title: Inception-ResNet-v2 model consists of how many layers?
body: <p>Inception-ResNet-v2 model consists of how many layers? I have counted them to be 96 but I am not sure. Kindly confirm me</p>
  
  <p><a href="https://pic2.zhimg.com/v2-04824ca7ee62de1a91a2989f324b61ec_r.jpg" rel="nofollow noreferrer">https://pic2.zhimg.com/v2-04824ca7ee62de1a91a2989f324b61ec_r.jpg</a></p>
  
  <p>Also my training and testing data consists of 600 and 62 images respectively. I am using three models: ResNet-152, Inception-ResNet and DenseNet-161 and they have following number of parameters:</p>
  
  <p>ResNet-152:
  Total params: 58,450,754
  Trainable params: 58,299,330
  Non-trainable params: 151,424</p>
  
  <p>DenseNet-161:
  Total params: 26,696,354
  Trainable params: 26,476,418 
  Non-trainable params: 219,936</p>
  
  <p>Inception-ResNet:
  Total params: 54,339,810
  Trainable params: 54,279,266
  Non-trainable params: 60,544</p>
  
  <p>Is the data too scarce for the models? Also ResNet model validation/testing curve is the most smooth, then is DenseNet's curve and the Inception-ResNet model is the most bumpy. Why is it so?</p>