--- a/doc/v2_planning/formulas.txt	Fri Sep 17 16:12:33 2010 -0400
+++ b/doc/v2_planning/formulas.txt	Fri Sep 17 16:13:58 2010 -0400
@@ -9,47 +9,6 @@
 - Olivier B.
 - Nicolas
 
-TODO 
-----
-* define a list of search tag to start with
-* propose an interface(many inputs, outputs, doc style, hierrache, to search, html output?)
-* find existing repositories with files for formulas.
-* move existing formulas to pylearn as examples and add other basics ones.
-** theano.tensor.nnet will probably be copied to pylearn.formulas.nnet and depricated.
-
-Why we need formulas
---------------------
-
-Their is a few reasons why having a library of mathematical formula for theano is a good reason:
-
-* Some formula have some special thing needed for the gpu. 
-   * Sometimes we need to cast to floatX...
-* Some formula have numerical stability problem.
-* Some formula gradiant have numerical stability problem. (Happen more frequently then the previous ones)
-   * If theano don't always do some stability optimization, we could do it manually in the formulas
-* Some formula as complex to implement and take many try to do correctly. 
-
-Having a library help in that we solve those problem only once.
-
-Formulas definition
--------------------
-
-We define formulas as something that don't have a state. They are implemented as python function 
-that take theano variable as input and output theano variable. If you want state, look at what the 
-learner commity will do.
-
-Formulas doc must have
-----------------------
-
-* A latex mathematical description of the formulas(for picture representation in generated documentation)
-* Tags(for searching):
-   * a list of lower lovel fct used
-   * category(name of the submodule itself)
-* Tell if we did some work to make it more numerical stable. Do theano do the optimization needed?
-* Tell if the grad is numericaly stable? Do theano do the optimization needed?
-* Tell if work on gpu/not/unknow
-* Tell alternate name
-* Tell the domaine, range of the input/output(range should use the english notation of including or excluding)
 
 List of existing repos
 ----------------------
@@ -57,33 +16,3 @@
 Olivier B. ?
 Xavier G.: git@github.com:glorotxa/DeepANN.git, see file deepANN/{Activations.py(to nnet),Noise.py,Reconstruction_cost.py(to costs),Regularization.py(to regularization}
 
-Proposed hierarchy
-------------------
-
-Here is the proposed hierarchy for formulas
-
-pylearn.formulas.costs: generic / common cost functions, e.g. various cross-entropies, squared error, 
-abs. error, various sparsity penalties (L1, Student)
-
-pylearn.formulas.regularization: formulas for regularization
-
-pylearn.formulas.linear: formulas for linear classifier, linear regression, factor analysis, PCA
-
-pylearn.formulas.nnet: formulas for building layers of various kinds, various activation functions,
-layers which could be plugged with various costs & penalties, and stacked
-
-pylearn.formulas.ae: formulas for auto-encoders and denoising auto-encoder variants
-
-pylearn.formulas.noise: formulas for corruption processes
-
-pylearn.formulas.rbm: energies, free energies, conditional distributions, Gibbs sampling
-
-pylearn.formulas.trees: formulas for decision trees
-
-pylearn.formulas.boosting: formulas for boosting variants
-
-pylearn.formulas.maths for other math formulas
-
-pylearn.formulas.scipy.stats: example to implement the same interface as existing lib
-
-etc.