[GitHub] [incubator-mxnet] rondogency commented on a change in pull request #17241: Add CustomOp tutorial doc

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

rondogency commented on a change in pull request #17241: Add CustomOp tutorial doc
URL: https://github.com/apache/incubator-mxnet/pull/17241#discussion_r369830264
 
 

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 File path: example/extensions/lib_custom_op/README.md
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+CustomOp Example and Tutorial
+====
+
+## Getting Started
+
+### Have MXNet Ready:
+
+First you should install MXNet either from compiling from source code or download from nightly build. It doesn’t matter if the build comes with CUDA or MKLDNN. The custom operator doesn’t interact with the execution of other native MXNet operators.
+
+### Run An Example:
+
+You can start getting familiar with custom operator by running some examples we provide in the **example/extensions/lib_custom_op** directory. Let’s start with gemm (Generalized Matrix Multiplication) operator, a common linear algebra operator. Go to that directory and follow the steps:
+
+1. run `make gemm_lib`, the Makefile will generate a dynamic library **libgemm_lib.so** compiled from gemm_lib.cc. This is the library you are going to load that contains everything of the custom gemm operator.
+2. run `python test_gemm.py`, and it’ll first load the above .so library, find operators,  register them in the MXNet backend, print "Found x operators"; then invoke the operator like a regular MXNet operator and output the result.
+
+### Basic Files For Gemm Library:
+
+* **lib_custom_op/gemm_lib.cc**: This file has source code implementation of all required components of a custom operator, as well as the registration of the custom operator.
+
+* **lib_custom_op/Makefile**: Compile source code to a dynamic shared library, with a header file **include/mxnet/lib_api.h** from MXNet source code. Currently the custom operator is compatible with C++11 onwards.
+
+* **lib_custom_op/test_gemm.py**: This file calls `mx.library.load(‘libgemm_lib.so’)` to load the library containing the custom operator, invoke the operator using both ndarray and symbol API, and print outputs of forward and backward pass. The outputs should be the same as the regular MXNet gemm operator.
+
+## Writing Custom Operators:
+
+### Regular Custom Operator:
+
+There are several basic building blocks for making a (stateless) custom operator:
+
+* [parseAttrs](./gemm_lib.cc#L118) - Attribute Parser:
 
 Review comment:
   can you provide me an example of how to do it?

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