5273d873b9154ad706bfdfcf4fc8e2354fd425c0,deepchem/models/__init__.py,Model,predict,#Model#Any#,146

Before Change

      if sys.getsizeof(X) > MAX_GPU_RAM:
        nb_block = float(sys.getsizeof(X))/MAX_GPU_RAM
        nb_sample = np.shape(X)[0]
        interval_points = np.linspace(0,nb_sample,nb_block+1).astype(int)
        y_preds = []
        for j in range(0,len(interval_points)-1):
          indices = range(interval_points[j],interval_points[j+1])
          y_preds.append(self.predict_on_batch(X[indices,:]))

After Change

    for (X, y, w, ids) in dataset.itershards():
      nb_sample = np.shape(X)[0]
      interval_points = np.linspace(
          0, nb_sample, np.ceil(float(nb_sample)/batch_size)+1).astype(int)
      y_preds = []
      for j in range(0,len(interval_points)-1):
        indices = range(interval_points[j],interval_points[j+1])

Instances