./Inference/README.md use the same checkpoint for R50 and R50IBN ?

[taqta]

it seems that creating_embeddings.py use R50 model, and use "logs/market1501/256_resnet50/train_ctl_model/version_0/checkpoints/epoch=119.ckpt" as ckpt in README.md

python inference/create_embeddings.py \
--config_file="configs/256_resnet50.yml" \
GPU_IDS [0] \
DATASETS.ROOT_DIR '/data/my-image-dataset/' \
TEST.IMS_PER_BATCH 128 \
OUTPUT_DIR 'output-dir' \
TEST.ONLY_TEST True \
MODEL.PRETRAIN_PATH "logs/market1501/256_resnet50/train_ctl_model/version_0/checkpoints/epoch=119.ckpt"

and get_similar.py use R50_IBN as model, and use "logs/market1501/256_resnet50/train_ctl_model/version_0/checkpoints/epoch=119.ckpt" as ckpt in README.md

python inference/get_similar.py \
--config_file="configs/320_resnet50_ibn_a.yml" \
--gallery_data='output-dir' \
--normalize_features \
--topk=100 \
GPU_IDS [0] \
DATASETS.ROOT_DIR '/data/query-images/'  \
TEST.IMS_PER_BATCH 128 \
OUTPUT_DIR 'output-dir' \
TEST.ONLY_TEST True \
MODEL.PRETRAIN_PATH "logs/market1501/256_resnet50/train_ctl_model/version_0/checkpoints/epoch=119.ckpt" \
SOLVER.DISTANCE_FUNC 'cosine'

I want to ask that why the same checkpoint can be used in R50 and R50_IBN, and does it mean that R50_IBN use the default mean and var if I run the prompt as README.md.