Cannot install RFDiffusion on VM with X86-64, pytorch_cuda-12.8.1, RTX 5090 GPU

Hello everyone,
I use vm to install RFDiffusion with spec:
X86-64, RTX 5090 GPU
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2025 NVIDIA Corporation
Built on Fri_Feb_21_20:23:50_PST_2025
Cuda compilation tools, release 12.8, V12.8.93
Build cuda_12.8.r12.8/compiler.35583870_0

It gave errors when running Conda Install SE3-Transformer code:
conda env create -f env/SE3nv.yml
conda activate SE3nv
cd env/SE3Transformer
pip install --no-cache-dir -r requirements.txt
python setup.py install
cd ../.. # change into the root directory of the repository
pip install -e . # install the rfdiffusion module from the root of the repository

The output errors are as follows. I'd like to learn any suggestions or advice! Thank you very much!
/workspace/RFdiffusion/rfdiffusion/inference/model_runners.py", line 722, in sample_step
msa_prev, pair_prev, px0, state_prev, alpha, logits, plddt = self.model(msa_masked,
File "/venv/SE3nv/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/workspace/RFdiffusion/rfdiffusion/RoseTTAFoldModel.py", line 103, in forward
msa, pair, R, T, alpha_s, state = self.simulator(seq, msa_latent, msa_full, pair, xyz[:,:,:3],
File "/venv/SE3nv/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/workspace/RFdiffusion/rfdiffusion/Track_module.py", line 420, in forward
msa_full, pair, R_in, T_in, state, alpha = self.extra_block[i_m](msa_full,
File "/venv/SE3nv/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/workspace/RFdiffusion/rfdiffusion/Track_module.py", line 332, in forward
R, T, state, alpha = self.str2str(msa, pair, R_in, T_in, xyz, state, idx, motif_mask=motif_mask, cyclic_reses=cyclic_reses, top_k=0)
File "/venv/SE3nv/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/venv/SE3nv/lib/python3.9/site-packages/torch/cuda/amp/autocast_mode.py", line 141, in decorate_autocast
return func(args, **kwargs)
File "/workspace/RFdiffusion/rfdiffusion/Track_module.py", line 266, in forward
shift = self.se3(G, node.reshape(BL, -1, 1), l1_feats, edge_feats)
File "/venv/SE3nv/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/workspace/RFdiffusion/rfdiffusion/SE3_network.py", line 83, in forward
return self.se3(G, node_features, edge_features)
File "/venv/SE3nv/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/venv/SE3nv/lib/python3.9/site-packages/se3_transformer/model/transformer.py", line 140, in forward
basis = basis or get_basis(graph.edata['rel_pos'], max_degree=self.max_degree, compute_gradients=False,
File "/venv/SE3nv/lib/python3.9/site-packages/se3_transformer/model/basis.py", line 166, in get_basis
with nvtx_range('spherical harmonics'):
File "/venv/SE3nv/lib/python3.9/contextlib.py", line 119, in enter
return next(self.gen)
File "/venv/SE3nv/lib/python3.9/site-packages/torch/cuda/nvtx.py", line 59, in range
range_push(msg.format(*args, **kwargs))
File "/venv/SE3nv/lib/python3.9/site-packages/torch/cuda/nvtx.py", line 28, in range_push 2755: /wor" 20:40 17-Oct-25
return _nvtx.rangePushA(msg)
File "/venv/SE3nv/lib/python3.9/site-packages/torch/cuda/nvtx.py", line 9, in _fail
raise RuntimeError("NVTX functions not installed. Are you sure you have a CUDA build?")
RuntimeError: NVTX functions not installed. Are you sure you have a CUDA build?

Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

Start with env/SE3nv.yml and env/SE3Transformer/requirements.txt, then reproduce the installation and run described in the issue. Trace the failure from rfdiffusion/Track_module.py through rfdiffusion/SE3_network.py to se3_transformer/model/basis.py; done means the documented environment installs and the reported run no longer fails at the NVTX call.