Remove unnecessary assignation in TransformerIterator.__init__
Remove unnecessary symbolic variable instantiation in make_symbolic_state methods
Add exception handling for missing MNIST dataset
Fix make_symbolic_state according to the same workaround as mf_state
Simplify theano expression
Add unit test for make_symbolic_state()
Use scalar num_examples instead of symbolic one for T.alloc
Fix typo in Softmax's make_symbolic_state method
Add unit test for make_layer_to_symbolic_state
Fix minuscule problem
Merge pull request #367 from vdumoulin/quick_fixes

Quick Fixes
I added a use_abs_loss variable to the mlp.linear layer so one can use the abs loss instead of the squared loss in the cost matrix
Update docstring
Fix way lambda function is defined
Add Conv2DSpace.default_axes, use it to avoid conversion errors

In particular for the case Conv2DSpace(b01c) -> VectorSpace ->
Conv2DSpace(c01b), because the VectorSpace has no way to know
what it is a flattened version of, and the second Conv2DSpace does not
now either.
Change tests to use Conv2DSpace.default_axes instead of ('b','c',0,1)

Also add test for indirect conv2d -> vector -> conv2d conversion
Merge pull request #382 from lamblin/fix_convert_fn

Make Conv2D to Vector conversions independent of axes
Added option to variable use_abs_loss on Linear layer of MLP
Add use_abs_loss variable to linear layer in mlp.py (with correct indentation)
Merge pull request #381 from risingsun007/master

MLP absolute loss