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Numpy 2.0 API compatibility issue #6869
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Summary: Numpy 2.0 was released yesterday ([post](https://numpy.org/news/#numpy-20-release-date-june-16)) and accordingly a couple of tests started breaking due to usage of a now-outdated API. This updates references to the now-deprecated `np.Inf` to `np.inf`, which is available in both old and new versions of numpy and so shouldn't create any issues. Our early-stopping tutorial is still breaking due to a similar issue in TensorBoard (tensorflow/tensorboard#6869), so not all tests are expected to pass as of now. Differential Revision: D58672474
Summary: Pull Request resolved: #2527 Numpy 2.0 was released yesterday ([post](https://numpy.org/news/#numpy-20-release-date-june-16)) and accordingly a couple of tests started breaking due to usage of a now-outdated API. This updates references to the now-deprecated `np.Inf` to `np.inf`, which is available in both old and new versions of numpy and so shouldn't create any issues. Our early-stopping tutorial is still breaking due to a similar issue in TensorBoard (tensorflow/tensorboard#6869), so not all tests are expected to pass as of now. Reviewed By: mpolson64 Differential Revision: D58672474 fbshipit-source-id: 717b751ac9608867976923bc60ecb5656cc36e08
Thanks so much for bringing up this issue and providing the pointer! Are you still interested in contributing to our repo? Please feel free to send us a PR :) Otherwise I can look into it. |
Yep, seeing this issue. |
@yatbear Can we get an update on this issue? Would love to remove the hacky fixes put in place to ensure our tests (using tensorboard) can pass. |
Thanks for the links. PR #6871 should be the fix. If all is well tomorrow will have a new working nightly build release. If it does not build I will reopen this issue. |
Hi there, thanks so much for the fix! Is there a plan to cut a new release so that this change makes it into latest? |
Summary: The latest TB version hasn't incorporated numpy2.0-compatible changes (tensorflow/tensorboard#6869 (comment)), and recently unpinned botorch (D60735276) means Ax CI is now failing. This pins numpy to < 2.0 to prevent issues in CI. Differential Revision: D60917879
Summary: Pull Request resolved: facebook#2641 The latest TB version hasn't incorporated numpy2.0-compatible changes (tensorflow/tensorboard#6869 (comment)), and recently unpinned botorch (D60735276) means Ax CI is now failing. This pins numpy to < 2.0 to prevent issues in CI. Differential Revision: D60917879
Summary: Pull Request resolved: facebook#2641 The latest TB version hasn't incorporated numpy2.0-compatible changes (tensorflow/tensorboard#6869 (comment)), and recently unpinned botorch (D60735276) means Ax CI is now failing. This pins numpy to < 2.0 to prevent issues in CI. Differential Revision: D60917879
Summary: Pull Request resolved: facebook#2641 The latest TB version hasn't incorporated numpy2.0-compatible changes (tensorflow/tensorboard#6869 (comment)), and recently unpinned botorch (D60735276) means Ax CI is now failing. This pins numpy to < 2.0 to prevent issues in CI. Differential Revision: D60917879
Summary: Pull Request resolved: #2641 The latest TB version hasn't incorporated numpy2.0-compatible changes (tensorflow/tensorboard#6869 (comment)), and recently unpinned botorch (D60735276) means Ax CI is now failing. This pins numpy to < 2.0 to prevent issues in CI. Differential Revision: D60917879 fbshipit-source-id: 8fda1ee98bde1000b970d45b75c75a735e205a08
cc @JamesHollyer just wanted to follow up on my previous message - is there a plan to cut a new release with these changes? Thanks for your help! |
Bumping this! Would be really helpful for us too. Currently we pinned our version which isn't the best fix. |
Typically we do our releases when Tensorflow does theirs. However, I will bring it up in our team meeting today and discuss doing a one off release. |
It seems tensorboard is still broken (2.17.0) |
We are working on a patch release(2.17.1). |
Patch release complete. |
@JamesHollyer thanks so much!! |
Heads-up that TB nightly builds are failing (pointer) due to the numpy 2.0 release (post). They've published a migration guide (link) which should hopefully make things simple to fix. Please let me know if this is something you're already looking into, or if it would be helpful for me to contribute a fix. Thanks!
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