Base40 results not good

[YuQianzi]

I cannnot reopen issue #12.
Actually, when I only train the first 40 base classes using the configs in the file "warp_faster_rcnn_R_50_C4_1x.yaml", the AP50 was about 30%. I think it is not reasonable.

[YuQianzi]

@JosephKJ :Hello! My configs is shown below:

BASE: "../Base-RCNN-C4.yaml"
MODEL:
WEIGHTS: "/sharefs/wwen/incremental/iOD/IOD/configs/MSRA-R-50.pkl"
MASK_ON: False
RESNETS:
DEPTH: 50
ROI_HEADS:
NUM_CLASSES: 80
LEARN_INCREMENTALLY: True
TRAIN_ON_BASE_CLASSES: True
NUM_BASE_CLASSES: 40
NUM_NOVEL_CLASSES: 40
NMS_THRESH_TEST: 0.4
DATASETS:
TRAIN: ("coco_2014_train",)
TEST: ("coco_2014_val",)

OUTPUT_DIR: ./output/coco_base_40
SEED: 3074309
VERSION: 2

SOLVER:
IMS_PER_BATCH: 16
BASE_LR: 0.02
STEPS: (140000, 160000)
MAX_ITER: 180000

WG:
ENABLE: False
TRAIN_WARP_AT_ITR_NO: 20
WARP_LAYERS: ("module.roi_heads.res5.2.conv3.weight",)
NUM_FEATURES_PER_CLASS: 100
NUM_IMAGES_PER_CLASS: 10
BATCH_SIZE: 2
USE_FEATURE_STORE: True
IMAGE_STORE_LOC: '/40_image_store.pth'

DISTILL:
ENABLE: False
BACKBONE: True
RPN: False
ROI_HEADS: True
ONLY_FG_ROIS: False
LOSS_WEIGHT: 0.2

the result of AP50 of the base 40 classes is 30.4642, which made me confused.