gaurav-gireesh commented on a change in pull request #12750: [MXNET -1030] Cosine Embedding Loss URL: https://github.com/apache/incubator-mxnet/pull/12750#discussion_r223231395
########## File path: python/mxnet/gluon/loss.py ########## @@ -706,3 +706,53 @@ def hybrid_forward(self, F, pred, positive, negative): axis=self._batch_axis, exclude=True) loss = F.relu(loss + self._margin) return _apply_weighting(F, loss, self._weight, None) + +class CosineEmbeddingLoss(Loss): + r"""For a target label 1 or -1, vectors target and pred, the function computes the cosine distance + between the vectors. This can be interpretted as how similar/dissimilar two input vectors are. + + + `pred`, `target` can have arbitrary shape as long as they have the same number of elements. Review comment: @szha Thank you! Incorporating that in the documentation. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services