dcharatan
commented
4 months ago This is a preprocessed ACID dataset (the same one used to train pixelSplat). There's a note about it here. Email me at charatan@mit.edu if you want the link.
Closed hmbbsbb closed 4 months ago
python3 -m flowmap.pretrain rm: 无法删除 'outputs/local': 没有那个文件或目录 Using cache found in /home/zmm/.cache/torch/hub/intel-isl_MiDaS_master Loading weights: None Using cache found in /home/zmm/.cache/torch/hub/rwightman_gen-efficientnet-pytorch_master 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 You are using a CUDA device ('NVIDIA GeForce RTX 4080 SUPER') 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 | flow_predictor | FlowPredictorGMFlow | 0
1 | model | Model | 21.3 M
21.3 M Trainable params 0 Non-trainable params 21.3 M Total params 85.382 Total estimated model params size (MB) Loading CO3D sequences: 100%|███████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 15.71it/s] Error executing job with overrides: []██████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 16.40it/s] Traceback (most recent call last): File "/home/zmm/anaconda3/envs/flowmap/flowmap/flowmap/pretrain.py", line 66, in pretrain trainer.fit( File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/site-packages/lightning/pytorch/trainer/trainer.py", line 544, in fit call._call_and_handle_interrupt( File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/site-packages/lightning/pytorch/trainer/call.py", line 44, in _call_and_handle_interrupt return trainer_fn(*args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/site-packages/lightning/pytorch/trainer/trainer.py", line 580, in _fit_impl self._run(model, ckpt_path=ckpt_path) File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/site-packages/lightning/pytorch/trainer/trainer.py", line 987, in _run results = self._run_stage() ^^^^^^^^^^^^^^^^^ File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/site-packages/lightning/pytorch/trainer/trainer.py", line 1031, in _run_stage self._run_sanity_check() File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/site-packages/lightning/pytorch/trainer/trainer.py", line 1060, in _run_sanity_check val_loop.run() File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/site-packages/lightning/pytorch/loops/utilities.py", line 182, in _decorator return loop_run(self, *args, *kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/site-packages/lightning/pytorch/loops/evaluation_loop.py", line 110, in run self.setup_data() File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/site-packages/lightning/pytorch/loops/evaluation_loop.py", line 166, in setup_data dataloaders = _request_dataloader(source) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/site-packages/lightning/pytorch/trainer/connectors/data_connector.py", line 342, in _request_dataloader return data_source.dataloader() ^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/site-packages/lightning/pytorch/trainer/connectors/data_connector.py", line 309, in dataloader return call._call_lightning_datamodule_hook(self.instance.trainer, self.name) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/site-packages/lightning/pytorch/trainer/call.py", line 179, in _call_lightning_datamodule_hook return fn(args, kwargs) ^^^^^^^^^^^^^^^^^^^ File "/home/zmm/anaconda3/envs/flowmap/flowmap/flowmap/dataset/data_module_pretrain.py", line 76, in val_dataloader dataset = get_dataset(self.dataset_cfgs, "val", self.frame_sampler_cfg) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/site-packages/jaxtyping/_decorator.py", line 450, in wrapped_fn out = fn(*args, *kwargs) ^^^^^^^^^^^^^^^^^^^ File "/home/zmm/anaconda3/envs/flowmap/flowmap/flowmap/dataset/init.py", line 34, in get_dataset datasets = [ ^ File "/home/zmm/anaconda3/envs/flowmap/flowmap/flowmap/dataset/init.py", line 35, in
DATASETS[cfg.name](cfg, stage, frame_sampler) for cfg in dataset_cfgs
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/site-packages/jaxtyping/_decorator.py", line 450, in wrapped_fn
out = fn( args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "/home/zmm/anaconda3/envs/flowmap/flowmap/flowmap/dataset/dataset_re10k.py", line 48, in init
[path for path in root.iterdir() if path.suffix == ".torch"]
File "/home/zmm/anaconda3/envs/flowmap/flowmap/flowmap/dataset/dataset_re10k.py", line 48, in
[path for path in root.iterdir() if path.suffix == ".torch"]
File "/home/zmm/anaconda3/envs/flowmap/lib/python3.11/pathlib.py", line 931, in iterdir
for name in os.listdir(self):
^^^^^^^^^^^^^^^^
FileNotFoundError: [Errno 2] No such file or directory: 'datasets/acid/test'
Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.