message: Updated losses.py to remove pylint error
diff: @@ -1681,13 +1681,14 @@ 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 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. 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.
  + 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. 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))`
  