# model settings model = dict( type='ImageClassifier', backbone=dict( type='ResNeSt', depth=269, num_stages=4, stem_channels=128, out_indices=(3, ), style='pytorch'), neck=dict(type='GlobalAveragePooling'), head=dict( type='LinearClsHead', num_classes=1000, in_channels=2048, loss=dict( type='LabelSmoothLoss', label_smooth_val=0.1, num_classes=1000, reduction='mean', loss_weight=1.0), topk=(1, 5), cal_acc=False)) train_cfg = dict(mixup=dict(alpha=0.2, num_classes=1000))