提交 7acd669e 编写于 作者: H hedaoyuan

Supplement the data format specifications for the parameters.

上级 0cc3d829
......@@ -126,6 +126,11 @@ void CrossMapNormalGrad<DEVICE_TYPE_CPU>(real* inputsGrad,
* N /max(0, f-[N/2])
*
* Argument in the Function:
* Input is NCHW format, while input.shape.ndims() is equal 4.
* And the meaning of each dimension(0-3) is respectively batch size,
* feature maps, rows and columns.
* The above formula is for each image.
*
* \param size_ represent N
* \param scale_ represent alpha / N
* \param pow_ represent beta
......@@ -135,7 +140,7 @@ void CrossMapNormalGrad<DEVICE_TYPE_CPU>(real* inputsGrad,
*
* note:
* Save output[1] is to simplify the backward calculation.
* So, if only consider the forward calculation, we can optimize to
* TODO, if only consider the forward calculation, we can optimize to
* remove the output[1].
*/
template <DeviceType Device>
......@@ -192,6 +197,9 @@ private:
* /
*
* Argument in the Function:
* The data of inputs/outputs format is the same as the forward interface
* and is NCHW.
*
* \param size_ represent N
* \param scale_ represent alpha / N
* \param pow_ represent beta
......
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