W3cubDocs

/TensorFlow Python

tf.contrib.losses.compute_weighted_loss

tf.contrib.losses.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.

© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/contrib/losses/compute_weighted_loss