diff options
Diffstat (limited to 'infer.py')
-rw-r--r-- | infer.py | 5 |
1 files changed, 3 insertions, 2 deletions
@@ -181,7 +181,7 @@ def save_args(basepath, args, extra={}): | |||
181 | json.dump(info, f, indent=4) | 181 | json.dump(info, f, indent=4) |
182 | 182 | ||
183 | 183 | ||
184 | def create_pipeline(model, ti_embeddings_dir, dtype): | 184 | def create_pipeline(model, embeddings_dir, dtype): |
185 | print("Loading Stable Diffusion pipeline...") | 185 | print("Loading Stable Diffusion pipeline...") |
186 | 186 | ||
187 | tokenizer = CLIPTokenizer.from_pretrained(model, subfolder='tokenizer', torch_dtype=dtype) | 187 | tokenizer = CLIPTokenizer.from_pretrained(model, subfolder='tokenizer', torch_dtype=dtype) |
@@ -190,7 +190,8 @@ def create_pipeline(model, ti_embeddings_dir, dtype): | |||
190 | unet = UNet2DConditionModel.from_pretrained(model, subfolder='unet', torch_dtype=dtype) | 190 | unet = UNet2DConditionModel.from_pretrained(model, subfolder='unet', torch_dtype=dtype) |
191 | scheduler = DDIMScheduler.from_pretrained(model, subfolder='scheduler', torch_dtype=dtype) | 191 | scheduler = DDIMScheduler.from_pretrained(model, subfolder='scheduler', torch_dtype=dtype) |
192 | 192 | ||
193 | load_text_embeddings(tokenizer, text_encoder, Path(ti_embeddings_dir)) | 193 | added_tokens = load_text_embeddings(tokenizer, text_encoder, embeddings_dir) |
194 | print(f"Added {len(added_tokens)} tokens from embeddings dir: {added_tokens}") | ||
194 | 195 | ||
195 | pipeline = VlpnStableDiffusion( | 196 | pipeline = VlpnStableDiffusion( |
196 | text_encoder=text_encoder, | 197 | text_encoder=text_encoder, |