def setup(self, model, dataset): x = dataset.get_batch_design(10000, include_labels=False) ml_vbias = rbm_utils.compute_ml_bias(x) model.vbias.set_value(ml_vbias) pval_v = sigm(model.vbias.get_value()) neg_v = model.rng.binomial(n=1, p=pval_v, size=(model.batch_size, model.n_v)) model.neg_v.set_value(neg_v.astype(floatX)) super(TrainingAlgorithm, self).setup(model, dataset)
def init_parameters_from_data(self, x): if self.flags['ml_vbias']: self.vbias.set_value(rbm_utils.compute_ml_bias(x)) if self.flags['enable_centering']: self.cv.set_value(x.mean(axis=0).astype(floatX))
def setup(self, model, dataset): super(TrainingAlgorithm, self).setup(model, dataset) ml_vbias = rbm_utils.compute_ml_bias(dataset.X[:10000]) model.vbias.set_value(ml_vbias)