tf.contrib.losses.mean_pairwise_squared_error( predictions, labels=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 pairwise-errors-squared loss to the training procedure. (deprecated)
THIS FUNCTION IS DEPRECATED. It will be removed after 2016-12-30. Instructions for updating: Use tf.losses.mean_pairwise_squared_error instead. Note that the order of the predictions and labels arguments has been changed.
Unlike mean_squared_error
, which is a measure of the differences between corresponding elements of predictions
and labels
, mean_pairwise_squared_error
is a measure of the differences between pairs of corresponding elements of predictions
and labels
.
For example, if labels
=[a, b, c] and predictions
=[x, y, z], there are three pairs of differences are summed to compute the loss: loss = [ ((a-b) - (x-y)).^2 + ((a-c) - (x-z)).^2 + ((b-c) - (y-z)).^2 ] / 3
Note that since the inputs are of size [batch_size, d0, ... dN], the corresponding pairs are computed within each batch sample but not across samples within a batch. For example, if predictions
represents a batch of 16 grayscale images of dimension [batch_size, 100, 200], then the set of pairs is drawn from each image, but not across images.
weights
acts as a coefficient for the loss. If a scalar is provided, then the loss is simply scaled by the given value. If weights
is a tensor of size [batch_size], then the total loss for each sample of the batch is rescaled by the corresponding element in the weights
vector.
predictions
: The predicted outputs, a tensor of size [batch_size, d0, .. dN] where N+1 is the total number of dimensions in predictions
.labels
: The ground truth output tensor, whose shape must match the shape of the predictions
tensor.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.A scalar Tensor
representing the loss value.
ValueError
: If the shape of predictions
doesn't match that of labels
or if the shape of weights
is invalid.
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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/mean_pairwise_squared_error