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restore sd_model arg for backward compat

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Kohya S
2023-04-19 21:11:12 +09:00
parent f770cd96c6
commit 314a364f61
1 changed files with 17 additions and 5 deletions
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22
networks/lora_interrogator.py
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@@ -17,9 +17,13 @@ DEVICE = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
def interrogate(args): def interrogate(args):
weights_dtype = torch.float16
# いろいろ準備する # いろいろ準備する
print(f"loading SD model: {args.sd_model}") print(f"loading SD model: {args.sd_model}")
text_encoder, vae, unet, _ = train_util.load_target_model(args, args.sd_model, DEVICE) args.pretrained_model_name_or_path = args.sd_model
args.vae = None
text_encoder, vae, unet, _ = train_util.load_target_model(args,weights_dtype, DEVICE)
print(f"loading LoRA: {args.model}") print(f"loading LoRA: {args.model}")
network, weights_sd = lora.create_network_from_weights(1.0, args.model, vae, text_encoder, unet) network, weights_sd = lora.create_network_from_weights(1.0, args.model, vae, text_encoder, unet)
@@ -41,9 +45,9 @@ def interrogate(args):
else: else:
tokenizer: CLIPTokenizer = CLIPTokenizer.from_pretrained(TOKENIZER_PATH) # , model_max_length=max_token_length + 2) tokenizer: CLIPTokenizer = CLIPTokenizer.from_pretrained(TOKENIZER_PATH) # , model_max_length=max_token_length + 2)
text_encoder.to(DEVICE) text_encoder.to(DEVICE, dtype=weights_dtype)
text_encoder.eval() text_encoder.eval()
unet.to(DEVICE) unet.to(DEVICE, dtype=weights_dtype)
unet.eval() # U-Netは呼び出さないので不要だけど unet.eval() # U-Netは呼び出さないので不要だけど
# トークンをひとつひとつ当たっていく # トークンをひとつひとつ当たっていく
@@ -79,9 +83,14 @@ def interrogate(args):
orig_embs = get_all_embeddings(text_encoder) orig_embs = get_all_embeddings(text_encoder)
network.apply_to(text_encoder, unet, True, len(network.unet_loras) > 0) network.apply_to(text_encoder, unet, True, len(network.unet_loras) > 0)
network.to(DEVICE) info = network.load_state_dict(weights_sd, strict=False)
print(f"Loading LoRA weights: {info}")
network.to(DEVICE, dtype=weights_dtype)
network.eval() network.eval()
del unet
print("You can ignore warning messages start with '_IncompatibleKeys' (LoRA model does not have alpha because trained by older script) / '_IncompatibleKeys'の警告は無視して構いません（以前のスクリプトで学習されたLoRAモデルのためalphaの定義がありません）") print("You can ignore warning messages start with '_IncompatibleKeys' (LoRA model does not have alpha because trained by older script) / '_IncompatibleKeys'の警告は無視して構いません（以前のスクリプトで学習されたLoRAモデルのためalphaの定義がありません）")
print("get text encoder embeddings with lora.") print("get text encoder embeddings with lora.")
lora_embs = get_all_embeddings(text_encoder) lora_embs = get_all_embeddings(text_encoder)
@@ -109,7 +118,10 @@ def interrogate(args):
def setup_parser() -> argparse.ArgumentParser: def setup_parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
train_util.add_sd_models_arguments(parser) parser.add_argument("--v2", action='store_true',
help='load Stable Diffusion v2.x model / Stable Diffusion 2.xのモデルを読み込む')
parser.add_argument("--sd_model", type=str, default=None,
help="Stable Diffusion model to load: ckpt or safetensors file / 読み込むSDのモデル、ckptまたはsafetensors")
parser.add_argument("--model", type=str, default=None, parser.add_argument("--model", type=str, default=None,
help="LoRA model to interrogate: ckpt or safetensors file / 調査するLoRAモデル、ckptまたはsafetensors") help="LoRA model to interrogate: ckpt or safetensors file / 調査するLoRAモデル、ckptまたはsafetensors")
parser.add_argument("--batch_size", type=int, default=16, parser.add_argument("--batch_size", type=int, default=16,