title: tensorflow.python.framework.errors_impl.ResourceExhaustedError
body: <p>I'm using an object detection module for classifying images. My specs are as follows:</p>
  <ul>
  <li>OS: Ubuntu 18.04 LTS</li>
  <li>Python: 3.6.7</li>
  <li>VirtualEnv: Version: 16.4.3</li>
  <li>Pip3 version inside virtualenv: 19.0.3</li>
  <li>TensorFlow Version: 1.13.1</li>
  <li>Protoc Version: 3.0.0-9</li>
  </ul>
  <p>I'm working on Windows virtualenv and google-colab. This is the error message I get:</p>
  <pre><code>python3 legacy/train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/ssd_mobilenet_v1_pets.config
  
  
  INFO:tensorflow:global step 1: loss = 18.5013 (48.934 sec/step)
  INFO:tensorflow:Finished training! Saving model to disk.
  /home/priyank/venv/lib/python3.6/site-packages/tensorflow/python/summary/writer/writer.py:386: UserWarning: Attempting to use a closed FileWriter. The operation will be a noop unless the FileWriter is explicitly reopened.
    warnings.warn(&quot;Attempting to use a closed FileWriter. &quot;
  Traceback (most recent call last):
    File &quot;legacy/train.py&quot;, line 184, in &lt;module&gt;
      tf.app.run()
    File &quot;/home/priyank/venv/lib/python3.6/site-packages/tensorflow/python/platform/app.py&quot;, line 125, in run
      _sys.exit(main(argv))
    File &quot;/home/priyank/venv/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py&quot;, line 324, in new_func
      return func(*args, **kwargs)
    File &quot;legacy/train.py&quot;, line 180, in main
      graph_hook_fn=graph_rewriter_fn)
    File &quot;/home/priyank/venv/models-master/research/object_detection/legacy/trainer.py&quot;, line 416, in train
      saver=saver)
    File &quot;/home/priyank/venv/lib/python3.6/site-packages/tensorflow/contrib/slim/python/slim/learning.py&quot;, line 785, in train
      ignore_live_threads=ignore_live_threads)
    File &quot;/home/priyank/venv/lib/python3.6/site-packages/tensorflow/python/training/supervisor.py&quot;, line 832, in stop
      ignore_live_threads=ignore_live_threads)
    File &quot;/home/priyank/venv/lib/python3.6/site-packages/tensorflow/python/training/coordinator.py&quot;, line 389, in join
      six.reraise(*self._exc_info_to_raise)
    File &quot;/home/priyank/venv/lib/python3.6/site-packages/six.py&quot;, line 693, in reraise
      raise value
    File &quot;/home/priyank/venv/lib/python3.6/site-packages/tensorflow/python/training/queue_runner_impl.py&quot;, line 257, in _run
      enqueue_callable()
    File &quot;/home/priyank/venv/lib/python3.6/site-packages/tensorflow/python/client/session.py&quot;, line 1257, in _single_operation_run
      self._call_tf_sessionrun(None, {}, [], target_list, None)
    File &quot;/home/priyank/venv/lib/python3.6/site-packages/tensorflow/python/client/session.py&quot;, line 1407, in _call_tf_sessionrun
      run_metadata)
  &lt;b&gt;tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[15,1,1755,2777,3] and type float on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu
       [[{{node batch}}]]
  Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.&lt;/b&gt;
  </code></pre>