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I ran your approach with the diffusers library pipeline for WAN T2V 14 B and received the following messages:
Warning: DiT library is not accessible. DiTCacheHelper cannot be used.
Warning: CalibrationHelper not imported.
Warning: DiffuserCalibrationHelper not imported. Ensure Diffusers is installed.
bypassing smoothcache processing. I used the code below:
if device == 'cpu': pipe.enable_model_cpu_offload() else: pipe = pipe.to(device=device) # Import SmoothCacheHelper from SmoothCache import DiffuserCacheHelper import json # Initialize the DiffuserCacheHelper with the model with open("./SmoothCache/smoothcache_schedules/diffuser_schedule.json", "r") as f: schedule = json.load(f) cache_helper = DiffuserCacheHelper(pipe.transformer, schedule=schedule) # Enable the caching helper cache_helper.enable()
Is there an alternative approach that can be used?
The text was updated successfully, but these errors were encountered:
I ran your approach with the diffusers library pipeline for WAN T2V 14 B and received the following messages:
Warning: DiT library is not accessible. DiTCacheHelper cannot be used.
Warning: CalibrationHelper not imported.
Warning: DiffuserCalibrationHelper not imported. Ensure Diffusers is installed.
bypassing smoothcache processing. I used the code below:
if device == 'cpu': pipe.enable_model_cpu_offload() else: pipe = pipe.to(device=device) # Import SmoothCacheHelper from SmoothCache import DiffuserCacheHelper import json # Initialize the DiffuserCacheHelper with the model with open("./SmoothCache/smoothcache_schedules/diffuser_schedule.json", "r") as f: schedule = json.load(f) cache_helper = DiffuserCacheHelper(pipe.transformer, schedule=schedule) # Enable the caching helper cache_helper.enable()
Is there an alternative approach that can be used?
The text was updated successfully, but these errors were encountered: