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authorTianxingHe <[email protected]>2016-03-07 11:23:13 +0800
committerTianxingHe <[email protected]>2016-03-07 11:23:13 +0800
commit18990c8d90ad8e57fed2e5fd4d4acd4af491f880 (patch)
tree5412bbc767182d2f4d9bb71f636a6395cae4f090 /nerv
parent155132e122eca83942f49bb6a95c9dcf2bae8a81 (diff)
Update nerv_matrix.md
Doc change about the softmax operation.
Diffstat (limited to 'nerv')
-rw-r--r--nerv/doc/nerv_matrix.md4
1 files changed, 2 insertions, 2 deletions
diff --git a/nerv/doc/nerv_matrix.md b/nerv/doc/nerv_matrix.md
index 8ae97f9..3782eb3 100644
--- a/nerv/doc/nerv_matrix.md
+++ b/nerv/doc/nerv_matrix.md
@@ -83,8 +83,8 @@ Fill the content of __Matrix__ `self` to be `value`.
Set the element of __Matrix__ `self` to be elementwise-sigmoid of `ma`.
* __void Matrix.sigmoid_grad(Matrix self, Matrix err, Matrix output)__
Set the element of __Matrix__ `self`, to be `self[i][j]=err[i][j]*output[i][j]*(1-output[i][j])`. This function is used to propagate sigmoid layer error.
-* __void Matrix.softmax(Matrix self, Matrix a)__
-Calculate a row-by-row softmax of __Matrix__ `a` and save the result in `self`.
+* __Matrix Matrix.softmax(Matrix self, Matrix a)__
+Calculate a row-by-row softmax of __Matrix__ `a` and save the result in `self`. Returns a new `self.nrow*1` index matrix that stores the index of the maximum value of each row.
* __void Matrix.mul_elem(Matrix self, Matrix ma, Matrix mb)__
Calculate element-wise multiplication of __Matrix__ `ma` and `mb`, store the result in `self`.
* __void Matrix.log_elem(Matrix self, Matrix ma)__