W = tf.Variable(tf.constant(0.0, shape=[vocab_size, embedding_dim]),
    trainable=False, name='W')
embedding_placeholder = tf.placeholder(tf.float32, [vocab_size, embedding_dim])
embedding_init = W.assign(embedding_placeholder)
Using a pre-trained word embedding (word2vec or Glove) in TensorFlow