summaryrefslogtreecommitdiffstats
path: root/training/functional.py
diff options
context:
space:
mode:
Diffstat (limited to 'training/functional.py')
-rw-r--r--training/functional.py4
1 files changed, 2 insertions, 2 deletions
diff --git a/training/functional.py b/training/functional.py
index 1d8e2ee..96ecbc1 100644
--- a/training/functional.py
+++ b/training/functional.py
@@ -73,7 +73,7 @@ def make_grid(images, rows, cols):
73 return grid 73 return grid
74 74
75 75
76def get_models(pretrained_model_name_or_path: str, emb_alpha: float = 1.0): 76def get_models(pretrained_model_name_or_path: str):
77 tokenizer = MultiCLIPTokenizer.from_pretrained(pretrained_model_name_or_path, subfolder='tokenizer') 77 tokenizer = MultiCLIPTokenizer.from_pretrained(pretrained_model_name_or_path, subfolder='tokenizer')
78 text_encoder = CLIPTextModel.from_pretrained(pretrained_model_name_or_path, subfolder='text_encoder') 78 text_encoder = CLIPTextModel.from_pretrained(pretrained_model_name_or_path, subfolder='text_encoder')
79 vae = AutoencoderKL.from_pretrained(pretrained_model_name_or_path, subfolder='vae') 79 vae = AutoencoderKL.from_pretrained(pretrained_model_name_or_path, subfolder='vae')
@@ -82,7 +82,7 @@ def get_models(pretrained_model_name_or_path: str, emb_alpha: float = 1.0):
82 sample_scheduler = UniPCMultistepScheduler.from_pretrained( 82 sample_scheduler = UniPCMultistepScheduler.from_pretrained(
83 pretrained_model_name_or_path, subfolder='scheduler') 83 pretrained_model_name_or_path, subfolder='scheduler')
84 84
85 embeddings = patch_managed_embeddings(text_encoder, emb_alpha) 85 embeddings = patch_managed_embeddings(text_encoder)
86 86
87 return tokenizer, text_encoder, vae, unet, noise_scheduler, sample_scheduler, embeddings 87 return tokenizer, text_encoder, vae, unet, noise_scheduler, sample_scheduler, embeddings
88 88