Added Lion optimizer

1 files changed, 5 insertions, 4 deletions

diff --git a/training/functional.py b/training/functional.py
index 41794ea..4d0cf0e 100644
--- a/training/functional.py
+++ b/training/functional.py
@@ -12,7 +12,7 @@ from torch.utils.data import DataLoader
 
 from accelerate import Accelerator
 from transformers import CLIPTextModel
-from diffusers import AutoencoderKL, DDPMScheduler, UNet2DConditionModel, UniPCMultistepScheduler
+from diffusers import AutoencoderKL, UNet2DConditionModel, UniPCMultistepScheduler
 
 from tqdm.auto import tqdm
 from PIL import Image
@@ -22,6 +22,7 @@ from pipelines.stable_diffusion.vlpn_stable_diffusion import VlpnStableDiffusion
 from models.clip.embeddings import ManagedCLIPTextEmbeddings, patch_managed_embeddings
 from models.clip.util import get_extended_embeddings
 from models.clip.tokenizer import MultiCLIPTokenizer
+from schedulers.scheduling_deis_multistep import DEISMultistepScheduler
 from training.util import AverageMeter
 
 
@@ -78,7 +79,7 @@ def get_models(pretrained_model_name_or_path: str):
     text_encoder = CLIPTextModel.from_pretrained(pretrained_model_name_or_path, subfolder='text_encoder')
     vae = AutoencoderKL.from_pretrained(pretrained_model_name_or_path, subfolder='vae')
     unet = UNet2DConditionModel.from_pretrained(pretrained_model_name_or_path, subfolder='unet')
-    noise_scheduler = DDPMScheduler.from_pretrained(pretrained_model_name_or_path, subfolder='scheduler')
+    noise_scheduler = DEISMultistepScheduler.from_pretrained(pretrained_model_name_or_path, subfolder='scheduler')
     sample_scheduler = UniPCMultistepScheduler.from_pretrained(
         pretrained_model_name_or_path, subfolder='scheduler')
 
@@ -251,7 +252,7 @@ def add_placeholder_tokens(
 
 def loss_step(
     vae: AutoencoderKL,
-    noise_scheduler: DDPMScheduler,
+    noise_scheduler: DEISMultistepScheduler,
     unet: UNet2DConditionModel,
     text_encoder: CLIPTextModel,
     with_prior_preservation: bool,
@@ -551,7 +552,7 @@ def train(
     unet: UNet2DConditionModel,
     text_encoder: CLIPTextModel,
     vae: AutoencoderKL,
-    noise_scheduler: DDPMScheduler,
+    noise_scheduler: DEISMultistepScheduler,
     dtype: torch.dtype,
     seed: int,
     project: str,