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src/diffusers/pipelines/lumina/pipeline_lumina.py

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@@ -777,7 +777,7 @@ def __call__(
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# 4. Prepare timesteps
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timesteps, num_inference_steps = retrieve_timesteps(
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self.scheduler, num_inference_steps, device, timesteps,
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self.scheduler, num_inference_steps, device, timesteps, sigmas
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)
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# 5. Prepare latents.

src/diffusers/schedulers/scheduling_flow_match_euler_discrete.py

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@@ -300,7 +300,7 @@ def step(
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sigma = self.sigmas[self.step_index]
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sigma_next = self.sigmas[self.step_index + 1]
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prev_sample = sample + (sigma_next - sigma) * model_output
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# Cast sample back to model compatible dtype

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