title: Keras convolution filter size issue
body: <p>I'm <em>very</em> new to Keras, and in my early experiments I've been encountering an error when I create convolutional layers. When I run this code (found <a href="https://keras.io/getting-started/functional-api-guide/#more-examples" rel="nofollow" title="here">here</a>; "Shared vision model" section)</p>
  
  <pre><code>from keras.models import *
  from keras.layers import *
  from keras.layers.convolutional import *
  from keras.layers.pooling import *
  
  digit_input = Input(shape=(1, 27, 27))
  x = Convolution2D(64, 3, 3)(digit_input)
  x = MaxPooling2D((2, 2))(x)
  
  mdl = Model(digit_input, x)
  </code></pre>
  
  <p>I get the following error (traceback points to the Convolution2D line):</p>
  
  <pre><code>ValueError: Filter must not be larger than the input: Filter: (3, 3) Input: (1, 27)
  </code></pre>
  
  <p>I'd assume I was misusing the interface--especially since no one else seems to have this particular problem--but I pulled the code directly from the Keras docs. The problem persists when I use the <code>model.add()</code> syntax. Interestingly though, when I shrink the filter size to 1x1 or increase the number of input channels to 3, the error goes away. I have tried manually setting <code>dim_ordering='tf'</code> for the convolution and my keras.json file reads:</p>
  
  <pre><code>{
  "image_dim_ordering": "tf",
  "epsilon": 1e-07,
  "floatx": "float32",
  "backend": "tensorflow"
  }
  </code></pre>
  
  <p>Keras looks like a great tool, but I'm completely unable to use it so far. </p>
  
  <p>P.S. I am using Keras 1.1.0 and Tensorflow 0.10. </p>