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Added training for Wan2.1. Not finalized, wait.
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@@ -310,6 +310,8 @@ class BaseSDTrainProcess(BaseTrainProcess):
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refiner_start_at=sample_config.refiner_start_at,
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extra_values=sample_config.extra_values,
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logger=self.logger,
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num_frames=sample_config.num_frames,
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fps=sample_config.fps,
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**extra_args
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))
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@@ -909,13 +911,16 @@ class BaseSDTrainProcess(BaseTrainProcess):
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raise ValueError("Batch must be provided for consistent noise")
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noise = self.get_consistent_noise(latents, batch, dtype=dtype)
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else:
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# get noise
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noise = self.sd.get_latent_noise(
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height=latents.shape[2],
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width=latents.shape[3],
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batch_size=batch_size,
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noise_offset=self.train_config.noise_offset,
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).to(self.device_torch, dtype=dtype)
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if hasattr(self.sd, 'get_latent_noise_from_latents'):
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noise = self.sd.get_latent_noise_from_latents(latents).to(self.device_torch, dtype=dtype)
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else:
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# get noise
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noise = self.sd.get_latent_noise(
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height=latents.shape[2],
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width=latents.shape[3],
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batch_size=batch_size,
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noise_offset=self.train_config.noise_offset,
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).to(self.device_torch, dtype=dtype)
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if self.train_config.random_noise_shift > 0.0:
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# get random noise -1 to 1
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@@ -929,9 +934,10 @@ class BaseSDTrainProcess(BaseTrainProcess):
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noise += noise_shift
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# standardize the noise
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std = noise.std(dim=(2, 3), keepdim=True)
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normalizer = 1 / (std + 1e-6)
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noise = noise * normalizer
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# shouldnt be needed?
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# std = noise.std(dim=(2, 3), keepdim=True)
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# normalizer = 1 / (std + 1e-6)
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# noise = noise * normalizer
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return noise
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