added prompt dropout to happen indempendently on each TE

scripts/make_lcm_sdxl_model.py

@@ -0,0 +1,67 @@
+import argparse
+from collections import OrderedDict
+
+import torch
+
+from toolkit.config_modules import ModelConfig
+from toolkit.stable_diffusion_model import StableDiffusion
+
+
+parser = argparse.ArgumentParser()
+parser.add_argument(
+    'input_path',
+    type=str,
+    help='Path to original sdxl model'
+)
+parser.add_argument(
+    'output_path',
+    type=str,
+    help='output path'
+)
+parser.add_argument('--sdxl', action='store_true', help='is sdxl model')
+parser.add_argument('--refiner', action='store_true', help='is refiner model')
+parser.add_argument('--ssd', action='store_true', help='is ssd model')
+parser.add_argument('--sd2', action='store_true', help='is sd 2 model')
+
+args = parser.parse_args()
+device = torch.device('cpu')
+dtype = torch.float32
+
+print(f"Loading model from {args.input_path}")
+
+if args.sdxl:
+    adapter_id = "latent-consistency/lcm-lora-sdxl"
+if args.refiner:
+    adapter_id = "latent-consistency/lcm-lora-sdxl"
+elif args.ssd:
+    adapter_id = "latent-consistency/lcm-lora-ssd-1b"
+else:
+    adapter_id = "latent-consistency/lcm-lora-sdv1-5"
+
+
+diffusers_model_config = ModelConfig(
+        name_or_path=args.input_path,
+        is_xl=args.sdxl,
+        is_v2=args.sd2,
+        is_ssd=args.ssd,
+        dtype=dtype,
+    )
+diffusers_sd = StableDiffusion(
+    model_config=diffusers_model_config,
+    device=device,
+    dtype=dtype,
+)
+diffusers_sd.load_model()
+
+
+print(f"Loaded model from {args.input_path}")
+
+diffusers_sd.pipeline.load_lora_weights(adapter_id)
+diffusers_sd.pipeline.fuse_lora()
+
+meta = OrderedDict()
+
+diffusers_sd.save(args.output_path, meta=meta)
+
+
+print(f"Saved to {args.output_path}")