ModuleNotFoundError: No module named 'tinycudann'

[kerrigenwan]

Can someone help me take a look at the errors I have encountered?Here are the error codes I encountered.
Training with 1 GPUs.
Using random seed 0
Make folder logs/example_group/example_name

• checkpoint:
  • save_epoch: 9999999999
  • save_iter: 20000
  • save_latest_iter: 9999999999
  • save_period: 9999999999
  • strict_resume: True
• cudnn:
  • benchmark: True
  • deterministic: False
• data:
  • name: dummy
  • num_images: None
  • num_workers: 4
  • preload: True
  • readjust:
    • center: [0.0, 0.0, 0.0]
    • scale: 1.0
  • root: datasets/lego_ds2
  • train:
    • batch_size: 2
    • image_size: [802, 802]
    • subset: None
  • type: projects.neuralangelo.data
  • use_multi_epoch_loader: True
  • val:
    • batch_size: 2
    • image_size: [300, 300]
    • max_viz_samples: 16
    • subset: 4
• image_save_iter: 9999999999
• inference_args:
• local_rank: 0
• logdir: logs/example_group/example_name
• logging_iter: 9999999999999
• max_epoch: 9999999999
• max_iter: 500000
• metrics_epoch: None
• metrics_iter: None
• model:
  • appear_embed:
    • dim: 8
    • enabled: False
  • background:
    • enabled: True
    • encoding:
      • levels: 10
      • type: fourier
    • encoding_view:
      • levels: 3
      • type: spherical
    • mlp:
      • activ: relu
      • activ_density: softplus
      • activ_density_params:
      • activ_params:
      • hidden_dim: 256
      • hidden_dim_rgb: 128
      • num_layers: 8
      • num_layers_rgb: 2
      • skip: [4]
      • skip_rgb: []
    • view_dep: True
    • white: False
  • object:
    • rgb:
      • encoding_view:
        • levels: 3
        • type: spherical
      • mlp:
        • activ: relu_
        • activ_params:
        • hidden_dim: 256
        • num_layers: 4
        • skip: []
        • weight_norm: True
      • mode: idr
    • s_var:
      • anneal_end: 0.1
      • init_val: 3.0
    • sdf:
      • encoding:
        • coarse2fine:
          • enabled: True
          • init_active_level: 4
          • step: 5000
        • hashgrid:
          • dict_size: 22
          • dim: 8
          • max_logres: 11
          • min_logres: 5
          • range: [-2, 2]
        • levels: 16
        • type: hashgrid
      • gradient:
        • mode: numerical
        • taps: 4
      • mlp:
        • activ: softplus
        • activ_params:
          • beta: 100
        • geometric_init: True
        • hidden_dim: 256
        • inside_out: False
        • num_layers: 1
        • out_bias: 0.5
        • skip: []
        • weight_norm: True
  • render:
    • num_sample_hierarchy: 4
    • num_samples:
      • background: 32
      • coarse: 64
      • fine: 16
    • rand_rays: 512
    • stratified: True
  • type: projects.neuralangelo.model
• nvtx_profile: False
• optim:
  • fused_opt: False
  • params:
    • lr: 0.001
    • weight_decay: 0.01
  • sched:
    • gamma: 10.0
    • iteration_mode: True
    • step_size: 9999999999
    • two_steps: [300000, 400000]
    • type: two_steps_with_warmup
    • warm_up_end: 5000
  • type: AdamW
• pretrained_weight: None
• source_filename: projects/neuralangelo/configs/custom/lego.yaml
• speed_benchmark: False
• test_data:
  • name: dummy
  • num_workers: 0
  • test:
    • batch_size: 1
    • is_lmdb: False
    • roots: None
  • type: imaginaire.datasets.images
• timeout_period: 9999999
• trainer:
  • amp_config:
    • backoff_factor: 0.5
    • enabled: False
    • growth_factor: 2.0
    • growth_interval: 2000
    • init_scale: 65536.0
  • ddp_config:
    • find_unused_parameters: False
    • static_graph: True
  • depth_vis_scale: 0.5
  • ema_config:
    • beta: 0.9999
    • enabled: False
    • load_ema_checkpoint: False
    • start_iteration: 0
  • grad_accum_iter: 1
  • image_to_tensorboard: False
  • init:
    • gain: None
    • type: none
  • loss_weight:
    • curvature: 0.0005
    • eikonal: 0.1
    • render: 1.0
  • type: projects.neuralangelo.trainer
• validation_iter: 5000
• wandb_image_iter: 10000
• wandb_scalar_iter: 100
  cudnn benchmark: True
  cudnn deterministic: False
  Setup trainer.
  Using random seed 0
  Traceback (most recent call last):
  File "train.py", line 104, in
  main()
  File "train.py", line 79, in main
  trainer = get_trainer(cfg, is_inference=False, seed=args.seed)
  File "/home/intel/neuralangelo/imaginaire/trainers/utils/get_trainer.py", line 32, in get_trainer
  trainer = trainer_lib.Trainer(cfg, is_inference=is_inference, seed=seed)
  File "/home/intel/neuralangelo/projects/neuralangelo/trainer.py", line 26, in init
  super().init(cfg, is_inference=is_inference, seed=seed)
  File "/home/intel/neuralangelo/projects/nerf/trainers/base.py", line 28, in init
  super().init(cfg, is_inference=is_inference, seed=seed)
  File "/home/intel/neuralangelo/imaginaire/trainers/base.py", line 50, in init
  self.model = self.setup_model(cfg, seed=seed)
  File "/home/intel/neuralangelo/imaginaire/trainers/base.py", line 116, in setup_model
  lib_model = importlib.import_module(cfg.model.type)
  File "/home/intel/miniconda3/envs/neuralangelo/lib/python3.8/importlib/init.py", line 127, in import_module
  return _bootstrap._gcd_import(name[level:], package, level)
  File "", line 1014, in _gcd_import
  File "", line 991, in _find_and_load
  File "", line 975, in _find_and_load_unlocked
  File "", line 671, in _load_unlocked
  File "", line 843, in exec_module
  File "", line 219, in _call_with_frames_removed
  File "/home/intel/neuralangelo/projects/neuralangelo/model.py", line 21, in
  from projects.neuralangelo.utils.modules import NeuralSDF, NeuralRGB, BackgroundNeRF
  File "/home/intel/neuralangelo/projects/neuralangelo/utils/modules.py", line 16, in
  import tinycudann as tcnn
  ModuleNotFoundError: No module named 'tinycudann'
  [2024-03-25 20:11:48,544] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 0 (pid: 37238) of binary: /home/intel/miniconda3/envs/neuralangelo/bin/python
  Traceback (most recent call last):
  File "/home/intel/miniconda3/envs/neuralangelo/bin/torchrun", line 10, in
  sys.exit(main())
  File "/home/intel/miniconda3/envs/neuralangelo/lib/python3.8/site-packages/torch/distributed/elastic/multiprocessing/errors/init.py", line 346, in wrapper
  return f(*args, **kwargs)
  File "/home/intel/miniconda3/envs/neuralangelo/lib/python3.8/site-packages/torch/distributed/run.py", line 806, in main
  run(args)
  File "/home/intel/miniconda3/envs/neuralangelo/lib/python3.8/site-packages/torch/distributed/run.py", line 797, in run
  elastic_launch(
  File "/home/intel/miniconda3/envs/neuralangelo/lib/python3.8/site-packages/torch/distributed/launcher/api.py", line 134, in call
  return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/intel/miniconda3/envs/neuralangelo/lib/python3.8/site-packages/torch/distributed/launcher/api.py", line 264, in launch_agent
  raise ChildFailedError(
  torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
  ============================================================
  train.py FAILED

---

Failures:
<NO_OTHER_FAILURES>

Root Cause (first observed failure):
[0]:
time : 2024-03-25_20:11:48
host : intel-MD72-HB1-00
rank : 0 (local_rank: 0)
exitcode : 1 (pid: 37238)
error_file: <N/A>
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html