[jira] [Commented] (TIKA-2672) Upgrade dl4j to 1.0.0-beta

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[jira] [Commented] (TIKA-2672) Upgrade dl4j to 1.0.0-beta

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    [ https://issues.apache.org/jira/browse/TIKA-2672?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16536809#comment-16536809 ]

ASF GitHub Bot commented on TIKA-2672:

ThejanW commented on issue #241: Fix for TIKA-2672
URL: https://github.com/apache/tika/pull/241#issuecomment-403449343
   oops! unit tests worked fine for me, we can safely exclude javacpp from tika-dl, then I got a dependency convergence issue:
   > Dependency convergence error for net.java.dev.jna:jna:4.1.0 paths to dependency are:
   In my latest commit, I have excluded jna in edu.ucar dependencies of tika-parsers and have added jna as a direct dependency. Any objections for that? @chrismattmann @tballison, I built the entire Tika project, the build was a success in my linux machine.

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> Upgrade dl4j to 1.0.0-beta
> --------------------------
>                 Key: TIKA-2672
>                 URL: https://issues.apache.org/jira/browse/TIKA-2672
>             Project: Tika
>          Issue Type: Task
>            Reporter: Tim Allison
>            Priority: Major
>         Attachments: TIKA-2672.patch
> Let's try to upgrade dl4j.  I think I got us most of the way there, but I got this error when reading the json config file.  Can someone with more knowledge of layer specs help ([~thammegowda], perhaps :))?
> {noformat}
> org.deeplearning4j.exception.DL4JInvalidConfigException: Invalid configuration for layer (idx=-1, name=convolution2d_2, type=ConvolutionLayer) for width dimension:  Invalid input configuration for kernel width. Require 0 < kW <= inWidth + 2*padW; got (kW=3, inWidth=1, padW=0)
> Input type = InputTypeConvolutional(h=149,w=1,c=32), kernel = [3, 3], strides = [1, 1], padding = [0, 0], layer size (output channels) = 32, convolution mode = Truncate
> {noformat}

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