refactoring: made varprop.py a package varprop/
added tanh transfer to varprop
fixed indentation
added varprop rnns; some refactoring involved
stop is now only tested during reports
die if lookups fail
corrected 1- error for fast dropout
added way to project variables into a l2 ball
added proper variance calculation of fast dropout into recurrent calculations
merged
clipping sigmoid approximation for fast dropout to avoid numerical errors in negative cross entropy
added additional parameter to powerfit to avoid calculation of training loss
sampling sigmoid added
added sampling sigmoid 

This makes it possible to respect variance when using with nce/nces, since a sample is dependent on the variance.
More efficient and also the correct way of fast dropout.
FIX: forward prop was wrong
added truncation of gradients
respect mode
sample dims added
FIX: supervised RNNs did not use batch sizes