NeRFStudio and gsplat version?

[NOTE] Not running eval iterations since only viewer is enabled. Use --vis {wandb, tensorboard, viewer+wandb, viewer+tensorboard} to run with eval. No Nerfstudio checkpoint to load, so training from scratch. Disabled comet/tensorboard/wandb event writers Caching / undistorting train images full_images_datamanager.py:230 C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\torch\utils\cpp_extension.py:380: UserWarning: Error checking compiler version for cl: [WinError 2] 系统找不到指定的文件。 warnings.warn(f'Error checking compiler version for {compiler}: {error}') C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\torch\utils\cpp_extension.py:1965: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST']. warnings.warn( ( ● ) gsplat: Setting up CUDA (This may take a few minutes the first time)信息: 用提供的模式无法找到文件。 Printing profiling stats, from longest to shortest duration in seconds VanillaPipeline.get_train_loss_dict: 0.5474 Trainer.train_iteration: 0.5474 Traceback (most recent call last): File "C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\gsplat\cuda_backend.py", line 41, in from gsplat import csrc as _C ImportError: cannot import name 'csrc' from 'gsplat' (C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\gsplat__init__.py)

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "C:\ProgramData\anaconda3\envs\spann3r\lib\runpy.py", line 197, in _run_module_as_main return _run_code(code, main_globals, None, File "C:\ProgramData\anaconda3\envs\spann3r\lib\runpy.py", line 87, in _run_code exec(code, run_globals) File "C:\Users\Administrator\AppData\Roaming\Python\Python39\Scripts\ns-train.exe__main__.py", line 7, in sys.exit(entrypoint()) File "C:\Users\Administrator\AppData\Roaming\Python\Python39\site-packages\nerfstudio\scripts\train.py", line 262, in entrypoint main( File "C:\Users\Administrator\AppData\Roaming\Python\Python39\site-packages\nerfstudio\scripts\train.py", line 247, in main launch( File "C:\Users\Administrator\AppData\Roaming\Python\Python39\site-packages\nerfstudio\scripts\train.py", line 189, in launch main_func(local_rank=0, world_size=world_size, config=config) File "C:\Users\Administrator\AppData\Roaming\Python\Python39\site-packages\nerfstudio\scripts\train.py", line 100, in train_loop trainer.train() File "C:\Users\Administrator\AppData\Roaming\Python\Python39\site-packages\nerfstudio\engine\trainer.py", line 262, in train loss, loss_dict, metrics_dict = self.train_iteration(step) File "C:\Users\Administrator\AppData\Roaming\Python\Python39\site-packages\nerfstudio\utils\profiler.py", line 111, in inner out = func(*args, kwargs) File "C:\Users\Administrator\AppData\Roaming\Python\Python39\site-packages\nerfstudio\engine\trainer.py", line 497, in trainiteration , loss_dict, metrics_dict = self.pipeline.get_train_loss_dict(step=step) File "C:\Users\Administrator\AppData\Roaming\Python\Python39\site-packages\nerfstudio\utils\profiler.py", line 111, in inner out = func(*args, *kwargs) File "C:\Users\Administrator\AppData\Roaming\Python\Python39\site-packages\nerfstudio\pipelines\base_pipeline.py", line 300, in get_train_loss_dict model_outputs = self._model(ray_bundle) # train distributed data parallel model if world_size > 1 File "C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl return self._call_impl(args, kwargs) File "C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl return forward_call(*args, *kwargs) File "C:\Users\Administrator\AppData\Roaming\Python\Python39\site-packages\nerfstudio\models\base_model.py", line 143, in forward return self.get_outputs(ray_bundle) File "C:\Users\Administrator\AppData\Roaming\Python\Python39\site-packages\nerfstudio\models\splatfacto.py", line 815, in get_outputs render, alpha, info = rasterization( File "C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\gsplat\rendering.py", line 212, in rasterization proj_results = fully_fused_projection( File "C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\gsplat\cuda_wrapper.py", line 260, in fully_fused_projection return _FullyFusedProjection.apply( File "C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\torch\autograd\function.py", line 574, in apply return super().apply(args, *kwargs) # type: ignore[misc] File "C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\gsplat\cuda_wrapper.py", line 692, in forward radii, means2d, depths, conics, compensations = _make_lazy_cuda_func( File "C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\gsplat\cuda_wrapper.py", line 10, in call_cuda from ._backend import _C File "C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\gsplat\cuda_backend.py", line 84, in _C = load( File "C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\torch\utils\cpp_extension.py", line 1312, in load return _jit_compile( File "C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\torch\utils\cpp_extension.py", line 1722, in _jit_compile _write_ninja_file_and_build_library( File "C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\torch\utils\cpp_extension.py", line 1821, in _write_ninja_file_and_build_library _write_ninja_file_to_build_library( File "C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\torch\utils\cpp_extension.py", line 2246, in _write_ninja_file_to_build_library _write_ninja_file( File "C:\ProgramData\anaconda3\envs\spann3r\lib\site-packages\torch\utils\cpp_extension.py", line 2382, in _write_ninja_file cl_paths = subprocess.check_output(['where', File "C:\ProgramData\anaconda3\envs\spann3r\lib\subprocess.py", line 424, in check_output return run(popenargs, stdout=PIPE, timeout=timeout, check=True, File "C:\ProgramData\anaconda3\envs\spann3r\lib\subprocess.py", line 528, in run raise CalledProcessError(retcode, process.args, subprocess.CalledProcessError: Command '['where', 'cl']' returned non-zero exit status 1.

when execute "ns-train splatfacto --data ./output/demo/s00567 --pipeline.model.camera-optimizer.mode SO3xR3", meet the above error. what are the correct NeRFStudio and gsplat version if you meet no errors?

HengyiWang / spann3r

NeRFStudio and gsplat version? #30