Thanks for your great work. I tried to run your code on my data but the code is stuck here:
python launch.py --config configs/bakedsdf-colmap.yaml --gpu 0 --train dataset.root_dir=./data/360_v2/garden/
Global seed set to 42
/home/zh/.conda/envs/bakedsdf/lib/python3.8/site-packages/torch/nn/utils/weight_norm.py:30: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.
warnings.warn("torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.")
Using 16bit None Automatic Mixed Precision (AMP)
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
`Trainer(limit_train_batches=1.0)` was configured so 100% of the batches per epoch will be used..
[rank: 0] Global seed set to 42
Initializing distributed: GLOBAL_RANK: 0, MEMBER: 1/1
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distributed_backend=nccl
All distributed processes registered. Starting with 1 processes
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You are using a CUDA device ('NVIDIA GeForce RTX 4090') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
| Name | Type | Params
----------------------------------------
0 | model | BakedSDFModel | 41.9 M
----------------------------------------
41.9 M Trainable params
0 Non-trainable params
41.9 M Total params
83.865 Total estimated model params size (MB)
Epoch 0: : 0it [00:00, ?it/s]
Thanks for your great work. I tried to run your code on my data but the code is stuck here:
When I cancel this task, it exits from this line:
This is my environment:
Could you give me a hand : )