message: Mentioned tf.keras.losses.cosine_similarity() as a real number
diff: @@ -1681,10 +1681,10 @@ def poisson(y_true, y_pred):
  def cosine_similarity(y_true, y_pred, axis=-1):
  """Computes the cosine similarity between labels and predictions.
  - Note that it is a negative quantity between -1 and 0, where 0 indicates
  - orthogonality and values closer to -1 indicate greater similarity. This makes
  - it usable as a loss function in a setting where you try to maximize the
  - proximity between predictions and targets. If either `y_true` or `y_pred`
  + Note that it is a real number. When it is a negative number between -1 and 0, 0
  + indicates orthogonality and values closer to -1 indicate greater similarity.
  + This makes it usable as a loss function in a setting where you try to maximize
  + the proximity between predictions and targets. If either `y_true` or `y_pred`
  is a zero vector, cosine similarity will be 0 regardless of the proximity
  between predictions and targets.
  