Correct way to pass multiple samplers

Along with DistributedSampler what if I wanted to pass another sampler like so to DataLoader?

class PneumoSampler(Sampler):
    def __init__(self, train_df, positive_perc=0.8):
        assert positive_perc > 0, 'percentage of positive pneumothorax images must be greater then zero'
        self.train_df = train_df
        self.positive_perc = positive_perc
        self.positive_idxs = self.train_df.query('has_mask==1').index.values
        self.negative_idxs = self.train_df.query('has_mask!=1').index.values
        self.n_positive = len(self.positive_idxs)
        self.n_negative = int(self.n_positive * (1 - self.positive_perc) / self.positive_perc)
    def __iter__(self):
        negative_sample = np.random.choice(self.negative_idxs, size=self.n_negative)
        shuffled = np.random.permutation(np.hstack((negative_sample, self.positive_idxs)))
        return iter(shuffled.tolist())

    def __len__(self):
        return self.n_positive + self.n_negative

The sampler is taken from here.

@ptrblck any ideas here?