tf.losses.cosine_distance( labels, predictions, axis=None, weights=1.0, scope=None, loss_collection=tf.GraphKeys.LOSSES, reduction=Reduction.SUM_BY_NONZERO_WEIGHTS, dim=None )
Adds a cosine-distance loss to the training procedure. (deprecated arguments)
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
labels are already unit-normalized.
Tensorwhose shape matches 'predictions'
predictions: An arbitrary matrix.
axis: The dimension along which the cosine distance is computed.
Tensorwhose rank is either 0, or the same rank as
labels, and must be broadcastable to
labels(i.e., all dimensions must be either
1, or the same as the corresponding
scope: The scope for the operations performed in computing the loss.
loss_collection: collection to which this loss will be added.
reduction: Type of reduction to apply to loss.
dim: The old (deprecated) name for
Weighted loss float
NONE, this has the same shape as
labels; otherwise, it is scalar.
predictionsshape doesn't match
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Code samples licensed under the Apache 2.0 License.