title: TypeError: 'Tensor' object is not callable | Keras-Bert
body: <p>I'm building this model:</p>
  
  <pre><code>inputs = model.inputs[:2] 
  layer_output = model.get_layer('Encoder-12-FeedForward-Norm').output  
  input_layer= keras.layers.Input(shape=(SEQ_LEN,768))(layer_output)
  conv_layer= keras.layers.Conv1D(100, kernel_size=3, activation='relu', data_format='channels_first')(input_layer)   
  maxpool_layer = keras.layers.MaxPooling1D(pool_size=4)(conv_layer)
  flat_layer= keras.layers.Flatten()(maxpool_layer)
  outputs = keras.layers.Dense(units=3, activation='softmax')(flat_layer)
  model = keras.models.Model(inputs, outputs)
  model.compile(RAdam(learning_rate =LR),loss='sparse_categorical_crossentropy',metrics=['sparse_categorical_accuracy'])
  </code></pre>
  
  <p>and I keep getting this error <code>TypeError: 'Tensor' object is not callable</code> I know <code>layer_output</code> is a tensor and not a layer and Keras works with layers. But I'm finding it difficult to figure out the right thing to do. I have previously build a biLSTM model with similar inputs and it works fine. Can someone point me to something that will help me understand the issue better? I have tried passing the <code>input_layer</code> to the <code>conv_layer</code> but I get this error <code>TypeError: Layer conv1d_1 does not support masking, but was passed an input_mask: Tensor("Encoder-12-FeedForward-Add/All:0", shape=(?, 35), dtype=bool)</code></p>