message: calling array_ops instead of erroneus tf
diff: @@ -334,7 +334,7 @@ def sampled_sparse_softmax_loss(weights,
  # There is only one true label. _compute_sampled_logits puts the true logit
  # at index 0.
  - labels = tf.zeros([array_ops.shape(logits)[0], 1], dtype=dtypes.int64)
  + labels = array_ops.zeros([array_ops.shape(logits)[0], 1], dtype=dtypes.int64)
  sampled_losses = nn_ops.sparse_softmax_cross_entropy_with_logits(
  labels=array_ops.squeeze(labels), logits=logits)
  