From 9b4e9cc8a0311e5243d69b73ed073e7ea441982e Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期三, 27 三月 2024 16:05:29 +0800
Subject: [PATCH] train update
---
funasr/models/campplus/cluster_backend.py | 8 +++++---
1 files changed, 5 insertions(+), 3 deletions(-)
diff --git a/funasr/models/campplus/cluster_backend.py b/funasr/models/campplus/cluster_backend.py
index 3bac0a0..93d3bce 100644
--- a/funasr/models/campplus/cluster_backend.py
+++ b/funasr/models/campplus/cluster_backend.py
@@ -4,11 +4,9 @@
# MIT License (https://opensource.org/licenses/MIT)
# Modified from 3D-Speaker (https://github.com/alibaba-damo-academy/3D-Speaker)
-import umap
import scipy
import torch
import sklearn
-import hdbscan
import numpy as np
from sklearn.cluster._kmeans import k_means
@@ -117,15 +115,18 @@
self.min_samples = min_samples
self.min_cluster_size = min_cluster_size
self.metric = metric
+ import hdbscan
+ self.hdbscan = hdbscan
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 = self.hdbscan.HDBSCAN(
min_samples=self.min_samples,
min_cluster_size=self.min_cluster_size,
allow_single_cluster=True).fit_predict(umap_X)
@@ -156,6 +157,7 @@
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)
--
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