Keras replacing input layer : <p>The code that I have (that I can't change) uses the Resnet with <code>my_input_tensor</code> as the input_tensor.</p>

<pre><code>model1 = keras.applications.resnet50.ResNet50(input_tensor=my_input_tensor, weights='imagenet')
</code></pre>

<p>Investigating the <a href="https://github.com/keras-team/keras/blob/master/keras/applications/resnet50.py" rel="noreferrer">source code</a>, ResNet50 function creates a new keras Input Layer with <code>my_input_tensor</code> and then create the rest of the model. This is the behavior that I want to copy with my own model. I load my model from h5 file.</p>

<pre><code>model2 = keras.models.load_model('my_model.h5')
</code></pre>

<p>Since this model already has an Input Layer, I want to replace it with a new Input Layer defined with <code>my_input_tensor</code>.</p>

<p>How can I replace an input layer?</p>
