我建立了一个cnn模型，尺寸方面遇到了麻烦。

src = Input(shape=(196,41,3))

conv11 = Conv2D(32,kernel_size=4,activation='relu')(src)

pool11 = MaxPooling2D(pool_size=(2,2))(conv11)

conv12 = Conv2D(16,activation='relu')(pool11)

drop = Dropout(0.3)

pool12 = MaxPooling2D(pool_size=(2,2))(conv12)

flat1 = flatten()(pool12)

# second input model
trgt = Input(shape=(196,3))
conv21 = Conv2D(32,activation='relu')(trgt)

pool21 = MaxPooling2D(pool_size=(2,2))(conv21)

conv22 = Conv2D(16,activation='relu')(pool21)

pool22 = MaxPooling2D(pool_size=(2,2))(conv22)

flat2 = flatten()(pool22)
# merge input models
merge = keras.layers.concatenate([flat1,flat2])

# interpretation model
hidden1 = Dense(64,activation='relu')(merge)
output = Dense(196,activation='relu')(hidden1)

arch = Model(inputs=[src,trgt],outputs=output)

我明白了

检查目标时出错：预期density_35具有2维，但数组的形状为（70，41，196，3）