Failed lstm experiment

natanielruiz

2017-09-27 43416c4717d2430c3e11f042294d12b781fee2e1

 code/train.py

@@ -149,6 +149,7 @@
    softmax = nn.Softmax()
    criterion = nn.CrossEntropyLoss().cuda()
    reg_criterion = nn.MSELoss().cuda()
    smooth_l1_loss = nn.SmoothL1Loss().cuda()
    # Regression loss coefficient
    alpha = args.alpha

@@ -157,7 +158,7 @@

    optimizer = torch.optim.Adam([{'params': get_ignored_params(model), 'lr': 0},
                                  {'params': get_non_ignored_params(model), 'lr': args.lr},
                                  {'params': get_fc_params(model), 'lr': args.lr * 2}],
                                  {'params': get_fc_params(model), 'lr': args.lr * 5}],
                                   lr = args.lr)

    print 'Ready to train network.'
@@ -266,8 +267,12 @@
            loss_seq = [loss_yaw, loss_pitch, loss_roll]
            for idx in xrange(1,len(angles)):
                label_angles_residuals = label_angles - angles[0] * 3 - 99
                for idy in xrange(1,idx):
                    label_angles_residuals += angles[idy] * 3 - 99
                label_angles_residuals = label_angles_residuals.detach()
                loss_angles = reg_criterion(angles[idx], label_angles_residuals)
                # Reconvert to other unit
                label_angles_residuals = label_angles_residuals / 3.0 + 33
                loss_angles = smooth_l1_loss(angles[idx], label_angles_residuals)
                loss_seq.append(loss_angles)

            grad_seq = [torch.Tensor(1).cuda(gpu) for _ in range(len(loss_seq))]