当尝试实现时,纸生成级联网络(Lipton等人,2015)将来自LSTM的隐藏状态输出与解码器输入进行无级级联,以馈入解码器级,但出现以下错误: >
“节点=层。_inbound_nodes[node_index] AttributeError:'NoneType'对象没有属性'_inbound_nodes'“
from keras.layers import Input, Embedding, LSTM, Dense
from keras.models import Model
import keras
import tensorflow as tf
encoder_input = Input(shape=(46, 21), dtype='float32', name='encoder_input')
# Encoder stage
_, h_s, c_s = LSTM(256,
return_sequences=True,
return_state=True,
dropout=0.0,
recurrent_dropout=0.0)(encoder_input)
encoder_states = [h_s, c_s]
decoder_input = Input(shape=(46, 21), name='decoder_input')
conc = True
if conc:
# Reshape tensor to dimensions -1, 46, 21
h_s_s = tf.reshape(h_s, (-1, 46, 21))
x = keras.layers.concatenate([h_s_s, decoder_input])
else:
x = decoder_input
# Decoder stage
decoder_lstm = LSTM(256, return_sequences=True, return_state=True,
dropout=0.0,
recurrent_dropout=0.0)
decoder_outputs, _, _ = decoder_lstm(x,
initial_state=encoder_states)
# FC layer
main_output = Dense(21, activation='sigmoid', name='main_output')(decoder_outputs)
model = Model(inputs=[encoder_input, decoder_input], outputs=[main_output])
我希望对象模型是a,但是在创建对象时错误是:
“节点=层。_inbound_nodes[node_index] AttributeError:'NoneType'对象没有属性'_inbound_nodes'“
答案 0 :(得分:0)
问题在这里:
php artisan scout:import "App\Models\YourModel
您不能直接在Keras张量中应用TF或后端操作,您需要将它们包装在Lambda层中,但是已经有一个用于重塑的层:
h_s_s = tf.reshape(h_s, (-1, 46, 21))
这将产生另一个错误(from keras.layers import Reshape
h_s_s = Reshape((46, 21))(h_s)
),并且您必须对其进行修复,因为重塑尺寸不适用于图层输出。只有OP知道正确的值。