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)