storytold/FineTrainers-Conditioning
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Moved the norm back to prepare latents step.

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Now its time to add the adapter layer.
This commit is contained in:
CrossProduct
2025-01-18 04:18:25 +00:00
parent 44df9e3bce
commit 2720d24f62
3 changed files with 4 additions and 16 deletions
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finetrainers/conditioning/condition_latents_prepare.py
+1 -4
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@@ -40,8 +40,6 @@ def _pack_latents(latents: torch.Tensor, patch_size: int = 1, patch_size_t: int
def post_conditioned_latent_patchify(
latents: torch.Tensor,
latents_mean: torch.Tensor,
latents_std: torch.Tensor,
num_frames: int,
height: int,
width: int,
@@ -49,7 +47,6 @@ def post_conditioned_latent_patchify(
patch_size_t: int = 1,
**kwargs,
) -> torch.Tensor:
latents = _normalize_latents(latents, latents_mean, latents_std)
latents = _pack_latents(latents, patch_size, patch_size_t)
return {"latents": latents, "num_frames": num_frames, "height": height, "width": width}
@@ -76,7 +73,7 @@ def prepare_latents_for_conditioning(
latents = latents.to(dtype=dtype)
_, _, num_frames, height, width = latents.shape
# latents = _normalize_latents(latents, vae.latents_mean, vae.latents_std)
latents = _normalize_latents(latents, vae.latents_mean, vae.latents_std)
# latents = _pack_latents(latents, patch_size, patch_size_t)
return {"latents": latents,
"num_frames": num_frames,