| |
| |
| import numpy as np |
|
|
|
|
| class ClusterResampler: |
| def __init__(self, cluster_path: str) -> None: |
| idx2prob = [] |
| with open(cluster_path, 'r') as fin: |
| for line in fin: |
| cluster_n_member = int(line.strip().split('\t')[-1]) |
| idx2prob.append(1 / cluster_n_member) |
| total = sum(idx2prob) |
| idx2prob = [p / total for p in idx2prob] |
| self.idx2prob = np.array(idx2prob) |
|
|
| def __call__(self, n_sample:int, replace: bool=False): |
| idxs = np.random.choice(len(self.idx2prob), size=n_sample, replace=replace, p=self.idx2prob) |
| return idxs |
