ginet_resnet101_os8_ade20k_520x520_150k.yml

_base_: '../_base_/ade20k.yml'
batch_size: 4
iters: 150000

train_dataset:
  transforms:
    - type: ResizeStepScaling
      min_scale_factor: 0.5
      max_scale_factor: 2.0
      scale_step_size: 0.25
    - type: RandomPaddingCrop
      crop_size: [520, 520]
    - type: RandomHorizontalFlip
    - type: RandomDistort
      brightness_range: 0.4
      contrast_range: 0.4
      saturation_range: 0.4
    - type: Normalize

model:
  type: GINet
  backbone:
    type: ResNet101_vd
    output_stride: 8
    pretrained: https://bj.bcebos.com/paddleseg/dygraph/resnet101_vd_ssld.tar.gz
  backbone_indices: [0, 1, 2, 3]
  enable_auxiliary_loss: True
  jpu: True
  align_corners: True
  pretrained: null

lr_scheduler:
  type: PolynomialDecay
  learning_rate: 0.005
  end_lr: 0
  power: 0.9

loss:
  types:
    - type: CrossEntropyLoss
    - type: CrossEntropyLoss
  coef: [1, 0.4]