Keras断言错误

我使用Keras函数API来实现一个简单的多输入多输出网络。但是我遇到了一些错误，我不知道如何解决它。 代码如下：

import numpy as np
from keras.layers import Dense, Activation, Input, merge, Lambda
from keras.models import Model
from keras.optimizers import SGD

def get_half_1(nparray):
    return nparray[:,:5]
def get_half_2(nparray):
    return nparray[:,5:]

train_x = np.random.uniform(0.0,1.0,size=(50,12))
train_y = np.random.uniform(0.0,1.0,(50,8))

x_row, x_col = train_x.shape
y_row, y_col = train_y.shape

x_input = Input(shape=(x_row, ), name='x_input')
y_input = Input(shape=(y_row, ), name='y_input')

x_hidden = Dense(5,activation='sigmoid')(x_input)
y_hidden = Dense(5,activation='sigmoid')(y_input)

#  merge two layers
com_x = merge([x_hidden, y_hidden],mode='concat')

feature_layer = Dense(10, activation='sigmoid')(com_x)

# decoding
com_x_transpose = Dense(10,activation='sigmoid')(feature_layer)

x_hidden_transpose = Lambda(get_half_1,output_shape=(50,5)) (com_x_transpose)
y_hidden_transpose = Lambda(get_half_2,output_shape=(50,5))(com_x_transpose)

x_recon_error = Dense(12,activation='sigmoid')(x_hidden_transpose)
y_recon_error = Dense(8,activation='sigmoid')(y_hidden_transpose)
#
model = Model(input=[x_input, y_input],output=[x_recon_error, y_recon_error])


model.compile(optimizer='rmsprop',loss='mean_square_error')

model.fit(train_x, train_y,nb_epoch=50,batch_size=50)  

我使用python3运行此代码，得到以下错误：

Traceback (most recent call last):
  File "splittest.py", line 35, in <module>
    x_recon_error = Dense(12,activation='sigmoid')(x_hidden_transpose)
  File "/Users/lw/Library/Python/3.5/lib/python/site- packages/keras/engine/topology.py", line 458, in __call__
    self.build(input_shapes[0])
  File "/Users/lw/Library/Python/3.5/lib/python/site-packages/keras/layers/core.py", line 583, in build
    assert len(input_shape) == 2
AssertionError

回溯（最近一次呼叫最后一次）：
文件“splittest.py”，第35行，在
x_侦察错误=密集（12，激活='sigmoid'）（x_隐藏转置）
文件“/Users/lw/Library/Python/3.5/lib/Python/site-packages/keras/engine/topology.py”，第458行，在__
自我构建（输入形状[0]）
文件“/Users/lw/Library/Python/3.5/lib/Python/site-packages/keras/layers/core.py”，第583行，内部版本
断言len（输入_形）==2
断言错误

只需更改

x_input = Input(shape=(x_row, ), name='x_input')
y_input = Input(shape=(y_row, ), name='y_input')

到

---

这是一个非常简单的例子。关于可变维度，我会犯一些错误吗？

x_input = Input(shape=train_x.shape, name='x_input')
y_input = Input(shape=train_y.shape, name='y_input')