[GitHub] [incubator-mxnet] kshitij12345 commented on a change in pull request #15331: [fix] missing input log higher order.

[GitBox <gi...@apache.org>]

kshitij12345 commented on a change in pull request #15331: [fix] missing input log higher order.
URL: https://github.com/apache/incubator-mxnet/pull/15331#discussion_r304541519
 
 

 ##########
 File path: src/operator/tensor/elemwise_unary_op_basic.cc
 ##########
 @@ -1117,15 +1117,15 @@ MXNET_OPERATOR_REGISTER_BINARY_WITH_SPARSE_CPU_DR(_backward_log10,
                                                   unary_bwd<mshadow_op::log10_grad>)
 .set_attr<nnvm::FGradient>("FGradient",
   [](const nnvm::NodePtr& n, const std::vector<nnvm::NodeEntry>& ograds) {
-    // ograds[0]: dL/dxgrad
+    // ograds[0]: dL/dygrad
 
 Review comment:
   I guess it should be, dL/dy_grad as we are computing/returning dL/dx_grad,
   Eg.
   ```
   y = f(dx_grad)
   L = g(y) # dx_grad formed part of the network and affected loss
   
   During backprop by chain rule,
   dL/dx_grad = dL/dy * dy/dx_grad
   
   In comments, we have called dL/dy (mentioned in the above example) as dL/dy_grad
   ```
   
   That is why we have,
   https://github.com/apache/incubator-mxnet/blob/5b95fb3ee3581ba20fe1def336621d68a811e17f/src/operator/tensor/elemwise_unary_op_basic.cc#L1111-L1112
   
   These multiplications performing, 
   ```
   dL/dx_grad = dL/dy * dy/dx_grad
   ```

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