nodes/kijai-ComfyUI-WanVideoWrapper
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handle I2V a bit for contexting

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kijai
2025-03-02 20:09:23 +02:00
parent bd31044ef5
commit 8e0a90f1a4
1 changed files with 11 additions and 5 deletions
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nodes.py
+11 -5
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@@ -1148,11 +1148,7 @@ class WanVideoSampler:
'device': device,
'freqs': freqs,
}
if transformer.model_type == "i2v":
args.update({
'y': [image_embeds["image_embeds"].to(device)],
})
pbar = ProgressBar(steps)
from latent_preview import prepare_callback
@@ -1269,10 +1265,17 @@ class WanVideoSampler:
# Use the appropriate prompt for this section
positive_prompt = text_embeds["prompt_embeds"][prompt_index]
img_emb = image_embeds.get("image_embeds", None)
if img_emb is not None:
print("img_emb shape", img_emb.shape)
partial_img_emb = img_emb[:, c, :, :]
partial_img_emb[:, 0, :, :] = img_emb[:, 0, :, :].to(intermediate_device)
partial_latent_model_input = [latent_model_input[0][:, c, :, :]]
# Model inference - returns [frames, channels, height, width]
noise_pred_cond = transformer(
partial_latent_model_input,
y=[partial_img_emb],
t=timestep,
current_step=i,
is_uncond=False,
@@ -1282,6 +1285,7 @@ class WanVideoSampler:
if cfg[i] != 1.0:
noise_pred_uncond = transformer(
partial_latent_model_input,
y=[partial_img_emb],
t=timestep,
current_step=i,
is_uncond=True,
@@ -1318,12 +1322,14 @@ class WanVideoSampler:
t=timestep,
current_step=i,
is_uncond=False,
y=[image_embeds.get("image_embeds", None)],
context = [text_embeds["prompt_embeds"][0]],
**args
)[0].to(intermediate_device)
if cfg[i] != 1.0:
noise_pred_uncond = transformer(
latent_model_input,
y=[image_embeds.get("image_embeds", None)],
t=timestep,
current_step=i,
is_uncond=True,