diff options
Diffstat (limited to 'tensorflow/python/ops/losses/losses_impl.py')
| -rw-r--r-- | tensorflow/python/ops/losses/losses_impl.py | 22 |
1 files changed, 15 insertions, 7 deletions
diff --git a/tensorflow/python/ops/losses/losses_impl.py b/tensorflow/python/ops/losses/losses_impl.py index 752d260fba..55a18d28ca 100644 --- a/tensorflow/python/ops/losses/losses_impl.py +++ b/tensorflow/python/ops/losses/losses_impl.py @@ -27,6 +27,7 @@ from tensorflow.python.ops import nn from tensorflow.python.ops import nn_ops from tensorflow.python.ops import weights_broadcast_ops from tensorflow.python.ops.losses import util +from tensorflow.python.util.deprecation import deprecated_args class Reduction(object): @@ -230,10 +231,12 @@ def absolute_difference( losses, weights, scope, loss_collection, reduction=reduction) +@deprecated_args(None, "dim is deprecated, use axis instead", "dim") def cosine_distance( - labels, predictions, dim=None, weights=1.0, scope=None, + labels, predictions, axis=None, weights=1.0, scope=None, loss_collection=ops.GraphKeys.LOSSES, - reduction=Reduction.SUM_BY_NONZERO_WEIGHTS): + reduction=Reduction.SUM_BY_NONZERO_WEIGHTS, + dim=None): """Adds a cosine-distance loss to the training procedure. Note that the function assumes that `predictions` and `labels` are already @@ -242,13 +245,14 @@ def cosine_distance( Args: labels: `Tensor` whose shape matches 'predictions' predictions: An arbitrary matrix. - dim: The dimension along which the cosine distance is computed. + axis: The dimension along which the cosine distance is computed. weights: Optional `Tensor` whose rank is either 0, or the same rank as `labels`, and must be broadcastable to `labels` (i.e., all dimensions must be either `1`, or the same as the corresponding `losses` dimension). scope: The scope for the operations performed in computing the loss. loss_collection: collection to which this loss will be added. reduction: Type of reduction to apply to loss. + dim: The old (deprecated) name for `axis`. Returns: Weighted loss float `Tensor`. If `reduction` is `NONE`, this has the same @@ -256,10 +260,14 @@ def cosine_distance( Raises: ValueError: If `predictions` shape doesn't match `labels` shape, or - `dim`, `labels`, `predictions` or `weights` is `None`. + `axis`, `labels`, `predictions` or `weights` is `None`. """ - if dim is None: - raise ValueError("`dim` cannot be 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: + raise ValueError("You must specify 'axis'.") if labels is None: raise ValueError("labels must not be None.") if predictions is None: @@ -271,7 +279,7 @@ def cosine_distance( predictions.get_shape().assert_is_compatible_with(labels.get_shape()) radial_diffs = math_ops.multiply(predictions, labels) - losses = 1 - math_ops.reduce_sum(radial_diffs, axis=(dim,), keep_dims=True) + losses = 1 - math_ops.reduce_sum(radial_diffs, axis=(axis,), keep_dims=True) return compute_weighted_loss( losses, weights, scope, loss_collection, reduction=reduction) |