message: Added statement for values closer to 1
diff: @@ -1683,10 +1683,11 @@ def cosine_similarity(y_true, y_pred, axis=-1):
  Note that it is a number between -1 and 1. 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.
  + similarity. The values closer to 1 indicate greater dissimilarity. 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.
  `loss = -sum(l2_norm(y_true) * l2_norm(y_pred))`
  