Having Error 'c10::HIPError'

[haotiansun14]

Hi! I have encountered an error when trying to train the model. I tried different datasets, but the error remains. Thank you for helping me!
My env: Python 3.7.0 and Pytorch 1.10.1

The complete error message goes as follows:

terminate called after throwing an instance of 'c10::HIPError' | 0/500 [00:00<?, ?it/s]
what(): HIP error: hipErrorNoDevice
HIP kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing HIP_LAUNCH_BLOCKING=1.
Exception raised from deviceCount at /pytorch/aten/src/ATen/hip/impl/HIPGuardImplMasqueradingAsCUDA.h:102 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x42 (0x7f9eff1e7212 in /nethome/hsun409/anaconda3/envs/GDSS_env/lib/python3.7/site-packages/torch/lib/libc10.so)
frame #1: + 0x5618da (0x7f9f14f4a8da in /nethome/hsun409/anaconda3/envs/GDSS_env/lib/python3.7/site-packages/torch/lib/libtorch_hip.so)
frame #2: torch::autograd::Engine::start_device_threads() + 0x21a (0x7f9f4b4d82ca in /nethome/hsun409/anaconda3/envs/GDSS_env/lib/python3.7/site-packages/torch/lib/libtorch_cpu.so)
frame #3: + 0xf907 (0x7f9f61c86907 in /lib/x86_64-linux-gnu/libpthread.so.0)
frame #4: torch::autograd::Engine::initialize_device_threads_pool() + 0xcd (0x7f9f4b4d70bd in /nethome/hsun409/anaconda3/envs/GDSS_env/lib/python3.7/site-packages/torch/lib/libtorch_cpu.so)
frame #5: torch::autograd::Engine::execute_with_graph_task(std::shared_ptrtorch::autograd::GraphTask const&, std::shared_ptrtorch::autograd::Node, torch::autograd::InputBuffer&&) + 0x28 (0x7f9f4b4ddf78 in /nethome/hsun409/anaconda3/envs/GDSS_env/lib/python3.7/site-packages/torch/lib/libtorch_cpu.so)
frame #6: torch::autograd::python::PythonEngine::execute_with_graph_task(std::shared_ptrtorch::autograd::GraphTask const&, std::shared_ptrtorch::autograd::Node, torch::autograd::InputBuffer&&) + 0x3c (0x7f9f5ed7ba3c in /nethome/hsun409/anaconda3/envs/GDSS_env/lib/python3.7/site-packages/torch/lib/libtorch_python.so)
frame #7: torch::autograd::Engine::execute(std::vector<torch::autograd::Edge, std::allocatortorch::autograd::Edge > const&, std::vector<at::Tensor, std::allocatorat::Tensor > const&, bool, bool, bool, std::vector<torch::autograd::Edge, std::allocatortorch::autograd::Edge > const&) + 0x900 (0x7f9f4b4dc1a0 in /nethome/hsun409/anaconda3/envs/GDSS_env/lib/python3.7/site-packages/torch/lib/libtorch_cpu.so)
frame #8: torch::autograd::python::PythonEngine::execute(std::vector<torch::autograd::Edge, std::allocatortorch::autograd::Edge > const&, std::vector<at::Tensor, std::allocatorat::Tensor > const&, bool, bool, bool, std::vector<torch::autograd::Edge, std::allocatortorch::autograd::Edge > const&) + 0x56 (0x7f9f5ed7b996 in /nethome/hsun409/anaconda3/envs/GDSS_env/lib/python3.7/site-packages/torch/lib/libtorch_python.so)
frame #9: THPEngine_run_backward(_object*, _object*, _object*) + 0x9d4 (0x7f9f5ed7c4a4 in /nethome/hsun409/anaconda3/envs/GDSS_env/lib/python3.7/site-packages/torch/lib/libtorch_python.so)

frame #31: __libc_start_main + 0xe7 (0x7f9f618a7c87 in /lib/x86_64-linux-gnu/libc.so.6)

[haotiansun14]

Update my torch to the latest version and the problem is solved.