title: Why does it say I can't convert a symbolic tensor to a numpy array when I don't use any numpy operations?
body: <p>When running this code:</p>
  <pre class="lang-py prettyprint-override"><code>import tensorflow as tf
  import keras
  import numpy as np
  import tensorflow_hub as hub
  
  module_url = 'https://tfhub.dev/google/universal-sentence-encoder-qa/3'
  embed = hub.load(module_url)
  
  input_layer = keras.Input(shape=())
  embed_layer = hub.KerasLayer(embed, input_shape=(), dtype=tf.string, trainable=True, signature='response_encoder', signature_outputs_as_dict=True)(input=tf.constant(input_layer))
  outputs = keras.layers.Dense(18, activation='softmax')(embed_layer)
  
  model = keras.Model(inputs=input_layer, outputs=outputs)
  </code></pre>
  <p>I get this error message:</p>
  <pre class="lang-py prettyprint-override"><code>---------------------------------------------------------------------------
  NotImplementedError                       Traceback (most recent call last)
  &lt;ipython-input-19-28e3d937cdc2&gt; in &lt;module&gt;()
        3 # labels = keras.utils.to_categorical(answers_context_ds['ALL_QUESTIONS'][1], num_classes=num_classes)
        4 input_layer = keras.Input(shape=())
  ----&gt; 5 embed_layer = hub.KerasLayer(embed, input_shape=(), dtype=tf.string, trainable=True, signature='response_encoder', signature_outputs_as_dict=True)(input=tf.constant(input_layer))
        6 outputs = keras.layers.Dense(18, activation='softmax')(embed_layer)
        7 
  
  4 frames
  /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in constant(value, dtype, shape, name)
      262   &quot;&quot;&quot;
      263   return _constant_impl(value, dtype, shape, name, verify_shape=False,
  --&gt; 264                         allow_broadcast=True)
      265 
      266 
  
  /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in _constant_impl(value, dtype, shape, name, verify_shape, allow_broadcast)
      273       with trace.Trace(&quot;tf.constant&quot;):
      274         return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
  --&gt; 275     return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
      276 
      277   g = ops.get_default_graph()
  
  /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
      298 def _constant_eager_impl(ctx, value, dtype, shape, verify_shape):
      299   &quot;&quot;&quot;Implementation of eager constant.&quot;&quot;&quot;
  --&gt; 300   t = convert_to_eager_tensor(value, ctx, dtype)
      301   if shape is None:
      302     return t
  
  /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in convert_to_eager_tensor(value, ctx, dtype)
       96       dtype = dtypes.as_dtype(dtype).as_datatype_enum
       97   ctx.ensure_initialized()
  ---&gt; 98   return ops.EagerTensor(value, ctx.device_name, dtype)
       99 
      100 
  
  /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in __array__(self)
      846         &quot;Cannot convert a symbolic Tensor ({}) to a numpy array.&quot;
      847         &quot; This error may indicate that you're trying to pass a Tensor to&quot;
  --&gt; 848         &quot; a NumPy call, which is not supported&quot;.format(self.name))
      849 
      850   def __len__(self):
  
  NotImplementedError: Cannot convert a symbolic Tensor (input_4:0) to a numpy array. This error may indicate that you're trying to pass a Tensor to a NumPy call, which is not supported
  </code></pre>
  <p>Even though I don't include any numpy operations. The desired output is for the model to compile without any errors. Why is this happening and how can I fix it to make it compile correctly?</p>
  <p>Edit: The inputs being passed to the model is meant to be a list of strings if that wasn't clear or if that information is needed to answer the question.</p>