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Initial work for training wan first and last frame

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This commit is contained in:
Jaret Burkett
2025-08-04 11:37:26 -06:00
parent ef1d60ba34
commit 9dfb614755
1 changed files with 13 additions and 1 deletions
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14
toolkit/models/wan21/wan_utils.py
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@@ -116,7 +116,8 @@ def add_first_frame_conditioning(
def add_first_frame_conditioning_v22(
latent_model_input,
first_frame,
vae
vae,
last_frame=None
):
"""
Overwrites first few time steps in latent_model_input with VAE-encoded first_frame,
@@ -161,5 +162,16 @@ def add_first_frame_conditioning_v22(
# Mask: 0 where conditioned, 1 otherwise
mask = torch.ones(bs, 1, T, H, W, device=device, dtype=dtype)
mask[:, :, :encoded.shape[2]] = 0.0
if last_frame is not None:
# If last_frame is provided, encode it similarly
last_frame_up = F.interpolate(last_frame, size=(target_h, target_w), mode="bilinear", align_corners=False)
last_frame_up = last_frame_up.unsqueeze(2)
last_encoded = vae.encode(last_frame_up).latent_dist.sample().to(dtype).to(device)
last_encoded = (last_encoded - mean) * std
latent[:, :, -last_encoded.shape[2]:] = last_encoded # replace last
mask[:, :, -last_encoded.shape[2]:] = 0.0 #
# Ensure mask is still binary
mask = mask.clamp(0.0, 1.0)
return latent, mask