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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (BEAM-1233) Implement TFRecordIO (Reading/writing Tensorflow Standard format)
Date Sat, 07 Jan 2017 02:21:58 GMT

    [ https://issues.apache.org/jira/browse/BEAM-1233?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15806525#comment-15806525
] 

ASF GitHub Bot commented on BEAM-1233:
--------------------------------------

GitHub user yk5 opened a pull request:

    https://github.com/apache/beam/pull/1749

    [BEAM-1233] Create TFRecordIO, providing source/sink for TFRecords, 

    which is the dedicated record format for Tensorflow.
    
    For more about TFRecords, refer to https://github.com/tensorflow/tensorflow/blob/master/tensorflow/g3doc/api_docs/python/python_io.md
    
    Be sure to do all of the following to help us incorporate your contribution
    quickly and easily:
    
     - [ ] Make sure the PR title is formatted like:
       `[BEAM-<Jira issue #>] Description of pull request`
     - [ ] Make sure tests pass via `mvn clean verify`. (Even better, enable
           Travis-CI on your fork and ensure the whole test matrix passes).
     - [ ] Replace `<Jira issue #>` in the title with the actual Jira issue
           number, if there is one.
     - [ ] If this contribution is large, please file an Apache
           [Individual Contributor License Agreement](https://www.apache.org/licenses/icla.txt).
    
    ---


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

    $ git pull https://github.com/yk5/beam tfrecord

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

    https://github.com/apache/beam/pull/1749.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 #1749
    
----
commit 3bbd2c1c208860c48c7a4c1909e3936a1fab4faa
Author: Younghee Kwon <younghee.kwon@gmail.com>
Date:   2017-01-07T02:05:56Z

    Create TFRecordIO, which provides source/sink for TFRecords, the dedicated record format
for Tensorflow.
    
    For more about TFRecords, refer to https://github.com/tensorflow/tensorflow/blob/master/tensorflow/g3doc/api_docs/python/python_io.md

----


> Implement TFRecordIO (Reading/writing Tensorflow Standard format)
> -----------------------------------------------------------------
>
>                 Key: BEAM-1233
>                 URL: https://issues.apache.org/jira/browse/BEAM-1233
>             Project: Beam
>          Issue Type: New Feature
>          Components: sdk-py
>            Reporter: Younghee Kwon
>            Assignee: Ahmet Altay
>
> Tensorflow is an open source Machine Learning project, which is getting lots of attention
these days. Apache Beam can be used as a good preprocessing tool for this Machine Learning
tool, however Tensorflow supports limited number of input file formats -- only csv and its
own record format (so called TFRecord).
> On the other hand, Apache Beam doesn't support reading/writing in TFRecord format. This
would be useful once it supports TFRecordIO natively.



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