Dev gzf exp (#1647)

zhifu gao

2024-04-23 2ac38adbe5f4e1374a079e032ed4b504351a207c

 funasr/models/campplus/cluster_backend.py

@@ -1,14 +1,16 @@
# Copyright (c) Alibaba, Inc. and its affiliates.
#!/usr/bin/env python3
# -*- encoding: utf-8 -*-
# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
#  MIT License  (https://opensource.org/licenses/MIT)
# Modified from 3D-Speaker (https://github.com/alibaba-damo-academy/3D-Speaker)

from typing import Any, Dict, Union

import hdbscan
import numpy as np
import scipy
import torch
import sklearn
import umap
import numpy as np

from sklearn.cluster._kmeans import k_means
from torch import nn
from sklearn.cluster import HDBSCAN


class SpectralCluster:
@@ -116,20 +118,21 @@
        self.metric = metric

    def __call__(self, X):
        import umap.umap_ as umap
        umap_X = umap.UMAP(
            n_neighbors=self.n_neighbors,
            min_dist=0.0,
            n_components=min(self.n_components, X.shape[0] - 2),
            metric=self.metric,
        ).fit_transform(X)
        labels = hdbscan.HDBSCAN(
        labels = HDBSCAN(
            min_samples=self.min_samples,
            min_cluster_size=self.min_cluster_size,
            allow_single_cluster=True).fit_predict(umap_X)
        return labels


class ClusterBackend(nn.Module):
class ClusterBackend(torch.nn.Module):
    r"""Perfom clustering for input embeddings and output the labels.
    Args:
        model_dir: A model dir.
@@ -153,6 +156,7 @@
        if X.shape[0] < 20:
            return np.zeros(X.shape[0], dtype='int')
        if X.shape[0] < 2048 or k is not None:
            # unexpected corner case
            labels = self.spectral_cluster(X, k)
        else:
            labels = self.umap_hdbscan_cluster(X)