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segmenter_small_512x512_160k_ade20k_bs_16.yaml
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segmenter_small_512x512_160k_ade20k_bs_16.yaml
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DATA:
BATCH_SIZE: 2 # per GPU [total bs is set to 8 or 16]
BATCH_SIZE_VAL: 1 # per GPU
DATASET: 'ADE20K' # dataset name
DATA_PATH: '/home/ssd3/wutianyi/datasets/ADEChallengeData2016'
CROP_SIZE: (512,512) # input_size (training)
NUM_CLASSES: 150
MODEL:
NAME: 'Segmenter'
ENCODER:
TYPE: 'ViT'
OUT_INDICES: [11]
PRETRAINED: None
DECODER_TYPE: 'MaskTransformer'
SEGMENTER:
NUM_LAYERS: 2
NUM_CLASSES: 150
TRANS:
PATCH_SIZE: 16
HIDDEN_SIZE: 384 # 192(tiny), 384(small) 768(Base), 1024(Large), 1280(Huge)
MLP_RATIO: 4 # same as mlp_ratio = 4.0
NUM_HEADS: 6 # 3(tiny), 6(small), 12(Base), 16(Large), 16(Huge)
NUM_LAYERS: 12 # 12(tiny), 12(small), 12(Base), 24(Large), 32(Huge)
QKV_BIAS: True
KEEP_CLS_TOKEN: True
TRAIN:
BASE_LR: 0.001
END_LR: 1e-4
DECODER_LR_COEF: 10.0
ITERS: 160000
POWER: 0.9
DECAY_STEPS: 160000
LR_SCHEDULER:
NAME: 'PolynomialDecay'
OPTIMIZER:
WEIGHT_DECAY: 0.0
GRAD_CLIP: 1.0
NAME: 'SGD'
MOMENTUM: 0.9
VAL:
MULTI_SCALES_VAL: False
SCALE_RATIOS: [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
IMAGE_BASE_SIZE: 512
CROP_SIZE: [512, 512]
STRIDE_SIZE: [512, 512]
MEAN: [127.5, 127.5, 127.5]
STD: [127.5, 127.5, 127.5]
SAVE_DIR: "./output/segmenter_small_512x512_160k_ade20k_bs_16"