From a2d7251d899f02b317252e265cc17d5ec1bf074e Mon Sep 17 00:00:00 2001 From: Limitex <76650151+Limitex@users.noreply.github.com> Date: Mon, 1 Jan 2024 14:42:26 +0900 Subject: [PATCH] Unified autoencoder loading --- nodes.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/nodes.py b/nodes.py index d27e666..6d5fae7 100644 --- a/nodes.py +++ b/nodes.py @@ -280,7 +280,6 @@ class StreamDiffusionCreateStream: return { "required": { "maked_pipeline": ("MAKED_PIPELINE", ), - "autoencoder": ("AUTOENCODER", ), "t_index_list": ("LIST", ), "width": ("INT", {"default": 512, "min": 1, "max": 8192, "step": 1}), "height": ("INT", {"default": 512, "min": 1, "max": 8192, "step": 1}), @@ -298,7 +297,7 @@ class StreamDiffusionCreateStream: CATEGORY = "Diffusers/StreamDiffusion" - def load_stream(self, maked_pipeline, autoencoder, t_index_list, width, height, do_add_noise, use_denoising_batch, frame_buffer_size, cfg_type, xformers_memory_efficient_attention, lcm_lora): + def load_stream(self, maked_pipeline, t_index_list, width, height, do_add_noise, use_denoising_batch, frame_buffer_size, cfg_type, xformers_memory_efficient_attention, lcm_lora): maked_pipeline = copy.deepcopy(maked_pipeline) stream = StreamDiffusion( pipe = maked_pipeline, @@ -313,7 +312,7 @@ class StreamDiffusionCreateStream: ) stream.load_lcm_lora(lcm_lora) stream.fuse_lora() - stream.vae = autoencoder.to(self.torch_device) + stream.vae = maked_pipeline.vae.to(self.torch_device) if xformers_memory_efficient_attention: maked_pipeline.enable_xformers_memory_efficient_attention()