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https://issues.apache.org/jira/browse/SINGA-81?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15076287#comment-15076287
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ASF subversion and git services commented on SINGA-81:
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Commit ceb066560708a6b5e4cbdbbcba095821f18db327 in incubator-singa's branch
refs/heads/master from chonho
[ https://git-wip-us.apache.org/repos/asf?p=incubator-singa.git;h=ceb0665 ]
SINGA-81 Add Python Helper, which enables users to construct a model (JobProto)
and run Singa in Python
- Update model.py to take care of cudnn
. fit() receives device field, a list of gpu id
. setCudnnLayerType converts LayerType to CdunnLayerType
- Add examples for cudnn
> 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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