minor in act

include/mxnet/operator.h

@@ -69,7 +69,7 @@ class Operator {
    *     in_shape allows unknown elements, which are checked by shape.ndim() == 0.
    *     For unknown shapes, InferShape will try to fill in the correct Shape in in_shape
    *     For known shapes, InferShape will check shape consistency
-   *  
+   *
    *     common practice: set the shape of data input, and usually weight's shape can be infered
    *
    * \param out_shape the shape of outputs of the operator
@@ -81,7 +81,7 @@ class Operator {
    * \brief perform a forward operation of operator, save the output to TBlob
    * \param opt option on Forward such as whether this is training phase
    * \param ctx runtime context
-   * \param in_data array of input data
+   * \param in_data array of input data, it is const
    * \param out_data array of output data,
    *        the space of TBlob in out_data must be pre-allocated with InferShape
    */
@@ -97,14 +97,15 @@ class Operator {
    * \param out_grad array of output gradient, there could be three possible TBlob
    *  in the each element in the array
    * \param req_types request types of the gradient saving operation
+   *                  only inplace will change input data
    * \sa GradReqType
    */
   virtual void Backward(RunContext ctx,
                         const std::vector<TBlob> &grad_next,
                         const std::vector<TBlob> &in_data,
                         const std::vector<TBlob> &out_grad,
                         const std::vector<GradReqType> &req);
-  
+
   /*!
    * \brief factory unction, create a new operator
    * \param type the type of operator

src/operator/activation_op-inl.h

@@ -50,8 +50,9 @@ class ActivationOp : public Operator {
       static_cast<mshadow::Stream<xpu> *>(ctx.stream);
     mshadow::Tensor<xpu, 2> grad = grad_next[0].FlatTo2D<xpu, real_t>(stream);
     mshadow::Tensor<xpu, 2> data = in_data[0].FlatTo2D<xpu, real_t>(stream);
-    mshadow::Tensor<xpu, 2> out = in_data[0].FlatTo2D<xpu, real_t>(stream);
-    Assign(out, req[0], mshadow::expr::F<BackOp>(data) * grad);
+    mshadow::Tensor<xpu, 2> out = out_grad[0].FlatTo2D<xpu, real_t>(stream);
+    Assign(out, req[0], mshadow::expr::F<BackOp>(
+        mshadow::expr::F<ForwardOp>(data)) * grad);
   }
 };  // class ActivationOp
 }  // namespace op