0514d4b6de97d652e6cd99c7b557018890a6ec99,snorkel/learning/disc_learning.py,TFNoiseAwareModel,train,#TFNoiseAwareModel#Any#Any#Any#Any#Any#Any#Any#Any#Any#,111

Before Change

            train_idxs = LabelBalancer(Y_train).get_train_idxs(rebalance)
            X_train = [X_train[j] for j in train_idxs] if self.representation \
                else X_train[train_idxs, :]
            Y_train = np.ravel(Y_train)[train_idxs]

        // Create new graph, build network, and start session
        self._build_new_graph_session(**kwargs)

After Change

            train_idxs = LabelBalancer(Y_train).get_train_idxs(rebalance)
        else:
            // In categorical setting, just remove unlabeled
            diffs = Y_train.max(axis=1) - Y_train.min(axis=1)
            train_idxs = np.where(diffs > 1e-6)[0]
        X_train = [X_train[j] for j in train_idxs] if self.representation \
            else X_train[train_idxs, :]
        Y_train = Y_train[train_idxs]

Instances