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[NPU] Support Helios-Mid / Distilled (#1648)

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Canlin Guo authored and GitHub committed 2026-03-08 17:24:25 +08:00
1 parent b255654a76
commit c3a59f10f3
1 file changed
+5 -4
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vllm_omni/diffusion/models/helios/scheduling_helios.py
+5 -4
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@@ -78,7 +78,7 @@ class HeliosScheduler(SchedulerMixin, ConfigMixin):
num_train_timesteps = self.config.num_train_timesteps
shift = self.config.shift
alphas = np.linspace(1, 1 / num_train_timesteps, num_train_timesteps + 1)
alphas = np.linspace(1, 1 / num_train_timesteps, num_train_timesteps + 1, dtype=np.float32)
sigmas = 1.0 - alphas
sigmas = np.flip(shift * sigmas / (1 + (shift - 1) * sigmas))[:-1].copy()
sigmas = torch.from_numpy(sigmas)
@@ -133,11 +133,11 @@ class HeliosScheduler(SchedulerMixin, ConfigMixin):
timestep_ratio = self.timestep_ratios[i_s]
timestep_max = min(self.timesteps[int(timestep_ratio[0] * training_steps)], 999)
timestep_min = self.timesteps[min(int(timestep_ratio[1] * training_steps), training_steps - 1)]
timesteps = np.linspace(timestep_max, timestep_min, training_steps + 1)
timesteps = np.linspace(timestep_max, timestep_min, training_steps + 1, dtype=np.float32)
self.timesteps_per_stage[i_s] = (
timesteps[:-1] if isinstance(timesteps, torch.Tensor) else torch.from_numpy(timesteps[:-1])
)
stage_sigmas = np.linspace(0.999, 0, training_steps + 1)
stage_sigmas = np.linspace(0.999, 0, training_steps + 1, dtype=np.float32)
self.sigmas_per_stage[i_s] = torch.from_numpy(stage_sigmas[:-1])
@property
@@ -188,10 +188,11 @@ class HeliosScheduler(SchedulerMixin, ConfigMixin):
stage_timesteps[0].item(),
stage_timesteps[-1].item(),
num_inference_steps,
dtype=np.float32,
)
stage_sigmas = self.sigmas_per_stage[stage_index]
ratios = np.linspace(stage_sigmas[0].item(), stage_sigmas[-1].item(), num_inference_steps)
ratios = np.linspace(stage_sigmas[0].item(), stage_sigmas[-1].item(), num_inference_steps, dtype=np.float32)
sigmas = torch.from_numpy(ratios)
self.timesteps = torch.from_numpy(timesteps).to(device=device)