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I am trying to run SplaTAM on a dataset that i've collected offline using the method from #59. After doing the necessary processing I run $ python scripts/splatam.py configs/iphone/splatam.py
resulting in the folllowing error log
Selected Keyframes at Frame 0: [0]
Tracking Result Time Step: 0: 0%| | 0/1 [00:00<?, ?it/s]
0%| | 0/10 [00:00<?, ?it/s]
Traceback (most recent call last): | 0/60 [00:00<?, ?it/s]
File "/zhome/75/8/168142/Desktop/Bachelorprojekt/SplaTAM/scripts/splatam.py", line 1007, in
rgbd_slam(experiment.config)
File "/zhome/75/8/168142/Desktop/Bachelorprojekt/SplaTAM/scripts/splatam.py", line 840, in rgbd_slam
loss, variables, losses = get_loss(params, iter_data, variables, iter_time_idx, config['mapping']['loss_weights'],
File "/zhome/75/8/168142/Desktop/Bachelorprojekt/SplaTAM/scripts/splatam.py", line 253, in get_loss
im, radius, _, = Renderer(raster_settings=curr_data['cam'])(**rendervar)
File "/zhome/75/8/168142/miniconda3/envs/splatam/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/zhome/75/8/168142/miniconda3/envs/splatam/lib/python3.10/site-packages/diff_gaussian_rasterization/init.py", line 186, in forward
return rasterize_gaussians(
File "/zhome/75/8/168142/miniconda3/envs/splatam/lib/python3.10/site-packages/diff_gaussian_rasterization/init.py", line 28, in rasterize_gaussians
return _RasterizeGaussians.apply(
File "/zhome/75/8/168142/miniconda3/envs/splatam/lib/python3.10/site-packages/diff_gaussian_rasterization/init.py", line 79, in forward
num_rendered, color, radii, geomBuffer, binningBuffer, imgBuffer, depth = _C.rasterize_gaussians(*args)
RuntimeError: CUDA out of memory. Tried to allocate 131065.38 GiB (GPU 0; 39.39 GiB total capacity; 79.66 MiB already allocated; 38.00 GiB free; 96.00 MiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
Mapping Time Step: 0: 0%| | 0/60 [00:00<?, ?it/s]
As I understand from the runtime error, the program is trying to allocate 131065 gigabyte of memory on the GPU. This seems a bit crazy, since no GPU's have that kind of memory? Has anyone seen this error before or maybe someone knows how to reduce the amount of memory being allocated?
The text was updated successfully, but these errors were encountered:
I am trying to run SplaTAM on a dataset that i've collected offline using the method from #59. After doing the necessary processing I run $ python scripts/splatam.py configs/iphone/splatam.py
resulting in the folllowing error log
n-62-12-19(s214591) $ python scripts/splatam.py configs/iphone/splatam.py
System Paths:
/zhome/75/8/168142/Desktop/Bachelorprojekt/SplaTAM
/zhome/75/8/168142/Desktop/Bachelorprojekt/SplaTAM/scripts
/zhome/75/8/168142/miniconda3/envs/splatam/lib/python310.zip
/zhome/75/8/168142/miniconda3/envs/splatam/lib/python3.10
/zhome/75/8/168142/miniconda3/envs/splatam/lib/python3.10/lib-dynload
/zhome/75/8/168142/miniconda3/envs/splatam/lib/python3.10/site-packages
Seed set to: 0 (type: <class 'int'>)
Loaded Config:
{'workdir': '././experiments/iPhone_Captures/offline_demo', 'run_name': 'SplaTAM_iPhone', 'overwrite': False, 'depth_scale': 10.0, 'num_frames': 10, 'seed': 0, 'primary_device': 'cuda:0', 'map_every': 1, 'keyframe_every': 2, 'mapping_window_size': 32, 'report_global_progress_every': 100, 'eval_every': 1, 'scene_radius_depth_ratio': 3, 'mean_sq_dist_method': 'projective', 'report_iter_progress': False, 'load_checkpoint': False, 'checkpoint_time_idx': 130, 'save_checkpoints': False, 'checkpoint_interval': 5, 'use_wandb': False, 'data': {'dataset_name': 'nerfcapture', 'basedir': './experiments/iPhone_Captures', 'sequence': 'offline_demo', 'desired_image_height': 720, 'desired_image_width': 960, 'densification_image_height': 360, 'densification_image_width': 480, 'start': 0, 'end': -1, 'stride': 1, 'num_frames': 10}, 'tracking': {'use_gt_poses': False, 'forward_prop': True, 'visualize_tracking_loss': False, 'num_iters': 60, 'use_sil_for_loss': True, 'sil_thres': 0.99, 'use_l1': True, 'use_depth_loss_thres': True, 'depth_loss_thres': 20000, 'ignore_outlier_depth_loss': False, 'use_uncertainty_for_loss_mask': False, 'use_uncertainty_for_loss': False, 'use_chamfer': False, 'loss_weights': {'im': 0.5, 'depth': 1.0}, 'lrs': {'means3D': 0.0, 'rgb_colors': 0.0, 'unnorm_rotations': 0.0, 'logit_opacities': 0.0, 'log_scales': 0.0, 'cam_unnorm_rots': 0.001, 'cam_trans': 0.004}}, 'mapping': {'num_iters': 60, 'add_new_gaussians': True, 'sil_thres': 0.5, 'use_l1': True, 'ignore_outlier_depth_loss': False, 'use_sil_for_loss': False, 'use_uncertainty_for_loss_mask': False, 'use_uncertainty_for_loss': False, 'use_chamfer': False, 'loss_weights': {'im': 0.5, 'depth': 1.0}, 'lrs': {'means3D': 0.0001, 'rgb_colors': 0.0025, 'unnorm_rotations': 0.001, 'logit_opacities': 0.05, 'log_scales': 0.001, 'cam_unnorm_rots': 0.0, 'cam_trans': 0.0}, 'prune_gaussians': True, 'pruning_dict': {'start_after': 0, 'remove_big_after': 0, 'stop_after': 20, 'prune_every': 20, 'removal_opacity_threshold': 0.005, 'final_removal_opacity_threshold': 0.005, 'reset_opacities': False, 'reset_opacities_every': 500}, 'use_gaussian_splatting_densification': False, 'densify_dict': {'start_after': 500, 'remove_big_after': 3000, 'stop_after': 5000, 'densify_every': 100, 'grad_thresh': 0.0002, 'num_to_split_into': 2, 'removal_opacity_threshold': 0.005, 'final_removal_opacity_threshold': 0.005, 'reset_opacities_every': 3000}}, 'viz': {'render_mode': 'color', 'offset_first_viz_cam': True, 'show_sil': False, 'visualize_cams': True, 'viz_w': 600, 'viz_h': 340, 'viz_near': 0.01, 'viz_far': 100.0, 'view_scale': 2, 'viz_fps': 5, 'enter_interactive_post_online': False}}
Loading Dataset ...
0%| | 0/10 [00:00<?, ?it/sSaving parameters to: ././experiments/iPhone_Captures/offline_demo/SplaTAM_iPhonet/s]
Failed to evaluate trajectory.
Selected Keyframes at Frame 0: [0]
Tracking Result Time Step: 0: 0%| | 0/1 [00:00<?, ?it/s]
0%| | 0/10 [00:00<?, ?it/s]
Traceback (most recent call last): | 0/60 [00:00<?, ?it/s]
File "/zhome/75/8/168142/Desktop/Bachelorprojekt/SplaTAM/scripts/splatam.py", line 1007, in
rgbd_slam(experiment.config)
File "/zhome/75/8/168142/Desktop/Bachelorprojekt/SplaTAM/scripts/splatam.py", line 840, in rgbd_slam
loss, variables, losses = get_loss(params, iter_data, variables, iter_time_idx, config['mapping']['loss_weights'],
File "/zhome/75/8/168142/Desktop/Bachelorprojekt/SplaTAM/scripts/splatam.py", line 253, in get_loss
im, radius, _, = Renderer(raster_settings=curr_data['cam'])(**rendervar)
File "/zhome/75/8/168142/miniconda3/envs/splatam/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/zhome/75/8/168142/miniconda3/envs/splatam/lib/python3.10/site-packages/diff_gaussian_rasterization/init.py", line 186, in forward
return rasterize_gaussians(
File "/zhome/75/8/168142/miniconda3/envs/splatam/lib/python3.10/site-packages/diff_gaussian_rasterization/init.py", line 28, in rasterize_gaussians
return _RasterizeGaussians.apply(
File "/zhome/75/8/168142/miniconda3/envs/splatam/lib/python3.10/site-packages/diff_gaussian_rasterization/init.py", line 79, in forward
num_rendered, color, radii, geomBuffer, binningBuffer, imgBuffer, depth = _C.rasterize_gaussians(*args)
RuntimeError: CUDA out of memory. Tried to allocate 131065.38 GiB (GPU 0; 39.39 GiB total capacity; 79.66 MiB already allocated; 38.00 GiB free; 96.00 MiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
Mapping Time Step: 0: 0%| | 0/60 [00:00<?, ?it/s]
As I understand from the runtime error, the program is trying to allocate 131065 gigabyte of memory on the GPU. This seems a bit crazy, since no GPU's have that kind of memory? Has anyone seen this error before or maybe someone knows how to reduce the amount of memory being allocated?
The text was updated successfully, but these errors were encountered: