global:
  namespace: kubeflow
  shared_fs: efs 
  shared_pvc: tensorpack-efs-gp-bursting 
  source_cidr: "0.0.0.0/0" # Public IP source CIDR
maskrcnn:
  name: mask-rcnn-tensorflow
  gpus: 16
  gpu_nodes: 2
  gpus_per_node: 8
  image:
  train_script: /mask-rcnn-tensorflow/MaskRCNN/train.py
  tp_16: 1
  batch_size_per_gpu: 4
  data_fs: efs
  data_dir: data
  working_dir:  /mask-rcnn-tensorflow
  images_per_epoch: 120000 
  lr_epoch_schedule: "[(16, 0.1), (20, 0.01), (24, None)]"
  eval_period_in_epochs: 1 
  data_train: "[\"train2017\"]"
  data_val: "(\"val2017\")" 
  mode_fpn: 'True'
  mode_mask: 'True'
  backbone_norm: FreezeBN
  backbone_weights: data/pretrained-models/ImageNet-R50-AlignPadding.npz
  image_pull_policy: Always 
  horovod_cycle_time: "0.5"
  horovod_fusion_threshold: "67108864"
  nccl_socket_ifname: ^lo,docker0
  if_exclude:  lo,docker0
  nccl_min_rings: 8
  nccl_debug: INFO
  extra_config: 'TRAIN.GRADIENT_CLIP=0.36'
  backoff_limit: 20