Keras中使用稀疏分类交叉熵时的类型错误

当我运行这段代码时，我得到以下错误

model=Sequential()
model.add(LSTM(output_dim=32,input_shape=(200,304),return_sequences=True,activation='sigmoid',inner_activation='hard_sigmoid'))
model.add(Dropout(0.5))
model.add(TimeDistributed(Dense(4)))
model.add(Activation('softmax'))
model.compile(loss='sparse_categorical_crossentropy',optimizer='adagrad',metrics=['accuracy'])  

错误是：

    C:\Users\vicky\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py in sparse_categorical_crossentropy(output, target, from_logits)
   1991     if len(output_shape) == 3:
   1992         # if our output includes timesteps we need to reshape
-> 1993         return tf.reshape(res, [-1, int(output_shape[-2])])
   1994     else:
   1995         return res

TypeError: __int__ returned non-int (type NoneType)