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Allow refiner to be triggered by model timestep instead of sampling
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@ -156,7 +156,16 @@ replace_torchsde_browinan()
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def apply_refiner(cfg_denoiser):
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if opts.refiner_switch_by_sample_steps:
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completed_ratio = cfg_denoiser.step / cfg_denoiser.total_steps
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else:
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# torch.max(sigma) only to handle rare case where we might have different sigmas in the same batch
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try:
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timestep = torch.argmin(torch.abs(cfg_denoiser.inner_model.sigmas - torch.max(sigma)))
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except AttributeError: # for samplers that dont use sigmas (DDIM) sigma is actually the timestep
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timestep = torch.max(sigma).to(dtype=int)
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completed_ratio = (999 - timestep) / 1000
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refiner_switch_at = cfg_denoiser.p.refiner_switch_at
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refiner_checkpoint_info = cfg_denoiser.p.refiner_checkpoint_info
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