<p dir="auto"><code class="notranslate">tensorflow</code> currently handles duplicates in <code class="notranslate">SparseTensor</code> by keeping the value for the last index of a repeated coordinate. However, some operations for this would come in quite handy, namely non-max or non-min suppression (keeping the maximum or minimum values for repeated coordinates), sum (summing the values for repeated coordinates) or mean (averaging the values for repeated coordinates).</p>
<p dir="auto">There is currently a solution for this in <a href="https://stackoverflow.com/questions/38233821/merge-duplicate-indices-in-a-sparse-tensor" rel="nofollow">https://stackoverflow.com/questions/38233821/merge-duplicate-indices-in-a-sparse-tensor</a>. It works great, but to be honest it feels a bit clunky to use.</p>
<h3 dir="auto">System information</h3>
<ul dir="auto">
<li><strong>Have I written custom code (as opposed to using a stock example script provided in TensorFlow)</strong>: Yes</li>
<li><strong>OS Platform and Distribution (e.g., Linux Ubuntu 16.04)</strong>: Ubuntu 14.04</li>
<li><strong>TensorFlow installed from (source or binary)</strong>: Binary (pip install)</li>
<li><strong>TensorFlow version (use command below)</strong>: ('v1.2.0-rc2-21-g12f033d', '1.2.0')</li>
<li><strong>Bazel version (if compiling from source)</strong>: N/A</li>
<li><strong>CUDA/cuDNN version</strong>: 8.0</li>
<li><strong>GPU model and memory</strong>: Tesla P100-SXM2 16MB</li>
<li><strong>Exact command to reproduce</strong>: python caffe_to_tf_test.py</li>
</ul>
<h3 dir="auto">Describe the problem</h3>
<p dir="auto">Caffe convolution produce different results then tensorflow with the same parameters.   This has something to do with striding - the attached test fails with striding equal to 2, and succeeds with striding equal to 1.</p>
<h3 dir="auto">Source code / logs</h3>
<p dir="auto">Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem.</p>
<p dir="auto"><a href="https://github.com/tensorflow/tensorflow/files/1079200/x.zip">x.zip</a></p>