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feat: Added adaptive max pooling 1D to Ivy backend #22542
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Thanks for contributing to Ivy! 😊👏 |
Hey @arshPratap , can you fix the failing tests for jax, tf and paddle backends? |
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@arshPratap The tests in "run_test (1)" are failing due to generated output not matching the ground truth. Can you look into this, fix the conflicts and push again? |
This PR has been labelled as stale because it has been inactive for more than 7 days. If you would like to continue working on this PR, then please add another comment or this PR will be closed in 7 days. |
Thank you for this PR, here is the CI results: This pull request does not result in any additional test failures. Congratulations! |
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PR Compliance Checks Passed!
Rebased ! |
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Hi @arshPratap , |
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Hi
The logs show failures for the added tests
ivy_tests/test_ivy/test_functional/test_experimental/test_nn/test_layers.py::test_adaptive_max_pool1d,numpy
ivy_tests/test_ivy/test_functional/test_experimental/test_nn/test_layers.py::test_adaptive_max_pool1d,torch
ivy_tests/test_ivy/test_functional/test_experimental/test_nn/test_layers.py::test_adaptive_max_pool1d,paddle
ivy_tests/test_ivy/test_functional/test_experimental/test_nn/test_layers.py::test_adaptive_max_pool1d,jax
ivy_tests/test_ivy/test_functional/test_experimental/test_nn/test_layers.py::test_adaptive_max_pool1d,tensorflow
That you may see at https://github.com/unifyai/ivy/actions/runs/8003861982/job/21860150431?pr=22542
Are you able to fix these? Please let me know if something is unclear.
closing due to inactivity for over two weeks after requested changes. Please feel free reopen if you would like to continue working on this. Thanks :) |
PR Description
Added adaptive max pooling 1D function to ivy backend.
Currently utilized by Torch and Paddle Frameworks
This PR will be followed by another PRs that enables the said function into the designated framework frontends
Related Issue
Close #22317
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