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-rw-r--r-- | doc/nerv_matrix.md | 8 | ||||
m--------- | speech | 0 |
2 files changed, 7 insertions, 1 deletions
diff --git a/doc/nerv_matrix.md b/doc/nerv_matrix.md index 9f4df5a..ef5118e 100644 --- a/doc/nerv_matrix.md +++ b/doc/nerv_matrix.md @@ -23,7 +23,7 @@ Also note that all assigning operation in __Nerv__ is reference copy, you can us ###Class hierarchy### The class hierarchy of the matrix classes can be clearly observed in `matrix/init.c`. First there is a abstract base class __Nerv.Matrix__, which is inherited by __Nerv.CuMatrix__ and __Nerv.MMatrix__(also abstract). -Finally, there is __Nerv.CuMatrixFloat__, __Nerv.CuMatrixDouble__, inheriting __Nerv.CuMatrix__, and __Nerv.MMatrixFloat__, __Nerv.MMatrixDouble__, inheriting __Nerv.MMatrix__. +Finally, there is __Nerv.CuMatrixFloat__, __Nerv.CuMatrixDouble__, inheriting __Nerv.CuMatrix__, and __Nerv.MMatrixFloat__, __Nerv.MMatrixDouble__, __Nerv.MMatrixInt__ , inheriting __Nerv.MMatrix__. ##Methods## Mind that usually a matrix object can only do calculation with matrix of its own type(a __Nerv.CuMatrixFloat__ matrix can only do add operation with a __Nerv.CuMatrixFloat__). @@ -77,3 +77,9 @@ Set the element of __Matrix__ `self` to be elementwise-sigmoid of `ma`. 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`. +* __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)__ +Calculate element-wise log of __Matrix__ `ma`, store the result in `self`. +* __void Matrix.copy_rows_fromh_by_idx(Matrix self, MMatrix ma, MMatrixInt idx)__ +`idx` should be a row vector. This function copy the rows of `ma` to `self` according to `idx`, in other words, it assigns `ma[idx[i]]` to `self[i]`.
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