def get_resnet_train(sym): return get_sym_train(sym) #data = mx.symbol.Variable(name="data") ## shared convolutional layers conv_fpn_feat, conv_fpn_feat2 = get_resnet_conv(data, sym) ret_group = [] for stride in config.RPN_FEAT_STRIDE: ret = get_out(conv_fpn_feat, 'face', stride, config.FACE_LANDMARK, lr_mult=1.0) ret_group += ret if config.HEAD_BOX: ret = get_out(conv_fpn_feat2, 'head', stride, False, lr_mult=1.0) ret_group += ret
def get_mnet_train(sym): return get_sym_train(sym)
def get_resnet_train(sym): return get_sym_train(sym)