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Diffstat (limited to 'doc')
| -rw-r--r-- | doc/nerv_matrix.md | 26 |
1 files changed, 24 insertions, 2 deletions
diff --git a/doc/nerv_matrix.md b/doc/nerv_matrix.md index 00356c3..2cef099 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__). @@ -68,7 +68,7 @@ It sets the content of __Matrix__ `self` to be `alpha * ma + beta * mb`.__Matrix * __void Matrix.mul(Matrix self, Matrix ma, Matrix mb, Element_type alpha, Element_type beta, [string ta, string tb])__ It sets the content of __Matrix__ `self` to be `beta * self + alpha * ma * mb`. `ta` and `tb` is optional, if `ta` is 'T', then `ma` will be transposed, also if `tb` is 'T', `mb` will be transposed. * __void Matrix.add_row(Matrix self, Matrix va, Element_type beta)__ -It sets the content of __Matrix__ `self`(which should be row vector) to be `self + beta * va`. +Add `beta * va` to every row of __Matrix__ `self`. * __void Matrix.fill(Matrix self, Element_type value)__ Fill the content of __Matrix__ `self` to be `value`. * __void Matrix.sigmoid(Matrix self, Matrix ma)__ @@ -77,3 +77,25 @@ 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]`. +* __void Matrix.expand_frm(Matrix self, Matrix a, int context)__ +Treating each row of `a` as speech feature, and do a feature expansion. The `self` should of size `(a.nrow, a.ncol * (context * 2 + 1))`. `self[i]` will be `(a[i-context] a[i-context+1] ... a[i] a[i+1] a[i+context])`. `a[0]` and `a[nrow]` will be copied to extend the index range. +* __void Matrix.rearrange_frm(Matrix self, Matrix a, int step)__ +Rearrange `a` according to its feature dimension. The `step` is the length of context. So, `self[i][j]` will be assigned `a[i][j / step + (j % step) * (a.ncol / step)]`. `a` and `self` should be of the same size and `step` should be divisible by `a.ncol`. +* __void Matrix.scale_row(Matrix self, Matrix scale)__ +Scale each column of `self` according to a vector `scale`. `scale` should be of size `1 * self.ncol`. +* __Matrix Matrix.\_\_add\_\_(Matrix ma, Matrix mb)__ +Returns a new __Matrix__ which stores the result of `ma+mb`. +* __Matrix Matrix.\_\_sub\_\_(Matrix ma, Matrix mb)__ +Returns a new __Matrix__ which stores the result of `ma-mb`. +* __Matrix Matrix.\_\_mul\_\_(Matrix ma, Matrix mb)__ +Returns a new __Matrix__ which stores the result of `ma*mb`. +* __CuMatrix CuMatrix.new_from_host(MMatrix m)__ +Return a new __CuMatrix__ which is a copy of `m`. +* __MMatrix CuMatrix.new_to_host(CuMatrix self)__ +Return a new __MMatrix__ which is a copy of `self`.
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