我想在 LSTM 自動編碼器之上添加一個乘法層。乘法層應該將張量乘以一個常數(shù)值。我編寫了以下代碼，無需乘法層即可工作。有誰知道如何調(diào)整并使其工作？import kerasfrom keras import backend as Kfrom keras.models import Sequential, Modelfrom keras.layers import Input, LSTM, RepeatVector, TimeDistributedfrom keras.layers.core import Flatten, Dense, Dropout, Lambdafrom keras.optimizers import SGD, RMSprop, Adamfrom keras import objectivesfrom keras.engine.topology import Layerimport numpy as npclass LayerKMultiply(Layer):    def __init__(self, output_dim, **kwargs):        self.output_dim = output_dim        self.k = Null        super(LayerKMultiply, self).__init__(**kwargs)    def build(self, input_shape):        # Create a trainable weight variable for this layer.        self.k = self.add_weight(            name='k',            shape=(),            initializer='ones',            dtype='float32',            trainable=True,        )        super(LayerKMultiply, self).build(input_shape)  # Be sure to call this at the end    def call(self, x):        #return K.tf.multiply(self.k, x)        return self.k * x    def compute_output_shape(self, input_shape):        return (input_shape[0], self.output_dim)    timesteps, input_dim, latent_dim = 10, 3, 32inputs = Input(shape=(timesteps, input_dim))encoded = LSTM(latent_dim, return_sequences=False, activation='linear')(inputs)decoded = RepeatVector(timesteps)(encoded)decoded = LSTM(input_dim, return_sequences=True, activation='linear')(decoded)decoded = TimeDistributed(Dense(input_dim, activation='linear'))(decoded)#decoded = LayerKMultiply(k = 20)(decoded)sequence_autoencoder = Model(inputs, decoded)encoder = Model(inputs, encoded)autoencoder = Model(inputs, decoded)autoencoder.compile(optimizer='adam', loss='mse')    X = np.array([[[1,2,3,4,5,6,7,8,9,10],[1,2,3,4,5,6,7,8,9,10],[1,2,3,4,5,6,7,8,9,10]]])X = X.reshape(1,10,3)p = autoencoder.predict(x=X, batch_size=1)print(p)