DualFlow/models/uf-rl/超滤训练源码/UF_models.py

import torch
import numpy as np

# TMP 上升量模型
class TMPIncreaseModel(torch.nn.Module):
    def __init__(self):
        super().__init__()
    def forward(self, p, L_h):
        return float(p.alpha * (p.q_UF ** p.belta) * L_h)

# 反洗 TMP 去除模型
class TMPDecreaseModel(torch.nn.Module):
    def __init__(self):
        super().__init__()
    def forward(self, p, L_s, t_bw_s):
        L = max(float(L_s), 1.0)
        t = max(float(t_bw_s), 1e-6)
        upper_L = p.phi_bw_min + (p.phi_bw_max - p.phi_bw_min) * np.exp(- L / p.L_ref_s)
        time_gain = 1.0 - np.exp(- (t / p.tau_bw_s) ** p.gamma_t)
        phi = upper_L * time_gain
        return float(np.clip(phi, 0.0, 0.999))


if __name__ == "__main__":
    model_fp = TMPIncreaseModel()
    model_bw = TMPDecreaseModel()


    torch.save(model_fp.state_dict(), "uf_fp.pth")
    torch.save(model_bw.state_dict(), "uf_bw.pth")


    print("模型已安全保存为 uf_fp.pth、uf_bw.pth")