xinyun/ComfyUI-CogVideoXWrapper
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Update nodes.py

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kijai 2024-10-22 15:34:42 +03:00
parent 45c3f06d0a
commit 15bf8f51ab
1 changed files with 5 additions and 14 deletions
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nodes.py
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@ -1104,16 +1104,7 @@ class ToraEncodeTrajectory:
vae = pipeline["pipe"].vae
vae.enable_slicing()
vae._clear_fake_context_parallel_cache()
#get coordinates from string and convert to compatible range/format (has to be 256x256 for the model)
# coordinates = json.loads(coordinates.replace("'", '"'))
# coordinates = [(coord['x'], coord['y']) for coord in coordinates]
# traj_list_range_256 = scale_traj_list_to_256(coordinates, width, height)
print(f"Type of coordinates: {type(coordinates)}")
print(f"Structure of coordinates: {coordinates}")
print(len(coordinates))
vae._clear_fake_context_parallel_cache()
if len(coordinates) < 10:
coords_list = []
@ -1301,7 +1292,7 @@ class CogVideoSampler:
padding = torch.zeros((negative.shape[0], target_length - negative.shape[1], negative.shape[2]), device=negative.device)
negative = torch.cat((negative, padding), dim=1)
autocastcondition = not pipeline["onediff"]
autocastcondition = not pipeline["onediff"] or not dtype == torch.float32
autocast_context = torch.autocast(mm.get_autocast_device(device)) if autocastcondition else nullcontext()
with autocast_context:
latents = pipeline["pipe"](
@ -1471,7 +1462,7 @@ class CogVideoXFunSampler:
generator = torch.Generator(device=torch.device("cpu")).manual_seed(seed)
autocastcondition = not pipeline["onediff"]
autocastcondition = not pipeline["onediff"] or not dtype == torch.float32
autocast_context = torch.autocast(mm.get_autocast_device(device)) if autocastcondition else nullcontext()
with autocast_context:
video_length = int((video_length - 1) // pipe.vae.config.temporal_compression_ratio * pipe.vae.config.temporal_compression_ratio) + 1 if video_length != 1 else 1
@ -1566,7 +1557,7 @@ class CogVideoXFunVid2VidSampler:
generator = torch.Generator(device=torch.device("cpu")).manual_seed(seed)
autocastcondition = not pipeline["onediff"]
autocastcondition = not pipeline["onediff"] or not dtype == torch.float32
autocast_context = torch.autocast(mm.get_autocast_device(device)) if autocastcondition else nullcontext()
with autocast_context:
video_length = int((video_length - 1) // pipe.vae.config.temporal_compression_ratio * pipe.vae.config.temporal_compression_ratio) + 1 if video_length != 1 else 1
@ -1813,7 +1804,7 @@ class CogVideoXFunControlSampler:
generator = torch.Generator(device=torch.device("cpu")).manual_seed(seed)
autocastcondition = not pipeline["onediff"]
autocastcondition = not pipeline["onediff"] or not dtype == torch.float32
autocast_context = torch.autocast(mm.get_autocast_device(device)) if autocastcondition else nullcontext()
with autocast_context: