Module ImportFrom alias Assign NameStore Str ImportFrom alias ImportFrom alias ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam NameParam defaults Num Num Num Num Num kwarg body Expr Str Expr Call AttributeLoad NameLoad attr NameLoad NameLoad NameLoad Assign AttributeStore NameLoad attr Num Assign AttributeStore AttributeLoad NameLoad attr attr NameLoad Assign AttributeStore AttributeLoad NameLoad attr attr NameLoad Assign AttributeStore AttributeLoad NameLoad attr attr NameLoad Assign AttributeStore AttributeLoad NameLoad attr attr NameLoad Assign AttributeStore AttributeLoad NameLoad attr attr NameLoad Assign AttributeStore AttributeLoad NameLoad attr attr NameLoad Expr Call AttributeLoad AttributeLoad NameLoad attr attr AttributeLoad NameLoad attr decorator_list FunctionDef arguments args NameParam defaults body Expr Str Expr Call AttributeLoad AttributeLoad NameLoad attr attr Assign NameStore Num Assign NameStore Num For NameStore Call AttributeLoad AttributeLoad NameLoad attr attr body Assign TupleStore NameStore NameStore Call AttributeLoad NameLoad attr NameLoad AugAssignAdd NameStore NameLoad AugAssignAdd NameStore NameLoad If AttributeLoad NameLoad attr body Expr Call NameLoad Call AttributeLoad Str attr keyword AttributeLoad NameLoad attr keyword BinOpDiv NameLoad NameLoad keyword Call NameLoad Call AttributeLoad BinOpPow AttributeLoad AttributeLoad NameLoad attr attr Num attr Expr Call AttributeLoad AttributeLoad NameLoad attr attr Call AttributeLoad NameLoad attr BinOpSub AttributeLoad AttributeLoad NameLoad attr attr BinOpMult AttributeLoad NameLoad attr AttributeLoad AttributeLoad NameLoad attr attr AugAssignAdd AttributeStore NameLoad attr Num AugAssignAdd AttributeStore NameLoad attr Num Return BinOpDiv NameLoad NameLoad decorator_list decorator_list
N/A __future__ print_function N/A __author__ Martin Felder scipy sqrt pybrain.supervised.trainers BackpropTrainer RPropMinusTrainer N/A BackpropTrainer N/A N/A  Train the parameters of a module according to a supervised dataset (possibly sequential)
        by RProp without weight backtracking (aka RProp-, cf. [Igel&Huesken, Neurocomputing 50, 2003])
        and without ponderation, ie. all training samples have the same weight.  __init__ N/A N/A self module etaminus etaplus deltamin deltamax delta0 N/A 0.5 1.2 1e-06 5.0 0.1 kwargs N/A N/A  Set up training algorithm parameters, and objects associated with the trainer.

            :arg module: the module whose parameters should be trained.
            :key etaminus: factor by which step width is decreased when overstepping (0.5)
            :key etaplus: factor by which step width is increased when following gradient (1.2)
            :key delta: step width for each weight
            :key deltamin: minimum step width (1e-6)
            :key deltamax: maximum step width (5.0)
            :key delta0: initial step width (0.1)
         N/A N/A N/A BackpropTrainer __init__ self module kwargs N/A N/A self epoch 0 N/A N/A N/A self descent rprop True N/A N/A N/A self descent etaplus etaplus N/A N/A N/A self descent etaminus etaminus N/A N/A N/A self descent deltamin deltamin N/A N/A N/A self descent deltamax deltamax N/A N/A N/A self descent deltanull delta0 N/A N/A N/A N/A self descent init N/A module params N/A train N/A N/A self N/A N/A N/A  Train the network for one epoch  N/A N/A N/A N/A self module resetDerivatives N/A errors 0 N/A ponderation 0 N/A seq N/A N/A N/A self ds _provideSequences N/A N/A N/A e p N/A N/A self _calcDerivs seq N/A errors e N/A ponderation p N/A N/A self verbose N/A N/A N/A print N/A N/A epoch {epoch:6d}  total error {error:12.5g}   avg weight  {weight:12.5g} format epoch N/A self epoch error N/A errors ponderation weight N/A sqrt N/A N/A N/A N/A N/A self module params 2 mean N/A N/A N/A N/A self module _setParameters N/A N/A self descent N/A N/A N/A self module derivs N/A N/A self weightdecay N/A N/A self module params N/A N/A self epoch 1 N/A N/A self totalepochs 1 N/A N/A errors ponderation N/A N/A