title: Memory Estimation for Convolution Neural Network in Tensorflow
body: <h3>Hello Everyone,</h3>
  <p>I am working on a Image classification problem using tensorflow and Convolution Neural Network.
  My model is having following layers.</p>
  <ul>
  <li>Input image of size 2456x2058</li>
  <li>3 convolution Layer {Con1-shape(10,10,1,32); Con2-shape(5,5,32,64); Con3-shape(5,5,64,64)}</li>
  <li>3 max pool 2x2 layer</li>
  <li>1 fully connected layer.<BR/></li>
  </ul>
  <p>I have tried using the NVIDIA-SMI tool but it shows me the GPU memory consumption as the model runs. <br/>
  I would like to know if there is any method or a way to find the estimate of memory before running the model on GPU. So that I can design models with the consideration of available memory.<br/>
  I have tried using this <a href="https://telecombcn-dl.github.io/2017-dlcv/slides/D2L1-memory.pdf" rel="nofollow noreferrer">method for estimation</a> but my calculated memory and observed memory utilisation are no where near to each other.<br/></p>
  <h3>Thank you all for your time.</h3>