diff options
Diffstat (limited to 'tensorflow/contrib/losses')
| -rw-r--r-- | tensorflow/contrib/losses/python/losses/loss_ops.py | 9 | ||||
| -rw-r--r-- | tensorflow/contrib/losses/python/metric_learning/metric_loss_ops.py | 4 |
2 files changed, 6 insertions, 7 deletions
diff --git a/tensorflow/contrib/losses/python/losses/loss_ops.py b/tensorflow/contrib/losses/python/losses/loss_ops.py index 8c3a8afe7a..bdad34a665 100644 --- a/tensorflow/contrib/losses/python/losses/loss_ops.py +++ b/tensorflow/contrib/losses/python/losses/loss_ops.py @@ -29,6 +29,7 @@ from tensorflow.python.ops import nn from tensorflow.python.ops import nn_ops from tensorflow.python.util.deprecation import deprecated from tensorflow.python.util.deprecation import deprecated_args +from tensorflow.python.util.deprecation import deprecated_argument_lookup __all__ = [ "absolute_difference", "add_loss", "cosine_distance", @@ -651,11 +652,9 @@ def cosine_distance(predictions, ValueError: If `predictions` shape doesn't match `labels` shape, or `weights` is `None`. """ - if dim is not None: - if axis is not None: - raise ValueError("Cannot specify both 'axis' and 'dim'") - axis = dim - if axis is None and dim is None: + axis = deprecated_argument_lookup( + "axis", axis, "dim", dim) + if axis is None: raise ValueError("You must specify 'axis'.") with ops.name_scope(scope, "cosine_distance_loss", [predictions, labels, weights]) as scope: diff --git a/tensorflow/contrib/losses/python/metric_learning/metric_loss_ops.py b/tensorflow/contrib/losses/python/metric_learning/metric_loss_ops.py index 2b9eee4ef7..de76acb51f 100644 --- a/tensorflow/contrib/losses/python/metric_learning/metric_loss_ops.py +++ b/tensorflow/contrib/losses/python/metric_learning/metric_loss_ops.py @@ -711,7 +711,7 @@ def _find_loss_augmented_facility_idx(pairwise_distances, labels, chosen_ids, candidate_scores, margin_multiplier * nmi_scores) argmax_index = math_ops.to_int32( - math_ops.argmax(candidate_scores, dimension=0)) + math_ops.argmax(candidate_scores, axis=0)) return candidate_ids[argmax_index] @@ -811,7 +811,7 @@ def update_medoid_per_cluster(pairwise_distances, pairwise_distances_subset, candidate_scores = math_ops.add(scores_fac, margin_multiplier * scores_margin) argmax_index = math_ops.to_int32( - math_ops.argmax(candidate_scores, dimension=0)) + math_ops.argmax(candidate_scores, axis=0)) best_medoid = math_ops.to_int32(cluster_member_ids[argmax_index]) chosen_ids = update_1d_tensor(chosen_ids, cluster_idx, best_medoid) |