training_the_pretrained_model.py

with tf.Session(graph=graph) as session:
  init.run()
  average_loss = 0
  for step in range(10001):
    batch_inputs, batch_labels = generate_batch(batch_size, num_skips, skip_window)
    feed_dict = {train_inputs: batch_inputs, train_labels: batch_labels}
    _, loss_val, normalized_embeddings_np = session.run([optimizer, loss, normalized_embeddings], feed_dict=feed_dict)
    average_loss += loss_val
  final_embeddings = normalized_embeddings.eval()