xinyun/ComfyUI-CogVideoXWrapper
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possibly fix for diffusers 0.31.0

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This commit is contained in:
Jukka Seppänen 2024-10-22 22:12:49 +03:00
parent 2cc521062f
commit 5a024a0973
1 changed files with 20 additions and 5 deletions
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25
nodes.py
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@ -953,7 +953,10 @@ class CogVideoImageEncode:
vae.to(device) vae.to(device)
check_diffusers_version() check_diffusers_version()
vae._clear_fake_context_parallel_cache() try:
vae._clear_fake_context_parallel_cache()
except:
pass
input_image = image.clone() input_image = image.clone()
if mask is not None: if mask is not None:
@ -1038,7 +1041,10 @@ class CogVideoImageInterpolationEncode:
vae.to(device) vae.to(device)
check_diffusers_version() check_diffusers_version()
vae._clear_fake_context_parallel_cache() try:
vae._clear_fake_context_parallel_cache()
except:
pass
if mask is not None: if mask is not None:
pipeline["pipe"].original_mask = mask pipeline["pipe"].original_mask = mask
@ -1104,7 +1110,10 @@ class ToraEncodeTrajectory:
vae = pipeline["pipe"].vae vae = pipeline["pipe"].vae
vae.enable_slicing() vae.enable_slicing()
vae._clear_fake_context_parallel_cache() try:
vae._clear_fake_context_parallel_cache()
except:
pass
if len(coordinates) < 10: if len(coordinates) < 10:
coords_list = [] coords_list = []
@ -1185,7 +1194,10 @@ class ToraEncodeOpticalFlow:
vae = pipeline["pipe"].vae vae = pipeline["pipe"].vae
vae.enable_slicing() vae.enable_slicing()
vae._clear_fake_context_parallel_cache() try:
vae._clear_fake_context_parallel_cache()
except:
pass
video_flow = optical_flow * 2 - 1 video_flow = optical_flow * 2 - 1
video_flow = rearrange(video_flow, "(B T) H W C -> B C T H W", T=B, B=1) video_flow = rearrange(video_flow, "(B T) H W C -> B C T H W", T=B, B=1)
@ -1369,7 +1381,10 @@ class CogVideoDecode:
latents = latents.to(vae.dtype) latents = latents.to(vae.dtype)
latents = latents.permute(0, 2, 1, 3, 4) # [batch_size, num_channels, num_frames, height, width] latents = latents.permute(0, 2, 1, 3, 4) # [batch_size, num_channels, num_frames, height, width]
latents = 1 / vae.config.scaling_factor * latents latents = 1 / vae.config.scaling_factor * latents
vae._clear_fake_context_parallel_cache() try:
vae._clear_fake_context_parallel_cache()
except:
pass
frames = vae.decode(latents).sample frames = vae.decode(latents).sample
vae.disable_tiling() vae.disable_tiling()
if not pipeline["cpu_offloading"]: if not pipeline["cpu_offloading"]: