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Diffstat (limited to 'tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.nn.sampled_softmax_loss.md')
| -rw-r--r-- | tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.nn.sampled_softmax_loss.md | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.nn.sampled_softmax_loss.md b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.nn.sampled_softmax_loss.md index 6d22f67352..44388cce0c 100644 --- a/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.nn.sampled_softmax_loss.md +++ b/tensorflow/g3doc/api_docs/python/functions_and_classes/shard1/tf.nn.sampled_softmax_loss.md @@ -11,8 +11,8 @@ the full softmax loss. At inference time, you can compute full softmax probabilities with the expression `tf.nn.softmax(tf.matmul(inputs, tf.transpose(weights)) + biases)`. -See our [Candidate Sampling Algorithms Reference] -(../../extras/candidate_sampling.pdf) +See our +[Candidate Sampling Algorithms Reference](../../extras/candidate_sampling.pdf) Also see Section 3 of [Jean et al., 2014](http://arxiv.org/abs/1412.2007) ([pdf](http://arxiv.org/pdf/1412.2007.pdf)) for the math. |