I'm guessing this is a typo which was not spotted because iter_test never gets called
mnist was being loaded in as float32, which was causing errors on my laptop where floatX=float64, implicitly casting fixes this
Conv2DLayer implementation
conv1d implementations, Conv1DLayer, fixed InputLayer to support other dimensionalities properly
Merge branch 'master' of https://github.com/craffel/nntools
Additional things to ignore
Merge pull request #29 from craffel/master

Some quick changes to the mnist example + more stuff for git to ignore
Updated to reflect new __init__ call spec changed in 4d145a4
Merge pull request #32 from craffel/master

Updated to reflect new __init__ call spec changed in 4d145a4
fix typos in update functions
Merge pull request #33 from dimatura/rmsprop_typo

fix typos in update functions
xrange -> range for Python 3 compatibility + README update
DenseLayer fix + MaxPool2DLayer + range instead of xrange in examples/mnist.py for Python 3 compatibility
Glorot-style uniform initialization generalized to convolutional layers, convolution example
Use three functions to hopefully make eaxmple easier to grasp.
Merge pull request #35 from dnouri/mnist-example-refactor

clean up MNIST example
Remove Bunch fanciness; make 'train' a generator over epochs.
T.signal.downsample raises AttributeError on the T module for me.
Structure this example in the same way as mnist.py
Merge pull request #37 from dnouri/mnist-example-refactor

mnist_conv.py example refactor