[Bug] AssertionError: loss log variables are different across GPUs!

Prerequisite

[X] I have searched Issues and Discussions but cannot get the expected help.
[X] I have read the FAQ documentation but cannot get the expected help.
[X] The bug has not been fixed in the latest version (master) or latest version (1.x).

Task

I'm using the official example scripts/configs for the officially supported tasks/models/datasets.

Branch

master branch https://github.com/open-mmlab/mmrotate

Environment

sys.platform: linux Python: 3.8.16 (default, Jan 17 2023, 23:13:24) [GCC 11.2.0] CUDA available: True GPU 0,1,2,3,4,5,6,7: NVIDIA GeForce RTX 3090 CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 11.3, V11.3.58 GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0 PyTorch: 1.10.1+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 v2.2.3 (Git Hash 7336ca9f055cf1bfa13efb658fe15dc9b41f0740)
OpenMP 201511 (a.k.a. OpenMP 4.5)
LAPACK is enabled (usually provided by MKL)
NNPACK is enabled
CPU capability usage: AVX512
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 -DEDGE_PROFILER_USE_KINETO -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=1.10.1, 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: 0.11.2+cu111 OpenCV: 4.7.0 MMCV: 1.6.0 MMCV Compiler: GCC 7.3 MMCV CUDA Compiler: 11.1 MMRotate: 0.3.3+04da23d

Reproduces the problem - code sample

Traceback (most recent call last): File "./tools/train.py", line 192, in main() File "./tools/train.py", line 181, in main train_detector( File "/data1/code/SODA-mmrotate/mmrotate/apis/train.py", line 141, in train_detector runner.run(data_loaders, cfg.workflow) File "/home/anaconda3/envs/SODA_rotate/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 136, in run epoch_runner(data_loaders[i], kwargs) File "/home/anaconda3/envs/SODA_rotate/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 53, in train self.run_iter(data_batch, train_mode=True, kwargs) File "/home/anaconda3/envs/SODA_rotate/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 31, in run_iter outputs = self.model.train_step(data_batch, self.optimizer, File "/home/anaconda3/envs/SODA_rotate/lib/python3.8/site-packages/mmcv/parallel/distributed.py", line 63, in train_step output = self.module.train_step(*inputs[0], *kwargs[0]) File "/home/anaconda3/envs/SODA_rotate/lib/python3.8/site-packages/mmdet/models/detectors/base.py", line 249, in train_step loss, log_vars = self._parse_losses(losses) File "/home/anaconda3/envs/SODA_rotate/lib/python3.8/site-packages/mmdet/models/detectors/base.py", line 208, in _parse_losses assert log_var_length == len(log_vars) dist.get_world_size(), \ AssertionError: loss log variables are different across GPUs! rank 7 len(log_vars): 2 keys: loss_cls,loss_bbox

shaunyuan22 / SODA-mmrotate