Train error: 'Trainer' object has no attribute 'rgb_weight'

[summerlisa]

Command: CUDA_VISIBLE_DEVICES=0 python train.py configs/LLFF/fern.yaml Get error log: Traceback (most recent call last): File "train.py", line 362, in <module> train(cfg=cfg) File "train.py", line 208, in train loss_dict = trainer.train_step(batch, it, epoch_it, scheduling_start, render_path) File "/raid/xiayuwei/code/nope-nerf/model/training.py", line 79, in train_step loss_dict = self.compute_loss(data, it=it, epoch=epoch, scheduling_start=scheduling_start, out_render_path=render_path) File "/raid/xiayuwei/code/nope-nerf/model/training.py", line 201, in compute_loss weights_list = [self.anneal(getattr(self, w)[0], getattr(self, w)[1], scheduling_start, self.annealing_epochs, epoch) for w in weights_name_list] # loss weights File "/raid/xiayuwei/code/nope-nerf/model/training.py", line 201, in <listcomp> weights_list = [self.anneal(getattr(self, w)[0], getattr(self, w)[1], scheduling_start, self.annealing_epochs, epoch) for w in weights_name_list] # loss weights AttributeError: 'Trainer' object has no attribute 'rgb_weight'

[guanjunwu]

I got same problem. Any solutions?

[guanjunwu]

I got same problem. Any solutions?

I found that I can solve it if only change the code of Class Trainer by:

class Trainer(object):
    def __init__(self, model, optimizer, cfg, device=None, optimizer_pose=None, pose_param_net=None, 
                    optimizer_focal=None, focal_net=None, optimizer_distortion=None,distortion_net=None, **kwargs):
        """model trainer

        Args:
            model (nn.Module): model
            optimizer (optimizer):pytorch optimizer object
            cfg (dict): config argument options
            device (device): Pytorch device option. Defaults to None.
            optimizer_pose (optimizer, optional): pytorch optimizer for poses. Defaults to None.
            pose_param_net (nn.Module, optional): model with pose parameters. Defaults to None.
            optimizer_focal (optimizer, optional): pytorch optimizer for focal. Defaults to None.
            focal_net (nn.Module, optional): model with focal parameters. Defaults to None.
            optimizer_distortion (optimizer, optional): pytorch optimizer for depth distortion. Defaults to None.
            distortion_net (nn.Module, optional): model with distortion parameters. Defaults to None.
        """
        self.model = model
        self.optimizer = optimizer
        self.device = device
        self.optimizer_pose = optimizer_pose
        self.pose_param_net = pose_param_net
        self.focal_net = focal_net
        self.optimizer_focal = optimizer_focal
        self.distortion_net = distortion_net
        self.optimizer_distortion = optimizer_distortion

        self.n_training_points = cfg['n_training_points']
        self.rendering_technique = cfg['type']
        self.vis_geo = cfg['vis_geo']

        self.detach_gt_depth = cfg['detach_gt_depth']
        self.pc_ratio = cfg['pc_ratio']
        self.match_method = cfg['match_method']
        self.shift_first = cfg['shift_first']
        self.detach_ref_img = cfg['detach_ref_img']
        self.scale_pcs = cfg['scale_pcs']
        self.detach_rgbs_scale = cfg['detach_rgbs_scale']
        self.vis_reprojection_every = cfg['vis_reprojection_every']
        self.nearest_limit = cfg['nearest_limit']
        self.annealing_epochs = cfg['annealing_epochs']
        # add weight there
        self.rgb_weight = cfg['rgb_weight'] 
        self.depth_weight = cfg['depth_weight']
        self.pc_weight = cfg['pc_weight']
        self.rgb_s_weight=cfg['rgb_s_weight']
        self.depth_consistency_weight = cfg['depth_consistency_weight']
        self.weight_dist_2nd_loss = cfg['weight_dist_2nd_loss']
        self.weight_dist_1st_loss = cfg['weight_dist_1st_loss']

then the program execute successfully

[bianwenjing]

Apologise for this bug. It has now been fixed.