{"action":"created","issue":{"url":"https://api.github.com/repos/neil454/deep-motion/issues/10","repository_url":"https://api.github.com/repos/neil454/deep-motion","labels_url":"https://api.github.com/repos/neil454/deep-motion/issues/10/labels{/name}","comments_url":"https://api.github.com/repos/neil454/deep-motion/issues/10/comments","events_url":"https://api.github.com/repos/neil454/deep-motion/issues/10/events","html_url":"https://github.com/neil454/deep-motion/issues/10","id":314036240,"node_id":"MDU6SXNzdWUzMTQwMzYyNDA=","number":10,"title":"Issue with testing","user":{"login":"clausmichele","id":31700619,"node_id":"MDQ6VXNlcjMxNzAwNjE5","avatar_url":"https://avatars3.githubusercontent.com/u/31700619?v=4","gravatar_id":"","url":"https://api.github.com/users/clausmichele","html_url":"https://github.com/clausmichele","followers_url":"https://api.github.com/users/clausmichele/followers","following_url":"https://api.github.com/users/clausmichele/following{/other_user}","gists_url":"https://api.github.com/users/clausmichele/gists{/gist_id}","starred_url":"https://api.github.com/users/clausmichele/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/clausmichele/subscriptions","organizations_url":"https://api.github.com/users/clausmichele/orgs","repos_url":"https://api.github.com/users/clausmichele/repos","events_url":"https://api.github.com/users/clausmichele/events{/privacy}","received_events_url":"https://api.github.com/users/clausmichele/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":5,"created_at":"2018-04-13T09:34:55Z","updated_at":"2018-06-08T22:47:37Z","closed_at":null,"author_association":"NONE","body":"Hi,\r\nI was trying to test the model but I get the following errors:\r\n\r\nUsing TensorFlow backend.\r\n/home/cm72ein/Project/DeepMotion/deep-motion-master/src/FI_unet.py:59: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(32, (3, 3), padding=\"same\", activation=\"relu\")`\r\n  conv1 = Convolution2D(32, 3, 3, activation='relu', border_mode='same')(inputs)\r\n/home/cm72ein/Project/DeepMotion/deep-motion-master/src/FI_unet.py:61: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(32, (3, 3), padding=\"same\", activation=\"relu\")`\r\n  conv1 = Convolution2D(32, 3, 3, activation='relu', border_mode='same')(bn1)\r\n/home/cm72ein/Project/DeepMotion/deep-motion-master/src/FI_unet.py:65: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(64, (3, 3), padding=\"same\", activation=\"relu\")`\r\n  conv2 = Convolution2D(64, 3, 3, activation='relu', border_mode='same')(pool1)\r\n/home/cm72ein/Project/DeepMotion/deep-motion-master/src/FI_unet.py:67: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(64, (3, 3), padding=\"same\", activation=\"relu\")`\r\n  conv2 = Convolution2D(64, 3, 3, activation='relu', border_mode='same')(bn2)\r\n/home/cm72ein/Project/DeepMotion/deep-motion-master/src/FI_unet.py:71: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(128, (3, 3), padding=\"same\", activation=\"relu\")`\r\n  conv3 = Convolution2D(128, 3, 3, activation='relu', border_mode='same')(pool2)\r\n/home/cm72ein/Project/DeepMotion/deep-motion-master/src/FI_unet.py:73: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(128, (3, 3), padding=\"same\", activation=\"relu\")`\r\n  conv3 = Convolution2D(128, 3, 3, activation='relu', border_mode='same')(bn3)\r\nTraceback (most recent call last):\r\n  File \"train.py\", line 202, in <module>\r\n    main()\r\n  File \"train.py\", line 85, in main\r\n    model = get_unet_2(input_shape=(6, 128, 384))\r\n  File \"/home/cm72ein/Project/DeepMotion/deep-motion-master/src/FI_unet.py\", line 75, in get_unet_2\r\n    pool3 = MaxPooling2D(pool_size=(2, 2))(bn3)\r\n  File \"/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py\", line 619, in __call__\r\n    output = self.call(inputs, **kwargs)\r\n  File \"/usr/local/lib/python2.7/dist-packages/keras/layers/pooling.py\", line 158, in call\r\n    data_format=self.data_format)\r\n  File \"/usr/local/lib/python2.7/dist-packages/keras/layers/pooling.py\", line 221, in _pooling_function\r\n    pool_mode='max')\r\n  File \"/usr/local/lib/python2.7/dist-packages/keras/backend/tensorflow_backend.py\", line 3657, in pool2d\r\n    data_format=tf_data_format)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/nn_ops.py\", line 1958, in max_pool\r\n    name=name)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_nn_ops.py\", line 2806, in _max_pool\r\n    data_format=data_format, name=name)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py\", line 787, in _apply_op_helper\r\n    op_def=op_def)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py\", line 2958, in create_op\r\n    set_shapes_for_outputs(ret)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py\", line 2209, in set_shapes_for_outputs\r\n    shapes = shape_func(op)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py\", line 2159, in call_with_requiring\r\n    return call_cpp_shape_fn(op, require_shape_fn=True)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/common_shapes.py\", line 627, in call_cpp_shape_fn\r\n    require_shape_fn)\r\n  File \"/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/common_shapes.py\", line 691, in _call_cpp_shape_fn_impl\r\n    raise ValueError(err.message)\r\nValueError: Negative dimension size caused by subtracting 2 from 1 for 'max_pooling2d_3/MaxPool' (op: 'MaxPool') with input shapes: [?,1,32,128].\r\n"},"comment":{"url":"https://api.github.com/repos/neil454/deep-motion/issues/comments/395912583","html_url":"https://github.com/neil454/deep-motion/issues/10#issuecomment-395912583","issue_url":"https://api.github.com/repos/neil454/deep-motion/issues/10","id":395912583,"node_id":"MDEyOklzc3VlQ29tbWVudDM5NTkxMjU4Mw==","user":{"login":"SpaceMonkeyForever","id":22860578,"node_id":"MDQ6VXNlcjIyODYwNTc4","avatar_url":"https://avatars2.githubusercontent.com/u/22860578?v=4","gravatar_id":"","url":"https://api.github.com/users/SpaceMonkeyForever","html_url":"https://github.com/SpaceMonkeyForever","followers_url":"https://api.github.com/users/SpaceMonkeyForever/followers","following_url":"https://api.github.com/users/SpaceMonkeyForever/following{/other_user}","gists_url":"https://api.github.com/users/SpaceMonkeyForever/gists{/gist_id}","starred_url":"https://api.github.com/users/SpaceMonkeyForever/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/SpaceMonkeyForever/subscriptions","organizations_url":"https://api.github.com/users/SpaceMonkeyForever/orgs","repos_url":"https://api.github.com/users/SpaceMonkeyForever/repos","events_url":"https://api.github.com/users/SpaceMonkeyForever/events{/privacy}","received_events_url":"https://api.github.com/users/SpaceMonkeyForever/received_events","type":"User","site_admin":false},"created_at":"2018-06-08T22:47:37Z","updated_at":"2018-06-08T22:47:37Z","author_association":"NONE","body":"@lecode-official I see now that they mentioned the input dimensions cannot be changed because of batch normalisation in the model. I don't understand why this matters tho. How does batch normalisation on the hidden layers tie the dimensions of the input and the weights trained together?"}}
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