contrib.losses.cosine_distance
tf.contrib.losses.cosine_distance
tf.contrib.losses.cosine_distance
cosine_distance( predictions, labels=None, dim=None, 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.
Adds a cosine-distance loss to the training procedure. (deprecated)
THIS FUNCTION IS DEPRECATED. It will be removed after 2016-12-30. Instructions for updating: Use tf.losses.cosine_distance instead.
Note that the function assumes that predictions
and labels
are already unit-normalized.
Args:
-
predictions
: An arbitrary matrix. -
labels
: ATensor
whose shape matches 'predictions' -
dim
: 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 matchespredictions
. -
scope
: The scope for the operations performed in computing the loss.
Returns:
A scalar Tensor
representing the loss value.
Raises:
-
ValueError
: Ifpredictions
shape doesn't matchlabels
shape, orweights
isNone
.
© 2017 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/cosine_distance