Add description of ignore_label argument
@@ -195,7 +195,8 @@ def softmax_cross_entropy(
to 2, it computes a cross entropy of the replicated softmax if the
number of dimensions is greater than 2.
t (~chainer.Variable): Variable holding an int32 vector of ground truth
- labels. If ``t[i] == -1``, corresponding ``x[i]`` is ignored.
+ labels. If ``t[i] == ignore_label``, corresponding ``x[i]`` is
+ ignored.
normalize (bool): If ``True``, this function normalizes the cross
entropy loss across all instances. If ``False``, it only
normalizes along a batch size.
@@ -210,6 +211,8 @@ def softmax_cross_entropy(
``y[:, i]`` that is the corresponding log-softmax output of ``x``
and has the same shape as ``x`` before calculating the actual loss
value.
+ ignore_label (int): Label value you want to ignore. Its default value
+ is ``-1``. See description of the argument `t`.
Returns:
Variable: A variable holding a scalar array of the cross entropy loss.
