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: maskrcnn
  gpus: 16
  gpu_nodes: 2
  gpus_per_node: 8
  image:
  train_script: /tensorpack/examples/FasterRCNN/train.py
  data_fs: efs
  data_dir: data
  steps_per_epoch: 7500  # Must be equal to 120000/gpus 
  lr_schedule: "[240000,320000,360000]"
  eval_period_in_epochs: 1
  data_train: "[\"coco_train2017\"]"
  data_val: "(\"coco_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.CHECKPOINT_PERIOD=2'
  backoff_limit: 20