A lot of warnings in instance segmentation training

[ghazni123]

If you do not know the root cause of the problem / bug, and wish someone to help you, please
post according to this template:

Instructions To Reproduce the Issue:

1. what changes you made (git diff) or what code you wrote

<put diff or code here>

2. what exact command you run:
   I have tried below command

python train_net.py --config-file ../configs/COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml --num-gpus 2 SOLVER.IMS_PER_BATCH 12 SOLVER.BASE_LR 0.005 MODEL.WEIGHTS ./imgnet_trained_model/r2_101.pkl

r2_101.pkl: file downloaded from link in this repo

However there are lots and lots of warnings. sounds like not much was loaded. please find attached for warnings
training_warnings.log

I have also tried standard command (which downloads the weights from Model.Zoo of FAIR) but the results are same.

python train_net.py --config-file ../configs/COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml --num-gpus 2 SOLVER.IMS_PER_BATCH 12 SOLVER.BASE_LR 0.005

Could you please advise? Thank you.

3. what you observed (including full logs):

<put logs here>

4. please also simplify the steps as much as possible so they do not require additional resources to
   run, such as a private dataset.

Expected behavior:

I think even with res2net backbone, the training should have started clean.

If there are no obvious error in "what you observed" provided above,
please tell us the expected behavior.

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on how to train a new model.
Only in one of the two conditions we will help with it:
(1) You're unable to reproduce the results in detectron2 model zoo.
(2) It indicates a detectron2 bug.

Environment:

Provide your environment information using the following command:

wget -nc -q https://github.com/facebookresearch/detectron2/raw/master/detectron2/utils/collect_env.py && python collect_env.py

If your issue looks like an installation issue / environment issue,
please first try to solve it yourself with the instructions in
https://github.com/facebookresearch/detectron2/blob/master/INSTALL.md#common-installation-issues

[ghazni123]

Environment:
wget -nc -q https://github.com/facebookresearch/detectron2/raw/master/detectron2/utils/collect_env.py && python collect_env.py

---

sys.platform linux
Python 3.7.8 | packaged by conda-forge | (default, Nov 17 2020, 23:45:15) [GCC 7.5.0]
numpy 1.19.2
detectron2 0.1.1 @/home/mgsaeed/sg1tb/model-factory/res2net/Res2Net-detectron2/detectron2
detectron2 compiler GCC 7.5
detectron2 CUDA compiler 10.2
detectron2 arch flags sm_75
DETECTRON2_ENV_MODULE
PyTorch 1.5.0 @/home/mgsaeed/anaconda3/envs/detectron2_res2net/lib/python3.7/site-packages/torch
PyTorch debug build False
CUDA available True
GPU 0,1 GeForce RTX 2080 Ti
CUDA_HOME /usr/local/cuda-10.2
NVCC Cuda compilation tools, release 10.2, V10.2.89
Pillow 8.0.1
torchvision 0.6.0a0+82fd1c8 @/home/mgsaeed/anaconda3/envs/detectron2_res2net/lib/python3.7/site-packages/torchvision
torchvision arch flags sm_35, sm_50, sm_60, sm_70, sm_75
fvcore 0.1.2.post20201122
cv2 4.4.0

---

PyTorch built with:

• GCC 7.3
• C++ Version: 201402
• Intel(R) Math Kernel Library Version 2020.0.2 Product Build 20200624 for Intel(R) 64 architecture applications
• Intel(R) MKL-DNN v0.21.1 (Git Hash 7d2fd500bc78936d1d648ca713b901012f470dbc)
• OpenMP 201511 (a.k.a. OpenMP 4.5)
• NNPACK is enabled
• CPU capability usage: AVX2
• CUDA Runtime 10.2
• 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_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_37,code=compute_37
• CuDNN 7.6.5
• Magma 2.5.2
• Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_INTERNAL_THREADPOOL_IMPL -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-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -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, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=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, USE_STATIC_DISPATCH=OFF,