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Tensorflow Eager Execution

发布于 : May 15, 2018
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这一条目不在当前版本的技术雷达中。如果它出现在最近几期中,那么它很有可能仍然具有相关参考价值。如果这一条目出现在更早的雷达中,那么它很有可能已经不再具有相关性,我们的评估将不再适用于当下。很遗憾我们没有足够的带宽来持续评估以往的雷达内容。 了解更多
May 2018
Assess ? 在了解它将对你的企业产生什么影响的前提下值得探索

In the last issue we featured PyTorch, a deep-learning modeling framework that allows an imperative programming style. Now TensorFlow Eager Execution provides this imperative style in TensorFlow by enabling execution of modeling statements outside of the context of a session. This improvement could provide the ease of debugging and finer-grained model control of PyTorch with the widespread popularity and performance of TensorFlow models. The feature is still quite new so we’re anxious to see how it performs and how it’ll be received by the TensorFlow community.

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