{"action":"opened","issue":{"url":"https://api.github.com/repos/apache/incubator-mxnet/issues/10976","repository_url":"https://api.github.com/repos/apache/incubator-mxnet","labels_url":"https://api.github.com/repos/apache/incubator-mxnet/issues/10976/labels{/name}","comments_url":"https://api.github.com/repos/apache/incubator-mxnet/issues/10976/comments","events_url":"https://api.github.com/repos/apache/incubator-mxnet/issues/10976/events","html_url":"https://github.com/apache/incubator-mxnet/issues/10976","id":323722500,"number":10976,"title":"MNIST LeNet forward fails on master branch","user":{"login":"zhanghang1989","id":8041160,"avatar_url":"https://avatars1.githubusercontent.com/u/8041160?v=4","gravatar_id":"","url":"https://api.github.com/users/zhanghang1989","html_url":"https://github.com/zhanghang1989","followers_url":"https://api.github.com/users/zhanghang1989/followers","following_url":"https://api.github.com/users/zhanghang1989/following{/other_user}","gists_url":"https://api.github.com/users/zhanghang1989/gists{/gist_id}","starred_url":"https://api.github.com/users/zhanghang1989/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/zhanghang1989/subscriptions","organizations_url":"https://api.github.com/users/zhanghang1989/orgs","repos_url":"https://api.github.com/users/zhanghang1989/repos","events_url":"https://api.github.com/users/zhanghang1989/events{/privacy}","received_events_url":"https://api.github.com/users/zhanghang1989/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-05-16T17:48:20Z","updated_at":"2018-05-16T17:48:20Z","closed_at":null,"author_association":"CONTRIBUTOR","body":"MNIST LeNet forward fails on master branch. @eric-haibin-lin mentioned that it may be related to this PR https://github.com/apache/incubator-mxnet/pull/10911\r\n```python\r\nimport mxnet as mx\r\nfrom mxnet.gluon import nn, Block\r\nnet = nn.HybridSequential()\r\nwith net.name_scope():\r\n        net.add(nn.Conv2D(in_channels=1, channels=20, kernel_size=5))\r\n        net.add(nn.Activation('relu'))\r\n        net.add(nn.MaxPool2D(pool_size=2, strides=2))\r\n        net.add(nn.Conv2D(in_channels=20, channels=50, kernel_size=5))\r\n        net.add(nn.Activation('relu'))\r\n        net.add(nn.MaxPool2D(pool_size=2, strides=2))\r\n        # The Flatten layer collapses all axis, except the first one, into one axis.\r\n        net.add(nn.Flatten())\r\n        net.add(nn.Dense(512,in_units=800))\r\n        net.add(nn.Activation('relu'))\r\n        net.add(nn.Dense(10, in_units=512))\r\nnet.collect_params().initialize()\r\nx = mx.random.uniform(shape=(8, 1, 28, 28))\r\nnet(x)\r\n```\r\nGot this error\r\n```bash\r\nSegmentation fault (core dumped)\r\n```\r\n"}}
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