feat: Add frontend jax.numpy.fft.ifftn #28550
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Medo072
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Mar 16, 2024
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Hi @Medo072
Thank you very much for the PR.
Currently the test_jax_numpy_ifftn seems to fail with torch and numpy backends. You can check the ci logs here https://github.com/unifyai/ivy/actions/runs/8235689979/job/22521391264?pr=28550 under combined test result by searching for test_jax_numpy_ifftn. Alternatively you can run the tests locally with --backend torch and --num-examples 200 to catch the failures. Hope that helps. Let me know if something is unclear. :)
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there was an issue in the _x_and_ifftn function in test_layers.py as Jax only accept axes of max size = 3 but the function doesn't handle this case, so, I added a new function to handle this case in test_layers.py. |
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PR Description
Related Issue
Closes #28549
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