title: Initializing tensorflow Variable with an array larger than 2GB
body: <p>I am trying to initialize a tensorflow <code>Variable</code> with pre-trained <code>word2vec</code> embeddings.</p>
  
  <p>I have the following code:</p>
  
  <pre><code>import tensorflow as tf
  from gensim import models
  
  model = models.Word2Vec.load_word2vec_format('GoogleNews-vectors-negative300.bin', binary=True)
  X = model.syn0
  
  embeddings = tf.Variable(tf.random_uniform(X.shape, minval=-0.1, maxval=0.1), trainable=False)
  
  sess.run(tf.initialize_all_variables())
  
  sess.run(embeddings.assign(X))
  </code></pre>
  
  <p>And I am receiving the following error:</p>
  
  <pre><code>ValueError: Cannot create an Operation with a NodeDef larger than 2GB.
  </code></pre>
  
  <p>The array (<code>X</code>) I am trying to assign is of shape <code>(3000000, 300)</code> and its size is 3.6GB. </p>
  
  <p>I am getting the same error if I try <code>tf.convert_to_tensor(X)</code> as well.</p>
  
  <p>I know that it fails due to the fact that the array is larger than 2GB. However, I do not know how to assign an array larger than 2GB to a tensorflow <code>Variable</code></p>