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| with the License. You may obtain a copy of the License at |
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| http://www.apache.org/licenses/LICENSE-2.0 |
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| Unless required by applicable law or agreed to in writing, |
| software distributed under the License is distributed on an |
| "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
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| ## 下载 SINGA |
| |
| * 要验证下载的tar.gz文件,请下载KEY和ASC文件,然后执行以下命令 |
| |
| % gpg --import KEYS |
| % gpg --verify downloaded_file.asc downloaded_file |
| |
| 您还可以检查SHA512或MD5值以查看下载是否已完成 |
| |
| * Incubating v1.2.0 (2018年6月6日): |
| * [Apache SINGA 1.2.0 (incubating)](http://www.apache.org/dyn/closer.cgi/incubator/singa/1.2.0/apache-singa-incubating-1.2.0.tar.gz) |
| [\[SHA512\]](https://www.apache.org/dist/incubator/singa/1.2.0/apache-singa-incubating-1.2.0.tar.gz.sha512) |
| [\[KEYS\]](https://www.apache.org/dist/incubator/singa/1.2.0/KEYS) |
| [\[ASC\]](https://www.apache.org/dist/incubator/singa/1.2.0/apache-singa-incubating-1.2.0.tar.gz.asc) |
| * [发行说明 1.2.0 (incubating)](releases/RELEASE_NOTES_1.2.0.html) |
| * 新功能和主要更新, |
| * 实现 autograd (目前支持MLP模型) |
| * 升级 PySinga 以支持 Python 3 |
| * 为 Tensor 类添加 stride field |
| * 讲 cuDNN 从 V5 升级到 V7 |
| * 为 ImageNet 分类任务添加 VGG, Inception V4, ResNet, 及 DenseNet 模型 |
| * 为 conda 包创建别名 |
| * 完善中文文档 |
| * 添加在 Windows 上运行 Singa 的说明 |
| * 更新编译, CI |
| * 修复一些错误 |
| |
| |
| |
| * Incubating v1.1.0 (2017年2月12日): |
| * [Apache SINGA 1.1.0 (incubating)](http://www.apache.org/dyn/closer.cgi/incubator/singa/1.1.0/apache-singa-incubating-1.1.0.tar.gz) |
| [\[MD5\]](https://archive.apache.org/dist/incubator/singa/1.1.0/apache-singa-incubating-1.1.0.tar.gz.md5) |
| [\[KEYS\]](https://archive.apache.org/dist/incubator/singa/1.1.0/KEYS) |
| [\[ASC\]](https://archive.apache.org/dist/incubator/singa/1.1.0/apache-singa-incubating-1.1.0.tar.gz.asc) |
| * [发行说明 1.1.0 (incubating)](releases/RELEASE_NOTES_1.1.0.html) |
| * 新功能和主要更新, |
| * 创建 Docker 镜像(CPU和GPU版本) |
| * 为 SINGA 创建 Amazon AMI(CPU版本) |
| * 与 Jenkins 集成以自动生成 Wheel 和 Debian 软件包(用于安装),并更新网站. |
| * 增强 FeedFowardNet, 例如,用于调试的多输入和详细模式 |
| * 添加 Concat 和 Slice 层 |
| * 扩展 CrossEntropyLoss 以接受具有多个标签的实例 |
| * 添加 image_tool.py 与图像增强方法 |
| * 通过 Snapshot API 支持模型加载和保存 |
| * 在 Windows 上编译 SINGA 源代码 |
| * 用 SINGA 代码编译强制依赖库 |
| * 启用 SINGA 的 Java 绑定(基本) |
| * 在检查点文件中添加版本 ID |
| * 添加 Rafiki 工具包以提供 RESTFul API |
| * 添加 Caffe 预训练的例子,包括 GoogleNet |
| |
| |
| |
| * Incubating v1.0.0 (2016年9月8日): |
| * [Apache SINGA 1.0.0 (incubating)](https://archive.apache.org/dist/incubator/singa/1.0.0/apache-singa-incubating-1.0.0.tar.gz) |
| [\[MD5\]](https://archive.apache.org/dist/incubator/singa/1.0.0/apache-singa-incubating-1.0.0.tar.gz.md5) |
| [\[KEYS\]](https://archive.apache.org/dist/incubator/singa//1.0.0/KEYS) |
| [\[ASC\]](https://archive.apache.org/dist/incubator/singa/1.0.0/apache-singa-incubating-1.0.0.tar.gz.asc) |
| * [发行说明 1.0.0 (incubating)](releases/RELEASE_NOTES_1.0.0.html) |
| * 新功能和主要更新, |
| * 用于支持更多机器学习模型的张量抽象. |
| * 设备抽象运行在不同的硬件设备上,包括CPU,(Nvidia / AMD)GPU 和 FPGA(将在更高版本中测试). |
| * 用 cmake 替换 GNU autotool 进行编译. |
| * 支持 Mac OS |
| * 改进Python绑定,包括安装和编程 |
| * 更多深度学习模型, 包括 VGG 和 ResNet |
| * 读取/写入文件和编码/解码数据的更多 IO 类 |
| * 直接基于 Socket 的新网络通信组件. |
| * 包含 Dropout 和 RNN 层的 Cudnn V5. |
| * 将网站制作工具从 maven 替换为 Sphinx |
| * 整合 Travis-CI |
| |
| |
| * Incubating v0.3.0 (2016年4月20日): |
| * [Apache SINGA 0.3.0 (incubating)](https://archive.apache.org/dist/incubator/singa/0.3.0/apache-singa-incubating-0.3.0.tar.gz) |
| [\[MD5\]](https://archive.apache.org/dist/incubator/singa/0.3.0/apache-singa-incubating-0.3.0.tar.gz.md5) |
| [\[KEYS\]](https://archive.apache.org/dist/incubator/singa/0.3.0/KEYS) |
| [\[ASC\]](https://archive.apache.org/dist/incubator/singa/0.3.0/apache-singa-incubating-0.3.0.tar.gz.asc) |
| * [发行说明 0.3.0 (incubating)](releases/RELEASE_NOTES_0.3.0.html) |
| * 新功能和主要更新, |
| * [在 GPU 集群上](v0.3.0/gpu.html) 可以在 GPU 集群上训练深度学习模型. |
| * [Python 包装器的改进](v0.3.0/python.html) 使得配置工作变得很容易, 包括神经网络和 SGD 算法. |
| * [新增 SGD 更新器](v0.3.0/updater.html), 包括 Adam, AdaDelta 和 AdaMax. |
| * [安装](v0.3.0/installation.html) 具有较少的相关库, 对于单节点培训. |
| * 在 CPU 和 GPU 上进行异构训练. |
| * 支持 cuDNN V4. |
| * 数据预读取. |
| * 修复一些错误. |
| |
| |
| |
| * Incubating v0.2.0 (2016年1月14日): |
| * [Apache SINGA 0.2.0 (incubating)](https://archive.apache.org/dist/incubator/singa/0.2.0/apache-singa-incubating-0.2.0.tar.gz) |
| [\[MD5\]](https://archive.apache.org/dist/incubator/singa/0.2.0/apache-singa-incubating-0.2.0.tar.gz.md5) |
| [\[KEYS\]](https://archive.apache.org/dist/incubator/singa/0.2.0/KEYS) |
| [\[ASC\]](https://archive.apache.org/dist/incubator/singa/0.2.0/apache-singa-incubating-0.2.0.tar.gz.asc) |
| * [发行说明 0.2.0 (incubating)](releases/RELEASE_NOTES_0.2.0.html) |
| * 新功能和主要更新, |
| * [在 GPU 上进行训练](v0.2.0/gpu.html) 可以在具有多个 GPU 卡的单个节点上对复杂模型进行训练. |
| * [混合神经网络划分](v0.2.0/hybrid.html) 同时支持数据和模型并行. |
| * [Python 包装器](v0.2.0/python.html) 可以很容易地配置作业,包括神经网络和 SGD 算法. |
| * [RNN 模型和 BPTT 算法](v0.2.0/general-rnn.html) 实现并支持基于 RNN 模型的应用,例如 GRU. |
| * [云软件集成](v0.2.0/distributed-training.html) 包括 Mesos,Docker 和 HDFS. |
| * 可视化神经网络结构和层信息,有助于调试. |
| * 线性代数函数和针对 Blob 和原始数据指针的随机函数. |
| * 新层,包括 Softmax 层,ArgSort 层,Dummy 层,RNN 层和 cuDNN 层 |
| * 更新 Layer 类以携带多个数据/梯度 Blob. |
| * 通过加载预训练模型参数来提取新数据的特征和测试性能. |
| * 为 IO 操作添加 Store 类. |
| |
| |
| * Incubating v0.1.0 (2015年10月8日): |
| * [Apache SINGA 0.1.0 (incubating)](https://archive.apache.org/dist/incubator/singa/apache-singa-incubating-0.1.0.tar.gz) |
| [\[MD5\]](https://archive.apache.org/dist/incubator/singa/apache-singa-incubating-0.1.0.tar.gz.md5) |
| [\[KEYS\]](https://archive.apache.org/dist/incubator/singa/KEYS) |
| [\[ASC\]](https://archive.apache.org/dist/incubator/singa/apache-singa-incubating-0.1.0.tar.gz.asc) |
| * [Amazon EC2 image](https://console.aws.amazon.com/ec2/v2/home?region=ap-southeast-1#LaunchInstanceWizard:ami=ami-b41001e6) |
| * [发行说明 0.1.0 (incubating)](releases/RELEASE_NOTES_0.1.0.html) |
| * 主要功能包括, |
| * 使用 GNU build 程序进行安装 |
| * 用 zookeeper 进行工作管理的脚本 |
| * 基于神经网络和层抽象的编程模型. |
| * 基于 Worker,Server 和 Stub 的系统体系结构. |
| * 训练三种不同类别的模型,即前馈模型,能量模型和 RNN 模型. |
| * 使用 CPU 的同步和异步分布式训练框架 |
| * 检查点和恢复 |
| * 使用 gtest 进行单元测试 |
| |
| |
| **免责声明(英文)** |
| |
| Apache SINGA is an effort undergoing incubation at The Apache Software |
| Foundation (ASF), sponsored by the name of Apache Incubator PMC. Incubation is |
| required of all newly accepted projects until a further review indicates that |
| the infrastructure, communications, and decision making process have stabilized |
| in a manner consistent with other successful ASF projects. While incubation |
| status is not necessarily a reflection of the completeness or stability of the |
| code, it does indicate that the project has yet to be fully endorsed by the |
| ASF. |