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| author |  Neal Wu <wun@google.com> | 2017-03-20 14:33:54 -0800 |
|---|---|---|
| committer |  TensorFlower Gardener <gardener@tensorflow.org> | 2017-03-20 15:51:03 -0700 |
| commit | af62b5ccb9d06381096d18418920d06390d90be9 (patch) | |
| tree | e484c801873549e025cb9cf0121e2f22b8ee8b04 | |
| parent | 159f66df31234c77dd509876adddbd7280e445c2 (diff) | |
Fixed the order of arguments for softmax_loss_function in two places, including a semantic code change.
Change: 150685391
| -rw-r--r-- | tensorflow/contrib/seq2seq/python/ops/loss.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/tensorflow/contrib/seq2seq/python/ops/loss.py b/tensorflow/contrib/seq2seq/python/ops/loss.py index bb87111266..e14f07bc09 100644 --- a/tensorflow/contrib/seq2seq/python/ops/loss.py +++ b/tensorflow/contrib/seq2seq/python/ops/loss.py @@ -48,7 +48,7 @@ def sequence_loss(logits, targets, weights, timesteps. average_across_batch: If set, sum the cost across the batch dimension and divide the returned cost by the batch size. - softmax_loss_function: Function (inputs-batch, labels-batch) -> loss-batch + softmax_loss_function: Function (labels-batch, inputs-batch) -> loss-batch to be used instead of the standard softmax (the default if this is None). name: Optional name for this operation, defaults to "sequence_loss". @@ -76,7 +76,7 @@ def sequence_loss(logits, targets, weights, crossent = nn_ops.sparse_softmax_cross_entropy_with_logits( labels=targets, logits=probs_flat) else: - crossent = softmax_loss_function(probs_flat, targets) + crossent = softmax_loss_function(targets, probs_flat) crossent = crossent * array_ops.reshape(weights, [-1]) if average_across_timesteps and average_across_batch: crossent = math_ops.reduce_sum(crossent) |