hongxiaoy
commented
1 month ago Sorry for the late response.
I upload these two files to huggingface.
https://huggingface.co/datasets/hongxiaoy/OccScanNet/blob/main/train_subscenes.txt https://huggingface.co/datasets/hongxiaoy/OccScanNet/blob/main/val_subscenes.txt
You can download them and retry it. If it's still not work, just tell me.
首先感谢你这优秀的工作。我成功在NYU训练成功，但是在SCANNT数据集上一直失败，我可以确信某些数据应该是在计算损失的时候会出现nan，并且在您的原始代码中出现了类似# print(521, torch.any(torch.isnan(out_dict['depth_1_1'])))，请问是否是部分场景本身的错误导致，我根据你代码中的指示，删除了对应的场景，但还是在其他场景下出现了类似的错误。请问可以给出正确的train_subscenes.txt与val_subscenes.txt。非常感谢！！以下是我在训练过程中遇到的错误： Epoch 0: 2%| | 264/11422 [11:33<8:08:38, 2.63s/it, v_num=, train/loss_step=13/opt/conda/conda-bld/pytorch_1678402374358/work/aten/src/ATen/native/cuda/Loss.cu:92: operator(): block: [0,0,0], thread: [0,0,0] Assertion input_val >= zero && input_val <= one failed. Traceback (most recent call last): File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/trainer/call.py", line 42, in _call_and_handle_interrupt return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 92, in launch return function(*args, *kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 559, in _fit_impl self._run(model, ckpt_path=ckpt_path) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 935, in _run results = self._run_stage() File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 978, in _run_stage self.fit_loop.run() File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/loops/fit_loop.py", line 201, in run self.advance() File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/loops/fit_loop.py", line 354, in advance self.epoch_loop.run(self._data_fetcher) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/loops/training_epoch_loop.py", line 133, in run self.advance(data_fetcher) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/loops/training_epoch_loop.py", line 218, in advance batch_output = self.automatic_optimization.run(trainer.optimizers[0], kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/loops/optimization/automatic.py", line 185, in run self._optimizer_step(kwargs.get("batch_idx", 0), closure) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/loops/optimization/automatic.py", line 261, in _optimizer_step call._call_lightning_module_hook( File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/trainer/call.py", line 142, in _call_lightning_module_hook output = fn(args, kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/core/module.py", line 1266, in optimizer_step optimizer.step(closure=optimizer_closure) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/core/optimizer.py", line 158, in step step_output = self._strategy.optimizer_step(self._optimizer, closure, kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/strategies/ddp.py", line 257, in optimizer_step optimizer_output = super().optimizer_step(optimizer, closure, model, kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/strategies/strategy.py", line 224, in optimizer_step return self.precision_plugin.optimizer_step(optimizer, model=model, closure=closure, kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/plugins/precision/precision_plugin.py", line 114, in optimizer_step return optimizer.step(closure=closure, kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/torch/optim/lr_scheduler.py", line 69, in wrapper return wrapped(*args, kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/torch/optim/optimizer.py", line 280, in wrapper out = func(*args, *kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/torch/optim/optimizer.py", line 33, in _use_grad ret = func(self, args, kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/torch/optim/adamw.py", line 148, in step loss = closure() File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/plugins/precision/precision_plugin.py", line 101, in _wrap_closure closure_result = closure() File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/loops/optimization/automatic.py", line 140, in call self._result = self.closure(*args, kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/loops/optimization/automatic.py", line 126, in closure step_output = self._step_fn() File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/loops/optimization/automatic.py", line 308, in _training_step training_step_output = call._call_strategy_hook(trainer, "training_step", kwargs.values()) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/trainer/call.py", line 288, in _call_strategy_hook output = fn(args, kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/strategies/ddp.py", line 329, in training_step return self.model(*args, kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, *kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/torch/nn/parallel/distributed.py", line 1156, in forward output = self._run_ddp_forward(inputs, kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/torch/nn/parallel/distributed.py", line 1110, in _run_ddp_forward return module_to_run(*inputs[0], kwargs[0]) # type: ignore[index] File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, *kwargs) File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/pytorch_lightning/overrides/base.py", line 90, in forward output = self._forward_module.training_step(inputs, kwargs) File "/home/gwr/PycharmProjects/ISO/iso/models/iso.py", line 762, in training_step return self.step(batch, "train", self.train_metrics) File "/home/gwr/PycharmProjects/ISO/iso/models/iso.py", line 688, in step loss_sem_scal = sem_scal_loss(batch['name'], ssc_pred, target) File "/home/gwr/PycharmProjects/ISO/iso/loss/ssc_loss.py", line 69, in sem_scal_loss loss_precision = F.binary_cross_entropy( File "/home/gwr/.conda/envs/iso/lib/python3.9/site-packages/torch/nn/functional.py", line 3098, in binary_cross_entropy return torch._C._nn.binary_cross_entropy(input, target, weight, reduction_enum) RuntimeError: CUDA error: device-side assert triggered Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.