[
https://issues.apache.org/jira/browse/SINGA-115?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sheng Wang resolved SINGA-115.
------------------------------
Resolution: Fixed
Assignee: wangwei
> Print layer debug information in the neural net graph file
> ----------------------------------------------------------
>
> Key: SINGA-115
> URL: https://issues.apache.org/jira/browse/SINGA-115
> Project: Singa
> Issue Type: New Feature
> Reporter: wangwei
> Assignee: wangwei
>
> It is non-trivial to debug the code for deep learning, e.g., the BP
> algorithm, the hybrid partitioning and layer implementation.
> In SINGA, we print the neural net in INFO log as json string, which can be
> converted into an image with the net graph (nodes are layers). This graph can
> be used to check the neural net configuration, e.g., layer connection and
> neural net partitioning. However, it does not collect the run time data,
> e.g., gradient norm or value norm of each layer, which is important to debug
> accuracy etc. bugs.
> In this ticket, we will collect the gradient and value norm of each layer and
> each Param object. These information will be printed as attributes (or
> sub-nodes) of the layer node in the neural net graph. Users/developers can
> located the bugs by inspecting the graph after converting the json string
> into an image.
> Particularly, uses can set the disp_freq to 1 and running steps to a small
> number, e.g., 5. Then 5 neural net graphs will be printed, one per step. The
> debug option should be turned on in the job.conf file for printing.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
