【1、模型部分能力升级】

• 新模型支持：新增轻量级中文对话模型plato-mini，新增基于VOC数据集的高精度语义分割模型2个，语音分类模型3个。
• 迁移学习能力升级：新增图像语义分割、文本语义匹配、语音分类等相关任务的Fine-Tune能力以及相关任务数据集。

【2、部署能力重要升级】

• 完善部署能力：新增ONNX和PaddleInference等模型格式的导出功能。
• 重要开源生态合作：新增BentoML 云原生服务化部署能力，可以支持统一的多框架模型管理和模型部署的工作流，详细教程. 更多内容可以参考BentoML 最新 v0.12.1 Releasenote （感谢@ parano @cqvu @deehrlic）的贡献与支持

【3、问题修复】

• #7da1230 修复了模型未记录评估指标时无法恢复训练的问题。
• #b0b3144 修复了评估过程出现异常时线程没有正常退出的问题。
• #30aace4 优化模型安装流程，提升易用性。

[ 1. Improvements]

• Add supports for six new models, including an open-domain dialogue system(plato-mini), two high-precision semantic segmentation models based on VOC dataset and three voice classification models.
• Enforce the transfer learning capabilities for image semantic segmentation, text semantic matching and voice classification on related datasets.

[ 2. Upgrades of deployment capabilities]

• Add the export function APIs for two kinds of model formats, i.,e, ONNX and PaddleInference.
• Important Open-Source Ecological Cooperation: add the support for BentoML, which is a cloud native framework for serving deployment. Users can easily serve pre-trained models from PaddleHub by following the Tutorial notebooks. Also, see this announcement and Release note from BentoML. (Many thanks to @parano @cqvu @deehrlic for contributing this feature in PaddleHub)

[ 3. Bug fixes ]

• #7da1230 Fixed the problem that the model cannot resume training if metrics is not recorded.
• #b0b3144 Fixed the problem that the thread did not exit normally when the evaluation process was abnormal.
• #30aace4 Improve the model installation process.