title: how to convert a KerasTensor to a Tensor (Tensorflow)?
body: <p>I need to convert a KerasTensor to a Tensor because when I try to use a contional (<code>tf.cond()</code>) it reports an error:</p>
  <pre><code>def custon_loss(self, input_tensor): # input type = &lt;class 'tensorflow.python.keras.engine.keras_tensor.KerasTensor'&gt;
      def loss(y_actual, y_predicted):
          mse = K.mean(K.sum(K.square(y_actual - y_predicted)))
          mse = tf.reshape(mse, [1, 1])
          y_actual = keras.layers.core.Reshape([1, 1])(y_actual)[0]
          ax_input = tf.reshape(input_tensor[0][-1:][0][:1], [1, 1])
  
          # convert here ax_input to Tensor
  
          greater_equal = tf.reshape(tf.math.logical_and(tf.math.greater_equal(ax_input, y_actual), tf.math.greater_equal(ax_input, y_predicted))[0], [1, 1])
          less_equal = tf.reshape(tf.math.logical_and(tf.math.less_equal(ax_input, y_actual), tf.math.less_equal(ax_input, y_predicted))[0], [1, 1])
          logical_or = tf.reshape(tf.math.logical_or(greater_equal, less_equal)[0], [1, 1])
          
          return tf.cond(logical_or, lambda: mse, lambda: tf.math.multiply(mse, 10))
      return loss
  </code></pre>
  <p>Error caused in <code>tf.cond</code>:</p>
  <pre><code>TypeError: Cannot convert a symbolic Keras input/output to a numpy array. This error may indicate that you're trying to pass a symbolic value to a NumPy call, which is not supported. Or, you may be trying to pass Keras symbolic inputs/outputs to a TF API that does not register dispatching, preventing Keras from automatically converting the API call to a lambda layer in the Functional Model.
  </code></pre>
  <p>I believe that converting the tensor will not make the error.</p>