我的音频文件，其中一个三维数据集X.shape是(329,20,85)。我想运行一个简单的准系统模型，所以请不要挑剔并只解决手头的问题。这是代码：
model = tf.keras.models.Sequential()
model.add(tf.keras.layers.LSTM(32, return_sequences=True, stateful=False, input_shape = (20,85,1)))
model.add(tf.keras.layers.LSTM(20))
model.add(tf.keras.layers.Dense(nb_classes, activation='softmax'))
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=["accuracy"])
model.summary()
print("Train...")
model.fit(X_train, y_train, batch_size=batch_size, nb_epoch=50, validation_data=(X_test, y_test))
但是后来我遇到了标题中提到的错误：
ValueError: Shapes (None, 1) and (None, 3) are incompatible
这里是 model.summary()
Model: "sequential_13"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
lstm_21 (LSTM) (None, 20, 32) 15104
_________________________________________________________________
lstm_22 (LSTM) (None, 20) 4240
_________________________________________________________________
dense_8 (Dense) (None, 3) 63
=================================================================
Total params: 19,407
Trainable params: 19,407
Non-trainable params: 0
_________________________________________________________________
Train... …