{"action":"opened","issue":{"url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1253","repository_url":"https://api.github.com/repos/NVIDIA/DIGITS","labels_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1253/labels{/name}","comments_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1253/comments","events_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1253/events","html_url":"https://github.com/NVIDIA/DIGITS/issues/1253","id":188543536,"number":1253,"title":"Error when adding dice.py python layer to caffe alex-net","user":{"login":"klaimane","id":23376544,"avatar_url":"https://avatars.githubusercontent.com/u/23376544?v=3","gravatar_id":"","url":"https://api.github.com/users/klaimane","html_url":"https://github.com/klaimane","followers_url":"https://api.github.com/users/klaimane/followers","following_url":"https://api.github.com/users/klaimane/following{/other_user}","gists_url":"https://api.github.com/users/klaimane/gists{/gist_id}","starred_url":"https://api.github.com/users/klaimane/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/klaimane/subscriptions","organizations_url":"https://api.github.com/users/klaimane/orgs","repos_url":"https://api.github.com/users/klaimane/repos","events_url":"https://api.github.com/users/klaimane/events{/privacy}","received_events_url":"https://api.github.com/users/klaimane/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2016-11-10T15:48:53Z","updated_at":"2016-11-10T15:48:53Z","closed_at":null,"body":"Hi,\r\n\r\nTrying to add Dice metric layer to network to manage dataset imbalance.\r\nI followed the instructions in the medical imaging example but receive error this when training the net:\r\n\r\n> ERROR: Check failed: registry.count(type) == 1 (0 vs. 1) Unknown layer type: Python (known types: AbsVal, Accuracy, ArgMax, BNLL, BatchNorm, BatchReindex, Bias, Concat, ContrastiveLoss, Convolution, Crop, Data, Deconvolution, Dropout, DummyData, ELU, Eltwise, Embed, EuclideanLoss, Exp, Filter, Flatten, HDF5Data, HDF5Output, HingeLoss, Im2col, ImageData, InfogainLoss, InnerProduct, Input, LRN, LSTM, LSTMUnit, Log, MVN, MemoryData, MultinomialLogisticLoss, PReLU, Parameter, Pooling, Power, RNN, ReLU, Reduction, Reshape, SPP, Scale, Sigmoid, SigmoidCrossEntropyLoss, Silence, Slice, Softmax, SoftmaxWithLoss, Split, TanH, Threshold, Tile, WindowData)\r\n\r\n**from output log:**\r\n\r\n> I1110 16:44:09.254968 172016 layer_factory.hpp:77] Creating layer dice\r\n\r\n> F1110 16:44:09.255031 172016 layer_factory.hpp:81] Check failed: registry.count(type) == 1 (0 vs. 1) Unknown layer type: Python (known types: AbsVal, Accuracy, ArgMax, BNLL, BatchNorm, BatchReindex, Bias, Concat, ContrastiveLoss, Convolution, Crop, Data, Deconvolution, Dropout, DummyData, ELU, Eltwise, Embed, EuclideanLoss, Exp, Filter, Flatten, HDF5Data, HDF5Output, HingeLoss, Im2col, ImageData, InfogainLoss, InnerProduct, Input, LRN, LSTM, LSTMUnit, Log, MVN, MemoryData, MultinomialLogisticLoss, PReLU, Parameter, Pooling, Power, RNN, ReLU, Reduction, Reshape, SPP, Scale, Sigmoid, SigmoidCrossEntropyLoss, Silence, Slice, Softmax, SoftmaxWithLoss, Split, TanH, Threshold, Tile, WindowData)\r\n\r\n> *** Check failure stack trace: ***\r\n> @     0x7ffff1b4c9fd  google::LogMessage::Fail()\r\n> @     0x7ffff1b4e7cc  google::LogMessage::SendToLog()\r\n> @     0x7ffff1b4c5ec  google::LogMessage::Flush()\r\n> @     0x7ffff1b4f0de  google::LogMessageFatal::~LogMessageFatal()\r\n> @     0x7ffff730079f  caffe::LayerRegistry<>::CreateLayer()\r\n> @     0x7ffff742544c  caffe::Net<>::Init()\r\n> @     0x7ffff7427545  caffe::Net<>::Net()\r\n> @     0x7ffff740cf3a  caffe::Solver<>::InitTrainNet()\r\n> @     0x7ffff740e03c  caffe::Solver<>::Init()\r\n> @     0x7ffff740e36a  caffe::Solver<>::Solver()\r\n> @     0x7ffff7400e23  caffe::Creator_SGDSolver<>()\r\n> @           0x410aed  caffe::SolverRegistry<>::CreateSolver()\r\n> @           0x409ec2  train()\r\n> @           0x40752c  main\r\n> @     0x7fffe9ebcb15  __libc_start_main\r\n> @           0x407d9d  (unknown)"}}
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