import tensorflow as tf

  Returns:
    loss: Loss tensor of type float.
  """
  with tf.name_scope('segment_loss'):
    # logits = tf.reshape(logits, (-1, num_classes))
    epsilon = tf.constant(value=1e-7)
    labels = tf.to_float(labels)
    # labels = tf.to_float(tf.reshape(labels, (-1, num_classes)))

    softmax = tf.nn.softmax(logits) + epsilon
