Update app.py

app.py

@@ -7,7 +7,7 @@ import tempfile
 import numpy as np
 import cv2
 import subprocess
-
+from DeepCache import DeepCacheSDHelper
 from diffusers import AnimateDiffPipeline, MotionAdapter, EulerDiscreteScheduler
 from huggingface_hub import hf_hub_download
 from safetensors.torch import load_file
@@ -34,6 +34,22 @@ dtype = torch.float16
 pipe = AnimateDiffPipeline.from_pretrained(bases[base_loaded], torch_dtype=dtype).to(device)
 pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing", beta_schedule="linear")
 
+
+# Note Julian: I'm not sure this works well when the pipeline changes dynamically.. to check
+helper = DeepCacheSDHelper(pipe=pipe)
+helper.set_params(
+    # cache_interval means the frequency of feature caching, specified as the number of steps between each cache operation.
+    
+    cache_interval=3,
+
+    # cache_branch_id identifies which branch of the network (ordered from the shallowest to the deepest layer) is responsible for executing the caching processes. 
+    cache_branch_id=0,
+
+    # Opting for a lower cache_branch_id or a larger cache_interval can lead to faster inference speed at the expense of reduced image quality
+    #(ablation experiments of these two hyperparameters can be found in the paper).
+)
+helper.enable()
+
 # ----------------------------- VIDEO ENCODING ---------------------------------
 # Unfortunately, the Hugging Face Diffusers utils hardcode MP4V as a codec,
 # which is not supported by all browsers. This is a critical issue for AiTube,