{"action":"created","issue":{"url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1219","repository_url":"https://api.github.com/repos/NVIDIA/DIGITS","labels_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1219/labels{/name}","comments_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1219/comments","events_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1219/events","html_url":"https://github.com/NVIDIA/DIGITS/issues/1219","id":185320943,"number":1219,"title":"Semantic segmentation, net_surgery.py error","user":{"login":"imrael202","id":20860578,"avatar_url":"https://avatars.githubusercontent.com/u/20860578?v=3","gravatar_id":"","url":"https://api.github.com/users/imrael202","html_url":"https://github.com/imrael202","followers_url":"https://api.github.com/users/imrael202/followers","following_url":"https://api.github.com/users/imrael202/following{/other_user}","gists_url":"https://api.github.com/users/imrael202/gists{/gist_id}","starred_url":"https://api.github.com/users/imrael202/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/imrael202/subscriptions","organizations_url":"https://api.github.com/users/imrael202/orgs","repos_url":"https://api.github.com/users/imrael202/repos","events_url":"https://api.github.com/users/imrael202/events{/privacy}","received_events_url":"https://api.github.com/users/imrael202/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/NVIDIA/DIGITS/labels/question","name":"question","color":"cc317c"}],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2016-10-26T07:52:52Z","updated_at":"2016-10-26T08:58:03Z","closed_at":null,"body":"Hello\r\ni follow instructions [here](https://github.com/NVIDIA/DIGITS/tree/200d7c4b7e26ed14bf85d32ee40bc03bb63c85fd/examples/semantic-segmentation)\r\nwhen i try to ./net_surgery.py it is an error\r\n```\r\n./net_surgery.py\r\nDownloading files (this might take a few minutes)...\r\nDownloading https://raw.githubusercontent.com/BVLC/caffe/rc3/models/bvlc_alexnet/deploy.prototxt...\r\nDownloading http://dl.caffe.berkeleyvision.org/bvlc_alexnet.caffemodel...\r\nLoading Alexnet model...\r\nWARNING: Logging before InitGoogleLogging() is written to STDERR\r\nI1026 11:35:47.297135 39779 net.cpp:52] Initializing net from parameters:\r\nname: \"AlexNet\"\r\ninput: \"data\"\r\nstate {\r\n  phase: TEST\r\n}\r\ninput_shape {\r\n  dim: 10\r\n  dim: 3\r\n  dim: 227\r\n  dim: 227\r\n}\r\nlayer {\r\n  name: \"conv1\"\r\n  type: \"Convolution\"\r\n  bottom: \"data\"\r\n  top: \"conv1\"\r\n  param {\r\n    lr_mult: 1\r\n    decay_mult: 1\r\n  }\r\n  param {\r\n    lr_mult: 2\r\n    decay_mult: 0\r\n  }\r\n  convolution_param {\r\n    num_output: 96\r\n    kernel_size: 11\r\n    stride: 4\r\n  }\r\n}\r\nlayer {\r\n  name: \"relu1\"\r\n  type: \"ReLU\"\r\n  bottom: \"conv1\"\r\n  top: \"conv1\"\r\n}\r\nlayer {\r\n  name: \"norm1\"\r\n  type: \"LRN\"\r\n  bottom: \"conv1\"\r\n  top: \"norm1\"\r\n  lrn_param {\r\n    local_size: 5\r\n    alpha: 0.0001\r\n    beta: 0.75\r\n  }\r\n}\r\nlayer {\r\n  name: \"pool1\"\r\n  type: \"Pooling\"\r\n  bottom: \"norm1\"\r\n  top: \"pool1\"\r\n  pooling_param {\r\n    pool: MAX\r\n    kernel_size: 3\r\n    stride: 2\r\n  }\r\n}\r\nlayer {\r\n  name: \"conv2\"\r\n  type: \"Convolution\"\r\n  bottom: \"pool1\"\r\n  top: \"conv2\"\r\n  param {\r\n    lr_mult: 1\r\n    decay_mult: 1\r\n  }\r\n  param {\r\n    lr_mult: 2\r\n    decay_mult: 0\r\n  }\r\n  convolution_param {\r\n    num_output: 256\r\n    pad: 2\r\n    kernel_size: 5\r\n    group: 2\r\n  }\r\n}\r\nlayer {\r\n  name: \"relu2\"\r\n  type: \"ReLU\"\r\n  bottom: \"conv2\"\r\n  top: \"conv2\"\r\n}\r\nlayer {\r\n  name: \"norm2\"\r\n  type: \"LRN\"\r\n  bottom: \"conv2\"\r\n  top: \"norm2\"\r\n  lrn_param {\r\n    local_size: 5\r\n    alpha: 0.0001\r\n    beta: 0.75\r\n  }\r\n}\r\nlayer {\r\n  name: \"pool2\"\r\n  type: \"Pooling\"\r\n  bottom: \"norm2\"\r\n  top: \"pool2\"\r\n  pooling_param {\r\n    pool: MAX\r\n    kernel_size: 3\r\n    stride: 2\r\n  }\r\n}\r\nlayer {\r\n  name: \"conv3\"\r\n  type: \"Convolution\"\r\n  bottom: \"pool2\"\r\n  top: \"conv3\"\r\n  param {\r\n    lr_mult: 1\r\n    decay_mult: 1\r\n  }\r\n  param {\r\n    lr_mult: 2\r\n    decay_mult: 0\r\n  }\r\n  convolution_param {\r\n    num_output: 384\r\n    pad: 1\r\n    kernel_size: 3\r\n  }\r\n}\r\nlayer {\r\n  name: \"relu3\"\r\n  type: \"ReLU\"\r\n  bottom: \"conv3\"\r\n  top: \"conv3\"\r\n}\r\nlayer {\r\n  name: \"conv4\"\r\n  type: \"Convolution\"\r\n  bottom: \"conv3\"\r\n  top: \"conv4\"\r\n  param {\r\n    lr_mult: 1\r\n    decay_mult: 1\r\n  }\r\n  param {\r\n    lr_mult: 2\r\n    decay_mult: 0\r\n  }\r\n  convolution_param {\r\n    num_output: 384\r\n    pad: 1\r\n    kernel_size: 3\r\n    group: 2\r\n  }\r\n}\r\nlayer {\r\n  name: \"relu4\"\r\n  type: \"ReLU\"\r\n  bottom: \"conv4\"\r\n  top: \"conv4\"\r\n}\r\nlayer {\r\n  name: \"conv5\"\r\n  type: \"Convolution\"\r\n  bottom: \"conv4\"\r\n  top: \"conv5\"\r\n  param {\r\n    lr_mult: 1\r\n    decay_mult: 1\r\n  }\r\n  param {\r\n    lr_mult: 2\r\n    decay_mult: 0\r\n  }\r\n  convolution_param {\r\n    num_output: 256\r\n    pad: 1\r\n    kernel_size: 3\r\n    group: 2\r\n  }\r\n}\r\nlayer {\r\n  name: \"relu5\"\r\n  type: \"ReLU\"\r\n  bottom: \"conv5\"\r\n  top: \"conv5\"\r\n}\r\nlayer {\r\n  name: \"pool5\"\r\n  type: \"Pooling\"\r\n  bottom: \"conv5\"\r\n  top: \"pool5\"\r\n  pooling_param {\r\n    pool: MAX\r\n    kernel_size: 3\r\n    stride: 2\r\n  }\r\n}\r\nlayer {\r\n  name: \"fc6\"\r\n  type: \"InnerProduct\"\r\n  bottom: \"pool5\"\r\n  top: \"fc6\"\r\n  param {\r\n    lr_mult: 1\r\n    decay_mult: 1\r\n  }\r\n  param {\r\n    lr_mult: 2\r\n    decay_mult: 0\r\n  }\r\n  inner_product_param {\r\n    num_output: 4096\r\n  }\r\n}\r\nlayer {\r\n  name: \"relu6\"\r\n  type: \"ReLU\"\r\n  bottom: \"fc6\"\r\n  top: \"fc6\"\r\n}\r\nlayer {\r\n  name: \"drop6\"\r\n  type: \"Dropout\"\r\n  bottom: \"fc6\"\r\n  top: \"fc6\"\r\n  dropout_param {\r\n    dropout_ratio: 0.5\r\n  }\r\n}\r\nlayer {\r\n  name: \"fc7\"\r\n  type: \"InnerProduct\"\r\n  bottom: \"fc6\"\r\n  top: \"fc7\"\r\n  param {\r\n    lr_mult: 1\r\n    decay_mult: 1\r\n  }\r\n  param {\r\n    lr_mult: 2\r\n    decay_mult: 0\r\n  }\r\n  inner_product_param {\r\n    num_output: 4096\r\n  }\r\n}\r\nlayer {\r\n  name: \"relu7\"\r\n  type: \"ReLU\"\r\n  bottom: \"fc7\"\r\n  top: \"fc7\"\r\n}\r\nlayer {\r\n  name: \"drop7\"\r\n  type: \"Dropout\"\r\n  bottom: \"fc7\"\r\n  top: \"fc7\"\r\n  dropout_param {\r\n    dropout_ratio: 0.5\r\n  }\r\n}\r\nlayer {\r\n  name: \"fc8\"\r\n  type: \"InnerProduct\"\r\n  bottom: \"fc7\"\r\n  top: \"fc8\"\r\n  param {\r\n    lr_mult: 1\r\n    decay_mult: 1\r\n  }\r\n  param {\r\n    lr_mult: 2\r\n    decay_mult: 0\r\n  }\r\n  inner_product_param {\r\n    num_output: 1000\r\n  }\r\n}\r\nlayer {\r\n  name: \"prob\"\r\n  type: \"Softmax\"\r\n  bottom: \"fc8\"\r\n  top: \"prob\"\r\n}\r\nI1026 11:35:47.303450 39779 net.cpp:416] Input 0 -> data\r\nI1026 11:35:47.307706 39779 layer_factory.hpp:76] Creating layer conv1\r\nI1026 11:35:47.307770 39779 net.cpp:109] Creating Layer conv1\r\nI1026 11:35:47.307785 39779 net.cpp:457] conv1 <- data\r\nI1026 11:35:47.307801 39779 net.cpp:414] conv1 -> conv1\r\nI1026 11:35:47.386621 39779 net.cpp:153] Setting up conv1\r\nI1026 11:35:47.386705 39779 net.cpp:160] Top shape: 10 96 55 55 (2904000)\r\nI1026 11:35:47.386721 39779 net.cpp:168] Memory required for data: 11616000\r\nI1026 11:35:47.386976 39779 layer_factory.hpp:76] Creating layer relu1\r\nI1026 11:35:47.387012 39779 net.cpp:109] Creating Layer relu1\r\nI1026 11:35:47.387029 39779 net.cpp:457] relu1 <- conv1\r\nI1026 11:35:47.387048 39779 net.cpp:400] relu1 -> conv1 (in-place)\r\nI1026 11:35:47.388077 39779 net.cpp:153] Setting up relu1\r\nI1026 11:35:47.388113 39779 net.cpp:160] Top shape: 10 96 55 55 (2904000)\r\nI1026 11:35:47.388126 39779 net.cpp:168] Memory required for data: 23232000\r\nI1026 11:35:47.388139 39779 layer_factory.hpp:76] Creating layer norm1\r\nI1026 11:35:47.388164 39779 net.cpp:109] Creating Layer norm1\r\nI1026 11:35:47.388177 39779 net.cpp:457] norm1 <- conv1\r\nI1026 11:35:47.388197 39779 net.cpp:414] norm1 -> norm1\r\nI1026 11:35:47.388231 39779 net.cpp:153] Setting up norm1\r\nI1026 11:35:47.388249 39779 net.cpp:160] Top shape: 10 96 55 55 (2904000)\r\nI1026 11:35:47.388303 39779 net.cpp:168] Memory required for data: 34848000\r\nI1026 11:35:47.388321 39779 layer_factory.hpp:76] Creating layer pool1\r\nI1026 11:35:47.388362 39779 net.cpp:109] Creating Layer pool1\r\nI1026 11:35:47.388381 39779 net.cpp:457] pool1 <- norm1\r\nI1026 11:35:47.388419 39779 net.cpp:414] pool1 -> pool1\r\nI1026 11:35:47.388463 39779 net.cpp:153] Setting up pool1\r\nI1026 11:35:47.388496 39779 net.cpp:160] Top shape: 10 96 27 27 (699840)\r\nI1026 11:35:47.388512 39779 net.cpp:168] Memory required for data: 37647360\r\nI1026 11:35:47.388523 39779 layer_factory.hpp:76] Creating layer conv2\r\nI1026 11:35:47.388567 39779 net.cpp:109] Creating Layer conv2\r\nI1026 11:35:47.388586 39779 net.cpp:457] conv2 <- pool1\r\nI1026 11:35:47.388622 39779 net.cpp:414] conv2 -> conv2\r\nI1026 11:35:47.389605 39779 net.cpp:153] Setting up conv2\r\nI1026 11:35:47.389636 39779 net.cpp:160] Top shape: 10 256 27 27 (1866240)\r\nI1026 11:35:47.389649 39779 net.cpp:168] Memory required for data: 45112320\r\nI1026 11:35:47.389668 39779 layer_factory.hpp:76] Creating layer relu2\r\nI1026 11:35:47.389689 39779 net.cpp:109] Creating Layer relu2\r\nI1026 11:35:47.389703 39779 net.cpp:457] relu2 <- conv2\r\nI1026 11:35:47.389719 39779 net.cpp:400] relu2 -> conv2 (in-place)\r\nI1026 11:35:47.389762 39779 net.cpp:153] Setting up relu2\r\nI1026 11:35:47.389786 39779 net.cpp:160] Top shape: 10 256 27 27 (1866240)\r\nI1026 11:35:47.389816 39779 net.cpp:168] Memory required for data: 52577280\r\nI1026 11:35:47.389835 39779 layer_factory.hpp:76] Creating layer norm2\r\nI1026 11:35:47.389874 39779 net.cpp:109] Creating Layer norm2\r\nI1026 11:35:47.389894 39779 net.cpp:457] norm2 <- conv2\r\nI1026 11:35:47.389925 39779 net.cpp:414] norm2 -> norm2\r\nI1026 11:35:47.389947 39779 net.cpp:153] Setting up norm2\r\nI1026 11:35:47.389986 39779 net.cpp:160] Top shape: 10 256 27 27 (1866240)\r\nI1026 11:35:47.390017 39779 net.cpp:168] Memory required for data: 60042240\r\nI1026 11:35:47.390034 39779 layer_factory.hpp:76] Creating layer pool2\r\nI1026 11:35:47.390053 39779 net.cpp:109] Creating Layer pool2\r\nI1026 11:35:47.390089 39779 net.cpp:457] pool2 <- norm2\r\nI1026 11:35:47.390125 39779 net.cpp:414] pool2 -> pool2\r\nI1026 11:35:47.390151 39779 net.cpp:153] Setting up pool2\r\nI1026 11:35:47.390182 39779 net.cpp:160] Top shape: 10 256 13 13 (432640)\r\nI1026 11:35:47.390194 39779 net.cpp:168] Memory required for data: 61772800\r\nI1026 11:35:47.390228 39779 layer_factory.hpp:76] Creating layer conv3\r\nI1026 11:35:47.390271 39779 net.cpp:109] Creating Layer conv3\r\nI1026 11:35:47.390292 39779 net.cpp:457] conv3 <- pool2\r\nI1026 11:35:47.390323 39779 net.cpp:414] conv3 -> conv3\r\nI1026 11:35:47.392560 39779 net.cpp:153] Setting up conv3\r\nI1026 11:35:47.392590 39779 net.cpp:160] Top shape: 10 384 13 13 (648960)\r\nI1026 11:35:47.392606 39779 net.cpp:168] Memory required for data: 64368640\r\nI1026 11:35:47.392624 39779 layer_factory.hpp:76] Creating layer relu3\r\nI1026 11:35:47.392645 39779 net.cpp:109] Creating Layer relu3\r\nI1026 11:35:47.392659 39779 net.cpp:457] relu3 <- conv3\r\nI1026 11:35:47.392675 39779 net.cpp:400] relu3 -> conv3 (in-place)\r\nI1026 11:35:47.392712 39779 net.cpp:153] Setting up relu3\r\nI1026 11:35:47.392734 39779 net.cpp:160] Top shape: 10 384 13 13 (648960)\r\nI1026 11:35:47.392747 39779 net.cpp:168] Memory required for data: 66964480\r\nI1026 11:35:47.392782 39779 layer_factory.hpp:76] Creating layer conv4\r\nI1026 11:35:47.392807 39779 net.cpp:109] Creating Layer conv4\r\nI1026 11:35:47.392843 39779 net.cpp:457] conv4 <- conv3\r\nI1026 11:35:47.392877 39779 net.cpp:414] conv4 -> conv4\r\nI1026 11:35:47.394611 39779 net.cpp:153] Setting up conv4\r\nI1026 11:35:47.394641 39779 net.cpp:160] Top shape: 10 384 13 13 (648960)\r\nI1026 11:35:47.394656 39779 net.cpp:168] Memory required for data: 69560320\r\nI1026 11:35:47.394672 39779 layer_factory.hpp:76] Creating layer relu4\r\nI1026 11:35:47.394690 39779 net.cpp:109] Creating Layer relu4\r\nI1026 11:35:47.394703 39779 net.cpp:457] relu4 <- conv4\r\nI1026 11:35:47.394719 39779 net.cpp:400] relu4 -> conv4 (in-place)\r\nI1026 11:35:47.394737 39779 net.cpp:153] Setting up relu4\r\nI1026 11:35:47.394778 39779 net.cpp:160] Top shape: 10 384 13 13 (648960)\r\nI1026 11:35:47.394793 39779 net.cpp:168] Memory required for data: 72156160\r\nI1026 11:35:47.394804 39779 layer_factory.hpp:76] Creating layer conv5\r\nI1026 11:35:47.394850 39779 net.cpp:109] Creating Layer conv5\r\nI1026 11:35:47.394865 39779 net.cpp:457] conv5 <- conv4\r\nI1026 11:35:47.394881 39779 net.cpp:414] conv5 -> conv5\r\nI1026 11:35:47.396128 39779 net.cpp:153] Setting up conv5\r\nI1026 11:35:47.396157 39779 net.cpp:160] Top shape: 10 256 13 13 (432640)\r\nI1026 11:35:47.396169 39779 net.cpp:168] Memory required for data: 73886720\r\nI1026 11:35:47.396188 39779 layer_factory.hpp:76] Creating layer relu5\r\nI1026 11:35:47.396209 39779 net.cpp:109] Creating Layer relu5\r\nI1026 11:35:47.396224 39779 net.cpp:457] relu5 <- conv5\r\nI1026 11:35:47.396239 39779 net.cpp:400] relu5 -> conv5 (in-place)\r\nI1026 11:35:47.396255 39779 net.cpp:153] Setting up relu5\r\nI1026 11:35:47.396294 39779 net.cpp:160] Top shape: 10 256 13 13 (432640)\r\nI1026 11:35:47.396309 39779 net.cpp:168] Memory required for data: 75617280\r\nI1026 11:35:47.396322 39779 layer_factory.hpp:76] Creating layer pool5\r\nI1026 11:35:47.396363 39779 net.cpp:109] Creating Layer pool5\r\nI1026 11:35:47.396378 39779 net.cpp:457] pool5 <- conv5\r\nI1026 11:35:47.396394 39779 net.cpp:414] pool5 -> pool5\r\nI1026 11:35:47.396414 39779 net.cpp:153] Setting up pool5\r\nI1026 11:35:47.396453 39779 net.cpp:160] Top shape: 10 256 6 6 (92160)\r\nI1026 11:35:47.396469 39779 net.cpp:168] Memory required for data: 75985920\r\nI1026 11:35:47.396482 39779 layer_factory.hpp:76] Creating layer fc6\r\nI1026 11:35:47.396508 39779 net.cpp:109] Creating Layer fc6\r\nI1026 11:35:47.396523 39779 net.cpp:457] fc6 <- pool5\r\nI1026 11:35:47.396561 39779 net.cpp:414] fc6 -> fc6\r\nI1026 11:35:47.466017 39779 net.cpp:153] Setting up fc6\r\nI1026 11:35:47.466096 39779 net.cpp:160] Top shape: 10 4096 (40960)\r\nI1026 11:35:47.466109 39779 net.cpp:168] Memory required for data: 76149760\r\nI1026 11:35:47.466132 39779 layer_factory.hpp:76] Creating layer relu6\r\nI1026 11:35:47.466161 39779 net.cpp:109] Creating Layer relu6\r\nI1026 11:35:47.466174 39779 net.cpp:457] relu6 <- fc6\r\nI1026 11:35:47.466193 39779 net.cpp:400] relu6 -> fc6 (in-place)\r\nI1026 11:35:47.466223 39779 net.cpp:153] Setting up relu6\r\nI1026 11:35:47.466238 39779 net.cpp:160] Top shape: 10 4096 (40960)\r\nI1026 11:35:47.466255 39779 net.cpp:168] Memory required for data: 76313600\r\nI1026 11:35:47.466313 39779 layer_factory.hpp:76] Creating layer drop6\r\nI1026 11:35:47.467512 39779 net.cpp:109] Creating Layer drop6\r\nI1026 11:35:47.467548 39779 net.cpp:457] drop6 <- fc6\r\nI1026 11:35:47.467572 39779 net.cpp:400] drop6 -> fc6 (in-place)\r\nI1026 11:35:47.467599 39779 net.cpp:153] Setting up drop6\r\nI1026 11:35:47.467617 39779 net.cpp:160] Top shape: 10 4096 (40960)\r\nI1026 11:35:47.467629 39779 net.cpp:168] Memory required for data: 76477440\r\nI1026 11:35:47.467643 39779 layer_factory.hpp:76] Creating layer fc7\r\nI1026 11:35:47.467702 39779 net.cpp:109] Creating Layer fc7\r\nI1026 11:35:47.467720 39779 net.cpp:457] fc7 <- fc6\r\nI1026 11:35:47.467761 39779 net.cpp:414] fc7 -> fc7\r\nI1026 11:35:47.498826 39779 net.cpp:153] Setting up fc7\r\nI1026 11:35:47.498908 39779 net.cpp:160] Top shape: 10 4096 (40960)\r\nI1026 11:35:47.498920 39779 net.cpp:168] Memory required for data: 76641280\r\nI1026 11:35:47.498944 39779 layer_factory.hpp:76] Creating layer relu7\r\nI1026 11:35:47.498970 39779 net.cpp:109] Creating Layer relu7\r\nI1026 11:35:47.498983 39779 net.cpp:457] relu7 <- fc7\r\nI1026 11:35:47.499001 39779 net.cpp:400] relu7 -> fc7 (in-place)\r\nI1026 11:35:47.499027 39779 net.cpp:153] Setting up relu7\r\nI1026 11:35:47.499042 39779 net.cpp:160] Top shape: 10 4096 (40960)\r\nI1026 11:35:47.499060 39779 net.cpp:168] Memory required for data: 76805120\r\nI1026 11:35:47.499119 39779 layer_factory.hpp:76] Creating layer drop7\r\nI1026 11:35:47.499153 39779 net.cpp:109] Creating Layer drop7\r\nI1026 11:35:47.499171 39779 net.cpp:457] drop7 <- fc7\r\nI1026 11:35:47.499210 39779 net.cpp:400] drop7 -> fc7 (in-place)\r\nI1026 11:35:47.499234 39779 net.cpp:153] Setting up drop7\r\nI1026 11:35:47.499250 39779 net.cpp:160] Top shape: 10 4096 (40960)\r\nI1026 11:35:47.499264 39779 net.cpp:168] Memory required for data: 76968960\r\nI1026 11:35:47.499274 39779 layer_factory.hpp:76] Creating layer fc8\r\nI1026 11:35:47.499316 39779 net.cpp:109] Creating Layer fc8\r\nI1026 11:35:47.499333 39779 net.cpp:457] fc8 <- fc7\r\nI1026 11:35:47.499349 39779 net.cpp:414] fc8 -> fc8\r\nI1026 11:35:47.506927 39779 net.cpp:153] Setting up fc8\r\nI1026 11:35:47.507002 39779 net.cpp:160] Top shape: 10 1000 (10000)\r\nI1026 11:35:47.507015 39779 net.cpp:168] Memory required for data: 77008960\r\nI1026 11:35:47.507035 39779 layer_factory.hpp:76] Creating layer prob\r\nI1026 11:35:47.507076 39779 net.cpp:109] Creating Layer prob\r\nI1026 11:35:47.507098 39779 net.cpp:457] prob <- fc8\r\nI1026 11:35:47.507161 39779 net.cpp:414] prob -> prob\r\nI1026 11:35:47.507230 39779 net.cpp:153] Setting up prob\r\nI1026 11:35:47.507254 39779 net.cpp:160] Top shape: 10 1000 (10000)\r\nI1026 11:35:47.507287 39779 net.cpp:168] Memory required for data: 77048960\r\nI1026 11:35:47.507302 39779 net.cpp:231] prob does not need backward computation.\r\nI1026 11:35:47.507319 39779 net.cpp:231] fc8 does not need backward computation.\r\nI1026 11:35:47.507333 39779 net.cpp:231] drop7 does not need backward computation.\r\nI1026 11:35:47.507346 39779 net.cpp:231] relu7 does not need backward computation.\r\nI1026 11:35:47.507359 39779 net.cpp:231] fc7 does not need backward computation.\r\nI1026 11:35:47.507370 39779 net.cpp:231] drop6 does not need backward computation.\r\nI1026 11:35:47.507382 39779 net.cpp:231] relu6 does not need backward computation.\r\nI1026 11:35:47.507396 39779 net.cpp:231] fc6 does not need backward computation.\r\nI1026 11:35:47.507410 39779 net.cpp:231] pool5 does not need backward computation.\r\nI1026 11:35:47.507421 39779 net.cpp:231] relu5 does not need backward computation.\r\nI1026 11:35:47.507432 39779 net.cpp:231] conv5 does not need backward computation.\r\nI1026 11:35:47.507464 39779 net.cpp:231] relu4 does not need backward computation.\r\nI1026 11:35:47.507483 39779 net.cpp:231] conv4 does not need backward computation.\r\nI1026 11:35:47.507498 39779 net.cpp:231] relu3 does not need backward computation.\r\nI1026 11:35:47.507511 39779 net.cpp:231] conv3 does not need backward computation.\r\nI1026 11:35:47.507526 39779 net.cpp:231] pool2 does not need backward computation.\r\nI1026 11:35:47.507557 39779 net.cpp:231] norm2 does not need backward computation.\r\nI1026 11:35:47.507575 39779 net.cpp:231] relu2 does not need backward computation.\r\nI1026 11:35:47.507588 39779 net.cpp:231] conv2 does not need backward computation.\r\nI1026 11:35:47.507602 39779 net.cpp:231] pool1 does not need backward computation.\r\nI1026 11:35:47.507616 39779 net.cpp:231] norm1 does not need backward computation.\r\nI1026 11:35:47.507652 39779 net.cpp:231] relu1 does not need backward computation.\r\nI1026 11:35:47.507668 39779 net.cpp:231] conv1 does not need backward computation.\r\nI1026 11:35:47.507681 39779 net.cpp:273] This network produces output prob\r\nI1026 11:35:47.507710 39779 net.cpp:286] Network initialization done.\r\nI1026 11:35:48.051743 39779 upgrade_proto.cpp:609] Attempting to upgrade input file specified using deprecated transformation parameters: bvlc_alexnet.caffemodel\r\nI1026 11:35:48.051813 39779 upgrade_proto.cpp:612] Successfully upgraded file specified using deprecated data transformation parameters.\r\nW1026 11:35:48.051827 39779 upgrade_proto.cpp:614] Note that future Caffe releases will only support transform_param messages for transformation fields.\r\nI1026 11:35:48.051841 39779 upgrade_proto.cpp:618] Attempting to upgrade input file specified using deprecated V1LayerParameter: bvlc_alexnet.caffemodel\r\nI1026 11:35:48.313885 39779 upgrade_proto.cpp:626] Successfully upgraded file specified using deprecated V1LayerParameter\r\nLoading FCN-Alexnet prototxt...\r\n[libprotobuf ERROR google/protobuf/text_format.cc:245] Error parsing text-format caffe.NetParameter: 269:14: Message type \"caffe.LayerParameter\" has no field named \"crop_param\".\r\nF1026 11:35:48.373462 39779 upgrade_proto.cpp:928] Check failed: ReadProtoFromTextFile(param_file, param) Failed to parse NetParameter file: fcn_alexnet.deploy.prototxt\r\n*** Check failure stack trace: ***\r\nAborted (core dumped)\r\n```\r\nHow i can fix it?"},"comment":{"url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/comments/256288734","html_url":"https://github.com/NVIDIA/DIGITS/issues/1219#issuecomment-256288734","issue_url":"https://api.github.com/repos/NVIDIA/DIGITS/issues/1219","id":256288734,"user":{"login":"imrael202","id":20860578,"avatar_url":"https://avatars.githubusercontent.com/u/20860578?v=3","gravatar_id":"","url":"https://api.github.com/users/imrael202","html_url":"https://github.com/imrael202","followers_url":"https://api.github.com/users/imrael202/followers","following_url":"https://api.github.com/users/imrael202/following{/other_user}","gists_url":"https://api.github.com/users/imrael202/gists{/gist_id}","starred_url":"https://api.github.com/users/imrael202/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/imrael202/subscriptions","organizations_url":"https://api.github.com/users/imrael202/orgs","repos_url":"https://api.github.com/users/imrael202/repos","events_url":"https://api.github.com/users/imrael202/events{/privacy}","received_events_url":"https://api.github.com/users/imrael202/received_events","type":"User","site_admin":false},"created_at":"2016-10-26T08:58:03Z","updated_at":"2016-10-26T08:58:03Z","body":"![ver](https://cloud.githubusercontent.com/assets/20860578/19719614/c3a63c00-9b7b-11e6-9c7d-f675bf214789.png)\r\nDIGITS version:  5.1-dev\r\nCaffe version:  1.0.0-rc3"}}
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