storytold/FineTrainers-Conditioning
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Ok adapter trains need to get the pass for validation using a skeleton.

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This commit is contained in:
CrossProduct
2025-01-22 22:07:52 +00:00
parent d631737329
commit d6b3615421
1 changed files with 11 additions and 9 deletions
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finetrainers/trainer.py
+11 -9
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@@ -825,15 +825,8 @@ class Trainer:
width=latent_conditions["width"],
patch_size = 1,
patch_size_t = 1)
# target
latent_conditions["latents"] = post_conditioned_latent_patchify(
latents=latent_conditions["latents"],
num_frames=latent_conditions["num_frames"],
height=latent_conditions["height"],
width=latent_conditions["width"],
patch_size = 1,
patch_size_t = 1
)
# target latent patchified
# pose information latent
latent_conditions.update({"noisy_latents": latent_final["latents"]})
latent_conditions.update({"noisy_latents_residual":noisy_latents_residual["latents"]})
@@ -875,6 +868,15 @@ class Trainer:
scheduler=self.scheduler, noise=noise, latents=latent_conditions["latents"]
)
if self.pose_condition:
# patchify target
target = post_conditioned_latent_patchify(latents=target,
num_frames=latent_conditions["num_frames"],
height=latent_conditions["height"],
width=latent_conditions["width"],
patch_size = 1,
patch_size_t = 1)["latents"]
loss = weights.float() * (pred["latents"].float() - target.float()).pow(2)
# Average loss across all but batch dimension
loss = loss.mean(list(range(1, loss.ndim)))