title: TF-Slim: (Unreasonable?) running out of memory
body: <p>I am trying to run one of the tutorials in TF SLIM, the one where you fine tune the flowers dataset using Inception-V3 (~104Mb). The GPU has about 2Gb of memory. When I have a batch size more than 8, I get an error because the GPU runs out of memory. In fact, it seems I get several messages, each looking like:</p>
  
  <pre><code>W tensorflow/core/common_runtime/bfc_allocator.cc:217] Ran out of memory trying to allocate 646.50MiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
  </code></pre>
  
  <p>and</p>
  
  <pre><code>W tensorflow/core/common_runtime/bfc_allocator.cc:274]     **************************************x*************************************************************
  W tensorflow/core/common_runtime/bfc_allocator.cc:275] Ran out of memory trying to allocate 168.8KiB.  See logs for memory state.
  </code></pre>
  
  <p>Now, it could very well be that my GPU has not big enough RAM. However, 2GB seems more than enough to load a ~100Mb model. Also, with Caffe I could fine-tune an Alexnet (~400Mb) with no problem. Besides, I also tried to allow for GPU growth (from what I understand using the system's RAM) with </p>
  
  <pre><code>session_config = tf.ConfigProto(allow_soft_placement=True)
  session_config.gpu_options.allow_growth = True
  session_config.gpu_options.allocator_type = 'BFC'"
  </code></pre>
  
  <p>but it doesn't seem to help.</p>
  
  <p>Do you know if </p>
  
  <p>a) I am doing something wrong
  b) the GPU is just not big enough
  c) TF Slim consumes by construction too much memory</p>
  
  <p>?</p>
  
  <p>Thanks,</p>