如何静音 Apache OpenNLP 日志
How to mute Apache OpenNLP logs
如何禁用或静音如下所示的 Apache OpenNLP 日志:
Performing 100 iterations.
1: .. loglikelihood=-3384.6376826743144 0.38951464263772273
2: .. loglikelihood=-2191.9266688597672 0.9397911120212984
3: .. loglikelihood=-1645.8640771555981 0.9643661683391358
4: .. loglikelihood=-1340.386303774519 0.9739913987302887
5: .. loglikelihood=-1148.4141548519624 0.9748105672742167
...<skipping a bunch of iterations>...
95: .. loglikelihood=-288.25556805874436 0.9834118369854598
96: .. loglikelihood=-287.2283680343481 0.9834118369854598
97: .. loglikelihood=-286.2174830344526 0.9834118369854598
98: .. loglikelihood=-285.222486981048 0.9834118369854598
99: .. loglikelihood=-284.24296917223916 0.9834118369854598
100: .. loglikelihood=-283.2785335773966 0.9834118369854598
更新:我需要在 java 代码中执行此操作。
您可以通过设置 属性 PrintMessages=false 在训练期间静音 Apache OpenNLP 日志,通过 -params 选项默认设置为 true。 属性 应在 属性 文件中提供:
$ cat params.props
PrintMessages=false
然后开始训练:
$ opennlp TokenNameFinderTrainer -lang en -data en-ner.train -model en-ner.bin -params params.props
如何禁用或静音如下所示的 Apache OpenNLP 日志:
Performing 100 iterations.
1: .. loglikelihood=-3384.6376826743144 0.38951464263772273
2: .. loglikelihood=-2191.9266688597672 0.9397911120212984
3: .. loglikelihood=-1645.8640771555981 0.9643661683391358
4: .. loglikelihood=-1340.386303774519 0.9739913987302887
5: .. loglikelihood=-1148.4141548519624 0.9748105672742167
...<skipping a bunch of iterations>...
95: .. loglikelihood=-288.25556805874436 0.9834118369854598
96: .. loglikelihood=-287.2283680343481 0.9834118369854598
97: .. loglikelihood=-286.2174830344526 0.9834118369854598
98: .. loglikelihood=-285.222486981048 0.9834118369854598
99: .. loglikelihood=-284.24296917223916 0.9834118369854598
100: .. loglikelihood=-283.2785335773966 0.9834118369854598
更新:我需要在 java 代码中执行此操作。
您可以通过设置 属性 PrintMessages=false 在训练期间静音 Apache OpenNLP 日志,通过 -params 选项默认设置为 true。 属性 应在 属性 文件中提供:
$ cat params.props
PrintMessages=false
然后开始训练:
$ opennlp TokenNameFinderTrainer -lang en -data en-ner.train -model en-ner.bin -params params.props