{"action":"created","issue":{"url":"https://api.github.com/repos/snap-stanford/snapvx/issues/5","labels_url":"https://api.github.com/repos/snap-stanford/snapvx/issues/5/labels{/name}","comments_url":"https://api.github.com/repos/snap-stanford/snapvx/issues/5/comments","events_url":"https://api.github.com/repos/snap-stanford/snapvx/issues/5/events","html_url":"https://github.com/snap-stanford/snapvx/issues/5","id":109689259,"number":5,"title":"Segmentation fault","user":{"login":"quantdaddy","id":8163570,"avatar_url":"https://avatars.githubusercontent.com/u/8163570?v=3","gravatar_id":"","url":"https://api.github.com/users/quantdaddy","html_url":"https://github.com/quantdaddy","followers_url":"https://api.github.com/users/quantdaddy/followers","following_url":"https://api.github.com/users/quantdaddy/following{/other_user}","gists_url":"https://api.github.com/users/quantdaddy/gists{/gist_id}","starred_url":"https://api.github.com/users/quantdaddy/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/quantdaddy/subscriptions","organizations_url":"https://api.github.com/users/quantdaddy/orgs","repos_url":"https://api.github.com/users/quantdaddy/repos","events_url":"https://api.github.com/users/quantdaddy/events{/privacy}","received_events_url":"https://api.github.com/users/quantdaddy/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":4,"created_at":"2015-10-04T16:09:54Z","updated_at":"2015-10-23T01:18:09Z","closed_at":null,"body":"Hello, \r\n\r\nI'm trying to use snapvx on a t2.micro ec2 instance with 8Gb memory. I'm trying to define a network with 125145 nodes and 4129676 edges. The observed value for each node is a 3x1 vector. I'm getting segmentation fault error . Below is the code I'm using. Do you think I need more memory? \r\n\r\nThank you so much. \r\n\r\n'''>>> from snapvx import *\r\n>>> def node_obj(data):\r\n...   x = Variable(1,name='x');\r\n...   return power(norm(x - float(data[0])),2);\r\n... \r\n>>> def laplace_reg(src, dst, data):\r\n...   return norm(src['x'] - dst['x']);\r\n... \r\n>>> gvx = LoadEdgeList('edges_supervoxel.txt');\r\n>>> gvx.AddNodeObjectives('superVoxelMeans.csv', node_obj);\r\nSegmentation fault (core dumped)'''"},"comment":{"url":"https://api.github.com/repos/snap-stanford/snapvx/issues/comments/150400433","html_url":"https://github.com/snap-stanford/snapvx/issues/5#issuecomment-150400433","issue_url":"https://api.github.com/repos/snap-stanford/snapvx/issues/5","id":150400433,"user":{"login":"quantdaddy","id":8163570,"avatar_url":"https://avatars.githubusercontent.com/u/8163570?v=3","gravatar_id":"","url":"https://api.github.com/users/quantdaddy","html_url":"https://github.com/quantdaddy","followers_url":"https://api.github.com/users/quantdaddy/followers","following_url":"https://api.github.com/users/quantdaddy/following{/other_user}","gists_url":"https://api.github.com/users/quantdaddy/gists{/gist_id}","starred_url":"https://api.github.com/users/quantdaddy/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/quantdaddy/subscriptions","organizations_url":"https://api.github.com/users/quantdaddy/orgs","repos_url":"https://api.github.com/users/quantdaddy/repos","events_url":"https://api.github.com/users/quantdaddy/events{/privacy}","received_events_url":"https://api.github.com/users/quantdaddy/received_events","type":"User","site_admin":false},"created_at":"2015-10-23T01:18:09Z","updated_at":"2015-10-23T01:18:09Z","body":"Sorry, it turns out that the CPU had only 1GB of memory which might have\nbeen too small for the amount of data I had. ​\n\nOn Thu, Oct 8, 2015 at 11:49 PM, davidhallac <notifications@github.com>\nwrote:\n\n> Hmm, I was able to get your problem set up on our machines using ~2.5GB of\n> memory. You said the segfault occurs after AddNodeObjectives, right? Were\n> you able to get a smaller problem running on EC2, or did all SnapVX\n> problems cause issues? I don't have any AWS experience, but I could learn\n> and set something up if it appears like an EC2 problem.\n>\n> I should also note that a second issue does pop up. In your graph, some\n> nodes (for example node 10) have a degree of 0, so they are not\n> instantiated when you load the graph from edges_supervoxel.txt. This is\n> fine, but your csv file includes these nodes, so when you bulk load it gets\n> offset (for example thinking that row 10 belongs to node 11 in the graph).\n> Then, when it goes through all the nodes and still has data in the CSV\n> file, it throws an error because it does not know what to do with these\n> remaining rows. We have ways of specifying which nodes to bulk load, but we\n> do not let the user specify which rows of the csv file to ignore (i.e. row\n> 10). The easiest quick-fix is to delete the rows of nodes with no\n> neighbors, and in the meantime we can look into easier ways of handling\n> this through SnapVX\n>\n> —\n> Reply to this email directly or view it on GitHub\n> <https://github.com/snap-stanford/snapvx/issues/5#issuecomment-146748480>.\n>\n"}}