title: Keras resnet50 get_layer() 'no such layer' error
body: <p>So I'm loading the keras Resnet50 model using the below code:</p>
  <pre><code>backbone = resnet50.ResNet50(include_top=False, weights=None, input_tensor=None, pooling=None, classes=1000)
  </code></pre>
  <p>I need to get a batch normalization layer which is named '<strong>bn5c_branch2c</strong>' in the resnet50 code on <a href="https://github.com/keras-team/keras-applications/blob/master/keras_applications/resnet50.py" rel="nofollow noreferrer">github(line 75)</a>.</p>
  <p>Running <code>backbone.get_layer('bn5c_branch2c')</code> gives me a <strong>ValueError: No such layer: bn5c_branch2c.</strong></p>
  <p>Printing the names of the layers using:</p>
  <pre><code>for layer in backbone.layers:
       print(layer.name)
  </code></pre>
  <p>I found that indeed none of the layers go by this name, instead they're named something like '<strong>conv5_block1_3_bn</strong>'. However, in the code of resnet50 the name is clearly fed as '<strong>bn5c_branch2c</strong>'. I'm unable to understand how this is happening and how can I extract a layer by the name it is assigned in the code. Any help would be great. Thanks.</p>
  <p>tensorflow - 2.3.1
  keras - 2.4.3
  OS - Ubuntu 20.04.1 LTS</p>