9c158b87f5fb2dca1ed95884e667ab2fc218e1b7,dragonn/models.py,SequenceDNN,deeplift,#SequenceDNN#,175

Before Change

        
        Returns (num_task, num_samples, 1, num_bases, sequence_length) deeplift score array.
        
        if sys.version_info[0] != 2:
            raise RuntimeError("DeepLIFT requires Python2!")
        assert len(np.shape(X)) == 4 and np.shape(X)[1] == 1
        from deeplift.conversion import keras_conversion as kc
        from deeplift.blobs import NonlinearMxtsMode

After Change

        score_func = deeplift_model.get_target_contribs_func(
            find_scores_layer_idx=0)
        // use a 40% GC reference
        input_references = [np.array([0.3, 0.2, 0.2, 0.3])[None, None, :, None]]
        // get deeplift scores
        deeplift_scores = np.zeros((self.num_tasks,) + X.shape)
        for i in range(self.num_tasks):

Instances