diff --git a/tools/convert_diffusers20_original_sd.py b/tools/convert_diffusers20_original_sd.py index b9365b51..a6774328 100644 --- a/tools/convert_diffusers20_original_sd.py +++ b/tools/convert_diffusers20_original_sd.py @@ -23,7 +23,7 @@ def convert(args): is_load_ckpt = os.path.isfile(args.model_to_load) is_save_ckpt = len(os.path.splitext(args.model_to_save)[1]) > 0 - assert not is_load_ckpt or args.v1 != args.v2, f"v1 or v2 is required to load checkpoint / checkpointの読み込みにはv1/v2指定が必要です" + assert not is_load_ckpt or args.v1 != args.v2, "v1 or v2 is required to load checkpoint / checkpointの読み込みにはv1/v2指定が必要です" # assert ( # is_save_ckpt or args.reference_model is not None # ), f"reference model is required to save as Diffusers / Diffusers形式での保存には参照モデルが必要です" @@ -37,7 +37,7 @@ def convert(args): text_encoder, vae, unet = model_util.load_models_from_stable_diffusion_checkpoint(v2_model, args.model_to_load, unet_use_linear_projection_in_v2=args.unet_use_linear_projection) else: pipe = StableDiffusionPipeline.from_pretrained( - args.model_to_load, torch_dtype=load_dtype, tokenizer=None, safety_checker=None + args.model_to_load, torch_dtype=load_dtype, tokenizer=None, safety_checker=None, variant=args.variant ) text_encoder = pipe.text_encoder vae = pipe.vae @@ -57,7 +57,7 @@ def convert(args): if is_save_ckpt: original_model = args.model_to_load if is_load_ckpt else None key_count = model_util.save_stable_diffusion_checkpoint( - v2_model, args.model_to_save, text_encoder, unet, original_model, args.epoch, args.global_step, save_dtype, vae + v2_model, args.model_to_save, text_encoder, unet, original_model, args.epoch, args.global_step, None if args.metadata is None else eval(args.metadata), save_dtype=save_dtype, vae=vae ) print(f"model saved. total converted state_dict keys: {key_count}") else: @@ -65,7 +65,7 @@ def convert(args): model_util.save_diffusers_checkpoint( v2_model, args.model_to_save, text_encoder, unet, args.reference_model, vae, args.use_safetensors ) - print(f"model saved.") + print("model saved.") def setup_parser() -> argparse.ArgumentParser: @@ -99,6 +99,18 @@ def setup_parser() -> argparse.ArgumentParser: parser.add_argument( "--global_step", type=int, default=0, help="global_step to write to checkpoint / checkpointに記録するglobal_stepの値" ) + parser.add_argument( + "--metadata", + type=str, + default=None, + help='metadata: metadata written in to the model in Python Dictionary. Example metadata: \'{"name": "model_name", "resolution": "512x512"}\'', + ) + parser.add_argument( + "--variant", + type=str, + default=None, + help="variant: Diffusers variant to load. Example: fp16", + ) parser.add_argument( "--reference_model", type=str, From 3b5c1a1d4b7def40633147c57082840ca42e30e7 Mon Sep 17 00:00:00 2001 From: Kohya S Date: Sun, 24 Dec 2023 21:45:51 +0900 Subject: [PATCH 2/2] Fix issue with tools/convert_diffusers20_original_sd.py --- README.md | 7 ++++++ tools/convert_diffusers20_original_sd.py | 27 ++++++++++++++++++------ 2 files changed, 28 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 55a7d5c2..f103d958 100644 --- a/README.md +++ b/README.md @@ -249,6 +249,13 @@ ControlNet-LLLite, a novel method for ControlNet with SDXL, is added. See [docum ## Change History +### Dec 24, 2023 / 2023/12/24 + +- Fixed to work `tools/convert_diffusers20_original_sd.py`. Thanks to Disty0! PR [#1016](https://github.com/kohya-ss/sd-scripts/pull/1016) + +- `tools/convert_diffusers20_original_sd.py` が動かなくなっていたのが修正されました。Disty0 氏に感謝します。 PR [#1016](https://github.com/kohya-ss/sd-scripts/pull/1016) + + ### Dec 21, 2023 / 2023/12/21 - The issues in multi-GPU training are fixed. Thanks to Isotr0py! PR [#989](https://github.com/kohya-ss/sd-scripts/pull/989) and [#1000](https://github.com/kohya-ss/sd-scripts/pull/1000) diff --git a/tools/convert_diffusers20_original_sd.py b/tools/convert_diffusers20_original_sd.py index a6774328..fe30996a 100644 --- a/tools/convert_diffusers20_original_sd.py +++ b/tools/convert_diffusers20_original_sd.py @@ -34,7 +34,9 @@ def convert(args): if is_load_ckpt: v2_model = args.v2 - text_encoder, vae, unet = model_util.load_models_from_stable_diffusion_checkpoint(v2_model, args.model_to_load, unet_use_linear_projection_in_v2=args.unet_use_linear_projection) + text_encoder, vae, unet = model_util.load_models_from_stable_diffusion_checkpoint( + v2_model, args.model_to_load, unet_use_linear_projection_in_v2=args.unet_use_linear_projection + ) else: pipe = StableDiffusionPipeline.from_pretrained( args.model_to_load, torch_dtype=load_dtype, tokenizer=None, safety_checker=None, variant=args.variant @@ -57,11 +59,22 @@ def convert(args): if is_save_ckpt: original_model = args.model_to_load if is_load_ckpt else None key_count = model_util.save_stable_diffusion_checkpoint( - v2_model, args.model_to_save, text_encoder, unet, original_model, args.epoch, args.global_step, None if args.metadata is None else eval(args.metadata), save_dtype=save_dtype, vae=vae + v2_model, + args.model_to_save, + text_encoder, + unet, + original_model, + args.epoch, + args.global_step, + None if args.metadata is None else eval(args.metadata), + save_dtype=save_dtype, + vae=vae, ) print(f"model saved. total converted state_dict keys: {key_count}") else: - print(f"copy scheduler/tokenizer config from: {args.reference_model if args.reference_model is not None else 'default model'}") + print( + f"copy scheduler/tokenizer config from: {args.reference_model if args.reference_model is not None else 'default model'}" + ) model_util.save_diffusers_checkpoint( v2_model, args.model_to_save, text_encoder, unet, args.reference_model, vae, args.use_safetensors ) @@ -77,7 +90,9 @@ def setup_parser() -> argparse.ArgumentParser: "--v2", action="store_true", help="load v2.0 model (v1 or v2 is required to load checkpoint) / 2.0のモデルを読み込む" ) parser.add_argument( - "--unet_use_linear_projection", action="store_true", help="When saving v2 model as Diffusers, set U-Net config to `use_linear_projection=true` (to match stabilityai's model) / Diffusers形式でv2モデルを保存するときにU-Netの設定を`use_linear_projection=true`にする（stabilityaiのモデルと合わせる）" + "--unet_use_linear_projection", + action="store_true", + help="When saving v2 model as Diffusers, set U-Net config to `use_linear_projection=true` (to match stabilityai's model) / Diffusers形式でv2モデルを保存するときにU-Netの設定を`use_linear_projection=true`にする（stabilityaiのモデルと合わせる）", ) parser.add_argument( "--fp16", @@ -103,13 +118,13 @@ def setup_parser() -> argparse.ArgumentParser: "--metadata", type=str, default=None, - help='metadata: metadata written in to the model in Python Dictionary. Example metadata: \'{"name": "model_name", "resolution": "512x512"}\'', + help='モデルに保存されるメタデータ、Pythonの辞書形式で指定 / metadata: metadata written in to the model in Python Dictionary. Example metadata: \'{"name": "model_name", "resolution": "512x512"}\'', ) parser.add_argument( "--variant", type=str, default=None, - help="variant: Diffusers variant to load. Example: fp16", + help="読む込むDiffusersのvariantを指定する、例: fp16 / variant: Diffusers variant to load. Example: fp16", ) parser.add_argument( "--reference_model",