RuntimeError: CUDA error: no kernel image is available for execution on the device

[xibian1120]

when running the code ,it appers the error as follows:

Traceback (most recent call last):
  File "./train.py", line 95, in <module>
  File "./train.y", line 78, in main
    zero_shot_evaluation(model, val_loaders, opts)
  File "/media/yxl/a/2025191008/VALOR-master/train_utils.py", line 247, in zero_shot_evaluation
    eval_log = validate(model, test_loader, opts, global_step=0, total_step=opts.num_train_steps)
  File "/media/yxl/a/2025191008/VALOR-master/test.py", line 26, in validate
    val_log = validate_single(model, loader, task.split('--')[0], opts, global_step, total_step,task.split('--')[1])
  File "/home/yxl/anaconda3/envs/valor_env/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 28, in decorate_context
    return func(*args, **kwargs)
  File "/media/yxl/a/2025191008/VALOR-master/test.py", line 40, in validate_single
    return validate_cap(model, val_loader, task, opts, global_step, dset_name)
  File "/home/yxl/anaconda3/envs/valor_env/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 28, in decorate_context
    return func(*args, **kwargs)
  File "/media/yxl/a/2025191008/VALOR-master/test.py", line 161, in validate_cap
    evaluation_dict = model(batch, task_str, compute_loss=False)
  File "/home/yxl/anaconda3/envs/valor_env/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/yxl/anaconda3/envs/valor_env/lib/python3.8/site-packages/torch/nn/parallel/distributed.py", line 799, in forward
    output = self.module(*inputs[0], **kwargs[0])
  File "/home/yxl/anaconda3/envs/valor_env/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/yxl/anaconda3/envs/valor_env/lib/python3.8/site-packages/apex/amp/_initialize.py", line 196, in new_fwd
    output = old_fwd(*applier(args, input_caster),
  File "/media/yxl/a/2025191008/VALOR-master/model/pretrain.py", line 135, in forward
    return self.forward_cap(batch, task, compute_loss=compute_loss)
  File "/media/yxl/a/2025191008/VALOR-master/model/pretrain.py", line 726, in forward_cap
    return self.generate_cap(batch, task)
  File "/media/yxl/a/2025191008/VALOR-master/model/pretrain.py", line 930, in generate_cap
    video_input = self.get_multimodal_forward_input_video(video_output) 
  File "/media/yxl/a/2025191008/VALOR-master/model/modeling.py", line 490, in get_multimodal_forward_input_video
    video_output =  video_output + self.video_frame_embedding[:,:video_output.shape[1],:].unsqueeze(-2)
RuntimeError: CUDA error: no kernel image is available for execution on the device
  0%|                                                                                                                                                      | 0/1495 [00:00<?, ?it/s]
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 15399) of binary: /home/yxl/anaconda3/envs/valor_env/bin/python
ERROR:torch.distributed.elastic.agent.server.local_elastic_agent:[default] Worker group failed

I've tried every method on the Internet but still don't solve the problem.
My environment :
_sys.platform linux
Python 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0]
numpy 1.24.4
detectron2 failed to import
detectron2._C not built correctly: No module named 'detectron2'
Compiler ($CXX) c++ (GCC) 7.3.0
CUDA compiler Build cuda_11.1.TC455_06.29190527_0
DETECTRON2_ENV_MODULE
PyTorch 1.9.0+cu111 @/home/yxl/anaconda3/envs/valor_env/lib/python3.8/site-packages/torch
PyTorch debug build False
GPU available True
GPU 0 GeForce RTX 2080 Ti (arch=7.5)
CUDA_HOME /usr/local/cuda
TORCH_CUDA_ARCH_LIST 7.5
Pillow 10.1.0
torchvision 0.10.0+cu111 @/home/yxl/anaconda3/envs/valor_env/lib/python3.8/site-packages/torchvision
torchvision arch flags 3.5, 5.0, 6.0, 7.0, 7.5, 8.0, 8.6
cv2 Not found

---

PyTorch built with:

• GCC 7.3
• C++ Version: 201402
• Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
• Intel(R) MKL-DNN v2.1.2 (Git Hash 98be7e8afa711dc9b66c8ff3504129cb82013cdb)
• OpenMP 201511 (a.k.a. OpenMP 4.5)
• NNPACK is enabled
• CPU capability usage: AVX2
• CUDA Runtime 11.1
• NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86
• CuDNN 8.0.5
• Magma 2.5.2
• Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.9.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON,_