Torchview - package for visualizing pytorch models

ConvolutionalAtom: <p>Hi,</p>
<p>I wanted to announce that I have recently created a python package for visualizing pytorch models, called torchview.</p>
<p>If you wanted to checkout the repo for the project, see <a href="https://github.com/mert-kurttutan/torchview" rel="noopener nofollow ugc">here</a></p>
<p>As far as I could have tried, it can capture any type of models with any type of operation in it.</p>
<p>For instances, the part of resnet18 graph from torchview (picture of the entire model is huge) is</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/d/b/db455c35cde25717f82920e211ebdb688fec14a2.png" data-download-href="https://discuss.pytorch.org/uploads/default/db455c35cde25717f82920e211ebdb688fec14a2" title="resnet_snippet"><img src="https://discuss.pytorch.org/uploads/default/original/3X/d/b/db455c35cde25717f82920e211ebdb688fec14a2.png" alt="resnet_snippet" data-base62-sha1="vhLavNAhU4VZYhAqGtsQSziqBnc" width="489" height="500" data-dominant-color="EEF7EE"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">resnet_snippet</span><span class="informations">524×535 19.8 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>
<p>One of the cool features is that it can return rolled version of recursive networks. For instance,<br>
<img src="https://discuss.pytorch.org/uploads/default/original/3X/1/4/1443d6e9b0563e7a59429c6c5e6c6f4b10ed29b3.png" alt="rnn" data-base62-sha1="2TgTtTEbEkuh9oP0sQvKFDTbMLp" width="686" height="444"></p>
<p>I added colab notebooks where you can explore some basic and complex/famous models.</p>
<p>I also listed todo list which I think should be fine to be implemented.</p>
<p>Any feedback/issue/pr is much appreciated!!!</p>

ConvolutionalAtom: <p>Update!<br>
New version for the package is released. After the new update, it also supports more proper representation of nested modules. For instance, resnet18 is represented as follows</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/4/d/4d310188f621a584b8c22be6876e711892006474.png" data-download-href="https://discuss.pytorch.org/uploads/default/4d310188f621a584b8c22be6876e711892006474" title="resnet_partial"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/4/d/4d310188f621a584b8c22be6876e711892006474_2_307x500.png" alt="resnet_partial" data-base62-sha1="b0RL7M1g5WE29MqOBubfxYajno0" width="307" height="500" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/4/d/4d310188f621a584b8c22be6876e711892006474_2_307x500.png, https://discuss.pytorch.org/uploads/default/optimized/3X/4/d/4d310188f621a584b8c22be6876e711892006474_2_460x750.png 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/4/d/4d310188f621a584b8c22be6876e711892006474.png 2x" data-dominant-color="F3F8F3"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">resnet_partial</span><span class="informations">589×958 71.3 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>