[GitHub] madlib issue #342: Minibatch Preprocessor for Deep learning

2018-12-19 Thread asfgit
Github user asfgit commented on the issue:

https://github.com/apache/madlib/pull/342
  

Refer to this link for build results (access rights to CI server needed): 
https://builds.apache.org/job/madlib-pr-build/717/



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[GitHub] madlib issue #342: Minibatch Preprocessor for Deep learning

2018-12-19 Thread fmcquillan99
Github user fmcquillan99 commented on the issue:

https://github.com/apache/madlib/pull/342
  
https://issues.apache.org/jira/browse/MADLIB-1290
associated JIRA


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[GitHub] madlib pull request #342: Minibatch Preprocessor for Deep learning

2018-12-19 Thread njayaram2
GitHub user njayaram2 opened a pull request:

https://github.com/apache/madlib/pull/342

Minibatch Preprocessor for Deep learning

The minibatch preprocessor we currently have in MADlib is bloated for DL
tasks. This feature adds a simplified version of creating buffers, and
divides each element of the independent array by a normalizing constant
for standardization (which is 255.0 by default). This is standard practice
with image data.

Co-authored-by: Arvind Sridhar 
Co-authored-by: Domino Valdano 

You can merge this pull request into a Git repository by running:

$ git pull https://github.com/madlib/madlib 
deep-learning/minibatch-preprocessor

Alternatively you can review and apply these changes as the patch at:

https://github.com/apache/madlib/pull/342.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

This closes #342


commit c983aafcd5e31bab5dbc278178ff9e2e17942ea1
Author: Nandish Jayaram 
Date:   2018-12-18T01:54:42Z

Minibatch Preprocessor for Deep learning

The minibatch preprocessor we currently have in MADlib is bloated for DL
tasks. This feature adds a simplified version of creating buffers, and
divides each element of the independent array by a normalizing constant
for standardization (which is 255.0 by default). This is standard practice
with image data.

Co-authored-by: Arvind Sridhar 
Co-authored-by: Domino Valdano 




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[GitHub] madlib pull request #341: Minibatch Preprocessor for Deep learning

2018-12-19 Thread njayaram2
Github user njayaram2 closed the pull request at:

https://github.com/apache/madlib/pull/341


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[GitHub] madlib issue #341: Minibatch Preprocessor for Deep learning

2018-12-19 Thread asfgit
Github user asfgit commented on the issue:

https://github.com/apache/madlib/pull/341
  

Refer to this link for build results (access rights to CI server needed): 
https://builds.apache.org/job/madlib-pr-build/716/



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[GitHub] madlib pull request #341: Minibatch Preprocessor for Deep learning

2018-12-19 Thread njayaram2
GitHub user njayaram2 opened a pull request:

https://github.com/apache/madlib/pull/341

Minibatch Preprocessor for Deep learning

The minibatch preprocessor we currently have in MADlib is bloated for DL
tasks. This feature adds a simplified version of creating buffers, and
divides each element of the independent array by a normalizing constant
for standardization (which is 255.0 by default). This is standard practice
with image data.

Co-authored-by: Arvind Sridhar 
Co-authored-by: Domino Valdano 

You can merge this pull request into a Git repository by running:

$ git pull https://github.com/madlib/madlib 
deep-learning/minibatch-preprocessor

Alternatively you can review and apply these changes as the patch at:

https://github.com/apache/madlib/pull/341.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

This closes #341


commit 78430bc8586ae0256a24de2472392564a15f7f8e
Author: Nandish Jayaram 
Date:   2018-12-18T01:54:42Z

Minibatch Preprocessor for Deep learning

The minibatch preprocessor we currently have in MADlib is bloated for DL
tasks. This feature adds a simplified version of creating buffers, and
divides each element of the independent array by a normalizing constant
for standardization (which is 255.0 by default). This is standard practice
with image data.

Co-authored-by: Arvind Sridhar 
Co-authored-by: Domino Valdano 




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