RuntimeError: expected scalar type Float but found Double

[nangongliufeng]

Thanks for this very good work, how can this problem be solved？ File "launch.py", line 125, in main() File "launch.py", line 114, in main trainer.fit(system, datamodule=dm) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 608, in fit call._call_and_handle_interrupt( File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/trainer/call.py", line 36, in _call_and_handle_interrupt return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 88, in launch return function(*args, *kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 650, in _fit_impl self._run(model, ckpt_path=self.ckpt_path) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1112, in _run results = self._run_stage() File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1191, in _run_stage self._run_train() File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1214, in _run_train self.fit_loop.run() File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 199, in run self.advance(args, kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/loops/fit_loop.py", line 267, in advance self._outputs = self.epoch_loop.run(self._data_fetcher) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 199, in run self.advance(*args, kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 213, in advance batch_output = self.batch_loop.run(kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 199, in run self.advance(*args, *kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 88, in advance outputs = self.optimizer_loop.run(optimizers, kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 199, in run self.advance(args, kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/loops/optimization/optimizer_loop.py", line 202, in advance result = self._run_optimization(kwargs, self._optimizers[self.optim_progress.optimizer_position]) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/loops/optimization/optimizer_loop.py", line 249, in _run_optimization self._optimizer_step(optimizer, opt_idx, kwargs.get("batch_idx", 0), closure) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/loops/optimization/optimizer_loop.py", line 370, in _optimizer_step self.trainer._call_lightning_module_hook( File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1356, in _call_lightning_module_hook output = fn(*args, kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/core/module.py", line 1754, in optimizer_step optimizer.step(closure=optimizer_closure) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/core/optimizer.py", line 169, in step step_output = self._strategy.optimizer_step(self._optimizer, self._optimizer_idx, closure, kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/strategies/ddp.py", line 280, in optimizer_step optimizer_output = super().optimizer_step(optimizer, opt_idx, closure, model, kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/strategies/strategy.py", line 234, in optimizer_step return self.precision_plugin.optimizer_step( File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/plugins/precision/native_amp.py", line 75, in optimizer_step closure_result = closure() File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/loops/optimization/optimizer_loop.py", line 149, in call self._result = self.closure(*args, kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/loops/optimization/optimizer_loop.py", line 135, in closure step_output = self._step_fn() File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/loops/optimization/optimizer_loop.py", line 419, in _training_step training_step_output = self.trainer._call_strategy_hook("training_step", kwargs.values()) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1494, in _call_strategy_hook output = fn(args, kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/strategies/ddp.py", line 351, in training_step return self.model(*args, kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl return forward_call(*input, kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/torch/nn/parallel/distributed.py", line 1008, in forward output = self._run_ddp_forward(*inputs, *kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/torch/nn/parallel/distributed.py", line 969, in _run_ddp_forward return module_to_run(inputs[0], kwargs[0]) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl return forward_call(*input, kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/pytorch_lightning/overrides/base.py", line 98, in forward output = self._forward_module.training_step(*inputs, *kwargs) File "/home/vge/code/instant-nsr-pl/systems/neus.py", line 89, in training_step out = self(batch) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl return forward_call(input, kwargs) File "/home/vge/code/instant-nsr-pl/systems/neus.py", line 32, in forward return self.model(batch['rays']) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl return forwardcall(*input, **kwargs) File "/home/vge/code/instant-nsr-pl/models/neus.py", line 284, in forward out = self.forward(rays) File "/home/vge/code/instant-nsr-pl/models/neus.py", line 262, in forward_ out_bg = self.forwardbg(rays) File "/home/vge/code/instant-nsr-pl/models/neus.py", line 159, in forwardbg ray_indices, t_starts, t_ends = ray_marching( File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context return func(*args, *kwargs) File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/nerfacc/ray_marching.py", line 177, in ray_marching packed_info, ray_indices, t_starts, t_ends = _C.ray_marching( File "/home/vge/anaconda3/envs/nsr/lib/python3.8/site-packages/nerfacc/cuda/init.py", line 13, in call_cuda return getattr(_C, name)(args, **kwargs) RuntimeError: expected scalar type Float but found Double Epoch 0: : 0it [00:02, ?it/s]

[bennyguo]

Fixed in the latest commit. Could you try again?

[wangyida]

Oh wow, it is the other way out for my scenario, need to adjust the variables to double from float. Haven’t checked in details for such error, anyone have insight?

[nangongliufeng]

Fixed in the latest commit. Could you try again? Thank you, it has been solved！