[GitHub] zihaolucky commented on issue #7341: Usage of Tensorboard in Distributed MXNet

2017-08-07 Thread git
zihaolucky commented on issue #7341: Usage of Tensorboard in Distributed MXNet
URL: 
https://github.com/apache/incubator-mxnet/issues/7341#issuecomment-320829394
 
 
   @LakeCarrot There're some discussions on this issue, 
https://stackoverflow.com/questions/40830085/tensorboard-can-not-read-summaries-on-google-cloud-storage.
 As far as I know, I haven't seen this feature in origin TensorBoard, and our 
standalone version only supports reading from local. This feature has been 
raised in https://github.com/dmlc/tensorboard/issues/39, I'll follow this issue 
and update the status.
 

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[GitHub] zihaolucky commented on issue #7341: Usage of Tensorboard in Distributed MXNet

2017-08-04 Thread git
zihaolucky commented on issue #7341: Usage of Tensorboard in Distributed MXNet
URL: 
https://github.com/apache/incubator-mxnet/issues/7341#issuecomment-320414116
 
 
   @LakeCarrot Here is an example 
https://github.com/apache/incubator-mxnet/blob/master/python/mxnet/contrib/tensorboard.py
 in which we use the callback to log training/eval metrics.
   
   In functionality, I suppose the usage of TensorBoard would have no 
difference than in TensorFlow, as we just write something to the event file. So 
if you want to log/monitor the overall learning process, I think you should 
dive into the logging mechanism of MXNet. 
   
   But I haven't try distributed MXNet before, I'm not sure whether the example 
above could help. It depends on how these metrics are aggregated and computed, 
and where the event file is.
 

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