1 files changed, 3 insertions, 9 deletions

diff --git a/training/functional.py b/training/functional.py
index 49c21c7..56c2995 100644
--- a/training/functional.py
+++ b/training/functional.py
@@ -20,7 +20,7 @@ from tqdm.auto import tqdm
 
 from data.csv import VlpnDataset
 from pipelines.stable_diffusion.vlpn_stable_diffusion import VlpnStableDiffusion
-from models.clip.embeddings import ManagedCLIPTextEmbeddings, patch_managed_embeddings
+from models.clip.embeddings import ManagedCLIPTextEmbeddings
 from models.clip.util import get_extended_embeddings
 from models.clip.tokenizer import MultiCLIPTokenizer
 from models.convnext.discriminator import ConvNeXtDiscriminator
@@ -68,11 +68,7 @@ class TrainingStrategy():
     prepare: TrainingStrategyPrepareCallable
 
 
-def get_models(
-    pretrained_model_name_or_path: str,
-    emb_alpha: int = 8,
-    emb_dropout: float = 0.0
-):
+def get_models(pretrained_model_name_or_path: str):
     tokenizer = MultiCLIPTokenizer.from_pretrained(pretrained_model_name_or_path, subfolder='tokenizer')
     text_encoder = CLIPTextModel.from_pretrained(pretrained_model_name_or_path, subfolder='text_encoder')
     vae = AutoencoderKL.from_pretrained(pretrained_model_name_or_path, subfolder='vae')
@@ -81,9 +77,7 @@ def get_models(
     sample_scheduler = UniPCMultistepScheduler.from_pretrained(
         pretrained_model_name_or_path, subfolder='scheduler')
 
-    embeddings = patch_managed_embeddings(text_encoder, emb_alpha, emb_dropout)
-
-    return tokenizer, text_encoder, vae, unet, noise_scheduler, sample_scheduler, embeddings
+    return tokenizer, text_encoder, vae, unet, noise_scheduler, sample_scheduler
 
 
 def save_samples(