>>>print(model.summary()) __________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to ================================================================================================== input_anchor (InputLayer) (None, 299, 299, 3) 0 __________________________________________________________________________________________________ input_pos (InputLayer) (None, 299, 299, 3) 0 __________________________________________________________________________________________________ input_neg (InputLayer) (None, 299, 299, 3) 0 __________________________________________________________________________________________________ resnet_model (Model) (None, 128) 23883008 input_anchor[0][0] input_pos[0][0] input_neg[0][0] __________________________________________________________________________________________________ pos_dist (Lambda) (None, 1) 0 resnet_model[1][0] resnet_model[2][0] __________________________________________________________________________________________________ neg_dist (Lambda) (None, 1) 0 resnet_model[1][0] resnet_model[3][0] __________________________________________________________________________________________________ stacked_dists (Lambda) (None, 2, 1) 0 pos_dist[0][0] neg_dist[0][0] ================================================================================================== Total params: 23,883,008 Trainable params: 295,296 Non-trainable params: 23,587,712 __________________________________________________________________________________________________ None
keras中summary()打印上一篇的网络函数
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转载自blog.csdn.net/qq_25964837/article/details/79745953
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