use this to replace https://github.com/real-stanford/diffusion_policy/blob/main/diffusion_policy/policy/diffusion_unet_hybrid_image_policy.py we find beta(0.5, 0.5) sampling and loss reweighting(more noisy, more weight on gt, verse visa) can beat trigflow/flow matching/diffusion in only one step.
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Use two head: one to predict x_real another predcit x_noise, with the mixup as input. A simplified version of trigflow
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