model:
    arch: CMP
    total_iter: 42000
    lr_steps: [24000, 36000]
    lr_mults: [0.1, 0.1]
    lr: 0.1
    optim: SGD
    warmup_lr: []
    warmup_steps: []
    module:
        arch: CMP
        image_encoder: resnet50
        sparse_encoder: shallownet8x
        flow_decoder: MotionDecoderSkipLayer
        skip_layer: True
        img_enc_dim: 256
        sparse_enc_dim: 16
        output_dim: 198
        decoder_combo: [1,2,4]
        pretrained_image_encoder: False
        flow_criterion: "DiscreteLoss"
        nbins: 99
        fmax: 50
data:
    workers: 2
    batch_size: 8
    batch_size_test: 1
    data_mean: [123.675, 116.28, 103.53] # RGB
    data_div: [58.395, 57.12, 57.375]
    short_size: 416
    crop_size: [384, 384]
    sample_strategy: ['grid', 'watershed']
    sample_bg_ratio: 5.74e-5
    nms_ks: 41
    max_num_guide: -1

    flow_file_type: "jpg"
    image_flow_aug:
        flip: False
    flow_aug:
        reverse: False
        scale: False
        rotate: False
    train_source:
        - data/VIP/lists/train.txt
        - data/MPII/lists/train.txt
    val_source:
        - data/VIP/lists/randval.txt
    memcached: False
trainer:
    initial_val: True
    print_freq: 100
    val_freq: 5000
    save_freq: 5000
    val_iter: -1
    val_disp_start_iter: 0
    val_disp_end_iter: 16
    loss_record: ['loss_flow']
    tensorboard: True