system:
  mode: 0 # 0 for graph mode, 1 for pynative mode in MindSpore
  distribute: True
  amp_level: 'O0'
  seed: 42
  log_interval: 100
  val_while_train: False
  drop_overflow_update: False

common:
  character_dict_path: &character_dict_path
  num_classes: &num_classes 37
  max_text_len: &max_text_len 25
  infer_mode: &infer_mode False
  use_space_char: &use_space_char False
  batch_size: &batch_size 96

model:
  type: rec
  pretrained : "./tmp_rec/pretrain.ckpt"
  transform: null
  backbone:
    name: abinet_backbone
    pretrained: False
    batchsize: *batch_size
  head:
    name: ABINetHead
    batchsize: *batch_size

postprocess:
  name: ABINetLabelDecode

metric:
  name: RecMetric
  main_indicator: acc
  character_dict_path: *character_dict_path
  ignore_space: True
  print_flag: False
  filter_ood: False

loss:
  name: ABINetLoss


scheduler:
  scheduler: step_decay
  decay_rate: 0.1
  decay_epochs: 6
  warmup_epochs: 0
  lr: 0.0001
  num_epochs : 10


optimizer:
  opt: adam


train:
  clip_grad: True
  clip_norm: 20.0
  ckpt_save_dir: './tmp_rec'
  dataset_sink_mode: False
  dataset:
    type: LMDBDataset
    dataset_root: path/to/data_lmdb_release/
    data_dir: train/
    # label_files: # not required when using LMDBDataset
    sample_ratio: 1.0
    shuffle: True
    transform_pipeline:
      - ABINetTransforms:
      - ABINetRecAug:
      - NormalizeImage:
          is_hwc: False
          mean: [0.485, 0.456, 0.406]
          std: [0.485, 0.456, 0.406]
    # #  the order of the dataloader list, matching the network input and the input labels for the loss function, and optional data for debug/visaulize
    output_columns: ['image','label','length','label_for_mask'] #'img_path']

  loader:
      shuffle: True # TODO: tbc
      batch_size: *batch_size
      drop_remainder: True
      max_rowsize: 128
      num_workers: 20

eval:
  ckpt_load_path: ./tmp_rec/best.ckpt
  dataset_sink_mode: False
  dataset:
    type: LMDBDataset
    dataset_root: path/to/data_lmdb_release/
    data_dir: evaluation/
    # label_files: # not required when using LMDBDataset
    sample_ratio: 1.0
    shuffle: False
    transform_pipeline:
      - ABINetEvalTransforms:
      - ABINetEval:
    #  the order of the dataloader list, matching the network input and the input labels for the loss function, and optional data for debug/visaulize
    output_columns: ['image','label','length','label_for_mask']  # TODO return text string padding w/ fixed length, and a scaler to indicate the length
    net_input_column_index: [0] # input indices for network forward func in output_columns
    label_column_index: [1, 2] # input indices marked as label

  loader:
      shuffle: False # TODO: tbc
      batch_size: *batch_size
      drop_remainder: False
      max_rowsize: 128
      num_workers: 8