contrib.losses.compute_weighted_loss

tf.contrib.losses.compute_weighted_loss

tf.contrib.losses.compute_weighted_loss

compute_weighted_loss(
    losses,
    weights=1.0,
    scope=None
)

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

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

Computes the weighted loss. (deprecated)

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

Args:

• losses: A tensor of size [batch_size, d1, ... dN].
• weights: A tensor of size [1] or [batch_size, d1, ... dK] where K < N.
• scope: the scope for the operations performed in computing the loss.

Returns:

A scalar Tensor that returns the weighted loss.

Raises:

• ValueError: If weights is None or the shape is not compatible with losses, or if the number of dimensions (rank) of either losses or weights is missing.