Googlenet Network architecture

username: 111296
cooked: <p>Googlenet.py and googlenet-1378be20.pth can change googlenet architecture. This web(<a href="https://www.twblogs.net/a/5b8d787b2b717718833e3c25?lang=zh-cn" rel="noopener nofollow ugc">https://www.twblogs.net/a/5b8d787b2b717718833e3c25?lang=zh-cn</a>) can change network architecture. But I don’t know how to do it step by step.</p>

username: BramVanroy
cooked: <p>Can you provide more information? This is very brief. Please be more elaborate.</p>

username: 111296
cooked: <p>I used this method to change googlenet nerwork’s dropout layer.<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/6/2/62af628a724f89e61d444f2dc254b8df43aaaa51.png" data-download-href="https://discuss.pytorch.org/uploads/default/62af628a724f89e61d444f2dc254b8df43aaaa51" title="2020-09-29 11-11-59 的螢幕擷圖"><img src="https://discuss.pytorch.org/uploads/default/original/3X/6/2/62af628a724f89e61d444f2dc254b8df43aaaa51.png" alt="2020-09-29 11-11-59 的螢幕擷圖" data-base62-sha1="e50yg5AEfditGQpJ32qw2eAinzb" width="690" height="360" data-dominant-color="F3F3F3"><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">2020-09-29 11-11-59 的螢幕擷圖</span><span class="informations">711×371 32.1 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>After chaging it, this is changed condition on the picture.<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/4/4/441319be2426b73f2223af9d4b83326642076196.jpeg" data-download-href="https://discuss.pytorch.org/uploads/default/441319be2426b73f2223af9d4b83326642076196" title="2020-09-29 10-46-42 的螢幕擷圖"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/4/4/441319be2426b73f2223af9d4b83326642076196_2_690x388.jpeg" alt="2020-09-29 10-46-42 的螢幕擷圖" data-base62-sha1="9Idoe1ObdKLpP2T2eaOwsjrTmf4" width="690" height="388" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/4/4/441319be2426b73f2223af9d4b83326642076196_2_690x388.jpeg, https://discuss.pytorch.org/uploads/default/optimized/3X/4/4/441319be2426b73f2223af9d4b83326642076196_2_1035x582.jpeg 1.5x, https://discuss.pytorch.org/uploads/default/optimized/3X/4/4/441319be2426b73f2223af9d4b83326642076196_2_1380x776.jpeg 2x" data-dominant-color="3A1A30"><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">2020-09-29 10-46-42 的螢幕擷圖</span><span class="informations">1920×1080 356 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>I used the web(<a href="https://github.com/dusty-nv/jetson-inference/blob/master/docs/pytorch-collect.md" class="inline-onebox" rel="noopener nofollow ugc">jetson-inference/docs/pytorch-collect.md at master · dusty-nv/jetson-inference · GitHub</a>) to train, and convert to onnx. After converting onnx, the drop didn’t change.<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/7/f/7ff8df06ef3ff323f13f6381cedadfa1968328c6.jpeg" data-download-href="https://discuss.pytorch.org/uploads/default/7ff8df06ef3ff323f13f6381cedadfa1968328c6" title="2020-09-29 11-04-17 的螢幕擷圖"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/7/f/7ff8df06ef3ff323f13f6381cedadfa1968328c6_2_690x388.jpeg" alt="2020-09-29 11-04-17 的螢幕擷圖" data-base62-sha1="ig5QfQHlvcBJLBfkvmxn3h63Lng" width="690" height="388" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/7/f/7ff8df06ef3ff323f13f6381cedadfa1968328c6_2_690x388.jpeg, https://discuss.pytorch.org/uploads/default/optimized/3X/7/f/7ff8df06ef3ff323f13f6381cedadfa1968328c6_2_1035x582.jpeg 1.5x, https://discuss.pytorch.org/uploads/default/optimized/3X/7/f/7ff8df06ef3ff323f13f6381cedadfa1968328c6_2_1380x776.jpeg 2x" data-dominant-color="3B1B31"><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">2020-09-29 11-04-17 的螢幕擷圖</span><span class="informations">1920×1080 311 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>