{"id":1134,"date":"2021-10-12T17:29:12","date_gmt":"2021-10-12T22:29:12","guid":{"rendered":"http:\/\/www.gergltd.com\/home\/?p=1134"},"modified":"2021-10-12T17:33:16","modified_gmt":"2021-10-12T22:33:16","slug":"tensorboard-subsamples-scalars-when-plotting","status":"publish","type":"post","link":"https:\/\/www.gergltd.com\/home\/tensorboard-subsamples-scalars-when-plotting\/","title":{"rendered":"Tensorboard subsamples scalars when plotting"},"content":{"rendered":"<p>I have noticed for year that tensorboard v2.x subscamples scalars when plotting.\u00a0 I never tried to reproduce the problem but noticed if I had a longish training run, every epoch&#8217;s loss was not displayed on tensorboard.\u00a0 This would produce a strange jaggy effect of the plot which I never liked, especially given my signal processing background.\u00a0 It was also not obvious why or how it was subsampling.\u00a0 For all I knew, it wasn&#8217;t even subsampling but doing some kind of filtering which resulted in the skipping of scalar values on the plots.<\/p>\n<p>Today, I finally figured out how to fix this issue.\u00a0 I was able to correct the issue by using a tensorboard command prompt of:<\/p>\n<p>start &#8220;tensorboard&#8221; &#8220;e:\\python_3.8\\scripts\\tensorboard&#8221; &#8211;samples_per_plugin scalars=9999999 &#8211;logdir .<\/p>\n<p>The addition of the &#8211;samples_per_plugin scalars=999999 fixes the issue.\u00a0 Now, all of the points I write out to tensorboard are displayed.<\/p>\n<p>Ref: https:\/\/stackoverflow.com\/questions\/43763858\/change-images-slider-step-in-tensorboard<\/p>\n","protected":false},"excerpt":{"rendered":"<p>I have noticed for year that tensorboard v2.x subscamples scalars when plotting.\u00a0 I never tried to reproduce the problem but noticed if I had a longish training run, every epoch&#8217;s loss was not displayed on tensorboard.\u00a0 This would produce a strange jaggy effect of the plot which I never liked, especially given my signal processing [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"nf_dc_page":"","_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1134","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/www.gergltd.com\/home\/wp-json\/wp\/v2\/posts\/1134","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.gergltd.com\/home\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.gergltd.com\/home\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.gergltd.com\/home\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.gergltd.com\/home\/wp-json\/wp\/v2\/comments?post=1134"}],"version-history":[{"count":1,"href":"https:\/\/www.gergltd.com\/home\/wp-json\/wp\/v2\/posts\/1134\/revisions"}],"predecessor-version":[{"id":1135,"href":"https:\/\/www.gergltd.com\/home\/wp-json\/wp\/v2\/posts\/1134\/revisions\/1135"}],"wp:attachment":[{"href":"https:\/\/www.gergltd.com\/home\/wp-json\/wp\/v2\/media?parent=1134"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.gergltd.com\/home\/wp-json\/wp\/v2\/categories?post=1134"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.gergltd.com\/home\/wp-json\/wp\/v2\/tags?post=1134"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}