TypeError when train CVA-MVSNet

[YuhsiHu]

Thank you for sharing this great paper and excellent code. I followed the README file in CVA-MVSNet. When I tried to train the model, there was a TypeError. Could you please help me? Thank you for your time.

GPU available: True, used: True INFO:lightning:GPU available: True, used: True No environment variable for node rank defined. Set as 0. WARNING:lightning:No environment variable for node rank defined. Set as 0. CUDA_VISIBLE_DEVICES: [0] INFO:lightning:CUDA_VISIBLE_DEVICES: [0] Validation sanity check: 0it [00:00, ?it/s]/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2228.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] Epoch 1: 0%| | 0/2714 [00:00<?, ?it/s]Traceback (most recent call last): File "train.py", line 126, in main(*parse_args(parser)) File "train.py", line 122, in main trainer.fit(model) File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 859, in fit self.single_gpu_train(model) File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/pytorch_lightning/trainer/distrib_parts.py", line 503, in single_gpu_train self.run_pretrain_routine(model) File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1015, in run_pretrain_routine self.train() File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 347, in train self.run_training_epoch() File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 406, in run_training_epoch enumerate(_with_is_last(train_dataloader)), "get_train_batch" File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/pytorch_lightning/profiler/profilers.py", line 64, in profile_iterable value = next(iterator) File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 801, in _with_is_last last = next(it) File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 530, in next data = self._next_data() File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1224, in _next_data return self._process_data(data) File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1250, in _process_data data.reraise() File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/torch/_utils.py", line 457, in reraise raise exception TypeError: Caught TypeError in DataLoader worker process 0. Original Traceback (most recent call last): File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 287, in _worker_loop data = fetcher.fetch(index) File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 49, in data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/hyx/tandem/cva_mvsnet/models/datasets.py", line 583, in getitem item = self.dataset.getitem(idx) File "/home/hyx/tandem/cva_mvsnet/models/datasets.py", line 562, in getitem data = self.transform(data) File "/home/hyx/tandem/cva_mvsnet/models/datasets.py", line 97, in preprocess img_aug = color_trans(img_ori) File "/home/hyx/anaconda3/envs/tandem/lib/python3.7/site-packages/torchvision/transforms/transforms.py", line 95, in call img = t(img) TypeError: 'tuple' object is not callable

[ddyj]

Did you solve this problem, I have this problem too

[YuhsiHu]

No, I didn't.

[wyt1004]

I guess this may be caused by different pytorch versions. The transforms.ColorJitter.get_params function in datasets.py returns a tuple, and the tuple cannot be called as a function in the transforms.Compose function. I tried a working method, modifying datasets.py:

fn_idx, brightness_factor, contrast_factor, saturation_factor, hue_factor = transforms.ColorJitter.get_params( brightness=brightness, contrast=contrast, saturation=saturation, hue=hue ) color_trans = transforms.Compose([ transforms.ToPILImage(), transforms.ColorJitter(brightness=brightness_factor, contrast=contrast_factor, saturation=saturation_factor), ]) Hope this helps you.