(base) root@autodl-container-d9d74196c3-86022e61:/autodl-tmp/GSDF# python train.py -s /root/autodl-tmp/data/qpj -m /root/autodl-tmp/data/qpj/output-gsdf --eval --position_lr_init 0.000016 --scaling_lr 0.001 --percent_dense 0.0005
0
found tf board
2025-11-12 18:16:44,164 - INFO: args: Namespace(checkpoint_iterations=[], compute_cov3D_python=False, convert_SHs_python=False, data_device='cuda', debug=False, debug_from=-1, densify_grad_threshold=0.0002, detect_anomaly=False, eval=True, feat_dim=32, feature_lr=0.0075, gpu='-1', images='images', ip='127.0.0.1', iterations=45000, lambda_dssim=0.2, lod=0, min_opacity=0.005, mlp_color_lr_delay_mult=0.01, mlp_color_lr_final=5e-05, mlp_color_lr_init=0.008, mlp_color_lr_max_steps=45000, mlp_cov_lr_delay_mult=0.01, mlp_cov_lr_final=0.004, mlp_cov_lr_init=0.004, mlp_cov_lr_max_steps=45000, mlp_featurebank_lr_delay_mult=0.01, mlp_featurebank_lr_final=1e-05, mlp_featurebank_lr_init=0.01, mlp_featurebank_lr_max_steps=45000, mlp_opacity_lr_delay_mult=0.01, mlp_opacity_lr_final=2e-05, mlp_opacity_lr_init=0.002, mlp_opacity_lr_max_steps=45000, model_path='/root/autodl-tmp/data/qpj/output-gsdf', n_offsets=10, offset_lr_delay_mult=0.01, offset_lr_final=0.0001, offset_lr_init=0.01, offset_lr_max_steps=45000, opacity_lr=0.02, percent_dense=0.0005, port=6009, position_lr_delay_mult=0.01, position_lr_final=0.0, position_lr_init=1.6e-05, position_lr_max_steps=45000, quiet=False, resolution=-1, rotation_lr=0.002, save_iterations=[30000, 45000], scaling_lr=0.001, sh_degree=3, source_path='/root/autodl-tmp/data/qpj', start_checkpoint=None, start_stat=500, success_threshold=0.8, test_iterations=[30000], update_depth=3, update_from=1500, update_hierachy_factor=4, update_init_factor=16, update_interval=100, update_until=30000, use_feat_bank=False, use_tcnn=False, use_wandb=False, voxel_size=0.001, white_background=False)
2025-11-12 18:16:44,166 - INFO: save code failed
2025-11-12 18:16:44,166 - INFO: Optimizing /root/autodl-tmp/data/qpj/output-gsdf
Output folder: /root/autodl-tmp/data/qpj/output-gsdf [12/11 18:16:44]
Reading camera 151/151 [12/11 18:16:46]
Loading Training Cameras [12/11 18:16:47]
[ INFO ] Encountered quite large input images (>1.6K pixels width), rescaling to 1.6K.
If this is not desired, please explicitly specify '--resolution/-r' as 1 [12/11 18:16:47]
Loading Test Cameras [12/11 18:16:56]
Initial voxel_size: 0.001 [12/11 18:16:58]
Number of points at initialisation : 60668 [12/11 18:16:58]
Training progress: 0%| | 0/45000 [00:00<?, ?it/s]/root/autodl-tmp/GSDF/gaussian_splatting/utils/general_utils.py:82: RuntimeWarning: divide by zero encountered in log
log_lerp = np.exp(np.log(lr_init) * (1 - t) + np.log(lr_final) * t)
Traceback (most recent call last):
File "train.py", line 525, in
training(lp.extract(args), op.extract(args), pp.extract(args), dataset, args.test_iterations, args.save_iterations, args.checkpoint_iterations, args.start_checkpoint, args.debug_from, wandb, logger)
File "train.py", line 146, in training
voxel_visible_mask = prefilter_voxel(viewpoint_cam, gaussians, pipe,background)
File "/root/autodl-tmp/GSDF/gaussian_splatting/gaussian_renderer/init.py", line 261, in prefilter_voxel
radii_pure = rasterizer.visible_filter(means3D = means3D,
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1614, in getattr
raise AttributeError("'{}' object has no attribute '{}'".format(
AttributeError: 'GaussianRasterizer' object has no attribute 'visible_filter'
Training progress: 0%| | 0/45000 [00:00<?, ?it/s]
(base) root@autodl-container-d9d74196c3-86022e61:
/autodl-tmp/GSDF# python train.py -s /root/autodl-tmp/data/qpj -m /root/autodl-tmp/data/qpj/output-gsdf --eval --position_lr_init 0.000016 --scaling_lr 0.001 --percent_dense 0.00050
found tf board
2025-11-12 18:16:44,164 - INFO: args: Namespace(checkpoint_iterations=[], compute_cov3D_python=False, convert_SHs_python=False, data_device='cuda', debug=False, debug_from=-1, densify_grad_threshold=0.0002, detect_anomaly=False, eval=True, feat_dim=32, feature_lr=0.0075, gpu='-1', images='images', ip='127.0.0.1', iterations=45000, lambda_dssim=0.2, lod=0, min_opacity=0.005, mlp_color_lr_delay_mult=0.01, mlp_color_lr_final=5e-05, mlp_color_lr_init=0.008, mlp_color_lr_max_steps=45000, mlp_cov_lr_delay_mult=0.01, mlp_cov_lr_final=0.004, mlp_cov_lr_init=0.004, mlp_cov_lr_max_steps=45000, mlp_featurebank_lr_delay_mult=0.01, mlp_featurebank_lr_final=1e-05, mlp_featurebank_lr_init=0.01, mlp_featurebank_lr_max_steps=45000, mlp_opacity_lr_delay_mult=0.01, mlp_opacity_lr_final=2e-05, mlp_opacity_lr_init=0.002, mlp_opacity_lr_max_steps=45000, model_path='/root/autodl-tmp/data/qpj/output-gsdf', n_offsets=10, offset_lr_delay_mult=0.01, offset_lr_final=0.0001, offset_lr_init=0.01, offset_lr_max_steps=45000, opacity_lr=0.02, percent_dense=0.0005, port=6009, position_lr_delay_mult=0.01, position_lr_final=0.0, position_lr_init=1.6e-05, position_lr_max_steps=45000, quiet=False, resolution=-1, rotation_lr=0.002, save_iterations=[30000, 45000], scaling_lr=0.001, sh_degree=3, source_path='/root/autodl-tmp/data/qpj', start_checkpoint=None, start_stat=500, success_threshold=0.8, test_iterations=[30000], update_depth=3, update_from=1500, update_hierachy_factor=4, update_init_factor=16, update_interval=100, update_until=30000, use_feat_bank=False, use_tcnn=False, use_wandb=False, voxel_size=0.001, white_background=False)
2025-11-12 18:16:44,166 - INFO: save code failed
2025-11-12 18:16:44,166 - INFO: Optimizing /root/autodl-tmp/data/qpj/output-gsdf
Output folder: /root/autodl-tmp/data/qpj/output-gsdf [12/11 18:16:44]
Reading camera 151/151 [12/11 18:16:46]
Loading Training Cameras [12/11 18:16:47]
[ INFO ] Encountered quite large input images (>1.6K pixels width), rescaling to 1.6K.
If this is not desired, please explicitly specify '--resolution/-r' as 1 [12/11 18:16:47]
Loading Test Cameras [12/11 18:16:56]
Initial voxel_size: 0.001 [12/11 18:16:58]
Number of points at initialisation : 60668 [12/11 18:16:58]
Training progress: 0%| | 0/45000 [00:00<?, ?it/s]/root/autodl-tmp/GSDF/gaussian_splatting/utils/general_utils.py:82: RuntimeWarning: divide by zero encountered in log
log_lerp = np.exp(np.log(lr_init) * (1 - t) + np.log(lr_final) * t)
Traceback (most recent call last):
File "train.py", line 525, in
training(lp.extract(args), op.extract(args), pp.extract(args), dataset, args.test_iterations, args.save_iterations, args.checkpoint_iterations, args.start_checkpoint, args.debug_from, wandb, logger)
File "train.py", line 146, in training
voxel_visible_mask = prefilter_voxel(viewpoint_cam, gaussians, pipe,background)
File "/root/autodl-tmp/GSDF/gaussian_splatting/gaussian_renderer/init.py", line 261, in prefilter_voxel
radii_pure = rasterizer.visible_filter(means3D = means3D,
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1614, in getattr
raise AttributeError("'{}' object has no attribute '{}'".format(
AttributeError: 'GaussianRasterizer' object has no attribute 'visible_filter'
Training progress: 0%| | 0/45000 [00:00<?, ?it/s]