text: Title: Incredibly high map, are there potential bugs in evaluation codes?
  Body: I have trained a video-based model which has a outstanding performance:
  My training script is:
  ```shell
  python main.py --app video\
                 -s    dukemtmcvidreid\
                 -t    dukemtmcvidreid\
                 -j 8 \
                 --height 256 \
                 --width 128 \
                 --optim amsgrad \
                 --label-smooth \
                 --lr 0.0003 \
                 --max-epoch 60 \
                 --stepsize 20 40 \
                 --fixbase-epoch 10 \
                 --open-layers classifier \
                 --save-dir log/pcb-Duke-Video-combined-freeze\
                 --root ../../dataset/DukeMTMC-VideoReID\
                 --batch-size 16\
                 --gpu-devices 0,1\
                 -a pcb_p6\
                 --train-sampler RandomIdentitySampler\
                 --loss triplet     
  ```
  And the performance imformation logged :
  ```
  ##### Evaluating dukemtmcvidreid (source) #####
  Extracting features from query set ...
  Done, obtained 702-by-12288 matrix
  Extracting features from gallery set ...
  Done, obtained 2636-by-12288 matrix
  Speed: 0.0620 sec/batch
  Computing CMC and mAP ...
  ** Results **
  mAP: 90.0%
  CMC curve
  Rank-1  : 89.3%
  Rank-5  : 97.4%
  Rank-10 : 98.9%
  Rank-20 : 99.3%
  ```
  It's almost **SOTA**, I'm wondering whether there could be some bugs in evaluation.
  
  Also, is it regular that mAP is higher than rank-1?