[04/19 10:19:41] fastreid INFO: Rank of current process: 0. World size: 4
[04/19 10:19:41] fastreid INFO: Environment info:
----------------------  ----------------------------------------------------------------------------------------------
sys.platform            linux
Python                  3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0]
numpy                   1.25.2
fastreid                0.1.0 @/home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/./fastreid
FASTREID_ENV_MODULE     <not set>
PyTorch                 1.12.1+cu113 @/home/ma-user/anaconda3/envs/Generate3D/lib/python3.10/site-packages/torch
PyTorch debug build     False
GPU available           True
GPU 0,1,2,3             Tesla V100S-PCIE-32GB
CUDA_HOME               /usr/local/cuda
Pillow                  10.1.0
torchvision             0.13.1+cu113 @/home/ma-user/anaconda3/envs/Generate3D/lib/python3.10/site-packages/torchvision
torchvision arch flags  sm_35, sm_50, sm_60, sm_70, sm_75, sm_80, sm_86
fvcore                  0.1.5.post20221221
cv2                     4.8.0
----------------------  ----------------------------------------------------------------------------------------------
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 8.5  (built against CUDA 11.7)
    - 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, 

[04/19 10:19:41] fastreid INFO: Command line arguments: Namespace(config_file='configs/CMDM/msmt17_mgn_R50_lion.yml', finetune=False, resume=False, eval_only=False, num_gpus=4, num_machines=1, machine_rank=0, dist_url='tcp://127.0.0.1:39354', opts=[])
[04/19 10:19:41] fastreid INFO: Contents of args.config_file=configs/CMDM/msmt17_mgn_R50_lion.yml:
_BASE_: "../Base-MGN.yml"

MODEL:
  BACKBONE:
    WITH_IBN: False
    EXTRA_BN: True
    PRETRAIN_PATH: "/home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth"
  PIXEL_MEAN: [123.675, 116.280, 103.530]
  PIXEL_STD: [58.395, 57.120, 57.375]

INPUT:
  REA:
    MEAN: [0.0, 0.0, 0.0]
  DO_AUTOAUG: False

SOLVER:
  HEADS_LR_FACTOR: 1.0
  BACKBONE_BN_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: -1

DATASETS:
  NAMES: ("CMDM",)
  TESTS: ("CMDM",)
  KWARGS: 'data_name:msmt17+split_mode:id+split_ratio:1.0'
  ROOT: "/home/ma-user/work/Datasets/ImageReID_Datasets/mixreid"

TEST:
  EVAL_PERIOD: 60

OUTPUT_DIR: "logs/msmt17/ResNet50_ViTdefault_LION_MGN"

[04/19 10:19:41] fastreid INFO: Running with full config:
CUDNN_BENCHMARK: True
DATALOADER:
  NAIVE_WAY: True
  NUM_INSTANCE: 16
  NUM_WORKERS: 8
  PK_SAMPLER: True
DATASETS:
  COMBINEALL: False
  IS_LMDB: False
  KWARGS: data_name:msmt17+split_mode:id+split_ratio:1.0
  NAMES: ('CMDM',)
  ROOT: /home/ma-user/work/Datasets/ImageReID_Datasets/mixreid
  TESTS: ('CMDM',)
INPUT:
  CJ:
    BRIGHTNESS: 0.15
    CONTRAST: 0.15
    ENABLED: False
    HUE: 0.1
    PROB: 0.8
    SATURATION: 0.1
  DO_AUGMIX: False
  DO_AUTOAUG: False
  DO_FLIP: True
  DO_PAD: True
  FLIP_PROB: 0.5
  PADDING: 10
  PADDING_MODE: constant
  REA:
    ENABLED: True
    MEAN: [0.0, 0.0, 0.0]
    PROB: 0.5
  RPT:
    ENABLED: False
    PROB: 0.5
  SIZE_TEST: [384, 128]
  SIZE_TRAIN: [384, 128]
MODEL:
  BACKBONE:
    DEPTH: 50x
    EXTRA_BN: True
    FEAT_DIM: 2048
    LAST_STRIDE: 1
    NAME: build_resnet_backbone
    NORM: BN
    PRETRAIN: True
    PRETRAIN_PATH: /home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth
    WITH_IBN: False
    WITH_NL: False
    WITH_SE: False
  DEVICE: cuda
  FREEZE_LAYERS: ['backbone', 'b1', 'b2', 'b3']
  HEADS:
    CLS_LAYER: circleSoftmax
    EMBEDDING_DIM: 256
    MARGIN: 0.35
    NAME: EmbeddingHead
    NECK_FEAT: after
    NORM: BN
    NUM_CLASSES: 0
    POOL_LAYER: gempoolP
    SCALE: 64
    WITH_BNNECK: True
  LOSSES:
    CE:
      ALPHA: 0.2
      EPSILON: 0.1
      SCALE: 1.0
    CIRCLE:
      ALPHA: 128
      MARGIN: 0.25
      SCALE: 1.0
    FL:
      ALPHA: 0.25
      GAMMA: 2
      SCALE: 1.0
    NAME: ('CrossEntropyLoss', 'TripletLoss')
    TRI:
      HARD_MINING: True
      MARGIN: 0.0
      NORM_FEAT: False
      SCALE: 1.0
  META_ARCHITECTURE: MGN
  PIXEL_MEAN: [123.675, 116.28, 103.53]
  PIXEL_STD: [58.395, 57.12, 57.375]
  WEIGHTS: 
OUTPUT_DIR: logs/msmt17/ResNet50_ViTdefault_LION_MGN
SOLVER:
  AMP_ENABLED: False
  BACKBONE_BN_LR_FACTOR: 1.0
  BASE_LR: 0.00035
  BIAS_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: -1
  DELAY_ITERS: 30
  ETA_MIN_LR: 7.7e-07
  FREEZE_ITERS: 10
  GAMMA: 0.1
  HEADS_LR_FACTOR: 1.0
  IMS_PER_BATCH: 64
  MAX_ITER: 60
  MOMENTUM: 0.9
  OPT: Adam
  SCHED: WarmupCosineAnnealingLR
  STEPS: [40, 90]
  SWA:
    ENABLED: False
    ETA_MIN_LR: 3.5e-06
    ITER: 10
    LR_FACTOR: 10.0
    LR_SCHED: False
    PERIOD: 2
  WARMUP_FACTOR: 0.01
  WARMUP_ITERS: 10
  WARMUP_METHOD: linear
  WEIGHT_DECAY: 0.0005
  WEIGHT_DECAY_BIAS: 0.0005
TEST:
  AQE:
    ALPHA: 3.0
    ENABLED: False
    QE_K: 5
    QE_TIME: 1
  EVAL_PERIOD: 60
  IMS_PER_BATCH: 128
  METRIC: cosine
  PRECISE_BN:
    DATASET: Market1501
    ENABLED: False
    NUM_ITER: 300
  RERANK:
    ENABLED: False
    K1: 20
    K2: 6
    LAMBDA: 0.3
  ROC_ENABLED: False
[04/19 10:19:41] fastreid INFO: Full config saved to /home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/logs/msmt17/ResNet50_ViTdefault_LION_MGN/config.yaml
[04/19 10:19:41] fastreid.utils.env INFO: Using a generated random seed 44402500
[04/19 10:19:41] fastreid.engine.defaults INFO: Prepare training set
[04/19 10:21:59] fastreid INFO: Rank of current process: 0. World size: 4
[04/19 10:21:59] fastreid INFO: Environment info:
----------------------  ----------------------------------------------------------------------------------------------
sys.platform            linux
Python                  3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0]
numpy                   1.25.2
fastreid                0.1.0 @/home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/./fastreid
FASTREID_ENV_MODULE     <not set>
PyTorch                 1.12.1+cu113 @/home/ma-user/anaconda3/envs/Generate3D/lib/python3.10/site-packages/torch
PyTorch debug build     False
GPU available           True
GPU 0,1,2,3             Tesla V100S-PCIE-32GB
CUDA_HOME               /usr/local/cuda
Pillow                  10.1.0
torchvision             0.13.1+cu113 @/home/ma-user/anaconda3/envs/Generate3D/lib/python3.10/site-packages/torchvision
torchvision arch flags  sm_35, sm_50, sm_60, sm_70, sm_75, sm_80, sm_86
fvcore                  0.1.5.post20221221
cv2                     4.8.0
----------------------  ----------------------------------------------------------------------------------------------
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 8.5  (built against CUDA 11.7)
    - 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, 

[04/19 10:21:59] fastreid INFO: Command line arguments: Namespace(config_file='configs/CMDM/msmt17_mgn_R50_lion.yml', finetune=False, resume=False, eval_only=False, num_gpus=4, num_machines=1, machine_rank=0, dist_url='tcp://127.0.0.1:38447', opts=[])
[04/19 10:21:59] fastreid INFO: Contents of args.config_file=configs/CMDM/msmt17_mgn_R50_lion.yml:
_BASE_: "../Base-MGN.yml"

MODEL:
  BACKBONE:
    WITH_IBN: False
    EXTRA_BN: True
    PRETRAIN_PATH: "/home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth"
  PIXEL_MEAN: [123.675, 116.280, 103.530]
  PIXEL_STD: [58.395, 57.120, 57.375]

INPUT:
  REA:
    MEAN: [0.0, 0.0, 0.0]
  DO_AUTOAUG: False

SOLVER:
  HEADS_LR_FACTOR: 1.0
  BACKBONE_BN_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: -1

DATASETS:
  NAMES: ("CMDM",)
  TESTS: ("CMDM",)
  KWARGS: 'data_name:msmt17+split_mode:id+split_ratio:1.0'
  ROOT: "/home/ma-user/work/Datasets/ImageReID_Datasets/mixreid"

TEST:
  EVAL_PERIOD: 60

OUTPUT_DIR: "logs/msmt17/ResNet50_ViTdefault_LION_MGN"

[04/19 10:21:59] fastreid INFO: Running with full config:
CUDNN_BENCHMARK: True
DATALOADER:
  NAIVE_WAY: True
  NUM_INSTANCE: 16
  NUM_WORKERS: 8
  PK_SAMPLER: True
DATASETS:
  COMBINEALL: False
  IS_LMDB: False
  KWARGS: data_name:msmt17+split_mode:id+split_ratio:1.0
  NAMES: ('CMDM',)
  ROOT: /home/ma-user/work/Datasets/ImageReID_Datasets/mixreid
  TESTS: ('CMDM',)
INPUT:
  CJ:
    BRIGHTNESS: 0.15
    CONTRAST: 0.15
    ENABLED: False
    HUE: 0.1
    PROB: 0.8
    SATURATION: 0.1
  DO_AUGMIX: False
  DO_AUTOAUG: False
  DO_FLIP: True
  DO_PAD: True
  FLIP_PROB: 0.5
  PADDING: 10
  PADDING_MODE: constant
  REA:
    ENABLED: True
    MEAN: [0.0, 0.0, 0.0]
    PROB: 0.5
  RPT:
    ENABLED: False
    PROB: 0.5
  SIZE_TEST: [384, 128]
  SIZE_TRAIN: [384, 128]
MODEL:
  BACKBONE:
    DEPTH: 50x
    EXTRA_BN: True
    FEAT_DIM: 2048
    LAST_STRIDE: 1
    NAME: build_resnet_backbone
    NORM: BN
    PRETRAIN: True
    PRETRAIN_PATH: /home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth
    WITH_IBN: False
    WITH_NL: False
    WITH_SE: False
  DEVICE: cuda
  FREEZE_LAYERS: ['backbone', 'b1', 'b2', 'b3']
  HEADS:
    CLS_LAYER: circleSoftmax
    EMBEDDING_DIM: 256
    MARGIN: 0.35
    NAME: EmbeddingHead
    NECK_FEAT: after
    NORM: BN
    NUM_CLASSES: 0
    POOL_LAYER: gempoolP
    SCALE: 64
    WITH_BNNECK: True
  LOSSES:
    CE:
      ALPHA: 0.2
      EPSILON: 0.1
      SCALE: 1.0
    CIRCLE:
      ALPHA: 128
      MARGIN: 0.25
      SCALE: 1.0
    FL:
      ALPHA: 0.25
      GAMMA: 2
      SCALE: 1.0
    NAME: ('CrossEntropyLoss', 'TripletLoss')
    TRI:
      HARD_MINING: True
      MARGIN: 0.0
      NORM_FEAT: False
      SCALE: 1.0
  META_ARCHITECTURE: MGN
  PIXEL_MEAN: [123.675, 116.28, 103.53]
  PIXEL_STD: [58.395, 57.12, 57.375]
  WEIGHTS: 
OUTPUT_DIR: logs/msmt17/ResNet50_ViTdefault_LION_MGN
SOLVER:
  AMP_ENABLED: False
  BACKBONE_BN_LR_FACTOR: 1.0
  BASE_LR: 0.00035
  BIAS_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: -1
  DELAY_ITERS: 30
  ETA_MIN_LR: 7.7e-07
  FREEZE_ITERS: 10
  GAMMA: 0.1
  HEADS_LR_FACTOR: 1.0
  IMS_PER_BATCH: 64
  MAX_ITER: 60
  MOMENTUM: 0.9
  OPT: Adam
  SCHED: WarmupCosineAnnealingLR
  STEPS: [40, 90]
  SWA:
    ENABLED: False
    ETA_MIN_LR: 3.5e-06
    ITER: 10
    LR_FACTOR: 10.0
    LR_SCHED: False
    PERIOD: 2
  WARMUP_FACTOR: 0.01
  WARMUP_ITERS: 10
  WARMUP_METHOD: linear
  WEIGHT_DECAY: 0.0005
  WEIGHT_DECAY_BIAS: 0.0005
TEST:
  AQE:
    ALPHA: 3.0
    ENABLED: False
    QE_K: 5
    QE_TIME: 1
  EVAL_PERIOD: 60
  IMS_PER_BATCH: 128
  METRIC: cosine
  PRECISE_BN:
    DATASET: Market1501
    ENABLED: False
    NUM_ITER: 300
  RERANK:
    ENABLED: False
    K1: 20
    K2: 6
    LAMBDA: 0.3
  ROC_ENABLED: False
[04/19 10:21:59] fastreid INFO: Full config saved to /home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/logs/msmt17/ResNet50_ViTdefault_LION_MGN/config.yaml
[04/19 10:21:59] fastreid.utils.env INFO: Using a generated random seed 62318657
[04/19 10:21:59] fastreid.engine.defaults INFO: Prepare training set
[04/19 10:36:42] fastreid INFO: Rank of current process: 0. World size: 4
[04/19 10:36:43] fastreid INFO: Environment info:
----------------------  ----------------------------------------------------------------------------------------------
sys.platform            linux
Python                  3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0]
numpy                   1.25.2
fastreid                0.1.0 @/home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/./fastreid
FASTREID_ENV_MODULE     <not set>
PyTorch                 1.12.1+cu113 @/home/ma-user/anaconda3/envs/Generate3D/lib/python3.10/site-packages/torch
PyTorch debug build     False
GPU available           True
GPU 0,1,2,3             Tesla V100S-PCIE-32GB
CUDA_HOME               /usr/local/cuda
Pillow                  10.1.0
torchvision             0.13.1+cu113 @/home/ma-user/anaconda3/envs/Generate3D/lib/python3.10/site-packages/torchvision
torchvision arch flags  sm_35, sm_50, sm_60, sm_70, sm_75, sm_80, sm_86
fvcore                  0.1.5.post20221221
cv2                     4.8.0
----------------------  ----------------------------------------------------------------------------------------------
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 8.5  (built against CUDA 11.7)
    - 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, 

[04/19 10:36:43] fastreid INFO: Command line arguments: Namespace(config_file='configs/CMDM/msmt17_mgn_R50_lion.yml', finetune=False, resume=False, eval_only=False, num_gpus=4, num_machines=1, machine_rank=0, dist_url='tcp://127.0.0.1:38746', opts=[])
[04/19 10:36:43] fastreid INFO: Contents of args.config_file=configs/CMDM/msmt17_mgn_R50_lion.yml:
_BASE_: "../Base-MGN.yml"

MODEL:
  BACKBONE:
    WITH_IBN: False
    EXTRA_BN: True
    PRETRAIN_PATH: "/home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth"
  PIXEL_MEAN: [123.675, 116.280, 103.530]
  PIXEL_STD: [58.395, 57.120, 57.375]

INPUT:
  REA:
    MEAN: [0.0, 0.0, 0.0]
  DO_AUTOAUG: False

SOLVER:
  HEADS_LR_FACTOR: 1.0
  BACKBONE_BN_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: -1

DATASETS:
  NAMES: ("CMDM",)
  TESTS: ("CMDM",)
  KWARGS: 'data_name:msmt17+split_mode:id+split_ratio:1.0'
  ROOT: "/home/ma-user/work/Datasets/ImageReID_Datasets/mixreid"

TEST:
  EVAL_PERIOD: 60

OUTPUT_DIR: "logs/msmt17/ResNet50_ViTdefault_LION_MGN"

[04/19 10:36:43] fastreid INFO: Running with full config:
CUDNN_BENCHMARK: True
DATALOADER:
  NAIVE_WAY: True
  NUM_INSTANCE: 16
  NUM_WORKERS: 8
  PK_SAMPLER: True
DATASETS:
  COMBINEALL: False
  IS_LMDB: False
  KWARGS: data_name:msmt17+split_mode:id+split_ratio:1.0
  NAMES: ('CMDM',)
  ROOT: /home/ma-user/work/Datasets/ImageReID_Datasets/mixreid
  TESTS: ('CMDM',)
INPUT:
  CJ:
    BRIGHTNESS: 0.15
    CONTRAST: 0.15
    ENABLED: False
    HUE: 0.1
    PROB: 0.8
    SATURATION: 0.1
  DO_AUGMIX: False
  DO_AUTOAUG: False
  DO_FLIP: True
  DO_PAD: True
  FLIP_PROB: 0.5
  PADDING: 10
  PADDING_MODE: constant
  REA:
    ENABLED: True
    MEAN: [0.0, 0.0, 0.0]
    PROB: 0.5
  RPT:
    ENABLED: False
    PROB: 0.5
  SIZE_TEST: [384, 128]
  SIZE_TRAIN: [384, 128]
MODEL:
  BACKBONE:
    DEPTH: 50x
    EXTRA_BN: True
    FEAT_DIM: 2048
    LAST_STRIDE: 1
    NAME: build_resnet_backbone
    NORM: BN
    PRETRAIN: True
    PRETRAIN_PATH: /home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth
    WITH_IBN: False
    WITH_NL: False
    WITH_SE: False
  DEVICE: cuda
  FREEZE_LAYERS: ['backbone', 'b1', 'b2', 'b3']
  HEADS:
    CLS_LAYER: circleSoftmax
    EMBEDDING_DIM: 256
    MARGIN: 0.35
    NAME: EmbeddingHead
    NECK_FEAT: after
    NORM: BN
    NUM_CLASSES: 0
    POOL_LAYER: gempoolP
    SCALE: 64
    WITH_BNNECK: True
  LOSSES:
    CE:
      ALPHA: 0.2
      EPSILON: 0.1
      SCALE: 1.0
    CIRCLE:
      ALPHA: 128
      MARGIN: 0.25
      SCALE: 1.0
    FL:
      ALPHA: 0.25
      GAMMA: 2
      SCALE: 1.0
    NAME: ('CrossEntropyLoss', 'TripletLoss')
    TRI:
      HARD_MINING: True
      MARGIN: 0.0
      NORM_FEAT: False
      SCALE: 1.0
  META_ARCHITECTURE: MGN
  PIXEL_MEAN: [123.675, 116.28, 103.53]
  PIXEL_STD: [58.395, 57.12, 57.375]
  WEIGHTS: 
OUTPUT_DIR: logs/msmt17/ResNet50_ViTdefault_LION_MGN
SOLVER:
  AMP_ENABLED: False
  BACKBONE_BN_LR_FACTOR: 1.0
  BASE_LR: 0.00035
  BIAS_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: -1
  DELAY_ITERS: 30
  ETA_MIN_LR: 7.7e-07
  FREEZE_ITERS: 10
  GAMMA: 0.1
  HEADS_LR_FACTOR: 1.0
  IMS_PER_BATCH: 64
  MAX_ITER: 60
  MOMENTUM: 0.9
  OPT: Adam
  SCHED: WarmupCosineAnnealingLR
  STEPS: [40, 90]
  SWA:
    ENABLED: False
    ETA_MIN_LR: 3.5e-06
    ITER: 10
    LR_FACTOR: 10.0
    LR_SCHED: False
    PERIOD: 2
  WARMUP_FACTOR: 0.01
  WARMUP_ITERS: 10
  WARMUP_METHOD: linear
  WEIGHT_DECAY: 0.0005
  WEIGHT_DECAY_BIAS: 0.0005
TEST:
  AQE:
    ALPHA: 3.0
    ENABLED: False
    QE_K: 5
    QE_TIME: 1
  EVAL_PERIOD: 60
  IMS_PER_BATCH: 128
  METRIC: cosine
  PRECISE_BN:
    DATASET: Market1501
    ENABLED: False
    NUM_ITER: 300
  RERANK:
    ENABLED: False
    K1: 20
    K2: 6
    LAMBDA: 0.3
  ROC_ENABLED: False
[04/19 10:36:43] fastreid INFO: Full config saved to /home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/logs/msmt17/ResNet50_ViTdefault_LION_MGN/config.yaml
[04/19 10:36:43] fastreid.utils.env INFO: Using a generated random seed 46092688
[04/19 10:36:43] fastreid.engine.defaults INFO: Prepare training set
[04/19 10:39:51] fastreid INFO: Rank of current process: 0. World size: 4
[04/19 10:39:52] fastreid INFO: Environment info:
----------------------  ----------------------------------------------------------------------------------------------
sys.platform            linux
Python                  3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0]
numpy                   1.25.2
fastreid                0.1.0 @/home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/./fastreid
FASTREID_ENV_MODULE     <not set>
PyTorch                 1.12.1+cu113 @/home/ma-user/anaconda3/envs/Generate3D/lib/python3.10/site-packages/torch
PyTorch debug build     False
GPU available           True
GPU 0,1,2,3             Tesla V100S-PCIE-32GB
CUDA_HOME               /usr/local/cuda
Pillow                  10.1.0
torchvision             0.13.1+cu113 @/home/ma-user/anaconda3/envs/Generate3D/lib/python3.10/site-packages/torchvision
torchvision arch flags  sm_35, sm_50, sm_60, sm_70, sm_75, sm_80, sm_86
fvcore                  0.1.5.post20221221
cv2                     4.8.0
----------------------  ----------------------------------------------------------------------------------------------
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 8.5  (built against CUDA 11.7)
    - 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, 

[04/19 10:39:52] fastreid INFO: Command line arguments: Namespace(config_file='configs/CMDM/msmt17_mgn_R50_lion.yml', finetune=False, resume=False, eval_only=False, num_gpus=4, num_machines=1, machine_rank=0, dist_url='tcp://127.0.0.1:35216', opts=[])
[04/19 10:39:52] fastreid INFO: Contents of args.config_file=configs/CMDM/msmt17_mgn_R50_lion.yml:
_BASE_: "../Base-MGN.yml"

MODEL:
  BACKBONE:
    WITH_IBN: False
    EXTRA_BN: True
    PRETRAIN_PATH: "/home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth"
  PIXEL_MEAN: [123.675, 116.280, 103.530]
  PIXEL_STD: [58.395, 57.120, 57.375]

INPUT:
  REA:
    MEAN: [0.0, 0.0, 0.0]
  DO_AUTOAUG: False

SOLVER:
  HEADS_LR_FACTOR: 1.0
  BACKBONE_BN_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: -1

DATASETS:
  NAMES: ("MSMT17",)
  TESTS: ("MSMT17",)
  #KWARGS: 'data_name:msmt17+split_mode:id+split_ratio:1.0'
  ROOT: "/home/ma-user/work/Datasets/ImageReID_Datasets/mixreid"

TEST:
  EVAL_PERIOD: 60

OUTPUT_DIR: "logs/msmt17/ResNet50_ViTdefault_LION_MGN"

[04/19 10:39:52] fastreid INFO: Running with full config:
CUDNN_BENCHMARK: True
DATALOADER:
  NAIVE_WAY: True
  NUM_INSTANCE: 16
  NUM_WORKERS: 8
  PK_SAMPLER: True
DATASETS:
  COMBINEALL: False
  IS_LMDB: False
  KWARGS: 
  NAMES: ('MSMT17',)
  ROOT: /home/ma-user/work/Datasets/ImageReID_Datasets/mixreid
  TESTS: ('MSMT17',)
INPUT:
  CJ:
    BRIGHTNESS: 0.15
    CONTRAST: 0.15
    ENABLED: False
    HUE: 0.1
    PROB: 0.8
    SATURATION: 0.1
  DO_AUGMIX: False
  DO_AUTOAUG: False
  DO_FLIP: True
  DO_PAD: True
  FLIP_PROB: 0.5
  PADDING: 10
  PADDING_MODE: constant
  REA:
    ENABLED: True
    MEAN: [0.0, 0.0, 0.0]
    PROB: 0.5
  RPT:
    ENABLED: False
    PROB: 0.5
  SIZE_TEST: [384, 128]
  SIZE_TRAIN: [384, 128]
MODEL:
  BACKBONE:
    DEPTH: 50x
    EXTRA_BN: True
    FEAT_DIM: 2048
    LAST_STRIDE: 1
    NAME: build_resnet_backbone
    NORM: BN
    PRETRAIN: True
    PRETRAIN_PATH: /home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth
    WITH_IBN: False
    WITH_NL: False
    WITH_SE: False
  DEVICE: cuda
  FREEZE_LAYERS: ['backbone', 'b1', 'b2', 'b3']
  HEADS:
    CLS_LAYER: circleSoftmax
    EMBEDDING_DIM: 256
    MARGIN: 0.35
    NAME: EmbeddingHead
    NECK_FEAT: after
    NORM: BN
    NUM_CLASSES: 0
    POOL_LAYER: gempoolP
    SCALE: 64
    WITH_BNNECK: True
  LOSSES:
    CE:
      ALPHA: 0.2
      EPSILON: 0.1
      SCALE: 1.0
    CIRCLE:
      ALPHA: 128
      MARGIN: 0.25
      SCALE: 1.0
    FL:
      ALPHA: 0.25
      GAMMA: 2
      SCALE: 1.0
    NAME: ('CrossEntropyLoss', 'TripletLoss')
    TRI:
      HARD_MINING: True
      MARGIN: 0.0
      NORM_FEAT: False
      SCALE: 1.0
  META_ARCHITECTURE: MGN
  PIXEL_MEAN: [123.675, 116.28, 103.53]
  PIXEL_STD: [58.395, 57.12, 57.375]
  WEIGHTS: 
OUTPUT_DIR: logs/msmt17/ResNet50_ViTdefault_LION_MGN
SOLVER:
  AMP_ENABLED: False
  BACKBONE_BN_LR_FACTOR: 1.0
  BASE_LR: 0.00035
  BIAS_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: -1
  DELAY_ITERS: 30
  ETA_MIN_LR: 7.7e-07
  FREEZE_ITERS: 10
  GAMMA: 0.1
  HEADS_LR_FACTOR: 1.0
  IMS_PER_BATCH: 64
  MAX_ITER: 60
  MOMENTUM: 0.9
  OPT: Adam
  SCHED: WarmupCosineAnnealingLR
  STEPS: [40, 90]
  SWA:
    ENABLED: False
    ETA_MIN_LR: 3.5e-06
    ITER: 10
    LR_FACTOR: 10.0
    LR_SCHED: False
    PERIOD: 2
  WARMUP_FACTOR: 0.01
  WARMUP_ITERS: 10
  WARMUP_METHOD: linear
  WEIGHT_DECAY: 0.0005
  WEIGHT_DECAY_BIAS: 0.0005
TEST:
  AQE:
    ALPHA: 3.0
    ENABLED: False
    QE_K: 5
    QE_TIME: 1
  EVAL_PERIOD: 60
  IMS_PER_BATCH: 128
  METRIC: cosine
  PRECISE_BN:
    DATASET: Market1501
    ENABLED: False
    NUM_ITER: 300
  RERANK:
    ENABLED: False
    K1: 20
    K2: 6
    LAMBDA: 0.3
  ROC_ENABLED: False
[04/19 10:39:52] fastreid INFO: Full config saved to /home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/logs/msmt17/ResNet50_ViTdefault_LION_MGN/config.yaml
[04/19 10:39:52] fastreid.utils.env INFO: Using a generated random seed 55013521
[04/19 10:39:52] fastreid.engine.defaults INFO: Prepare training set
[04/19 10:41:41] fastreid INFO: Rank of current process: 0. World size: 4
[04/19 10:41:42] fastreid INFO: Environment info:
----------------------  ----------------------------------------------------------------------------------------------
sys.platform            linux
Python                  3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0]
numpy                   1.25.2
fastreid                0.1.0 @/home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/./fastreid
FASTREID_ENV_MODULE     <not set>
PyTorch                 1.12.1+cu113 @/home/ma-user/anaconda3/envs/Generate3D/lib/python3.10/site-packages/torch
PyTorch debug build     False
GPU available           True
GPU 0,1,2,3             Tesla V100S-PCIE-32GB
CUDA_HOME               /usr/local/cuda
Pillow                  10.1.0
torchvision             0.13.1+cu113 @/home/ma-user/anaconda3/envs/Generate3D/lib/python3.10/site-packages/torchvision
torchvision arch flags  sm_35, sm_50, sm_60, sm_70, sm_75, sm_80, sm_86
fvcore                  0.1.5.post20221221
cv2                     4.8.0
----------------------  ----------------------------------------------------------------------------------------------
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 8.5  (built against CUDA 11.7)
    - 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, 

[04/19 10:41:42] fastreid INFO: Command line arguments: Namespace(config_file='configs/CMDM/msmt17_mgn_R50_lion.yml', finetune=False, resume=False, eval_only=False, num_gpus=4, num_machines=1, machine_rank=0, dist_url='tcp://127.0.0.1:36212', opts=[])
[04/19 10:41:42] fastreid INFO: Contents of args.config_file=configs/CMDM/msmt17_mgn_R50_lion.yml:
_BASE_: "../Base-MGN.yml"

MODEL:
  BACKBONE:
    WITH_IBN: False
    EXTRA_BN: True
    PRETRAIN_PATH: "/home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth"
  PIXEL_MEAN: [123.675, 116.280, 103.530]
  PIXEL_STD: [58.395, 57.120, 57.375]

INPUT:
  REA:
    MEAN: [0.0, 0.0, 0.0]
  DO_AUTOAUG: False

SOLVER:
  HEADS_LR_FACTOR: 1.0
  BACKBONE_BN_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: -1

DATASETS:
  NAMES: ("MSMT17",)
  TESTS: ("MSMT17",)
  #KWARGS: 'data_name:msmt17+split_mode:id+split_ratio:1.0'
  ROOT: "/home/ma-user/work/Datasets/ImageReID_Datasets/mixreid"

TEST:
  EVAL_PERIOD: 60

OUTPUT_DIR: "logs/msmt17/ResNet50_ViTdefault_LION_MGN"

[04/19 10:41:42] fastreid INFO: Running with full config:
CUDNN_BENCHMARK: True
DATALOADER:
  NAIVE_WAY: True
  NUM_INSTANCE: 16
  NUM_WORKERS: 8
  PK_SAMPLER: True
DATASETS:
  COMBINEALL: False
  IS_LMDB: False
  KWARGS: 
  NAMES: ('MSMT17',)
  ROOT: /home/ma-user/work/Datasets/ImageReID_Datasets/mixreid
  TESTS: ('MSMT17',)
INPUT:
  CJ:
    BRIGHTNESS: 0.15
    CONTRAST: 0.15
    ENABLED: False
    HUE: 0.1
    PROB: 0.8
    SATURATION: 0.1
  DO_AUGMIX: False
  DO_AUTOAUG: False
  DO_FLIP: True
  DO_PAD: True
  FLIP_PROB: 0.5
  PADDING: 10
  PADDING_MODE: constant
  REA:
    ENABLED: True
    MEAN: [0.0, 0.0, 0.0]
    PROB: 0.5
  RPT:
    ENABLED: False
    PROB: 0.5
  SIZE_TEST: [384, 128]
  SIZE_TRAIN: [384, 128]
MODEL:
  BACKBONE:
    DEPTH: 50x
    EXTRA_BN: True
    FEAT_DIM: 2048
    LAST_STRIDE: 1
    NAME: build_resnet_backbone
    NORM: BN
    PRETRAIN: True
    PRETRAIN_PATH: /home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth
    WITH_IBN: False
    WITH_NL: False
    WITH_SE: False
  DEVICE: cuda
  FREEZE_LAYERS: ['backbone', 'b1', 'b2', 'b3']
  HEADS:
    CLS_LAYER: circleSoftmax
    EMBEDDING_DIM: 256
    MARGIN: 0.35
    NAME: EmbeddingHead
    NECK_FEAT: after
    NORM: BN
    NUM_CLASSES: 0
    POOL_LAYER: gempoolP
    SCALE: 64
    WITH_BNNECK: True
  LOSSES:
    CE:
      ALPHA: 0.2
      EPSILON: 0.1
      SCALE: 1.0
    CIRCLE:
      ALPHA: 128
      MARGIN: 0.25
      SCALE: 1.0
    FL:
      ALPHA: 0.25
      GAMMA: 2
      SCALE: 1.0
    NAME: ('CrossEntropyLoss', 'TripletLoss')
    TRI:
      HARD_MINING: True
      MARGIN: 0.0
      NORM_FEAT: False
      SCALE: 1.0
  META_ARCHITECTURE: MGN
  PIXEL_MEAN: [123.675, 116.28, 103.53]
  PIXEL_STD: [58.395, 57.12, 57.375]
  WEIGHTS: 
OUTPUT_DIR: logs/msmt17/ResNet50_ViTdefault_LION_MGN
SOLVER:
  AMP_ENABLED: False
  BACKBONE_BN_LR_FACTOR: 1.0
  BASE_LR: 0.00035
  BIAS_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: -1
  DELAY_ITERS: 30
  ETA_MIN_LR: 7.7e-07
  FREEZE_ITERS: 10
  GAMMA: 0.1
  HEADS_LR_FACTOR: 1.0
  IMS_PER_BATCH: 64
  MAX_ITER: 60
  MOMENTUM: 0.9
  OPT: Adam
  SCHED: WarmupCosineAnnealingLR
  STEPS: [40, 90]
  SWA:
    ENABLED: False
    ETA_MIN_LR: 3.5e-06
    ITER: 10
    LR_FACTOR: 10.0
    LR_SCHED: False
    PERIOD: 2
  WARMUP_FACTOR: 0.01
  WARMUP_ITERS: 10
  WARMUP_METHOD: linear
  WEIGHT_DECAY: 0.0005
  WEIGHT_DECAY_BIAS: 0.0005
TEST:
  AQE:
    ALPHA: 3.0
    ENABLED: False
    QE_K: 5
    QE_TIME: 1
  EVAL_PERIOD: 60
  IMS_PER_BATCH: 128
  METRIC: cosine
  PRECISE_BN:
    DATASET: Market1501
    ENABLED: False
    NUM_ITER: 300
  RERANK:
    ENABLED: False
    K1: 20
    K2: 6
    LAMBDA: 0.3
  ROC_ENABLED: False
[04/19 10:41:42] fastreid INFO: Full config saved to /home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/logs/msmt17/ResNet50_ViTdefault_LION_MGN/config.yaml
[04/19 10:41:42] fastreid.utils.env INFO: Using a generated random seed 45085878
[04/19 10:41:42] fastreid.engine.defaults INFO: Prepare training set
[04/19 10:41:42] fastreid.data.datasets.bases INFO: => Loaded MSMT17 in csv format: 
[36m| subset   | # ids   | # images   | # cameras   |
|:---------|:--------|:-----------|:------------|
| train    | 1041    | 30248      | 15          |[0m
[04/19 10:41:42] fastreid.engine.defaults INFO: Auto-scaling the config to num_classes=1041, max_Iter=28320, wamrup_Iter=4720, freeze_Iter=4720, delay_Iter=14160, step_Iter=[18880, 42480], ckpt_Iter=-473, eval_Iter=28400.
[04/19 10:41:45] fastreid.modeling.backbones.resnet INFO: Loading pretrained model from /home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth
[04/19 10:42:03] fastreid.engine.defaults INFO: Freeze layer group "backbone,b1,b2,b3" training for 4720 iterations
[04/19 10:42:03] fastreid.utils.checkpoint INFO: No checkpoint found. Training model from scratch
[04/19 10:42:03] fastreid.engine.train_loop INFO: Starting training from iteration 0
[04/19 10:43:09] fastreid.utils.events INFO:  eta: 2:00:04  iter: 199  total_loss: 56.69  loss_cls_b1: 6.313  loss_cls_b2: 6.325  loss_cls_b21: 6.383  loss_cls_b22: 6.341  loss_cls_b3: 6.395  loss_cls_b31: 6.363  loss_cls_b32: 6.308  loss_cls_b33: 6.409  loss_triplet_b1: 0.9324  loss_triplet_b2: 0.9214  loss_triplet_b3: 0.9329  loss_triplet_b22: 1.303  loss_triplet_b33: 1.54  time: 0.2575  data_time: 0.0008  lr: 1.81e-05  max_mem: 19416M
[04/19 10:43:27] fastreid.engine.hooks INFO: Overall training speed: 256 iterations in 0:01:06 (0.2579 s / it)
[04/19 10:43:27] fastreid.engine.hooks INFO: Total training time: 0:01:18 (0:00:12 on hooks)
[04/19 10:51:05] fastreid INFO: Rank of current process: 0. World size: 4
[04/19 10:51:05] fastreid INFO: Environment info:
----------------------  ----------------------------------------------------------------------------------------------
sys.platform            linux
Python                  3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0]
numpy                   1.25.2
fastreid                0.1.0 @/home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/./fastreid
FASTREID_ENV_MODULE     <not set>
PyTorch                 1.12.1+cu113 @/home/ma-user/anaconda3/envs/Generate3D/lib/python3.10/site-packages/torch
PyTorch debug build     False
GPU available           True
GPU 0,1,2,3             Tesla V100S-PCIE-32GB
CUDA_HOME               /usr/local/cuda
Pillow                  10.1.0
torchvision             0.13.1+cu113 @/home/ma-user/anaconda3/envs/Generate3D/lib/python3.10/site-packages/torchvision
torchvision arch flags  sm_35, sm_50, sm_60, sm_70, sm_75, sm_80, sm_86
fvcore                  0.1.5.post20221221
cv2                     4.8.0
----------------------  ----------------------------------------------------------------------------------------------
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 8.5  (built against CUDA 11.7)
    - 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, 

[04/19 10:51:05] fastreid INFO: Command line arguments: Namespace(config_file='configs/CMDM/msmt17_mgn_R50_lion.yml', finetune=False, resume=False, eval_only=False, num_gpus=4, num_machines=1, machine_rank=0, dist_url='tcp://127.0.0.1:37092', opts=[])
[04/19 10:51:05] fastreid INFO: Contents of args.config_file=configs/CMDM/msmt17_mgn_R50_lion.yml:
_BASE_: "../Base-MGN.yml"

MODEL:
  BACKBONE:
    WITH_IBN: False
    EXTRA_BN: True
    PRETRAIN_PATH: "/home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth"
  PIXEL_MEAN: [123.675, 116.280, 103.530]
  PIXEL_STD: [58.395, 57.120, 57.375]

INPUT:
  REA:
    MEAN: [0.0, 0.0, 0.0]
  DO_AUTOAUG: False

SOLVER:
  HEADS_LR_FACTOR: 1.0
  BACKBONE_BN_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: -1

DATASETS:
  NAMES: ("MSMT17",)
  TESTS: ("MSMT17",)
  KWARGS: 'combineall'
  ROOT: "/home/ma-user/work/Datasets/ImageReID_Datasets/mixreid"

TEST:
  EVAL_PERIOD: 60

OUTPUT_DIR: "logs/msmt17/ResNet50_ViTdefault_LION_MGN"

[04/19 10:51:05] fastreid INFO: Running with full config:
CUDNN_BENCHMARK: True
DATALOADER:
  NAIVE_WAY: True
  NUM_INSTANCE: 16
  NUM_WORKERS: 8
  PK_SAMPLER: True
DATASETS:
  COMBINEALL: False
  IS_LMDB: False
  KWARGS: combineall
  NAMES: ('MSMT17',)
  ROOT: /home/ma-user/work/Datasets/ImageReID_Datasets/mixreid
  TESTS: ('MSMT17',)
INPUT:
  CJ:
    BRIGHTNESS: 0.15
    CONTRAST: 0.15
    ENABLED: False
    HUE: 0.1
    PROB: 0.8
    SATURATION: 0.1
  DO_AUGMIX: False
  DO_AUTOAUG: False
  DO_FLIP: True
  DO_PAD: True
  FLIP_PROB: 0.5
  PADDING: 10
  PADDING_MODE: constant
  REA:
    ENABLED: True
    MEAN: [0.0, 0.0, 0.0]
    PROB: 0.5
  RPT:
    ENABLED: False
    PROB: 0.5
  SIZE_TEST: [384, 128]
  SIZE_TRAIN: [384, 128]
MODEL:
  BACKBONE:
    DEPTH: 50x
    EXTRA_BN: True
    FEAT_DIM: 2048
    LAST_STRIDE: 1
    NAME: build_resnet_backbone
    NORM: BN
    PRETRAIN: True
    PRETRAIN_PATH: /home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth
    WITH_IBN: False
    WITH_NL: False
    WITH_SE: False
  DEVICE: cuda
  FREEZE_LAYERS: ['backbone', 'b1', 'b2', 'b3']
  HEADS:
    CLS_LAYER: circleSoftmax
    EMBEDDING_DIM: 256
    MARGIN: 0.35
    NAME: EmbeddingHead
    NECK_FEAT: after
    NORM: BN
    NUM_CLASSES: 0
    POOL_LAYER: gempoolP
    SCALE: 64
    WITH_BNNECK: True
  LOSSES:
    CE:
      ALPHA: 0.2
      EPSILON: 0.1
      SCALE: 1.0
    CIRCLE:
      ALPHA: 128
      MARGIN: 0.25
      SCALE: 1.0
    FL:
      ALPHA: 0.25
      GAMMA: 2
      SCALE: 1.0
    NAME: ('CrossEntropyLoss', 'TripletLoss')
    TRI:
      HARD_MINING: True
      MARGIN: 0.0
      NORM_FEAT: False
      SCALE: 1.0
  META_ARCHITECTURE: MGN
  PIXEL_MEAN: [123.675, 116.28, 103.53]
  PIXEL_STD: [58.395, 57.12, 57.375]
  WEIGHTS: 
OUTPUT_DIR: logs/msmt17/ResNet50_ViTdefault_LION_MGN
SOLVER:
  AMP_ENABLED: False
  BACKBONE_BN_LR_FACTOR: 1.0
  BASE_LR: 0.00035
  BIAS_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: -1
  DELAY_ITERS: 30
  ETA_MIN_LR: 7.7e-07
  FREEZE_ITERS: 10
  GAMMA: 0.1
  HEADS_LR_FACTOR: 1.0
  IMS_PER_BATCH: 64
  MAX_ITER: 60
  MOMENTUM: 0.9
  OPT: Adam
  SCHED: WarmupCosineAnnealingLR
  STEPS: [40, 90]
  SWA:
    ENABLED: False
    ETA_MIN_LR: 3.5e-06
    ITER: 10
    LR_FACTOR: 10.0
    LR_SCHED: False
    PERIOD: 2
  WARMUP_FACTOR: 0.01
  WARMUP_ITERS: 10
  WARMUP_METHOD: linear
  WEIGHT_DECAY: 0.0005
  WEIGHT_DECAY_BIAS: 0.0005
TEST:
  AQE:
    ALPHA: 3.0
    ENABLED: False
    QE_K: 5
    QE_TIME: 1
  EVAL_PERIOD: 60
  IMS_PER_BATCH: 128
  METRIC: cosine
  PRECISE_BN:
    DATASET: Market1501
    ENABLED: False
    NUM_ITER: 300
  RERANK:
    ENABLED: False
    K1: 20
    K2: 6
    LAMBDA: 0.3
  ROC_ENABLED: False
[04/19 10:51:05] fastreid INFO: Full config saved to /home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/logs/msmt17/ResNet50_ViTdefault_LION_MGN/config.yaml
[04/19 10:51:05] fastreid.utils.env INFO: Using a generated random seed 8743251
[04/19 10:51:05] fastreid.engine.defaults INFO: Prepare training set
[04/19 10:52:25] fastreid INFO: Rank of current process: 0. World size: 4
[04/19 10:52:26] fastreid INFO: Environment info:
----------------------  ----------------------------------------------------------------------------------------------
sys.platform            linux
Python                  3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0]
numpy                   1.25.2
fastreid                0.1.0 @/home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/./fastreid
FASTREID_ENV_MODULE     <not set>
PyTorch                 1.12.1+cu113 @/home/ma-user/anaconda3/envs/Generate3D/lib/python3.10/site-packages/torch
PyTorch debug build     False
GPU available           True
GPU 0,1,2,3             Tesla V100S-PCIE-32GB
CUDA_HOME               /usr/local/cuda
Pillow                  10.1.0
torchvision             0.13.1+cu113 @/home/ma-user/anaconda3/envs/Generate3D/lib/python3.10/site-packages/torchvision
torchvision arch flags  sm_35, sm_50, sm_60, sm_70, sm_75, sm_80, sm_86
fvcore                  0.1.5.post20221221
cv2                     4.8.0
----------------------  ----------------------------------------------------------------------------------------------
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 8.5  (built against CUDA 11.7)
    - 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, 

[04/19 10:52:26] fastreid INFO: Command line arguments: Namespace(config_file='configs/CMDM/msmt17_mgn_R50_lion.yml', finetune=False, resume=False, eval_only=False, num_gpus=4, num_machines=1, machine_rank=0, dist_url='tcp://127.0.0.1:39355', opts=[])
[04/19 10:52:26] fastreid INFO: Contents of args.config_file=configs/CMDM/msmt17_mgn_R50_lion.yml:
_BASE_: "../Base-MGN.yml"

MODEL:
  BACKBONE:
    WITH_IBN: False
    EXTRA_BN: True
    PRETRAIN_PATH: "/home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth"
  PIXEL_MEAN: [123.675, 116.280, 103.530]
  PIXEL_STD: [58.395, 57.120, 57.375]

INPUT:
  REA:
    MEAN: [0.0, 0.0, 0.0]
  DO_AUTOAUG: False

SOLVER:
  HEADS_LR_FACTOR: 1.0
  BACKBONE_BN_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: -1

DATASETS:
  NAMES: ("MSMT17",)
  TESTS: ("MSMT17",)
  ROOT: "/home/ma-user/work/Datasets/ImageReID_Datasets/mixreid"

TEST:
  EVAL_PERIOD: 60

OUTPUT_DIR: "logs/msmt17/ResNet50_ViTdefault_LION_MGN"

[04/19 10:52:26] fastreid INFO: Running with full config:
CUDNN_BENCHMARK: True
DATALOADER:
  NAIVE_WAY: True
  NUM_INSTANCE: 16
  NUM_WORKERS: 8
  PK_SAMPLER: True
DATASETS:
  COMBINEALL: False
  IS_LMDB: False
  KWARGS: 
  NAMES: ('MSMT17',)
  ROOT: /home/ma-user/work/Datasets/ImageReID_Datasets/mixreid
  TESTS: ('MSMT17',)
INPUT:
  CJ:
    BRIGHTNESS: 0.15
    CONTRAST: 0.15
    ENABLED: False
    HUE: 0.1
    PROB: 0.8
    SATURATION: 0.1
  DO_AUGMIX: False
  DO_AUTOAUG: False
  DO_FLIP: True
  DO_PAD: True
  FLIP_PROB: 0.5
  PADDING: 10
  PADDING_MODE: constant
  REA:
    ENABLED: True
    MEAN: [0.0, 0.0, 0.0]
    PROB: 0.5
  RPT:
    ENABLED: False
    PROB: 0.5
  SIZE_TEST: [384, 128]
  SIZE_TRAIN: [384, 128]
MODEL:
  BACKBONE:
    DEPTH: 50x
    EXTRA_BN: True
    FEAT_DIM: 2048
    LAST_STRIDE: 1
    NAME: build_resnet_backbone
    NORM: BN
    PRETRAIN: True
    PRETRAIN_PATH: /home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth
    WITH_IBN: False
    WITH_NL: False
    WITH_SE: False
  DEVICE: cuda
  FREEZE_LAYERS: ['backbone', 'b1', 'b2', 'b3']
  HEADS:
    CLS_LAYER: circleSoftmax
    EMBEDDING_DIM: 256
    MARGIN: 0.35
    NAME: EmbeddingHead
    NECK_FEAT: after
    NORM: BN
    NUM_CLASSES: 0
    POOL_LAYER: gempoolP
    SCALE: 64
    WITH_BNNECK: True
  LOSSES:
    CE:
      ALPHA: 0.2
      EPSILON: 0.1
      SCALE: 1.0
    CIRCLE:
      ALPHA: 128
      MARGIN: 0.25
      SCALE: 1.0
    FL:
      ALPHA: 0.25
      GAMMA: 2
      SCALE: 1.0
    NAME: ('CrossEntropyLoss', 'TripletLoss')
    TRI:
      HARD_MINING: True
      MARGIN: 0.0
      NORM_FEAT: False
      SCALE: 1.0
  META_ARCHITECTURE: MGN
  PIXEL_MEAN: [123.675, 116.28, 103.53]
  PIXEL_STD: [58.395, 57.12, 57.375]
  WEIGHTS: 
OUTPUT_DIR: logs/msmt17/ResNet50_ViTdefault_LION_MGN
SOLVER:
  AMP_ENABLED: False
  BACKBONE_BN_LR_FACTOR: 1.0
  BASE_LR: 0.00035
  BIAS_LR_FACTOR: 1.0
  CHECKPOINT_PERIOD: -1
  DELAY_ITERS: 30
  ETA_MIN_LR: 7.7e-07
  FREEZE_ITERS: 10
  GAMMA: 0.1
  HEADS_LR_FACTOR: 1.0
  IMS_PER_BATCH: 64
  MAX_ITER: 60
  MOMENTUM: 0.9
  OPT: Adam
  SCHED: WarmupCosineAnnealingLR
  STEPS: [40, 90]
  SWA:
    ENABLED: False
    ETA_MIN_LR: 3.5e-06
    ITER: 10
    LR_FACTOR: 10.0
    LR_SCHED: False
    PERIOD: 2
  WARMUP_FACTOR: 0.01
  WARMUP_ITERS: 10
  WARMUP_METHOD: linear
  WEIGHT_DECAY: 0.0005
  WEIGHT_DECAY_BIAS: 0.0005
TEST:
  AQE:
    ALPHA: 3.0
    ENABLED: False
    QE_K: 5
    QE_TIME: 1
  EVAL_PERIOD: 60
  IMS_PER_BATCH: 128
  METRIC: cosine
  PRECISE_BN:
    DATASET: Market1501
    ENABLED: False
    NUM_ITER: 300
  RERANK:
    ENABLED: False
    K1: 20
    K2: 6
    LAMBDA: 0.3
  ROC_ENABLED: False
[04/19 10:52:26] fastreid INFO: Full config saved to /home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/logs/msmt17/ResNet50_ViTdefault_LION_MGN/config.yaml
[04/19 10:52:26] fastreid.utils.env INFO: Using a generated random seed 29006566
[04/19 10:52:26] fastreid.engine.defaults INFO: Prepare training set
[04/19 10:52:26] fastreid.data.datasets.bases INFO: => Loaded MSMT17 in csv format: 
[36m| subset   | # ids   | # images   | # cameras   |
|:---------|:--------|:-----------|:------------|
| train    | 1041    | 32621      | 15          |[0m
[04/19 10:52:26] fastreid.engine.defaults INFO: Auto-scaling the config to num_classes=1041, max_Iter=30540, wamrup_Iter=5090, freeze_Iter=5090, delay_Iter=15270, step_Iter=[20360, 45810], ckpt_Iter=-510, eval_Iter=30600.
[04/19 10:52:27] fastreid.modeling.backbones.resnet INFO: Loading pretrained model from /home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet50_ViTdefault_2468_406080100_bs120_originaldino_noreid.pth
[04/19 10:52:44] fastreid.engine.defaults INFO: Freeze layer group "backbone,b1,b2,b3" training for 5090 iterations
[04/19 10:52:44] fastreid.utils.checkpoint INFO: No checkpoint found. Training model from scratch
[04/19 10:52:44] fastreid.engine.train_loop INFO: Starting training from iteration 0
[04/19 10:53:50] fastreid.utils.events INFO:  eta: 2:09:38  iter: 199  total_loss: 56.75  loss_cls_b1: 6.331  loss_cls_b2: 6.429  loss_cls_b21: 6.375  loss_cls_b22: 6.336  loss_cls_b3: 6.359  loss_cls_b31: 6.34  loss_cls_b32: 6.385  loss_cls_b33: 6.335  loss_triplet_b1: 0.9104  loss_triplet_b2: 0.9191  loss_triplet_b3: 0.9146  loss_triplet_b22: 1.22  loss_triplet_b33: 1.53  time: 0.2577  data_time: 0.0008  lr: 1.70e-05  max_mem: 19416M
[04/19 10:54:51] fastreid.utils.events INFO:  eta: 2:08:21  iter: 399  total_loss: 56.19  loss_cls_b1: 6.268  loss_cls_b2: 6.304  loss_cls_b21: 6.327  loss_cls_b22: 6.231  loss_cls_b3: 6.352  loss_cls_b31: 6.306  loss_cls_b32: 6.254  loss_cls_b33: 6.356  loss_triplet_b1: 0.9243  loss_triplet_b2: 0.9802  loss_triplet_b3: 0.9711  loss_triplet_b22: 1.283  loss_triplet_b33: 1.634  time: 0.2562  data_time: 0.0004  lr: 3.07e-05  max_mem: 19416M
[04/19 10:55:51] fastreid.utils.events INFO:  eta: 2:07:09  iter: 599  total_loss: 55.73  loss_cls_b1: 6.373  loss_cls_b2: 6.335  loss_cls_b21: 6.294  loss_cls_b22: 6.223  loss_cls_b3: 6.362  loss_cls_b31: 6.213  loss_cls_b32: 6.294  loss_cls_b33: 6.315  loss_triplet_b1: 0.8523  loss_triplet_b2: 0.9221  loss_triplet_b3: 0.8978  loss_triplet_b22: 1.234  loss_triplet_b33: 1.532  time: 0.2550  data_time: 0.0007  lr: 4.43e-05  max_mem: 19416M
[04/19 10:56:50] fastreid.utils.events INFO:  eta: 2:06:09  iter: 799  total_loss: 54.14  loss_cls_b1: 6.02  loss_cls_b2: 6.101  loss_cls_b21: 6.126  loss_cls_b22: 6.152  loss_cls_b3: 6.105  loss_cls_b31: 6.175  loss_cls_b32: 6.176  loss_cls_b33: 6.162  loss_triplet_b1: 0.8877  loss_triplet_b2: 0.9326  loss_triplet_b3: 0.9048  loss_triplet_b22: 1.254  loss_triplet_b33: 1.553  time: 0.2545  data_time: 0.0004  lr: 5.79e-05  max_mem: 19416M
[04/19 10:57:50] fastreid.utils.events INFO:  eta: 2:05:11  iter: 999  total_loss: 53.48  loss_cls_b1: 6.097  loss_cls_b2: 6.116  loss_cls_b21: 6.145  loss_cls_b22: 6.151  loss_cls_b3: 6.101  loss_cls_b31: 6.05  loss_cls_b32: 6.049  loss_cls_b33: 6.286  loss_triplet_b1: 0.7595  loss_triplet_b2: 0.7771  loss_triplet_b3: 0.7875  loss_triplet_b22: 1.059  loss_triplet_b33: 1.332  time: 0.2543  data_time: 0.0008  lr: 7.15e-05  max_mem: 19416M
[04/19 10:58:50] fastreid.utils.events INFO:  eta: 2:04:10  iter: 1199  total_loss: 52.75  loss_cls_b1: 5.866  loss_cls_b2: 5.933  loss_cls_b21: 6.009  loss_cls_b22: 5.996  loss_cls_b3: 5.952  loss_cls_b31: 6.014  loss_cls_b32: 5.953  loss_cls_b33: 6.082  loss_triplet_b1: 0.8016  loss_triplet_b2: 0.7993  loss_triplet_b3: 0.7573  loss_triplet_b22: 1.1  loss_triplet_b33: 1.37  time: 0.2540  data_time: 0.0005  lr: 8.51e-05  max_mem: 19416M
[04/19 10:59:50] fastreid.utils.events INFO:  eta: 2:03:19  iter: 1399  total_loss: 50.62  loss_cls_b1: 5.67  loss_cls_b2: 5.674  loss_cls_b21: 5.756  loss_cls_b22: 5.835  loss_cls_b3: 5.762  loss_cls_b31: 5.901  loss_cls_b32: 5.83  loss_cls_b33: 5.857  loss_triplet_b1: 0.7149  loss_triplet_b2: 0.7224  loss_triplet_b3: 0.6913  loss_triplet_b22: 0.9783  loss_triplet_b33: 1.2  time: 0.2540  data_time: 0.0008  lr: 9.87e-05  max_mem: 19416M
[04/19 11:00:50] fastreid.utils.events INFO:  eta: 2:02:33  iter: 1599  total_loss: 48.93  loss_cls_b1: 5.539  loss_cls_b2: 5.553  loss_cls_b21: 5.613  loss_cls_b22: 5.642  loss_cls_b3: 5.591  loss_cls_b31: 5.605  loss_cls_b32: 5.581  loss_cls_b33: 5.751  loss_triplet_b1: 0.6294  loss_triplet_b2: 0.6889  loss_triplet_b3: 0.6528  loss_triplet_b22: 0.8861  loss_triplet_b33: 1.146  time: 0.2539  data_time: 0.0005  lr: 1.12e-04  max_mem: 19416M
[04/19 11:01:50] fastreid.utils.events INFO:  eta: 2:01:47  iter: 1799  total_loss: 47.56  loss_cls_b1: 5.393  loss_cls_b2: 5.448  loss_cls_b21: 5.412  loss_cls_b22: 5.535  loss_cls_b3: 5.51  loss_cls_b31: 5.586  loss_cls_b32: 5.593  loss_cls_b33: 5.625  loss_triplet_b1: 0.6901  loss_triplet_b2: 0.7009  loss_triplet_b3: 0.6946  loss_triplet_b22: 0.993  loss_triplet_b33: 1.214  time: 0.2538  data_time: 0.0008  lr: 1.26e-04  max_mem: 19416M
[04/19 11:02:50] fastreid.utils.events INFO:  eta: 2:01:00  iter: 1999  total_loss: 46.18  loss_cls_b1: 5.121  loss_cls_b2: 5.108  loss_cls_b21: 5.158  loss_cls_b22: 5.298  loss_cls_b3: 5.164  loss_cls_b31: 5.248  loss_cls_b32: 5.214  loss_cls_b33: 5.489  loss_triplet_b1: 0.6952  loss_triplet_b2: 0.6783  loss_triplet_b3: 0.7117  loss_triplet_b22: 0.9589  loss_triplet_b33: 1.179  time: 0.2537  data_time: 0.0006  lr: 1.40e-04  max_mem: 19416M
[04/19 11:03:50] fastreid.utils.events INFO:  eta: 2:00:07  iter: 2199  total_loss: 45.65  loss_cls_b1: 5.038  loss_cls_b2: 5.082  loss_cls_b21: 5.152  loss_cls_b22: 5.33  loss_cls_b3: 5.138  loss_cls_b31: 5.142  loss_cls_b32: 5.111  loss_cls_b33: 5.331  loss_triplet_b1: 0.6146  loss_triplet_b2: 0.6145  loss_triplet_b3: 0.5846  loss_triplet_b22: 0.8148  loss_triplet_b33: 1.026  time: 0.2536  data_time: 0.0009  lr: 1.53e-04  max_mem: 19416M
[04/19 11:04:50] fastreid.utils.events INFO:  eta: 1:59:10  iter: 2399  total_loss: 43.37  loss_cls_b1: 4.768  loss_cls_b2: 4.673  loss_cls_b21: 4.776  loss_cls_b22: 4.9  loss_cls_b3: 4.727  loss_cls_b31: 4.839  loss_cls_b32: 4.944  loss_cls_b33: 5.038  loss_triplet_b1: 0.5946  loss_triplet_b2: 0.6162  loss_triplet_b3: 0.5704  loss_triplet_b22: 0.8402  loss_triplet_b33: 1.039  time: 0.2535  data_time: 0.0006  lr: 1.67e-04  max_mem: 19416M
[04/19 11:05:49] fastreid.utils.events INFO:  eta: 1:58:08  iter: 2599  total_loss: 41.14  loss_cls_b1: 4.466  loss_cls_b2: 4.773  loss_cls_b21: 4.706  loss_cls_b22: 4.807  loss_cls_b3: 4.58  loss_cls_b31: 4.908  loss_cls_b32: 4.778  loss_cls_b33: 4.962  loss_triplet_b1: 0.6797  loss_triplet_b2: 0.6526  loss_triplet_b3: 0.6312  loss_triplet_b22: 0.877  loss_triplet_b33: 1.063  time: 0.2533  data_time: 0.0008  lr: 1.80e-04  max_mem: 19416M
[04/19 11:06:49] fastreid.utils.events INFO:  eta: 1:57:12  iter: 2799  total_loss: 40.42  loss_cls_b1: 4.372  loss_cls_b2: 4.429  loss_cls_b21: 4.662  loss_cls_b22: 4.568  loss_cls_b3: 4.365  loss_cls_b31: 4.701  loss_cls_b32: 4.611  loss_cls_b33: 4.833  loss_triplet_b1: 0.5835  loss_triplet_b2: 0.5349  loss_triplet_b3: 0.5718  loss_triplet_b22: 0.8031  loss_triplet_b33: 1.017  time: 0.2533  data_time: 0.0007  lr: 1.94e-04  max_mem: 19416M
[04/19 11:07:49] fastreid.utils.events INFO:  eta: 1:56:20  iter: 2999  total_loss: 30.94  loss_cls_b1: 3.174  loss_cls_b2: 3.189  loss_cls_b21: 3.454  loss_cls_b22: 3.71  loss_cls_b3: 3.191  loss_cls_b31: 3.589  loss_cls_b32: 3.39  loss_cls_b33: 4.059  loss_triplet_b1: 0.5049  loss_triplet_b2: 0.5242  loss_triplet_b3: 0.5028  loss_triplet_b22: 0.717  loss_triplet_b33: 0.8115  time: 0.2533  data_time: 0.0005  lr: 2.08e-04  max_mem: 19416M
[04/19 11:08:49] fastreid.utils.events INFO:  eta: 1:55:29  iter: 3199  total_loss: 37.26  loss_cls_b1: 3.946  loss_cls_b2: 4.089  loss_cls_b21: 4.182  loss_cls_b22: 4.354  loss_cls_b3: 4.019  loss_cls_b31: 4.186  loss_cls_b32: 4.349  loss_cls_b33: 4.584  loss_triplet_b1: 0.6516  loss_triplet_b2: 0.6068  loss_triplet_b3: 0.6326  loss_triplet_b22: 0.9574  loss_triplet_b33: 1.046  time: 0.2532  data_time: 0.0007  lr: 2.21e-04  max_mem: 19416M
[04/19 11:09:49] fastreid.utils.events INFO:  eta: 1:54:44  iter: 3399  total_loss: 32.37  loss_cls_b1: 3.16  loss_cls_b2: 3.335  loss_cls_b21: 3.417  loss_cls_b22: 3.671  loss_cls_b3: 3.289  loss_cls_b31: 3.639  loss_cls_b32: 3.569  loss_cls_b33: 3.956  loss_triplet_b1: 0.5672  loss_triplet_b2: 0.6064  loss_triplet_b3: 0.5753  loss_triplet_b22: 0.8105  loss_triplet_b33: 0.9372  time: 0.2532  data_time: 0.0004  lr: 2.35e-04  max_mem: 19416M
[04/19 11:10:49] fastreid.utils.events INFO:  eta: 1:53:53  iter: 3599  total_loss: 34  loss_cls_b1: 3.618  loss_cls_b2: 3.681  loss_cls_b21: 4.014  loss_cls_b22: 3.959  loss_cls_b3: 3.621  loss_cls_b31: 4.116  loss_cls_b32: 4.025  loss_cls_b33: 4.178  loss_triplet_b1: 0.59  loss_triplet_b2: 0.5789  loss_triplet_b3: 0.5953  loss_triplet_b22: 0.7766  loss_triplet_b33: 0.8921  time: 0.2531  data_time: 0.0007  lr: 2.49e-04  max_mem: 19416M
[04/19 11:11:49] fastreid.utils.events INFO:  eta: 1:53:01  iter: 3799  total_loss: 31.4  loss_cls_b1: 3.175  loss_cls_b2: 3.195  loss_cls_b21: 3.468  loss_cls_b22: 3.725  loss_cls_b3: 3.209  loss_cls_b31: 3.584  loss_cls_b32: 3.577  loss_cls_b33: 3.927  loss_triplet_b1: 0.5703  loss_triplet_b2: 0.5653  loss_triplet_b3: 0.5359  loss_triplet_b22: 0.7614  loss_triplet_b33: 0.939  time: 0.2531  data_time: 0.0005  lr: 2.62e-04  max_mem: 19416M
[04/19 11:12:48] fastreid.utils.events INFO:  eta: 1:52:00  iter: 3999  total_loss: 32.65  loss_cls_b1: 3.372  loss_cls_b2: 3.36  loss_cls_b21: 3.708  loss_cls_b22: 3.875  loss_cls_b3: 3.472  loss_cls_b31: 3.732  loss_cls_b32: 3.803  loss_cls_b33: 4.091  loss_triplet_b1: 0.5849  loss_triplet_b2: 0.5853  loss_triplet_b3: 0.6043  loss_triplet_b22: 0.7504  loss_triplet_b33: 0.8849  time: 0.2530  data_time: 0.0008  lr: 2.76e-04  max_mem: 19416M
[04/19 11:13:48] fastreid.utils.events INFO:  eta: 1:51:11  iter: 4199  total_loss: 29.47  loss_cls_b1: 3.154  loss_cls_b2: 2.995  loss_cls_b21: 3.245  loss_cls_b22: 3.516  loss_cls_b3: 3.163  loss_cls_b31: 3.366  loss_cls_b32: 3.427  loss_cls_b33: 3.89  loss_triplet_b1: 0.442  loss_triplet_b2: 0.4548  loss_triplet_b3: 0.4659  loss_triplet_b22: 0.6148  loss_triplet_b33: 0.7504  time: 0.2530  data_time: 0.0005  lr: 2.89e-04  max_mem: 19416M
[04/19 11:14:48] fastreid.utils.events INFO:  eta: 1:50:21  iter: 4399  total_loss: 29.48  loss_cls_b1: 3.086  loss_cls_b2: 3.12  loss_cls_b21: 3.378  loss_cls_b22: 3.405  loss_cls_b3: 2.96  loss_cls_b31: 3.483  loss_cls_b32: 3.389  loss_cls_b33: 3.702  loss_triplet_b1: 0.445  loss_triplet_b2: 0.44  loss_triplet_b3: 0.4326  loss_triplet_b22: 0.5208  loss_triplet_b33: 0.632  time: 0.2530  data_time: 0.0009  lr: 3.03e-04  max_mem: 19416M
[04/19 11:15:48] fastreid.utils.events INFO:  eta: 1:49:28  iter: 4599  total_loss: 28.04  loss_cls_b1: 2.92  loss_cls_b2: 2.91  loss_cls_b21: 3.167  loss_cls_b22: 3.29  loss_cls_b3: 2.908  loss_cls_b31: 3.33  loss_cls_b32: 3.291  loss_cls_b33: 3.682  loss_triplet_b1: 0.4365  loss_triplet_b2: 0.4402  loss_triplet_b3: 0.4073  loss_triplet_b22: 0.5929  loss_triplet_b33: 0.7232  time: 0.2529  data_time: 0.0006  lr: 3.17e-04  max_mem: 19416M
[04/19 11:16:48] fastreid.utils.events INFO:  eta: 1:48:40  iter: 4799  total_loss: 29.84  loss_cls_b1: 3.045  loss_cls_b2: 3.056  loss_cls_b21: 3.25  loss_cls_b22: 3.544  loss_cls_b3: 2.997  loss_cls_b31: 3.41  loss_cls_b32: 3.376  loss_cls_b33: 3.966  loss_triplet_b1: 0.5512  loss_triplet_b2: 0.539  loss_triplet_b3: 0.5001  loss_triplet_b22: 0.6813  loss_triplet_b33: 0.7274  time: 0.2529  data_time: 0.0008  lr: 3.30e-04  max_mem: 19416M
[04/19 11:17:48] fastreid.utils.events INFO:  eta: 1:47:51  iter: 4999  total_loss: 26.91  loss_cls_b1: 2.755  loss_cls_b2: 2.729  loss_cls_b21: 3.04  loss_cls_b22: 3.164  loss_cls_b3: 2.719  loss_cls_b31: 3.103  loss_cls_b32: 3.131  loss_cls_b33: 3.541  loss_triplet_b1: 0.4556  loss_triplet_b2: 0.4724  loss_triplet_b3: 0.4497  loss_triplet_b22: 0.6303  loss_triplet_b33: 0.6885  time: 0.2529  data_time: 0.0006  lr: 3.44e-04  max_mem: 19416M
[04/19 11:18:50] fastreid.utils.events INFO:  eta: 1:47:27  iter: 5199  total_loss: 29.93  loss_cls_b1: 3.213  loss_cls_b2: 3.103  loss_cls_b21: 3.308  loss_cls_b22: 3.563  loss_cls_b3: 3.068  loss_cls_b31: 3.592  loss_cls_b32: 3.284  loss_cls_b33: 3.962  loss_triplet_b1: 0.4426  loss_triplet_b2: 0.3894  loss_triplet_b3: 0.4274  loss_triplet_b22: 0.5046  loss_triplet_b33: 0.6389  time: 0.2543  data_time: 0.0011  lr: 3.50e-04  max_mem: 19416M
[04/19 11:19:53] fastreid.utils.events INFO:  eta: 1:47:42  iter: 5399  total_loss: 26.12  loss_cls_b1: 2.803  loss_cls_b2: 2.78  loss_cls_b21: 2.968  loss_cls_b22: 3.25  loss_cls_b3: 2.708  loss_cls_b31: 3.251  loss_cls_b32: 3.127  loss_cls_b33: 3.596  loss_triplet_b1: 0.3062  loss_triplet_b2: 0.2746  loss_triplet_b3: 0.2754  loss_triplet_b22: 0.3539  loss_triplet_b33: 0.4401  time: 0.2566  data_time: 0.0006  lr: 3.50e-04  max_mem: 19416M
[04/19 11:20:57] fastreid.utils.events INFO:  eta: 2:09:28  iter: 5599  total_loss: 21.32  loss_cls_b1: 2.061  loss_cls_b2: 2.03  loss_cls_b21: 2.223  loss_cls_b22: 2.642  loss_cls_b3: 2.043  loss_cls_b31: 2.429  loss_cls_b32: 2.58  loss_cls_b33: 3.106  loss_triplet_b1: 0.3066  loss_triplet_b2: 0.2999  loss_triplet_b3: 0.2661  loss_triplet_b22: 0.413  loss_triplet_b33: 0.4478  time: 0.2587  data_time: 0.0008  lr: 3.50e-04  max_mem: 19416M
[04/19 11:22:01] fastreid.utils.events INFO:  eta: 2:09:49  iter: 5799  total_loss: 24.89  loss_cls_b1: 2.671  loss_cls_b2: 2.539  loss_cls_b21: 2.996  loss_cls_b22: 2.964  loss_cls_b3: 2.504  loss_cls_b31: 3.052  loss_cls_b32: 3.092  loss_cls_b33: 3.308  loss_triplet_b1: 0.245  loss_triplet_b2: 0.234  loss_triplet_b3: 0.2358  loss_triplet_b22: 0.3076  loss_triplet_b33: 0.3883  time: 0.2607  data_time: 0.0006  lr: 3.50e-04  max_mem: 19416M
[04/19 11:23:04] fastreid.utils.events INFO:  eta: 2:09:04  iter: 5999  total_loss: 20.24  loss_cls_b1: 2.01  loss_cls_b2: 1.966  loss_cls_b21: 2.249  loss_cls_b22: 2.767  loss_cls_b3: 1.993  loss_cls_b31: 2.426  loss_cls_b32: 2.522  loss_cls_b33: 3.1  loss_triplet_b1: 0.25  loss_triplet_b2: 0.2073  loss_triplet_b3: 0.2105  loss_triplet_b22: 0.2942  loss_triplet_b33: 0.3393  time: 0.2625  data_time: 0.0004  lr: 3.50e-04  max_mem: 19416M
[04/19 11:24:08] fastreid.utils.events INFO:  eta: 2:08:06  iter: 6199  total_loss: 24.02  loss_cls_b1: 2.631  loss_cls_b2: 2.461  loss_cls_b21: 2.824  loss_cls_b22: 3.013  loss_cls_b3: 2.497  loss_cls_b31: 3.022  loss_cls_b32: 3.024  loss_cls_b33: 3.378  loss_triplet_b1: 0.257  loss_triplet_b2: 0.2119  loss_triplet_b3: 0.2004  loss_triplet_b22: 0.2747  loss_triplet_b33: 0.3272  time: 0.2642  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 11:25:12] fastreid.utils.events INFO:  eta: 2:07:07  iter: 6399  total_loss: 23.52  loss_cls_b1: 2.36  loss_cls_b2: 2.276  loss_cls_b21: 2.575  loss_cls_b22: 2.841  loss_cls_b3: 2.315  loss_cls_b31: 2.793  loss_cls_b32: 2.766  loss_cls_b33: 3.37  loss_triplet_b1: 0.3219  loss_triplet_b2: 0.2598  loss_triplet_b3: 0.2787  loss_triplet_b22: 0.3435  loss_triplet_b33: 0.3964  time: 0.2659  data_time: 0.0005  lr: 3.50e-04  max_mem: 19416M
[04/19 11:26:15] fastreid.utils.events INFO:  eta: 2:06:03  iter: 6599  total_loss: 21  loss_cls_b1: 2.288  loss_cls_b2: 2.096  loss_cls_b21: 2.572  loss_cls_b22: 2.674  loss_cls_b3: 2.076  loss_cls_b31: 2.654  loss_cls_b32: 2.802  loss_cls_b33: 3.03  loss_triplet_b1: 0.2051  loss_triplet_b2: 0.1477  loss_triplet_b3: 0.1928  loss_triplet_b22: 0.2247  loss_triplet_b33: 0.2617  time: 0.2674  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 11:27:19] fastreid.utils.events INFO:  eta: 2:05:00  iter: 6799  total_loss: 18.62  loss_cls_b1: 1.826  loss_cls_b2: 1.769  loss_cls_b21: 2.179  loss_cls_b22: 2.285  loss_cls_b3: 1.797  loss_cls_b31: 2.381  loss_cls_b32: 2.397  loss_cls_b33: 2.812  loss_triplet_b1: 0.1559  loss_triplet_b2: 0.1305  loss_triplet_b3: 0.1527  loss_triplet_b22: 0.172  loss_triplet_b33: 0.2296  time: 0.2688  data_time: 0.0005  lr: 3.50e-04  max_mem: 19416M
[04/19 11:28:22] fastreid.utils.events INFO:  eta: 2:03:59  iter: 6999  total_loss: 18.87  loss_cls_b1: 2.067  loss_cls_b2: 1.908  loss_cls_b21: 2.286  loss_cls_b22: 2.358  loss_cls_b3: 1.948  loss_cls_b31: 2.417  loss_cls_b32: 2.536  loss_cls_b33: 2.788  loss_triplet_b1: 0.1315  loss_triplet_b2: 0.1131  loss_triplet_b3: 0.1019  loss_triplet_b22: 0.1391  loss_triplet_b33: 0.1719  time: 0.2702  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 11:29:26] fastreid.utils.events INFO:  eta: 2:02:59  iter: 7199  total_loss: 18.47  loss_cls_b1: 1.841  loss_cls_b2: 1.758  loss_cls_b21: 2.165  loss_cls_b22: 2.39  loss_cls_b3: 1.77  loss_cls_b31: 2.419  loss_cls_b32: 2.327  loss_cls_b33: 2.838  loss_triplet_b1: 0.1944  loss_triplet_b2: 0.1572  loss_triplet_b3: 0.1534  loss_triplet_b22: 0.1596  loss_triplet_b33: 0.1886  time: 0.2715  data_time: 0.0005  lr: 3.50e-04  max_mem: 19416M
[04/19 11:30:30] fastreid.utils.events INFO:  eta: 2:01:54  iter: 7399  total_loss: 18.24  loss_cls_b1: 1.915  loss_cls_b2: 1.824  loss_cls_b21: 2.209  loss_cls_b22: 2.366  loss_cls_b3: 1.859  loss_cls_b31: 2.434  loss_cls_b32: 2.404  loss_cls_b33: 2.72  loss_triplet_b1: 0.1511  loss_triplet_b2: 0.1261  loss_triplet_b3: 0.12  loss_triplet_b22: 0.1573  loss_triplet_b33: 0.1998  time: 0.2727  data_time: 0.0008  lr: 3.50e-04  max_mem: 19416M
[04/19 11:31:33] fastreid.utils.events INFO:  eta: 2:00:51  iter: 7599  total_loss: 17.61  loss_cls_b1: 1.779  loss_cls_b2: 1.764  loss_cls_b21: 1.978  loss_cls_b22: 2.331  loss_cls_b3: 1.731  loss_cls_b31: 2.181  loss_cls_b32: 2.196  loss_cls_b33: 2.755  loss_triplet_b1: 0.1358  loss_triplet_b2: 0.09701  loss_triplet_b3: 0.1074  loss_triplet_b22: 0.1403  loss_triplet_b33: 0.1607  time: 0.2738  data_time: 0.0006  lr: 3.50e-04  max_mem: 19416M
[04/19 11:32:37] fastreid.utils.events INFO:  eta: 1:59:51  iter: 7799  total_loss: 18.87  loss_cls_b1: 1.954  loss_cls_b2: 1.895  loss_cls_b21: 2.241  loss_cls_b22: 2.375  loss_cls_b3: 1.844  loss_cls_b31: 2.438  loss_cls_b32: 2.394  loss_cls_b33: 2.8  loss_triplet_b1: 0.1393  loss_triplet_b2: 0.1259  loss_triplet_b3: 0.1299  loss_triplet_b22: 0.1507  loss_triplet_b33: 0.1951  time: 0.2749  data_time: 0.0009  lr: 3.50e-04  max_mem: 19416M
[04/19 11:33:41] fastreid.utils.events INFO:  eta: 1:58:47  iter: 7999  total_loss: 18.67  loss_cls_b1: 1.951  loss_cls_b2: 1.862  loss_cls_b21: 2.272  loss_cls_b22: 2.376  loss_cls_b3: 1.856  loss_cls_b31: 2.437  loss_cls_b32: 2.391  loss_cls_b33: 2.794  loss_triplet_b1: 0.1613  loss_triplet_b2: 0.1298  loss_triplet_b3: 0.1237  loss_triplet_b22: 0.1791  loss_triplet_b33: 0.2033  time: 0.2760  data_time: 0.0006  lr: 3.50e-04  max_mem: 19416M
[04/19 11:34:44] fastreid.utils.events INFO:  eta: 1:57:39  iter: 8199  total_loss: 13.76  loss_cls_b1: 1.385  loss_cls_b2: 1.278  loss_cls_b21: 1.667  loss_cls_b22: 1.88  loss_cls_b3: 1.292  loss_cls_b31: 1.863  loss_cls_b32: 1.738  loss_cls_b33: 2.551  loss_triplet_b1: 0.09708  loss_triplet_b2: 0.07794  loss_triplet_b3: 0.08886  loss_triplet_b22: 0.09944  loss_triplet_b33: 0.135  time: 0.2769  data_time: 0.0009  lr: 3.50e-04  max_mem: 19416M
[04/19 11:35:48] fastreid.utils.events INFO:  eta: 1:56:34  iter: 8399  total_loss: 16.66  loss_cls_b1: 1.721  loss_cls_b2: 1.586  loss_cls_b21: 1.882  loss_cls_b22: 2.207  loss_cls_b3: 1.595  loss_cls_b31: 2.137  loss_cls_b32: 2.211  loss_cls_b33: 2.677  loss_triplet_b1: 0.137  loss_triplet_b2: 0.1029  loss_triplet_b3: 0.1048  loss_triplet_b22: 0.1375  loss_triplet_b33: 0.1429  time: 0.2779  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 11:36:51] fastreid.utils.events INFO:  eta: 1:55:32  iter: 8599  total_loss: 13.94  loss_cls_b1: 1.326  loss_cls_b2: 1.265  loss_cls_b21: 1.682  loss_cls_b22: 1.932  loss_cls_b3: 1.258  loss_cls_b31: 1.812  loss_cls_b32: 1.818  loss_cls_b33: 2.356  loss_triplet_b1: 0.1544  loss_triplet_b2: 0.141  loss_triplet_b3: 0.1502  loss_triplet_b22: 0.1816  loss_triplet_b33: 0.2068  time: 0.2788  data_time: 0.0004  lr: 3.50e-04  max_mem: 19416M
[04/19 11:37:55] fastreid.utils.events INFO:  eta: 1:54:26  iter: 8799  total_loss: 16.14  loss_cls_b1: 1.734  loss_cls_b2: 1.59  loss_cls_b21: 1.906  loss_cls_b22: 2.048  loss_cls_b3: 1.566  loss_cls_b31: 2.074  loss_cls_b32: 2.027  loss_cls_b33: 2.473  loss_triplet_b1: 0.1446  loss_triplet_b2: 0.1155  loss_triplet_b3: 0.122  loss_triplet_b22: 0.1454  loss_triplet_b33: 0.1831  time: 0.2796  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 11:38:59] fastreid.utils.events INFO:  eta: 1:53:25  iter: 8999  total_loss: 14.83  loss_cls_b1: 1.525  loss_cls_b2: 1.34  loss_cls_b21: 1.749  loss_cls_b22: 1.978  loss_cls_b3: 1.346  loss_cls_b31: 1.885  loss_cls_b32: 1.955  loss_cls_b33: 2.449  loss_triplet_b1: 0.1384  loss_triplet_b2: 0.1115  loss_triplet_b3: 0.1183  loss_triplet_b22: 0.154  loss_triplet_b33: 0.1743  time: 0.2804  data_time: 0.0004  lr: 3.50e-04  max_mem: 19416M
[04/19 11:40:02] fastreid.utils.events INFO:  eta: 1:52:24  iter: 9199  total_loss: 16.13  loss_cls_b1: 1.698  loss_cls_b2: 1.493  loss_cls_b21: 1.857  loss_cls_b22: 2.037  loss_cls_b3: 1.571  loss_cls_b31: 2.064  loss_cls_b32: 2.141  loss_cls_b33: 2.474  loss_triplet_b1: 0.1514  loss_triplet_b2: 0.1085  loss_triplet_b3: 0.1228  loss_triplet_b22: 0.1585  loss_triplet_b33: 0.1855  time: 0.2812  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 11:41:06] fastreid.utils.events INFO:  eta: 1:51:19  iter: 9399  total_loss: 14.97  loss_cls_b1: 1.418  loss_cls_b2: 1.406  loss_cls_b21: 1.694  loss_cls_b22: 2.029  loss_cls_b3: 1.343  loss_cls_b31: 1.907  loss_cls_b32: 1.952  loss_cls_b33: 2.448  loss_triplet_b1: 0.1282  loss_triplet_b2: 0.1024  loss_triplet_b3: 0.09468  loss_triplet_b22: 0.1321  loss_triplet_b33: 0.1272  time: 0.2819  data_time: 0.0005  lr: 3.50e-04  max_mem: 19416M
[04/19 11:42:10] fastreid.utils.events INFO:  eta: 1:50:16  iter: 9599  total_loss: 15.05  loss_cls_b1: 1.576  loss_cls_b2: 1.44  loss_cls_b21: 1.83  loss_cls_b22: 2.032  loss_cls_b3: 1.43  loss_cls_b31: 1.915  loss_cls_b32: 2.028  loss_cls_b33: 2.481  loss_triplet_b1: 0.1187  loss_triplet_b2: 0.09573  loss_triplet_b3: 0.08498  loss_triplet_b22: 0.1182  loss_triplet_b33: 0.1181  time: 0.2827  data_time: 0.0008  lr: 3.50e-04  max_mem: 19416M
[04/19 11:43:13] fastreid.utils.events INFO:  eta: 1:49:11  iter: 9799  total_loss: 14.68  loss_cls_b1: 1.468  loss_cls_b2: 1.359  loss_cls_b21: 1.678  loss_cls_b22: 1.964  loss_cls_b3: 1.311  loss_cls_b31: 1.859  loss_cls_b32: 1.928  loss_cls_b33: 2.381  loss_triplet_b1: 0.1272  loss_triplet_b2: 0.09815  loss_triplet_b3: 0.09975  loss_triplet_b22: 0.134  loss_triplet_b33: 0.1661  time: 0.2834  data_time: 0.0005  lr: 3.50e-04  max_mem: 19416M
[04/19 11:44:17] fastreid.utils.events INFO:  eta: 1:48:08  iter: 9999  total_loss: 14.8  loss_cls_b1: 1.417  loss_cls_b2: 1.422  loss_cls_b21: 1.739  loss_cls_b22: 1.997  loss_cls_b3: 1.395  loss_cls_b31: 2.003  loss_cls_b32: 2.088  loss_cls_b33: 2.396  loss_triplet_b1: 0.1233  loss_triplet_b2: 0.09963  loss_triplet_b3: 0.09726  loss_triplet_b22: 0.1297  loss_triplet_b33: 0.1322  time: 0.2840  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 11:45:20] fastreid.utils.events INFO:  eta: 1:47:04  iter: 10199  total_loss: 14.12  loss_cls_b1: 1.481  loss_cls_b2: 1.342  loss_cls_b21: 1.703  loss_cls_b22: 1.865  loss_cls_b3: 1.353  loss_cls_b31: 1.89  loss_cls_b32: 1.93  loss_cls_b33: 2.221  loss_triplet_b1: 0.1297  loss_triplet_b2: 0.08233  loss_triplet_b3: 0.0923  loss_triplet_b22: 0.1058  loss_triplet_b33: 0.12  time: 0.2846  data_time: 0.0005  lr: 3.50e-04  max_mem: 19416M
[04/19 11:46:24] fastreid.utils.events INFO:  eta: 1:46:04  iter: 10399  total_loss: 14.49  loss_cls_b1: 1.443  loss_cls_b2: 1.361  loss_cls_b21: 1.749  loss_cls_b22: 1.996  loss_cls_b3: 1.293  loss_cls_b31: 1.842  loss_cls_b32: 2.03  loss_cls_b33: 2.342  loss_triplet_b1: 0.1045  loss_triplet_b2: 0.083  loss_triplet_b3: 0.09174  loss_triplet_b22: 0.1178  loss_triplet_b33: 0.1341  time: 0.2853  data_time: 0.0008  lr: 3.50e-04  max_mem: 19416M
[04/19 11:47:28] fastreid.utils.events INFO:  eta: 1:45:00  iter: 10599  total_loss: 14.21  loss_cls_b1: 1.493  loss_cls_b2: 1.384  loss_cls_b21: 1.665  loss_cls_b22: 1.846  loss_cls_b3: 1.356  loss_cls_b31: 1.849  loss_cls_b32: 1.977  loss_cls_b33: 2.265  loss_triplet_b1: 0.1258  loss_triplet_b2: 0.08909  loss_triplet_b3: 0.1023  loss_triplet_b22: 0.1252  loss_triplet_b33: 0.1588  time: 0.2858  data_time: 0.0006  lr: 3.50e-04  max_mem: 19416M
[04/19 11:48:31] fastreid.utils.events INFO:  eta: 1:43:58  iter: 10799  total_loss: 14.85  loss_cls_b1: 1.537  loss_cls_b2: 1.413  loss_cls_b21: 1.704  loss_cls_b22: 1.94  loss_cls_b3: 1.365  loss_cls_b31: 1.838  loss_cls_b32: 2.088  loss_cls_b33: 2.234  loss_triplet_b1: 0.09564  loss_triplet_b2: 0.07825  loss_triplet_b3: 0.09834  loss_triplet_b22: 0.09168  loss_triplet_b33: 0.1192  time: 0.2864  data_time: 0.0008  lr: 3.50e-04  max_mem: 19416M
[04/19 11:49:35] fastreid.utils.events INFO:  eta: 1:42:54  iter: 10999  total_loss: 15.31  loss_cls_b1: 1.542  loss_cls_b2: 1.402  loss_cls_b21: 1.721  loss_cls_b22: 2.034  loss_cls_b3: 1.416  loss_cls_b31: 1.932  loss_cls_b32: 2.027  loss_cls_b33: 2.372  loss_triplet_b1: 0.148  loss_triplet_b2: 0.1123  loss_triplet_b3: 0.1042  loss_triplet_b22: 0.1371  loss_triplet_b33: 0.17  time: 0.2869  data_time: 0.0006  lr: 3.50e-04  max_mem: 19416M
[04/19 11:50:38] fastreid.utils.events INFO:  eta: 1:41:49  iter: 11199  total_loss: 9.145  loss_cls_b1: 0.8562  loss_cls_b2: 0.7412  loss_cls_b21: 1.08  loss_cls_b22: 1.146  loss_cls_b3: 0.7265  loss_cls_b31: 1.199  loss_cls_b32: 1.238  loss_cls_b33: 1.585  loss_triplet_b1: 0.08551  loss_triplet_b2: 0.0604  loss_triplet_b3: 0.06034  loss_triplet_b22: 0.07854  loss_triplet_b33: 0.08652  time: 0.2875  data_time: 0.0008  lr: 3.50e-04  max_mem: 19416M
[04/19 11:51:42] fastreid.utils.events INFO:  eta: 1:40:44  iter: 11399  total_loss: 13.2  loss_cls_b1: 1.356  loss_cls_b2: 1.222  loss_cls_b21: 1.527  loss_cls_b22: 1.897  loss_cls_b3: 1.186  loss_cls_b31: 1.679  loss_cls_b32: 1.838  loss_cls_b33: 2.265  loss_triplet_b1: 0.1006  loss_triplet_b2: 0.08631  loss_triplet_b3: 0.07549  loss_triplet_b22: 0.1022  loss_triplet_b33: 0.0932  time: 0.2879  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 11:52:46] fastreid.utils.events INFO:  eta: 1:39:40  iter: 11599  total_loss: 10.99  loss_cls_b1: 1.059  loss_cls_b2: 0.9855  loss_cls_b21: 1.208  loss_cls_b22: 1.565  loss_cls_b3: 0.9386  loss_cls_b31: 1.324  loss_cls_b32: 1.531  loss_cls_b33: 2.013  loss_triplet_b1: 0.08066  loss_triplet_b2: 0.06451  loss_triplet_b3: 0.0557  loss_triplet_b22: 0.08117  loss_triplet_b33: 0.07225  time: 0.2884  data_time: 0.0004  lr: 3.50e-04  max_mem: 19416M
[04/19 11:53:49] fastreid.utils.events INFO:  eta: 1:38:36  iter: 11799  total_loss: 12.39  loss_cls_b1: 1.233  loss_cls_b2: 1.078  loss_cls_b21: 1.385  loss_cls_b22: 1.745  loss_cls_b3: 1.044  loss_cls_b31: 1.62  loss_cls_b32: 1.787  loss_cls_b33: 2.011  loss_triplet_b1: 0.1129  loss_triplet_b2: 0.08571  loss_triplet_b3: 0.09387  loss_triplet_b22: 0.1091  loss_triplet_b33: 0.1172  time: 0.2889  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 11:54:53] fastreid.utils.events INFO:  eta: 1:37:33  iter: 11999  total_loss: 10.77  loss_cls_b1: 1.075  loss_cls_b2: 0.9113  loss_cls_b21: 1.235  loss_cls_b22: 1.545  loss_cls_b3: 0.8954  loss_cls_b31: 1.372  loss_cls_b32: 1.437  loss_cls_b33: 1.948  loss_triplet_b1: 0.08253  loss_triplet_b2: 0.05864  loss_triplet_b3: 0.04913  loss_triplet_b22: 0.07018  loss_triplet_b33: 0.08943  time: 0.2893  data_time: 0.0005  lr: 3.50e-04  max_mem: 19416M
[04/19 11:55:56] fastreid.utils.events INFO:  eta: 1:36:31  iter: 12199  total_loss: 13.22  loss_cls_b1: 1.317  loss_cls_b2: 1.183  loss_cls_b21: 1.479  loss_cls_b22: 1.828  loss_cls_b3: 1.121  loss_cls_b31: 1.635  loss_cls_b32: 1.793  loss_cls_b33: 2.226  loss_triplet_b1: 0.1073  loss_triplet_b2: 0.06396  loss_triplet_b3: 0.06982  loss_triplet_b22: 0.08709  loss_triplet_b33: 0.09526  time: 0.2898  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 11:57:00] fastreid.utils.events INFO:  eta: 1:35:31  iter: 12399  total_loss: 12.02  loss_cls_b1: 1.206  loss_cls_b2: 1.08  loss_cls_b21: 1.31  loss_cls_b22: 1.695  loss_cls_b3: 1.029  loss_cls_b31: 1.455  loss_cls_b32: 1.672  loss_cls_b33: 2.056  loss_triplet_b1: 0.1005  loss_triplet_b2: 0.0711  loss_triplet_b3: 0.06775  loss_triplet_b22: 0.07146  loss_triplet_b33: 0.1009  time: 0.2902  data_time: 0.0005  lr: 3.50e-04  max_mem: 19416M
[04/19 11:58:04] fastreid.utils.events INFO:  eta: 1:34:29  iter: 12599  total_loss: 13.76  loss_cls_b1: 1.427  loss_cls_b2: 1.244  loss_cls_b21: 1.607  loss_cls_b22: 1.788  loss_cls_b3: 1.222  loss_cls_b31: 1.817  loss_cls_b32: 1.82  loss_cls_b33: 2.135  loss_triplet_b1: 0.1196  loss_triplet_b2: 0.08378  loss_triplet_b3: 0.0949  loss_triplet_b22: 0.101  loss_triplet_b33: 0.1097  time: 0.2906  data_time: 0.0008  lr: 3.50e-04  max_mem: 19416M
[04/19 11:59:07] fastreid.utils.events INFO:  eta: 1:33:26  iter: 12799  total_loss: 11.6  loss_cls_b1: 1.176  loss_cls_b2: 1.048  loss_cls_b21: 1.402  loss_cls_b22: 1.549  loss_cls_b3: 0.9762  loss_cls_b31: 1.503  loss_cls_b32: 1.643  loss_cls_b33: 1.958  loss_triplet_b1: 0.07961  loss_triplet_b2: 0.05466  loss_triplet_b3: 0.05628  loss_triplet_b22: 0.06758  loss_triplet_b33: 0.06902  time: 0.2910  data_time: 0.0005  lr: 3.50e-04  max_mem: 19416M
[04/19 12:00:11] fastreid.utils.events INFO:  eta: 1:32:22  iter: 12999  total_loss: 12.69  loss_cls_b1: 1.276  loss_cls_b2: 1.107  loss_cls_b21: 1.426  loss_cls_b22: 1.695  loss_cls_b3: 1.154  loss_cls_b31: 1.662  loss_cls_b32: 1.755  loss_cls_b33: 2.081  loss_triplet_b1: 0.0986  loss_triplet_b2: 0.07166  loss_triplet_b3: 0.06907  loss_triplet_b22: 0.08009  loss_triplet_b33: 0.08699  time: 0.2914  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 12:01:14] fastreid.utils.events INFO:  eta: 1:31:19  iter: 13199  total_loss: 12.05  loss_cls_b1: 1.185  loss_cls_b2: 1.099  loss_cls_b21: 1.513  loss_cls_b22: 1.506  loss_cls_b3: 1.067  loss_cls_b31: 1.702  loss_cls_b32: 1.757  loss_cls_b33: 2.013  loss_triplet_b1: 0.08674  loss_triplet_b2: 0.06078  loss_triplet_b3: 0.07357  loss_triplet_b22: 0.07406  loss_triplet_b33: 0.08551  time: 0.2918  data_time: 0.0005  lr: 3.50e-04  max_mem: 19416M
[04/19 12:02:18] fastreid.utils.events INFO:  eta: 1:30:11  iter: 13399  total_loss: 11.97  loss_cls_b1: 1.192  loss_cls_b2: 1.013  loss_cls_b21: 1.388  loss_cls_b22: 1.61  loss_cls_b3: 1.038  loss_cls_b31: 1.58  loss_cls_b32: 1.73  loss_cls_b33: 2.05  loss_triplet_b1: 0.09208  loss_triplet_b2: 0.06356  loss_triplet_b3: 0.06216  loss_triplet_b22: 0.07705  loss_triplet_b33: 0.09076  time: 0.2922  data_time: 0.0008  lr: 3.50e-04  max_mem: 19416M
[04/19 12:03:22] fastreid.utils.events INFO:  eta: 1:29:08  iter: 13599  total_loss: 11.07  loss_cls_b1: 1.126  loss_cls_b2: 0.8965  loss_cls_b21: 1.327  loss_cls_b22: 1.491  loss_cls_b3: 0.9411  loss_cls_b31: 1.502  loss_cls_b32: 1.623  loss_cls_b33: 1.984  loss_triplet_b1: 0.09506  loss_triplet_b2: 0.06639  loss_triplet_b3: 0.06937  loss_triplet_b22: 0.08272  loss_triplet_b33: 0.08212  time: 0.2925  data_time: 0.0006  lr: 3.50e-04  max_mem: 19416M
[04/19 12:04:25] fastreid.utils.events INFO:  eta: 1:28:04  iter: 13799  total_loss: 10.5  loss_cls_b1: 1.053  loss_cls_b2: 0.95  loss_cls_b21: 1.244  loss_cls_b22: 1.433  loss_cls_b3: 0.8859  loss_cls_b31: 1.388  loss_cls_b32: 1.484  loss_cls_b33: 1.834  loss_triplet_b1: 0.08528  loss_triplet_b2: 0.05405  loss_triplet_b3: 0.05635  loss_triplet_b22: 0.06582  loss_triplet_b33: 0.07824  time: 0.2928  data_time: 0.0009  lr: 3.50e-04  max_mem: 19416M
[04/19 12:05:29] fastreid.utils.events INFO:  eta: 1:27:02  iter: 13999  total_loss: 12.53  loss_cls_b1: 1.244  loss_cls_b2: 1.105  loss_cls_b21: 1.477  loss_cls_b22: 1.633  loss_cls_b3: 1.173  loss_cls_b31: 1.735  loss_cls_b32: 1.717  loss_cls_b33: 2.054  loss_triplet_b1: 0.1064  loss_triplet_b2: 0.07519  loss_triplet_b3: 0.06567  loss_triplet_b22: 0.09626  loss_triplet_b33: 0.1039  time: 0.2932  data_time: 0.0006  lr: 3.50e-04  max_mem: 19416M
[04/19 12:06:32] fastreid.utils.events INFO:  eta: 1:26:01  iter: 14199  total_loss: 9.586  loss_cls_b1: 0.9797  loss_cls_b2: 0.7985  loss_cls_b21: 1.198  loss_cls_b22: 1.256  loss_cls_b3: 0.7284  loss_cls_b31: 1.278  loss_cls_b32: 1.288  loss_cls_b33: 1.661  loss_triplet_b1: 0.08685  loss_triplet_b2: 0.05794  loss_triplet_b3: 0.05664  loss_triplet_b22: 0.07609  loss_triplet_b33: 0.07659  time: 0.2935  data_time: 0.0004  lr: 3.50e-04  max_mem: 19416M
[04/19 12:07:36] fastreid.utils.events INFO:  eta: 1:25:00  iter: 14399  total_loss: 11.82  loss_cls_b1: 1.221  loss_cls_b2: 1.073  loss_cls_b21: 1.399  loss_cls_b22: 1.59  loss_cls_b3: 1.052  loss_cls_b31: 1.561  loss_cls_b32: 1.582  loss_cls_b33: 2.065  loss_triplet_b1: 0.1063  loss_triplet_b2: 0.08029  loss_triplet_b3: 0.07298  loss_triplet_b22: 0.0982  loss_triplet_b33: 0.1057  time: 0.2938  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 12:08:40] fastreid.utils.events INFO:  eta: 1:23:57  iter: 14599  total_loss: 10.05  loss_cls_b1: 0.9763  loss_cls_b2: 0.8589  loss_cls_b21: 1.082  loss_cls_b22: 1.363  loss_cls_b3: 0.8451  loss_cls_b31: 1.306  loss_cls_b32: 1.408  loss_cls_b33: 1.686  loss_triplet_b1: 0.08575  loss_triplet_b2: 0.05983  loss_triplet_b3: 0.06278  loss_triplet_b22: 0.07713  loss_triplet_b33: 0.07819  time: 0.2941  data_time: 0.0004  lr: 3.50e-04  max_mem: 19416M
[04/19 12:09:44] fastreid.utils.events INFO:  eta: 1:22:55  iter: 14799  total_loss: 11.37  loss_cls_b1: 1.163  loss_cls_b2: 1.005  loss_cls_b21: 1.325  loss_cls_b22: 1.51  loss_cls_b3: 1.031  loss_cls_b31: 1.52  loss_cls_b32: 1.543  loss_cls_b33: 1.922  loss_triplet_b1: 0.07655  loss_triplet_b2: 0.06517  loss_triplet_b3: 0.062  loss_triplet_b22: 0.07448  loss_triplet_b33: 0.07839  time: 0.2944  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 12:10:47] fastreid.utils.events INFO:  eta: 1:21:52  iter: 14999  total_loss: 10.8  loss_cls_b1: 1.085  loss_cls_b2: 0.9261  loss_cls_b21: 1.272  loss_cls_b22: 1.557  loss_cls_b3: 0.9284  loss_cls_b31: 1.37  loss_cls_b32: 1.572  loss_cls_b33: 1.964  loss_triplet_b1: 0.1083  loss_triplet_b2: 0.06942  loss_triplet_b3: 0.07229  loss_triplet_b22: 0.08707  loss_triplet_b33: 0.08343  time: 0.2947  data_time: 0.0004  lr: 3.50e-04  max_mem: 19416M
[04/19 12:11:51] fastreid.utils.events INFO:  eta: 1:20:46  iter: 15199  total_loss: 11.76  loss_cls_b1: 1.2  loss_cls_b2: 0.9992  loss_cls_b21: 1.465  loss_cls_b22: 1.533  loss_cls_b3: 1.022  loss_cls_b31: 1.606  loss_cls_b32: 1.636  loss_cls_b33: 1.935  loss_triplet_b1: 0.08662  loss_triplet_b2: 0.06211  loss_triplet_b3: 0.0632  loss_triplet_b22: 0.06871  loss_triplet_b33: 0.07082  time: 0.2950  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 12:12:54] fastreid.utils.events INFO:  eta: 1:19:43  iter: 15399  total_loss: 11.68  loss_cls_b1: 1.183  loss_cls_b2: 1.018  loss_cls_b21: 1.287  loss_cls_b22: 1.565  loss_cls_b3: 0.9777  loss_cls_b31: 1.45  loss_cls_b32: 1.534  loss_cls_b33: 1.944  loss_triplet_b1: 0.1096  loss_triplet_b2: 0.07976  loss_triplet_b3: 0.07018  loss_triplet_b22: 0.09328  loss_triplet_b33: 0.1014  time: 0.2953  data_time: 0.0005  lr: 3.50e-04  max_mem: 19416M
[04/19 12:13:58] fastreid.utils.events INFO:  eta: 1:18:39  iter: 15599  total_loss: 11.28  loss_cls_b1: 1.127  loss_cls_b2: 1.006  loss_cls_b21: 1.277  loss_cls_b22: 1.594  loss_cls_b3: 0.9793  loss_cls_b31: 1.337  loss_cls_b32: 1.538  loss_cls_b33: 1.874  loss_triplet_b1: 0.09042  loss_triplet_b2: 0.05759  loss_triplet_b3: 0.06031  loss_triplet_b22: 0.06728  loss_triplet_b33: 0.07348  time: 0.2955  data_time: 0.0007  lr: 3.50e-04  max_mem: 19416M
[04/19 12:15:02] fastreid.utils.events INFO:  eta: 1:17:38  iter: 15799  total_loss: 10.45  loss_cls_b1: 1.124  loss_cls_b2: 0.8936  loss_cls_b21: 1.234  loss_cls_b22: 1.399  loss_cls_b3: 0.8975  loss_cls_b31: 1.358  loss_cls_b32: 1.465  loss_cls_b33: 1.856  loss_triplet_b1: 0.07013  loss_triplet_b2: 0.05056  loss_triplet_b3: 0.04257  loss_triplet_b22: 0.05668  loss_triplet_b33: 0.04908  time: 0.2958  data_time: 0.0005  lr: 3.49e-04  max_mem: 19416M
[04/19 12:16:05] fastreid.utils.events INFO:  eta: 1:16:34  iter: 15999  total_loss: 10.04  loss_cls_b1: 0.9869  loss_cls_b2: 0.8632  loss_cls_b21: 1.123  loss_cls_b22: 1.416  loss_cls_b3: 0.8504  loss_cls_b31: 1.295  loss_cls_b32: 1.418  loss_cls_b33: 1.691  loss_triplet_b1: 0.06834  loss_triplet_b2: 0.05289  loss_triplet_b3: 0.05407  loss_triplet_b22: 0.06547  loss_triplet_b33: 0.05843  time: 0.2961  data_time: 0.0008  lr: 3.48e-04  max_mem: 19416M
[04/19 12:17:09] fastreid.utils.events INFO:  eta: 1:15:31  iter: 16199  total_loss: 11.37  loss_cls_b1: 1.09  loss_cls_b2: 0.926  loss_cls_b21: 1.258  loss_cls_b22: 1.558  loss_cls_b3: 0.9829  loss_cls_b31: 1.359  loss_cls_b32: 1.546  loss_cls_b33: 1.875  loss_triplet_b1: 0.0908  loss_triplet_b2: 0.06097  loss_triplet_b3: 0.05345  loss_triplet_b22: 0.07495  loss_triplet_b33: 0.07356  time: 0.2963  data_time: 0.0006  lr: 3.47e-04  max_mem: 19416M
[04/19 12:18:13] fastreid.utils.events INFO:  eta: 1:14:28  iter: 16399  total_loss: 10.97  loss_cls_b1: 1.063  loss_cls_b2: 0.9381  loss_cls_b21: 1.323  loss_cls_b22: 1.488  loss_cls_b3: 0.9719  loss_cls_b31: 1.514  loss_cls_b32: 1.572  loss_cls_b33: 1.888  loss_triplet_b1: 0.07647  loss_triplet_b2: 0.05668  loss_triplet_b3: 0.04998  loss_triplet_b22: 0.06372  loss_triplet_b33: 0.06607  time: 0.2966  data_time: 0.0008  lr: 3.45e-04  max_mem: 19416M
[04/19 12:19:17] fastreid.utils.events INFO:  eta: 1:13:25  iter: 16599  total_loss: 9.951  loss_cls_b1: 1.023  loss_cls_b2: 0.8765  loss_cls_b21: 1.168  loss_cls_b22: 1.404  loss_cls_b3: 0.8204  loss_cls_b31: 1.28  loss_cls_b32: 1.411  loss_cls_b33: 1.761  loss_triplet_b1: 0.06413  loss_triplet_b2: 0.03598  loss_triplet_b3: 0.04166  loss_triplet_b22: 0.04473  loss_triplet_b33: 0.05544  time: 0.2968  data_time: 0.0006  lr: 3.44e-04  max_mem: 19416M
[04/19 12:20:20] fastreid.utils.events INFO:  eta: 1:12:21  iter: 16799  total_loss: 7.901  loss_cls_b1: 0.7733  loss_cls_b2: 0.6256  loss_cls_b21: 0.926  loss_cls_b22: 1.112  loss_cls_b3: 0.5954  loss_cls_b31: 1.034  loss_cls_b32: 1.11  loss_cls_b33: 1.443  loss_triplet_b1: 0.06398  loss_triplet_b2: 0.04439  loss_triplet_b3: 0.0376  loss_triplet_b22: 0.04936  loss_triplet_b33: 0.05215  time: 0.2970  data_time: 0.0007  lr: 3.41e-04  max_mem: 19416M
[04/19 12:21:24] fastreid.utils.events INFO:  eta: 1:11:22  iter: 16999  total_loss: 10.91  loss_cls_b1: 1.1  loss_cls_b2: 0.915  loss_cls_b21: 1.185  loss_cls_b22: 1.448  loss_cls_b3: 0.9683  loss_cls_b31: 1.409  loss_cls_b32: 1.513  loss_cls_b33: 1.841  loss_triplet_b1: 0.0871  loss_triplet_b2: 0.05862  loss_triplet_b3: 0.05963  loss_triplet_b22: 0.06716  loss_triplet_b33: 0.07276  time: 0.2973  data_time: 0.0006  lr: 3.39e-04  max_mem: 19416M
[04/19 12:22:28] fastreid.utils.events INFO:  eta: 1:10:18  iter: 17199  total_loss: 8.078  loss_cls_b1: 0.8034  loss_cls_b2: 0.6286  loss_cls_b21: 0.9157  loss_cls_b22: 1.165  loss_cls_b3: 0.6297  loss_cls_b31: 1.043  loss_cls_b32: 1.187  loss_cls_b33: 1.435  loss_triplet_b1: 0.08223  loss_triplet_b2: 0.04567  loss_triplet_b3: 0.04853  loss_triplet_b22: 0.06155  loss_triplet_b33: 0.07079  time: 0.2975  data_time: 0.0004  lr: 3.36e-04  max_mem: 19416M
[04/19 12:23:31] fastreid.utils.events INFO:  eta: 1:09:15  iter: 17399  total_loss: 10.7  loss_cls_b1: 1.084  loss_cls_b2: 0.9375  loss_cls_b21: 1.268  loss_cls_b22: 1.443  loss_cls_b3: 0.9331  loss_cls_b31: 1.367  loss_cls_b32: 1.482  loss_cls_b33: 1.797  loss_triplet_b1: 0.07923  loss_triplet_b2: 0.05557  loss_triplet_b3: 0.05376  loss_triplet_b22: 0.06187  loss_triplet_b33: 0.06763  time: 0.2977  data_time: 0.0007  lr: 3.34e-04  max_mem: 19416M
[04/19 12:24:35] fastreid.utils.events INFO:  eta: 1:08:11  iter: 17599  total_loss: 9.516  loss_cls_b1: 0.9482  loss_cls_b2: 0.8032  loss_cls_b21: 1.076  loss_cls_b22: 1.31  loss_cls_b3: 0.7925  loss_cls_b31: 1.289  loss_cls_b32: 1.381  loss_cls_b33: 1.657  loss_triplet_b1: 0.07856  loss_triplet_b2: 0.05849  loss_triplet_b3: 0.05292  loss_triplet_b22: 0.0622  loss_triplet_b33: 0.06602  time: 0.2979  data_time: 0.0005  lr: 3.30e-04  max_mem: 19416M
[04/19 12:25:39] fastreid.utils.events INFO:  eta: 1:07:08  iter: 17799  total_loss: 10.4  loss_cls_b1: 1.01  loss_cls_b2: 0.8444  loss_cls_b21: 1.239  loss_cls_b22: 1.369  loss_cls_b3: 0.8237  loss_cls_b31: 1.339  loss_cls_b32: 1.391  loss_cls_b33: 1.706  loss_triplet_b1: 0.06894  loss_triplet_b2: 0.04855  loss_triplet_b3: 0.0457  loss_triplet_b22: 0.05747  loss_triplet_b33: 0.05675  time: 0.2981  data_time: 0.0007  lr: 3.27e-04  max_mem: 19416M
[04/19 12:26:42] fastreid.utils.events INFO:  eta: 1:06:02  iter: 17999  total_loss: 9.27  loss_cls_b1: 0.934  loss_cls_b2: 0.8158  loss_cls_b21: 1.12  loss_cls_b22: 1.271  loss_cls_b3: 0.8013  loss_cls_b31: 1.203  loss_cls_b32: 1.242  loss_cls_b33: 1.661  loss_triplet_b1: 0.07098  loss_triplet_b2: 0.04172  loss_triplet_b3: 0.04401  loss_triplet_b22: 0.04379  loss_triplet_b33: 0.04688  time: 0.2983  data_time: 0.0005  lr: 3.23e-04  max_mem: 19416M
[04/19 12:27:46] fastreid.utils.events INFO:  eta: 1:04:58  iter: 18199  total_loss: 10.45  loss_cls_b1: 1.139  loss_cls_b2: 0.9598  loss_cls_b21: 1.237  loss_cls_b22: 1.414  loss_cls_b3: 0.9005  loss_cls_b31: 1.306  loss_cls_b32: 1.565  loss_cls_b33: 1.742  loss_triplet_b1: 0.07977  loss_triplet_b2: 0.05238  loss_triplet_b3: 0.0578  loss_triplet_b22: 0.05984  loss_triplet_b33: 0.06784  time: 0.2985  data_time: 0.0007  lr: 3.19e-04  max_mem: 19416M
[04/19 12:28:50] fastreid.utils.events INFO:  eta: 1:03:55  iter: 18399  total_loss: 9.385  loss_cls_b1: 0.9631  loss_cls_b2: 0.7899  loss_cls_b21: 1.105  loss_cls_b22: 1.356  loss_cls_b3: 0.8021  loss_cls_b31: 1.15  loss_cls_b32: 1.351  loss_cls_b33: 1.768  loss_triplet_b1: 0.06191  loss_triplet_b2: 0.04667  loss_triplet_b3: 0.04467  loss_triplet_b22: 0.05732  loss_triplet_b33: 0.0572  time: 0.2987  data_time: 0.0005  lr: 3.15e-04  max_mem: 19416M
[04/19 12:29:54] fastreid.utils.events INFO:  eta: 1:02:53  iter: 18599  total_loss: 9.959  loss_cls_b1: 1.059  loss_cls_b2: 0.8687  loss_cls_b21: 1.156  loss_cls_b22: 1.362  loss_cls_b3: 0.8584  loss_cls_b31: 1.263  loss_cls_b32: 1.466  loss_cls_b33: 1.661  loss_triplet_b1: 0.08824  loss_triplet_b2: 0.05985  loss_triplet_b3: 0.05165  loss_triplet_b22: 0.06683  loss_triplet_b33: 0.06717  time: 0.2989  data_time: 0.0008  lr: 3.11e-04  max_mem: 19416M
[04/19 12:30:57] fastreid.utils.events INFO:  eta: 1:01:52  iter: 18799  total_loss: 9.854  loss_cls_b1: 0.9717  loss_cls_b2: 0.8534  loss_cls_b21: 1.18  loss_cls_b22: 1.306  loss_cls_b3: 0.7959  loss_cls_b31: 1.3  loss_cls_b32: 1.321  loss_cls_b33: 1.68  loss_triplet_b1: 0.06399  loss_triplet_b2: 0.04641  loss_triplet_b3: 0.04636  loss_triplet_b22: 0.05424  loss_triplet_b33: 0.05459  time: 0.2991  data_time: 0.0006  lr: 3.06e-04  max_mem: 19416M
[04/19 12:32:01] fastreid.utils.events INFO:  eta: 1:00:48  iter: 18999  total_loss: 9.353  loss_cls_b1: 0.9181  loss_cls_b2: 0.7773  loss_cls_b21: 1.117  loss_cls_b22: 1.246  loss_cls_b3: 0.782  loss_cls_b31: 1.281  loss_cls_b32: 1.403  loss_cls_b33: 1.498  loss_triplet_b1: 0.06994  loss_triplet_b2: 0.05159  loss_triplet_b3: 0.05297  loss_triplet_b22: 0.05277  loss_triplet_b33: 0.06227  time: 0.2993  data_time: 0.0008  lr: 3.01e-04  max_mem: 19416M
[04/19 12:33:05] fastreid.utils.events INFO:  eta: 0:59:46  iter: 19199  total_loss: 9.452  loss_cls_b1: 0.9524  loss_cls_b2: 0.7787  loss_cls_b21: 1.111  loss_cls_b22: 1.331  loss_cls_b3: 0.8487  loss_cls_b31: 1.27  loss_cls_b32: 1.256  loss_cls_b33: 1.786  loss_triplet_b1: 0.07065  loss_triplet_b2: 0.05175  loss_triplet_b3: 0.0452  loss_triplet_b22: 0.05032  loss_triplet_b33: 0.04685  time: 0.2995  data_time: 0.0006  lr: 2.96e-04  max_mem: 19416M
[04/19 12:34:09] fastreid.utils.events INFO:  eta: 0:58:44  iter: 19399  total_loss: 6.153  loss_cls_b1: 0.5736  loss_cls_b2: 0.4633  loss_cls_b21: 0.7032  loss_cls_b22: 0.8852  loss_cls_b3: 0.4778  loss_cls_b31: 0.8326  loss_cls_b32: 0.8574  loss_cls_b33: 1.13  loss_triplet_b1: 0.04996  loss_triplet_b2: 0.0336  loss_triplet_b3: 0.0314  loss_triplet_b22: 0.04047  loss_triplet_b33: 0.03354  time: 0.2996  data_time: 0.0009  lr: 2.91e-04  max_mem: 19416M
[04/19 12:35:12] fastreid.utils.events INFO:  eta: 0:57:39  iter: 19599  total_loss: 9.408  loss_cls_b1: 0.9062  loss_cls_b2: 0.7491  loss_cls_b21: 1.064  loss_cls_b22: 1.261  loss_cls_b3: 0.7521  loss_cls_b31: 1.191  loss_cls_b32: 1.35  loss_cls_b33: 1.506  loss_triplet_b1: 0.06921  loss_triplet_b2: 0.0525  loss_triplet_b3: 0.04755  loss_triplet_b22: 0.06073  loss_triplet_b33: 0.05867  time: 0.2998  data_time: 0.0006  lr: 2.85e-04  max_mem: 19416M
[04/19 12:36:16] fastreid.utils.events INFO:  eta: 0:56:34  iter: 19799  total_loss: 6.156  loss_cls_b1: 0.612  loss_cls_b2: 0.4806  loss_cls_b21: 0.6844  loss_cls_b22: 0.8309  loss_cls_b3: 0.496  loss_cls_b31: 0.7778  loss_cls_b32: 0.8671  loss_cls_b33: 1.176  loss_triplet_b1: 0.04357  loss_triplet_b2: 0.02789  loss_triplet_b3: 0.02353  loss_triplet_b22: 0.0294  loss_triplet_b33: 0.02585  time: 0.3000  data_time: 0.0004  lr: 2.80e-04  max_mem: 19416M
[04/19 12:37:19] fastreid.utils.events INFO:  eta: 0:55:31  iter: 19999  total_loss: 9.072  loss_cls_b1: 0.8809  loss_cls_b2: 0.7199  loss_cls_b21: 1.029  loss_cls_b22: 1.206  loss_cls_b3: 0.6924  loss_cls_b31: 1.238  loss_cls_b32: 1.277  loss_cls_b33: 1.577  loss_triplet_b1: 0.07012  loss_triplet_b2: 0.04859  loss_triplet_b3: 0.04304  loss_triplet_b22: 0.06432  loss_triplet_b33: 0.06478  time: 0.3001  data_time: 0.0007  lr: 2.74e-04  max_mem: 19416M
[04/19 12:38:24] fastreid.utils.events INFO:  eta: 0:54:27  iter: 20199  total_loss: 7.773  loss_cls_b1: 0.768  loss_cls_b2: 0.6121  loss_cls_b21: 0.889  loss_cls_b22: 1.231  loss_cls_b3: 0.5716  loss_cls_b31: 0.965  loss_cls_b32: 1.116  loss_cls_b33: 1.444  loss_triplet_b1: 0.05443  loss_triplet_b2: 0.03613  loss_triplet_b3: 0.03268  loss_triplet_b22: 0.04595  loss_triplet_b33: 0.03816  time: 0.3003  data_time: 0.0005  lr: 2.68e-04  max_mem: 19416M
[04/19 12:39:34] fastreid.utils.events INFO:  eta: 0:53:27  iter: 20399  total_loss: 8.632  loss_cls_b1: 0.8489  loss_cls_b2: 0.6845  loss_cls_b21: 1.01  loss_cls_b22: 1.176  loss_cls_b3: 0.681  loss_cls_b31: 1.116  loss_cls_b32: 1.235  loss_cls_b33: 1.522  loss_triplet_b1: 0.06568  loss_triplet_b2: 0.04417  loss_triplet_b3: 0.04158  loss_triplet_b22: 0.05014  loss_triplet_b33: 0.03943  time: 0.3008  data_time: 0.0008  lr: 2.61e-04  max_mem: 19416M
[04/19 12:40:42] fastreid.utils.events INFO:  eta: 0:52:27  iter: 20599  total_loss: 8.288  loss_cls_b1: 0.8198  loss_cls_b2: 0.6112  loss_cls_b21: 0.8402  loss_cls_b22: 1.015  loss_cls_b3: 0.6093  loss_cls_b31: 0.9832  loss_cls_b32: 1.112  loss_cls_b33: 1.335  loss_triplet_b1: 0.05593  loss_triplet_b2: 0.04298  loss_triplet_b3: 0.04326  loss_triplet_b22: 0.05411  loss_triplet_b33: 0.0648  time: 0.3011  data_time: 0.0005  lr: 2.55e-04  max_mem: 19416M
[04/19 12:42:03] fastreid.utils.events INFO:  eta: 0:51:35  iter: 20799  total_loss: 8.057  loss_cls_b1: 0.7065  loss_cls_b2: 0.5745  loss_cls_b21: 0.8995  loss_cls_b22: 1.019  loss_cls_b3: 0.5673  loss_cls_b31: 1.105  loss_cls_b32: 1.08  loss_cls_b33: 1.357  loss_triplet_b1: 0.04694  loss_triplet_b2: 0.02601  loss_triplet_b3: 0.03296  loss_triplet_b22: 0.03489  loss_triplet_b33: 0.03941  time: 0.3021  data_time: 0.0007  lr: 2.49e-04  max_mem: 19416M
[04/19 12:43:09] fastreid.utils.events INFO:  eta: 0:50:39  iter: 20999  total_loss: 7.812  loss_cls_b1: 0.7329  loss_cls_b2: 0.5967  loss_cls_b21: 0.8182  loss_cls_b22: 1.125  loss_cls_b3: 0.5749  loss_cls_b31: 0.9469  loss_cls_b32: 1.133  loss_cls_b33: 1.376  loss_triplet_b1: 0.05473  loss_triplet_b2: 0.03905  loss_triplet_b3: 0.03429  loss_triplet_b22: 0.04365  loss_triplet_b33: 0.04387  time: 0.3024  data_time: 0.0005  lr: 2.42e-04  max_mem: 19416M
[04/19 12:44:13] fastreid.utils.events INFO:  eta: 0:49:32  iter: 21199  total_loss: 7.497  loss_cls_b1: 0.7439  loss_cls_b2: 0.6174  loss_cls_b21: 0.8879  loss_cls_b22: 1.008  loss_cls_b3: 0.6435  loss_cls_b31: 0.9651  loss_cls_b32: 1.123  loss_cls_b33: 1.355  loss_triplet_b1: 0.04585  loss_triplet_b2: 0.03295  loss_triplet_b3: 0.03277  loss_triplet_b22: 0.0354  loss_triplet_b33: 0.03647  time: 0.3025  data_time: 0.0007  lr: 2.35e-04  max_mem: 19416M
[04/19 12:45:17] fastreid.utils.events INFO:  eta: 0:48:21  iter: 21399  total_loss: 8.138  loss_cls_b1: 0.7725  loss_cls_b2: 0.6042  loss_cls_b21: 0.8456  loss_cls_b22: 1.16  loss_cls_b3: 0.6445  loss_cls_b31: 0.9767  loss_cls_b32: 1.146  loss_cls_b33: 1.447  loss_triplet_b1: 0.05052  loss_triplet_b2: 0.03469  loss_triplet_b3: 0.03786  loss_triplet_b22: 0.03289  loss_triplet_b33: 0.04016  time: 0.3026  data_time: 0.0005  lr: 2.29e-04  max_mem: 19416M
[04/19 12:46:20] fastreid.utils.events INFO:  eta: 0:47:15  iter: 21599  total_loss: 7.357  loss_cls_b1: 0.7031  loss_cls_b2: 0.5982  loss_cls_b21: 0.8525  loss_cls_b22: 1.05  loss_cls_b3: 0.5732  loss_cls_b31: 0.9705  loss_cls_b32: 1.117  loss_cls_b33: 1.41  loss_triplet_b1: 0.04841  loss_triplet_b2: 0.02934  loss_triplet_b3: 0.02765  loss_triplet_b22: 0.03451  loss_triplet_b33: 0.03186  time: 0.3027  data_time: 0.0008  lr: 2.22e-04  max_mem: 19416M
[04/19 12:47:24] fastreid.utils.events INFO:  eta: 0:46:04  iter: 21799  total_loss: 7.018  loss_cls_b1: 0.6958  loss_cls_b2: 0.5383  loss_cls_b21: 0.7854  loss_cls_b22: 1.078  loss_cls_b3: 0.5401  loss_cls_b31: 0.9846  loss_cls_b32: 0.9822  loss_cls_b33: 1.362  loss_triplet_b1: 0.05062  loss_triplet_b2: 0.02911  loss_triplet_b3: 0.03602  loss_triplet_b22: 0.03284  loss_triplet_b33: 0.03425  time: 0.3029  data_time: 0.0006  lr: 2.15e-04  max_mem: 19416M
[04/19 12:48:28] fastreid.utils.events INFO:  eta: 0:44:59  iter: 21999  total_loss: 6.982  loss_cls_b1: 0.6854  loss_cls_b2: 0.5718  loss_cls_b21: 0.7909  loss_cls_b22: 1.046  loss_cls_b3: 0.5477  loss_cls_b31: 0.9055  loss_cls_b32: 0.9769  loss_cls_b33: 1.261  loss_triplet_b1: 0.04743  loss_triplet_b2: 0.02852  loss_triplet_b3: 0.03107  loss_triplet_b22: 0.04149  loss_triplet_b33: 0.03704  time: 0.3030  data_time: 0.0008  lr: 2.08e-04  max_mem: 19416M
[04/19 12:49:31] fastreid.utils.events INFO:  eta: 0:43:55  iter: 22199  total_loss: 7.502  loss_cls_b1: 0.7782  loss_cls_b2: 0.5785  loss_cls_b21: 0.8028  loss_cls_b22: 1.041  loss_cls_b3: 0.6079  loss_cls_b31: 0.9441  loss_cls_b32: 1.102  loss_cls_b33: 1.367  loss_triplet_b1: 0.05059  loss_triplet_b2: 0.03205  loss_triplet_b3: 0.03055  loss_triplet_b22: 0.03474  loss_triplet_b33: 0.03707  time: 0.3031  data_time: 0.0006  lr: 2.01e-04  max_mem: 19416M
[04/19 12:50:35] fastreid.utils.events INFO:  eta: 0:42:52  iter: 22399  total_loss: 5.41  loss_cls_b1: 0.5179  loss_cls_b2: 0.4101  loss_cls_b21: 0.6169  loss_cls_b22: 0.7487  loss_cls_b3: 0.3929  loss_cls_b31: 0.7097  loss_cls_b32: 0.7419  loss_cls_b33: 1.052  loss_triplet_b1: 0.03514  loss_triplet_b2: 0.02123  loss_triplet_b3: 0.01902  loss_triplet_b22: 0.02328  loss_triplet_b33: 0.02249  time: 0.3032  data_time: 0.0005  lr: 1.94e-04  max_mem: 19416M
[04/19 12:51:39] fastreid.utils.events INFO:  eta: 0:41:50  iter: 22599  total_loss: 6.613  loss_cls_b1: 0.6608  loss_cls_b2: 0.5361  loss_cls_b21: 0.7995  loss_cls_b22: 0.8659  loss_cls_b3: 0.5434  loss_cls_b31: 0.902  loss_cls_b32: 0.984  loss_cls_b33: 1.166  loss_triplet_b1: 0.0406  loss_triplet_b2: 0.02669  loss_triplet_b3: 0.02658  loss_triplet_b22: 0.03058  loss_triplet_b33: 0.02941  time: 0.3033  data_time: 0.0007  lr: 1.86e-04  max_mem: 19416M
[04/19 12:52:43] fastreid.utils.events INFO:  eta: 0:40:47  iter: 22799  total_loss: 6.37  loss_cls_b1: 0.6108  loss_cls_b2: 0.495  loss_cls_b21: 0.7273  loss_cls_b22: 0.8716  loss_cls_b3: 0.4858  loss_cls_b31: 0.8312  loss_cls_b32: 0.9589  loss_cls_b33: 1.159  loss_triplet_b1: 0.04177  loss_triplet_b2: 0.02473  loss_triplet_b3: 0.02764  loss_triplet_b22: 0.02691  loss_triplet_b33: 0.02387  time: 0.3035  data_time: 0.0004  lr: 1.79e-04  max_mem: 19416M
[04/19 12:53:46] fastreid.utils.events INFO:  eta: 0:39:44  iter: 22999  total_loss: 6.165  loss_cls_b1: 0.5928  loss_cls_b2: 0.4769  loss_cls_b21: 0.7394  loss_cls_b22: 0.8431  loss_cls_b3: 0.4718  loss_cls_b31: 0.9003  loss_cls_b32: 0.9064  loss_cls_b33: 1.178  loss_triplet_b1: 0.03665  loss_triplet_b2: 0.03025  loss_triplet_b3: 0.02434  loss_triplet_b22: 0.0256  loss_triplet_b33: 0.02562  time: 0.3036  data_time: 0.0007  lr: 1.72e-04  max_mem: 19416M
[04/19 12:54:50] fastreid.utils.events INFO:  eta: 0:38:41  iter: 23199  total_loss: 6.249  loss_cls_b1: 0.5807  loss_cls_b2: 0.4523  loss_cls_b21: 0.7334  loss_cls_b22: 0.8581  loss_cls_b3: 0.4724  loss_cls_b31: 0.8768  loss_cls_b32: 0.93  loss_cls_b33: 1.245  loss_triplet_b1: 0.04575  loss_triplet_b2: 0.02817  loss_triplet_b3: 0.03018  loss_triplet_b22: 0.03501  loss_triplet_b33: 0.03255  time: 0.3037  data_time: 0.0005  lr: 1.65e-04  max_mem: 19416M
[04/19 12:55:54] fastreid.utils.events INFO:  eta: 0:37:37  iter: 23399  total_loss: 6.63  loss_cls_b1: 0.6641  loss_cls_b2: 0.474  loss_cls_b21: 0.6667  loss_cls_b22: 0.8634  loss_cls_b3: 0.4826  loss_cls_b31: 0.8395  loss_cls_b32: 1.02  loss_cls_b33: 1.149  loss_triplet_b1: 0.03895  loss_triplet_b2: 0.02338  loss_triplet_b3: 0.02307  loss_triplet_b22: 0.0248  loss_triplet_b33: 0.02384  time: 0.3038  data_time: 0.0007  lr: 1.58e-04  max_mem: 19416M
[04/19 12:56:57] fastreid.utils.events INFO:  eta: 0:36:33  iter: 23599  total_loss: 6.016  loss_cls_b1: 0.6061  loss_cls_b2: 0.4782  loss_cls_b21: 0.6923  loss_cls_b22: 0.8639  loss_cls_b3: 0.4459  loss_cls_b31: 0.7699  loss_cls_b32: 0.893  loss_cls_b33: 1.195  loss_triplet_b1: 0.03379  loss_triplet_b2: 0.02108  loss_triplet_b3: 0.02191  loss_triplet_b22: 0.02127  loss_triplet_b33: 0.01852  time: 0.3039  data_time: 0.0005  lr: 1.51e-04  max_mem: 19416M
[04/19 12:58:01] fastreid.utils.events INFO:  eta: 0:35:30  iter: 23799  total_loss: 6.339  loss_cls_b1: 0.6178  loss_cls_b2: 0.4618  loss_cls_b21: 0.6852  loss_cls_b22: 0.9369  loss_cls_b3: 0.4563  loss_cls_b31: 0.7458  loss_cls_b32: 0.9461  loss_cls_b33: 1.204  loss_triplet_b1: 0.03079  loss_triplet_b2: 0.01998  loss_triplet_b3: 0.02533  loss_triplet_b22: 0.01971  loss_triplet_b33: 0.02097  time: 0.3040  data_time: 0.0007  lr: 1.43e-04  max_mem: 19416M
[04/19 12:59:05] fastreid.utils.events INFO:  eta: 0:34:26  iter: 23999  total_loss: 5.799  loss_cls_b1: 0.5826  loss_cls_b2: 0.4302  loss_cls_b21: 0.6725  loss_cls_b22: 0.7898  loss_cls_b3: 0.4186  loss_cls_b31: 0.7412  loss_cls_b32: 0.8505  loss_cls_b33: 1.044  loss_triplet_b1: 0.03382  loss_triplet_b2: 0.02373  loss_triplet_b3: 0.0215  loss_triplet_b22: 0.02237  loss_triplet_b33: 0.0218  time: 0.3041  data_time: 0.0005  lr: 1.36e-04  max_mem: 19416M
[04/19 13:00:08] fastreid.utils.events INFO:  eta: 0:33:23  iter: 24199  total_loss: 5.673  loss_cls_b1: 0.5839  loss_cls_b2: 0.436  loss_cls_b21: 0.6336  loss_cls_b22: 0.7841  loss_cls_b3: 0.437  loss_cls_b31: 0.7995  loss_cls_b32: 0.825  loss_cls_b33: 1.063  loss_triplet_b1: 0.04747  loss_triplet_b2: 0.02654  loss_triplet_b3: 0.03054  loss_triplet_b22: 0.02321  loss_triplet_b33: 0.02556  time: 0.3042  data_time: 0.0008  lr: 1.29e-04  max_mem: 19416M
[04/19 13:01:12] fastreid.utils.events INFO:  eta: 0:32:19  iter: 24399  total_loss: 5.55  loss_cls_b1: 0.5664  loss_cls_b2: 0.4172  loss_cls_b21: 0.6316  loss_cls_b22: 0.7789  loss_cls_b3: 0.4263  loss_cls_b31: 0.7551  loss_cls_b32: 0.8239  loss_cls_b33: 1.165  loss_triplet_b1: 0.03416  loss_triplet_b2: 0.02037  loss_triplet_b3: 0.01847  loss_triplet_b22: 0.02108  loss_triplet_b33: 0.01856  time: 0.3043  data_time: 0.0006  lr: 1.23e-04  max_mem: 19416M
[04/19 13:02:16] fastreid.utils.events INFO:  eta: 0:31:16  iter: 24599  total_loss: 5.326  loss_cls_b1: 0.4902  loss_cls_b2: 0.3912  loss_cls_b21: 0.6163  loss_cls_b22: 0.7211  loss_cls_b3: 0.373  loss_cls_b31: 0.7413  loss_cls_b32: 0.8024  loss_cls_b33: 1.005  loss_triplet_b1: 0.02461  loss_triplet_b2: 0.01781  loss_triplet_b3: 0.01871  loss_triplet_b22: 0.01723  loss_triplet_b33: 0.01753  time: 0.3044  data_time: 0.0008  lr: 1.16e-04  max_mem: 19416M
[04/19 13:03:19] fastreid.utils.events INFO:  eta: 0:30:12  iter: 24799  total_loss: 5.103  loss_cls_b1: 0.5175  loss_cls_b2: 0.398  loss_cls_b21: 0.5805  loss_cls_b22: 0.7602  loss_cls_b3: 0.3939  loss_cls_b31: 0.6164  loss_cls_b32: 0.7405  loss_cls_b33: 0.9643  loss_triplet_b1: 0.02843  loss_triplet_b2: 0.01857  loss_triplet_b3: 0.01773  loss_triplet_b22: 0.01758  loss_triplet_b33: 0.01502  time: 0.3045  data_time: 0.0006  lr: 1.09e-04  max_mem: 19416M
[04/19 13:04:23] fastreid.utils.events INFO:  eta: 0:29:09  iter: 24999  total_loss: 3.394  loss_cls_b1: 0.3269  loss_cls_b2: 0.2392  loss_cls_b21: 0.3777  loss_cls_b22: 0.49  loss_cls_b3: 0.233  loss_cls_b31: 0.4625  loss_cls_b32: 0.4601  loss_cls_b33: 0.6735  loss_triplet_b1: 0.02422  loss_triplet_b2: 0.01181  loss_triplet_b3: 0.01374  loss_triplet_b22: 0.01473  loss_triplet_b33: 0.01496  time: 0.3046  data_time: 0.0008  lr: 1.02e-04  max_mem: 19416M
[04/19 13:05:27] fastreid.utils.events INFO:  eta: 0:28:06  iter: 25199  total_loss: 5.46  loss_cls_b1: 0.5294  loss_cls_b2: 0.3601  loss_cls_b21: 0.6125  loss_cls_b22: 0.8217  loss_cls_b3: 0.3799  loss_cls_b31: 0.7637  loss_cls_b32: 0.7903  loss_cls_b33: 1.132  loss_triplet_b1: 0.03301  loss_triplet_b2: 0.02217  loss_triplet_b3: 0.02122  loss_triplet_b22: 0.02088  loss_triplet_b33: 0.01747  time: 0.3047  data_time: 0.0006  lr: 9.60e-05  max_mem: 19416M
[04/19 13:06:30] fastreid.utils.events INFO:  eta: 0:27:02  iter: 25399  total_loss: 4.487  loss_cls_b1: 0.4452  loss_cls_b2: 0.3165  loss_cls_b21: 0.495  loss_cls_b22: 0.5773  loss_cls_b3: 0.3109  loss_cls_b31: 0.6307  loss_cls_b32: 0.6445  loss_cls_b33: 0.8423  loss_triplet_b1: 0.02792  loss_triplet_b2: 0.01286  loss_triplet_b3: 0.01248  loss_triplet_b22: 0.01582  loss_triplet_b33: 0.01184  time: 0.3048  data_time: 0.0004  lr: 8.97e-05  max_mem: 19416M
[04/19 13:07:34] fastreid.utils.events INFO:  eta: 0:25:59  iter: 25599  total_loss: 5.455  loss_cls_b1: 0.5197  loss_cls_b2: 0.4109  loss_cls_b21: 0.6286  loss_cls_b22: 0.844  loss_cls_b3: 0.3942  loss_cls_b31: 0.6813  loss_cls_b32: 0.8488  loss_cls_b33: 1.039  loss_triplet_b1: 0.03266  loss_triplet_b2: 0.01994  loss_triplet_b3: 0.01905  loss_triplet_b22: 0.01847  loss_triplet_b33: 0.01755  time: 0.3049  data_time: 0.0007  lr: 8.35e-05  max_mem: 19416M
[04/19 13:08:37] fastreid.utils.events INFO:  eta: 0:24:55  iter: 25799  total_loss: 5.221  loss_cls_b1: 0.4775  loss_cls_b2: 0.3744  loss_cls_b21: 0.6111  loss_cls_b22: 0.6874  loss_cls_b3: 0.3867  loss_cls_b31: 0.6275  loss_cls_b32: 0.7882  loss_cls_b33: 0.9612  loss_triplet_b1: 0.03065  loss_triplet_b2: 0.01782  loss_triplet_b3: 0.01899  loss_triplet_b22: 0.02042  loss_triplet_b33: 0.0165  time: 0.3049  data_time: 0.0004  lr: 7.75e-05  max_mem: 19416M
[04/19 13:09:41] fastreid.utils.events INFO:  eta: 0:23:52  iter: 25999  total_loss: 5.034  loss_cls_b1: 0.4781  loss_cls_b2: 0.3578  loss_cls_b21: 0.5249  loss_cls_b22: 0.7905  loss_cls_b3: 0.3311  loss_cls_b31: 0.6132  loss_cls_b32: 0.7654  loss_cls_b33: 1.046  loss_triplet_b1: 0.02772  loss_triplet_b2: 0.01839  loss_triplet_b3: 0.01992  loss_triplet_b22: 0.02267  loss_triplet_b33: 0.02241  time: 0.3050  data_time: 0.0006  lr: 7.16e-05  max_mem: 19416M
[04/19 13:10:44] fastreid.utils.events INFO:  eta: 0:22:49  iter: 26199  total_loss: 4.44  loss_cls_b1: 0.4745  loss_cls_b2: 0.3252  loss_cls_b21: 0.5328  loss_cls_b22: 0.6091  loss_cls_b3: 0.3206  loss_cls_b31: 0.6205  loss_cls_b32: 0.6597  loss_cls_b33: 0.839  loss_triplet_b1: 0.0324  loss_triplet_b2: 0.01902  loss_triplet_b3: 0.01984  loss_triplet_b22: 0.02202  loss_triplet_b33: 0.01753  time: 0.3051  data_time: 0.0005  lr: 6.59e-05  max_mem: 19416M
[04/19 13:11:48] fastreid.utils.events INFO:  eta: 0:21:46  iter: 26399  total_loss: 5.004  loss_cls_b1: 0.4888  loss_cls_b2: 0.3502  loss_cls_b21: 0.5775  loss_cls_b22: 0.6882  loss_cls_b3: 0.3624  loss_cls_b31: 0.653  loss_cls_b32: 0.8182  loss_cls_b33: 0.9695  loss_triplet_b1: 0.03109  loss_triplet_b2: 0.01714  loss_triplet_b3: 0.01462  loss_triplet_b22: 0.01867  loss_triplet_b33: 0.01666  time: 0.3052  data_time: 0.0007  lr: 6.04e-05  max_mem: 19416M
[04/19 13:12:51] fastreid.utils.events INFO:  eta: 0:20:43  iter: 26599  total_loss: 4.489  loss_cls_b1: 0.4205  loss_cls_b2: 0.3083  loss_cls_b21: 0.4718  loss_cls_b22: 0.7364  loss_cls_b3: 0.3292  loss_cls_b31: 0.6138  loss_cls_b32: 0.7126  loss_cls_b33: 0.9404  loss_triplet_b1: 0.02477  loss_triplet_b2: 0.01178  loss_triplet_b3: 0.01314  loss_triplet_b22: 0.01456  loss_triplet_b33: 0.01281  time: 0.3053  data_time: 0.0005  lr: 5.51e-05  max_mem: 19416M
[04/19 13:13:55] fastreid.utils.events INFO:  eta: 0:19:40  iter: 26799  total_loss: 5.102  loss_cls_b1: 0.4822  loss_cls_b2: 0.4149  loss_cls_b21: 0.6235  loss_cls_b22: 0.6871  loss_cls_b3: 0.3861  loss_cls_b31: 0.7176  loss_cls_b32: 0.7045  loss_cls_b33: 0.9725  loss_triplet_b1: 0.02732  loss_triplet_b2: 0.01652  loss_triplet_b3: 0.01795  loss_triplet_b22: 0.01753  loss_triplet_b33: 0.01525  time: 0.3053  data_time: 0.0008  lr: 5.00e-05  max_mem: 19416M
[04/19 13:14:59] fastreid.utils.events INFO:  eta: 0:18:37  iter: 26999  total_loss: 4.943  loss_cls_b1: 0.4736  loss_cls_b2: 0.3562  loss_cls_b21: 0.529  loss_cls_b22: 0.6856  loss_cls_b3: 0.368  loss_cls_b31: 0.6408  loss_cls_b32: 0.7153  loss_cls_b33: 0.8682  loss_triplet_b1: 0.02349  loss_triplet_b2: 0.01613  loss_triplet_b3: 0.01785  loss_triplet_b22: 0.01589  loss_triplet_b33: 0.0126  time: 0.3054  data_time: 0.0005  lr: 4.51e-05  max_mem: 19416M
[04/19 13:16:02] fastreid.utils.events INFO:  eta: 0:17:34  iter: 27199  total_loss: 4.636  loss_cls_b1: 0.4301  loss_cls_b2: 0.332  loss_cls_b21: 0.5051  loss_cls_b22: 0.6631  loss_cls_b3: 0.3288  loss_cls_b31: 0.6031  loss_cls_b32: 0.7196  loss_cls_b33: 0.9215  loss_triplet_b1: 0.02582  loss_triplet_b2: 0.01592  loss_triplet_b3: 0.01769  loss_triplet_b22: 0.01411  loss_triplet_b33: 0.01547  time: 0.3055  data_time: 0.0008  lr: 4.04e-05  max_mem: 19416M
[04/19 13:17:06] fastreid.utils.events INFO:  eta: 0:16:31  iter: 27399  total_loss: 4.41  loss_cls_b1: 0.3928  loss_cls_b2: 0.3187  loss_cls_b21: 0.4718  loss_cls_b22: 0.655  loss_cls_b3: 0.3296  loss_cls_b31: 0.5097  loss_cls_b32: 0.694  loss_cls_b33: 0.9377  loss_triplet_b1: 0.02159  loss_triplet_b2: 0.01505  loss_triplet_b3: 0.01454  loss_triplet_b22: 0.01451  loss_triplet_b33: 0.01314  time: 0.3056  data_time: 0.0006  lr: 3.60e-05  max_mem: 19416M
[04/19 13:18:09] fastreid.utils.events INFO:  eta: 0:15:27  iter: 27599  total_loss: 3.902  loss_cls_b1: 0.3456  loss_cls_b2: 0.265  loss_cls_b21: 0.4905  loss_cls_b22: 0.5163  loss_cls_b3: 0.2886  loss_cls_b31: 0.5834  loss_cls_b32: 0.5819  loss_cls_b33: 0.6607  loss_triplet_b1: 0.02234  loss_triplet_b2: 0.0116  loss_triplet_b3: 0.01445  loss_triplet_b22: 0.01261  loss_triplet_b33: 0.01191  time: 0.3056  data_time: 0.0009  lr: 3.18e-05  max_mem: 19416M
[04/19 13:19:13] fastreid.utils.events INFO:  eta: 0:14:24  iter: 27799  total_loss: 4.187  loss_cls_b1: 0.3998  loss_cls_b2: 0.2878  loss_cls_b21: 0.4816  loss_cls_b22: 0.5728  loss_cls_b3: 0.3079  loss_cls_b31: 0.5442  loss_cls_b32: 0.6039  loss_cls_b33: 0.783  loss_triplet_b1: 0.02008  loss_triplet_b2: 0.01208  loss_triplet_b3: 0.01264  loss_triplet_b22: 0.01243  loss_triplet_b33: 0.009972  time: 0.3057  data_time: 0.0006  lr: 2.78e-05  max_mem: 19416M
[04/19 13:20:16] fastreid.utils.events INFO:  eta: 0:13:21  iter: 27999  total_loss: 3.254  loss_cls_b1: 0.2878  loss_cls_b2: 0.2281  loss_cls_b21: 0.352  loss_cls_b22: 0.428  loss_cls_b3: 0.2345  loss_cls_b31: 0.4192  loss_cls_b32: 0.5083  loss_cls_b33: 0.5885  loss_triplet_b1: 0.01611  loss_triplet_b2: 0.00857  loss_triplet_b3: 0.01008  loss_triplet_b22: 0.007886  loss_triplet_b33: 0.007376  time: 0.3058  data_time: 0.0004  lr: 2.41e-05  max_mem: 19416M
[04/19 13:21:20] fastreid.utils.events INFO:  eta: 0:12:18  iter: 28199  total_loss: 3.973  loss_cls_b1: 0.369  loss_cls_b2: 0.3149  loss_cls_b21: 0.4902  loss_cls_b22: 0.5255  loss_cls_b3: 0.3174  loss_cls_b31: 0.6181  loss_cls_b32: 0.6401  loss_cls_b33: 0.754  loss_triplet_b1: 0.0208  loss_triplet_b2: 0.01655  loss_triplet_b3: 0.01485  loss_triplet_b22: 0.01555  loss_triplet_b33: 0.01067  time: 0.3059  data_time: 0.0007  lr: 2.06e-05  max_mem: 19416M
[04/19 13:22:24] fastreid.utils.events INFO:  eta: 0:11:15  iter: 28399  total_loss: 3.3  loss_cls_b1: 0.2893  loss_cls_b2: 0.2401  loss_cls_b21: 0.3815  loss_cls_b22: 0.4459  loss_cls_b3: 0.2511  loss_cls_b31: 0.4409  loss_cls_b32: 0.4779  loss_cls_b33: 0.6387  loss_triplet_b1: 0.01592  loss_triplet_b2: 0.01051  loss_triplet_b3: 0.009062  loss_triplet_b22: 0.009775  loss_triplet_b33: 0.007363  time: 0.3059  data_time: 0.0004  lr: 1.74e-05  max_mem: 19416M
[04/19 13:23:27] fastreid.utils.events INFO:  eta: 0:10:12  iter: 28599  total_loss: 4.134  loss_cls_b1: 0.4069  loss_cls_b2: 0.3014  loss_cls_b21: 0.4814  loss_cls_b22: 0.5501  loss_cls_b3: 0.3084  loss_cls_b31: 0.5444  loss_cls_b32: 0.668  loss_cls_b33: 0.7556  loss_triplet_b1: 0.02174  loss_triplet_b2: 0.01262  loss_triplet_b3: 0.01197  loss_triplet_b22: 0.01204  loss_triplet_b33: 0.01027  time: 0.3060  data_time: 0.0007  lr: 1.45e-05  max_mem: 19416M
[04/19 13:24:31] fastreid.utils.events INFO:  eta: 0:09:09  iter: 28799  total_loss: 3.78  loss_cls_b1: 0.3804  loss_cls_b2: 0.2788  loss_cls_b21: 0.4444  loss_cls_b22: 0.5545  loss_cls_b3: 0.2763  loss_cls_b31: 0.5328  loss_cls_b32: 0.563  loss_cls_b33: 0.8249  loss_triplet_b1: 0.02056  loss_triplet_b2: 0.01194  loss_triplet_b3: 0.01235  loss_triplet_b22: 0.01219  loss_triplet_b33: 0.008415  time: 0.3061  data_time: 0.0005  lr: 1.19e-05  max_mem: 19416M
[04/19 13:25:35] fastreid.utils.events INFO:  eta: 0:08:06  iter: 28999  total_loss: 4.424  loss_cls_b1: 0.4566  loss_cls_b2: 0.3002  loss_cls_b21: 0.4664  loss_cls_b22: 0.5798  loss_cls_b3: 0.3082  loss_cls_b31: 0.5924  loss_cls_b32: 0.6387  loss_cls_b33: 0.8064  loss_triplet_b1: 0.02123  loss_triplet_b2: 0.01104  loss_triplet_b3: 0.01393  loss_triplet_b22: 0.01128  loss_triplet_b33: 0.01126  time: 0.3061  data_time: 0.0007  lr: 9.47e-06  max_mem: 19416M
[04/19 13:26:38] fastreid.utils.events INFO:  eta: 0:07:03  iter: 29199  total_loss: 3.994  loss_cls_b1: 0.3729  loss_cls_b2: 0.2674  loss_cls_b21: 0.4204  loss_cls_b22: 0.5851  loss_cls_b3: 0.2906  loss_cls_b31: 0.5289  loss_cls_b32: 0.6301  loss_cls_b33: 0.8689  loss_triplet_b1: 0.01922  loss_triplet_b2: 0.01141  loss_triplet_b3: 0.01113  loss_triplet_b22: 0.0102  loss_triplet_b33: 0.009089  time: 0.3062  data_time: 0.0005  lr: 7.37e-06  max_mem: 19416M
[04/19 13:27:42] fastreid.utils.events INFO:  eta: 0:06:00  iter: 29399  total_loss: 4.362  loss_cls_b1: 0.3819  loss_cls_b2: 0.2951  loss_cls_b21: 0.4781  loss_cls_b22: 0.6319  loss_cls_b3: 0.3141  loss_cls_b31: 0.5579  loss_cls_b32: 0.6887  loss_cls_b33: 0.9134  loss_triplet_b1: 0.02103  loss_triplet_b2: 0.01147  loss_triplet_b3: 0.01288  loss_triplet_b22: 0.01173  loss_triplet_b33: 0.01023  time: 0.3063  data_time: 0.0008  lr: 5.56e-06  max_mem: 19416M
[04/19 13:28:45] fastreid.utils.events INFO:  eta: 0:04:57  iter: 29599  total_loss: 3.896  loss_cls_b1: 0.3609  loss_cls_b2: 0.2784  loss_cls_b21: 0.4794  loss_cls_b22: 0.5551  loss_cls_b3: 0.2936  loss_cls_b31: 0.6162  loss_cls_b32: 0.6513  loss_cls_b33: 0.8041  loss_triplet_b1: 0.02064  loss_triplet_b2: 0.01006  loss_triplet_b3: 0.01244  loss_triplet_b22: 0.01179  loss_triplet_b33: 0.0101  time: 0.3063  data_time: 0.0005  lr: 4.03e-06  max_mem: 19416M
[04/19 13:29:49] fastreid.utils.events INFO:  eta: 0:03:54  iter: 29799  total_loss: 4.165  loss_cls_b1: 0.3816  loss_cls_b2: 0.2896  loss_cls_b21: 0.4383  loss_cls_b22: 0.568  loss_cls_b3: 0.3053  loss_cls_b31: 0.5308  loss_cls_b32: 0.6412  loss_cls_b33: 0.8213  loss_triplet_b1: 0.02076  loss_triplet_b2: 0.0113  loss_triplet_b3: 0.01253  loss_triplet_b22: 0.009766  loss_triplet_b33: 0.008421  time: 0.3064  data_time: 0.0008  lr: 2.80e-06  max_mem: 19416M
[04/19 13:30:53] fastreid.utils.events INFO:  eta: 0:02:50  iter: 29999  total_loss: 3.803  loss_cls_b1: 0.3477  loss_cls_b2: 0.2864  loss_cls_b21: 0.4275  loss_cls_b22: 0.4983  loss_cls_b3: 0.2678  loss_cls_b31: 0.4927  loss_cls_b32: 0.5728  loss_cls_b33: 0.7396  loss_triplet_b1: 0.02077  loss_triplet_b2: 0.01073  loss_triplet_b3: 0.01006  loss_triplet_b22: 0.01108  loss_triplet_b33: 0.00822  time: 0.3065  data_time: 0.0006  lr: 1.85e-06  max_mem: 19416M
[04/19 13:31:56] fastreid.utils.events INFO:  eta: 0:01:47  iter: 30199  total_loss: 4.053  loss_cls_b1: 0.3756  loss_cls_b2: 0.2683  loss_cls_b21: 0.4775  loss_cls_b22: 0.6539  loss_cls_b3: 0.3005  loss_cls_b31: 0.5473  loss_cls_b32: 0.663  loss_cls_b33: 0.807  loss_triplet_b1: 0.01903  loss_triplet_b2: 0.01145  loss_triplet_b3: 0.01145  loss_triplet_b22: 0.0124  loss_triplet_b33: 0.01052  time: 0.3065  data_time: 0.0008  lr: 1.20e-06  max_mem: 19416M
[04/19 13:32:59] fastreid.utils.events INFO:  eta: 0:00:44  iter: 30399  total_loss: 4.105  loss_cls_b1: 0.3752  loss_cls_b2: 0.2882  loss_cls_b21: 0.4426  loss_cls_b22: 0.5829  loss_cls_b3: 0.2865  loss_cls_b31: 0.5101  loss_cls_b32: 0.6217  loss_cls_b33: 0.8358  loss_triplet_b1: 0.01924  loss_triplet_b2: 0.01088  loss_triplet_b3: 0.01038  loss_triplet_b22: 0.01128  loss_triplet_b33: 0.009939  time: 0.3066  data_time: 0.0006  lr: 8.43e-07  max_mem: 19416M
[04/19 13:33:44] fastreid.engine.defaults INFO: Prepare testing set
[04/19 13:33:44] fastreid.data.datasets.bases INFO: => Loaded MSMT17 in csv format: 
[36m| subset   | # ids   | # images   | # cameras   |
|:---------|:--------|:-----------|:------------|
| query    | 3060    | 11659      | 15          |
| gallery  | 3060    | 82161      | 15          |[0m
[04/19 13:33:44] fastreid.evaluation.evaluator INFO: Start inference on 93820 images
[04/19 13:33:54] fastreid.evaluation.evaluator INFO: Inference done 11/733. 0.0539 s / batch. ETA=0:01:05
[04/19 13:34:24] fastreid.evaluation.evaluator INFO: Inference done 397/733. 0.0284 s / batch. ETA=0:00:26
[04/19 13:34:51] fastreid.evaluation.evaluator INFO: Total inference time: 0:00:57.233123 (0.078617 s / batch per device)
[04/19 13:34:51] fastreid.evaluation.evaluator INFO: Total inference pure compute time: 0:00:20 (0.028287 s / batch per device)
[04/19 13:59:24] fastreid.evaluation.testing INFO: Evaluation results in csv format: 
[36m| Datasets   | Rank-1   | Rank-5   | Rank-10   | mAP    | mINP   |
|:-----------|:---------|:---------|:----------|:-------|:-------|
| MSMT17     | 87.74%   | 93.96%   | 95.51%    | 70.09% | 21.75% |[0m
[04/19 13:59:24] fastreid.utils.events INFO:  eta: 0:00:00  iter: 30539  total_loss: 3.515  loss_cls_b1: 0.3169  loss_cls_b2: 0.2518  loss_cls_b21: 0.3825  loss_cls_b22: 0.4888  loss_cls_b3: 0.2646  loss_cls_b31: 0.4742  loss_cls_b32: 0.5353  loss_cls_b33: 0.6555  loss_triplet_b1: 0.01978  loss_triplet_b2: 0.01092  loss_triplet_b3: 0.01015  loss_triplet_b22: 0.0098  loss_triplet_b33: 0.008758  time: 0.3066  data_time: 0.0005  lr: 7.70e-07  max_mem: 19416M
[04/19 13:59:24] fastreid.engine.hooks INFO: Overall training speed: 30537 iterations in 2:36:04 (0.3067 s / it)
[04/19 13:59:24] fastreid.engine.hooks INFO: Total training time: 3:06:33 (0:30:29 on hooks)
