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Posted to dev@singa.apache.org by "Lee Chonho (JIRA)" <ji...@apache.org> on 2015/12/11 03:38:10 UTC

[jira] [Updated] (SINGA-81) Add Python Helper, which enables users to construct a model (JobProto) and run Singa in Python

     [ https://issues.apache.org/jira/browse/SINGA-81?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Lee Chonho updated SINGA-81:
----------------------------
    Summary: Add Python Helper, which enables users to construct a model (JobProto) and run Singa in Python  (was: Helper API, which enables users to construct JobProto in C++ and by Python binding)

> Add Python Helper, which enables users to construct a model (JobProto) and run Singa in Python
> ----------------------------------------------------------------------------------------------
>
>                 Key: SINGA-81
>                 URL: https://issues.apache.org/jira/browse/SINGA-81
>             Project: Singa
>          Issue Type: New Feature
>            Reporter: Lee Chonho
>
> Proposed design v1
> - (1) have a class named Builder
> - (2) use Boost::parameter library (+ associated necessary header files)
> (1)
> Builder class implements api-like functions to configure JobProto including NetProto (LayerProto), ClusterProto, UpdaterProto, etc.
> Two options
> a. users call Builder's functions in main.cc like
> {code}
> JobProto jobproto;
> Builder builder( &jobproto, "job name" );
> builder.xxx(xxx)  // add data layer
> builder.xxx(xxx)  // add parser layer
> ... etc. ...
> {code}
> b. we set main.cc like below and users call Builders functions in Construct() 
> {code}
> JobProto jobproto;
> Builder builder( &jobproto, "model name" );
> builder.Construct()
> {code}
> (2)
> Planning to use header-only files from Boost library
> - if the necessary files are small enough
> - because we can use "named arguments" feature with no restriction of # of arguments, order, types.
> - because function will be intuitive, and adding users' own proto in a straightforward way.
> Example is here. http://theboostcpplibraries.com/boost.parameter
> By following the example, we can do like
> {code}
> BOOST_PARAMETER_MEMBER_FUNCTION(   
>  (char*), AddLayerData,   tag,   
>  (required     
>    (type, (int))  (name, (char*))  (src, (char*))
>  ) 
>  (optional     
>    (path, (char*), *) (bsize (int) *)
>  ) )
>  {
>     ...  // set values
>     return name;
>  }
> {code}
> Then, users can add a datalayer by
> {code}
> L1 = builder.AddLayerData(kShardData, "data", null, _path="train_shard", _bsize=1000);
> {code}
> (TODO)
> - make use of google protobuf reflection for efficient parameter setting
> - need to avoid multiple calls for adding same/similar layers
> Any suggestion, design idea, comments please.



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