use correct autoencoder class for different model exports (#1245)

bghira · Dec 25, 2024 · ff924cb · ff924cb
1 parent 933789c
commit ff924cb
Showing 1 changed file with 7 additions and 6 deletions.
diff --git a/helpers/training/trainer.py b/helpers/training/trainer.py
@@ -469,16 +469,17 @@ def init_vae(self, move_to_accelerator: bool = True):
             from diffusers import AutoencoderDC as AutoencoderClass
         else:
             from diffusers import AutoencoderKL as AutoencoderClass
+        self.vae_cls = AutoencoderClass
 
         with ContextManagers(deepspeed_zero_init_disabled_context_manager()):
             try:
-                self.vae = AutoencoderClass.from_pretrained(**self.config.vae_kwargs)
+                self.vae = self.vae_cls.from_pretrained(**self.config.vae_kwargs)
             except:
                 logger.warning(
                     "Couldn't load VAE with default path. Trying without a subfolder.."
                 )
                 self.config.vae_kwargs["subfolder"] = None
-                self.vae = AutoencoderClass.from_pretrained(**self.config.vae_kwargs)
+                self.vae = self.vae_cls.from_pretrained(**self.config.vae_kwargs)
         if (
             self.vae is not None
             and self.config.vae_enable_tiling
@@ -3233,7 +3234,7 @@ def train(self):
                         tokenizer_3=self.tokenizer_3,
                         vae=self.vae
                         or (
-                            AutoencoderKL.from_pretrained(
+                            self.vae_cls.from_pretrained(
                                 self.config.vae_path,
                                 subfolder=(
                                     "vae"
@@ -3305,7 +3306,7 @@ def train(self):
                         tokenizer=self.tokenizer_1,
                         vae=self.vae
                         or (
-                            AutoencoderKL.from_pretrained(
+                            self.vae_cls.from_pretrained(
                                 self.config.vae_path,
                                 subfolder=(
                                     "vae"
@@ -3339,7 +3340,7 @@ def train(self):
                         tokenizer=self.tokenizer_1,
                         vae=self.vae
                         or (
-                            AutoencoderKL.from_pretrained(
+                            self.vae_cls.from_pretrained(
                                 self.config.vae_path,
                                 subfolder=(
                                     "vae"
@@ -3408,7 +3409,7 @@ def train(self):
                         tokenizer=self.tokenizer_1,
                         tokenizer_2=self.tokenizer_2,
                         vae=StateTracker.get_vae()
-                        or AutoencoderKL.from_pretrained(
+                        or self.vae_cls.from_pretrained(
                             self.config.vae_path,
                             subfolder=(
                                 "vae"