ModuFlow/mask-ddpm
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update ks

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MingzheYang
2026-01-25 18:00:28 +08:00
parent cc10125fbf
commit 2a1a9a05c6
1 changed files with 7 additions and 2 deletions
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9
example/train.py
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@@ -293,12 +293,17 @@ def main():
if q_weight > 0: if q_weight > 0:
q_points = config.get("quantile_points", [0.05, 0.25, 0.5, 0.75, 0.95]) q_points = config.get("quantile_points", [0.05, 0.25, 0.5, 0.75, 0.95])
q_tensor = torch.tensor(q_points, device=device, dtype=x_cont.dtype) q_tensor = torch.tensor(q_points, device=device, dtype=x_cont.dtype)
# Use normalized space for stable quantiles. # Use normalized space for stable quantiles on x0.
x_real = x_cont x_real = x_cont
a_bar_t = alphas_cumprod[t].view(-1, 1, 1)
if cont_target == "x0": if cont_target == "x0":
x_gen = eps_pred x_gen = eps_pred
elif cont_target == "v":
v_pred = eps_pred
x_gen = torch.sqrt(a_bar_t) * x_cont_t - torch.sqrt(1.0 - a_bar_t) * v_pred
else: else:
x_gen = x_cont - noise # eps prediction
x_gen = (x_cont_t - torch.sqrt(1.0 - a_bar_t) * eps_pred) / torch.sqrt(a_bar_t)
x_real = x_real.view(-1, x_real.size(-1)) x_real = x_real.view(-1, x_real.size(-1))
x_gen = x_gen.view(-1, x_gen.size(-1)) x_gen = x_gen.view(-1, x_gen.size(-1))
q_real = torch.quantile(x_real, q_tensor, dim=0) q_real = torch.quantile(x_real, q_tensor, dim=0)