Ai大模型相关案例,AI
TensorfFlow 0.6.0 发布，更新如下：
主要特性和提升
- Python 3.3+ support via changes to python codebase and ability to specify python version via ./configure.
- Some improvements to GPU performance and memory usage:convnet benchmarksroughly equivalent with native cudnn v2 performance. Improvements mostly due to moving to 32-bit indices, faster shuffling kernels. More improvements to come in later releases.
Bug 修复
- Lots of fixes to documentation and tutorials, many contributed by the public.
- 271 closed issues on github issues.
向后兼容变化
- tf.nn.fixed_unigram_candidate_sampler changed its default ‘distortion’ attribute from 0.0 to 1.0. This was a bug in the original release that is now fixed.
更多内容请看：
https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md
TensorFlow 是谷歌的第二代机器学习系统，按照谷歌所说，在某些基准测试中，TensorFlow的表现比第一代的DistBelief快了2倍。
TensorFlow 内建深度学习的扩展支持，任何能够用计算流图形来表达的计算，都可以使用TensorFlow。任何基于梯度的机器学习算法都能够受益于TensorFlow的自动分 化（auto-differentiation）。通过灵活的Python接口，要在TensorFlow中表达想法也会很容易。
TensorFlow 对于实际的产品也是很有意义的。将思路从桌面GPU训练无缝搬迁到手机中运行。
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