{"action":"closed","issue":{"url":"https://api.github.com/repos/fchollet/keras/issues/2092","repository_url":"https://api.github.com/repos/fchollet/keras","labels_url":"https://api.github.com/repos/fchollet/keras/issues/2092/labels{/name}","comments_url":"https://api.github.com/repos/fchollet/keras/issues/2092/comments","events_url":"https://api.github.com/repos/fchollet/keras/issues/2092/events","html_url":"https://github.com/fchollet/keras/issues/2092","id":143756209,"number":2092,"title":"VGG-like convnet from Keras examples fails on custom data","user":{"login":"aaronpolhamus","id":2927860,"avatar_url":"https://avatars.githubusercontent.com/u/2927860?v=3","gravatar_id":"","url":"https://api.github.com/users/aaronpolhamus","html_url":"https://github.com/aaronpolhamus","followers_url":"https://api.github.com/users/aaronpolhamus/followers","following_url":"https://api.github.com/users/aaronpolhamus/following{/other_user}","gists_url":"https://api.github.com/users/aaronpolhamus/gists{/gist_id}","starred_url":"https://api.github.com/users/aaronpolhamus/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/aaronpolhamus/subscriptions","organizations_url":"https://api.github.com/users/aaronpolhamus/orgs","repos_url":"https://api.github.com/users/aaronpolhamus/repos","events_url":"https://api.github.com/users/aaronpolhamus/events{/privacy}","received_events_url":"https://api.github.com/users/aaronpolhamus/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"milestone":null,"comments":1,"created_at":"2016-03-26T22:39:29Z","updated_at":"2016-03-27T01:36:27Z","closed_at":"2016-03-27T01:36:27Z","body":"I'm trying to run the following network with Keras, powered by a TensorFlow backend. It's an adaptation of the \"VGG-like\" convnet from http://keras.io/examples/. I've linked a very small sample of the data to this issue report, and created scripts on Gist that can be used to reproduce the error (https://gist.github.com/aaronpolhamus/39c7a71151b8560d02dd). \r\n\r\nBasically I've adapted the website example to accept an array of greyscale, single-channel images. Seems pretty straightforward, but when I attempt to train the model after compiling it I'm seeing the following error: \r\n\r\n`ValueError: Cannot feed value of shape (32, 128, 256) for Tensor u'Placeholder_89:0', which has shape '(?, 1, 128, 256)'`\r\n\r\nI'm puzzled: shouldn't it be no problem to generate 32 convolution filters with dim (32, 128, 256) from a series of input images with dimenstions (1, 128, 256)? It's likely that I'm still a novice with this stuff, but this error just isn't informative enough for me to tell what's going wrong or how to fix it... \r\n\r\nHere's a link to sample data: \r\n[keras_ex_data.zip](https://github.com/fchollet/keras/files/190676/keras_ex_data.zip)\r\n\r\nThanks in advance!"}}