{"action":"created","issue":{"url":"https://api.github.com/repos/caseus-viridis/arnn-exp/issues/10","repository_url":"https://api.github.com/repos/caseus-viridis/arnn-exp","labels_url":"https://api.github.com/repos/caseus-viridis/arnn-exp/issues/10/labels{/name}","comments_url":"https://api.github.com/repos/caseus-viridis/arnn-exp/issues/10/comments","events_url":"https://api.github.com/repos/caseus-viridis/arnn-exp/issues/10/events","html_url":"https://github.com/caseus-viridis/arnn-exp/issues/10","id":336816740,"node_id":"MDU6SXNzdWUzMzY4MTY3NDA=","number":10,"title":"Deep supervised ARNN","user":{"login":"caseus-viridis","id":8757748,"node_id":"MDQ6VXNlcjg3NTc3NDg=","avatar_url":"https://avatars0.githubusercontent.com/u/8757748?v=4","gravatar_id":"","url":"https://api.github.com/users/caseus-viridis","html_url":"https://github.com/caseus-viridis","followers_url":"https://api.github.com/users/caseus-viridis/followers","following_url":"https://api.github.com/users/caseus-viridis/following{/other_user}","gists_url":"https://api.github.com/users/caseus-viridis/gists{/gist_id}","starred_url":"https://api.github.com/users/caseus-viridis/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/caseus-viridis/subscriptions","organizations_url":"https://api.github.com/users/caseus-viridis/orgs","repos_url":"https://api.github.com/users/caseus-viridis/repos","events_url":"https://api.github.com/users/caseus-viridis/events{/privacy}","received_events_url":"https://api.github.com/users/caseus-viridis/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":{"login":"caseus-viridis","id":8757748,"node_id":"MDQ6VXNlcjg3NTc3NDg=","avatar_url":"https://avatars0.githubusercontent.com/u/8757748?v=4","gravatar_id":"","url":"https://api.github.com/users/caseus-viridis","html_url":"https://github.com/caseus-viridis","followers_url":"https://api.github.com/users/caseus-viridis/followers","following_url":"https://api.github.com/users/caseus-viridis/following{/other_user}","gists_url":"https://api.github.com/users/caseus-viridis/gists{/gist_id}","starred_url":"https://api.github.com/users/caseus-viridis/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/caseus-viridis/subscriptions","organizations_url":"https://api.github.com/users/caseus-viridis/orgs","repos_url":"https://api.github.com/users/caseus-viridis/repos","events_url":"https://api.github.com/users/caseus-viridis/events{/privacy}","received_events_url":"https://api.github.com/users/caseus-viridis/received_events","type":"User","site_admin":false},"assignees":[{"login":"caseus-viridis","id":8757748,"node_id":"MDQ6VXNlcjg3NTc3NDg=","avatar_url":"https://avatars0.githubusercontent.com/u/8757748?v=4","gravatar_id":"","url":"https://api.github.com/users/caseus-viridis","html_url":"https://github.com/caseus-viridis","followers_url":"https://api.github.com/users/caseus-viridis/followers","following_url":"https://api.github.com/users/caseus-viridis/following{/other_user}","gists_url":"https://api.github.com/users/caseus-viridis/gists{/gist_id}","starred_url":"https://api.github.com/users/caseus-viridis/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/caseus-viridis/subscriptions","organizations_url":"https://api.github.com/users/caseus-viridis/orgs","repos_url":"https://api.github.com/users/caseus-viridis/repos","events_url":"https://api.github.com/users/caseus-viridis/events{/privacy}","received_events_url":"https://api.github.com/users/caseus-viridis/received_events","type":"User","site_admin":false}],"milestone":null,"comments":0,"created_at":"2018-06-28T23:48:05Z","updated_at":"2018-06-29T21:16:15Z","closed_at":null,"author_association":"OWNER","body":"Make all weights shared but exit on each step"},"comment":{"url":"https://api.github.com/repos/caseus-viridis/arnn-exp/issues/comments/401476165","html_url":"https://github.com/caseus-viridis/arnn-exp/issues/10#issuecomment-401476165","issue_url":"https://api.github.com/repos/caseus-viridis/arnn-exp/issues/10","id":401476165,"node_id":"MDEyOklzc3VlQ29tbWVudDQwMTQ3NjE2NQ==","user":{"login":"caseus-viridis","id":8757748,"node_id":"MDQ6VXNlcjg3NTc3NDg=","avatar_url":"https://avatars0.githubusercontent.com/u/8757748?v=4","gravatar_id":"","url":"https://api.github.com/users/caseus-viridis","html_url":"https://github.com/caseus-viridis","followers_url":"https://api.github.com/users/caseus-viridis/followers","following_url":"https://api.github.com/users/caseus-viridis/following{/other_user}","gists_url":"https://api.github.com/users/caseus-viridis/gists{/gist_id}","starred_url":"https://api.github.com/users/caseus-viridis/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/caseus-viridis/subscriptions","organizations_url":"https://api.github.com/users/caseus-viridis/orgs","repos_url":"https://api.github.com/users/caseus-viridis/repos","events_url":"https://api.github.com/users/caseus-viridis/events{/privacy}","received_events_url":"https://api.github.com/users/caseus-viridis/received_events","type":"User","site_admin":false},"created_at":"2018-06-29T21:16:15Z","updated_at":"2018-06-29T21:16:15Z","author_association":"OWNER","body":"Does not really work sharing the entire stack:  `python train_cifar10.py -d4 -w1 --share-all-blocks`\r\n```\r\nARNN(\r\n  (head): Conv2d(3, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\r\n  (body): ModuleList(\r\n    (0): ARNNCellStack(\r\n      (0): ARNNCell(\r\n        (head): BNReLUConv(\r\n          (bn): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\r\n          (conv): Conv2d(16, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\r\n        )\r\n        (body): BNReLUConv(\r\n          (bn): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\r\n          (conv): Conv2d(16, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\r\n        )\r\n      )\r\n      (1): ARNNCell(\r\n        (head): BNReLUConv(\r\n          (bn): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\r\n          (conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\r\n        )\r\n        (body): BNReLUConv(\r\n          (bn): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\r\n          (conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\r\n        )\r\n        (arm): BNReLUConv(\r\n          (bn): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\r\n          (conv): Conv2d(16, 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\r\n        )\r\n      )\r\n      (2): ARNNCell(\r\n        (head): BNReLUConv(\r\n          (bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\r\n          (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\r\n        )\r\n        (body): BNReLUConv(\r\n          (bn): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\r\n          (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\r\n        )\r\n        (arm): BNReLUConv(\r\n          (bn): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\r\n          (conv): Conv2d(32, 64, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\r\n        )\r\n      )\r\n    )\r\n  )\r\n  (tail): Sequential(\r\n    (0): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\r\n    (1): ReLU()\r\n    (2): AvgPool2d(kernel_size=8, stride=1, padding=0)\r\n    (3): Flatten()\r\n    (4): Linear(in_features=64, out_features=10, bias=True)\r\n  )\r\n)\r\nNumber of parameters = 121562\r\nEpoch   0: training loss = 1.4069, test loss = 3.0790,3.3621,3.4227,3.6745\r\n        correct% = 10.08,12.15,20.34,25.87\r\nEpoch   1: training loss = 1.0525, test loss = 2.1189,2.5401,4.2019,5.9344\r\n        correct% = 23.94,24.31,25.06,25.38\r\nEpoch   2: training loss = 0.9096, test loss = 2.4966,2.3651,3.5872,5.2659\r\n        correct% = 17.20,27.99,21.45,23.52\r\nEpoch   3: training loss = 0.8156, test loss = 2.4729,2.3645,2.1394,2.0171\r\n        correct% = 14.34,23.24,31.70,39.05\r\nEpoch   4: training loss = 0.7488, test loss = 2.4353,2.3997,2.3867,2.4475\r\n        correct% = 17.55,21.16,27.53,32.78\r\nEpoch   5: training loss = 0.6930, test loss = 2.6306,2.9355,3.7191,4.1555\r\n        correct% = 17.04,17.20,18.83,20.99\r\nEpoch   6: training loss = 0.6553, test loss = 2.6096,3.3484,4.2337,3.9121\r\n        correct% = 18.08,13.67,13.72,20.80\r\nEpoch   7: training loss = 0.6231, test loss = 3.4534,5.9763,7.5724,7.2377\r\n        correct% = 11.06,10.16,10.83,14.66\r\nEpoch   8: training loss = 0.5965, test loss = 2.7204,2.9072,3.4840,3.7327\r\n        correct% = 11.26,14.69,13.59,16.14\r\nEpoch   9: training loss = 0.5795, test loss = 2.7541,2.7525,2.6332,3.0217\r\n        correct% = 10.35,13.94,22.14,19.95\r\nEpoch  10: training loss = 0.5620, test loss = 2.9409,3.1817,3.7529,4.0479\r\n        correct% = 12.94,13.80,12.56,16.48\r\nEpoch  11: training loss = 0.5507, test loss = 2.7946,2.7999,2.8886,3.1588\r\n        correct% = 10.43,14.79,18.48,19.07\r\nEpoch  12: training loss = 0.5409, test loss = 2.6748,2.6850,3.0198,4.3511\r\n        correct% = 11.21,13.76,17.82,13.47\r\nEpoch  13: training loss = 0.5298, test loss = 2.7396,2.8378,3.0063,3.6641\r\n        correct% = 15.79,16.45,16.25,12.92\r\nEpoch  14: training loss = 0.5190, test loss = 2.9744,2.9852,2.8801,3.3676\r\n        correct% = 12.94,14.96,21.52,14.86\r\n```"}}
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