The logits, a float tensor. Note that logits are assumed to be
unbounded and 0-centered. A value > 0 (resp. < 0) is considered a positive
(resp. negative) binary prediction.
labels
The ground truth output tensor. Its shape should match the shape of
logits. The values of the tensor are expected to be 0.0 or 1.0. Internally
the {0,1} labels are converted to {-1,1} when calculating the hinge loss.
scope
The scope for the operations performed in computing the loss.
Returns
An unweighted Tensor of same shape as logits and labels representing
the
loss values across the batch.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.contrib.losses.hinge_loss\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/contrib/losses/python/losses/loss_ops.py#L452-L483) |\n\nMethod that returns the loss tensor for hinge loss. (deprecated) \n\n tf.contrib.losses.hinge_loss(\n logits, labels=None, scope=None\n )\n\n| **Warning:** THIS FUNCTION IS DEPRECATED. It will be removed after 2016-12-30. Instructions for updating: Use tf.losses.hinge_loss instead. Note that the order of the logits and labels arguments has been changed, and to stay unweighted, reduction=Reduction.NONE\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `logits` | The logits, a float tensor. Note that logits are assumed to be unbounded and 0-centered. A value \\\u003e 0 (resp. \\\u003c 0) is considered a positive (resp. negative) binary prediction. |\n| `labels` | The ground truth output tensor. Its shape should match the shape of logits. The values of the tensor are expected to be 0.0 or 1.0. Internally the {0,1} labels are converted to {-1,1} when calculating the hinge loss. |\n| `scope` | The scope for the operations performed in computing the loss. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| An unweighted `Tensor` of same shape as `logits` and `labels` representing the loss values across the batch. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|--------------|-----------------------------------------------------|\n| `ValueError` | If the shapes of `logits` and `labels` don't match. |\n\n\u003cbr /\u003e"]]