def _real_predict(self, X, sess): standardizer = self.prediction_iterator.standardizer da_params = standardizer.da_processing_params() util.veryify_args(da_params, ['sigma'], 'QuasiPredictor.standardizer does unknown da with param(s):') color_sigma = da_params.get('sigma', 0.0) tfs, color_vecs = tta.build_quasirandom_transforms(self.number_of_transforms, color_sigma=color_sigma, **self.cnf['aug_params']) multiple_predictions = [] for i, (xform, color_vec) in enumerate(zip(tfs, color_vecs), start=1): print('Quasi-random tta iteration: %d' % i) standardizer.set_tta_args(color_vec=color_vec) predictions = self.predictor._real_predict(X, sess, xform=xform) multiple_predictions.append(predictions) return np.mean(multiple_predictions, axis=0)
def _check_unused(unused, name): allowed_keys = ['is_training', 'reuse', 'outputs_collections', 'trainable'] helper.veryify_args(unused, allowed_keys, 'Layer "%s" got unexpected argument(s):' % name)