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April 6, 2023 12:40
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0,1 | |
Command Line Args: Namespace(config_file='configs/san_clip_vit_res4_coco.yaml', dist_url='tcp://127.0.0.1:52842', eval_only=False, machine_rank=0, num_gpus=2, num_machines=1, opts=['OUTPUT_DIR', './output'], resume=False) | |
Loading config configs/Base-coco-stuff-164K-171.yaml with yaml.unsafe_load. Your machine may be at risk if the file contains malicious content. | |
Loading config configs/Base-coco-stuff-164K-171.yaml with yaml.unsafe_load. Your machine may be at risk if the file contains malicious content. | |
[32m[04/06 20:36:53 detectron2]: [0mRank of current process: 0. World size: 2 | |
[32m[04/06 20:36:55 detectron2]: [0mEnvironment info: | |
------------------------------- ------------------------------------------------------------------------------------------------------ | |
sys.platform linux | |
Python 3.8.3 (default, Jul 2 2020, 16:21:59) [GCC 7.3.0] | |
numpy 1.20.0 | |
detectron2 0.6 @/gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/detectron2 | |
Compiler GCC 8.3 | |
CUDA compiler not available | |
DETECTRON2_ENV_MODULE <not set> | |
PyTorch 1.12.1+cu113 @/gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/torch | |
PyTorch debug build False | |
torch._C._GLIBCXX_USE_CXX11_ABI False | |
GPU available Yes | |
GPU 0,1 NVIDIA A100-PCIE-40GB (arch=8.0) | |
Driver version 470.57.02 | |
CUDA_HOME /gs/home/statchao/cuda-11.3 | |
Pillow 9.1.1 | |
torchvision 0.13.1+cu113 @/gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/torchvision | |
torchvision arch flags 3.5, 5.0, 6.0, 7.0, 7.5, 8.0, 8.6 | |
fvcore 0.1.5.post20221221 | |
iopath 0.1.9 | |
cv2 4.5.1 | |
------------------------------- ------------------------------------------------------------------------------------------------------ | |
PyTorch built with: | |
- GCC 9.3 | |
- 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 v2.6.0 (Git Hash 52b5f107dd9cf10910aaa19cb47f3abf9b349815) | |
- OpenMP 201511 (a.k.a. OpenMP 4.5) | |
- LAPACK is enabled (usually provided by MKL) | |
- NNPACK is enabled | |
- CPU capability usage: AVX2 | |
- CUDA Runtime 11.3 | |
- 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 8.2.1 | |
- Built with CuDNN 8.3.2 | |
- Magma 2.5.2 | |
- Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.3.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -fabi-version=11 -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-unused-parameter -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 -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.12.1, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, | |
[32m[04/06 20:36:55 detectron2]: [0mCommand line arguments: Namespace(config_file='configs/san_clip_vit_res4_coco.yaml', dist_url='tcp://127.0.0.1:52842', eval_only=False, machine_rank=0, num_gpus=2, num_machines=1, opts=['OUTPUT_DIR', './output'], resume=False) | |
[32m[04/06 20:36:55 detectron2]: [0mContents of args.config_file=configs/san_clip_vit_res4_coco.yaml: | |
[38;5;197m_BASE_[39m[38;5;15m:[39m[38;5;15m [39mBase-coco-stuff-164K-171.yaml | |
[38;5;197mMODEL[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mMETA_ARCHITECTURE[39m[38;5;15m:[39m[38;5;15m [39m[38;5;186m"[39m[38;5;186mSAN[39m[38;5;186m"[39m | |
[38;5;197mSOLVER[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mBACKBONE_MULTIPLIER[39m[38;5;15m:[39m[38;5;15m [39m1.0 | |
[32m[04/06 20:36:55 detectron2]: [0mRunning with full config: | |
[38;5;197mCUDNN_BENCHMARK[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;197mDATALOADER[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mASPECT_RATIO_GROUPING[39m[38;5;15m:[39m[38;5;15m [39mtrue | |
[38;5;15m [39m[38;5;197mFILTER_EMPTY_ANNOTATIONS[39m[38;5;15m:[39m[38;5;15m [39mtrue | |
[38;5;15m [39m[38;5;197mNUM_WORKERS[39m[38;5;15m:[39m[38;5;15m [39m2 | |
[38;5;15m [39m[38;5;197mREPEAT_THRESHOLD[39m[38;5;15m:[39m[38;5;15m [39m0.0 | |
[38;5;15m [39m[38;5;197mSAMPLER_TRAIN[39m[38;5;15m:[39m[38;5;15m [39mTrainingSampler | |
[38;5;197mDATASETS[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mPRECOMPUTED_PROPOSAL_TOPK_TEST[39m[38;5;15m:[39m[38;5;15m [39m1000 | |
[38;5;15m [39m[38;5;197mPRECOMPUTED_PROPOSAL_TOPK_TRAIN[39m[38;5;15m:[39m[38;5;15m [39m2000 | |
[38;5;15m [39m[38;5;197mPROPOSAL_FILES_TEST[39m[38;5;15m:[39m[38;5;15m [39m[] | |
[38;5;15m [39m[38;5;197mPROPOSAL_FILES_TRAIN[39m[38;5;15m:[39m[38;5;15m [39m[] | |
[38;5;15m [39m[38;5;197mTEST[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39mcoco_2017_test_stuff_sem_seg | |
[38;5;15m [39m-[38;5;15m [39mpcontext_sem_seg_val | |
[38;5;15m [39m[38;5;197mTRAIN[39m[38;5;15m:[39m | |
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[38;5;15m [39m[38;5;197mASPECT_RATIOS[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m-[38;5;15m [39m0.5 | |
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[38;5;15m [39m[38;5;197mNAME[39m[38;5;15m:[39m[38;5;15m [39mDefaultAnchorGenerator | |
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[38;5;15m [39m-[38;5;15m [39m512 | |
[38;5;15m [39m[38;5;197mBACKBONE[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mFREEZE_AT[39m[38;5;15m:[39m[38;5;15m [39m2 | |
[38;5;15m [39m[38;5;197mNAME[39m[38;5;15m:[39m[38;5;15m [39mbuild_resnet_backbone | |
[38;5;15m [39m[38;5;197mDEVICE[39m[38;5;15m:[39m[38;5;15m [39mcuda | |
[38;5;15m [39m[38;5;197mFLASH[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
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[38;5;15m [39m[38;5;197mIN_FEATURES[39m[38;5;15m:[39m[38;5;15m [39m[] | |
[38;5;15m [39m[38;5;197mNORM[39m[38;5;15m:[39m[38;5;15m [39m[38;5;186m'[39m[38;5;186m'[39m | |
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[38;5;15m [39m[38;5;197mMETA_ARCHITECTURE[39m[38;5;15m:[39m[38;5;15m [39mSAN | |
[38;5;15m [39m[38;5;197mPANOPTIC_FPN[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mCOMBINE[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mENABLED[39m[38;5;15m:[39m[38;5;15m [39mtrue | |
[38;5;15m [39m[38;5;197mINSTANCES_CONFIDENCE_THRESH[39m[38;5;15m:[39m[38;5;15m [39m0.5 | |
[38;5;15m [39m[38;5;197mOVERLAP_THRESH[39m[38;5;15m:[39m[38;5;15m [39m0.5 | |
[38;5;15m [39m[38;5;197mSTUFF_AREA_LIMIT[39m[38;5;15m:[39m[38;5;15m [39m4096 | |
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[38;5;15m [39m[38;5;197mPIXEL_MEAN[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m103.53 | |
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[38;5;15m [39m[38;5;197mPROPOSAL_GENERATOR[39m[38;5;15m:[39m | |
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[38;5;15m [39m[38;5;197mNAME[39m[38;5;15m:[39m[38;5;15m [39mRPN | |
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[38;5;15m [39m[38;5;197mDEFORM_MODULATED[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;15m [39m[38;5;197mDEFORM_NUM_GROUPS[39m[38;5;15m:[39m[38;5;15m [39m1 | |
[38;5;15m [39m[38;5;197mDEFORM_ON_PER_STAGE[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39mfalse | |
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[38;5;15m [39m-[38;5;15m [39mres4 | |
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[38;5;15m [39m[38;5;197mRES4_DILATION[39m[38;5;15m:[39m[38;5;15m [39m1 | |
[38;5;15m [39m[38;5;197mRES5_DILATION[39m[38;5;15m:[39m[38;5;15m [39m1 | |
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[38;5;15m [39m[38;5;197mSTRIDE_IN_1X1[39m[38;5;15m:[39m[38;5;15m [39mtrue | |
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[38;5;15m [39m[38;5;197mRETINANET[39m[38;5;15m:[39m | |
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[38;5;15m [39m[38;5;197mFOCAL_LOSS_ALPHA[39m[38;5;15m:[39m[38;5;15m [39m0.25 | |
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[38;5;15m [39m[38;5;197mPRIOR_PROB[39m[38;5;15m:[39m[38;5;15m [39m0.01 | |
[38;5;15m [39m[38;5;197mSCORE_THRESH_TEST[39m[38;5;15m:[39m[38;5;15m [39m0.05 | |
[38;5;15m [39m[38;5;197mSMOOTH_L1_LOSS_BETA[39m[38;5;15m:[39m[38;5;15m [39m0.1 | |
[38;5;15m [39m[38;5;197mTOPK_CANDIDATES_TEST[39m[38;5;15m:[39m[38;5;15m [39m1000 | |
[38;5;15m [39m[38;5;197mROI_BOX_CASCADE_HEAD[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mBBOX_REG_WEIGHTS[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m[38;5;15m&id001[39m | |
[38;5;15m [39m-[38;5;15m [39m10.0 | |
[38;5;15m [39m-[38;5;15m [39m10.0 | |
[38;5;15m [39m-[38;5;15m [39m5.0 | |
[38;5;15m [39m-[38;5;15m [39m5.0 | |
[38;5;15m [39m-[38;5;15m [39m-[38;5;15m [39m20.0 | |
[38;5;15m [39m-[38;5;15m [39m20.0 | |
[38;5;15m [39m-[38;5;15m [39m10.0 | |
[38;5;15m [39m-[38;5;15m [39m10.0 | |
[38;5;15m [39m-[38;5;15m [39m-[38;5;15m [39m30.0 | |
[38;5;15m [39m-[38;5;15m [39m30.0 | |
[38;5;15m [39m-[38;5;15m [39m15.0 | |
[38;5;15m [39m-[38;5;15m [39m15.0 | |
[38;5;15m [39m[38;5;197mIOUS[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m0.5 | |
[38;5;15m [39m-[38;5;15m [39m0.6 | |
[38;5;15m [39m-[38;5;15m [39m0.7 | |
[38;5;15m [39m[38;5;197mROI_BOX_HEAD[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mBBOX_REG_LOSS_TYPE[39m[38;5;15m:[39m[38;5;15m [39msmooth_l1 | |
[38;5;15m [39m[38;5;197mBBOX_REG_LOSS_WEIGHT[39m[38;5;15m:[39m[38;5;15m [39m1.0 | |
[38;5;15m [39m[38;5;197mBBOX_REG_WEIGHTS[39m[38;5;15m:[39m[38;5;15m [39m[38;5;15m*id001[39m | |
[38;5;15m [39m[38;5;197mCLS_AGNOSTIC_BBOX_REG[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;15m [39m[38;5;197mCONV_DIM[39m[38;5;15m:[39m[38;5;15m [39m256 | |
[38;5;15m [39m[38;5;197mFC_DIM[39m[38;5;15m:[39m[38;5;15m [39m1024 | |
[38;5;15m [39m[38;5;197mFED_LOSS_FREQ_WEIGHT_POWER[39m[38;5;15m:[39m[38;5;15m [39m0.5 | |
[38;5;15m [39m[38;5;197mFED_LOSS_NUM_CLASSES[39m[38;5;15m:[39m[38;5;15m [39m50 | |
[38;5;15m [39m[38;5;197mNAME[39m[38;5;15m:[39m[38;5;15m [39m[38;5;186m'[39m[38;5;186m'[39m | |
[38;5;15m [39m[38;5;197mNORM[39m[38;5;15m:[39m[38;5;15m [39m[38;5;186m'[39m[38;5;186m'[39m | |
[38;5;15m [39m[38;5;197mNUM_CONV[39m[38;5;15m:[39m[38;5;15m [39m0 | |
[38;5;15m [39m[38;5;197mNUM_FC[39m[38;5;15m:[39m[38;5;15m [39m0 | |
[38;5;15m [39m[38;5;197mPOOLER_RESOLUTION[39m[38;5;15m:[39m[38;5;15m [39m14 | |
[38;5;15m [39m[38;5;197mPOOLER_SAMPLING_RATIO[39m[38;5;15m:[39m[38;5;15m [39m0 | |
[38;5;15m [39m[38;5;197mPOOLER_TYPE[39m[38;5;15m:[39m[38;5;15m [39mROIAlignV2 | |
[38;5;15m [39m[38;5;197mSMOOTH_L1_BETA[39m[38;5;15m:[39m[38;5;15m [39m0.0 | |
[38;5;15m [39m[38;5;197mTRAIN_ON_PRED_BOXES[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;15m [39m[38;5;197mUSE_FED_LOSS[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;15m [39m[38;5;197mUSE_SIGMOID_CE[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;15m [39m[38;5;197mROI_HEADS[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mBATCH_SIZE_PER_IMAGE[39m[38;5;15m:[39m[38;5;15m [39m512 | |
[38;5;15m [39m[38;5;197mIN_FEATURES[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39mres4 | |
[38;5;15m [39m[38;5;197mIOU_LABELS[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m0 | |
[38;5;15m [39m-[38;5;15m [39m1 | |
[38;5;15m [39m[38;5;197mIOU_THRESHOLDS[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m0.5 | |
[38;5;15m [39m[38;5;197mNAME[39m[38;5;15m:[39m[38;5;15m [39mRes5ROIHeads | |
[38;5;15m [39m[38;5;197mNMS_THRESH_TEST[39m[38;5;15m:[39m[38;5;15m [39m0.5 | |
[38;5;15m [39m[38;5;197mNUM_CLASSES[39m[38;5;15m:[39m[38;5;15m [39m80 | |
[38;5;15m [39m[38;5;197mPOSITIVE_FRACTION[39m[38;5;15m:[39m[38;5;15m [39m0.25 | |
[38;5;15m [39m[38;5;197mPROPOSAL_APPEND_GT[39m[38;5;15m:[39m[38;5;15m [39mtrue | |
[38;5;15m [39m[38;5;197mSCORE_THRESH_TEST[39m[38;5;15m:[39m[38;5;15m [39m0.05 | |
[38;5;15m [39m[38;5;197mROI_KEYPOINT_HEAD[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mCONV_DIMS[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m512 | |
[38;5;15m [39m-[38;5;15m [39m512 | |
[38;5;15m [39m-[38;5;15m [39m512 | |
[38;5;15m [39m-[38;5;15m [39m512 | |
[38;5;15m [39m-[38;5;15m [39m512 | |
[38;5;15m [39m-[38;5;15m [39m512 | |
[38;5;15m [39m-[38;5;15m [39m512 | |
[38;5;15m [39m-[38;5;15m [39m512 | |
[38;5;15m [39m[38;5;197mLOSS_WEIGHT[39m[38;5;15m:[39m[38;5;15m [39m1.0 | |
[38;5;15m [39m[38;5;197mMIN_KEYPOINTS_PER_IMAGE[39m[38;5;15m:[39m[38;5;15m [39m1 | |
[38;5;15m [39m[38;5;197mNAME[39m[38;5;15m:[39m[38;5;15m [39mKRCNNConvDeconvUpsampleHead | |
[38;5;15m [39m[38;5;197mNORMALIZE_LOSS_BY_VISIBLE_KEYPOINTS[39m[38;5;15m:[39m[38;5;15m [39mtrue | |
[38;5;15m [39m[38;5;197mNUM_KEYPOINTS[39m[38;5;15m:[39m[38;5;15m [39m17 | |
[38;5;15m [39m[38;5;197mPOOLER_RESOLUTION[39m[38;5;15m:[39m[38;5;15m [39m14 | |
[38;5;15m [39m[38;5;197mPOOLER_SAMPLING_RATIO[39m[38;5;15m:[39m[38;5;15m [39m0 | |
[38;5;15m [39m[38;5;197mPOOLER_TYPE[39m[38;5;15m:[39m[38;5;15m [39mROIAlignV2 | |
[38;5;15m [39m[38;5;197mROI_MASK_HEAD[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mCLS_AGNOSTIC_MASK[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;15m [39m[38;5;197mCONV_DIM[39m[38;5;15m:[39m[38;5;15m [39m256 | |
[38;5;15m [39m[38;5;197mNAME[39m[38;5;15m:[39m[38;5;15m [39mMaskRCNNConvUpsampleHead | |
[38;5;15m [39m[38;5;197mNORM[39m[38;5;15m:[39m[38;5;15m [39m[38;5;186m'[39m[38;5;186m'[39m | |
[38;5;15m [39m[38;5;197mNUM_CONV[39m[38;5;15m:[39m[38;5;15m [39m0 | |
[38;5;15m [39m[38;5;197mPOOLER_RESOLUTION[39m[38;5;15m:[39m[38;5;15m [39m14 | |
[38;5;15m [39m[38;5;197mPOOLER_SAMPLING_RATIO[39m[38;5;15m:[39m[38;5;15m [39m0 | |
[38;5;15m [39m[38;5;197mPOOLER_TYPE[39m[38;5;15m:[39m[38;5;15m [39mROIAlignV2 | |
[38;5;15m [39m[38;5;197mRPN[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mBATCH_SIZE_PER_IMAGE[39m[38;5;15m:[39m[38;5;15m [39m256 | |
[38;5;15m [39m[38;5;197mBBOX_REG_LOSS_TYPE[39m[38;5;15m:[39m[38;5;15m [39msmooth_l1 | |
[38;5;15m [39m[38;5;197mBBOX_REG_LOSS_WEIGHT[39m[38;5;15m:[39m[38;5;15m [39m1.0 | |
[38;5;15m [39m[38;5;197mBBOX_REG_WEIGHTS[39m[38;5;15m:[39m[38;5;15m [39m[38;5;15m*id002[39m | |
[38;5;15m [39m[38;5;197mBOUNDARY_THRESH[39m[38;5;15m:[39m[38;5;15m [39m-1 | |
[38;5;15m [39m[38;5;197mCONV_DIMS[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m-1 | |
[38;5;15m [39m[38;5;197mHEAD_NAME[39m[38;5;15m:[39m[38;5;15m [39mStandardRPNHead | |
[38;5;15m [39m[38;5;197mIN_FEATURES[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39mres4 | |
[38;5;15m [39m[38;5;197mIOU_LABELS[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m0 | |
[38;5;15m [39m-[38;5;15m [39m-1 | |
[38;5;15m [39m-[38;5;15m [39m1 | |
[38;5;15m [39m[38;5;197mIOU_THRESHOLDS[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m0.3 | |
[38;5;15m [39m-[38;5;15m [39m0.7 | |
[38;5;15m [39m[38;5;197mLOSS_WEIGHT[39m[38;5;15m:[39m[38;5;15m [39m1.0 | |
[38;5;15m [39m[38;5;197mNMS_THRESH[39m[38;5;15m:[39m[38;5;15m [39m0.7 | |
[38;5;15m [39m[38;5;197mPOSITIVE_FRACTION[39m[38;5;15m:[39m[38;5;15m [39m0.5 | |
[38;5;15m [39m[38;5;197mPOST_NMS_TOPK_TEST[39m[38;5;15m:[39m[38;5;15m [39m1000 | |
[38;5;15m [39m[38;5;197mPOST_NMS_TOPK_TRAIN[39m[38;5;15m:[39m[38;5;15m [39m2000 | |
[38;5;15m [39m[38;5;197mPRE_NMS_TOPK_TEST[39m[38;5;15m:[39m[38;5;15m [39m6000 | |
[38;5;15m [39m[38;5;197mPRE_NMS_TOPK_TRAIN[39m[38;5;15m:[39m[38;5;15m [39m12000 | |
[38;5;15m [39m[38;5;197mSMOOTH_L1_BETA[39m[38;5;15m:[39m[38;5;15m [39m0.0 | |
[38;5;15m [39m[38;5;197mSAN[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mASYMETRIC_INPUT[39m[38;5;15m:[39m[38;5;15m [39mtrue | |
[38;5;15m [39m[38;5;197mCLASS_WEIGHT[39m[38;5;15m:[39m[38;5;15m [39m2.0 | |
[38;5;15m [39m[38;5;197mCLIP_DEEPER_FROZEN_EXCLUDE[39m[38;5;15m:[39m[38;5;15m [39m[] | |
[38;5;15m [39m[38;5;197mCLIP_FROZEN_EXCLUDE[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39mpositional_embedding | |
[38;5;15m [39m[38;5;197mCLIP_MODEL_NAME[39m[38;5;15m:[39m[38;5;15m [39mViT-B/16 | |
[38;5;15m [39m[38;5;197mCLIP_PRETRAINED_NAME[39m[38;5;15m:[39m[38;5;15m [39mopenai | |
[38;5;15m [39m[38;5;197mCLIP_RESOLUTION[39m[38;5;15m:[39m[38;5;15m [39m0.5 | |
[38;5;15m [39m[38;5;197mCLIP_TEMPLATE_SET[39m[38;5;15m:[39m[38;5;15m [39mvild | |
[38;5;15m [39m[38;5;197mDICE_WEIGHT[39m[38;5;15m:[39m[38;5;15m [39m5.0 | |
[38;5;15m [39m[38;5;197mFEATURE_LAST_LAYER_IDX[39m[38;5;15m:[39m[38;5;15m [39m9 | |
[38;5;15m [39m[38;5;197mIMPORTANCE_SAMPLE_RATIO[39m[38;5;15m:[39m[38;5;15m [39m0.75 | |
[38;5;15m [39m[38;5;197mMASK_WEIGHT[39m[38;5;15m:[39m[38;5;15m [39m5.0 | |
[38;5;15m [39m[38;5;197mNO_OBJECT_WEIGHT[39m[38;5;15m:[39m[38;5;15m [39m0.1 | |
[38;5;15m [39m[38;5;197mNUM_CLASSES[39m[38;5;15m:[39m[38;5;15m [39m171 | |
[38;5;15m [39m[38;5;197mOVERSAMPLE_RATIO[39m[38;5;15m:[39m[38;5;15m [39m3.0 | |
[38;5;15m [39m[38;5;197mREC_CROSS_ATTN[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;15m [39m[38;5;197mREC_DOWNSAMPLE_METHOD[39m[38;5;15m:[39m[38;5;15m [39mmax | |
[38;5;15m [39m[38;5;197mSEM_SEG_POSTPROCESS_BEFORE_INFERENCE[39m[38;5;15m:[39m[38;5;15m [39mtrue | |
[38;5;15m [39m[38;5;197mSIZE_DIVISIBILITY[39m[38;5;15m:[39m[38;5;15m [39m32 | |
[38;5;15m [39m[38;5;197mSOS_TOKEN_FORMAT[39m[38;5;15m:[39m[38;5;15m [39mcls_token | |
[38;5;15m [39m[38;5;197mTRAIN_NUM_POINTS[39m[38;5;15m:[39m[38;5;15m [39m12544 | |
[38;5;15m [39m[38;5;197mSEM_SEG_HEAD[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mASPP_CHANNELS[39m[38;5;15m:[39m[38;5;15m [39m256 | |
[38;5;15m [39m[38;5;197mASPP_DILATIONS[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m6 | |
[38;5;15m [39m-[38;5;15m [39m12 | |
[38;5;15m [39m-[38;5;15m [39m18 | |
[38;5;15m [39m[38;5;197mASPP_DROPOUT[39m[38;5;15m:[39m[38;5;15m [39m0.1 | |
[38;5;15m [39m[38;5;197mCOMMON_STRIDE[39m[38;5;15m:[39m[38;5;15m [39m4 | |
[38;5;15m [39m[38;5;197mCONVS_DIM[39m[38;5;15m:[39m[38;5;15m [39m128 | |
[38;5;15m [39m[38;5;197mIGNORE_VALUE[39m[38;5;15m:[39m[38;5;15m [39m255 | |
[38;5;15m [39m[38;5;197mIN_FEATURES[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39mp2 | |
[38;5;15m [39m-[38;5;15m [39mp3 | |
[38;5;15m [39m-[38;5;15m [39mp4 | |
[38;5;15m [39m-[38;5;15m [39mp5 | |
[38;5;15m [39m[38;5;197mLOSS_TYPE[39m[38;5;15m:[39m[38;5;15m [39mhard_pixel_mining | |
[38;5;15m [39m[38;5;197mLOSS_WEIGHT[39m[38;5;15m:[39m[38;5;15m [39m1.0 | |
[38;5;15m [39m[38;5;197mNAME[39m[38;5;15m:[39m[38;5;15m [39mSemSegFPNHead | |
[38;5;15m [39m[38;5;197mNORM[39m[38;5;15m:[39m[38;5;15m [39mGN | |
[38;5;15m [39m[38;5;197mNUM_CLASSES[39m[38;5;15m:[39m[38;5;15m [39m54 | |
[38;5;15m [39m[38;5;197mPROJECT_CHANNELS[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m48 | |
[38;5;15m [39m[38;5;197mPROJECT_FEATURES[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39mres2 | |
[38;5;15m [39m[38;5;197mUSE_DEPTHWISE_SEPARABLE_CONV[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;15m [39m[38;5;197mSIDE_ADAPTER[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mATTN_BIAS[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mEMBED_CHANNELS[39m[38;5;15m:[39m[38;5;15m [39m256 | |
[38;5;15m [39m[38;5;197mMLP_CHANNELS[39m[38;5;15m:[39m[38;5;15m [39m256 | |
[38;5;15m [39m[38;5;197mMLP_NUM_LAYERS[39m[38;5;15m:[39m[38;5;15m [39m3 | |
[38;5;15m [39m[38;5;197mNUM_HEADS[39m[38;5;15m:[39m[38;5;15m [39m12 | |
[38;5;15m [39m[38;5;197mNUM_LAYERS[39m[38;5;15m:[39m[38;5;15m [39m1 | |
[38;5;15m [39m[38;5;197mRESCALE_ATTN_BIAS[39m[38;5;15m:[39m[38;5;15m [39mtrue | |
[38;5;15m [39m[38;5;197mDEEP_SUPERVISION_IDXS[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m7 | |
[38;5;15m [39m-[38;5;15m [39m8 | |
[38;5;15m [39m[38;5;197mDROP_PATH_RATE[39m[38;5;15m:[39m[38;5;15m [39m0.0 | |
[38;5;15m [39m[38;5;197mFUSION_MAP[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m0->0 | |
[38;5;15m [39m-[38;5;15m [39m3->1 | |
[38;5;15m [39m-[38;5;15m [39m6->2 | |
[38;5;15m [39m-[38;5;15m [39m9->3 | |
[38;5;15m [39m[38;5;197mFUSION_TYPE[39m[38;5;15m:[39m[38;5;15m [39madd | |
[38;5;15m [39m[38;5;197mIMAGE_SIZE[39m[38;5;15m:[39m[38;5;15m [39m640 | |
[38;5;15m [39m[38;5;197mNAME[39m[38;5;15m:[39m[38;5;15m [39mRegionwiseSideAdapterNetwork | |
[38;5;15m [39m[38;5;197mNUM_QUERIES[39m[38;5;15m:[39m[38;5;15m [39m100 | |
[38;5;15m [39m[38;5;197mPRETRAINED[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;15m [39m[38;5;197mVIT_NAME[39m[38;5;15m:[39m[38;5;15m [39mvit_w240n6d8_patch16 | |
[38;5;15m [39m[38;5;197mWEIGHTS[39m[38;5;15m:[39m[38;5;15m [39m[38;5;186m'[39m[38;5;186m'[39m | |
[38;5;197mOUTPUT_DIR[39m[38;5;15m:[39m[38;5;15m [39m./output | |
[38;5;197mSEED[39m[38;5;15m:[39m[38;5;15m [39m-1 | |
[38;5;197mSOLVER[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mAMP[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mENABLED[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;15m [39m[38;5;197mBACKBONE_MULTIPLIER[39m[38;5;15m:[39m[38;5;15m [39m1.0 | |
[38;5;15m [39m[38;5;197mBASE_LR[39m[38;5;15m:[39m[38;5;15m [39m0.0001 | |
[38;5;15m [39m[38;5;197mBASE_LR_END[39m[38;5;15m:[39m[38;5;15m [39m0.0 | |
[38;5;15m [39m[38;5;197mBIAS_LR_FACTOR[39m[38;5;15m:[39m[38;5;15m [39m1.0 | |
[38;5;15m [39m[38;5;197mCHECKPOINT_PERIOD[39m[38;5;15m:[39m[38;5;15m [39m5000 | |
[38;5;15m [39m[38;5;197mCLIP_GRADIENTS[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mCLIP_TYPE[39m[38;5;15m:[39m[38;5;15m [39mfull_model | |
[38;5;15m [39m[38;5;197mCLIP_VALUE[39m[38;5;15m:[39m[38;5;15m [39m0.01 | |
[38;5;15m [39m[38;5;197mENABLED[39m[38;5;15m:[39m[38;5;15m [39mtrue | |
[38;5;15m [39m[38;5;197mNORM_TYPE[39m[38;5;15m:[39m[38;5;15m [39m2.0 | |
[38;5;15m [39m[38;5;197mCLIP_MULTIPLIER[39m[38;5;15m:[39m[38;5;15m [39m1.0 | |
[38;5;15m [39m[38;5;197mGAMMA[39m[38;5;15m:[39m[38;5;15m [39m0.1 | |
[38;5;15m [39m[38;5;197mIMS_PER_BATCH[39m[38;5;15m:[39m[38;5;15m [39m4 | |
[38;5;15m [39m[38;5;197mLR_SCHEDULER_NAME[39m[38;5;15m:[39m[38;5;15m [39mWarmupPolyLR | |
[38;5;15m [39m[38;5;197mMAX_ITER[39m[38;5;15m:[39m[38;5;15m [39m60000 | |
[38;5;15m [39m[38;5;197mMOMENTUM[39m[38;5;15m:[39m[38;5;15m [39m0.9 | |
[38;5;15m [39m[38;5;197mNESTEROV[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;15m [39m[38;5;197mNUM_DECAYS[39m[38;5;15m:[39m[38;5;15m [39m3 | |
[38;5;15m [39m[38;5;197mOPTIMIZER[39m[38;5;15m:[39m[38;5;15m [39mADAMW | |
[38;5;15m [39m[38;5;197mPOLY_LR_CONSTANT_ENDING[39m[38;5;15m:[39m[38;5;15m [39m0.0 | |
[38;5;15m [39m[38;5;197mPOLY_LR_POWER[39m[38;5;15m:[39m[38;5;15m [39m0.9 | |
[38;5;15m [39m[38;5;197mREFERENCE_WORLD_SIZE[39m[38;5;15m:[39m[38;5;15m [39m0 | |
[38;5;15m [39m[38;5;197mRESCALE_INTERVAL[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;15m [39m[38;5;197mSTEPS[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m30000 | |
[38;5;15m [39m[38;5;197mTEST_IMS_PER_BATCH[39m[38;5;15m:[39m[38;5;15m [39m1 | |
[38;5;15m [39m[38;5;197mWARMUP_FACTOR[39m[38;5;15m:[39m[38;5;15m [39m1.0 | |
[38;5;15m [39m[38;5;197mWARMUP_ITERS[39m[38;5;15m:[39m[38;5;15m [39m0 | |
[38;5;15m [39m[38;5;197mWARMUP_METHOD[39m[38;5;15m:[39m[38;5;15m [39mlinear | |
[38;5;15m [39m[38;5;197mWEIGHT_DECAY[39m[38;5;15m:[39m[38;5;15m [39m0.0001 | |
[38;5;15m [39m[38;5;197mWEIGHT_DECAY_BIAS[39m[38;5;15m:[39m[38;5;15m [39mnull | |
[38;5;15m [39m[38;5;197mWEIGHT_DECAY_EMBED[39m[38;5;15m:[39m[38;5;15m [39m0.0 | |
[38;5;15m [39m[38;5;197mWEIGHT_DECAY_EMBED_GROUP[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39mabsolute_pos_embed | |
[38;5;15m [39m-[38;5;15m [39mpositional_embedding | |
[38;5;15m [39m-[38;5;15m [39mpos_embed | |
[38;5;15m [39m-[38;5;15m [39mquery_embed | |
[38;5;15m [39m-[38;5;15m [39mrelative_position_bias_table | |
[38;5;15m [39m[38;5;197mWEIGHT_DECAY_NORM[39m[38;5;15m:[39m[38;5;15m [39m0.0 | |
[38;5;197mTEST[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mAUG[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mENABLED[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;15m [39m[38;5;197mFLIP[39m[38;5;15m:[39m[38;5;15m [39mtrue | |
[38;5;15m [39m[38;5;197mMAX_SIZE[39m[38;5;15m:[39m[38;5;15m [39m4480 | |
[38;5;15m [39m[38;5;197mMIN_SIZES[39m[38;5;15m:[39m | |
[38;5;15m [39m-[38;5;15m [39m320 | |
[38;5;15m [39m-[38;5;15m [39m480 | |
[38;5;15m [39m-[38;5;15m [39m640 | |
[38;5;15m [39m-[38;5;15m [39m800 | |
[38;5;15m [39m-[38;5;15m [39m960 | |
[38;5;15m [39m-[38;5;15m [39m1120 | |
[38;5;15m [39m[38;5;197mDETECTIONS_PER_IMAGE[39m[38;5;15m:[39m[38;5;15m [39m100 | |
[38;5;15m [39m[38;5;197mEVAL_PERIOD[39m[38;5;15m:[39m[38;5;15m [39m5000 | |
[38;5;15m [39m[38;5;197mEXPECTED_RESULTS[39m[38;5;15m:[39m[38;5;15m [39m[] | |
[38;5;15m [39m[38;5;197mKEYPOINT_OKS_SIGMAS[39m[38;5;15m:[39m[38;5;15m [39m[] | |
[38;5;15m [39m[38;5;197mPRECISE_BN[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mENABLED[39m[38;5;15m:[39m[38;5;15m [39mfalse | |
[38;5;15m [39m[38;5;197mNUM_ITER[39m[38;5;15m:[39m[38;5;15m [39m200 | |
[38;5;197mVERSION[39m[38;5;15m:[39m[38;5;15m [39m2 | |
[38;5;197mVIS_PERIOD[39m[38;5;15m:[39m[38;5;15m [39m0 | |
[38;5;197mWANDB[39m[38;5;15m:[39m | |
[38;5;15m [39m[38;5;197mNAME[39m[38;5;15m:[39m[38;5;15m [39mnull | |
[38;5;15m [39m[38;5;197mPROJECT[39m[38;5;15m:[39m[38;5;15m [39moseg_1111 | |
[32m[04/06 20:36:55 detectron2]: [0mFull config saved to ./output/config.yaml | |
[32m[04/06 20:36:56 d2.utils.env]: [0mUsing a generated random seed 56317096 | |
WARNING:timm.models.helpers:No pretrained configuration specified for vit_tiny_patch16_224.augreg_in21k model. Using a default. Please add a config to the model pretrained_cfg registry or pass explicitly. | |
WARNING:timm.models.helpers:No pretrained configuration specified for vit_tiny_patch16_224.augreg_in21k model. Using a default. Please add a config to the model pretrained_cfg registry or pass explicitly. | |
[32m[04/06 20:37:02 d2.engine.defaults]: [0mModel: | |
SAN( | |
(criterion): Criterion SetCriterion | |
matcher: Matcher HungarianMatcher | |
cost_class: 2.0 | |
cost_mask: 5.0 | |
cost_dice: 5.0 | |
losses: ['labels', 'masks'] | |
weight_dict: {'loss_ce': 2.0, 'loss_mask': 5.0, 'loss_dice': 5.0, 'loss_ce_0': 2.0, 'loss_mask_0': 5.0, 'loss_dice_0': 5.0} | |
num_classes: 171 | |
eos_coef: 0.1 | |
num_points: 12544 | |
oversample_ratio: 3.0 | |
importance_sample_ratio: 0.75 | |
(side_adapter_network): RegionwiseSideAdapterNetwork( | |
(vit_model): VisionTransformer( | |
(patch_embed): PatchEmbed( | |
(proj): Conv2d(3, 240, kernel_size=(16, 16), stride=(16, 16)) | |
(norm): Identity() | |
) | |
(pos_drop): Dropout(p=0.0, inplace=False) | |
(norm_pre): Identity() | |
(blocks): Sequential( | |
(0): Block( | |
(norm1): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(attn): Attention( | |
(qkv): Linear(in_features=240, out_features=720, bias=True) | |
(attn_drop): Dropout(p=0.0, inplace=False) | |
(proj): Linear(in_features=240, out_features=240, bias=True) | |
(proj_drop): Dropout(p=0.0, inplace=False) | |
) | |
(ls1): Identity() | |
(drop_path1): Identity() | |
(norm2): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(mlp): Mlp( | |
(fc1): Linear(in_features=240, out_features=960, bias=True) | |
(act): GELU(approximate=none) | |
(drop1): Dropout(p=0.0, inplace=False) | |
(fc2): Linear(in_features=960, out_features=240, bias=True) | |
(drop2): Dropout(p=0.0, inplace=False) | |
) | |
(ls2): Identity() | |
(drop_path2): Identity() | |
) | |
(1): Block( | |
(norm1): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(attn): Attention( | |
(qkv): Linear(in_features=240, out_features=720, bias=True) | |
(attn_drop): Dropout(p=0.0, inplace=False) | |
(proj): Linear(in_features=240, out_features=240, bias=True) | |
(proj_drop): Dropout(p=0.0, inplace=False) | |
) | |
(ls1): Identity() | |
(drop_path1): Identity() | |
(norm2): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(mlp): Mlp( | |
(fc1): Linear(in_features=240, out_features=960, bias=True) | |
(act): GELU(approximate=none) | |
(drop1): Dropout(p=0.0, inplace=False) | |
(fc2): Linear(in_features=960, out_features=240, bias=True) | |
(drop2): Dropout(p=0.0, inplace=False) | |
) | |
(ls2): Identity() | |
(drop_path2): Identity() | |
) | |
(2): Block( | |
(norm1): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(attn): Attention( | |
(qkv): Linear(in_features=240, out_features=720, bias=True) | |
(attn_drop): Dropout(p=0.0, inplace=False) | |
(proj): Linear(in_features=240, out_features=240, bias=True) | |
(proj_drop): Dropout(p=0.0, inplace=False) | |
) | |
(ls1): Identity() | |
(drop_path1): Identity() | |
(norm2): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(mlp): Mlp( | |
(fc1): Linear(in_features=240, out_features=960, bias=True) | |
(act): GELU(approximate=none) | |
(drop1): Dropout(p=0.0, inplace=False) | |
(fc2): Linear(in_features=960, out_features=240, bias=True) | |
(drop2): Dropout(p=0.0, inplace=False) | |
) | |
(ls2): Identity() | |
(drop_path2): Identity() | |
) | |
(3): Block( | |
(norm1): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(attn): Attention( | |
(qkv): Linear(in_features=240, out_features=720, bias=True) | |
(attn_drop): Dropout(p=0.0, inplace=False) | |
(proj): Linear(in_features=240, out_features=240, bias=True) | |
(proj_drop): Dropout(p=0.0, inplace=False) | |
) | |
(ls1): Identity() | |
(drop_path1): Identity() | |
(norm2): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(mlp): Mlp( | |
(fc1): Linear(in_features=240, out_features=960, bias=True) | |
(act): GELU(approximate=none) | |
(drop1): Dropout(p=0.0, inplace=False) | |
(fc2): Linear(in_features=960, out_features=240, bias=True) | |
(drop2): Dropout(p=0.0, inplace=False) | |
) | |
(ls2): Identity() | |
(drop_path2): Identity() | |
) | |
(4): Block( | |
(norm1): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(attn): Attention( | |
(qkv): Linear(in_features=240, out_features=720, bias=True) | |
(attn_drop): Dropout(p=0.0, inplace=False) | |
(proj): Linear(in_features=240, out_features=240, bias=True) | |
(proj_drop): Dropout(p=0.0, inplace=False) | |
) | |
(ls1): Identity() | |
(drop_path1): Identity() | |
(norm2): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(mlp): Mlp( | |
(fc1): Linear(in_features=240, out_features=960, bias=True) | |
(act): GELU(approximate=none) | |
(drop1): Dropout(p=0.0, inplace=False) | |
(fc2): Linear(in_features=960, out_features=240, bias=True) | |
(drop2): Dropout(p=0.0, inplace=False) | |
) | |
(ls2): Identity() | |
(drop_path2): Identity() | |
) | |
(5): Block( | |
(norm1): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(attn): Attention( | |
(qkv): Linear(in_features=240, out_features=720, bias=True) | |
(attn_drop): Dropout(p=0.0, inplace=False) | |
(proj): Linear(in_features=240, out_features=240, bias=True) | |
(proj_drop): Dropout(p=0.0, inplace=False) | |
) | |
(ls1): Identity() | |
(drop_path1): Identity() | |
(norm2): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(mlp): Mlp( | |
(fc1): Linear(in_features=240, out_features=960, bias=True) | |
(act): GELU(approximate=none) | |
(drop1): Dropout(p=0.0, inplace=False) | |
(fc2): Linear(in_features=960, out_features=240, bias=True) | |
(drop2): Dropout(p=0.0, inplace=False) | |
) | |
(ls2): Identity() | |
(drop_path2): Identity() | |
) | |
(6): Block( | |
(norm1): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(attn): Attention( | |
(qkv): Linear(in_features=240, out_features=720, bias=True) | |
(attn_drop): Dropout(p=0.0, inplace=False) | |
(proj): Linear(in_features=240, out_features=240, bias=True) | |
(proj_drop): Dropout(p=0.0, inplace=False) | |
) | |
(ls1): Identity() | |
(drop_path1): Identity() | |
(norm2): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(mlp): Mlp( | |
(fc1): Linear(in_features=240, out_features=960, bias=True) | |
(act): GELU(approximate=none) | |
(drop1): Dropout(p=0.0, inplace=False) | |
(fc2): Linear(in_features=960, out_features=240, bias=True) | |
(drop2): Dropout(p=0.0, inplace=False) | |
) | |
(ls2): Identity() | |
(drop_path2): Identity() | |
) | |
(7): Block( | |
(norm1): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(attn): Attention( | |
(qkv): Linear(in_features=240, out_features=720, bias=True) | |
(attn_drop): Dropout(p=0.0, inplace=False) | |
(proj): Linear(in_features=240, out_features=240, bias=True) | |
(proj_drop): Dropout(p=0.0, inplace=False) | |
) | |
(ls1): Identity() | |
(drop_path1): Identity() | |
(norm2): LayerNorm((240,), eps=1e-06, elementwise_affine=True) | |
(mlp): Mlp( | |
(fc1): Linear(in_features=240, out_features=960, bias=True) | |
(act): GELU(approximate=none) | |
(drop1): Dropout(p=0.0, inplace=False) | |
(fc2): Linear(in_features=960, out_features=240, bias=True) | |
(drop2): Dropout(p=0.0, inplace=False) | |
) | |
(ls2): Identity() | |
(drop_path2): Identity() | |
) | |
) | |
(fc_norm): Identity() | |
(head): Identity() | |
(norm): Identity() | |
) | |
(fusion_layers): ModuleDict( | |
(layer_0): AddFusion( | |
(input_proj): Sequential( | |
(0): LayerNorm() | |
(1): Conv2d(768, 240, kernel_size=(1, 1), stride=(1, 1)) | |
) | |
) | |
(layer_1): AddFusion( | |
(input_proj): Sequential( | |
(0): LayerNorm() | |
(1): Conv2d(768, 240, kernel_size=(1, 1), stride=(1, 1)) | |
) | |
) | |
(layer_2): AddFusion( | |
(input_proj): Sequential( | |
(0): LayerNorm() | |
(1): Conv2d(768, 240, kernel_size=(1, 1), stride=(1, 1)) | |
) | |
) | |
(layer_3): AddFusion( | |
(input_proj): Sequential( | |
(0): LayerNorm() | |
(1): Conv2d(768, 240, kernel_size=(1, 1), stride=(1, 1)) | |
) | |
) | |
) | |
(mask_decoder): MLPMaskDecoder( | |
(query_mlp): MLP( | |
(layers): ModuleList( | |
(0): Linear(in_features=240, out_features=256, bias=True) | |
(1): Linear(in_features=256, out_features=256, bias=True) | |
(2): Linear(in_features=256, out_features=256, bias=True) | |
) | |
) | |
(pix_mlp): MLP( | |
(layers): ModuleList( | |
(0): Conv2d(240, 256, kernel_size=(1, 1), stride=(1, 1)) | |
(1): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1)) | |
(2): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1)) | |
) | |
) | |
(attn_mlp): MLP( | |
(layers): ModuleList( | |
(0): Conv2d(240, 256, kernel_size=(1, 1), stride=(1, 1)) | |
(1): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1)) | |
(2): Conv2d(256, 3072, kernel_size=(1, 1), stride=(1, 1)) | |
) | |
) | |
(bias_scaling): Linear(in_features=1, out_features=1, bias=True) | |
) | |
) | |
(clip_visual_extractor): FeatureExtractor( | |
(patchnorm_pre_ln): Identity() | |
(conv1): Conv2d(3, 768, kernel_size=(16, 16), stride=(16, 16), bias=False) | |
(patch_dropout): Identity() | |
(ln_pre): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(resblocks): ModuleList( | |
(0): ResidualAttentionBlock( | |
(ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=768, out_features=3072, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=3072, out_features=768, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(1): ResidualAttentionBlock( | |
(ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=768, out_features=3072, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=3072, out_features=768, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(2): ResidualAttentionBlock( | |
(ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=768, out_features=3072, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=3072, out_features=768, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(3): ResidualAttentionBlock( | |
(ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=768, out_features=3072, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=3072, out_features=768, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(4): ResidualAttentionBlock( | |
(ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=768, out_features=3072, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=3072, out_features=768, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(5): ResidualAttentionBlock( | |
(ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=768, out_features=3072, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=3072, out_features=768, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(6): ResidualAttentionBlock( | |
(ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=768, out_features=3072, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=3072, out_features=768, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(7): ResidualAttentionBlock( | |
(ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=768, out_features=3072, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=3072, out_features=768, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(8): ResidualAttentionBlock( | |
(ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=768, out_features=3072, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=3072, out_features=768, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
) | |
) | |
(clip_rec_head): RecWithAttnbiasHead( | |
(resblocks): ModuleList( | |
(0): ResidualAttentionBlock( | |
(ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=768, out_features=3072, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=3072, out_features=768, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(1): ResidualAttentionBlock( | |
(ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=768, out_features=3072, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=3072, out_features=768, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(2): ResidualAttentionBlock( | |
(ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=768, out_features=3072, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=3072, out_features=768, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
) | |
(ln_post): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
) | |
(ov_classifier): LearnableBgOvClassifier( | |
(transformer): Transformer( | |
(resblocks): ModuleList( | |
(0): ResidualAttentionBlock( | |
(ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=512, out_features=2048, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=2048, out_features=512, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(1): ResidualAttentionBlock( | |
(ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=512, out_features=2048, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=2048, out_features=512, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(2): ResidualAttentionBlock( | |
(ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=512, out_features=2048, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=2048, out_features=512, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(3): ResidualAttentionBlock( | |
(ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=512, out_features=2048, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=2048, out_features=512, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(4): ResidualAttentionBlock( | |
(ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=512, out_features=2048, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=2048, out_features=512, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(5): ResidualAttentionBlock( | |
(ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=512, out_features=2048, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=2048, out_features=512, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(6): ResidualAttentionBlock( | |
(ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=512, out_features=2048, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=2048, out_features=512, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(7): ResidualAttentionBlock( | |
(ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=512, out_features=2048, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=2048, out_features=512, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(8): ResidualAttentionBlock( | |
(ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=512, out_features=2048, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=2048, out_features=512, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(9): ResidualAttentionBlock( | |
(ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=512, out_features=2048, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=2048, out_features=512, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(10): ResidualAttentionBlock( | |
(ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=512, out_features=2048, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=2048, out_features=512, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
(11): ResidualAttentionBlock( | |
(ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(attn): MultiheadAttention( | |
(out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True) | |
) | |
(ls_1): Identity() | |
(ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
(mlp): Sequential( | |
(c_fc): Linear(in_features=512, out_features=2048, bias=True) | |
(gelu): QuickGELU() | |
(c_proj): Linear(in_features=2048, out_features=512, bias=True) | |
) | |
(ls_2): Identity() | |
) | |
) | |
) | |
(token_embedding): Embedding(49408, 512) | |
(ln_final): LayerNorm((512,), eps=1e-05, elementwise_affine=True) | |
) | |
) | |
[32m[04/06 20:37:02 san]: [0mOptimizer Info: | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| Param Name | Param Shape | Lr | Wd | | |
+================================================================+===============+========+========+ | |
| side_adapter_network.query_embed | 1X100X240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.query_pos_embed | 1X100X240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.pos_embed | 1X1600X240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.patch_embed.proj.weight | 240X3X16X16 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.patch_embed.proj.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.0.norm1.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.0.norm1.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.0.attn.qkv.weight | 720X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.0.attn.qkv.bias | 720 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.0.attn.proj.weight | 240X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.0.attn.proj.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.0.norm2.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.0.norm2.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.0.mlp.fc1.weight | 960X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.0.mlp.fc1.bias | 960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.0.mlp.fc2.weight | 240X960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.0.mlp.fc2.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.1.norm1.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.1.norm1.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.1.attn.qkv.weight | 720X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.1.attn.qkv.bias | 720 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.1.attn.proj.weight | 240X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.1.attn.proj.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.1.norm2.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.1.norm2.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.1.mlp.fc1.weight | 960X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.1.mlp.fc1.bias | 960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.1.mlp.fc2.weight | 240X960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.1.mlp.fc2.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.2.norm1.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.2.norm1.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.2.attn.qkv.weight | 720X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.2.attn.qkv.bias | 720 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.2.attn.proj.weight | 240X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.2.attn.proj.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.2.norm2.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.2.norm2.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.2.mlp.fc1.weight | 960X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.2.mlp.fc1.bias | 960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.2.mlp.fc2.weight | 240X960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.2.mlp.fc2.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.3.norm1.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.3.norm1.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.3.attn.qkv.weight | 720X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.3.attn.qkv.bias | 720 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.3.attn.proj.weight | 240X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.3.attn.proj.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.3.norm2.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.3.norm2.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.3.mlp.fc1.weight | 960X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.3.mlp.fc1.bias | 960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.3.mlp.fc2.weight | 240X960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.3.mlp.fc2.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.4.norm1.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.4.norm1.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.4.attn.qkv.weight | 720X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.4.attn.qkv.bias | 720 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.4.attn.proj.weight | 240X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.4.attn.proj.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.4.norm2.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.4.norm2.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.4.mlp.fc1.weight | 960X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.4.mlp.fc1.bias | 960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.4.mlp.fc2.weight | 240X960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.4.mlp.fc2.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.5.norm1.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.5.norm1.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.5.attn.qkv.weight | 720X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.5.attn.qkv.bias | 720 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.5.attn.proj.weight | 240X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.5.attn.proj.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.5.norm2.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.5.norm2.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.5.mlp.fc1.weight | 960X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.5.mlp.fc1.bias | 960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.5.mlp.fc2.weight | 240X960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.5.mlp.fc2.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.6.norm1.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.6.norm1.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.6.attn.qkv.weight | 720X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.6.attn.qkv.bias | 720 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.6.attn.proj.weight | 240X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.6.attn.proj.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.6.norm2.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.6.norm2.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.6.mlp.fc1.weight | 960X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.6.mlp.fc1.bias | 960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.6.mlp.fc2.weight | 240X960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.6.mlp.fc2.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.7.norm1.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.7.norm1.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.7.attn.qkv.weight | 720X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.7.attn.qkv.bias | 720 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.7.attn.proj.weight | 240X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.7.attn.proj.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.7.norm2.weight | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.7.norm2.bias | 240 | 0.0001 | 0.0 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.7.mlp.fc1.weight | 960X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.7.mlp.fc1.bias | 960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.7.mlp.fc2.weight | 240X960 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.vit_model.blocks.7.mlp.fc2.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
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+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_0.input_proj.0.bias | 768 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_0.input_proj.1.weight | 240X768X1X1 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_0.input_proj.1.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_1.input_proj.0.weight | 768 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_1.input_proj.0.bias | 768 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_1.input_proj.1.weight | 240X768X1X1 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_1.input_proj.1.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_2.input_proj.0.weight | 768 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_2.input_proj.0.bias | 768 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_2.input_proj.1.weight | 240X768X1X1 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_2.input_proj.1.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_3.input_proj.0.weight | 768 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_3.input_proj.0.bias | 768 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_3.input_proj.1.weight | 240X768X1X1 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.fusion_layers.layer_3.input_proj.1.bias | 240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.query_mlp.layers.0.weight | 256X240 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.query_mlp.layers.0.bias | 256 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.query_mlp.layers.1.weight | 256X256 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.query_mlp.layers.1.bias | 256 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.query_mlp.layers.2.weight | 256X256 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.query_mlp.layers.2.bias | 256 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.pix_mlp.layers.0.weight | 256X240X1X1 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.pix_mlp.layers.0.bias | 256 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.pix_mlp.layers.1.weight | 256X256X1X1 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.pix_mlp.layers.1.bias | 256 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.pix_mlp.layers.2.weight | 256X256X1X1 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.pix_mlp.layers.2.bias | 256 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.attn_mlp.layers.0.weight | 256X240X1X1 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.attn_mlp.layers.0.bias | 256 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.attn_mlp.layers.1.weight | 256X256X1X1 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.attn_mlp.layers.1.bias | 256 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.attn_mlp.layers.2.weight | 3072X256X1X1 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.attn_mlp.layers.2.bias | 3072 | 0.0001 | 0.0001 | | |
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| side_adapter_network.mask_decoder.bias_scaling.weight | 1X1 | 0.0001 | 0.0001 | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
| side_adapter_network.mask_decoder.bias_scaling.bias | 1 | 0.0001 | 0.0001 | | |
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| clip_visual_extractor.positional_embedding | 197X768 | 0.0001 | 0.0 | | |
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| ov_classifier.bg_embed | 1X512 | 0.0001 | 0.0001 | | |
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| Total | 8.37M | - | - | | |
+----------------------------------------------------------------+---------------+--------+--------+ | |
[32m[04/06 20:37:02 san.data.dataset_mappers.mask_former_semantic_dataset_mapper]: [0m[MaskFormerSemanticDatasetMapper] Augmentations used in training: [ResizeShortestEdge(short_edge_length=(320, 384, 448, 512, 576, 640, 704, 768, 832, 896, 960), max_size=2560, sample_style='choice'), RandomCrop_CategoryAreaConstraint(crop_type='absolute', crop_size=[640, 640], single_category_max_area=1.0, ignored_category=255), <detectron2.projects.point_rend.color_augmentation.ColorAugSSDTransform object at 0x7f58cb1dce20>, RandomFlip()] | |
[5m[31mWARNING[0m [32m[04/06 20:37:07 d2.data.datasets.coco]: [0mDirectory datasets/coco/train2017 and datasets/coco/stuffthingmaps_detectron2/train2017 has 118287 and 118280 files, respectively. | |
[5m[31mWARNING[0m [32m[04/06 20:37:08 d2.data.datasets.coco]: [0mWill use their intersection of 118280 files. | |
[32m[04/06 20:37:08 d2.data.datasets.coco]: [0mLoaded 118280 images with semantic segmentation from datasets/coco/train2017 | |
[32m[04/06 20:37:08 san.data.build]: [0mUsing training sampler TrainingSampler | |
[32m[04/06 20:37:08 d2.data.common]: [0mSerializing the dataset using: <class 'detectron2.data.common._TorchSerializedList'> | |
[32m[04/06 20:37:08 d2.data.common]: [0mSerializing 118280 elements to byte tensors and concatenating them all ... | |
[32m[04/06 20:37:08 d2.data.common]: [0mSerialized dataset takes 24.48 MiB | |
[32m[04/06 20:37:10 d2.checkpoint.detection_checkpoint]: [0m[DetectionCheckpointer] Loading from ... | |
[32m[04/06 20:37:10 fvcore.common.checkpoint]: [0mNo checkpoint found. Initializing model from scratch | |
[32m[04/06 20:37:10 d2.engine.train_loop]: [0mStarting training from iteration 0 | |
*** Error in `/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python': double free or corruption (!prev): 0x0000562d2e7059a0 *** | |
======= Backtrace: ========= | |
/lib64/libc.so.6(+0x733cf)[0x7ff00f8d43cf] | |
/lib64/libc.so.6(+0x78c3e)[0x7ff00f8d9c3e] | |
/lib64/libc.so.6(+0x79917)[0x7ff00f8da917] | |
/lib64/ld-linux-x86-64.so.2(_dl_deallocate_tls+0x58)[0x7ff01003f588] | |
/lib64/libpthread.so.0(+0x71f7)[0x7ff00fc141f7] | |
/lib64/libpthread.so.0(+0x730f)[0x7ff00fc1430f] | |
/lib64/libpthread.so.0(pthread_join+0xdb)[0x7ff00fc1665b] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so(pthreadpool_destroy+0x82)[0x7fefab7d80b2] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so(+0x344abe7)[0x7fefa9021be7] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so(_ZN2at15set_num_threadsEi+0x38)[0x7fefa735c3c8] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/torch/lib/libtorch_python.so(+0x5e9d3a)[0x7feffb280d3a] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0x1401c5)[0x562d2b1471c5] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0xff58e)[0x562d2b10658e] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyFunction_Vectorcall+0x10b)[0x562d2b19216b] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(PyVectorcall_Call+0x71)[0x562d2b143a41] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyEval_EvalFrameDefault+0x207c)[0x562d2b1ca1dc] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyFunction_Vectorcall+0x10b)[0x562d2b19216b] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0xff56d)[0x562d2b10656d] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyEval_EvalCodeWithName+0x2d2)[0x562d2b1912a2] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyFunction_Vectorcall+0x1e3)[0x562d2b192243] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0xff56d)[0x562d2b10656d] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyFunction_Vectorcall+0x10b)[0x562d2b19216b] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0xff819)[0x562d2b106819] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyEval_EvalCodeWithName+0x2d2)[0x562d2b1912a2] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyFunction_Vectorcall+0x1e3)[0x562d2b192243] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0x10050b)[0x562d2b10750b] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyEval_EvalCodeWithName+0x2d2)[0x562d2b1912a2] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(PyEval_EvalCodeEx+0x44)[0x562d2b192054] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(PyEval_EvalCode+0x1c)[0x562d2b2205bc] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0x219664)[0x562d2b220664] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0x24b874)[0x562d2b252874] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(PyRun_StringFlags+0x7d)[0x562d2b2550cd] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(PyRun_SimpleStringFlags+0x3f)[0x562d2b11c488] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0x11598b)[0x562d2b11c98b] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(Py_BytesMain+0x39)[0x562d2b255389] | |
/lib64/libc.so.6(__libc_start_main+0xf5)[0x7ff00f882a85] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0x1de553)[0x562d2b1e5553] | |
======= Memory map: ======== | |
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562d2b066000-562d2b256000 r-xp 0005f000 00:29 306124776 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python3.8 | |
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7fef6fff2000-7fef6fff3000 rw-p 00002000 00:29 620965875 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/tokenizers.libs/libkeyutils-68db41cc.so.1.3 | |
7fef6fff3000-7fef6fff4000 rw-p 00003000 00:29 620965875 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/tokenizers.libs/libkeyutils-68db41cc.so.1.3 | |
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7fef701fd000-7fef701fe000 r--p 00009000 00:29 620965879 /gs/hom*** Error in `/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python': double free or corruption (!prev): 0x000055ba11ac59a0 *** | |
e/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/tokenizers.libs/libkrb5support-2ce1fd50.so.0.1 | |
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======= Memory map: ======== | |
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7f3d35c7a000-7f3d35c7d000 r-xp 00001000 00:29 550174871 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/lib-dynload/_heapq.cpython-38-x86_64-linux-gnu.so | |
7f3d35c7d000-7f3d35c80000 r--p 00004000 00:29 550174871 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/lib-dynload/_heapq.cpython-38-x86_64-linux-gnu.so | |
7f3d35c80000-7f3d35c81000 r--p 00006000 00:29 550174871 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/lib-dynload/_heapq.cpython-38-x86_64-linux-gnu.so | |
7f3d35c81000-7f3d35c82000 rw-p 00007000 00:29 550174871 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/lib-dynload/_heapq.cpython-38-x86_64-linux-gnu.so | |
7f3d35c82000-7f3d35c89000 r--s 00000000 fd:00 268455426 /usr/lib64/gconv/gconv-modules.cache | |
7f3d35c89000-7f3d35c8a000 rw-p 00000000 00:00 0 | |
7f3d35c8a000-7f3d35c8b000 r--p 00020000 fd:00 755249 /usr/lib64/ld-2.18.so | |
7f3d35c8b000-7f3d35c8c000 rw-p 00021000 fd:00 755249 /usr/lib64/ld-2.18.so | |
7f3d35c8c000-7f3d35c8d000 rw-p 00000000 00:00 0 | |
7ffc88845000-7ffc88868000 rwxp 00000000 00:00 0 [stack] | |
7ffc88868000-7ffc8886c000 rw-p 00000000 00:00 0 | |
7ffc889fb000-7ffc889fd000 r-xp 00000000 00:00 0 [vdso] | |
ffffffffff600000-ffffffffff601000 r-xp 00000000 00:00 0 [vsyscall] | |
*** Error in `/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python': double free or corruption (!prev): 0x00005630c147f9a0 *** | |
======= Backtrace: ========= | |
/lib64/libc.so.6(+0x733cf)[0x7f42473143cf] | |
/lib64/libc.so.6(+0x78c3e)[0x7f4247319c3e] | |
/lib64/libc.so.6(+0x79917)[0x7f424731a917] | |
/lib64/ld-linux-x86-64.so.2(_dl_deallocate_tls+0x58)[0x7f4247a7f588] | |
/lib64/libpthread.so.0(+0x71f7)[0x7f42476541f7] | |
/lib64/libpthread.so.0(+0x730f)[0x7f424765430f] | |
/lib64/libpthread.so.0(pthread_join+0xdb)[0x7f424765665b] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so(pthreadpool_destroy+0x82)[0x7f41e32180b2] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so(+0x344abe7)[0x7f41e0a61be7] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/torch/lib/libtorch_cpu.so(_ZN2at15set_num_threadsEi+0x38)[0x7f41ded9c3c8] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/torch/lib/libtorch_python.so(+0x5e9d3a)[0x7f4232cc0d3a] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0x1401c5)[0x5630bdf261c5] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0xff58e)[0x5630bdee558e] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyFunction_Vectorcall+0x10b)[0x5630bdf7116b] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(PyVectorcall_Call+0x71)[0x5630bdf22a41] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyEval_EvalFrameDefault+0x207c)[0x5630bdfa91dc] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyFunction_Vectorcall+0x10b)[0x5630bdf7116b] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0xff56d)[0x5630bdee556d] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyEval_EvalCodeWithName+0x2d2)[0x5630bdf702a2] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyFunction_Vectorcall+0x1e3)[0x5630bdf71243] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0xff56d)[0x5630bdee556d] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyFunction_Vectorcall+0x10b)[0x5630bdf7116b] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0xff819)[0x5630bdee5819] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyEval_EvalCodeWithName+0x2d2)[0x5630bdf702a2] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyFunction_Vectorcall+0x1e3)[0x5630bdf71243] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0x10050b)[0x5630bdee650b] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(_PyEval_EvalCodeWithName+0x2d2)[0x5630bdf702a2] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(PyEval_EvalCodeEx+0x44)[0x5630bdf71054] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(PyEval_EvalCode+0x1c)[0x5630bdfff5bc] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0x219664)[0x5630bdfff664] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0x24b874)[0x5630be031874] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(PyRun_StringFlags+0x7d)[0x5630be0340cd] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(PyRun_SimpleStringFlags+0x3f)[0x5630bdefb488] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0x11598b)[0x5630bdefb98b] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(Py_BytesMain+0x39)[0x5630be034389] | |
/lib64/libc.so.6(__libc_start_main+0xf5)[0x7f42472c2a85] | |
/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0x1de553)[0x5630bdfc4553] | |
======= Memory map: ======== | |
5630bdde6000-5630bde45000 r--p 00000000 00:29 306124776 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python3.8 | |
5630bde45000-5630be035000 r-xp 0005f000 00:29 306124776 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python3.8 | |
5630be035000-5630be11b000 r--p 0024f000 00:29 306124776 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python3.8 | |
5630be11b000-5630be120000 r--p 00334000 00:29 306124776 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python3.8 | |
5630be120000-5630be158000 rw-p 00339000 00:29 306124776 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python3.8 | |
5630be158000-5630be178000 rw-p 00000000 00:00 0 | |
5630bf2fd000-5630c80ba000 rw-p 00000000 00:00 0 [heap] | |
7f418cce5000-7f418cce6000 ---p 00000000 00:00 0 | |
7f418cce6000-7f418d4e6000 rwxp 00000000 00:00 0 | |
7f418d4e6000-7f418d4e7000 ---p 00000000 00:00 0 | |
7f418d4e7000-7f418dce7000 rwxp 00000000 00:00 0 | |
7f418dce7000-7f418dce8000 ---p 00000000 00:00 0 | |
7f418dce8000-7f418e4e8000 rwxp 00000000 00:00 0 | |
7f418e4e8000-7f418e4e9000 ---p 00000000 00:00 0 | |
7f418e4e9000-7f418ece9000 rwxp 00000000 00:00 0 | |
7f418ece9000-7f418ecea000 ---p 00000000 00:00 0 | |
7f418ecea000-7f418f4ea000 rwxp 00000000 00:00 0 | |
7f418f4ea000-7f418f4eb000 ---p 00000000 00:00 0 | |
7f418f4eb000-7f418fceb000 rwxp 00000000 00:00 0 | |
7f418fceb000-7f418fcec000 ---p 00000000 00:00 0 | |
7f418fcec000-7f41904ec000 rwxp 00000000 00:00 0 | |
7f41904ec000-7f41904ed000 ---p 00000000 00:00 0 | |
7f41904ed000-7f4190ced000 rwxp 00000000 00:00 0 | |
7f4190ced000-7f4190cee000 ---p 00000000 00:00 0 | |
7f4190cee000-7f41914ee000 rwxp 00000000 00:00 0 | |
7f41914ee000-7f41914ef000 ---p 00000000 00:00 0 | |
7f41914ef000-7f4191cef000 rwxp 00000000 00:00 0 | |
7f4191cef000-7f4191cf0000 ---p 00000000 00:00 0 | |
7f4191cf0000-7f41924f0000 rwxp 00000000 00:00 0 | |
7f41924f0000-7f41924f1000 ---p 00000000 00:00 0 | |
7f41924f1000-7f4192cf1000 rwxp 00000000 00:00 0 | |
7f4192cf1000-7f4192cf2000 ---p 00000000 00:00 0 | |
7f4192cf2000-7f41934f2000 rwxp 00000000 00:00 0 | |
7f41934f2000-7f41934f3000 ---p 00000000 00:00 0 | |
7f41934f3000-7f4193cf3000 rwxp 00000000 00:00 0 | |
7f4193cf3000-7f4193cf4000 ---p 00000000 00:00 0 | |
7f4193cf4000-7f41944f4000 rwxp 00000000 00:00 0 | |
7f41944f4000-7f41944f5000 ---p 00000000 00:00 0 | |
7f41944f5000-7f4194cf5000 rwxp 00000000 00:00 0 | |
7f4194cf5000-7f4194cf6000 ---p 00000000 00:00 0 | |
7f4194cf6000-7f41954f6000 rwxp 00000000 00:00 0 | |
7f41954f6000-7f41954f7000 ---p 00000000 00:00 0 | |
7f41954f7000-7f4195cf7000 rwxp 00000000 00:00 0 | |
7f4195cf7000-7f4195cf8000 ---p 00000000 00:00 0 | |
7f4195cf8000-7f41964f8000 rwxp 00000000 00:00 0 | |
7f41964f8000-7f41964f9000 ---p 00000000 00:00 0 | |
7f41964f9000-7f4196cf9000 rwxp 00000000 00:00 0 | |
7f4196cf9000-7f4196cfa000 ---p 00000000 00:00 0 | |
7f4196cfa000-7f41974fa000 rwxp 00000000 00:00 0 | |
7f41974fa000-7f41974fb000 ---p 00000000 00:00 0 | |
7f41974fb000-7f4197cfb000 rwxp 00000000 00:00 0 | |
7f4197cfb000-7f4197cfc000 ---p 00000000 00:00 0 | |
7f4197cfc000-7f41984fc000 rwxp 00000000 00:00 0 | |
7f41984fc000-7f41984fd000 ---p 00000000 00:00 0 | |
7f41984fd000-7f4198cfd000 rwxp 00000000 00:00 0 | |
7f4198cfd000-7f4198cfe000 ---p 00000000 00:00 0 | |
7f4198cfe000-7f41994fe000 rwxp 00000000 00:00 0 | |
7f41994fe000-7f41994ff000 ---p 00000000 00:00 0 | |
7f41994ff000-7f4199cff000 rwxp 00000000 00:00 0 | |
7f4199cff000-7f4199d00000 ---p 00000000 00:00 0 | |
7f4199d00000-7f419a500000 rwxp 00000000 00:00 0 | |
7f419a500000-7f419a501000 ---p 00000000 00:00 0 | |
7f419a501000-7f419ad01000 rwxp 00000000 00:00 0 | |
7f419ad01000-7f419ad02000 ---p 00000000 00:00 0 | |
7f419ad02000-7f419b502000 rwxp 00000000 00:00 0 | |
7f419b502000-7f419b503000 ---p 00000000 00:00 0 | |
7f419b503000-7f419bd03000 rwxp 00000000 00:00 0 | |
7f419bd03000-7f419bd04000 ---p 00000000 00:00 0 | |
7f419bd04000-7f419c504000 rwxp 00000000 00:00 0 | |
7f419c504000-7f419c505000 ---p 00000000 00:00 0 | |
7f419c505000-7f419cd05000 rwxp 00000000 00:00 0 | |
7f419cd05000-7f419cd06000 ---p 00000000 00:00 0 | |
7f419cd06000-7f419d506000 rwxp 00000000 00:00 0 | |
7f419d506000-7f419d507000 ---p 00000000 00:00 0 | |
7f419d507000-7f419dd07000 rwxp 00000000 00:00 0 | |
7f419dd07000-7f419dd08000 ---p 00000000 00:00 0 | |
7f419dd08000-7f419e508000 rwxp 00000000 00:00 0 | |
7f419e508000-7f419e509000 ---p 00000000 00:00 0 | |
7f419e509000-7f419ed09000 rwxp 00000000 00:00 0 | |
7f419ed09000-7f419ed0a000 ---p 00000000 00:00 0 | |
7f419ed0a000-7f419f50a000 rwxp 00000000 00:00 0 | |
7f419f50a000-7f419f50b000 ---p 00000000 00:00 0 | |
7f419f50b000-7f419fd0b000 rwxp 00000000 00:00 0 | |
7f419fd0b000-7f419fd0c000 ---p 00000000 00:00 0 | |
7f419fd0c000-7f41a050c000 rwxp 00000000 00:00 0 | |
7f41a050c000-7f41a050d000 ---p 00000000 00:00 0 | |
7f41a050d000-7f41a0d0d000 rwxp 00000000 00:00 0 | |
7f41a0d0d000-7f41a0d0e000 ---p 00000000 00:00 0 | |
7f41a0d0e000-7f41a150e000 rwxp 00000000 00:00 0 | |
7f41a150e000-7f41a150f000 ---p 00000000 00:00 0 | |
7f41a150f000-7f41a1d0f000 rwxp 00000000 00:00 0 | |
7f41a1d0f000-7f41a1d10000 ---p 00000000 00:00 0 | |
7f41a1d10000-7f41a2510000 rwxp 00000000 00:00 0 | |
7f41a2510000-7f41a28d0000 rw-p 00000000 00:00 0 | |
7f41a28d0000-7f41a29b8000 rw-s 00000000 00:13 3335756190 /dev/shm/torch_202626_2864713810_1 (deleted) | |
7f41a29b8000-7f41a4233000 rw-s 00000000 00:13 3335756189 /dev/shm/torch_202626_1217565150_0 (deleted) | |
7f41a4233000-7f41a42b3000 rw-p 00000000 00:00 0 | |
7f41a42b3000-7f41a42bd000 r--p 00000000 00:29 419647377 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/transform/rotation.cpython-38-x86_64-linux-gnu.so | |
7f41a42bd000-7f41a4318000 r-xp 0000a000 00:29 419647377 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/transform/rotation.cpython-38-x86_64-linux-gnu.so | |
7f41a4318000-7f41a432e000 r--p 00065000 00:29 419647377 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/transform/rotation.cpython-38-x86_64-linux-gnu.so | |
7f41a432e000-7f41a432f000 ---p 0007b000 00:29 419647377 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-pack*** Error in `/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python': double free or corruption (!prev): 0x000055c2d346a9a0 *** | |
ages/scipy/spatial/transform/rotation.cpython-38-x86_64-linux-gnu.so | |
7f41a432f000-7f41a4330000 r--p 0007b000 00:29 419647377 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/transform/rotation.cpython-38-x86_64-linux-gnu.so | |
7f41a4330000-7f41a4340000 rw-p 0007c000 00:29 419647377 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/transform/rotation.cpython-38-x86_64-linux-gnu.so | |
7f41a4340000-7f41a4381000 rw-p 00000000 00:00 0 | |
7f41a4381000-7f41a4387000 r--p 00000000 00:29 419647432 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_hausdorff.cpython-38-x86_64-linux-gnu.so | |
7f41a4387000-7f41a43a0000 r-xp 00006000 00:29 419647432 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_hausdorff.cpython-38-x86_64-linux-gnu.so | |
7f41a43a0000-7f41a43a6000 r--p 0001f000 00:29 419647432 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_hausdorff.cpython-38-x86_64-linux-gnu.so | |
7f41a43a6000-7f41a43a7000 ---p 00025000 00:29 419647432 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_hausdorff.cpython-38-x86_64-linux-gnu.so | |
7f41a43a7000-7f41a43a8000 r--p 00025000 00:29 419647432 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_hausdorff.cpython-38-x86_64-linux-gnu.so | |
7f41a43a8000-7f41a43ab000 rw-p 00026000 00:29 419647432 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_hausdorff.cpython-38-x86_64-linux-gnu.so | |
7f41a43ab000-7f41a43ad000 r--p 00000000 00:29 419647356 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_distance_wrap.cpython-38-x86_64-linux-gnu.so | |
7f41a43ad000-7f41a43c1000 r-xp 00002000 00:29 419647356 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_distance_wrap.cpython-38-x86_64-linux-gnu.so | |
7f41a43c1000-7f41a43c4000 r--p 00016000 00:29 419647356 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_distance_wrap.cpython-38-x86_64-linux-gnu.so | |
7f41a43c4000-7f41a43c5000 r--p 00018000 00:29 419647356 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_distance_wrap.cpython-38-x86_64-linux-gnu.so | |
7f41a43c5000-7f41a43c6000 rw-p 00019000 00:29 419647356 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_distance_wrap.cpython-38-x86_64-linux-gnu.so | |
7f41a43c6000-7f41a43cc000 r--p 00000000 00:29 419647436 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_voronoi.cpython-38-x86_64-linux-gnu.so | |
7f41a43cc000-7f41a43e4000 r-xp 00006000 00:29 419647436 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_voronoi.cpython-38-x86_64-linux-gnu.so | |
7f41a43e4000-7f41a43ea000 r--p 0001e000 00:29 419647436 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_voronoi.cpython-38-x86_64-linux-gnu.so | |
7f41a43ea000-7f41a43eb000 r--p 00023000 00:29 419647436 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_voronoi.cpython-38-x86_64-linux-gnu.so | |
7f41a43eb000-7f41a43ee000 rw-p 00024000 00:29 419647436 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_voronoi.cpython-38-x86_64-linux-gnu.so | |
7f41a43ee000-7f41a43fa000 r--p 00000000 00:29 419647447 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/qhull.cpython-38-x86_64-linux-gnu.so | |
7f41a43fa000-7f41a4492000 r-xp 0000c000 00:29 419647447 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/qhull.cpython-38-x86_64-linux-gnu.so | |
7f41a4492000-7f41a44c4000 r--p 000a4000 00:29 419647447 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/qhull.cpython-38-x86_64-linux-gnu.so | |
7f41a44c4000-7f41a44c5000 r--p 000d5000 00:29 419647447 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/qhull.cpython-38-x86_64-linux-gnu.so | |
7f41a44c5000-7f41a44ce000 rw-p 000d6000 00:29 419647447 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/qhull.cpython-38-x86_64-linux-gnu.so | |
7f41a44ce000-7f41a44cf000 rw-p 00000000 00:00 0 | |
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7f41a49bc000-7f41a49bf000 r--p ======= Backtrace: ========= | |
00000000 00:29 420172841 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/_lib/messagestream.cpython-38-x86_64-linux-gnu.so | |
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/gs/home/statchao/anaconda3/envs/guangrui_cuda11/bin/python(+0x11598b)[0x55c2cf3e898b] | |
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======= Memory map: ======== | |
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7fbe9fb79000-7fbe9fb7f000 r--p 0001e000 00:29 419647436 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_voronoi.cpython-38-x86_64-linux-gnu.so | |
7fbe9fb7f000-7fbe9fb80000 r--p 00023000 00:29 419647436 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_voronoi.cpython-38-x86_64-linux-gnu.so | |
7fbe9fb80000-7fbe9fb83000 rw-p 00024000 00:29 419647436 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/_voronoi.cpython-38-x86_64-linux-gnu.so | |
7fbe9fb83000-7fbe9fb8f000 r--p 00000000 00:29 419647447 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/qhull.cpython-38-x86_64-linux-gnu.so | |
7fbe9fb8f000-7fbe9fc27000 r-xp 0000c000 00:29 419647447 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/qhull.cpython-38-x86_64-linux-gnu.so | |
7fbe9fc27000-7fbe9fc59000 r--p 000a4000 00:29 419647447 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/qhull.cpython-38-x86_64-linux-gnu.so | |
7fbe9fc59000-7fbe9fc5a000 r--p 000d5000 00:29 419647447 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/qhull.cpython-38-x86_64-linux-gnu.so | |
7fbe9fc5a000-7fbe9fc63000 rw-p 000d6000 00:29 419647447 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/qhull.cpython-38-x86_64-linux-gnu.so | |
7fbe9fc63000-7fbe9fc64000 rw-p 00000000 00:00 0 | |
7fbe9fc64000-7fbe9fc6f000 r--p 00000000 00:29 419647449 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/ckdtree.cpython-38-x86_64-linux-gnu.so | |
7fbe9fc6f000-7fbe9fcfd000 r-xp 0000b000 00:29 419647449 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/ckdtree.cpython-38-x86_64-linux-gnu.so | |
7fbe9fcfd000-7fbe9fd11000 r--p 00099000 00:29 419647449 /gs/home/statchao/anaconda3/envs/guangrui_cuda11/lib/python3.8/site-packages/scipy/spatial/ckdtree.cpython-38-x86_64-linux-gnu.so | |
7fbe9fd11000-7fbe9fd12 |
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