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@@ -3,8 +3,8 @@ import torch
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def FlowMatchSFTLoss(pipe: BasePipeline, **inputs):
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max_timestep_boundary = int(inputs.get("max_timestep_boundary", 1) * pipe.scheduler.num_train_timesteps)
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min_timestep_boundary = int(inputs.get("min_timestep_boundary", 0) * pipe.scheduler.num_train_timesteps)
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max_timestep_boundary = int(inputs.get("max_timestep_boundary", 1) * len(pipe.scheduler.timesteps))
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min_timestep_boundary = int(inputs.get("min_timestep_boundary", 0) * len(pipe.scheduler.timesteps))
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timestep_id = torch.randint(min_timestep_boundary, max_timestep_boundary, (1,))
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timestep = pipe.scheduler.timesteps[timestep_id].to(dtype=pipe.torch_dtype, device=pipe.device)
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