Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

NerfAcc: Setting up CUDA (This may take a few minutes the first time)Killed #261

Open
Flyingdog-Huang opened this issue Oct 24, 2023 · 1 comment

Comments

@Flyingdog-Huang
Copy link

2023-10-24 02:00:54.767 | INFO | main:main:25 - ==> Init dataloader ...
100%|█████████████████████████████████████████████████████████| 800/800 [00:00<00:00, 204837.51it/s]
2023-10-24 02:00:54.944 | INFO | dataset.ray_dataset:init:42 - ==> Find 4 cameras
100%|████████████████████████████████████████████████████████████| 200/200 [00:01<00:00, 111.36it/s]
100%|███████████████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 550.07it/s]
100%|██████████████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 2726.73it/s]
100%|██████████████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 8469.83it/s]
100%|████████████████████████████████████████████████████████████████| 800/800 [00:00<00:00, 222524.25it/s]
2023-10-24 02:00:58.635 | INFO | dataset.ray_dataset:init:42 - ==> Find 4 cameras
100%|███████████████████████████████████████████████████████████████████| 200/200 [00:01<00:00, 111.41it/s]
100%|███████████████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 486.54it/s]
100%|██████████████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 5384.91it/s]
100%|██████████████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 6841.64it/s]
2023-10-24 02:01:02.330 | INFO | main:main:49 - ==> Init model ...
2023-10-24 02:01:04.057 | INFO | main:main:51 - TriMipRFModel(
(field): TriMipRF(
(encoding): TriMipEncoding()
(direction_encoding): Encoding(n_input_dims=3, n_output_dims=16, seed=1337, dtype=torch.float16, hyperparams={'degree': 4, 'otype': 'SphericalHarmonics'})
(mlp_base): Network(n_input_dims=48, n_output_dims=16, seed=1337, dtype=torch.float16, hyperparams={'encoding': {'offset': 0.0, 'otype': 'Identity', 'scale': 1.0}, 'network': {'activation': 'ReLU', 'n_hidden_layers': 2, 'n_neurons': 128, 'otype': 'FullyFusedMLP', 'output_activation': 'None'}, 'otype': 'NetworkWithInputEncoding'})
(mlp_head): Network(n_input_dims=31, n_output_dims=3, seed=1337, dtype=torch.float16, hyperparams={'encoding': {'offset': 0.0, 'otype': 'Identity', 'scale': 1.0}, 'network': {'activation': 'ReLU', 'n_hidden_layers': 4, 'n_neurons': 128, 'otype': 'FullyFusedMLP', 'output_activation': 'Sigmoid'}, 'otype': 'NetworkWithInputEncoding'})
)
(ray_sampler): OccupancyGrid()
)
2023-10-24 02:01:04.058 | INFO | main:main:53 - ==> Init trainer ...
2023-10-24 02:01:04.098 | INFO | trainer.trainer:init:60 - # Parameters for trimipRF.get_optimizer:

==============================================================================

trimipRF.get_optimizer.feature_lr_scale = 10.0
trimipRF.get_optimizer.lr = 0.002
trimipRF.get_optimizer.weight_decay = 1e-05

Parameters for get_scheduler:

==============================================================================

get_scheduler.gamma = 0.6

Parameters for main:

==============================================================================

main.batch_size = 24
main.model_name = 'Tri-MipRF'
main.num_workers = 4
main.seed = 42
main.stages = 'train_eval'
main.train_split = 'trainval'

Parameters for RayDataset:

==============================================================================

RayDataset.base_path =
'/home/jovyan/vol-1/Tri-MipRF/data/nerf_synthetic_multiscale'
RayDataset.num_rays = 8192
RayDataset.render_bkgd = 'white'
RayDataset.scene = 'chair'
RayDataset.scene_type = 'nerf_synthetic_multiscale'
RayDataset.to_world = True

Parameters for Trainer:

==============================================================================

Trainer.base_exp_dir = '/home/jovyan/vol-1/Tri-MipRF/output'
Trainer.dynamic_batch_size = True
Trainer.eval_step = 25000
Trainer.exp_name = 'nerf_synthetic_multiscale/chair/Tri-MipRF/2023-10-24_02-00-54'
Trainer.log_step = 1000
Trainer.max_steps = 25001
Trainer.num_rays = 8192
Trainer.target_sample_batch_size = 65536
Trainer.test_chunk_size = 8192
Trainer.varied_eval_img = True

Parameters for TriMipRF:

==============================================================================

TriMipRF.feature_dim = 16
TriMipRF.geo_feat_dim = 15
TriMipRF.n_levels = 8
TriMipRF.net_depth_base = 2
TriMipRF.net_depth_color = 4
TriMipRF.net_width = 128
TriMipRF.plane_size = 512

Parameters for TriMipRFModel:

==============================================================================

TriMipRFModel.occ_grid_resolution = 128
TriMipRFModel.samples_per_ray = 1024

2023-10-24 02:01:04.101 | INFO | trainer.trainer:fit:106 - ==> Start training ...
(● ) NerfAcc: Setting up CUDA (This may take a few minutes the first time)Killed

model:https://github.com/wbhu/Tri-MipRF
version:0.3.3/0.3.5

@Jerome-Hsieh
Copy link

have you solved this problem?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants