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softmax_triplet_with_center.yml
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softmax_triplet_with_center.yml
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MODEL:
PRETRAIN_CHOICE: 'imagenet'
PRETRAIN_PATH: '/home/haochen/.cache/torch/hub/checkpoints/resnet50-19c8e357.pth'
METRIC_LOSS_TYPE: 'triplet_center'
IF_LABELSMOOTH: 'on'
IF_WITH_CENTER: 'yes'
N_EMBD: 256
N_HEAD: 2
N_LAYER: 4
EMBD_PDROP: 0.1
ATTN_PDROP: 0.1
RESID_PDROP: 0.1
AFN: 'gelu'
CLF_PDROP: 0.1
TOPK: 20
LANDMARK: 5
INPUT:
SIZE_TRAIN: [256, 128]
SIZE_TEST: [256, 128]
PROB: 0.5 # random horizontal flip
RE_PROB: 0.5 # random erasing
PADDING: 10
DATASETS:
NAMES: ('market1501')
DATALOADER:
SAMPLER: 'softmax_triplet'
NUM_INSTANCE: 4
NUM_WORKERS: 8
SOLVER:
OPTIMIZER_NAME: 'Adam'
MAX_EPOCHS: 120
NFORMER_MAX_EPOCHS: 20
BASE_LR: 0.00035
CLUSTER_MARGIN: 0.3
CENTER_LR: 0.5
CENTER_LOSS_WEIGHT: 0.0005
RANGE_K: 2
RANGE_MARGIN: 0.3
RANGE_ALPHA: 0
RANGE_BETA: 1
RANGE_LOSS_WEIGHT: 1
BIAS_LR_FACTOR: 1
WEIGHT_DECAY: 0.0005
WEIGHT_DECAY_BIAS: 0.0005
IMS_PER_BATCH: 64
STEPS: [40, 70]
GAMMA: 0.1
WARMUP_FACTOR: 0.01
WARMUP_ITERS: 10
WARMUP_METHOD: 'linear'
CHECKPOINT_PERIOD: 40
LOG_PERIOD: 20
EVAL_PERIOD: 40
TEST:
IMS_PER_BATCH: 128
RE_RANKING: 'no'
WEIGHT: "path"
NECK_FEAT: 'after'
FEAT_NORM: 'yes'
TEST_NFORMER: 'NO'
OUTPUT_DIR: "work_dirs"