添加链接
link之家
链接快照平台
  • 输入网页链接,自动生成快照
  • 标签化管理网页链接
Collectives™ on Stack Overflow

Find centralized, trusted content and collaborate around the technologies you use most.

Learn more about Collectives

Teams

Q&A for work

Connect and share knowledge within a single location that is structured and easy to search.

Learn more about Teams

I am using a very small model for testing purposes using tensorflow 2.3 and keras. Looking at my terminal, I get the following warning:

I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:118] None of the MLIR optimization passes are enabled (registered 1)

However, the code works as expected. But what does this message mean?

Thanks.

This is not an error message. The I at the beginning of the message means this is an informational log message. – jkr Sep 14, 2020 at 15:02

MLIR is being used as another solution to implementing and optimizing Tensorflow logic. This informative message is benign and is saying MLIR was not being used. This is expected as in TF 2.3, the MLIR based implementation is still being developed and proven, so end users are generally not expected to use the MLIR implementation and are instead expected to use the non-MLIR feature complete implementation.

Update: still experimental on version 2.9.1. On the docs it is written:

DO NOT USE, DEV AND TESTING ONLY AT THE MOMENT.

@daniel451: The official documentation says: DO NOT USE, DEV AND TESTING ONLY AT THE MOMENT. – Elazar Oct 5, 2021 at 16:48 Your answer could be improved with additional supporting information. Please edit to add further details, such as citations or documentation, so that others can confirm that your answer is correct. You can find more information on how to write good answers in the help center. – Community Dec 2, 2021 at 9:25 As it’s currently written, your answer is unclear. Please edit to add additional details that will help others understand how this addresses the question asked. You can find more information on how to write good answers in the help center. – Community Nov 18, 2021 at 11:11

Thanks for contributing an answer to Stack Overflow!

  • Please be sure to answer the question. Provide details and share your research!

But avoid

  • Asking for help, clarification, or responding to other answers.
  • Making statements based on opinion; back them up with references or personal experience.

To learn more, see our tips on writing great answers.