title: What's the equivalent of initializing a tf.Session with tf.ConfigProto in TensorFlow 2?
body: <p>There are two ways I know of for controlling which GPUs a <code>tf.Session</code> will take over.  One is the environment variable <code>CUDA_VISIBLE_DEVICES</code>, the other is initializing a <code>tf.Session</code> with an explicit <code>tf.ConfigProto</code> and setting <code>config.gpu_options.visible_device_list</code>.</p>
  
  <p>When using <code>nccl</code>, the environment variable route doesn't work, so <code>tf.ConfigProto</code> is the only way.  However, my understanding is that in Tensorflow 2.0 <code>tf.Session</code> construction is not explicit.  Is there an equivalent of the <code>ConfigProto.gpu_options.visible_device_list</code> route?</p>