{"action":"closed","issue":{"url":"https://api.github.com/repos/NifTK/NiftyNet/issues/73","repository_url":"https://api.github.com/repos/NifTK/NiftyNet","labels_url":"https://api.github.com/repos/NifTK/NiftyNet/issues/73/labels{/name}","comments_url":"https://api.github.com/repos/NifTK/NiftyNet/issues/73/comments","events_url":"https://api.github.com/repos/NifTK/NiftyNet/issues/73/events","html_url":"https://github.com/NifTK/NiftyNet/issues/73","id":309897131,"node_id":"MDU6SXNzdWUzMDk4OTcxMzE=","number":73,"title":"3d image regression","user":{"login":"yenhochen","id":12815796,"node_id":"MDQ6VXNlcjEyODE1Nzk2","avatar_url":"https://avatars3.githubusercontent.com/u/12815796?v=4","gravatar_id":"","url":"https://api.github.com/users/yenhochen","html_url":"https://github.com/yenhochen","followers_url":"https://api.github.com/users/yenhochen/followers","following_url":"https://api.github.com/users/yenhochen/following{/other_user}","gists_url":"https://api.github.com/users/yenhochen/gists{/gist_id}","starred_url":"https://api.github.com/users/yenhochen/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/yenhochen/subscriptions","organizations_url":"https://api.github.com/users/yenhochen/orgs","repos_url":"https://api.github.com/users/yenhochen/repos","events_url":"https://api.github.com/users/yenhochen/events{/privacy}","received_events_url":"https://api.github.com/users/yenhochen/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2018-03-29T20:43:06Z","updated_at":"2018-09-11T13:42:10Z","closed_at":"2018-09-11T13:42:10Z","author_association":"NONE","body":"I'm trying to do a 3d image regression using the following configuration file. However, I keep getting nans during the training session. All of my images are standardized, cropped to the same dimension, and are given a generated mask. I assume the gradients are exploding. what can I do about this?\r\n\r\n[INPUT]\r\nspatial_window_size=(32,32,32)\r\ncsv_file=/work/radiology/s180052/TractTBI/test_in.csv\r\ninterp_order=3\r\n\r\n[OUTPUT]\r\nspatial_window_size=(32,32,32)\r\ncsv_file=/work/radiology/s180052/TractTBI/test_out.csv\r\ninterp_order=3\r\n\r\n[MASK]\r\nspatial_window_size=(32,32,32)\r\ncsv_file=/work/radiology/s180052/TractTBI/mask/mask.csv\r\ninterp_order=0\r\n\r\n\r\n[TRAINING]\r\nloss_type=RMSE\r\nsample_per_volume=32\r\nmax_iter=500\r\nsave_every_n=100\r\nmax_checkpoints=5\r\noptimiser=adam\r\nlr=0.00000005\r\nstarting_iter=0\r\nscaling_percentage=(-10.0, 10.0)\r\nrandom_flipping_axes= 0,1\r\n\r\nvalidation_every_n = 10\r\nexclude_fraction_for_inference = 0.15\r\nexclude_fraction_for_validation = 0.15\r\n\r\n[NETWORK]\r\nwindow_sampling=weighted\r\nname=highres3dnet_small\r\nactivation_function=prelu\r\nbatch_size=2\r\nvolume_padding_size=(0, 0, 0)\r\nwhitening=True\r\nnormalisation=False\r\n\r\n[SYSTEM]\r\ncuda_devices=0\r\nnum_gpus=1\r\nnum_threads=4\r\nqueue_length=256\r\nmodel_dir=/work/radiology/s180052/TractTBI/models\r\n\r\n[REGRESSION]\r\nimage=INPUT\r\noutput=OUTPUT\r\nsampler=MASK\r\nloss_border=8\r\nerror_map=True\r\n\r\n[INFERENCE]\r\nborder = (2,0,0)\r\noutput_interp_order = 3\r\nsave_seg_dir=/work/radiology/s180052/TractTBI/models/output\r\nspatial_window_size = (8,256,256)"}}
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