[04/30 20:02:07] fastreid INFO: Rank of current process: 0. World size: 4
[04/30 20:02:07] 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, 

[04/30 20:02:07] fastreid INFO: Command line arguments: Namespace(config_file='configs/CMDM/market1501_mgn_R152_lion.yml', finetune=False, resume=False, eval_only=False, num_gpus=4, num_machines=1, machine_rank=0, dist_url='tcp://127.0.0.1:43184', opts=[])
[04/30 20:02:07] fastreid INFO: Contents of args.config_file=configs/CMDM/market1501_mgn_R152_lion.yml:
_BASE_: "../Base-MGN.yml"

MODEL:
  BACKBONE:
    WITH_IBN: False
    EXTRA_BN: True
    DEPTH: "152x"
    PRETRAIN_PATH: "/home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet152.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:market+split_mode:id+split_ratio:1.0'
  ROOT: "/home/ma-user/work/Datasets/ImageReID_Datasets/mixreid"

TEST:
  EVAL_PERIOD: 60

OUTPUT_DIR: "logs/market/ResNet152_LION_MGN"

[04/30 20:02:07] 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:market+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: 152x
    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/ResNet152.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/market/ResNet152_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
[04/30 20:02:07] fastreid INFO: Full config saved to /home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/logs/market/ResNet152_LION_MGN/config.yaml
[04/30 20:02:07] fastreid.utils.env INFO: Using a generated random seed 8507741
[04/30 20:02:07] fastreid.engine.defaults INFO: Prepare training set
[04/30 20:02:07] fastreid.data.datasets.bases INFO: => Loaded CMDM in csv format: 
[36m| subset   | # ids   | # images   | # cameras   |
|:---------|:--------|:-----------|:------------|
| train    | 751     | 12936      | 6           |[0m
[04/30 20:02:08] fastreid.engine.defaults INFO: Auto-scaling the config to num_classes=751, max_Iter=12120, wamrup_Iter=2020, freeze_Iter=2020, delay_Iter=6060, step_Iter=[8080, 18180], ckpt_Iter=-203, eval_Iter=12200.
[04/30 20:02:09] fastreid.modeling.backbones.resnet INFO: Loading pretrained model from /home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet152.pth
[04/30 20:02:30] fastreid.engine.defaults INFO: Freeze layer group "backbone,b1,b2,b3" training for 2020 iterations
[04/30 20:02:30] fastreid.utils.checkpoint INFO: No checkpoint found. Training model from scratch
[04/30 20:02:30] fastreid.engine.train_loop INFO: Starting training from iteration 0
[04/30 20:04:09] fastreid.engine.hooks INFO: Overall training speed: 134 iterations in 0:01:31 (0.6844 s / it)
[04/30 20:04:09] fastreid.engine.hooks INFO: Total training time: 0:01:32 (0:00:00 on hooks)
[04/30 20:04:50] fastreid INFO: Rank of current process: 0. World size: 4
[04/30 20:04:51] 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, 

[04/30 20:04:51] fastreid INFO: Command line arguments: Namespace(config_file='configs/CMDM/market1501_mgn_R152_lion.yml', finetune=False, resume=False, eval_only=False, num_gpus=4, num_machines=1, machine_rank=0, dist_url='tcp://127.0.0.1:37196', opts=[])
[04/30 20:04:51] fastreid INFO: Contents of args.config_file=configs/CMDM/market1501_mgn_R152_lion.yml:
_BASE_: "../Base-MGN.yml"

MODEL:
  BACKBONE:
    WITH_IBN: False
    EXTRA_BN: True
    DEPTH: "152x"
    PRETRAIN_PATH: "/home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet152.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:market+split_mode:id+split_ratio:1.0'
  ROOT: "/home/ma-user/work/Datasets/ImageReID_Datasets/mixreid"

TEST:
  EVAL_PERIOD: 60

OUTPUT_DIR: "logs/market/ResNet152_LION_MGN"

[04/30 20:04:51] 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:market+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: 152x
    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/ResNet152.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/market/ResNet152_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
[04/30 20:04:51] fastreid INFO: Full config saved to /home/ma-user/work/Projects/ReIDNet_Finetune/FastReID/logs/market/ResNet152_LION_MGN/config.yaml
[04/30 20:04:51] fastreid.utils.env INFO: Using a generated random seed 52359599
[04/30 20:04:51] fastreid.engine.defaults INFO: Prepare training set
[04/30 20:04:51] fastreid.data.datasets.bases INFO: => Loaded CMDM in csv format: 
[36m| subset   | # ids   | # images   | # cameras   |
|:---------|:--------|:-----------|:------------|
| train    | 751     | 12936      | 6           |[0m
[04/30 20:04:51] fastreid.engine.defaults INFO: Auto-scaling the config to num_classes=751, max_Iter=12120, wamrup_Iter=2020, freeze_Iter=2020, delay_Iter=6060, step_Iter=[8080, 18180], ckpt_Iter=-203, eval_Iter=12200.
[04/30 20:04:53] fastreid.modeling.backbones.resnet INFO: Loading pretrained model from /home/ma-user/work/Projects/ReIDNets_Checkpoints_TransReID/ResNet152.pth
[04/30 20:05:14] fastreid.engine.defaults INFO: Freeze layer group "backbone,b1,b2,b3" training for 2020 iterations
[04/30 20:05:14] fastreid.utils.checkpoint INFO: No checkpoint found. Training model from scratch
[04/30 20:05:14] fastreid.engine.train_loop INFO: Starting training from iteration 0
[04/30 20:07:37] fastreid.utils.events INFO:  eta: 2:15:09  iter: 199  total_loss: 55.53  loss_cls_b1: 6.339  loss_cls_b2: 6.218  loss_cls_b21: 6.264  loss_cls_b22: 6.278  loss_cls_b3: 6.285  loss_cls_b31: 6.412  loss_cls_b32: 6.261  loss_cls_b33: 6.347  loss_triplet_b1: 0.7799  loss_triplet_b2: 0.7567  loss_triplet_b3: 0.8039  loss_triplet_b22: 1.074  loss_triplet_b33: 1.504  time: 0.6846  data_time: 0.0005  lr: 3.76e-05  max_mem: 21550M
[04/30 20:09:54] fastreid.utils.events INFO:  eta: 2:12:49  iter: 399  total_loss: 53.93  loss_cls_b1: 6.241  loss_cls_b2: 6.151  loss_cls_b21: 6.099  loss_cls_b22: 6.289  loss_cls_b3: 6.169  loss_cls_b31: 6.19  loss_cls_b32: 6.252  loss_cls_b33: 6.204  loss_triplet_b1: 0.6519  loss_triplet_b2: 0.6813  loss_triplet_b3: 0.6898  loss_triplet_b22: 1.053  loss_triplet_b33: 1.316  time: 0.6821  data_time: 0.0005  lr: 7.19e-05  max_mem: 21550M
[04/30 20:12:10] fastreid.utils.events INFO:  eta: 2:10:29  iter: 599  total_loss: 52.46  loss_cls_b1: 5.996  loss_cls_b2: 6.015  loss_cls_b21: 6.095  loss_cls_b22: 6.014  loss_cls_b3: 5.99  loss_cls_b31: 6.153  loss_cls_b32: 6.076  loss_cls_b33: 6.117  loss_triplet_b1: 0.6322  loss_triplet_b2: 0.6542  loss_triplet_b3: 0.6702  loss_triplet_b22: 0.9757  loss_triplet_b33: 1.199  time: 0.6809  data_time: 0.0005  lr: 1.06e-04  max_mem: 21550M
[04/30 20:14:27] fastreid.utils.events INFO:  eta: 2:08:12  iter: 799  total_loss: 50.01  loss_cls_b1: 5.786  loss_cls_b2: 5.725  loss_cls_b21: 5.725  loss_cls_b22: 5.765  loss_cls_b3: 5.734  loss_cls_b31: 5.781  loss_cls_b32: 5.892  loss_cls_b33: 5.839  loss_triplet_b1: 0.5036  loss_triplet_b2: 0.542  loss_triplet_b3: 0.5666  loss_triplet_b22: 0.7651  loss_triplet_b33: 1.015  time: 0.6803  data_time: 0.0005  lr: 1.41e-04  max_mem: 21550M
[04/30 20:16:43] fastreid.utils.events INFO:  eta: 2:05:53  iter: 999  total_loss: 46.86  loss_cls_b1: 5.459  loss_cls_b2: 5.371  loss_cls_b21: 5.367  loss_cls_b22: 5.449  loss_cls_b3: 5.243  loss_cls_b31: 5.487  loss_cls_b32: 5.38  loss_cls_b33: 5.547  loss_triplet_b1: 0.4464  loss_triplet_b2: 0.4916  loss_triplet_b3: 0.4723  loss_triplet_b22: 0.6434  loss_triplet_b33: 0.869  time: 0.6798  data_time: 0.0005  lr: 1.75e-04  max_mem: 21550M
[04/30 20:18:59] fastreid.utils.events INFO:  eta: 2:03:34  iter: 1199  total_loss: 44.73  loss_cls_b1: 5.116  loss_cls_b2: 5.187  loss_cls_b21: 5.198  loss_cls_b22: 5.24  loss_cls_b3: 5.043  loss_cls_b31: 5.339  loss_cls_b32: 5.154  loss_cls_b33: 5.272  loss_triplet_b1: 0.4437  loss_triplet_b2: 0.4719  loss_triplet_b3: 0.4345  loss_triplet_b22: 0.5797  loss_triplet_b33: 0.821  time: 0.6796  data_time: 0.0005  lr: 2.09e-04  max_mem: 21550M
[04/30 20:21:16] fastreid.utils.events INFO:  eta: 2:01:17  iter: 1399  total_loss: 39.42  loss_cls_b1: 4.543  loss_cls_b2: 4.657  loss_cls_b21: 4.6  loss_cls_b22: 4.735  loss_cls_b3: 4.411  loss_cls_b31: 4.79  loss_cls_b32: 4.678  loss_cls_b33: 4.919  loss_triplet_b1: 0.3889  loss_triplet_b2: 0.3885  loss_triplet_b3: 0.3676  loss_triplet_b22: 0.5246  loss_triplet_b33: 0.637  time: 0.6794  data_time: 0.0005  lr: 2.43e-04  max_mem: 21550M
[04/30 20:23:32] fastreid.utils.events INFO:  eta: 1:59:01  iter: 1599  total_loss: 35.95  loss_cls_b1: 4.125  loss_cls_b2: 4.055  loss_cls_b21: 4.303  loss_cls_b22: 4.279  loss_cls_b3: 4.113  loss_cls_b31: 4.454  loss_cls_b32: 4.343  loss_cls_b33: 4.423  loss_triplet_b1: 0.3324  loss_triplet_b2: 0.3601  loss_triplet_b3: 0.3455  loss_triplet_b22: 0.4232  loss_triplet_b33: 0.6582  time: 0.6792  data_time: 0.0005  lr: 2.78e-04  max_mem: 21550M
[04/30 20:25:49] fastreid.utils.events INFO:  eta: 1:56:47  iter: 1799  total_loss: 33.14  loss_cls_b1: 3.664  loss_cls_b2: 3.546  loss_cls_b21: 3.94  loss_cls_b22: 3.944  loss_cls_b3: 3.671  loss_cls_b31: 4.064  loss_cls_b32: 3.952  loss_cls_b33: 4.019  loss_triplet_b1: 0.3641  loss_triplet_b2: 0.3498  loss_triplet_b3: 0.3233  loss_triplet_b22: 0.4538  loss_triplet_b33: 0.5577  time: 0.6793  data_time: 0.0005  lr: 3.12e-04  max_mem: 21550M
[04/30 20:28:05] fastreid.utils.events INFO:  eta: 1:54:31  iter: 1999  total_loss: 28.83  loss_cls_b1: 3.281  loss_cls_b2: 3.228  loss_cls_b21: 3.347  loss_cls_b22: 3.575  loss_cls_b3: 3.198  loss_cls_b31: 3.542  loss_cls_b32: 3.434  loss_cls_b33: 3.777  loss_triplet_b1: 0.2518  loss_triplet_b2: 0.2629  loss_triplet_b3: 0.2338  loss_triplet_b22: 0.3115  loss_triplet_b33: 0.4495  time: 0.6791  data_time: 0.0005  lr: 3.46e-04  max_mem: 21550M
[04/30 20:30:40] fastreid.utils.events INFO:  eta: 1:52:24  iter: 2199  total_loss: 30.52  loss_cls_b1: 3.499  loss_cls_b2: 3.368  loss_cls_b21: 3.861  loss_cls_b22: 3.621  loss_cls_b3: 3.463  loss_cls_b31: 3.908  loss_cls_b32: 3.776  loss_cls_b33: 3.843  loss_triplet_b1: 0.2475  loss_triplet_b2: 0.1942  loss_triplet_b3: 0.1902  loss_triplet_b22: 0.2685  loss_triplet_b33: 0.3327  time: 0.6874  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 20:33:17] fastreid.utils.events INFO:  eta: 1:50:26  iter: 2399  total_loss: 26.2  loss_cls_b1: 2.981  loss_cls_b2: 2.93  loss_cls_b21: 3.179  loss_cls_b22: 3.41  loss_cls_b3: 2.915  loss_cls_b31: 3.407  loss_cls_b32: 3.258  loss_cls_b33: 3.564  loss_triplet_b1: 0.1272  loss_triplet_b2: 0.1325  loss_triplet_b3: 0.09126  loss_triplet_b22: 0.1275  loss_triplet_b33: 0.1967  time: 0.6948  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 20:35:53] fastreid.utils.events INFO:  eta: 2:02:19  iter: 2599  total_loss: 24.26  loss_cls_b1: 2.718  loss_cls_b2: 2.731  loss_cls_b21: 2.878  loss_cls_b22: 2.975  loss_cls_b3: 2.696  loss_cls_b31: 3.018  loss_cls_b32: 2.945  loss_cls_b33: 3.367  loss_triplet_b1: 0.0878  loss_triplet_b2: 0.09413  loss_triplet_b3: 0.0634  loss_triplet_b22: 0.1005  loss_triplet_b33: 0.133  time: 0.7010  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 20:38:29] fastreid.utils.events INFO:  eta: 2:00:06  iter: 2799  total_loss: 22.05  loss_cls_b1: 2.462  loss_cls_b2: 2.334  loss_cls_b21: 2.745  loss_cls_b22: 2.795  loss_cls_b3: 2.392  loss_cls_b31: 2.993  loss_cls_b32: 2.692  loss_cls_b33: 3.204  loss_triplet_b1: 0.08194  loss_triplet_b2: 0.05927  loss_triplet_b3: 0.07291  loss_triplet_b22: 0.06866  loss_triplet_b33: 0.1484  time: 0.7063  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 20:41:06] fastreid.utils.events INFO:  eta: 1:57:40  iter: 2999  total_loss: 20.21  loss_cls_b1: 2.226  loss_cls_b2: 2.201  loss_cls_b21: 2.489  loss_cls_b22: 2.633  loss_cls_b3: 2.218  loss_cls_b31: 2.851  loss_cls_b32: 2.477  loss_cls_b33: 2.964  loss_triplet_b1: 0.04258  loss_triplet_b2: 0.03097  loss_triplet_b3: 0.02993  loss_triplet_b22: 0.04936  loss_triplet_b33: 0.06954  time: 0.7108  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 20:43:42] fastreid.utils.events INFO:  eta: 1:55:05  iter: 3199  total_loss: 18.08  loss_cls_b1: 1.9  loss_cls_b2: 1.888  loss_cls_b21: 2.242  loss_cls_b22: 2.362  loss_cls_b3: 1.874  loss_cls_b31: 2.505  loss_cls_b32: 2.158  loss_cls_b33: 2.805  loss_triplet_b1: 0.03854  loss_triplet_b2: 0.03411  loss_triplet_b3: 0.04169  loss_triplet_b22: 0.03907  loss_triplet_b33: 0.05952  time: 0.7148  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 20:46:18] fastreid.utils.events INFO:  eta: 1:52:31  iter: 3399  total_loss: 18.01  loss_cls_b1: 1.914  loss_cls_b2: 1.862  loss_cls_b21: 2.214  loss_cls_b22: 2.448  loss_cls_b3: 1.904  loss_cls_b31: 2.507  loss_cls_b32: 2.162  loss_cls_b33: 2.825  loss_triplet_b1: 0.04078  loss_triplet_b2: 0.03789  loss_triplet_b3: 0.02401  loss_triplet_b22: 0.03828  loss_triplet_b33: 0.04007  time: 0.7184  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 20:48:55] fastreid.utils.events INFO:  eta: 1:49:56  iter: 3599  total_loss: 16.79  loss_cls_b1: 1.723  loss_cls_b2: 1.651  loss_cls_b21: 1.996  loss_cls_b22: 2.224  loss_cls_b3: 1.6  loss_cls_b31: 2.348  loss_cls_b32: 1.899  loss_cls_b33: 2.756  loss_triplet_b1: 0.05185  loss_triplet_b2: 0.04249  loss_triplet_b3: 0.03875  loss_triplet_b22: 0.05207  loss_triplet_b33: 0.05874  time: 0.7216  data_time: 0.0006  lr: 3.50e-04  max_mem: 21550M
[04/30 20:51:31] fastreid.utils.events INFO:  eta: 1:47:23  iter: 3799  total_loss: 16.5  loss_cls_b1: 1.649  loss_cls_b2: 1.541  loss_cls_b21: 2.163  loss_cls_b22: 2.066  loss_cls_b3: 1.544  loss_cls_b31: 2.396  loss_cls_b32: 2.021  loss_cls_b33: 2.599  loss_triplet_b1: 0.03885  loss_triplet_b2: 0.02699  loss_triplet_b3: 0.02556  loss_triplet_b22: 0.0311  loss_triplet_b33: 0.03182  time: 0.7245  data_time: 0.0006  lr: 3.50e-04  max_mem: 21550M
[04/30 20:54:08] fastreid.utils.events INFO:  eta: 1:44:50  iter: 3999  total_loss: 16.35  loss_cls_b1: 1.682  loss_cls_b2: 1.646  loss_cls_b21: 2.044  loss_cls_b22: 2.308  loss_cls_b3: 1.573  loss_cls_b31: 2.436  loss_cls_b32: 1.955  loss_cls_b33: 2.578  loss_triplet_b1: 0.06291  loss_triplet_b2: 0.04357  loss_triplet_b3: 0.02749  loss_triplet_b22: 0.05038  loss_triplet_b33: 0.05406  time: 0.7270  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 20:56:44] fastreid.utils.events INFO:  eta: 1:42:15  iter: 4199  total_loss: 15.51  loss_cls_b1: 1.579  loss_cls_b2: 1.511  loss_cls_b21: 1.937  loss_cls_b22: 2.012  loss_cls_b3: 1.477  loss_cls_b31: 2.177  loss_cls_b32: 1.844  loss_cls_b33: 2.574  loss_triplet_b1: 0.0534  loss_triplet_b2: 0.03326  loss_triplet_b3: 0.04486  loss_triplet_b22: 0.04887  loss_triplet_b33: 0.04565  time: 0.7293  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 20:59:20] fastreid.utils.events INFO:  eta: 1:39:38  iter: 4399  total_loss: 15.74  loss_cls_b1: 1.597  loss_cls_b2: 1.487  loss_cls_b21: 1.956  loss_cls_b22: 2.029  loss_cls_b3: 1.495  loss_cls_b31: 2.257  loss_cls_b32: 1.926  loss_cls_b33: 2.618  loss_triplet_b1: 0.03185  loss_triplet_b2: 0.02435  loss_triplet_b3: 0.02841  loss_triplet_b22: 0.03359  loss_triplet_b33: 0.04346  time: 0.7313  data_time: 0.0004  lr: 3.50e-04  max_mem: 21550M
[04/30 21:01:57] fastreid.utils.events INFO:  eta: 1:37:02  iter: 4599  total_loss: 15.26  loss_cls_b1: 1.522  loss_cls_b2: 1.391  loss_cls_b21: 1.839  loss_cls_b22: 1.903  loss_cls_b3: 1.397  loss_cls_b31: 2.309  loss_cls_b32: 1.706  loss_cls_b33: 2.436  loss_triplet_b1: 0.03374  loss_triplet_b2: 0.02898  loss_triplet_b3: 0.02323  loss_triplet_b22: 0.02825  loss_triplet_b33: 0.03818  time: 0.7333  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 21:04:33] fastreid.utils.events INFO:  eta: 1:34:25  iter: 4799  total_loss: 13.74  loss_cls_b1: 1.372  loss_cls_b2: 1.272  loss_cls_b21: 1.666  loss_cls_b22: 1.695  loss_cls_b3: 1.321  loss_cls_b31: 2.085  loss_cls_b32: 1.639  loss_cls_b33: 2.242  loss_triplet_b1: 0.03398  loss_triplet_b2: 0.02319  loss_triplet_b3: 0.02582  loss_triplet_b22: 0.03087  loss_triplet_b33: 0.03071  time: 0.7350  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 21:07:09] fastreid.utils.events INFO:  eta: 1:31:49  iter: 4999  total_loss: 12.71  loss_cls_b1: 1.231  loss_cls_b2: 1.252  loss_cls_b21: 1.599  loss_cls_b22: 1.601  loss_cls_b3: 1.235  loss_cls_b31: 1.971  loss_cls_b32: 1.506  loss_cls_b33: 2.199  loss_triplet_b1: 0.03636  loss_triplet_b2: 0.02215  loss_triplet_b3: 0.02406  loss_triplet_b22: 0.02276  loss_triplet_b33: 0.02842  time: 0.7366  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 21:09:46] fastreid.utils.events INFO:  eta: 1:29:14  iter: 5199  total_loss: 12.62  loss_cls_b1: 1.24  loss_cls_b2: 1.159  loss_cls_b21: 1.549  loss_cls_b22: 1.717  loss_cls_b3: 1.16  loss_cls_b31: 1.831  loss_cls_b32: 1.556  loss_cls_b33: 2.213  loss_triplet_b1: 0.03012  loss_triplet_b2: 0.02269  loss_triplet_b3: 0.02423  loss_triplet_b22: 0.03072  loss_triplet_b33: 0.03436  time: 0.7380  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 21:12:23] fastreid.utils.events INFO:  eta: 1:26:40  iter: 5399  total_loss: 11.87  loss_cls_b1: 1.099  loss_cls_b2: 0.9967  loss_cls_b21: 1.426  loss_cls_b22: 1.493  loss_cls_b3: 1.017  loss_cls_b31: 1.715  loss_cls_b32: 1.334  loss_cls_b33: 2.028  loss_triplet_b1: 0.02556  loss_triplet_b2: 0.02091  loss_triplet_b3: 0.02093  loss_triplet_b22: 0.03266  loss_triplet_b33: 0.02636  time: 0.7394  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 21:14:59] fastreid.utils.events INFO:  eta: 1:24:05  iter: 5599  total_loss: 11.16  loss_cls_b1: 1.095  loss_cls_b2: 0.9239  loss_cls_b21: 1.333  loss_cls_b22: 1.449  loss_cls_b3: 1.03  loss_cls_b31: 1.741  loss_cls_b32: 1.348  loss_cls_b33: 2  loss_triplet_b1: 0.02906  loss_triplet_b2: 0.0188  loss_triplet_b3: 0.01552  loss_triplet_b22: 0.02007  loss_triplet_b33: 0.01824  time: 0.7407  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 21:17:35] fastreid.utils.events INFO:  eta: 1:21:31  iter: 5799  total_loss: 11.77  loss_cls_b1: 1.14  loss_cls_b2: 1.044  loss_cls_b21: 1.461  loss_cls_b22: 1.479  loss_cls_b3: 1.111  loss_cls_b31: 1.796  loss_cls_b32: 1.463  loss_cls_b33: 1.947  loss_triplet_b1: 0.03894  loss_triplet_b2: 0.02334  loss_triplet_b3: 0.02556  loss_triplet_b22: 0.02988  loss_triplet_b33: 0.02805  time: 0.7418  data_time: 0.0006  lr: 3.50e-04  max_mem: 21550M
[04/30 21:20:11] fastreid.utils.events INFO:  eta: 1:18:55  iter: 5999  total_loss: 10.92  loss_cls_b1: 1.054  loss_cls_b2: 0.9776  loss_cls_b21: 1.382  loss_cls_b22: 1.44  loss_cls_b3: 0.9614  loss_cls_b31: 1.643  loss_cls_b32: 1.322  loss_cls_b33: 1.86  loss_triplet_b1: 0.01715  loss_triplet_b2: 0.01931  loss_triplet_b3: 0.01154  loss_triplet_b22: 0.01917  loss_triplet_b33: 0.01141  time: 0.7429  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 21:22:48] fastreid.utils.events INFO:  eta: 1:16:19  iter: 6199  total_loss: 10.51  loss_cls_b1: 1.103  loss_cls_b2: 0.9186  loss_cls_b21: 1.461  loss_cls_b22: 1.391  loss_cls_b3: 0.9004  loss_cls_b31: 1.581  loss_cls_b32: 1.326  loss_cls_b33: 1.931  loss_triplet_b1: 0.02344  loss_triplet_b2: 0.01521  loss_triplet_b3: 0.01864  loss_triplet_b22: 0.01299  loss_triplet_b33: 0.01598  time: 0.7439  data_time: 0.0005  lr: 3.50e-04  max_mem: 21550M
[04/30 21:25:24] fastreid.utils.events INFO:  eta: 1:13:43  iter: 6399  total_loss: 9.926  loss_cls_b1: 1.035  loss_cls_b2: 0.8272  loss_cls_b21: 1.307  loss_cls_b22: 1.4  loss_cls_b3: 0.8452  loss_cls_b31: 1.643  loss_cls_b32: 1.305  loss_cls_b33: 1.869  loss_triplet_b1: 0.029  loss_triplet_b2: 0.01785  loss_triplet_b3: 0.02042  loss_triplet_b22: 0.02522  loss_triplet_b33: 0.03129  time: 0.7448  data_time: 0.0005  lr: 3.47e-04  max_mem: 21550M
[04/30 21:28:01] fastreid.utils.events INFO:  eta: 1:11:07  iter: 6599  total_loss: 9.442  loss_cls_b1: 0.8699  loss_cls_b2: 0.8046  loss_cls_b21: 1.18  loss_cls_b22: 1.207  loss_cls_b3: 0.7601  loss_cls_b31: 1.611  loss_cls_b32: 1.098  loss_cls_b33: 1.743  loss_triplet_b1: 0.01852  loss_triplet_b2: 0.01687  loss_triplet_b3: 0.01418  loss_triplet_b22: 0.01728  loss_triplet_b33: 0.01547  time: 0.7457  data_time: 0.0005  lr: 3.43e-04  max_mem: 21550M
[04/30 21:30:37] fastreid.utils.events INFO:  eta: 1:08:30  iter: 6799  total_loss: 8.773  loss_cls_b1: 0.8303  loss_cls_b2: 0.7563  loss_cls_b21: 1.156  loss_cls_b22: 1.182  loss_cls_b3: 0.766  loss_cls_b31: 1.423  loss_cls_b32: 1.114  loss_cls_b33: 1.611  loss_triplet_b1: 0.0154  loss_triplet_b2: 0.01185  loss_triplet_b3: 0.01063  loss_triplet_b22: 0.01624  loss_triplet_b33: 0.01266  time: 0.7465  data_time: 0.0005  lr: 3.37e-04  max_mem: 21550M
[04/30 21:33:13] fastreid.utils.events INFO:  eta: 1:05:54  iter: 6999  total_loss: 8.733  loss_cls_b1: 0.8045  loss_cls_b2: 0.7187  loss_cls_b21: 1.138  loss_cls_b22: 1.103  loss_cls_b3: 0.724  loss_cls_b31: 1.396  loss_cls_b32: 1.1  loss_cls_b33: 1.594  loss_triplet_b1: 0.01493  loss_triplet_b2: 0.01446  loss_triplet_b3: 0.01255  loss_triplet_b22: 0.01342  loss_triplet_b33: 0.008101  time: 0.7472  data_time: 0.0006  lr: 3.30e-04  max_mem: 21550M
[04/30 21:35:50] fastreid.utils.events INFO:  eta: 1:03:19  iter: 7199  total_loss: 8.099  loss_cls_b1: 0.7345  loss_cls_b2: 0.6787  loss_cls_b21: 1.107  loss_cls_b22: 1.042  loss_cls_b3: 0.6158  loss_cls_b31: 1.481  loss_cls_b32: 0.948  loss_cls_b33: 1.523  loss_triplet_b1: 0.01709  loss_triplet_b2: 0.01412  loss_triplet_b3: 0.01168  loss_triplet_b22: 0.01394  loss_triplet_b33: 0.01252  time: 0.7479  data_time: 0.0005  lr: 3.20e-04  max_mem: 21550M
[04/30 21:38:26] fastreid.utils.events INFO:  eta: 1:00:43  iter: 7399  total_loss: 7.653  loss_cls_b1: 0.7058  loss_cls_b2: 0.6206  loss_cls_b21: 0.98  loss_cls_b22: 0.9191  loss_cls_b3: 0.6407  loss_cls_b31: 1.268  loss_cls_b32: 0.9458  loss_cls_b33: 1.327  loss_triplet_b1: 0.01286  loss_triplet_b2: 0.007881  loss_triplet_b3: 0.007225  loss_triplet_b22: 0.008861  loss_triplet_b33: 0.01007  time: 0.7486  data_time: 0.0006  lr: 3.10e-04  max_mem: 21550M
[04/30 21:41:02] fastreid.utils.events INFO:  eta: 0:58:08  iter: 7599  total_loss: 7.884  loss_cls_b1: 0.7204  loss_cls_b2: 0.6089  loss_cls_b21: 1.018  loss_cls_b22: 1.074  loss_cls_b3: 0.5973  loss_cls_b31: 1.296  loss_cls_b32: 0.9628  loss_cls_b33: 1.511  loss_triplet_b1: 0.01732  loss_triplet_b2: 0.01085  loss_triplet_b3: 0.01046  loss_triplet_b22: 0.01257  loss_triplet_b33: 0.009297  time: 0.7492  data_time: 0.0005  lr: 2.97e-04  max_mem: 21550M
[04/30 21:43:38] fastreid.utils.events INFO:  eta: 0:55:33  iter: 7799  total_loss: 7.528  loss_cls_b1: 0.7412  loss_cls_b2: 0.622  loss_cls_b21: 0.9432  loss_cls_b22: 0.9938  loss_cls_b3: 0.6461  loss_cls_b31: 1.212  loss_cls_b32: 0.9378  loss_cls_b33: 1.452  loss_triplet_b1: 0.01825  loss_triplet_b2: 0.01158  loss_triplet_b3: 0.01347  loss_triplet_b22: 0.01158  loss_triplet_b33: 0.009688  time: 0.7498  data_time: 0.0005  lr: 2.84e-04  max_mem: 21550M
[04/30 21:46:15] fastreid.utils.events INFO:  eta: 0:52:59  iter: 7999  total_loss: 6.967  loss_cls_b1: 0.7171  loss_cls_b2: 0.5728  loss_cls_b21: 0.8719  loss_cls_b22: 0.9285  loss_cls_b3: 0.575  loss_cls_b31: 1.153  loss_cls_b32: 0.9035  loss_cls_b33: 1.385  loss_triplet_b1: 0.01175  loss_triplet_b2: 0.005943  loss_triplet_b3: 0.00734  loss_triplet_b22: 0.005946  loss_triplet_b33: 0.007323  time: 0.7504  data_time: 0.0005  lr: 2.69e-04  max_mem: 21550M
[04/30 21:48:51] fastreid.utils.events INFO:  eta: 0:50:25  iter: 8199  total_loss: 6.822  loss_cls_b1: 0.6568  loss_cls_b2: 0.5073  loss_cls_b21: 0.9425  loss_cls_b22: 0.8271  loss_cls_b3: 0.5415  loss_cls_b31: 1.288  loss_cls_b32: 0.8942  loss_cls_b33: 1.249  loss_triplet_b1: 0.01455  loss_triplet_b2: 0.00831  loss_triplet_b3: 0.009401  loss_triplet_b22: 0.008121  loss_triplet_b33: 0.00933  time: 0.7509  data_time: 0.0005  lr: 2.53e-04  max_mem: 21550M
[04/30 21:51:27] fastreid.utils.events INFO:  eta: 0:47:50  iter: 8399  total_loss: 6.263  loss_cls_b1: 0.5685  loss_cls_b2: 0.4773  loss_cls_b21: 0.8048  loss_cls_b22: 0.8717  loss_cls_b3: 0.4635  loss_cls_b31: 1.117  loss_cls_b32: 0.7918  loss_cls_b33: 1.379  loss_triplet_b1: 0.01164  loss_triplet_b2: 0.01028  loss_triplet_b3: 0.00716  loss_triplet_b22: 0.008822  loss_triplet_b33: 0.007083  time: 0.7514  data_time: 0.0005  lr: 2.37e-04  max_mem: 21550M
[04/30 21:54:04] fastreid.utils.events INFO:  eta: 0:45:15  iter: 8599  total_loss: 6.514  loss_cls_b1: 0.5979  loss_cls_b2: 0.51  loss_cls_b21: 0.7922  loss_cls_b22: 0.8587  loss_cls_b3: 0.5324  loss_cls_b31: 1.037  loss_cls_b32: 0.8338  loss_cls_b33: 1.265  loss_triplet_b1: 0.008226  loss_triplet_b2: 0.005067  loss_triplet_b3: 0.006421  loss_triplet_b22: 0.003865  loss_triplet_b33: 0.00583  time: 0.7519  data_time: 0.0005  lr: 2.19e-04  max_mem: 21550M
[04/30 21:56:40] fastreid.utils.events INFO:  eta: 0:42:42  iter: 8799  total_loss: 6.102  loss_cls_b1: 0.5718  loss_cls_b2: 0.4728  loss_cls_b21: 0.7368  loss_cls_b22: 0.8175  loss_cls_b3: 0.479  loss_cls_b31: 1  loss_cls_b32: 0.7018  loss_cls_b33: 1.238  loss_triplet_b1: 0.01102  loss_triplet_b2: 0.005515  loss_triplet_b3: 0.005636  loss_triplet_b22: 0.007208  loss_triplet_b33: 0.004728  time: 0.7524  data_time: 0.0005  lr: 2.02e-04  max_mem: 21550M
[04/30 21:59:16] fastreid.utils.events INFO:  eta: 0:40:07  iter: 8999  total_loss: 5.558  loss_cls_b1: 0.5026  loss_cls_b2: 0.4099  loss_cls_b21: 0.7079  loss_cls_b22: 0.725  loss_cls_b3: 0.4173  loss_cls_b31: 0.9176  loss_cls_b32: 0.6942  loss_cls_b33: 1.18  loss_triplet_b1: 0.008823  loss_triplet_b2: 0.005161  loss_triplet_b3: 0.006748  loss_triplet_b22: 0.00467  loss_triplet_b33: 0.004237  time: 0.7528  data_time: 0.0005  lr: 1.84e-04  max_mem: 21550M
[04/30 22:01:53] fastreid.utils.events INFO:  eta: 0:37:32  iter: 9199  total_loss: 5.259  loss_cls_b1: 0.471  loss_cls_b2: 0.3769  loss_cls_b21: 0.613  loss_cls_b22: 0.6589  loss_cls_b3: 0.3653  loss_cls_b31: 0.881  loss_cls_b32: 0.6591  loss_cls_b33: 0.9623  loss_triplet_b1: 0.005966  loss_triplet_b2: 0.003356  loss_triplet_b3: 0.004224  loss_triplet_b22: 0.004077  loss_triplet_b33: 0.002183  time: 0.7533  data_time: 0.0005  lr: 1.66e-04  max_mem: 21550M
[04/30 22:04:29] fastreid.utils.events INFO:  eta: 0:34:59  iter: 9399  total_loss: 4.46  loss_cls_b1: 0.3796  loss_cls_b2: 0.3296  loss_cls_b21: 0.541  loss_cls_b22: 0.5561  loss_cls_b3: 0.3287  loss_cls_b31: 0.6896  loss_cls_b32: 0.5619  loss_cls_b33: 0.9277  loss_triplet_b1: 0.004542  loss_triplet_b2: 0.002719  loss_triplet_b3: 0.003461  loss_triplet_b22: 0.002332  loss_triplet_b33: 0.001228  time: 0.7537  data_time: 0.0005  lr: 1.48e-04  max_mem: 21550M
[04/30 22:07:05] fastreid.utils.events INFO:  eta: 0:32:25  iter: 9599  total_loss: 4.943  loss_cls_b1: 0.4365  loss_cls_b2: 0.3307  loss_cls_b21: 0.5738  loss_cls_b22: 0.6484  loss_cls_b3: 0.3596  loss_cls_b31: 0.8258  loss_cls_b32: 0.5656  loss_cls_b33: 0.9659  loss_triplet_b1: 0.003461  loss_triplet_b2: 0.002272  loss_triplet_b3: 0.002132  loss_triplet_b22: 0.001247  loss_triplet_b33: 0.0008419  time: 0.7541  data_time: 0.0005  lr: 1.30e-04  max_mem: 21550M
[04/30 22:09:42] fastreid.utils.events INFO:  eta: 0:29:51  iter: 9799  total_loss: 4.979  loss_cls_b1: 0.3942  loss_cls_b2: 0.3527  loss_cls_b21: 0.5791  loss_cls_b22: 0.6408  loss_cls_b3: 0.3913  loss_cls_b31: 0.719  loss_cls_b32: 0.6158  loss_cls_b33: 1.045  loss_triplet_b1: 0.005631  loss_triplet_b2: 0.004658  loss_triplet_b3: 0.006673  loss_triplet_b22: 0.004533  loss_triplet_b33: 0.003258  time: 0.7545  data_time: 0.0005  lr: 1.13e-04  max_mem: 21550M
[04/30 22:12:18] fastreid.utils.events INFO:  eta: 0:27:17  iter: 9999  total_loss: 3.78  loss_cls_b1: 0.3192  loss_cls_b2: 0.2771  loss_cls_b21: 0.5005  loss_cls_b22: 0.5231  loss_cls_b3: 0.2852  loss_cls_b31: 0.6416  loss_cls_b32: 0.5049  loss_cls_b33: 0.8086  loss_triplet_b1: 0.002203  loss_triplet_b2: 0.001546  loss_triplet_b3: 0.00191  loss_triplet_b22: 0.001361  loss_triplet_b33: 0.0005796  time: 0.7548  data_time: 0.0005  lr: 9.61e-05  max_mem: 21550M
[04/30 22:14:54] fastreid.utils.events INFO:  eta: 0:24:42  iter: 10199  total_loss: 3.834  loss_cls_b1: 0.2951  loss_cls_b2: 0.2551  loss_cls_b21: 0.4196  loss_cls_b22: 0.4948  loss_cls_b3: 0.2567  loss_cls_b31: 0.5932  loss_cls_b32: 0.4315  loss_cls_b33: 0.8082  loss_triplet_b1: 0.002741  loss_triplet_b2: 0.002254  loss_triplet_b3: 0.001924  loss_triplet_b22: 0.00122  loss_triplet_b33: 0.0008381  time: 0.7552  data_time: 0.0005  lr: 8.04e-05  max_mem: 21550M
[04/30 22:17:31] fastreid.utils.events INFO:  eta: 0:22:08  iter: 10399  total_loss: 4.128  loss_cls_b1: 0.3536  loss_cls_b2: 0.3065  loss_cls_b21: 0.4765  loss_cls_b22: 0.5275  loss_cls_b3: 0.3276  loss_cls_b31: 0.6784  loss_cls_b32: 0.5149  loss_cls_b33: 0.8567  loss_triplet_b1: 0.003592  loss_triplet_b2: 0.00261  loss_triplet_b3: 0.002956  loss_triplet_b22: 0.001302  loss_triplet_b33: 0.001694  time: 0.7555  data_time: 0.0005  lr: 6.58e-05  max_mem: 21550M
[04/30 22:20:07] fastreid.utils.events INFO:  eta: 0:19:34  iter: 10599  total_loss: 3.447  loss_cls_b1: 0.3294  loss_cls_b2: 0.2721  loss_cls_b21: 0.4231  loss_cls_b22: 0.4446  loss_cls_b3: 0.2609  loss_cls_b31: 0.5772  loss_cls_b32: 0.4327  loss_cls_b33: 0.771  loss_triplet_b1: 0.004643  loss_triplet_b2: 0.002368  loss_triplet_b3: 0.002746  loss_triplet_b22: 0.001958  loss_triplet_b33: 0.001096  time: 0.7559  data_time: 0.0005  lr: 5.23e-05  max_mem: 21550M
[04/30 22:22:43] fastreid.utils.events INFO:  eta: 0:16:59  iter: 10799  total_loss: 3.057  loss_cls_b1: 0.265  loss_cls_b2: 0.2224  loss_cls_b21: 0.3688  loss_cls_b22: 0.4272  loss_cls_b3: 0.239  loss_cls_b31: 0.5243  loss_cls_b32: 0.3871  loss_cls_b33: 0.6873  loss_triplet_b1: 0.002028  loss_triplet_b2: 0.001339  loss_triplet_b3: 0.00139  loss_triplet_b22: 0.0009926  loss_triplet_b33: 0.0004898  time: 0.7561  data_time: 0.0005  lr: 4.01e-05  max_mem: 21550M
[04/30 22:25:20] fastreid.utils.events INFO:  eta: 0:14:24  iter: 10999  total_loss: 3.526  loss_cls_b1: 0.297  loss_cls_b2: 0.2692  loss_cls_b21: 0.4052  loss_cls_b22: 0.4648  loss_cls_b3: 0.2744  loss_cls_b31: 0.5538  loss_cls_b32: 0.4495  loss_cls_b33: 0.7311  loss_triplet_b1: 0.002946  loss_triplet_b2: 0.003205  loss_triplet_b3: 0.003324  loss_triplet_b22: 0.001884  loss_triplet_b33: 0.0008639  time: 0.7564  data_time: 0.0005  lr: 2.94e-05  max_mem: 21550M
[04/30 22:27:56] fastreid.utils.events INFO:  eta: 0:11:50  iter: 11199  total_loss: 3.53  loss_cls_b1: 0.3029  loss_cls_b2: 0.2559  loss_cls_b21: 0.4228  loss_cls_b22: 0.4361  loss_cls_b3: 0.262  loss_cls_b31: 0.5887  loss_cls_b32: 0.4543  loss_cls_b33: 0.7075  loss_triplet_b1: 0.003305  loss_triplet_b2: 0.002691  loss_triplet_b3: 0.002939  loss_triplet_b22: 0.002424  loss_triplet_b33: 0.001076  time: 0.7567  data_time: 0.0005  lr: 2.03e-05  max_mem: 21550M
[04/30 22:30:32] fastreid.utils.events INFO:  eta: 0:09:16  iter: 11399  total_loss: 3.092  loss_cls_b1: 0.2695  loss_cls_b2: 0.2345  loss_cls_b21: 0.3719  loss_cls_b22: 0.4022  loss_cls_b3: 0.2271  loss_cls_b31: 0.53  loss_cls_b32: 0.3811  loss_cls_b33: 0.6584  loss_triplet_b1: 0.002496  loss_triplet_b2: 0.001412  loss_triplet_b3: 0.001181  loss_triplet_b22: 0.0007791  loss_triplet_b33: 0.001122  time: 0.7570  data_time: 0.0005  lr: 1.28e-05  max_mem: 21550M
[04/30 22:33:08] fastreid.utils.events INFO:  eta: 0:06:41  iter: 11599  total_loss: 2.926  loss_cls_b1: 0.2406  loss_cls_b2: 0.2374  loss_cls_b21: 0.3639  loss_cls_b22: 0.3857  loss_cls_b3: 0.2463  loss_cls_b31: 0.4595  loss_cls_b32: 0.3842  loss_cls_b33: 0.6339  loss_triplet_b1: 0.002192  loss_triplet_b2: 0.001943  loss_triplet_b3: 0.002388  loss_triplet_b22: 0.001282  loss_triplet_b33: 0.0008857  time: 0.7573  data_time: 0.0006  lr: 7.10e-06  max_mem: 21550M
[04/30 22:35:45] fastreid.utils.events INFO:  eta: 0:04:07  iter: 11799  total_loss: 2.873  loss_cls_b1: 0.2371  loss_cls_b2: 0.2075  loss_cls_b21: 0.3453  loss_cls_b22: 0.3741  loss_cls_b3: 0.2264  loss_cls_b31: 0.4979  loss_cls_b32: 0.3441  loss_cls_b33: 0.6057  loss_triplet_b1: 0.002361  loss_triplet_b2: 0.001402  loss_triplet_b3: 0.00176  loss_triplet_b22: 0.0008343  loss_triplet_b33: 0.0006234  time: 0.7575  data_time: 0.0005  lr: 3.18e-06  max_mem: 21550M
[04/30 22:38:21] fastreid.utils.events INFO:  eta: 0:01:33  iter: 11999  total_loss: 2.973  loss_cls_b1: 0.2629  loss_cls_b2: 0.2125  loss_cls_b21: 0.4005  loss_cls_b22: 0.3635  loss_cls_b3: 0.2273  loss_cls_b31: 0.5723  loss_cls_b32: 0.3997  loss_cls_b33: 0.6755  loss_triplet_b1: 0.001609  loss_triplet_b2: 0.001748  loss_triplet_b3: 0.001721  loss_triplet_b22: 0.00137  loss_triplet_b33: 0.0005648  time: 0.7578  data_time: 0.0005  lr: 1.11e-06  max_mem: 21550M
[04/30 22:39:55] fastreid.engine.defaults INFO: Prepare testing set
[04/30 22:39:55] fastreid.data.datasets.bases INFO: => Loaded CMDM in csv format: 
[36m| subset   | # ids   | # images   | # cameras   |
|:---------|:--------|:-----------|:------------|
| query    | 750     | 3368       | 6           |
| gallery  | 751     | 15913      | 6           |[0m
[04/30 22:39:55] fastreid.evaluation.evaluator INFO: Start inference on 19281 images
[04/30 22:40:06] fastreid.evaluation.evaluator INFO: Inference done 11/151. 0.0873 s / batch. ETA=0:00:20
[04/30 22:40:31] fastreid.evaluation.evaluator INFO: Total inference time: 0:00:26.320086 (0.180275 s / batch per device)
[04/30 22:40:31] fastreid.evaluation.evaluator INFO: Total inference pure compute time: 0:00:13 (0.089630 s / batch per device)
[04/30 22:41:56] fastreid.evaluation.testing INFO: Evaluation results in csv format: 
[36m| Datasets   | Rank-1   | Rank-5   | Rank-10   | mAP    | mINP   |
|:-----------|:---------|:---------|:----------|:-------|:-------|
| CMDM       | 97.33%   | 99.05%   | 99.47%    | 93.05% | 77.21% |[0m
[04/30 22:41:56] fastreid.utils.events INFO:  eta: 0:00:00  iter: 12119  total_loss: 3.229  loss_cls_b1: 0.2922  loss_cls_b2: 0.249  loss_cls_b21: 0.3842  loss_cls_b22: 0.3775  loss_cls_b3: 0.2714  loss_cls_b31: 0.5728  loss_cls_b32: 0.4149  loss_cls_b33: 0.6949  loss_triplet_b1: 0.002551  loss_triplet_b2: 0.002475  loss_triplet_b3: 0.002835  loss_triplet_b22: 0.001314  loss_triplet_b33: 0.0007245  time: 0.7579  data_time: 0.0005  lr: 7.70e-07  max_mem: 21550M
[04/30 22:41:56] fastreid.engine.hooks INFO: Overall training speed: 12117 iterations in 2:33:04 (0.7580 s / it)
[04/30 22:41:56] fastreid.engine.hooks INFO: Total training time: 2:36:34 (0:03:29 on hooks)
