Update app_fast.py

app_fast.py

@@ -2,7 +2,7 @@ import spaces
 import torch
 from diffusers import AutoencoderKLWan, WanPipeline, WanImageToVideoPipeline, UniPCMultistepScheduler
 from diffusers.utils import export_to_video
-from diffusers.hooks import apply_first_block_cache, FirstBlockCacheConfig
+#from diffusers.hooks import apply_first_block_cache, FirstBlockCacheConfig
 import gradio as gr
 import tempfile
 from huggingface_hub import hf_hub_download
@@ -12,19 +12,21 @@ import random
 
 MODEL_ID = "FastVideo/FastWan2.2-TI2V-5B-FullAttn-Diffusers"
 vae = AutoencoderKLWan.from_pretrained(MODEL_ID, subfolder="vae", torch_dtype=torch.float32)
-#vae = AutoencoderKLWan.from_pretrained("Kijai/WanVideo_comfy", filename="Wan2_2_VAE_bf16.safetensors", torch_dtype=torch.bfloat16)
 
 # Initialize pipelines
 text_to_video_pipe = WanPipeline.from_pretrained(MODEL_ID, vae=vae, torch_dtype=torch.bfloat16)
 image_to_video_pipe = WanImageToVideoPipeline.from_pretrained(MODEL_ID, vae=vae, torch_dtype=torch.bfloat16)
 
-#apply_first_block_cache(pipe.transformer, FirstBlockCacheConfig(threshold=0.2))
 
 for pipe in [text_to_video_pipe, image_to_video_pipe]:
     pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config, flow_shift=5.0)
     pipe.to("cuda")    
+    
 ##Lora testing
+#vae = AutoencoderKLWan.from_pretrained("Kijai/WanVideo_comfy", filename="Wan2_2_VAE_bf16.safetensors", torch_dtype=torch.bfloat16)
 # LORA_REPO_ID = "JERRYNPC/WAN2.2-LORA-NSFW"
+#apply_first_block_cache(pipe.transformer, FirstBlockCacheConfig(threshold=0.2))
+
 # LORA_FILENAME= "jerry_HIGH-nsfw-V10E800.safetensors"
 
 # causvid_path = hf_hub_download(repo_id=LORA_REPO_ID, filename=LORA_FILENAME)