title: Training model on AWS Deep Learning AMI instance - gets 'killed' with warnings
body: <p>I am trying to train inception ResNetV2 model on my own dataset on Amazon's Deep Learning AMI</p>
  
  <p>When I try to train on local machine the training starts as usual but when I try to train on aws instance it gets killed.</p>
  
  <p>First I tried to train with MXNET backend . It gave the following error :</p>
  
  <p><a href="https://i.stack.imgur.com/n5LBV.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/n5LBV.png" alt="enter image description here"></a></p>
  
  <p>Notice that it gets killed.</p>
  
  <p>So in</p>
  
  <pre><code>nano ~/.keras/keras.json
  </code></pre>
  
  <p>I tried to set image data format to channels_first :</p>
  
  <pre><code>{
      "image_data_format": "channels_first", 
      "backend": "mxnet"
  }
  </code></pre>
  
  <p>Then I got the error:</p>
  
  <pre><code>Traceback (most recent call last):
      File "train.py", line 17, in &lt;module&gt;
          model = applications.inception_resnet_v2.InceptionResNetV2(include_top=False, weights='imagenet', input_shape = (img_width, img_height, 3))
      File "/home/ubuntu/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/keras_applications/inception_resnet_v2.py", line 243, in InceptionResNetV2
  weights=weights)
      File "/home/ubuntu/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/keras_applications/imagenet_utils.py", line 296, in _obtain_input_shape
  '`input_shape=' + str(input_shape) + '`')
  ValueError: The input must have 3 channels; got `input_shape=(182, 182, 3)`
  </code></pre>
  
  <p>Then I tried to switch to tensorflow backend to see how it plays out because there might be some misunderstanding on my part on how this process works. But when I switched to tensorflow backend and started training I got the following error :</p>
  
  <p><a href="https://i.stack.imgur.com/tU6ix.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/tU6ix.png" alt="enter image description here"></a></p>
  
  <p>As you can see it gets killed again.
  I am not sure what to do next. Some help would be great.</p>
  
  <p>P.S I am sorry for the screenshots. You're going to have to zoom in a little to get a better view.</p>