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https://issues.apache.org/jira/browse/SYSTEMML-1686?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Glenn Weidner updated SYSTEMML-1686:
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Fix Version/s: (was: SystemML 1.0)
SystemML 0.15
> Transpose Conv2d has incorrect filter shape and incorrect input size argument
> -----------------------------------------------------------------------------
>
> Key: SYSTEMML-1686
> URL: https://issues.apache.org/jira/browse/SYSTEMML-1686
> Project: SystemML
> Issue Type: Bug
> Affects Versions: SystemML 1.0
> Reporter: Mike Dusenberry
> Assignee: Matthias Boehm
> Fix For: SystemML 0.15
>
>
> Currently, the transpose conv2d layer ([{{nn/layers/conv2d_tranpose.dml}} |
> https://github.com/apache/systemml/blob/master/scripts/nn/layers/conv2d_transpose.dml]
> has a bug in which the filters tensor {{W}} has an incorrect shape, and the
> {{conv2d_backward_data}} op has an incorrect input shape argument. This
> results in an exception when the number of input channels {{C}} is not equal
> to the number of filters {{F}} (i.e. number of output channels). Since the
> transpose conv2d op is the gradient of the conv2d op, the filter tensor needs
> to have the shape {{C, F, Hf, Wf}} for {{F}} filters, rather than {{F, C, Hf,
> Wf}}, in order to map from an input with {{C}} channels to an output with
> {{F}} channels during the input data gradient function
> ({{conv2d_backward_data}}) that is used in the forward pass. Additionally,
> the {{input_shape}} argument for {{conv2d_backward_data}} needs to be {{N, F,
> Hout, Wout}}, rather than {{N, C, Hout, Wout}} in order to map from an input
> with {{C}} channels to an output with {{F}} channels. Our current test cases
> did not catch this issue because the tests used {{C = F = 1}}.
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