<p>I'm testing Seldon Core and I have a sample model up and running with only <code>predict</code> function in my serving model <code>MyModel(object)</code>. 
Now, I added <code>transform_input</code> function to preprocess input data before sending the input to the class. Again I deployed the model and it seemed working perfectly but I found that <code>transform_input</code> is not working or it's not used.
I have found the <a href="https://docs.seldon.io/projects/seldon-core/en/latest/python/python_component.html" rel="nofollow noreferrer">doc</a> and <a href="https://github.com/SeldonIO/seldon-core/blob/master/examples/transformers/mean_transformer/MeanTransformer.py" rel="nofollow noreferrer">example</a> but it only shows to add the function <code>transform_input</code>. Am I missing something? </p>

<p>Even if your model already provides a <code>transform_input</code> function, you still need to add it as a <code>TRANSFORMER</code> node in your inference graph. For your particular case, you would need to define a graph like the following one:</p>

<pre class="lang-yaml prettyprint-override"><code>  graph:
    name: my-input-transformer
    type: TRANSFORMER
    children:
      - name: my-model
        type: MODEL
</code></pre>

<p>Both nodes (<code>my-model</code> and <code>my-input-transformer</code>) would point to the same Docker image.</p>
