我想获得resnet密集层，但是输出中有些错误。我尝试使用layer [-1]，它将被打印，但是layer [-4]错误。我是深度学习的新手。非常感谢。
weight_path = '/triplet_loss_resnet50.h5'
model = load_model(weight_path, compile=False)
model.summary()
# compile model
model.compile(optimizer='rmsprop',
loss=triplet_loss,
metrics=['accuracy'])
inp = model.input # input placeholder
outputs = model.layers[-4].output
输出消息
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_anchor (InputLayer) (None, 224, 224, 3) 0
__________________________________________________________________________________________________
input_pos (InputLayer) (None, 224, 224, 3) 0
__________________________________________________________________________________________________
input_neg (InputLayer) (None, 224, 224, 3) 0
__________________________________________________________________________________________________
resnet_model (Model) (None, 1000) 25636712 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: 25,636,712
Trainable params: 2,049,000
Non-trainable params: 23,587,712
__________________________________________________________________________________________________
Traceback (most recent call last):
AttributeError: Layer resnet_model has multiple inbound nodes, hence the notion of "layer output" is ill-defined. Use `get_output_at(node_index)` instead.