gatelfpytorchjson.modelwrapper module

class gatelfpytorchjson.modelwrapper.ModelWrapper(dataset, config={})

Bases: object

Common base class for all wrappers. Defines instance methods which are the same for all subclasses plus common static utility methods.

static accuracy(batch_predictions, batch_targets, pad_index=-1)

Calculate the accuracy from a tensor with predictions, which contains scores for each class in the last dimension (higher scores are better) and a tensor with target indices. Tensor elements where the target has the padding index are ignored. If the tensors represent sequences the shape of the predictions is batchsize, maxseqlen, nclasses and of the targets is batchsize, maxseqlen, otherwise the predictions have shape batchsize, nclasses, targets have shape batchsize

static early_stopping_checker(losses=None, accs=None, patience=2, mindelta=0.0)

Takes two lists of numbers, representing the losses and/or accuracies of all validation steps. If accs is not None, it is used, otherwise losses is used if not None, otherwise always returns False (do not stop). If accuracies are used, at most patience number of the last validation accuracies can NOT be at least mindelta larger than the best one so far. If losses are used, at most patience number of last validation losses can NOT be at least mindelta smaller then the best one so far. In other words this stops if more that patience of the last metrics are not an improvement of at least mindelta over the current best.

classmethod load(filenameprefix)

Load a saved wrapper instance and return it. The file name is made of the filenameprefix with ‘.wrapper.pickle’ appended.

static makeless(n, func=<built-in function pow>, preshift=-1.0, postshift=1.0, p1=0.5)

Function to return logarithmic or inverse polynomial values for such tasks as calculating number of dimensions from vocabulary size.