tf.contrib.losses.cosine_distance

tf.contrib.losses.cosine_distance(
    predictions,
    labels=None,
    axis=None,
    weights=1.0,
    scope=None,
    dim=None
)

Defined in tensorflow/contrib/losses/python/losses/loss_ops.py.

See the guide: Losses (contrib) > Loss operations for use in neural networks.

Adds a cosine-distance loss to the training procedure. (deprecated arguments) (deprecated)

THIS FUNCTION IS DEPRECATED. It will be removed after 2016-12-30. Instructions for updating: Use tf.losses.cosine_distance instead.

SOME ARGUMENTS ARE DEPRECATED. They will be removed in a future version. Instructions for updating: dim is deprecated, use axis instead

Note that the function assumes that predictions and labels are already unit-normalized.

Args:

  • predictions: An arbitrary matrix.
  • labels: A Tensor whose shape matches 'predictions'
  • axis: The dimension along which the cosine distance is computed.
  • weights: Coefficients for the loss a scalar, a tensor of shape [batch_size] or a tensor whose shape matches predictions.
  • scope: The scope for the operations performed in computing the loss.
  • dim: The old (deprecated) name for axis.

Returns:

A scalar Tensor representing the loss value.

Raises:

  • ValueError: If predictions shape doesn't match labels shape, or weights is None.