CUDA error: CUBLAS_STATUS_EXECUTION_FAILED when calling `cublasSgemm

Branch

main branch (1.x version, such as v1.0.0, or dev-1.x branch)

Prerequisite

[X] I have searched Issues and Discussions but cannot get the expected help.
[X] I have read the documentation but cannot get the expected help.
[X] The bug has not been fixed in the latest version.

Environment

CUDA_HOME: /usr/local/cuda-11.1 NVCC: Cuda compilation tools, release 11.1, V11.1.105 GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0 PyTorch: 1.8.1+cu111 PyTorch compiling details: 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 v1.7.0 (Git Hash 7aed236906b1f7a05c0917e5257a1af05e9ff683)
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 -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=1.8.1, 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,

TorchVision: 0.9.1+cu111 OpenCV: 4.9.0 MMEngine: 0.10.3 MMAction2: 1.2.0+4d6c934 MMCV: 2.1.0

Describe the bug

Traceback (most recent call last): File "tools/train.py", line 145, in main() File "tools/train.py", line 141, in main runner.train() File "/home/miniconda3/envs/openmmlab/lib/python3.8/site-packages/mmengine/runner/runner.py", line 1777, in train model = self.train_loop.run() # type: ignore File "/home/miniconda3/envs/openmmlab/lib/python3.8/site-packages/mmengine/runner/loops.py", line 96, in run self.run_epoch() File "/home/miniconda3/envs/openmmlab/lib/python3.8/site-packages/mmengine/runner/loops.py", line 112, in run_epoch self.run_iter(idx, data_batch) File "/home/miniconda3/envs/openmmlab/lib/python3.8/site-packages/mmengine/runner/loops.py", line 128, in run_iter outputs = self.runner.model.train_step( File "/home/miniconda3/envs/openmmlab/lib/python3.8/site-packages/mmengine/model/base_model/base_model.py", line 116, in train_step optim_wrapper.update_params(parsed_losses) File "/home/miniconda3/envs/openmmlab/lib/python3.8/site-packages/mmengine/optim/optimizer/optimizer_wrapper.py", line 196, in update_params self.backward(loss) File "/home/miniconda3/envs/openmmlab/lib/python3.8/site-packages/mmengine/optim/optimizer/optimizer_wrapper.py", line 220, in backward loss.backward(**kwargs) File "/home/miniconda3/envs/openmmlab/lib/python3.8/site-packages/torch/tensor.py", line 245, in backward torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs) File "/home/miniconda3/envs/openmmlab/lib/python3.8/site-packages/torch/autograd/init.py", line 145, in backward Variable._execution_engine.run_backward( RuntimeError: CUDA error: CUBLAS_STATUS_EXECUTION_FAILED when calling cublasSgemm( handle, opa, opb, m, n, k, &alpha, a, lda, b, ldb, &beta, c, ldc)

I encountered this issue when running all three methods（mvit,timesformer,uniformerv2）

Reproduces the problem - code sample

No response

Reproduces the problem - command or script

python tools/train.py configs/recognition/mvit/mvit-small-p244_32xb16-16x4x1-200e_kinetics400-rgb.py --seed=0 --deterministic

Reproduces the problem - error message

No response

Additional information

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open-mmlab / mmaction2