title: How to feed multiple inputs to tf.keras.Model.predict?
body: <p>Given this simple tensorflow toy model</p>
  <pre><code>import tensorflow as tf
  inputs = {
      &quot;a&quot;:tf.keras.Input(shape=(), name=&quot;input_a&quot;),
      &quot;b&quot;:tf.keras.Input(shape=(), name=&quot;input_b&quot;)
  }
  outputs = tf.keras.layers.Add()([inputs[&quot;a&quot;], inputs[&quot;b&quot;]])
  model = tf.keras.Model(inputs=inputs, outputs=outputs)
  </code></pre>
  <p>I can get its output by invoking it with inputs as defined, so the following:</p>
  <pre><code>model({&quot;a&quot;:2,&quot;b&quot;:3})
  </code></pre>
  <p>Gives the output:</p>
  <pre><code>&lt;tf.Tensor: shape=(), dtype=float32, numpy=5.0&gt;
  </code></pre>
  <p>But invoking the predict function:</p>
  <pre><code>model.predict({&quot;a&quot;:2,&quot;b&quot;:3})
  </code></pre>
  <p>Gives the following error:</p>
  <pre><code>ValueError: Failed to find data adapter that can handle input: (&lt;class 'dict'&gt; containing {&quot;&lt;class 'str'&gt;&quot;} keys and {&quot;&lt;class 'int'&gt;&quot;} values), &lt;class 'NoneType'&gt;
  </code></pre>
  <p>So how do I correctly invoke the predict function when my model has more than a single input as in this case?</p>