message: Add an example of tf.nn.weighted_cross_entropy_with_logits
diff: @@ -287,10 +287,22 @@ def weighted_cross_entropy_with_logits_v2(labels, logits, pos_weight,
  `logits` and `labels` must have the same type and shape.
  + >>> labels = tf.constant([1., 0.5, 0.])
  + >>> logits = tf.constant([1.5, -0.1, -10.])
  + >>> tf.nn.weighted_cross_entropy_with_logits(
  + ... labels=labels, logits=logits, pos_weight=tf.constant(1.5)).numpy()
  + array([3.0211994e-01, 8.8049585e-01, 4.5776367e-05], dtype=float32)
  + >>> tf.nn.weighted_cross_entropy_with_logits(
  + ... labels=labels, logits=logits, pos_weight=tf.constant(0.5)).numpy()
  + array([1.00706644e-01, 5.08297503e-01, 4.57763672e-05], dtype=float32)
  +
  Args:
  - labels: A `Tensor` of the same type and shape as `logits`.
  - logits: A `Tensor` of type `float32` or `float64`.
  - pos_weight: A coefficient to use on the positive examples.
  + labels: A `Tensor` of the same type and shape as `logits`, with values
  + between 0 and 1 inclusive.
  + logits: A `Tensor` of type `float32` or `float64`, any real numbers.
  + pos_weight: A coefficient to use on the positive examples, typically a
  + scalar but otherwise broadcastable to the shape of `logits`. Its value
  + should be non-negative.
  name: A name for the operation (optional).
  Returns:
  