Details of implementation


Where can I get the detailed implementation of linear regression in mxnet. I have looked at, regression_output-inl.h , But it uses namespace mshadow and I cannot get into the details of how the gradient calculations and forward passes are calculated. Kindly consider helping me in this regards. Thanks in advance for your help.


Tensor<xpu, 2> out = out_data[reg_enum::kOut].FlatTo2D<xpu, real_t>(s);
Tensor<xpu, 2> grad = in_grad[reg_enum::kData].FlatTo2D<xpu, real_t>(s);
Tensor<xpu, 2> label = in_data[reg_enum::kLabel]

inside regression_output-inl.h, where are these functions defined ?